Isabel Nikola

EXPLORING NEW PARADIGMS OF TRANSLATIONAL REGULATION IN EUKARYOTES

Keywords: Régulation traductionnelle, 4E-IPs, Interaction protéine-ARN, Traductome, cellules bêta pancréatiques, Opéron ARN, Pore nucléaire Translation regulation, 4E-IPs, RNA-protein interactions, Translatome, pancreatic β cells, RNA operon, Nuclear pore

three years. Special thanks to the lunch group Baptiste, Miguel Luis Nikhil

I. Introduction

A.Gene expression regulation

A single cell is capable of generating a multicellular organism in which genetically homogeneous cells differ dramatically in both structure and function. To achieve this, cells have developed a complex system of regulation able to modify their patterns of gene expression in response to internal or external cues with a precise spatial and temporal coordination (Fig. 1).

Epigenetic regulation and transcription

The activity of genes and their DNA is tightly linked to a myriad of epigenetic modifications.

These reversible and inheritable modifications alter gene expression without modifying the genetic code and are, in great part, responsible for the complexity of cellular identities found in adult organisms. Epigenetic changes can affect the DNA (e.g. DNA-methylation) or DNA associated proteins, known as histones, by decorating them with different post-translational modifications (e.g. acetylation, methylation, phosphorylation, ubiquitination, biotinylation, etc.).

These modulate the accessibility of the transcription machinery to genes, allowing for a RNA molecule to be synthetized from its template DNA sequence. Transcription is orchestrated by a cohort of factors (e.g. transcription factors) which regulate the recruitment and activity of the transcriptional machinery, known as RNA polymerases. Eukaryotes possess three different RNA polymerases: Pol I, Pol II, Pol III. Each polymerase has specific targets, activities and regulation; Pol I and III are mainly responsible for the synthesis of non-coding RNAs (e.g. ribosomal RNA, t-RNA). Pol II is responsible for the transcription of some non-coding RNAs (e.g. siRNAs, snRNAs, lncRNAs) but also of protein coding RNAs, called messenger RNAs (mRNAs). As a nascent RNA molecule is being transcribed, it readily associates with proteins to form Ribonucleoprotein (RNP) complexes. When these include a messenger RNA they are named mRNPs. The generation of mRNPs from transcribed genes is essential for coupling transcription with diverse mechanisms of pre-mRNA maturation, essential to produce mature, functional RNAs. The RNA Pol II plays a pivotal role during the maturation of the RNAs that it transcribes [START_REF] Bentley | Coupling mRNA processing with transcription in time and space[END_REF].

Co-transcriptional pre-mRNA processing Soon after the Pol II has begun to transcribe, the 5' end of the nascent mRNA is readily capped by addition of a methylated guanosine (m 7 GTP). This uniquely modified nucleotide protects the transcript from 5'-3' exonucleases but also participates in the recruitment of different factors required for splicing, export and translation [START_REF] Ramanathan | mRNA capping: biological functions and applications[END_REF]. For example, the recruitment of the cap-binding complex (CBC, composed of CBP80 and CBP20) promotes the assembly of the spliceosome, a rather large and dynamic complex responsible for the splicing of precursor RNAs. Splicing removes parts of the transcribed RNA, defined as introns, while the remaining segments, called exons, are joined together to form the processed mRNA.

Interestingly, exons can either be included or excluded from the final mRNA, a process known as alternative splicing. Thus, through alternative splicing each gene generates different mRNA isoforms that increase the complexity of gene expression patterns in a cell. Indeed, the different mRNA products can code for different protein isoforms, differing in their amino acid composition and thus having different cellular functions. In other cases, due to a variation in the untranslated regions of the mRNA (UTRs), the mRNA isoforms can form different mRNPs that will have different fates. Another process, that participates in increasing the variation of gene expression during splicing, is the retention of introns on the matured mRNA. Intron retention was considered as an erroneous splicing event, but it has recently been described as a widespread mechanism involved in the regulation of gene expression [START_REF] Middleton | IRFinder: assessing the impact of intron retention on mammalian gene expression[END_REF]. Splicing also favors the 3' end cleavage of the nascent transcript and its polyadenylation. Polyadenylation consists in the synthesis of an adenosine rich nucleotide sequence (poly-A) at the 3' end of the transcript. The poly-A is found in most mRNAs apart from histone transcripts [START_REF] Gilmartin | Eukaryotic mRNA 3' processing: a common means to different ends[END_REF]. The poly-A protects the mRNA from 3'-5' nucleolytic degradation and its length is an important determinant of the fate of the mRNA, influencing its export, stability and translation [START_REF] Eckmann | Control of poly(A) tail length: Control of poly(A) tail length[END_REF]. Finally, splicing also favors the deposition of a protein complex, called the exon junction complex (EJC), at the splice sites.

The EJC will remain associated with the mature mRNA until the first round of translation, known as the pioneer round of translation. Taken together, these examples help to understand how the mRNP components and their continuous remodelling interconnect the various steps of maturation of an RNA molecule.

The Nuclear Pore Complex

The mechanisms of gene expression control described above, all take place in the nuclear compartment in a co-transcriptional manner. However, the regulation of gene expression extends way beyond the place where RNAs are produced, occurring during the export of RNA into the cytosol compartment, in which, different regulatory steps will determine the localization, the stability and the translation efficiency of the mRNAs. Nucleus and cytosol are physically separated by the nuclear envelope, a membrane composed of a double lipid bilayer.

One of the biggest macromolecular protein complexes present in the cell, called the Nuclear Pore Complex (NPC), connects the two compartments. The NPC is composed of more than 30 different proteins known as nucleoporins (Nups), each of which present in multiple copies but respecting a very precise stoichiometry (Beck and Hurt, 2017). Nups have been shown to form stable sub-complexes, essential for the assembly of the full NPC: the inner pore ring, the nuclear and cytoplasmic rings and the nuclear basket and the cytoplasmic filaments. The full NPCs are assembled mainly via two different pathways: the mitotic and the interphase pathways. The mitotic pathway takes place during active mitosis: at the end of the mitotic stage, both the nuclear envelope and the NPCs are quickly reassembled [START_REF] Dultz | Systematic kinetic analysis of mitotic dis-and reassembly of the nuclear pore in living cells[END_REF].

Post-translational modifications, such as phosphorylation of Nups, are of critical importance in the regulation of the disassembly and reassembly of the NPCs during the mitotic assembly pathway (Weberruss and Antonin, 2016). The interphase pathway is responsible for the increase in the number of NPCs from the G1 to the G2 phase when the nuclear envelope is intact. This pathway has much slower kinetics compared to the mitotic pathway [START_REF] Dultz | Live imaging of single nuclear pores reveals unique assembly kinetics and mechanism in interphase[END_REF].

The number of NPCs per cell is highly variable and it is regulated in a cell type specific manner, spanning from a few hundred to more than tens of thousands (Maul and Deaven, 1977). To date, the exact mechanisms by which cells regulate the number of NPCs remain poorly understood. A recent report has shed some light in this matter, by showing that the number of NPCs is under a negative control by the ERK pathway [START_REF] Mccloskey | Tpr regulates the total number of nuclear pore complexes per cell nucleus[END_REF]. Thus, while we have a clear picture of the structure and the processes required for the assembly of NPCs, very little is known about the mechanisms sensing and adjusting the biogenesis of the NPCs in response to changes in the physiological context and how Nups are produced in precise stochiometric amounts.

The NPCs form a selective barrier between the nucleus and cytosolic compartments allowing for the passive diffusion of small molecules across the nuclear membrane, while achieving selective transport for larger molecules such as proteins or mRNPs. This is achieved by the concerted action of a subset of Nups containing an intrinsically disordered domain, rich in phenylalanine-glycine (FG) repeats (Fig. 2, FG-Nups are underlined in bold). These FG domains form a disordered web that fills the internal channel creating a barrier in the NPC. To be transported through the nuclear pore, proteins must contain either the nuclear localization or the export signals (NLS/NES). Specialized proteins, known as importins and exportins, are able to recognize these signal sequences and dynamically interact with the FG repeats of the Nups allowing the transport of their cargo through the NPCs. Importantly, the formation and dissociation of these complexes is tightly regulated on both side of the nuclear pore to achieve directionality and irreversibility of the transport (Wente and Rout, 2010). Despite being tightly regulated, the process of nucleo-cytoplasmic transport remains an incredibly fast process. In which manner cells achieve such efficiency, known as the "transport paradox", is still largely ununderstood (reviewed in (Beck and Hurt, 2017)).

Figure 2. The architecture of the yeast nuclear pore complex

Schematic representation of the yeast nuclear pore complex and its constituent nucleoproteins (Nups). FG-Nups are highlighted in bold and underlined. Taken from [START_REF] Rouvière | A SUMO-dependent feedback loop senses and controls the biogenesis of nuclear pore subunits[END_REF] The Nups circled in green belong to the outer ring subcomplex, while those circled in pink compose the inner ring. The Nups circled with light green form the nuclear basket and the external FG-Nups, while those circled in purple form the cytoplasmic filaments. Moreover, circle in red are the transmembrane Nups, while in dark yellow the central FG-Nups.

Besides regulating nucleo-cytoplasmic transport, the NPC participates in the regulation of other cellular processes such as cell cycle progression (Rodriguez-Bravo et al., 2014), genome stability [START_REF] Bukata | Nuclear pore complexes in the maintenance of genome integrity[END_REF] and gene expression. For all these processes, Nups play an essential role in bridging transcription, nuclear export and cellular function [START_REF] Raices | Nuclear pore complexes and regulation of gene expression[END_REF].

A particularly family of post-translational modifications, has been shown to be important for the regulation of many of the NPC functions mentioned above: SUMOylation. SUMO (Small Ubiquitin-like Modifier) proteins are a family of small peptides (conserved among eukaryotes) that are covalently bound to other proteins, affecting their function. SUMOylation of target proteins has been shown to affect protein activity, stability, or interactions with other proteins and to be essential for various cellular processes, like nuclear-cytosolic transport, transcriptional regulation, apoptosis, response to stress, cell cycle progression, heterochromatin formation, etc. (Flotho and Melchior, 2013). Notably, some of the enzymes implicated in the SUMO pathway are found in association with nuclear pores. For example, the SUMO proteases Ulp1 (Ubl-specific protease Ulp1) in yeast (Fig. 2) and the human ortholog SENP2 (sentrin-specific proteases), are anchored to the inner side of the nuclear envelope which appears to be a conserved eukaryotic feature (Palancade and Doye, 2008).

Therefore, the localization of the SUMO proteases at the NPC seem important in the modulation of the function and activity of NPCs.

Nuclear export of mRNAs

A fully matured mRNA, as described in the sections above, is an essential pre-requisite for allowing its export from the nucleus to the cytosol. In turn, the transport of mRNAs to the cytoplasm is essential for the mRNA to continue its journey until it is translated into a protein.

To begin their export, mRNPs must recruit specialized mRNA export receptors. In metazoans, two different pathways have been described; the first and most studied mRNA export pathway involves the receptor heterodimer NXF1-NXT1 (Nuclear RNA export factor 1 and NTF2related export protein 1 (reviewed in [START_REF] Carmody | mRNA nuclear export at a glance[END_REF]). This heterodimer is recruited onto mRNAs via interactions with different trans-acting factors located along the mRNA sequence. For example, the NXF1-NXT1 complex is recruited by a yet unknown transacting element, onto the mRNA region that codes for the signal peptide of ER and Mitochondria-resident proteins [START_REF] Cenik | Genome Analysis Reveals Interplay between 5′UTR Introns and Nuclear mRNA Export for Secretory and Mitochondrial Genes[END_REF]; the second export pathway depends on the exportin CRM1 (chromosomal maintenance 1, also known as Exportin 1 (XPO1)). CRM1 is recruited onto mRNPs by different RBPs recognizing specific cis-elements (reviewed in (Natalizio and Wente, 2013)).

Once the mRNPs reach the cytosolic side of the NPC, they undergo a general remodelling where the export receptors and other RBPs quickly dissociate in order to prevent their re-entry into the nucleus. Importantly, not all the trans-acting factors that associate with mRNPs in the nucleus, are removed when the mRNPs first reach the cytosol [START_REF] Carmody | mRNA nuclear export at a glance[END_REF] due to their important function in regulating mRNA localization and translation. For example, mRNPs containing mRNAs that require transport to specific sites of translation are kept in a translationally inactive state by the concerted action of different RBPs. A well-studied example found in yeast is the ASH1 mRNP. The ASH1 mRNA associates with different RBPs in the nucleus, which are essential for the transport of the mRNP to its correct cytosolic localization and for maintaining its translational repression during transport [START_REF] Niedner | Of social molecules: The interactive assembly of ASH1 mRNA-transport complexes in yeast[END_REF].

Pioneer round of Translation

Once in the cytoplasm, the mRNAs are subjected to a quality control step defined as the pioneer round of translation [START_REF] Isken | The multiple lives of NMD factors: balancing roles in gene and genome regulation[END_REF]. The nuclear cap-binding complex (CBC) helps loading of one or more ribosome onto the mRNA. The ribosome in association with SURF complex, which is composed by SMG1 (Nonsense Mediated mRNA Decay Associated PI3K Related Kinase), UPF1 (up-frameshift 1), and the two translation termination factors eRF1 and eRF3 (eukaryotic release factor 1 and 3), read the mRNA and actively remove the protein complexes deposited at the exon junction sites (EJCs). If the translating ribosomes recognize a premature stop codon located more than 50 nucleotides upstream of an EJC, the UPF1 and SMG1 proteins are transferred to the downstream EJC and trigger the nonsense mediated decay pathway (NDM), inducing the degradation of the mRNA. The CBC complex, by interacting with UPF1 strongly enhances the activation of the NMD pathway [START_REF] Hwang | UPF1 Association with the Cap-Binding Protein, CBP80, Promotes Nonsense-Mediated mRNA Decay at Two Distinct Steps[END_REF]. Given the need to ensure the fidelity and quality of the mRNAs that will be translated into proteins, several other EJC-independent mRNA surveillance mechanisms are found in cells:

-No-go decay detects stalled ribosomes [START_REF] Harigaya | No-go decay: a quality control mechanism for RNA in translation: No-go decay[END_REF]; -Non-stop decay detects mRNAs missing a stop codon [START_REF] Klauer | Degradation of mRNAs that lack a stop codon: a decade of nonstop progress: Degradation of mRNAs that lack a stop codon[END_REF]; -Non-EJC-dependent NMD mechanism is triggered by premature translation termination codons (PTCs) [START_REF] Wen | Splicing-dependent NMD does not require the EJC in Schizosaccharomyces pombe[END_REF]; If none of these surveillance pathways are engaged, the nuclear CBC is replaced by the cytosolic cap-binding protein eIF4E, a step that will allow the mRNA to finally enter active translation.

mRNP granules biogenesis and function

The mRNPs that are not actively translated often assemble together into non-membranous cytoplasmic structures termed mRNPs granules. Despite different roles and compositions, the cytoplasmic mRNPs granules share some common features: they can re-enter active translation [START_REF] Brengues | Movement of Eukaryotic mRNAs Between Polysomes and Cytoplasmic Processing Bodies[END_REF] and they can share the same mRNAs (which can dynamically change from one type of granule to another) [START_REF] Buchan | Eukaryotic Stress Granules: The Ins and Outs of Translation[END_REF]. Depending on the composition of the mRNPs, these granules have been described to modulate transport (e.g. neuronal transport granules (Kiebler and Bassell, 2006)), storage and degradation. Two types of granules have been identified in the cells: Stress granules (SGs) and P-bodies (PBs). While PBs are constitutively found in the cells, SGs form under stress situations which provoke inhibition of translation (e.g. arsenate, viral infection, heat-shock). In these condition SGs form next to pre-existing PBs by an unknown mechanism. Unlike PBs, SGs contain mRNA blocked at the initiation stage of translation. Indeed, despite containing a shared core of elements PBs and SGs are distinguished by a set of proteins which are specific or preferentially localized to one of the two types of granules (Youn et al., 2018) (Hubstenberger et al., 2017).

mRNP transport granules and mRNA localization

An increasing amount of evidence shows that accurate localization of specific mRNAs is achieved in different organisms: for example, ASH1 in S. Cerevisiae [START_REF] Niedner | Of social molecules: The interactive assembly of ASH1 mRNA-transport complexes in yeast[END_REF], oskar mRNA in embryos of D. Melanogaster (Kim-Ha et al., 1995), cytoskeletal mRNAs in mammalian fibroblast cells (Willett et al., 2011) and specific mRNAs in neurons [START_REF] Jung | Translational Control by Neuroguidin, a Eukaryotic Initiation Factor 4E and CPEB Binding Protein[END_REF]. It is now clear that cis-acting elements, mostly found in the 3' UTR of these mRNA, recruit trans-acting factors that will drive the formation of transport granules. These granules will transport mRNAs to a specific localization by either passive diffusion or active transport along cytoskeleton filaments. A striking feature of these granules is that they are always in a translational inert state, albeit containing both ribosomes and decay factors (e.g. neural granules). Usually, functionally related mRNAs are co-transported by the same particles.

The mRNAs coding for membrane embedded proteins, organelle resident proteins (Endoplasmic reticulum, Golgi apparatus, lysosomes…) usually use a well describe pathway, known as the co-translational translocation, which allows transfer of the nascent polypeptide chain into the ER lumen or membrane while they are being synthetized. The first bases of the 5' end of these mRNAs code for a "signal peptide" that is recognized by the signal recognition particle (SRP), a specialized RNP complex composed of different proteins associated to the signal recognition particle RNA, (also known as 7SL). Next, the SRP interact with the membrane-bound SRP Receptor (SR) that will facilitate the delivery of the nascent polypeptide to the Sec61 translocation complex which forms a channel on the ER membrane (reviewed in [START_REF] Luirink | SRP-mediated protein targeting: structure and function revisited[END_REF]. A specific pathway is adopted by the nuclear transcribe mitochondrial mRNAs [START_REF] Eliyahu | Tom20 mediates localization of mRNAs to mitochondria in a translation-dependent manner[END_REF] Thus, the purpose of the specialized complexes is to finely regulate the localization where the protein will be synthetized.

Interplay between translation and decay

After its long journey from its inception in the nucleus, until reaching the cytoplasm or its final destination, the mRNAs can finally associate with the ribosomes, which are able to read the genetic information contained in the mRNA translating it in an amino acid chain. Translation is divided in three steps: initiation: recruitment and full assembly of the translational machinery at the initiation codon of the mature mRNA, elongation: the ribosomes and aminoacyl tRNAs read the genetic code to synthetize a polypeptide and termination: the ribosome encounters a stop-codon, leading to its disassembly and dissociation from the mRNA.

Here, further mechanisms come into play, to fine-tune the expression of mRNAs. Namely, a fine interplay between translation and decay, will dictate the fate of the mRNA and further contribute to the regulation of gene expression. In the past, over-simplistic views about this question, suggested that translation and decay were directly linked and mutually exclusive: "translation protects from degradation". We now know that these two processes are closely interconnected. All cellular mRNAs have a limited half-life spanning from a few minutes to more than 24 hours and their half-life is not directly proportional to the rate of translation (Schwanhäusser et al., 2011). Moreover, the pool of mRNAs coding for the same protein can exist in different types of mRNPs: actively translating, transiently silenced or targeted for decay. The interchange between these different states is possible because two features of the mRNAs, the 5'cap and the poly A tail, are targeted by machinery regulating both translation and decay. Indeed, translation is highly dependent on the formation of a closed loop conformation, bringing together the two extremities of the mRNA. On the other hand, the rate of mRNA decay is limited (and dependent) by the shortening of the poly A tail and the decapping of the 5' end.

Regulation of mRNA stability by mRNA decay, and regulation of translation, which define the rate of newly synthetized proteins, are two key events in gene expression.

Post-translational regulation of proteins

Once proteins are synthesized, they are continuously modified by diverse post-translational modifications (PTMs), significantly increasing the diversity and complexity of the proteome. These PTMs regulate proteins at diverse levels, influencing its localization, structure, function and half-life. A staggering amount of different modifications has been described and new modification keep being reported and documented in protein data repositories like UniProt [START_REF] Khoury | Proteome-wide posttranslational modification statistics: frequency analysis and curation of the swiss-prot database[END_REF].

Importance of post-transcriptional regulations

Transcription is a significant contributor of gene expression and has been the main focus of study for many years. Recent technological advancements, highlighted the complexity and importance of the post-transcriptional events, in which RNA binding proteins and processing factors coordinate regulation of functionally related transcripts, defining the RNA operons (Keene, 2007).

To test the contribution of these post-transcriptional regulations recent studies tried to quantify the contribution of the four major events regulating gene expression: transcription, mRNA halflife, translation and protein degradation. Translation regulation emerged to account for protein levels to a similar extent as transcription (Schwanhäusser et al., 2011) (Kristensen et al., 2014).

In energetics terms, translation is one of most expensive process in the cell, accounting to almost 90% of energy consumption in mammalian cells (Buttgereit and Brand, 1995). As consequence, cells, are able to quickly downregulate their rates of translation in stress condition to avoid energy-consumption and increasing their survival rates by enhancing translation of specific stress responsive genes.

The need of post-transcriptional regulation is also apparent in cellular types transcriptional control is not possible such as in reticulocytes, which are enucleated cells. Post-transcriptional regulation account also for the correct spatial and temporal expression of the coded proteins.

Finally, all the gene expression levels described before ranging from regulation of transcriptional activity until protein degradation all function in a unique system that finely regulates gene expression.

During my PhD I focused on the study of post-transcriptional regulations with particular attention towards regulations at the translation level. Although the three steps characterizing translation (initiation, elongation and termination) are all open to regulation, most of it takes place at the initiation phase which will be the topic of the next chapter.

B.Players and mechanism of translation initiation 1. The players of translation process

Translation process is carried out by a specialized mRNP that requires the participation of three fundamental elements: the mRNA, the ribosomes and accessory proteins, known as the eukaryotic initiation factors (eIFs).

mRNA

The fully mature mRNA possesses two characteristics shared by almost all the mRNAs: the 5' cap and the poly-A tail. Each mRNA can be further divided in three components: a 5' untranslated sequence (5' UTR), a central coding sequence and 3' untranslated sequence (3' UTR). During evolution, the UTRs of the mRNA, have acquired a series of distinctive features that influence the stability and functionality of mRNA (Fig. 3). These features are referred as cis-elements and can be either recognized by regulatory factors such as RNA-binding proteins and miRNA. Further, merely their presence can influence the stability and/or translation of the mRNA. The 5' UTR features mainly regulate translation: for example, ribosome internal entry site (IRES) allows a cap-independent translation initiation and, in some cases, generation of two completely different proteins from the same mRNA defined as polycistronic mRNA [START_REF] Karginov | Mammalian Polycistronic mRNAs and Disease[END_REF]. Another example is the upstream open reading frame (uORFs) which are important regulators of translation efficiency [START_REF] Mcgillivray | A comprehensive catalog of predicted functional upstream open reading frames in humans[END_REF]. The 3' UTR contains cis-element that recruit trans-active factors involved in mRNPs transport and regulate stability (e.g. miRNA binding site and AU-rich elements).

The focus of recent research is to characterize the chemical modifications of the mRNAs (e.g. methylation), driven by technological advancement. This has allowed the establishment of a new layer of post-transcriptional regulation called the "epitranscriptome". As for epigenetic regulation, the epitranscriptome, has its own readers, writers and erasers which are able to depose remove and read the modifications on the RNAs. The epitranscriptome has been implicated in regulating many post-transcriptional processes including translation [START_REF] Lewis | RNA modifications and structures cooperate to guide RNA-protein interactions[END_REF].

Ribosomes

The Ribosome is a macromolecular complex composed by the ribosomal proteins (RPs) and non-coding ribosomal RNA (rRNA). In eukaryotic cells, ribosomes are composed by two subunits: the small subunit (40S) and the large subunit (60S). Together, they constitute the complete ribosome (80S). The large subunit consists of three rRNA: 5S, 5.8S and 28S and 50 proteins. The small subunit is composed of one rRNA (18S) and 33 proteins (Garrett and Grisham, 2010). Importantly, single-copy mutations in specific ribosomal proteins or defects in ribosome biogenesis factors are known to cause a heterogeneous group of human disorders, called ribosomopathies [START_REF] Mills | Ribosomopathies: There's strength in numbers[END_REF]. Recent studies also claim the existence of heterogeneous ribosomes at the level of core ribosomal proteins which can affect translation of specific sub pools of mRNAs [START_REF] Shi | Heterogeneous Ribosomes Preferentially Translate Distinct Subpools of mRNAs Genome-wide[END_REF]. For example, ribosomal protein L38 selectively facilitates the translation of subsets of Hox mRNAs [START_REF] Kondrashov | Ribosome-Mediated Specificity in Hox mRNA Translation and Vertebrate Tissue Patterning[END_REF].

Eukaryotic Factors for translation

The eukaryotic translation factors are proteins which help structurally and enzymatically during several phases of translation, therefore they have been named accordingly to the translation phase they participate: eukaryotic initiation factors (eIFs), eukaryotic elongation factors (eEFs), eukaryotic release factors (eRFs) and ribosome recycling factors (RRF) which are needed to release the ribosome after protein synthesis. These factors are also the main targets that regulate translation as discussed in subsequent sections.

The translation initiation process

Generally, translation is a sequence of of three steps: initiation, elongation and termination.

Although they are all susceptible to regulation, most of which takes place at the initiation step which is rate limiting step. In eukaryotes, cells usually initiate translation via a cap-dependent mechanism named Cap dependent translation [START_REF] Von Der Haar | The mRNA cap-binding protein eIF4E in post-transcriptional gene expression[END_REF]. The cap is a guanosine methylated in position N7 linked to the first 5' nucleotide by an unusual 5' to 5' triphosphate bond. The interaction of eIFs factor with the cap allow the recruitment of the ribosomal subunits onto the mRNA. Translation initiation is a multi-step process (overview in Fig. 4) that involves twenty-five eIFs factor and the auxiliary factor PABP (poly-A binding protein). The process can be divided in different steps as described in subsequent sections.

Translation initiation requires primed ribosomal subunits

Translation initiation requires a pool of non-associated 60S and 40S ribosomal subunits. To this end, the large 60S ribosomal subunit is bound by eIF6 to block its interaction with 40S subunit. The small ribosomal subunit is bound by eIF1A, eIF1, eIF3 and eIF5 that induce a conformational change that opens the 40S mRNA binding channel. Moreover, their association is required for 40S priming, which is necessary for the upcoming translation initiation steps [START_REF] Hinnebusch | The Scanning Mechanism of Eukaryotic Translation Initiation[END_REF].

Formation of the pre-initiation complex

A key step in translation initiation is the recycling of eIF2-GDP by eIF2B to the eIF2-GTP activated form. Once eIF2 is bound to GTP, it can recruit a Met-tRNAi Met to form the ternary complex (eIF2-GTP-Met-tRNAi Met ). The ternary complex associates with a primed 40S subunit forming the 43S preinitiation complex (PIC). Importantly, eIF1 and eIF1A enhance the recruitment and stability of the ternary complex on the mRNA [START_REF] Passmore | The Eukaryotic Translation Initiation Factors eIF1 and eIF1A Induce an Open Conformation of the 40S Ribosome[END_REF]. The eIF3 complex, by interacting with eIF1, eIF1A, eIF2, eIF5 and the rRNA of the 40S, stabilizes the newly formed 43S complex [START_REF] Querol-Audi | Architecture of Human Translation Initiation Factor 3[END_REF].

Formation of the eIF4F complex

The 5' cap of the mRNA is bound by the eukaryotic Initiation Factor 4E (eIF4E) [START_REF] Sonenberg | A polypeptide in eukaryotic initiation factors that crosslinks specifically to the 5'-terminal cap in mRNA[END_REF], which replaces the nuclear CBC during the pioneer round of translation. eIF4E recruits eIF4G, a scaffold protein that on one hand enhances eIF4E affinity for the cap structure [START_REF] Haghighat | eIF4G dramatically enhances the binding of eIF4E to the mRNA 5'-cap structure[END_REF], and on the other hand recruits eIF4A, an RNA helicase that unwinds the 5' UTR secondary structures. The activity of eIF4A is modulated by two other factors: eIF4B and eIF4H [START_REF] Rogers | Modulation of the Helicase Activity of eIF4A by eIF4B, eIF4H, and eIF4F[END_REF]. Together, these factors form a complex known as eIF4F. Moreover, eIF4G binds to the PABPs (PolyA binding proteins) family members, that cover the poly-A tail at the 3' end of the mRNA. As a consequence, the two mRNA extremities are brought together forming the closed loop conformation which enhances translation efficiency and recycling of the components involved in the initiation step [START_REF] Kahvejian | The mRNA closed-loop model: the function of PABP and PABP-interacting proteins in mRNA translation[END_REF].

Figure 4. Cap-dependent eukaryotic translation initiation

1. During the recycling step, the 60S interacts with eIF6 which impedes its association with the 40S while the latter is bound by eIF1A, eIF3 and eIF5. 2. eIF2B enhances the recycling of eIF2-GDP to eIF2-GTP which forms the ternary complex with the Met-tRNAi Met . 3. Ternary complex associates with the recycled 40S forming the preinitiation complex 43S. 4. Meanwhile,the eIF4F complex (eIF4E,eIF4G,eIF4A) binds to the 5' cap of the mRNA through bound PABPs hence forming the close loop conformation. 5. The preinitiation complex is recruited onto the mRNA by the eIF4F complex forming the 48S complex which scans the mRNA for the start codon, which when recognized induces eIF5-mediated hydrolysis of eIF2bound GTP and inorganic phosphate (Pi) release. 6. 60S is recruited causing displacement of the eIFs factors. 7. Hydrolysis of eIF5B-bound GTP results in its release of eIF1A from the assembled 80S ribosomes, which will commence the Elongation stage. After termination ribosomes subunits re-enter the cycle (modified/adapted from Nature Reviews Molecular Cell Biology 11, 113-127 (2010)).

Formation of the 48S initiation complex

Both eIF4G and the eIF3 are required for the following step where the 43S is recruited onto the mRNA to form the 48S complex, also known as the pre-initiation complex (PIC). The 48S complex will then start scanning the 5'UTR for the proper AUG triplet in an optimum context, defined Kozak sequence [START_REF] Kozak | An analysis of 5'-noncoding sequences from 699 vertebrate messenger RNAs[END_REF]. Importantly, to allow the proper reading from the first nucleotide, the eIF4E is likely to be displaced from the cap structure [START_REF] Kumar | Toward the mechanism of eIF4F-mediated ribosomal attachment to mammalian capped mRNAs[END_REF].

While the PIC complex scans the 5'UTR of the mRNA, eIF1 and eIF1A are responsible for the fidelity of the recognition of the start codon. Their concomitant absence induces recognition of erroneous starting codons [START_REF] Pestova | Eukaryotic ribosomes require initiation factors 1 and 1A to locate initiation codons[END_REF]. Once the proper starting codon is recognized, the PIC complex undergoes a structural change to switch to closed conformation of the mRNA binding channel. This conformational change allows eIF5B-GTP to interact with eIF2-GTP causing its hydrolysis to eIF2-GDP and Pi [START_REF] Algire | Pi Release from eIF2, Not GTP Hydrolysis, Is the Step Controlled by Start-Site Selection during Eukaryotic Translation Initiation[END_REF].

60S joining and eIFs displacement

The eIF5B-GTP through its interaction with eIF1A, allows the joining of the large subunit of the ribosome with the PIC causing dissociation of the eIFs from the complex [START_REF] Acker | Interaction between Eukaryotic Initiation Factors 1A and 5B Is Required for Efficient Ribosomal Subunit Joining[END_REF]. Before its dissociation eIF5B-GTP gets hydrolyzed to eIF5B-GDP thus causing release of eIF1A from the assembled ribosome [START_REF] Allen | Structural insights on the translation initiation complex: ghosts of a universal initiation complex[END_REF]. Furthermore, eIF6 interacts with RACK1 (receptor for activated protein kinase C) that, when activated, causes eIF6 release from the 60S thus allowing formation of the 80S [START_REF] Ceci | Release of eIF6 (p27BBP) from the 60S subunit allows 80S ribosome assembly[END_REF]. Ribosome can now enter the elongation stage.

3.

A new complex for cap-dependent translation It has been recently demonstrated that eIF3d, a subunit of the eIF3 complex, can recognize the 5' cap of the mRNAs (Fig. 5). Importantly, the region which binds to the cap is conserved in three different kingdoms: plants, fungi and animals suggesting an evolutionary conservation [START_REF] Lee | eIF3d is an mRNA cap-binding protein that is required for specialized translation initiation[END_REF]. A follow up study published recently identified DAP5 as protein partner of eIF3d when bound to the cap (ref). DAP5 is a member of the eIF4G family which has the ability to interact with the eIF3 complex and eIF4A, but it has lost the N-terminal domain, through which the other two eIF4Gs (4G1 and 4G2) interact with eIF4E and the PABPs [START_REF] Imataka | A new translational regulator with homology to eukaryotic translation initiation factor 4G[END_REF]. DAP5 was previously known to participate in a cap-independent translation which require particular RNA structures known as IRESs (Internal Ribosome entry sites) (Lewis et al., 2007). However, silencing of DAP5 induces a 20% loss of protein synthesis rates which does not reflect the number of mRNAs translated via IRES elements. Moreover, genome wide studies demonstrated that DAP5 affect translation of large number of genes that does not possess a known IRES element (de la [START_REF] De La Parra | A widespread alternate form of cap-dependent mRNA translation initiation[END_REF]. It is thus likely that some mRNAs could use both eIF4E or DAP5 cap-complexes to initiate translation. This could be a major breakthrough in understanding why and how many mRNAs are translated under condition in which mTOR signalling inhibits eIF4E-4G interaction (See Chapter B, "4E-BPs").

Figure 5. Possible initiation complex formed by eIF3d-DAP5 on 5' cap of the mRNAs

The eIF3d subunit of the eIF3 complex is able to interact with the cap at the 5'UTR of the mRNAs and together with DAP5, homolog of eIF4G possibly allows recruitment of the preinitiation complex.

The mechanisms regulating translation initiation can be divided in two categories: the first where the activity of the initiation factors is modulated by post-translational modification or by binding partners, while the second depends on the mRNA characteristic, named cis-elements, which modulate the composition of the mRNP and therefore its own fate. This classification is arbitrary, since the two groups are intertwined, and its only scope is to aid describing the various actors of translation initiation. In the following chapters, I will discuss the regulation of the eIFs and the pathways involved. In the second chapter I will discuss the different ways by which mRNA cis elements affect translation initiation.

.

C. Regulation of eIFs

As described in the previous chapter, eIFs are the main actors in the initiation of translation and thus, unsurprisingly, most of the regulation of translation initiation focuses on the modulation of their activities. The regulation of eIFs is known to occur by two major mechanisms: post-translational modifications, among which phosphorylation is by far the most important, and intervention of protein partners. The following section focuses on these important modes of regulation and brings to light some key examples.

eIFs phosphorylation and dephosphorylation

Phosphorylation consists of the addition of a phosphoryl group (PO3-) by enzymes called kinases to the side chains of specific amino acids which, in eukaryotes, are usually serine, threonine, tyrosine and, to a lesser extent, histidine. Phosphorylation is the most common post-translational modification found in the cells and plays a key role in many cellular processes including translation, where if a key modulator of the activity of the eIFs. A good effort has been made to identify the phosphorylated eIFs, the sites or residues phosphorylated and the responsible kinases. The functional roles of some of these eIF phosphorylations have been investigated thoroughly, especially those regulated by the mammalian target of rapamycin (mTOR) pathway [START_REF] Masvidal | mTORsensitive translation: Cleared fog reveals more trees[END_REF]. However, the mechanisms and roles of newly discovered phosphorylation sites identified by genome wide methods, are yet to be uncovered. Particularly, the importance of these phosphorylation sites in regulating the translatome (the ensemble of mRNA being translated in the cells) is still largely unknown (table 1, summarize all the known phosphorylation sites of the different eIFs). Importantly, the phosphorylation of the eIFs is counterbalanced by enzymes known as phosphatases that remove the phosphoryl group from the modified amino acids. Phosphatases behave like buffering systems that avoid over-signalling via feedback loops or by directly counteracting phosphorylation.

The phosphorylation dynamics of eIF2 are major modulators of translation initiation due to the central role of eIF2 in enhancing the rate limiting step of ternary complex assembly.

Importantly, both kinases and phosphatases have been shown to regulate eIF2 phosphorylation status. In the following paragraph I will enter in the details of eIF2 regulation. Between square brackets the kinase responsible (if known). Adapted from [START_REF] Roux | Signaling Pathways Involved in the Regulation of mRNA Translation[END_REF].

Protein

a) Regulation of eIF2 and eIF2B

eIF2 is a highly conserved protein composed of three subunits (α, β and γ). The α and β subunits have regulatory function while the γ subunit interacts with both the Met-tRNAi Met and the GTP to form a ternary complex (TC). During translation initiation eIF2-GTP is hydrolyzed to eIF2-GDP to allow 60S joining. To re-form the TC, eIF2 is recycled to eIF2-bound GTP by the decameric complex eIF2B which possess guanine nucleotide exchange (GEF) function [START_REF] Bogorad | eIF2B Mechanisms of Action and Regulation: A Thermodynamic View[END_REF]. eIF2α phosphorylated at Ser 51 sequesters eIF2B, inhibiting TC recycling and thus shutting down global translation [START_REF] Sonenberg | Regulation of Translation Initiation in Eukaryotes: Mechanisms and Biological Targets[END_REF]. eIF2α could be phosphorylated by either of the four kinases mentioned below, that respond to a wide array of cellular stresses, in a pathway known as the integrated stress response (ISR):

i. As depicted in figure 6, there are many other regulations affecting the activity of these two factors. For example, eIF2β can also be phosphorylated at Ser2/67 by CK2 and by the mTOR complex 1 (mTORC1) [START_REF] Llorens | The N-terminal domain of the human eIF2β subunit and the CK2 phosphorylation sites are required for its function[END_REF][START_REF] Gandin | mTORC1 and CK2 coordinate ternary and eIF4F complex assembly[END_REF]. Phosphorylated eIF2β favors the interaction of the tyrosine kinase adaptor protein 1 (NCK1). NCK1 then recruits protein phosphatase 1 (PP1) complex which results in the dephosphorylation of eIF2α.

The activity of PP1 is regulated by different regulatory subunit: GADD34 (growth arrest and DNA damage-inducible protein 34), and the constitutive repressor of eIF2 phosphorylation (CreP) [START_REF] Rojas | An eIF2α-binding motif in protein phosphatase 1 subunit GADD34 and its viral orthologs is required to promote dephosphorylation of eIF2α[END_REF].

Phosphorylation sites have also been identified on the ε subunit of eIF2B. While most of these phosphorylation sites are required for GEF (Guanine nucleotide exchange factors) activity of eIF2B and its interaction with eIF2 [START_REF] Wang | Regulation of elongation factor 2 kinase by p90RSK1 and p70 S6 kinase[END_REF], phosphorylations at Ser544 or at Ser 540 by the GSK3β (Glycogen synthase kinase 3 beta) inhibit the activity of eIF2Bε [START_REF] Welsh | Regulation of eukaryotic initiation factor eIF2B: glycogen synthase kinase-3 phosphorylates a conserved serine which undergoes dephosphorylation in response to insulin[END_REF].

eIFs regulation by protein partners: the case of eIF4E

The activity and the recruitment of the eIFs during translation initiation is also modulated by some of their protein partners.

Most eukaryotic mRNAs are translated by the cap-dependent mechanism, that requires eIF4E to be bound to the 5' cap structure of the mRNA. In this conformation, eIF4E recruits eIF4G onto the mRNA paving the way for ribosome recruitment. Therefore, the bond between eIF4E and eIF4G has become a core regulatory mechanism of translation initiation. Indeed, various proteins, termed the eIF4E-interacting proteins (4E-IPs), are able to compete with eIF4G for binding to eIF4E. We have suggested that the 4E-IPs evolved independently in the different taxonomic groups through a process of molecular tinkering (Hernández et al., 2016).

Most of the 4E-IPs interact with eIF4E via the consensus motif YXXXXLϕ (where ϕ is an aliphatic amino acid (L, F or M)), while few of them have opted for different strategies: the human promyelocytic leukemia (PML) and the arenavirus Z protein interact through a RING motif [START_REF] Kentsis | The RING domains of the promyelocytic leukemia protein PML and the arenaviral protein Z repress translation by directly inhibiting translation initiation factor eIF4E 1 1Edited by D. Draper[END_REF]. Instead, the Cytoplasmic FMR1-interacting protein 1 (CYFIP1), interacts via a peptide which tertiary structure mimics the tertiary structure of the YXXXXLϕ motif [START_REF] Napoli | The Fragile X Syndrome Protein Represses Activity-Dependent Translation through CYFIP1, a New 4E-BP[END_REF]. The following section addresses the role and regulation of the most studied family of 4E-IPs: the 4E-BP family. This is continued by a further discussion of the roles of other 4E-IPs.

a) 4E-BPs

Three members of the 4E-BP family have been identified in vertebrates: 4E-BP1, 4E-BP2 and 4E-BP3 (Table 2). They share approximately 60% protein identity (Fig. 6B) and they are expressed in all tissues in varying amounts, depending largely on tissue-specific contexts.

Mechanistically, hyperphosphorylated 4E-BPs (phosphorylation on multiples sites) cannot interact with eIF4E, while hypophosphorylated they sequester eIF4E from eIF4G (Gingras et al., 1998). Under favorable physiological context the two isoforms 4E-BP1 and 4E-BP2 are recruited to the mTORC1 complex (mammalian target of rapamycin complex 1) via the interaction between the Raptor, subunit of mTORC1, and their C-terminal TOS (TOR signaling) motifs (also known as FEMDI) (Fig 6A). In this conformation, the kinase subunit mTOR phosphorylates 4E-BP1 and 4E-BP2 in a hierarchical way: phosphorylation of Thr37 and Thr46 precedes phosphorylation of Thr70 and Ser65 [START_REF] Gingras | Regulation of translation initiation by FRAP/mTOR[END_REF].

Upon a wide range of stimuli including growth factors, hormones, cellular energy status, and oxygen availability, mTORC1 is inhibited resulting in a quick dephosphorylation of the 4E-BPs.

Importantly, the phosphatases belonging to two different families PP1/PP2 and PPM, have been shown to be important players in this process [START_REF] Gardner | Phosphatase control of 4E-BP1 phosphorylation state is central for glycolytic regulation of retinal protein synthesis[END_REF]. Once, hypophosphorylated, the 4E-BPs are free to sequester eIF4E shutting down translation initiation.

More importantly, other kinases have been shown to be capable of 4E-BPs phosphorylation on identical or dissimilar residues. However, their physiological relevance is not yet well understood (reviewed in [START_REF] Batool | Reappraisal to the study of 4E-BP1 as an mTOR substrate -A normative critique[END_REF]).

Strikingly 4E-BP3 is likely regulated in a unique manner since rapamycin, a specific inhibitor of mTORC1 (blocks mTOR-Raptor interaction) does not affect 4E-BP3 binding to eIF4E.

Indeed, in a recent work, 4E-BP3 was shown to play an important role as translation repressor when mTORC1 remained inhibited for a prolonged period of time [START_REF] Tsukumo | Transcriptional induction of 4E-BP3 prolongs translation repression[END_REF].



They also regulate eIF4E localization: PML sequesters eIF4E in the nuclear bodies. In fact, in many cells, a prominent part of eIF4E is in the nuclear compartment [START_REF] Dostie | Nuclear eukaryotic initiation factor 4E (eIF4E) colocalizes with splicing factors in speckles[END_REF]. DDX3 interacts with eIF4E in the P-bodies. 4E-T is responsible for the shuttling of eIF4E between nucleus and cytosol, but it also causes eIF4E re-localization to P-bodies.



They regulate nuclear export: LRPPRC regulates nuclear export by binding mRNAs bearing on their 3' UTR a motif of 50 to 100 nucleotides with a highly conserved secondary structure, called 4E-SE (4E-sensitivity element) [START_REF] Topisirovic | The proline-rich homeodomain protein, PRH, is a tissuespecific inhibitor of eIF4E-dependent cyclin D1 mRNA transport and growth[END_REF].

A complete overview of the known mammalian 4E-IPs is listed in following Table 2.

Protein Binding partner

Biological process Reference 4E-BP1; 4E-BP2; 4E-BP3;

eIF4E1 Cell cycle progression, cell growth and proliferation; Synaptic plasticity and memory formation. [START_REF] Haghighat | Repression of capdependent translation by 4E-binding protein 1: competition with p220 for binding to eukaryotic initiation factor-4E[END_REF]; [START_REF] Pause | Insulin-dependent stimulation of protein synthesis by phosphorylation of a regulator of 5'-cap function[END_REF]; [START_REF] Lin | PHAS-I as a link between mitogen-activated protein kinase and translation initiation[END_REF]; [START_REF] Poulin | 4E-BP3, a new member of the eukaryotic initiation factor 4E-binding protein family[END_REF] Adapted from [START_REF] Hernández | Was the initiation of translation in early eukaryotes IRESdriven?[END_REF] 3. Specialized family members: eIF4E paralogs Gene duplication events are a major driving force of evolution in eukaryotes. Gene descending from a unique common ancestor are defined as paralogs. The most important characteristic of paralogs genes is to code for proteins during evolution have acquired new independent functions. This is also the case also for many of the eIF factors [START_REF] Hernández | Functional analysis of seven genes encoding eight translation initiation factor 4E (eIF4E) isoforms in Drosophila[END_REF]. For example, the family of eIF4E is composed of three paralogs genes (eIF4E1, eIF4E2 and eIF4E3) which originated from one common ancestor and they share 30% sequence similarity [START_REF] Joshi | Phylogenetic analysis of eIF4Efamily members[END_REF]. The three classes are defined based on presence of tryptophan at position 43 et 56 (human sequence) and the latter reside in the interaction domain with the cap structure. The three classes of eIF4E have substantially different characteristics (summarized in table 3):

 they differ for their ability to interact with the cap structure,

 not all the three classes interact with the two major protein interactors (eIF4G and 4E-BPs),

 they also differ for their expression levels and distribution among the different tissues which strongly indicates specific and independent roles between the three classes.

In tetrapoda eIF4E1 is present in two copies eIF4E1a and eIF4E1b that arose from gene duplication. In mammals, the eIF4E1b expression is confined to oocytes [START_REF] Evsikov | Cracking the egg: molecular dynamics and evolutionary aspects of the transition from the fully grown oocyte to embryo[END_REF] and has 3-fold reduced affinity for the cap compared to eIF4E1a [START_REF] Kubacka | Distinct features of cap binding by eIF4E1b proteins[END_REF]. To date, eIF4E1b functional role remains a mystery.

Instead, eIF4E1a is ubiquitously expressed and since it has always been the center of researcher's attention is historically referred as eIF4E.

Despite being the general regulator of cap-dependent translation, eIF4E has been shown to exert a stronger translational control on those mRNA containing a long and highly structured 5' UTR. These features suggest that translation initiation for these mRNA is strongly influenced by the helicase activity of eIF4A, which is strongly enhanced when part of eIF4F complex (formed by eIF4E, eIF4G and eIF4A).

Importantly, many of the genes affected by eIF4E are known proto-oncogenes involved in important hallmarks of cancer such as cell cycle regulation, survival and angiogenesis (De Benedetti and Harris, 1999) [START_REF] Mamane | Epigenetic Activation of a Subset of mRNAs by eIF4E Explains Its Effects on Cell Proliferation[END_REF]. Accordingly, over-expression of eIF4E by 2-3 folds is sufficient to induce tumorigenesis [START_REF] Ruggero | The translation factor eIF-4E promotes tumor formation and cooperates with c-Myc in lymphomagenesis[END_REF] and indeed is a common feature of many types of cancers (reviewed in [START_REF] Hsieh | Targeting Eukaryotic Translation Initiation Factor 4E (eIF4E) in Cancer[END_REF]). Surprisingly eIF4E down-regulation in cellular models did not affect global proteins synthesis rates [START_REF] Yanagiya | Translational Homeostasis via the mRNA Cap-Binding Protein, eIF4E[END_REF] and in mouse models its downregulation to 50% of initial levels did not affect normal development [START_REF] Truitt | Differential Requirements for eIF4E Dose in Normal Development and Cancer[END_REF] but affected stress responses and increased cancer rates. In the next paragraph I will focus on the recent advances in understanding the role of the two less studied classes eIF4E2 and 4E3. a) The eIF4E2

Interactions

The paralog eIF4E2 is ubiquitously expressed albeit at 10-fold lower levels of expression than eIF4E1. Its affinity for the cap structure is one hundred times less strong than eIF4E1 [START_REF] Zuberek | Weak binding affinity of human 4EHP for mRNA cap analogs[END_REF]. The role of eIF4E2 has remained elusive until recent years when it has been reported to regulate translation of a subset of genes during hypoxic stress, where eIF4E2 is brought to the 5' cap structure by RBM4 (RNA-Binding Motif protein 4) and HIF-2α (Hypoxia Inducible Factor 2α) that bind to the RNA hypoxia response element (rHRE) present on the 3'UTRs of specific mRNAs. Then, eIF4E2 forms an alternative eIF4F complex by recruiting eIF4G3 and eIF4A. Thus, eIF4E2 induces an adaptive, cap-dependent hypoxic translatome [START_REF] Uniacke | An oxygen-regulated switch in the protein synthesis machinery[END_REF]. The mRNAs translationally regulated by eIF4E2 have been shown to be involved in cancer progression. Interestingly, eIF4E2 has been found to be mutated in many cancers [START_REF] Melanson | The eIF4E2-Directed Hypoxic Cap-Dependent Translation Machinery Reveals Novel Therapeutic Potential for Cancer Treatment[END_REF] where hypoxia is a driving force that favors angiogenesis, metastasis, and resistance to therapy. Moreover, another report has shown that during embryonic development, a process driven by hypoxic condition, eIF4E2 forms a complex with GYGYF2 (GRB10-interacting GYF protein 2) and the zinc finger protein 598 (ZNF598). Knock out of either of these proteins lead to perinatal mortality [START_REF] Morita | A Novel 4EHP-GIGYF2 Translational Repressor Complex Is Essential for Mammalian Development[END_REF].

Taken together, these results highlighted that eIF4E2 is able to form different cap binding complexes that shape the translatome depending on the proteins partners and the cellular context.

Beside eIF4E2 role under hypoxic condition, it has been described to participate also under other cellular stresses:

-Various stresses such as interferon stimulation, response to genotoxic stress and pathogen infection induce eIF4E2 ISGylation (ubiquitin like modification) by ISG15 (Interferon-stimulated gene 15) which increase its affinity for the 5' cap structure [START_REF] Okumura | ISG15 modification of the eIF4E cognate 4EHP enhances cap structure-binding activity of 4EHP[END_REF];

-Energy balance has been shown to regulate eIF4E2 expression [START_REF] Parker | Gene expression profiling of mice with genetically modified muscle glycogen content[END_REF]. Some examples are during forebrain ischemia [START_REF] Nagata | Profiling of genes associated with transcriptional responses in mouse hippocampus after transient forebrain ischemia using high-density oligonucleotide DNA array[END_REF] and by microgravity [START_REF] Liu | Transcriptional analysis of normal human fibroblast responses to microgravity stress[END_REF]; -eIF4E2 interacts also with 4E-T (eIF4E transporter) to repress global translation. As for eIF4E1, 4E-T has been shown to re-locate eIF4E2 to the P-bodies but, surprisingly, it is not responsible for eIF4E2 shuttling to the nucleus as it is the case for eIF4E1 [START_REF] Kubacka | Investigating the consequences of eIF4E2 (4EHP) interaction with 4E-transporter on its cellular distribution in HeLa cells[END_REF].

-the murine eIF4E2 has been shown to interact with Prep1 (also known as Homeobox protein PKNOX1) and inhibit the translation of Hoxb4 mRNA [START_REF] Villaescusa | Cytoplasmic Prep1 Interacts with 4EHP Inhibiting Hoxb4 Translation[END_REF] b) The eIF4E3

Contrary to the other classes, eIF4E3 is expressed in a tissue specific manner [START_REF] Joshi | Phylogenetic analysis of eIF4Efamily members[END_REF], with the highest expression in muscular tissues. The mechanism of cap recognition by eIF4E3 diverge from the other two eIF4E classes but its affinity for the cap structure is comparable to eIF4E2 affinity [START_REF] Osborne | eIF4E3 acts as a tumor suppressor by utilizing an atypical mode of methyl-7-guanosine cap recognition[END_REF].

Importantly eIF4E3 ability to bind eIF4G in vivo is highly disputed. Landon and co-authors reported that eIF4E3 is able to bind eIF4G [START_REF] Landon | MNKs act as a regulatory switch for eIF4E1 and eIF4E3 driven mRNA translation in DLBCL[END_REF], while Osborne and colleagues failed to detect such interaction [START_REF] Osborne | eIF4E3 acts as a tumor suppressor by utilizing an atypical mode of methyl-7-guanosine cap recognition[END_REF]. A latter work confirmed the interaction with eIF4G but only for the longer isoform of eIF4E3 [START_REF] Frydryskova | Distinct recruitment of human eIF4E isoforms to processing bodies and stress granules[END_REF].

Interestingly, eIF4E3 has never been reported to interact with the 4E-BPs [START_REF] Joshi | Phylogenetic analysis of eIF4Efamily members[END_REF] thus it might partially escape mTOR-driven regulation. The role of eIF4E3 has been recently investigated in DLBCL cells (Diffuse Large B-Cell Lymphoma). Authors presented evidence where eIF4E1 phosphorylation at Serine 209 by the MNK1 and MNK 2 (MAP kinaseinteracting 1 and 2) regulated expression levels of both eIF4E1 and 4E3 functions [START_REF] Landon | MNKs act as a regulatory switch for eIF4E1 and eIF4E3 driven mRNA translation in DLBCL[END_REF]. Inhibition of MNK kinase activity on eIF4E1 resulted in upregulation of eIF4E3, which can attenuate eIF4E1 cap binding (Fig. 8). Moreover, investigation of the translatome where either eIF4E3 or eIF4E1 were overexpressed, showed partially non-over-lapping targets genes [START_REF] Landon | MNKs act as a regulatory switch for eIF4E1 and eIF4E3 driven mRNA translation in DLBCL[END_REF]. Among the mRNAs regulated by eIF4E1 authors identified genes known for their oncogenic potential. Thus, the balance between eIF4E3 and eIF4E1 expression levels could play a central role in cancer progression, where eIF4E3 could counteract the pro-oncogenic potential of eIF4E1. new wave of studies focusing on how each isoform is post-transcriptionally regulated and their impact of translation initiation [START_REF] Mrvová | Major splice variants and multiple polyadenylation site utilization in mRNAs encoding human translation initiation factors eIF4E1 and eIF4E3 regulate the translational regulators?[END_REF].

D. The mRNA features drive translation initiation

As briefly discussed before (see Chapter B, 1, "The players of translation:") the fully mature mRNAs differ between each other under multiple aspects. While some of the are shared by almost all mRNA such the 5' cap and poly-A tail (except for histone mRNAs), others can be specific to a subset of mRNAs and thus induce specific regulation. These specific features can fall under different classes:

-Structural characteristics such as lengths of coding region and of the UTRs. Length of 5'

UTR is an important modulator of translation initiation efficiency. In humans 5' UTRs have a median length of 218 nucleotides [START_REF] Leppek | Functional 5′ UTR mRNA structures in eukaryotic translation regulation and how to find them[END_REF] but they vary dramatically among genes. The 3' UTRs during evolution have immensely increase their length with cases well over then thousand nucleotides. These increase size underlines their importance as regulators.

-Specific nucleic acid sequences, defined as cis elements. Cis-elements can be classified based on their mechanism of action. For example, some of the cis-elements can affect translation merely with their presence (cis-driven regulation), while others, to exert their regulation, they require trans-acting factor (trans-driven regulation).

The fact that cis-driven elements could be affected by trans-acting regulators add a level of complexity. But the proposed classification paves the way to a global analysis of cis-elements functionality in specific cellular contexts that considers the expression pattern of trans-acting factors.

Cis-driven regulation

Cis-elements can be defined as "drivers" of the regulation if they regulate translation without requiring any trans-acting element. This does not exclude that, in certain tissues or condition, a particular trans-acting factor if expressed or activated could enhance or reduce the functionality of the cis-element. Here, I will discuss some of the major mRNA features that affect translation.

Translation initiation rates of mRNAs are highly affected by the 5' UTR. In fact, most mRNAs that are efficiently translated possess short unstructured 5'UTR. The rationale behind this is quite simple: longer the sequence that precede the start codon, higher are the chances to contain cis-acting elements. The cis-elements on the 5' UTRs can be divided in structured elements, when they form secondary and tertiary structures, and unstructured elements, when the nucleic acid sequence carries out the function.

a) Linear elements: The upstream Open Reading

Frame

According to the scanning model of translation initiation described before, the pre-initiation complex is recruited onto the mRNA at the 5′ end of the mRNA and then scans the 5′UTR until it encounters the first AUG codon (first-AUG rule). When the first AUG codon is not flanked by a favorable sequence (Kozak consensus," 5′ (A/G)CCAUGG 3′) it can be skipped in favor of a more favorable AUG. Among the factors involved in this "choice", eIF1 and eIF5 have been shown to be fundamental: eIF1 favors scanning by blocking recognition of non-optimal AUGs, while eIF5 antagonizes eIF1 function. A striking example such regulation is the autoregulation of translation of eIF1 and eIF5 that is conserved between eukaryotes [START_REF] Loughran | Stringency of start codon selection modulates autoregulation of translation initiation factor eIF5[END_REF].

In some cases, mRNAs contain more than one proper AUG along their 5' UTRs and those which resides upstream of the "main" AUG are defined as uAUGs (upstream AUGs). If the ribosome starts the elongation step from uAUG in frame with the stop codon of the main ORF (open reading frame), it will synthetize a different protein isoform that differs just for the Nterminal with the canonical protein isoform.

Instead, when the uAUGs are not in the same frame of the main AUG and are followed stop codon, they are defined as upstream open reading frames (uORF). The uORFs can be divided in fully upstream, when the start and stop codons of the uORF reside completely on the 5'UTR, or in overlapping the main coding sequence, when the stop codon is downstream of the canonical AUG. Importantly, both type of uORFs have been shown to be functional and regulate translation [START_REF] Kozak | An analysis of 5'-noncoding sequences from 699 vertebrate messenger RNAs[END_REF].

The uORFs are one of the most common feature of the mammalian mRNAs: bioinformatic analyses predict that, in mammals, around 40% of the mRNA contain at least one uORF [START_REF] Calvo | Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans[END_REF]. The main effect of uORF is to attenuate expression of the downstream main ORF (30%-80% less [START_REF] Calvo | Upstream open reading frames cause widespread reduction of protein expression and are polymorphic among humans[END_REF]). This can be achieved by different strategies (Fig 7 ): if the uORF is translated, ribosome can either stall thus inducing activation of the NMD pathway, or, once the stop codon is recognized, dissociate from the mRNA. In some cases, ribosomes can re-initiate the scanning process directly downstream of the uORF without dissociating from the mRNA. Another possible situation is when the scanning PIC does not recognize the uAUG, a process known as "leaky scanning".

Both leaky scanning and re-initiation downstream of an uORF are highly dependent on the availability of the ternary complex (TC). Non-limiting levels of the ternary complex (TC) enhance translation of the uORFs while limited availability of TC caused mainly by eIF2 α phosphorylation, favor leaky scanning or re-initiation which result in enhanced translation of the downstream main ORF (Andreev et al., 2015).

The presence of multiples uORFs plays a crucial role in the effect of eIF2α phosphorylation.

One of the most studied case is the mammalian ATF4 mRNA that possesses two uORFs and the second uORF partially overlaps with the main ORF. Therefore, when the TC is highly available, the main ORF is rarely translated. Upon cellular stresses that cause decrease in TC complex, leaky scanning allows translation of the main ORF [START_REF] Vattem | Reinitiation involving upstream ORFs regulates ATF4 mRNA translation in mammalian cells[END_REF].

Figure 9. Possible mechanisms of regulation by uORFs

The scanning PIC complex encountering the uAUG either recognizes the start codon hence the ribosome assembles and translates the uORF (1) or "leaks" through (2). uORF can cause stalling of the ribosome (e.g. rare codons) causing mRNA degradation or simply dissociate from the mRNA (3). In some cases, such as for short uORF, re-initiation occurs directly downstream of the uORF (4). Availability of the TC will determine if the downstream uORF will be translated: in case of eIF2α phosphorylation hence scarce TC (ternary complex) will allow leaky scanning and thus enhance expression of the main ORF (5). In contrast fast reacquisition of TC will enhance translation of the 2nd uORF decreasing chances of expression of the main ORF.

b) Structured elements

High GC content or high values for folding free energy (ΔG) are usually associated with presence of RNA secondary structures. One of the first report that associated secondary structures to inhibition of translation was done on the ODC1 mRNA (Ornithine decarboxylase 1) which contains a GC-rich region in the 5' UTR that is sufficient to inhibit translation initiation [START_REF] Manzella | Regulation of rat ornithine decarboxylase mRNA translation by its 5'-untranslated region[END_REF]. Despite being widely adopted, GC-richness and length have been proven not precise enough to predict the efficiency of translation of the mRNAs. Indeed, some mRNAs with long 5'UTR with high GC content have been shown to be efficiently translated.

G-quadruplex and pseudoknots

Emerging data, indicated that local RNA secondary structures are important elements in regulating translation initiation, by decreasing the efficiency of eIF4A helicase to unwind RNA structures. One example of such local structure is the G-quadruplex (RG4, 12-nucleotide long 4*(CGG)) which have been shown to cause translational repression by either slowing down scanning or inhibiting recruitment of the preinitiation complex [START_REF] Halder | Predictable suppression of gene expression by 5′-UTR-based RNA quadruplexes[END_REF].

RNA secondary structure can assemble in more complex tertiary structures. One example are pseudoknots, where at least two different stem-loops interact giving rise to a more complex shaped structure. A conserved pseudoknots structure has been found in the interferon gamma mRNA (IFNG), where acts as an activator for the PKR kinase (see Chapter B, 1 "eIF2 and eIF2B"). Local activation of the PKR kinase is thought to limit IFNG expression in normal conditions [START_REF] Ben-Asouli | Human interferon-gamma mRNA autoregulates its translation through a pseudoknot that activates the interferon-inducible protein kinase PKR[END_REF].

IRESs

One of the most studied RNA structures are the IRESs (internal ribosome entry site) that allow translation initiation in a cap independent manner. IRESs were firstly described as tertiary structures found on the 5' UTRs of viral RNA [START_REF] Pelletier | Internal initiation of translation of eukaryotic mRNA directed by a sequence derived from poliovirus RNA[END_REF]. Viral infection causes a block of cap-dependent translation which is overcome by IRESs on the viral mRNAs.

Indeed, many viral mRNAs do not have a 5' cap and their translation is based solely on IRESs.

Importantly IRES dependent translation is not limited to viral RNAs. 10% of total mRNAs are predicted to contain IRESs [START_REF] Spriggs | Interaction between NANOS2 and the CCR4-NOT deadenylation complex is essential for male germ cell development in mouse[END_REF]. A online database (http://iresite.org/) reports that at least 115 eukaryotic mRNA contain an IRES [START_REF] Mokrejš | IRESite-a tool for the examination of viral and cellular internal ribosome entry sites[END_REF] but, to date, only few of them have been validated [START_REF] Leppek | Functional 5′ UTR mRNA structures in eukaryotic translation regulation and how to find them[END_REF]. The IRES containing mRNAs are efficiently translated in a selective manner during inhibition of cap-dependent translation upon altered physiological conditions such as viral infection, cellular growth, cell cycle progression, apoptosis and stresses.

Since their discovery, cellular IRES have been described to adopt different strategies to recruit ribosomes on the mRNAs [START_REF] Komar | Cellular IRES-mediated translation: The war of ITAFs in pathophysiological states[END_REF]:

I. Some IRESs require almost all canonical eIFs (eIF4E excluded due to eIF4G cleavage upon viral infections that remove the eIF4E binding domain) and many IRES-trans acting factors (ITAFs) (Fig. 10A).

II. IRESs which require ITAFs but less eIFs (no eIF4F) to recruit directly the 40S (Fig. 7B).

III. IRESs and ITAFs only recruit the ribosomal subunits (Fig. 7)

As we have just described, cellular IRESs usually require ITAFs for the correct activation, thus they can be considered as dependent of a trans-regulatory element. Adapted from [START_REF] Komar | Cellular IRES-mediated translation: The war of ITAFs in pathophysiological states[END_REF] In some cases, the presence of other cis-elements regulates IRES dependent translation of mammalian mRNAs:

 IRES dependent translation is enhanced by the presence of the RNA structure defined TIE (translation inhibition element). For example, a TIE element strongly inhibits capdependent initiation of the Hox9a gene forcing IRES dependent translation through a RPL38-dependent mechanism [START_REF] Xue | RNA regulons in Hox 5′ UTRs confer ribosome specificity to gene regulation[END_REF]. This is example proves the importance of IRESs dependent translation in developmental gene expression programs.

 uORFs have been shown to regulate IRES in both ways: in some cases, such as VEGFA (vascular endothelial growth factor) and FGF9 (fibroblast growing factor 9)

they have an inhibitory effect while in other like for CAT1 mRNA (upstream of amino acid transporter cationic 1, also known as SLC7A1) they have stimulatory effect.

 RG4 structures on the IRES of VEGFA have been shown to be important contributor for their IRES mediated translation by directly recruiting the small ribosomal subunit [START_REF] Bhattacharyya | An Independently Folding RNA G-Quadruplex Domain Directly Recruits the 40S Ribosomal Subunit[END_REF].

CITE (Cap-Independent Translation Enhancers)

Another particular case of RNA structure favoring translation have discovered in plant viruses (Carrington, 1990) and they have been named cap-independent translation enhancers (CITE).

Their existence has been proven also in mammalian cells [START_REF] Terenin | A novel mechanism of eukaryotic translation initiation that is neither m7G-cap-, nor IRESdependent[END_REF]. CITEs are mainly found on the 3' UTRs. Like IRESs these structures are able to recruit onto the mRNA the 48S complex in a cap-independent manner. Contrary to IRESs dependent translation, CITEs require scanning of 5'UTR by the PIC complex. As consequence CITEs cannot enhance translation of the second ORF in bicistronic construct. (reviewed in [START_REF] Shatsky | Cap-and IRES-independent scanning mechanism of translation initiation as an alternative to the concept of cellular IRESs[END_REF]).

Trans-driven regulation

The vast majority of the known cis-element, to be functionally active, they require the presence of a transactive factor. Therefore, the derived regulation can be classified as "trans-driven regulation".

The transacting elements can regulate many aspect of the target mRNA fate: they can regulate the mRNAs translation rate, the localization, the stability and the post-transcriptional modifications (epitranscriptome). Transacting elements can either be proteins, defined as RNA binding proteins or non-coding RNA. In the following paragraphs I will discuss the different types of transacting elements starting from RNA binding proteins.

a) RNA Binding Proteins

The proteins able to bind RNA sequences or structures are defined as RNA binding proteins (RBPs). In humans at least 1542 protein coding genes, which correspond to 7% of the total number of genes, have been reported to interact with RNA. It is thought that at least half of them regulates somehow gene expression at post-transcriptional level [START_REF] Gerstberger | A census of human RNA-binding proteins[END_REF]. RBPs can be ubiquitously expressed or expressed in a tissue/time dependent manner.

Depending on their specificity for the cis-element, they can either act on wide or on small array of mRNAs. RBPs can recruit other factors onto the mRNA through protein-proteins interactions (PPIs), thus favoring the assembly of larger complex. This is highly dynamic interactions allow appropriate responses to cellular stimulations [START_REF] Mrvová | Major splice variants and multiple polyadenylation site utilization in mRNAs encoding human translation initiation factors eIF4E1 and eIF4E3 regulate the translational regulators?[END_REF]. Many

RBPs are regulated by signaling pathways through post-translational modification, or cellular levels of co-factors (e.g. cellular iron levels). In the following paragraphs I will focus on some examples of RBPs known to regulate translation initiation.

TOP mRNAs

Perhaps one of the biggest mysteries in the translation regulation field is a class of mRNAs described 20 years ago which contain a 5′-Terminal OligoPyrimidine tract (TOP, a cytosine directly after the mRNA cap followed by a tract of 4-15 pyrimidines) [START_REF] Meyuhas | The race to decipher the top secrets of TOP mRNAs[END_REF]. This cis-element is mainly found in mRNAs of ribosomal proteins or translation factors where is hold responsible for the high dependency of these mRNA to the mTOR signalling for their translation regulation. The way by which mTOR regulates translation of these mRNA remained elusive until recent years when Tcherkezian and colleagues demonstrated that LARP1 (La-related protein 1) is a key regulator of TOP mRNAs [START_REF] Tcherkezian | Proteomic analysis of cap-dependent translation identifies LARP1 as a key regulator of 5'TOP mRNA translation[END_REF].

Since then, LARP1 has become center of research to decipher its role:

 LARP1 is phosphorylated by the mTORC1 (interact with raptor) and AKT/S6K1 at different residues [START_REF] Hong | LARP1 functions as a molecular switch for mTORC1mediated translation of an essential class of mRNAs[END_REF].

 LARP1 apparently is able to bind to the poly-A tail of the TOP mRNAs [START_REF] Aoki | LARP1 specifically recognizes the 3′ terminus of poly(A) mRNA[END_REF]) [START_REF] Hong | LARP1 functions as a molecular switch for mTORC1mediated translation of an essential class of mRNAs[END_REF] and it regulates their stability [START_REF] Fonseca | La-related Protein 1 (LARP1) Represses Terminal Oligopyrimidine (TOP) mRNA Translation Downstream of mTOR Complex 1 (mTORC1)[END_REF] [START_REF] Gentilella | Autogenous Control of 5′TOP mRNA Stability by 40S Ribosomes[END_REF]) [START_REF] Aoki | LARP1 specifically recognizes the 3′ terminus of poly(A) mRNA[END_REF]  LARP1 interacts with 5' TOP via the DM15 region [START_REF] Lahr | The La-related protein 1-specific domain repurposes HEAT-like repeats to directly bind a 5′TOP sequence[END_REF] by binding both to the TOP motif and to the mRNA cap becoming a new cap binding protein [START_REF] Lahr | La-related protein 1 (LARP1) binds the mRNA cap, blocking eIF4F assembly on TOP mRNAs[END_REF] in competition with eIF4E.

 The ability to bind to the TOP mRNAs is controlled by a regulatory region sitting next to the DM15 domain. LARP1 repress translation of TOP targets, inactivation of mTORC1 release it [START_REF] Philippe | La-related protein 1 (LARP1) repression of TOP mRNA translation is mediated through its capbinding domain and controlled by an adjacent regulatory region[END_REF]  LARP1 also contains a La-motif (LAM) followed by a RNA recognition motif (RRM) which presumably work synergistically to bind together RNA [START_REF] Bousquet-Antonelli | A comprehensive analysis of the La-motif protein superfamily[END_REF].

 LARP1 binds to other 3'UTR mRNAs apart from the TOPs [START_REF] Hopkins | The RNA-binding protein LARP1 is a post-transcriptional regulator of survival and tumorigenesis in ovarian cancer[END_REF]) [START_REF] Hong | LARP1 functions as a molecular switch for mTORC1mediated translation of an essential class of mRNAs[END_REF].

Philippe and colleagues, in their recently published work, proposed a unifying model on how LARP1 regulates TOP mRNA [START_REF] Philippe | La-related protein 1 (LARP1) repression of TOP mRNA translation is mediated through its capbinding domain and controlled by an adjacent regulatory region[END_REF]. LARP1 act as a phosphorylation sensitive switch: in normal condition LARP1 and 4E-BP1 are phosphorylated hence inactivated by mTORC1. Upon cellular stress (see Chapter B, "4E-BPs") mTORC1 is inactivated and thus 4E-BP1 sequester eIF4E freeing the cap structure of the TOP mRNAs for LARP1 binding which shuts off cap-dependent translation (Fig. 8) LARP1 bound to the 5'end of TOP mRNAs might also protect them from degradation by the decapping machinery hence stabilizing the mRNA as it has been 7reported in many works.

A recent work with goal of identified LARP1 binding site on targets genes in a mTORC1 dependent context showed that LARP1 interacts with pyrimidine-enriched sequence (PES)

both in 5' and 3' UTRs of many TOP and non-TOP mRNAs [START_REF] Hong | LARP1 functions as a molecular switch for mTORC1mediated translation of an essential class of mRNAs[END_REF]. Therefore, even though these advances shed light in the understanding of TOP mRNAs regulation, more work will be needed to address better the role of LARP1 both mechanistically and physiologically.

PolyA binding proteins couple translation with RNA stability

Poly-A tail is a common feature of eukaryotic mRNAs, in animals, 250 adenosines are added co-transcriptionally to the 3' end of the mRNA and have been shown to be important in mRNA stability and translation. These functions are achieved by Poly-A Binding Proteins (PABPs) that coat the poly-A tail. PABPs enhance translation and stability of the mRNAs by interacting with eIF4G increasing both eIF4E cap affinity [START_REF] Wei | Wheat Germ Poly(A) Binding Protein Enhances the Binding Affinity of Eukaryotic Initiation Factor 4F and (iso)4F for Cap Analogues †[END_REF] and eIF4A helicase activity [START_REF] Svitkin | The requirement for eukaryotic initiation factor 4A (elF4A) in translation is in direct proportion to the degree of mRNA 5' secondary structure[END_REF]. This interaction favors the formation of the so called closed loop conformation which enhances translation initiation and ribosome recycling and is thought to provide stability to the mRNA [START_REF] Rajkowitsch | Reinitiation and recycling are distinct processes occurring downstream of translation termination in yeast[END_REF].

Importantly two PABPs interacting proteins (Paip1 and 2) have been shown to regulate PABPs function: Paip1 enhances interaction of PABPs with eIF4G by also contacting eIF3 [START_REF] Martineau | Poly(A)-binding proteininteracting protein 1 binds to eukaryotic translation initiation factor 3 to stimulate translation[END_REF] while Paip2 have an opposing effect by competing with eIF4G for PABPs binding [START_REF] Karim | A mechanism of translational repression by competition of Paip2 with eIF4G for poly(A) binding protein (PABP) binding[END_REF] and also by inhibiting PABPs binding to the poly-A tail [START_REF] Khaleghpour | Translational repression by a novel partner of human poly(A) binding protein, Paip2[END_REF].

Historically, longer tails were thought to increase mRNA stability and translation, but recent studies argue that highly expressed and well translated genes possess short poly-A tails [START_REF] Lima | Short poly(A) tails are a conserved feature of highly expressed genes[END_REF]. Moreover, in somatic cells translation efficiency decreases only if poly-A tails become shorter than 30 adenosines [START_REF] Park | Regulation of Poly(A) Tail and Translation during the Somatic Cell Cycle[END_REF] suggesting that only one PABP protein is sufficient for efficient translation and stability. Interestingly, a new work showed that the PABP at the 3' UTR-poly-A junction binds mRNA in a different manner binding both nucleotides of the 3' UTR and of the poly-A tail [START_REF] Webster | mRNA Deadenylation Is Coupled to Translation Rates by the Differential Activities of Ccr4-Not Nucleases[END_REF].

Length of poly-A tail has also been associated to gene expression regulation. The Poly-A tail length of cell cycle genes has been shown to vary with cell cycle progression and to cause translation repression [START_REF] Park | Regulation of Poly(A) Tail and Translation during the Somatic Cell Cycle[END_REF]. How is this gene specific regulation specified? Many cis-elements found in the 3'UTRs have been shown to play a crucial role in provoking mRNA decay such as A-U rich elements (ARE) or microRNAs in which PABPs contribute [START_REF] Jonas | Towards a molecular understanding of microRNAmediated gene silencing[END_REF].

The mRNA decay pathway starts with the removal of the poly-A tail, defined as deadenylation [START_REF] Chen | Mechanisms of deadenylation-dependent decay: Mechanisms of deadenylation-dependent decay[END_REF]. Two recent works in yeast [START_REF] Webster | mRNA Deadenylation Is Coupled to Translation Rates by the Differential Activities of Ccr4-Not Nucleases[END_REF] and in human cells [START_REF] Yi | PABP Cooperates with the CCR4-NOT Complex to Promote mRNA Deadenylation and Block Precocious Decay[END_REF] have revisited the previously proposed biphasic deadenylation model where an initial step was performed by the PAN2-PAN3 (poly-A nuclease 2/3) and a subsequent step was performed by the CCR4-NOT complex (the carbon catabolite repression 4 (CCR4)negative on TATA-less (NOT) complex) [START_REF] Yamashita | Concerted action of poly(A) nucleases and decapping enzyme in mammalian mRNA turnover[END_REF].

Both studies have highlighted the importance of the PABPs: in both human and yeast, PABPC1 has been shown to interact with the CCR4-NOT complex inhibiting activity of one of the two deadenylases (CAF1, Ccr4p-associated factor) while stimulating the activity of the other (CCR4, Carbon catabolite repression 4). Moreover, both studies have showed that the PAN 2/3 complex is involved in early stage of deadenylation of the poly-A tail (up to 150 adenosines) but this early pruning has no effect on mRNA abundance [START_REF] Yi | PABP Cooperates with the CCR4-NOT Complex to Promote mRNA Deadenylation and Block Precocious Decay[END_REF] thus is not rate limiting.

Thus, these recent discoveries have proposed a central role for the CCR4-NOT complex, and especially for the CCR4 deadenylase family in regulating mRNA stability in both humans and yeast. In light of these result I will now describe the CCR4-NOT complex to then enter in the details of the CCR4 family.

The CCR4-NOT complex

The CCR4-NOT complex is a highly conserved multiprotein complex involved in almost all the expression regulations steps from epigenetics to mRNA decay (Inada and Makino, 2014). The CCR4-NOT complex contains 2 deadenylase subunits that belong to two different protein families. In humans, the first family is composed of CNOT6 and CNOT6L which are orthologs of the yeast CCR4 (carbon catabolite repression 4). The second family composed by CNOT7 and CNOT8 are orthologs of the yeast CAF1 (also known as Poly(A) ribonuclease POP2).

CNOT6/6L interact with CNOT7/8 via a leucine rich repeat (LRR) found on their N-terminal domains. This deadenylase heterodimer is recruited to a large complex composed different Not proteins (known in human as CNOT proteins), via interactions of the CNOT7/8 subunit with the MIF4G domain of the scaffold protein CNOT1.

The CNOT1 act as a scaffold protein recruiting also all the other Not proteins (Fig. 12):

 the CNOT2-CNOT3 heterodimer possibly function as positive regulator of deadenylase activity (Ito et al., 2011),

 the CNOT10-CNOT11 form a module with different functions depending on the species [START_REF] Färber | Trypanosome CNOT10 is essential for the integrity of the NOT deadenylase complex and for degradation of many mRNAs[END_REF],

 finally CNOT9, which has been recently shown to be involved, by structural analysis, in the CCR4-NOT miRNA mediated silencing (Chen et al., 2014). The CCR4-NOT complex exert its deadenylase activity when recruited onto the mRNAs by interacting with different transacting factors such as RBPs or miRNAs complexes that recognize cis-elements mainly found on the 3' UTRs. The interaction between the CCR4-NOT complex and the transacting factors are usually mediated by the CNOT1 subunit (Fig. 13). For example, CNOT1 has been shown to interact with:

-Tristetraprolin (TTP), which is involved in AU-rich element (ARE)-mediated mRNA decay.

-IGF2 mRNA-binding protein 1 (IGF2BP1) that induces post-transcriptional repression of the long noncoding RNA highly up-regulated in liver cancer (HULC) [START_REF] Hämmerle | Posttranscriptional destabilization of the liver-specific long noncoding RNA HULC by the IGF2 mRNAbinding protein 1 (IGF2BP1)[END_REF].

-The mammalian paralogs of the Nanos family (Nanos 1/2/3) (Suzuki et al., 2012).

-The human GW182 proteins (also known as TNRC6 A/B/C) which provides a platform for the recruitment of the CCR4-NOT complex on mRNA targeted by miRNAs [START_REF] Fabian | miRNA-mediated deadenylation is orchestrated by GW182 through two conserved motifs that interact with CCR4-NOT[END_REF].

The CCR4 family

The CCR4 family contains an Exonuclease/Endonuclease/Phosphatase (EEP) domain that is found on the C-terminal domain.

In higher eukaryotes, nineteen CCR4 related proteins have been identified and they have been classified in four different proteins families [START_REF] Dupressoir | Identification of four families of yCCR4-and Mg2+-dependent endonucleaserelated proteins in higher eukaryotes, and characterization of orthologs of yCCR4 with a conserved leucine-rich repeat essential for hCAF1/hPOP2 binding[END_REF]. The first family of CCR4 orthologs, CNOT6/6L mentioned above, possess a functional EEP domain at the C-terminal, while in the N-terminal region, a leucine rich repeat (LRR) allows interaction with the CAF1 proteins.

The remaining three families have been shown to have a conserved EEP domain while their N-terminus is highly variable with no LRR domain:

-The Nocturnin family, which was identified in Xenopus [START_REF] Green | Identification of a novel vertebrate circadian clock-regulated gene encoding the protein nocturnin[END_REF], has been shown to follow "circadian" (circa-about, and dies-day) expression and it has also been shown to be an immediate early gene (IEG). Nocturnin Knockout mice show a particular metabolic phenotype when they are fed with a High-Fat diet (HFD) [START_REF] Kornmann | System-driven and oscillator-dependent circadian transcription in mice with a conditionally active liver clock[END_REF]. To date, Nocturnin function is unclear and the possible recently demonstrated (T. Abshire et al., 2018) while, to date, the various attempts to

show in vitro activity have failed. Such unexpected behavior suggest that the human Nocturin requires some co-factor (e.g. proteins partners) to exert its deadenylase activity.

-The 3635 family (in humans PDE12) has been shown to be a specific regulator of poly-A tail of mitochondrial-mRNAs [START_REF] Rorbach | PDE12 removes mitochondrial RNA poly(A) tails and controls translation in human mitochondria[END_REF].

-The Angel family have been identified in Drosophila (Kurzik-Dumke and Zengerle, 1996). In the early stages of vertebrate evolution, the Angel gene has undergone a gene duplication event giving rise to two conserved paralog genes: Angel1 and Angel2.

These two paralogs have been shown to have two distinct roles in human cells: Angel1 is a cytoplasmic protein that is able to interact with eIF4E (Gosselin et al., 2013), while Angel2 is a nuclear protein which has been reported to form a particular CCR4-CAF1 complex in Cajal-bodies (Wagner et al., 2007) and to regulate cell cycle via regulation of the p21 mRNA (Yi et al., 2012). Adapted from [START_REF] Rorbach | PDE12 removes mitochondrial RNA poly(A) tails and controls translation in human mitochondria[END_REF]. The C-terminal region contains a conserved EEP. Then N-terminal regions are poorly conserved and only CNOT6 and CNOT6L contain the LRR domain that allows interaction with CNOT 7/8 deadenylases.

RBPs decipher a new layer of code to regulate translation: the epitranscriptome

Modifications of the nucleic acids of mRNAs are known since many decades when the N 6methyladenosine (m 6 A) was identified as the most abundant mRNA modification [START_REF] Desrosiers | Identification of methylated nucleosides in messenger RNA from Novikoff hepatoma cells[END_REF]. In the last years these field of research have seen major advancements thank to the development of new sequencing techniques, that have enabled detection of modified bases at genome-wide level, and to the discovery of enzymes able to "write" and "read" these modifications. To date, more than 180 different modification have been reported [START_REF] Boccaletto | MODOMICS: a database of RNA modification pathways. 2017 update[END_REF] and all together they define the so called epitranscriptome.

Transacting factor, mainly RBPs, are responsible for regulating the epitranscriptome and are divided in three classes: "writers" that create the code, "readers" that interact with the modification and "eraser" that render these events highly dynamics. These modifications can either alter the RNA structure thus exposing a masked RNA motif [START_REF] Liu | N6methyladenosine-dependent RNA structural switches regulate RNA-protein interactions[END_REF] or they can be directly recognized by a trans acting element. For example, METTL3, a RNA methyltransferase directly interacts with eIF3 which, independently of its methylase activity, leads to increase in translation rates of mRNA containing m6A [START_REF] Lin | The m(6)A Methyltransferase METTL3 Promotes Translation in Human Cancer Cells[END_REF]. D a) Non-coding RNA Different classes of non-coding RNAs have been shown to regulate translation as transacting elements. One of the best studied and used also to engineer gene expression are microRNAs.

They affect translation rate by mainly inducing mRNA decay through recruitment of the deadenylase complexes on their targets and only partially by inhibiting translation [START_REF] Izaurralde | Breakers and blockers--miRNAs at work[END_REF]. Apart from the microRNAs other classes of non-coding RNA have been linked directly to translation regulation:

Long non-coding RNAs

RNAs are defined as long and non-coding (lncRNA) if they are longer than 200 nucleotides and do not contain a sufficiently long ORF (reviewed in [START_REF] Kung | Identification of a novel Drosophila melanogaster gene, angel, a member of a nested gene cluster at locus 59F4,5[END_REF]). To date, most of the work on deciphering lncRNA function have focused on their role in the nucleus where they play key roles as regulators of the transcriptional programs.

In the cytoplasm lncRNAs have been shown to associate with RBPs forming specialized lncRNPs that have been involved in many different function such as controlling mRNA and proteins fate, act as decoy for miRNA or RBPs, and participate in signalling pathways [START_REF] Rashid | Long Non-coding RNAs in the Cytoplasm[END_REF]. To date, there are scarce examples of lncRNA regulating translation:

56

-Uchl1-AS1 is an antisense RNA, under stress conditions, shuttles to the cytoplasm where it binds to 5' UTR of the Uchl1 mRNA increasing its translation rates [START_REF] Carrieri | Long non-coding antisense RNA controls Uchl1 translation through an embedded SINEB2 repeat[END_REF].

-lncRNA GAS5 is recruited to the eIF4F complex by directly binding to eIF4E and has been shown to directly interact with c-MYC mRNA causing a decrease in its translation rates [START_REF] Hu | The Long Non-Coding RNA GAS5 Cooperates with the Eukaryotic Translation Initiation Factor 4E to Regulate c-Myc Translation[END_REF].

Others lncRNAs have been shown to act indirectly on translation of certain mRNAs by acting as miRNAs or RBPs decoys. For example, the LncMyoD RNA blocks IGF2-mRNA-binding protein 2 (IMP2), while HULC lncRNA presumably act as sponge for the miR-372 (for a general review on lncRNA cytoplasmic roles [START_REF] Noh | Cytoplasmic functions of long noncoding RNAs[END_REF]).

tRNA fragments

It is almost a decade since Yamasaki and colleagues have reported that angiogenin, a secreted ribonuclease, under stress condition, cleaves the tRNAs. The generated RNA fragments have been shown to cause a decrease in global translation rates of 10 -15 % [START_REF] Yamasaki | Angiogenin cleaves tRNA and promotes stress-induced translational repression[END_REF]. Following studies have showed that the specific 5' ends of the cleaved tRNA (especially tRNA Ala and tRNA Cys ) are able to form a G-quadruplex-like structure (G4motif) that cooperates with the translational repressor Y-box binding protein 1 (YB-1) to displace eIF4F from the cap of the mRNAs and induce stress granules assembly [START_REF] Ivanov | G-quadruplex structures contribute to the neuroprotective effects of angiogenin-induced tRNA fragments[END_REF].

A recent work showed that PUS7 (pseudouridine synthase 7) mediates pseudouridylation (Ψ)

of tRNA fragments promoting association with PABP1. Loss of pseudouridylation caused impaired translation regulation in stem cells [START_REF] Guzzi | Pseudouridylation of tRNA-Derived Fragments Steers Translational Control in Stem Cells[END_REF].

E. Glucose: a paradigm of translation regulation

In this chapter, I would like to take advantage of glucose, an important regulator of translation, to describe how the various regulation described in the previous chapter take place.

Glucose is one of the most important forms of energy for the cells and, some specialized tissues like the brain, can only metabolize glucose and not others forms of energy such as lipids. Glucose has been shown to regulate translation through two major pathways regulating translation initiation: the integrated stress response which regulates eIF2 phosphorylation and mTOR signaling, which regulate 4E-BP inhibition of eIF4E. I the following paragraphs I will describe the current knowledge of how glucose signals and modulate these two pathways.

The integrated stress response

Two of the four kinases of the integrated stress response (ISR; see page 32 "Regulation of eIF2 and eIF2B"), namely GCN2 and PERK, have been shown to be activated upon glucose starvation. GCN2 which is known to sense amino acid deficiency through binding to uncharged tRNA. Therefore, glucose starvation will likely cause a reduction in charged tRNA causing GCN2 activation [START_REF] Chaveroux | Nutrient shortage triggers the hexosamine biosynthetic pathway via the GCN2-ATF4 signalling pathway[END_REF]. PERK has been also reported to be activated by glucose starvation [START_REF] Shin | ERK2 Mediates Metabolic Stress Response to Regulate Cell Fate[END_REF] likely due to a failure in protein folding cause by a decrease in ATP availability. PERK activation might be particularly important in specialized secretory cells as in pancreatic β-cells [START_REF] Gomez | A decrease in cellular energy status stimulates PERK-dependent eIF2α phosphorylation and regulates protein synthesis in pancreatic β-cells[END_REF].

As described before, activation of ISR inhibits recycling of the ternary complex, which, as we discussed in the previous chapter, favors translation of the main ORF of the mRNAs containing uORF. One of the most studied mRNAs whose translation is upregulated by glucose starvation is the activating transcription factor 4 (ATF4), which is a master regulator of the stress response and, depending on the intensity or length of the stress, can either induce pro apoptotic genes (e.g. the transcription factor CHOP) or anti-apoptotic genes that inhibit activation of the cell death machinery and favor a decrease of the ER stress levels by inducing specific genes such as GADD34 responsible for eIF2 dephosphorylation [START_REF] Walter | The Unfolded Protein Response: From Stress Pathway to Homeostatic Regulation[END_REF].

The mTOR signaling pathway

The mTOR signaling pathway is a main player in glucose starvation response. Reduced levels of glucose allow the aldolases genes, key enzymes of one of the steps of the glycolysis, to form a complex associated to the lysosomal membrane. The complex is composed by the AMP-activated protein kinase (AMPK), the serine/threonine kinase 11 (STK11/LKB1), Axin, the v-ATPase and the Ragulator complex (Zhang et al., 2017). This multiproteic complex allows the phosphorylation and activation of AMPK by LKB1 [START_REF] Shaw | LKB1 and AMP-activated protein kinase control of mTOR signalling and growth[END_REF]) in a ADP independent manner which was previously thought to be the major mechanisms to activate APMK (Zhang et al., 2017). Once phosphorylated, AMPK directly regulates mTORC1 activity by phosphorylating Raptor (subunit of mTORC1 complex) which induce mTORC1

sequestration by the 14-3-3 proteins (Gwinn et al., 2008). AMPK has been also shown to regulate mTORC1 via phosphorylation of the TSC2 (Tuberous sclerosis complex 2, upstream of mTORC1) [START_REF] Inoki | Rheb GTPase is a direct target of TSC2 GAP activity and regulates mTOR signaling[END_REF].

Summarizing, upon glucose starvation mTORC1 is sequestered and inactivated on the lysosome surfaces and cannot exert its function.

When active mTORC1 phosphorylates:

-4E-BPs inhibiting its ability to sequester eIF4E, allowing eIF4F complex formation and hence cap-dependent translation (see Chapter 1, "4E-BPs").

-LARP1 that, when phosphorylated, is not able to block translation of the TOP mRNAs -The S6 protein Kinases 1 and 2 (S6K 1/2). Activated S6Ks are able to phosphorylate many components of the translational machinery. They phosphorylate PDC4 which triggers SCF βTrCP -dependent degradation [START_REF] Dorrello | S6K1-and TRCP-Mediated Degradation of PDCD4 Promotes Protein Translation and Cell Growth[END_REF]. De-phosphorylated PDC4 inhibits interaction between eIF4G and eIF4A. S6Ks phosphorylate eIF4B to enhance eIF4A helicase activity. Moreover, eIF4B phosphorylation has been reported

to favor recruitment and phosphorylation of the eIF3 complex [START_REF] Holz | mTOR and S6K1 Mediate Assembly of the Translation Preinitiation Complex through Dynamic Protein Interchange and Ordered Phosphorylation Events[END_REF].

Phosphorylated eIF3 favors its interaction with PAIP1 bolstering translation [START_REF] Martineau | Control of Paip1-Eukayrotic Translation Initiation Factor 3 Interaction by Amino Acids through S6 Kinase[END_REF]. The S6Ks also phosphorylate eukaryotic elongation factor 2 (eEF2) kinase (eEF2K) blocking its inhibitory role on eEF2 [START_REF] Wang | Regulation of elongation factor 2 kinase by p90RSK1 and p70 S6 kinase[END_REF], which is responsible for the step during translation elongation where the polypeptidyl-tRNAs is moved from the A to the P site of the ribosome [START_REF] Carlberg | Functional properties of phosphorylated elongation factor 2[END_REF]. Interestingly, AMPK when activated by nutrient deprivation induces eEF2K phosphorylation thus provoking inhibition translation elongation [START_REF] Leprivier | The eEF2 Kinase Confers Resistance to Nutrient Deprivation by Blocking Translation Elongation[END_REF]. Finally, eEF2k have been reported to be regulated also at translational level by the presence of an uORF (Andreev et al., 2015).

-eIF4G1 at multiple residues, but the functional consequences of such phosphorylation are not fully understood [START_REF] Raught | Serum-stimulated, rapamycin-sensitive phosphorylation sites in the eukaryotic translation initiation factor 4GI[END_REF].

It is thus clear that mTORC1 can directly or indirectly modulate each component of the eIF4F complex. The reasons of such a broad regulation on the eIF4F complex can be explained by looking at mRNAs affected by each subunit. Indeed, even though the different eIF4Fs components possess a common core of the regulated mRNAs, some mRNAs have been reported to more sensitive to the lack of a subunit.

-eIF4A is necessary for mRNAs with long 5' UTRs with a high GC content possibly forming G4-quadruplex [START_REF] Rubio | Transcriptome-wide characterization of the eIF4A signature highlights plasticity in translation regulation[END_REF].

-eIF4E specific targets have shorter 5′UTRs depleted of upstream start codons and upstream open reading frames (Joyce et al., 2017).

-eIF4G1 targets have multiple uORFs and low mRNA abundance [START_REF] Ramírez-Valle | eIF4GI links nutrient sensing by mTOR to cell proliferation and inhibition of autophagy[END_REF]. In cooperation with eIF1, eIF4G enables translation initiation of a subset of mRNA containing TISU elements (translation initiator of short 5' UTR) under energetic stress (Elfakess et al., 2011) [START_REF] Sinvani | Translational Tolerance of Mitochondrial Genes to Metabolic Energy Stress Involves TISU and eIF1-eIF4GI Cooperation in Start Codon Selection[END_REF].

Taken together, these different regulations point towards subtle regulations of the translatome that might be dependent on the levels of expression of each eIF4F subunit in the different tissues or the regulation of their activity by mTORC1.

Importantly, mTORC1 and its downstream targets regulates a plethora of biological processes outside protein translation coordinating cell growth to external condition by mainly promoting anabolic metabolism when activated (nicely reviewed in [START_REF] Saxton | mTOR Signaling in Growth, Metabolism, and Disease[END_REF]).

MAPK pathways and interplay with mTOR

The mitogen-activated protein kinases (MAPKs) are classified in three families: extracellular signal-regulated kinases (ERKs), Jun N-terminal protein kinases (JNKs), and p38 kinase (p38MAPKs) and their role has been widely addressed (reviewed in [START_REF] Chen | MAP Kinases[END_REF]). Each of these families act in cascades of kinases. These cascades, can be divided in modules with a common nomenclature: MAPKK kinase (MAPKKK), MAPK kinase (MAPKK), MAPK and finally MAPKAPK.

The MAPKAPK (MAPK-activated protein kinases), one of the many substrates of the ERKs and p38MAPKs, have been reported to regulate translation, in particular through the phosphorylation of both MNKs, which are known to phosphorylate eIF4E (see Chapter B, "The eIF4E3"), and the RSK (p90 ribosomal S6 kinase), which is known to phosphorylate targets shared with S6Ks such as eIF4B [START_REF] Shahbazian | The mTOR/PI3K and MAPK pathways converge on eIF4B to control its phosphorylation and activity[END_REF], eEFK2 [START_REF] Wang | Regulation of elongation factor 2 kinase by p90RSK1 and p70 S6 kinase[END_REF], PDCD4 [START_REF] Galan | Phosphoproteomic analysis identifies the tumor suppressor PDCD4 as a RSK substrate negatively regulated by 14-3-3[END_REF] and rps6 [START_REF] Roux | RAS/ERK Signaling Promotes Site-specific Ribosomal Protein S6 Phosphorylation via RSK and Stimulates Cap-dependent Translation[END_REF]. In the context of glucose stimulation, the p38MAPKs pathway have been shown to be activated by high concentration of glucose in many different cells type ( [START_REF] Xu | High glucose activates the p38 MAPK pathway in cultured human peritoneal mesothelial cells[END_REF] and references therein).

Moreover, the mTOR and MAPK pathways are known to cross-talk regulating each other at many levels (reviewed in [START_REF] Mendoza | The Ras-ERK and PI3K-mTOR pathways: cross-talk and compensation[END_REF]). For example, the inhibition of mTORC1 has been shown to cause hyperactivation of the Mitogen-activated protein kinase (MAPK) pathway in mammalian cells through the release of repression by the feedback loop of the SK61 on PIK3 (Phosphatidylinositol 4,5-bisphosphate 3-kinase) [START_REF] Carracedo | Inhibition of mTORC1 leads to MAPK pathway activation through a PI3K-dependent feedback loop in human cancer[END_REF].

F. Thesis objectives

The topics covered in this introduction argue in favor of the importance of translational regulation in the complex web of gene expression. The recent burst in the methods and technologies have helped the biologist to address regulation outside the "standard" measurement of mRNA steady levels. For example, Polysome-profiling associated with RNA sequencing and Ribosome-profiling have finally shed light on the translatome (the part of the transcriptome that is actively translated into proteins).

The work of my thesis focused on describing new regulations of gene expression at translational level. It can be divided in three main axes, each focusing on understanding how different types of regulations affect the traductome:

-The first chapter will be focusing on the characterization of the role of the human Angel1, a novel eIF4E binding protein that regulates translation of subset of mRNAs.

-Hek2, an RNA binding protein found in yeast acts as a translational regulator of members of the nuclear pore describing a new RNA regulon of a macromolecular complex. These results have been published and are presented in article format.

-The effect of glucose stimulation on the traductome of a cellular model of human pancreatic β-cells.

Introduction

Regulation of gene expression takes place at multiple levels ranging from transcription, mRNA-splicing, export, localization, mRNA stability, translation and protein stability. These layers of regulations shape the proteasome by deciding which proteins are expressed and their levels of expression. In response external or internal stimuli, post-transcriptional regulations allow rapid regulation of protein homeostasis without the need of de novo transcription. Many studies have reported poor correlation between mRNAs steady state levels and protein abundance [START_REF] Gygi | Correlation between Protein and mRNA Abundance in Yeast[END_REF] and, even though, is still under debate (Li and Biggin, 2015), translation has emerged as a major modulator of the proteome (Schwanhäusser et al., 2011) (Kristensen et al., 2014). Translation control has been shown to play pivotal roles in many biological processes that, when dysregulated, can lead to a wide array of pathologies including cancer [START_REF] Bhat | Targeting the translation machinery in cancer[END_REF]. Translation is a highly energy consuming process for the cells, it is responsible for the use of around 20% of cellular ATP in mammalian cells (Buttgereit and Brand, 1995). Therefore, translation is mainly regulated at initiation step, when ribosomes are recruited to the mRNAs [START_REF] Hinnebusch | The Scanning Mechanism of Eukaryotic Translation Initiation[END_REF]. Under most circumstances, translation initiation relies on the regulation of the 5' cap-binding protein eIF4E

(eukaryotic Initiation Factor 4E). Importantly, eIF4E has been the first translation factor to be characterized as a proto-oncogene [START_REF] Lazaris-Karatzas | Malignant transformation by a eukaryotic initiation factor subunit that binds to mRNA 5' cap[END_REF] and since then, a variety of studies, have demonstrated its role as a therapeutic target [START_REF] Hopkins | The RNA-binding protein LARP1 is a post-transcriptional regulator of survival and tumorigenesis in ovarian cancer[END_REF]. The activity of eIF4E is regulated by the 4E-IPs (eIF4E-Interacting Proteins), which can regulate the assembly of eIF4F by competing with eIF4G for the same binding site on eIF4E [START_REF] Igreja | 4E-BPs require non-canonical 4Ebinding motifs and a lateral surface of eIF4E to repress translation[END_REF]) [START_REF] Matsuo | Structure of translation factor eIF4E bound to m7GDP and interaction with 4Ebinding protein[END_REF]. Moreover, the 4E-IPs have roles outside translation regulation by being involved in other post-transcriptional regulations such as mRNA alternative splicing, export localization and stability (reviews in (Hernández et al., 2016) and references therein).

To explore eIF4E regulation, using an original approach combining bioinformatics and structural biology, we identified the protein Angel1 as a novel 4E-IP. We have shown that Angel1 is able to disrupt the interaction between eIF4E-eIF4G, suggesting a role as regulator of translation (Gosselin et al., 2013). Moreover, we have demonstrated, in different epithelial cancer cell lines, the pro-necrotic properties of the peptide of Angel1 necessary to bind eIF4E [START_REF] Masse | An eIF4E-interacting peptide induces cell death in cancer cell lines[END_REF]. These findings are consistent with the proto-oncogenic properties of eIF4E [START_REF] Mamane | eIF4E--from translation to transformation[END_REF] and the anti-oncogenic function of the 4E-BP family, which is the best characterized 4E-IPs in regulating translation [START_REF] Martineau | Anti-oncogenic potential of the eIF4E-binding proteins[END_REF].

We have also shown that Angel1 specifically localizes on the Endoplasmic Reticulum (ER)

and at the Golgi apparatus (Gosselin et al., 2013). Notably, translation of ER-associated ribosomes does not only involve transcripts coding for secreted or transmembrane proteins but also for mRNAs coding for important carcinogenic proteins such as c-myc and p53 (Reid and Nicchitta, 2012) [START_REF] Jagannathan | De novo translation initiation on membrane-bound ribosomes as a mechanism for localization of cytosolic protein mRNAs to the endoplasmic reticulum[END_REF]. Strikingly, we have noticed that 4E-BP1, the most extensively studied eIF4E regulator, is not localized to the ER but is rather restricted to the cytosolic compartment (Gosselin et al., 2013) leading us to hypothesize that Angel1 might be a specific regulator of eIF4E for the ER compartment.

On the other hand, Angel1 belongs to the CCR4 family of proteins, containing an EEP (Endonuclease-Exonuclease-Phosphatase) domain, that are able to deadenylate the 3'-polyA tail of the mRNAs, the major step that initiates mRNA decay (Inada and Makino, 2014). In addition, Angel1 has been shown to interact with another member of the CCR4-NOT complex Caf1b (Wagner et al., 2007). This would give to Angel1 a double role in regulating the mRNAs:

the first by sequestering eIF4E thus inhibiting translation initiation and the other by regulating their stability through its deadenylase activity

To better understand the contribution of Angel1 to the regulation of gene expression, we thus need to investigate mRNAs regulated at translational level and mRNAs regulated at their stability level.

To reach this objective, we took advantage of different methods that take advantage of new generation sequencing (NGS) such as RNA sequencing, Ribosome profiling, and RNA immunoprecipitation (RIP-seq).

At the transcriptome level, Angel1 is fairly expressed in most of the human tissues with the strongest expression in testis (https://gtexportal.org/home/gene/ANGEL1). The Protein Atlas project (https://www.proteinatlas.org), which aims to develop tissue specific repertoire of protein expression based on immunohistochemistry experiments, reported a strong staining of Angel1 in the testis and in the endocrine compartment of the pancreas, known as Islet of Langerhans. Islet of Langerhans represent 1-2% of the mass of the pancreas in adults and 60-80 % of their cells are β-cells, which are highly specialized cells devoted to the synthesis and secretion of Insulin in response to a rise in blood glucose levels. Synthesis of insulin and other proteins involved in the insulin secretion pathway, mainly takes place in the ER compartment, which is highly developed and active in these cells. ER stress has been widely

studied and identified as one of the principal causes of β-cells dysfunction that leads to diabetes [START_REF] Harding | Endoplasmic Reticulum Stress and the Development of Diabetes: A Review[END_REF]. Due to Angel1 specific localization to the ER and its possible role as regulator of mRNAs stability and translation, we decided to investigate Angel1 function in a unique human β-cell line (Ravassard et al., 2011) called EndoC-bH1. Angel1 down-regulation did not perturb translation rates in these cells.

Materials and Methods

Cell Culture

HeLa S3 cells were obtained from the American Tissue Culture Collection and maintained in Dulbecco's minimum essential medium (DMEM, Lonza) supplemented with 10% fetal bovine serum (FBS, Lonza) and 5 U/mL penicillin-streptomycin (Lonza) in 5% CO2. Constitutive silencing of Angel1 was obtained using pLKO vectors (Sigma-Aldrich) as previously described (52). shRNA vector accession numbers are as follows: Angel1 #1 (TRCN0000127505), Angel1

#2 (TRCN0000128671), Angel1 #3 (TRCN0000128796) and non-target shRNA control SHC002.

EndoC-bH1 cells were cultured in low-glucose (5.6 mmol/L) DMEM (Sigma-Aldrich) with 2%

BSA fraction V (Roche-Diagnostics), 50 mmol/L 2-mercaptoethanol,10 mmol/L nicotinamide (Calbiochem), 5.5 mg/mL transferrin (Sigma Aldrich), 6.7 ng/mL selenite (Sigma-Aldrich), 100 units/mL penicillin, and 100 mg/mL streptomycin. Cells were seeded at a 40% confluence on plates coated with Matrigel (1%; Sigma-Aldrich), fibronectin (2 mg/mL; Sigma-Aldrich). They were cultured at 37°C and 5% CO2 in an incubator and passaged once a week when they were 90-95% confluent.

Subcellular Fractionation and Protease Protection Assays

HeLa cells grown to confluence in 150mm plates were harvested by trypsinization and washed sequentially with ice-cold PBS containing 5% FBS and HME (10 mM HEPES, 250 mM mannitol, 0.5 mM EDTA, pH 7.4). Cells were resuspended in five volumes of HME containing 0.1 mM phenylmethylsulfonyl fluoride (PMSF) and then pass 20 gentle strokes with tight-fitted Dounce homogenizer. Nuclei and unbroken cells were pelleted at 1,500 X g, 10 min 4°C, followed by a spin at 10,000 X g, 10 min, 4°C. The supernatant was overlaid on a 20% sucrose cushion and further centrifuged at 100,000 X g, 60 min, 4°C. The S100 supernatant was also saved for Western blot analysis. For protease protection assays, the P100 pellets (12-16µg) were incubated at 0°C with or without 2% Triton X-100. After 60 min P100 pellets were adjusted to 3mM CaCl2 and to 0,5% SDS, and then incubated with different amounts of proteinase K (0, 1, 5 and 10 units) for 5 min on ice. Reactions were stopped by addition of 5 mM PMSF and boiled in SDS protein sample buffer for 5 min at 95°C. starting from HA-A1 described in (Gosselin et al., 2013) Immunofluorescence HeLa S3 cells were plated on 96-Cell Carriers (Perkin Elmer). After transfection with the different plasmid (Angel1-HA, Δ-A1-HA and DCP1), cells were grown for 24 hours at 37°C.

Where indicated, cells were treated with 0. Sequencing was performed by the Genom'ic platform (Institut Cochin, Paris). rRNA was removed using Ribo-zero rRNA removal kit (illumina) from immunoprecipitated RNA and input RNA and libraries were prepared using CATS Total RNA-seq Kit (diagenode) following manufacturer's instructions with the implementation of UMI system. High-throughput sequencing was performed using Hiseq 2000 system generating single-end reads of 75 nt.

Ribosome profiling

The ribosome profiling strategy was adapted from [START_REF] Ingolia | The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosomeprotected mRNA fragments[END_REF] acrylamide gel with 7M urea and images were acquired using a Typhoon machine.

Cell cycle analysis

For BrdU (Bromodeoxyuridine) and PI (Propidium Iodide) labelling experiments, cells were plated in 6-well culture plate at 6x10 5 cells/well and incubated for 24 hours. Cell proliferation was measured following incubation with 10 µM 5-bromo-2-deoxyuridine (BrdU; Sigma-Aldrich)

for 1 hour at 37°C. The wells were rinsed twice with phosphate-buffered saline (PBS) and were detached with trypsin and fixed with ice-cold 70% ethanol. After fixation, the cells were pelleted, washed with 5ml cold PBS, incubated for 30 min at room temperature in 2 M HCl containing 0.5% Triton X-100. Cells were then pelleted by centrifugation for 5 min 720 x g, pH was neutralized with 1 ml 0. Small interfering RNA transfection of EndoC-bH1

Small Interfering RNA Transfection of EndoC-bH1 Cells and Human Islets EndoC-bH1 cells were passaged and transfected using Lipofectamine RNAiMAX (Life Technologies) 24 h later.

ON-TARGETplus small interfering RNA (siRNA) SMARTpool for human Angel1, or ON-TARGETplus non-targeting control pool (siNT) were used (Dharmacon). Briefly, siRNA and Lipofectamine RNAiMAX were combined in OptiMEM and applied to the cells. Three hours later, medium was changed for fresh culture medium. 72 hours after transfection cells were used for further analysis.

Polysome Profiling

EndoC-bH1 cells were collected at 80-90% confluence 72 hours after siRNA transfection.

Cells, were washed in in ice cold PBS containing 100 µg/ml Cycloheximide. The PBS containing 100 µg/ml Cycloheximide was removed and the Lysis buffer (80 mM KCl, 10 mM Tris pH7.4, 5 mM MgCl2, 0.5% Triton X100, 0.5% Na-Deoxycholate, 40U/ µL RNAsin, 1 mM DTT) was added directly to the plate and cells were scraped and collected. After 10 minutes incubation on ice, the lysates were centrifuge at 10000 Xg for 5 min at 4°C. 10 A254 units of extract were layered onto a 11 ml 20-50% (wt/vol) sucrose gradient prepared in the lysis buffer without Triton X-100. The samples were ultra-centrifuged at 39,000 × g for 2.5 hours at 4 °C in a SW41 rotor. The gradients were fractionated in 14 fractions of 0.9 ml using an ISCO fractionation system with concomitant measurement of A254.

[35S]-Methionine incorporation assay

EndoC-bH1 cells plated in a 12 well plate was transfected with siA1 or siNT and grown for 72 hours. Two negative control samples for both siNT and siAngel1 were pretreated incubated for 20 at 37 °C minutes with 0.025 µg/µl CHX to block translation. Then, cells were incubated with fresh media containing 0.02 µg/µCi of [35S]-Methionine (Perkin Elmer) for 40 minutes at 37°C. Cells were then washed twice in PBS and collected with 2% 120 µl SDS lysis buffer ( 50mM Tris pH 7.6, 10 mM EDTA, 2% SDS). 6 µl of lysates were spotted on filter (Whatman, GE healthcare) and incubated with ice-cold 10% Trichloroacetic acid (TCA) for 3 hours at 4°C.

Then filters are washed for 15 minutes at 4°C with 5% TCA and heated at 90 °C for 30 minutes with 10% TCA followed by a 5% TCA wash at room temperature for 15 minutes. Filters are air dried and placed to a scintillation vials with 2 ml of scintillation fluid (Ultima Gold, Perkin Elmer).

As control to measure the total amounts of [35S]-Methionine 6ul of lysates were spotted on filter and transferred to scintillation vials with 2 ml scintillation fluid. Scintillation counts were measured with the help of a scintillation counter (Beckman LS 6500)

Bioinformatic analyses:

RNA-Seq analysis

Total RNA fastq files containing paired-end reads (2x75nt). Quality of the reads was assessed with FastQC v0.11.0 [START_REF] Leggett | Sequencing quality assessment tools to enable data-driven informatics for high throughput genomics[END_REF]. No reads were discarded. Reads were aligned to human genome (GRCh38/hg19) using the aligner Spliced Transcripts Alignment to Reference (STAR) version STAR 2.4.2a (Dobin et al., 2013) with defaults mapping parameters but allowing 9 mismatches for each read pair. The parameter --quantMode GeneCounts was used to generate an estimation of expression. For differential gene expression analysis, we implemented the Bioconductor package RNAseq123 [START_REF] Law | RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR[END_REF]. RNAseq123 utilizes edgeR package (Robinson et al., 2010) to import and normalize data, Limma package [START_REF] Law | RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR[END_REF] which applies a linear modelling and empirical Bayes. More in detail we used the function treat with the option argument lfc=0.5 (that defines the minimum log2-fold-change that is considered scientifically meaningful). For results visualization, Glimma package [START_REF] Su | Glimma: interactive graphics for gene expression analysis[END_REF] which allows interactive exploration of the generated results.

RIP-Seq analysis

RIP Fastq files with 75-nt single-end sequenced reads were quality-checked with FastQC v0.11.0. UMItools [START_REF] Smith | UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy[END_REF] was used to extract barcoding sequences from each read following developer instructions. Reads were aligned to the human genome (GRCh38/hg19) using STAR 2.6 (Dobin et al., 2013) with the following parameters -- Gene counts were normalized between replicates by first calculating a normalizing factor (sum of count of the two replicates divided total library size). Next, we merged the two normalized libraries in one single library by calculating the mean counts for each gene. Then, to remove possible outlier genes from our analysis we applied a filtering step: genes which count number was under 3 times the interquartile range were discarded. As last step we discarded the genes that were expressed in our negative control (Halotag) from the other RIP experiments.

Ribosome profile sequencing and analysis

Reads containing adapters were trimmed using cutadapt [START_REF] Martin | Cutadapt removes adapter sequences from high-throughput sequencing reads[END_REF]. Reads were also size-selected between 25-45 nt in length using cutadapt. Reads were then mapped to the human genome (GRCh38/hg19 from Ensembl 92) with STAR aligner using a specific indexed genome with overhang 35. STAR parameters were: --seedSearchStartLmaxOverLread 0.5, --outFilterMismatchNoverLmax 2.0, --outFilterMultimapScoreRange 0, --sjdbOverhang 35;

with the option --quantMode GeneCounts to generate table of counts. Relative changes in ribosome density were determined using the Bioconductor package RNAseq123 as described for the RNAseq analysis. As complementary analysis to identify mRNAs deregulated at translational level we analyzed our datasets of RNA-seq and RIBO-seq using the Babel R package [START_REF] Olshen | Assessing gene-level translational control from ribosome profiling[END_REF].

Results

Angel1 is localized to the cytosolic face of the ER allowing its interaction with the translational machinery

Ribosomes synthesize proteins in the cytosol or while associated with the ER. In our previous work we showed by immunofluorescence and cell fractionation experiments that Angel1 is mainly found in the ER and Golgi compartments (Gosselin et al., 2013). To validate our previously published, we decided to implement a different cell fractionation method [START_REF] Drenan | FKBP12-Rapamycinassociated Protein or Mammalian Target of Rapamycin (FRAP/mTOR) Localization in the Endoplasmic Reticulum and the Golgi Apparatus[END_REF]) by sequential centrifugation to purify the microsomal fraction (Fig. 1A). After mild homogenization and pelleting of nuclei and unbroken cells, heavy membranes such as mitochondria, lysosomes and peroxisomes, the supernatant was further centrifuged at high speed (100000 x g) to collect the microsomal fractions such as ER and Golgi apparatus.

Indeed, Calnexin and Golgin-97, an ER marker and Golgi apparatus marker respectively, were enriched in the P100 (microsomes) fraction. In agreement with our previous work, Angel1 was similarly enriched in the P100 fraction (Fig. 1A). Importantly, eIF4E was detected both in the P100 fraction and S100 while its main regulator, 4E-BP1, was not enriched in the P100 (Fig. 1A) confirming previous results (Gosselin et al., 2013).

To assess whether Angel1 localizes to the cytosolic face of the ER and consequently allowing its interaction with the translation machinery, we performed protease protection assay on the microsomal fraction (P100). The rationale of this assay is that if Angel1 is found on the external face of the microsomes, it should be quickly digested by the protease, while if Angel1 is expressed on the luminal side it should be protected by the digestion (Fig 1C). Strikingly, Angel1 was quickly processed by the protease even at the lowest concentrations (Fig 1B).

While calnexin was affected only at higher concentration and with clear appearance of a lower band at 60 KDa that correspond to its luminal domain. These results suggesting that Angel1 is expressed on the cytosolic face of the ER membrane

To investigate how Angel1 associates to the microsomal membranes we analyzed Angel1 amino acid sequence using SignalP 4.1 [START_REF] Petersen | SignalP 4.0: discriminating signal peptides from transmembrane regions[END_REF]. A signal peptide is predicted at the N-terminus with a possible cleavage site between amino acid 21-22. We reasoned that the possible signal peptide could be responsible for Angel1 localization to the ER. To address this hypothesis, we investigated the localization by immunofluorescence of a transiently expressed form of Angel1 deprived of the signal peptide (referred as Δ-A1-HA) compared to a wild type C-terminal HA tagged Angel1 (A1-HA) (Fig. 2A). While the A1-HA recapitulated the endogenous protein localization, the Δ-A1-HA shows a stronger nuclear localization and cytosolic foci (Fig. 2B). To test whether these foci could correspond to stress structures such P-bodies we co-expressed Angel1 with DCP1, a known decapping enzyme found mainly in P-bodies (Fig. 2C). Localization of the two isoforms of Angel1 was not affected by DCP1 expression and the foci of DCP1 and Δ-A1-HA did not overlap, but in some cases were juxtaposed (Fig. 2C zoom inlay). We concluded that Angel1 localization is mediated by its Nterminal peptide, deletion of this peptide causes mislocalization of the protein forming nuclear and cytosolic foci that do not correspond to P-bodies. We further investigated whether Angel1 localization could be affected by arsenate treatment known to induce stress granules (SG)

that are another type of dynamic cytosolic mRNP granules closely related to P-bodies but containing also the translation initiation factors and the small ribosomal subunit [START_REF] Decker | P-Bodies and Stress Granules: Possible Roles in the Control of Translation and mRNA Degradation[END_REF]. Arsenate treatment did not affect localization of A1-HA nor Δ-A1-HA hence we concluded that Angel1 does not localize to SGs nor to P-bodies.

Angel1 does not have deadenylation activity in vitro but affects mRNA abundance of a discrete set of genes Angel1 has been described as a member of CCR4 (carbon catabolite repression 4) [START_REF] Winkler | Heterogeneity and complexity within the nuclease module of the Ccr4-Not complex[END_REF]) [START_REF] Dupressoir | Identification of four families of yCCR4-and Mg2+-dependent endonucleaserelated proteins in higher eukaryotes, and characterization of orthologs of yCCR4 with a conserved leucine-rich repeat essential for hCAF1/hPOP2 binding[END_REF]. This family possess an endonucleaseexonuclease-phosphatase (EEP) group and display a Mg2+-dependent 3'-5' deadenylase activity that is involved in the first step of the degradation of poly(A) mRNAs [START_REF] Chen | CCR4, a 3′-5′ poly(A) RNA and ssDNA exonuclease, is the catalytic component of the cytoplasmic deadenylase[END_REF]. We decided to test if, Angel1 exhibit a deadenylase activity. To this end, Halo-tagged Angel1 wild type or a catalytically dead mutant (an ANGEL1 protein rendered inactive by the substitution of a required glutamic acid by an Alanine [START_REF] Winkler | Heterogeneity and complexity within the nuclease module of the Ccr4-Not complex[END_REF]), produced in transiently transfected HeLa S3 cells, purified proteins were incubated with a deadenylation substrate RNA containing a 20-nucleotide poly(A) tail. Firstly, we tested if in our conditions a purified xenopus Nocturnin that belongs to the CCR4 family, was able to deadenylate the target RNA. Indeed, Nocturnin showed the typical pattern of deadenylation while the GST tag did not affect the RNA (Fig 3A). Then we observed by Western blot that Angel1 was efficiently purified together with its known binding partner eIF4E. We thus incubated Angel1 complexes for up to 2 hours with the polyA RNA that was then analyzed on acrylamide gel (Fig 3A). None of the Angel1 purified constructs was able to deadenylate the target RNA. We concluded that Angel1 does not exert any deadenylase activity in vitro. To date, in vitro activity has not yet been reported for human Nocturnin, Angel2 and Angel1. Notably, Angel2, whose catalytic activity has not been proven in vitro has been shown to interact with TOE1 (alternatively called CAF1z due to homology with CAF1 deadenylase) which possess strong deadenylase activity (Wagner et al., 2007). Xenopus Nocturnin, which shares 66% amino acid identity with the human ortholog, was previously shown to possess deadenylase activity in vitro (Baggs and Green). It remains possible that Angel1 may be part of a deadenylase complex in vivo, especially since Wagner and colleagues reported that Angel1 co-immunoprecipitated with Caf1b (Wagner et al., 2007). It is interesting to note that, as we have previously reported (Hernández et al., 2016), we discovered the insertion of a completely new exon in Angel1 deadenylation domain. This exon codes for the eIF4E binding site. The hypothesis that this insertion might have compromised the deadenylase activity need further investigation.

To address the possible role of Angel1 in regulating in vivo the mRNA abundance we performed transcriptome analysis of Hela cells after Angel1 knock-down, two sub-clones were selected: SH-2 and SH-3. The efficiency was assessed by Western-blot and Immunofluorescence (Fig. 4A). Angel1 protein level was efficiently downregulated in SH2 while SH-3 was less efficient (Fig. 4A). For each cell line 4 independent replicates were prepared, sequencing generated between 30 and 40 million reads (Fig. 4A). Reads were then aligned on the human genome, around 70% of the reads were uniquely mapped (Fig. 4B).

Indeed, differential gene expression analysis, performed using the using RNAseq123 R package [START_REF] Law | RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR[END_REF] (for detailed workflow see Material and Methods), highlighted 39

genes differentially expressed for SH-2, of which 37 were downregulated in SH-2, while for SH-3 only 2 genes were identified as upregulated: FAM179A and LYPD1 (Ly6/PLAUR domain- containing protein 1) (Fig. 4C). Angel1 was the only gene to be commonly regulated between the 2 KD cell lines (Fig 4D andtable 1 contains full list of identified genes for SH-2 and SH-3).

We then assessed by RT-qPCR the downregulation of some of the identified targets of SH-2, using the housekeeping gene TBP (TATA box binding) as control since its expression was not affected by Angel1 depletion. Indeed, all the tested genes were downregulated in SH-2 cells but not in SCR nor SH-3 (Fig. 4E). These results can be explained by the difference in the efficiency of Angel1 downregulation (Fig. 4A) which might be insufficient in SH3 to induce a clear phenotype. Moreover, since also in SH2 cells Angel1 is still partially express (Fig. 4A),

we can hypothesize that in a knockout model the number of mRNAs affected would increase.

Most of the genes identified by transcriptome analysis were downregulated in absence of Angel1 therefore we concluded that Angel1 does not possess deadenylase activity since the expected phenotype would have been an increase in mRNA levels as was previously reported for CCR4a and CCR4b [START_REF] Mittal | The Ccr4a (CNOT6) and Ccr4b (CNOT6L) deadenylase subunits of the human Ccr4-Not complex contribute to the prevention of cell death and senescence[END_REF]. Taken together, these results indicate that Angel1, in vivo, affect mRNA abundances of a subset of genes independently of its deadenylase activity.

To analyze the role of the target genes we performed functional classification using DAVID database [START_REF] Huang | Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources[END_REF]. Characterization of Angel1 target mRNAs based on the localization of the coded proteins showed that most of them are secreted proteins or expressed on the plasma membrane or part of internal membranous organelles such the ER (Fig 4G). Importantly the mRNAs coding for these proteins are known to be translated by ERbound ribosomes. Classification based on the biological process highlighted that targets are involved in signaling, transmembrane transport and also in intracellular trafficking (Fig. 4G, pie chart).

Ribosome Profiling results

We next investigated the possible role in regulating translation initiation through binding to eIF4E. To tackle this question, we took advantage of the recently developed Ribosome

Profiling technique [START_REF] Ingolia | The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosomeprotected mRNA fragments[END_REF] . We noticed that this was due to a different distribution of read counts even after normalization as shown in Fig. 5B: the boxplot of the normalized distribution of gene counts expressed in logCPM (counts per million reads) for SCR-S2 and SH-2-S4. We thus proceeded with the analysis bearing in mind that the statistical power would be decreased. We identified 29 and 9 genes for SH-2 and SH-3 respectively that were down regulated in SCR condition while 22 and 2 were up regulated in SCR (Fig. 5E). Importantly 5

genes were in common between the 2 Sh-Angel1 lines, which represented more than half of SH-3 targets (Fig. 5F). The identified genes did not overlap with the genes identified in the transcriptome analysis validating their regulation at translational level. Moreover, we performed a complementary analysis using Babel [START_REF] Olshen | Assessing gene-level translational control from ribosome profiling[END_REF], a statistical method that, by considering variations at the transcriptome level is able identify mRNAs regulated at translational level only. This approach led to the identification of 40 genes regulated at translation level for SH2 while only one gene was identified in SH3. A core of 20 genes was identified by both approaches (Fig. 4D, listed in table 2 together with genes identified only by Babel analysis or by RNAseq123 for SH3, in blue the genes found to be in common between SH3 and SH2). Then, we assess why the genes found by the transcriptome analysis where not confirmed in this analysis. By looking at the expression levels, of each replicate we observed that one of the replicates of the SCR or SH2 did not have sufficient reads for these genes. As result the statistical tested fail to detect significant differential expression.

And we realized that, for most of the genes, one of the SCR experiment did not have any reads. As perspective, the identified genes will need to be validated by western blot or with a more complex approach combining SunSET experiments (Schmidt et al., 2009) followed by puromycin immunoprecipitation and detection of the protein of interest by western blot.

RIP-seq results

We have previously shown that Angel1 is found in a high-molecular weight complex (Gosselin et al., 2013). Moreover, we observed that Angel1 was purified with eIF4E in a cap-column experiment (Gosselin et al., 2013). We reasoned that, Angel1, in association with mRNAs and protein partners, forms a ribonucleoprotein complex (RNP) which is often the case for posttranscriptional regulators (Keene, 2007). To identify the mRNAs found in Angel1 mRNPs we decided to perform a native RNA Immunoprecipitation (RIP) experiment [START_REF] Keene | RIP-Chip: the isolation and identification of mRNAs, microRNAs and protein components of ribonucleoprotein complexes from cell extracts[END_REF].

In our case, since an antibody able to efficiently immunoprecipitate Angel1 is not commercially available, we decided to transiently express Halotag constructs: Angel1 wild-type, a mutated isoform called Angel1-YA (tyrosine to alanine) mutant previously shown to greatly decrease the ability to bind eIF4E (Gosselin et al., 2013) and other two newly proposed RNA-binding proteins that we recently identified: HSF2 and TRIP4. As positive control to setup the experiment we used a well-studied RNA binding protein CELF1 (previously called CUGBP1), while as negative control we expressed the Halo-tag only (Fig. 6A). Protein fused to the Halotag were eluted by cleavage using the Halo-TEV protease to release the RNP complexes from the beads in order to increase the specificity of the purified RNAs (Fig. 6A). The rationale to have such different samples is to determine the specific RNAs that not only are enriched over input but most importantly are significantly enriched comparing the samples between them.

Each expressed protein was validated for its expression and localization (Fig. 6B): RIP inputs and eluates were analyzed by Western-blot to verify efficient purification after cleavage by the TEV protease (Fig 6B). Libraries of around 20 million reads were generated (Fig. 6C). When the reads were mapped to the human genome, about 40% aligned for CELF1 (uniquely map and multimap reads, after removal of reads mapped to the luciferase RNA) reads samples while for the RIPs only 10-15% mapped to the human genome. Most of the unaligned reads mapped to the luciferase firefly RNA added during the protocol to help RNA precipitation.

RIP-seq experiments have been previously analyzed by applying two different approaches.

The first is to simply treat RIP samples as RNA-seq sample (sequencing of the totality of RNA in the cells i.e. transcriptome). The statistical power of transcriptome analysis is strictly dependent on two factors: number of replicates in each condition which must be at least of two replicates and size of the library. In our case the combination of only two replicates and the small size of our libraries implied that this solution was not applicable. The second strategy is treating sample similarly to the chromatin immunoprecipitation experiments (ChIP) where reads tend to accumulate to the actual binding site of the protein immunoprecipitated forming the so-called peaks. These peaks are identified through specific algorithms that are then compared to a negative control which is usually immunoprecipitation of the IgG antibody. In view of the clear similarities, in recent years many "peak-calling" algorithms have been specifically developed for RIP-seq and CLIP-seq data. In RIP-seq experiments, since there is no RNA digestion step as in CLIP, there should not be a precise peak but broader signal like the one obtained from ChIP experiments of histone marks. For these reasons peak-callers algorithm has been developed specifically for RIP datasets (RIPseeker, Piranha).

Unfortunately, we did not have enough reads to apply these methods.

We thus developed a custom ranking method. Firstly, we normalized and merged the two replicates libraries. Next, we filtered lowly expressed genes by applying a 3*IQR (Interquartile Range) cut-off. We then employed a second filter to remove the genes found to be nonspecifically precipitated in our negative control, the Halotag only, from the other samples.

Importantly as shown in Fig. 5D, removing the mRNAs precipitated by the Halotag, affected mainly the genes in common between all samples, while the specific genes of each RIP remained quite constant. After the Halo-background removal, we proceeded with validation of the targets of our positive control CELF1: we identified 1035 genes targets. We then compared the identified target genes for CELF1 with 2 recently published datasets of RIP [START_REF] Xia | CELF1 preferentially binds to exon-intron boundary and regulates alternative splicing in HeLa cells[END_REF] and CLIP [START_REF] Le Tonquèze | Identification of CELF1 RNA targets by CLIP-seq in human HeLa cells[END_REF] performed in HeLa cells. Xia and co-workers identified more than 5000 genes which contained peaks specific for CELF1. We were able to retrieve Ensembl IDs for 4220 genes while the rest was discarded. The authors of the CLIP experiment identified instead 1576 genes containing peaks both in coding and non-coding regions (list retrieve by table s3 in the supplementary material of (Le Tonquèze et al., 2016).

Our targets showed good overlap with both the experiment and notably there was a core of 161 genes common to all the three experiments (Fig. 6E). Importantly more than 50% of our CELF1 targets were also identified by Xia and co-workers. Taken together, these results validated our protocol of RIP from exogenous tagged proteins as viable alternative when antibodies are not available, and importantly served as validation of our ranking analysis. We then proceeded to the analysis of RIP of Angel1 wild type or mutated (YA) and by following this approach we were able to identify unique genes.

For Angel1 wild-type, 106 genes were enriched after removal Halotag background genes, while 84 for Angel YALA (Fig. 6E). More in detail, 14 genes were enriched only in Angel1 wild type and 10 for Angel1-YALA. Since it is well established many different RBPs and protein partners are simultaneously part of the same mRNP we decided to keep for further analysis also those gene shared with the others tested RBPs. Importantly, overlap between Angel1 and Angel1-YALA targets (Fig. 6F) showed good overlap between the two RIP experiments since 51 genes were found in common.

To investigate if possible RBPs are enriched in the mRNA targets of Angel1, we performed a RNA motif search of 102 known RBPs (Ray et al., 2013) using FIMO software (Grant et al., 2011) on the 5' and 3' of the 51 genes found in common between Angel1 and Angel1-YA (Fig. 6G). Then, we applied hypergeometric statistical test to evaluate if there was any statistically significant enrichment for the binding site of each of the tested RBPs.

This exploratory analysis identified some RBPs statistically enriched in both 5' and 3' UTRs (Fig. 6F marked with *). As perspective, the motif search described here, could be also applied to the target genes identified in the ribosome profiling and in the transcriptome analysis.

Inspection of the pattern of expression in the transcriptome and translatome analysis is undergoing.

Preliminary inspection detected 9 genes that are downregulated (logFC < -0.5) and 7 upregulated (logFC >0.5) in SH2 cells.

Supplementary results:

Angel1 is not phosphorylated by AKT/S6K

It is well established that post-translational modification can influence protein-protein interaction and one on the most studied is phosphorylation. Cap dependent translation is mainly regulated by the 4E-BP family (4E-BP1/2) and their ability to sequester eIF4E is tightly linked to their phosphorylation status. We have previously shown that binding of Angel1 to eIF4E is not sensitive to the mTOR pathway and is not affected by an increase in the eIF4E/4E-BP association. Therefore, we investigated if Angel1 ability to bind to eIF4E could be regulated by its phosphorylation status. We thus searched if in Angel1 amino acid sequence there was any phosphorylatable motif. Indeed, sequence analysis of Angel1 highlighted the presence of a strong consensus sequence for SK6/AKT phosphorylation site (RXRXXS/T) just after the binding site to eIF4E (Fig. 7A). To test this hypothesis Hela S3 cells were transiently transfected with Angel1-halo, subjected to 24 hours serum starvation and then stimulated or not by insulin. Then, we performed Angel1-Halo purification followed by Western blot analysis by specific antibodies raised against phosphorylated RXRXXS/T motif.

As shown in Fig. 7B, FBS starved inputs showed a global decrease in the levels of phosphorylation at RXRXXS/T sites while insulin treatment was partially able to recover the phenotype. After Angel1-halo purification we were not able to detect any phosphorylation at this site for any of the condition tested. We thus concluded that Angel1 is not phosphorylated at this site. Indeed, Databases collecting information about protein post-translational modifications (PTMs) such as (PhosphoSitePlus) do not report any phosphorylation identified at this site, and in general, for other reported sites there are still few proofs, and all are coming from high-throughput experiments.

Angel1 does not affect cell cycle progression

Angel1 belongs to the ccr4 (carbon catabolite repression 4) family and its closest ortholog is Angel2. Importantly, Angel2 expression depends on the cell cycle and its ectopic expression induces cell cycle arrest at G1 phase, while its down-regulation induces cell cycle progression (Yi et al., 2012).

We thus tested whether Angel1 could also affect cell cycle by Bromodeoxyuridine (BrdU) Angel1 expression is strongly induced at mRNA level at differentiation stage of pancreatic endoderm precursor of the pancreatic endocrine cells that form the Islet of Langerhans (Fig. 9D). Islet of Langerhans reflect 1-2% of the total pancreatic mass in adults and form endocrine compartment. Between 65 to 80% of total islet cells is composed by β-cells and their primary function is to store and release insulin which in turn regulates blood glucose levels. To study a possible role of Angel1 in regulation of insulin secretion we took advantage of a unique immortalized human Beta cell line able to secrete insulin in response to glucose stimulation (EndoC-βH1) (Ravassard et al., 2011).

incorporation
To assess the function of Angel1 in this cell line, we first validated a new siRNA against Angel1 by western blot, immunofluorescence and qRT-PCR assays. We observed a reduction of 70-80% of Angel1 mRNA and protein content (Fig. 9A). We then decided to investigate whether Angel1 downregulation impacts global translation rates by polysome profiling on sucrose gradients, which resolve free mRNPs and ribosomal subunits from translation-engaged mRNAs. Analysis of the generated profiles (Fig. 9B) didn't emphasize any difference in the number of actively translating ribosomes between the two conditions. We further verified that Angel1 did not change rates of protein synthesis by [S35]-methionine incorporation assay (Fig

Discussion

We have previously shown that Angel1 have a distinct perinuclear localization with strong colocalization with the Endoplasmic Reticulum and the Golgi apparatus. In this work we further characterized Angel1 localization. Firstly, we validated Angel1 localization by a different cell fractionation method (Fig. 1A) where Angel1 co-purified with an ER-enriched fraction (Fig. 1 A, line P100). Importantly, we confirmed that 4E-BP1 is only found in the cytosolic fractions (Fig. 1A lines S10, S100) while eI4E partially co-purified with the P100 fraction in agreement with our precedent work (Gosselin et al., 2013) and others (Willett et al., 2011). Secondly, by adopting a protease protection assay method, we showed that Angel1 associates with the cytosolic face of these membranes (Fig. 1B). These results support the idea that Angel1 can locally interact with the translation initiation factors and thus regulate expression of specific mRNAs. We then observed the presence of a 21-amino acid long N-terminal peptide which if removed causes a mis-localization of Angel1 (Fig. 2B, Δ-A1-HA). Moreover, we showed that neither Angel1 nor the Δ-A1-HA colocalized with DCP1, a marker of P-bodies (Fig. 2C).

Finally, Angel1 localization was not influenced by treatment with arsenate (Fig. 2D) which induces generation of oxygen reactive species (ROS) causing formation SGs.

Angel1 belongs to a family of proteins called the "Carbon Catabolite Repressor 4" (CCR4), whose members possess a conserved Mg 2+ -dependent nuclease domain shared by all members of the Exonuclease, Endonuclease, and Phosphatase (EEP) superfamily. Based on the strong conservation of the domain, Angel1 is predicted to have a deadenylation activity.

To date Angel1 deadenylation activity has not been proven despite a previous attempt have been made (Wagner et al., 2007). We were not able to detect any in vitro deadenylase activity for Angel1-Halo tagged purified from HeLa cells (Fig. 3A). Notably, for other two human proteins members of the CCR4 family, Angel2 and Nocturnin, in vitro deadenylation activity was not detected, but both proteins have been shown to have a role in vivo. Wagner and coauthors showed that Angel2 interacted with TOE1 (alternatively called CAF1z) (Wagner et al., 2007), while for Nocturnin a recent work demonstrated that point mutations on known amino acid required for deadenylase activity in the CCR4 family diminished mRNA repression in a tethered function assay (T. Abshire et al., 2018).

Next, we performed transcriptome analysis of HeLa cells were Angel1 have been silenced.

We demonstrated that Angel1 KD downregulated mRNA levels of a small pool of genes (Fig. 4D-G). This phenotype is in contrast with the role of the deadenylases as repressors of mRNA levels as demonstrated by the transcriptome analysis of the KD of two members of the CCR4 family (CNOT6 and CNOT6L) which led to 79 commonly up-regulated genes and only 4 downregulated [START_REF] Mittal | The Ccr4a (CNOT6) and Ccr4b (CNOT6L) deadenylase subunits of the human Ccr4-Not complex contribute to the prevention of cell death and senescence[END_REF]. These results point towards a loss of deadenylase activity for Angel1. One possible explanation of the loss of function for Angel1 could the insertion of a new exon coding for the eIF4E binding motif (Gosselin et al., 2013) between the exons coding the for the EEP domain. The downregulation of the identified genes could be explained by different reasons: Angel1 could, through others functional domains, regulate indirectly their transcription rates. As perspective it would be interesting to address the effect of a complete knout out of Angel1.

Then, we investigated the possible role of Angel1 in regulating translation of specific mRNAs since we have previously shown that Angel1 does not global rates of translation (Gosselin et al., 2013). To this end we performed ribosome profiling [START_REF] Ingolia | The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosomeprotected mRNA fragments[END_REF]) that led to identification of genes which translations rates were affected but not their mRNA steady state levels. Importantly 5 targets were in common between the SH-2 and SH-3, which represented more than 50% of the SH-3 targets. To corroborate our analysis, we performed a complementary analysis using the Babel R package [START_REF] Olshen | Assessing gene-level translational control from ribosome profiling[END_REF]. Importantly a core of 21 genes was common to both analyses. As next step, we will have to investigate by western blot analysis if the proteins levels of the identified genes are altered.

RIP-seq is another strategy that we adopted to identify Angel1 targets genes. To this end we developed a new RIP-seq workflow of RIP-seq Halo-tagged proteins. We demonstrated that mRNAs bound by our positive control, CELF1, shared a good overlap with the mRNAs identified by other groups. Moreover, we have developed a new strategy to identify possible target genes with a qualitative approach that allowed us to identify specific genes for Angel1.

The identified targets will need further validation by RIP combined with RT-qPCR.

As supplementary results we observed by cell cycle experiments that Angel1 does affect cell proliferation contrary to its closer family member Angel2 that was shown to modulate cell cycle progression by regulating the stability of p21 mRNA (Yi et al., 2012).

To address Angel1 function in a more physiological model we investigated the role of Angel1 in a unique human B-cell line. We showed that Angel1 is expressed, then we validated the efficient KD of Angel1. Angel1 KD did not show a clear effect on the global rates of translation analyzed by [35S]-Methionine incorporation assay and polysome profile. We conclude that also in this cellular model Angel1 affects only a subset of mRNAs. (marker of processing bodies) (Fig. 2C). Cell were treated with arsenate treatment to induce SGs (Fig. 2D). The z-projections are displayed, together with merged images with a nuclear staining (DAPI). Scale bar, 10 µm. In blue, genes found to be commonly differentially translated in SH2 and SH3 by RNAseq123 analysis.

Introduction

Pancreatic islet β-cell play a pivotal role in maintenance of normoglycemia by synthesizing, storing and secreting insulin. Glucose uptake and metabolism are essential for regulation of glycemia by stimulating insulin secretion and triggering specific gene expression, which has been widely studied in rodent animals and rodent β-cell lines since 1970s [START_REF] Hohmeier | Cell lines derived from pancreatic islets[END_REF]. On the other hand, due to the long-standing difficulties to generate a human cellular model [START_REF] Scharfmann | Concise Review: In Search of Unlimited Sources of Functional Human Pancreatic Beta Cells[END_REF] or to access to primary human islet preparations derived from deceased donors [START_REF] Movahedi | Pancreatic Duct Cells in Human Islet Cell Preparations Are a Source of Angiogenic Cytokines Interleukin-8 and Vascular Endothelial Growth Factor[END_REF], there is a scarcity of results obtained from human models. Importantly, despite many similarities, there are major differences between human and rodent models such as: the copy number of insulin genes, expression of different transcription factors, differences in glucose stimulated insulin secretion, architecture of the Islet of Langerhans with functional implication and finally different susceptibility to β-cell injury [START_REF] Scharfmann | Concise Review: In Search of Unlimited Sources of Functional Human Pancreatic Beta Cells[END_REF]. Moreover, concerning glucose dependent gene expression regulation, recent transcriptome studies have shown impressive differences between human and rodent cells line. A recent transcriptome study of the first human β-cell line (EndoC-Bh1) able to secrete insulin in response to glucose stimulation (Ravassard et al., 2011) showed scarce differences at the transcriptome level for cells either exposed for eight hours to high or low glucose concentrations [START_REF] Richards | MondoA Is an Essential Glucose-Responsive Transcription Factor in Human Pancreatic β-Cells[END_REF]. Accordingly, a previous report on donor human islet treated similarly for twenty-four hours [START_REF] Shalev | Oligonucleotide Microarray Analysis of Intact Human Pancreatic Islets: Identification of Glucose-Responsive Genes and a Highly Regulated TGFβ Signaling Pathway[END_REF] reported that the expression of only 20 genes was affected. On the other hand, a comparable study in the rat β-cell line INS-1 reported that more than 2000 genes were significantly affected [START_REF] Schmidt | Integrative Genomics Outlines a Biphasic Glucose Response and a ChREBP-RORγ Axis Regulating Proliferation in β Cells[END_REF]. Taken together these data highlight a striking difference in gene expression regulation at transcriptional level between human and mouse pancreatic β-cell.

Glucose regulation at post-transcriptional level has also been addressed in rodent models since the 70s. In particular researcher attention focused on regulation of insulin biosynthesis [START_REF] Itoh | Glucose stimulation of the proinsulin synthesis in isolated pancreatic islets without increasing amount of proinsulin mRNA[END_REF] (Welsh et al., 1986) [START_REF] Permutt | Effect of glucose on initiation and elongation rates in isolated rat pancreatic islets[END_REF] reported that replenishing of insulin in short term, up to 60 minutes [START_REF] Itoh | Glucose stimulation of the proinsulin synthesis in isolated pancreatic islets without increasing amount of proinsulin mRNA[END_REF], was entirely mediated at translational level without affecting mRNA abundance. Additionally, these works observed that the synthesis of other proteins were also stimulated, without being able to identify them. A genome wide translatome study addressed this issue in mouse insulinoma 6 (MIN6) cell line by polysome profiling followed by microarray analysis [START_REF] Greenman | Distinct glucosedependent stress responses revealed by translational profiling in pancreatic -cells[END_REF]. Authors reported the identification of 313 genes, for which the association with polysomes was changed by at least 1.5-fold-change. To date, no genome wide studies have been made on human β-cell cells that address glucose post-transcriptional regulation, and importantly there are no reports even for regulation of insulin biosynthesis. Here we showed that twenty-four hours of glucose starvation shut down translation by the mTORC1 pathway regulation and eIF2alpha phosphorylation in EndoC-βH2 cells, a human pancreatic β-cell line exhibiting glucose inducible insulin secretion [START_REF] Scharfmann | Development of a conditionally immortalized human pancreatic β cell line[END_REF]. Moreover, we show that short exposure (30 minutes) to high glucose concentrations quickly restores protein synthesis in a transcription independent manner. Next, to identify genes whose translation rates were changed by glucose we performed polysome profile combined with RNA sequencing. We report that the levels of 525 mRNAs associated with polysomes were significantly affected by glucose stimulation.

Materials and Methods

Cell culture and treatment

EndoC-bH2 cells [START_REF] Scharfmann | Development of a conditionally immortalized human pancreatic β cell line[END_REF] were cultured in low-glucose (5.6 mmol/L) DMEM (Sigma-Aldrich) with 2% BSA fraction V (Roche-Diagnostics), 50 mmol/L 2mercaptoethanol,10 mmol/L nicotinamide (Calbiochem), 5.5 mg/mL transferrin (Sigma Aldrich), 6.7 ng/mL selenite (Sigma-Aldrich), 100 units/mL penicillin, and 100 mg/mL streptomycin. Cells were seeded at a 40% confluence on plates coated with Matrigel (1%;

Sigma-Aldrich), fibronectin (2 mg/mL; Sigma-Aldrich). Cells were cultured at 37°C and 5%

CO2 in an incubator and passaged once a week when they were 90-95% confluent. For polysome profile experiments cells were plated 4 days before treatment to reach 80-90% confluence the day of experiment. Cells were glucose-starved for 24 hr at 0.5 mmol/L glucose and then media was replaced with fresh media (5.6 mmol/ml), fresh high-glucose media (20 mmol/L) or with low-glucose media (0.5 mmol/L) for 30 minutes. In SunSET experiments where indicated, glucose-starved cells were treated for 1 hour with either 50 nM rapamycin (RAPA, R8781 Sigma) or 50 µg/ml cycloheximide (CHX, C104450 Sigma-Aldrich).

fraction and genes was calculated the logarithmic ratio of means of high glucose over low glucose. The generated matrix set was then subjected to perform both to both hierarchical clustering (hclust of the Euclidean distances with the ward.d2 method) and classical K-means clustering, where the number of cluster was selected by applying a within groups sum of squares curve for different sizes of k.

mRNA features collection

A custom-made program was used to obtain, for each of the DEGs, the Ensembl transcript ID of the two most expressed transcripts in heavy polysomes, which was previously calculated via RSEM [START_REF] Li | RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome[END_REF]. Next, for each of the transcript ids, taking advantage of the bioMart database, different mRNA features were extracted using a program under development in our lab. The mRNA features that we calculated were: length of all the 5'UTR, CDS and 3'UTR; the GC content of both 5' and 3' UTR; the folding free energy for the 5' and 3' UTR. Due to incomplete annotation on the Ensembl database, few genes (14 genes) annotation of both the top expressed transcript we were not able to extract all the necessary values hence were discarded.

Results

Glucose induces rapid protein synthesis in human β-cells

Recently, a human pancreatic β-cell, called EndoC-βH1, able to secrete insulin in response to glucose have been developed (Ravassard et al., 2011). Surprisingly, in a recent published microarray study, after 8 h of exposure to high or low glucose (EndoC-βH1 cells), showed scare effect on gene expression regulation with only 21 genes affected. We thus hypothesized that glucose could induce changes in the rate of protein synthesis. To address our hypothesis, we performed the SunSET protocol (Schmidt et al., 2009) on a 2 nd generation of human β-cell line (EndoC-βH2 cells). The SunSET method estimates global proteins synthesis by measuring the rates of puromycin (PMC) incorporation using specific anti puromycin antibodies, by FACS and Western blot experiments. Cells were starved for 24 hours at 0.5 mM glucose and then were either kept at 0.5 mM or stimulated with 5.6 mM or 20 mM glucose for 30 minutes. In the last 10 minutes of stimulation, puromycin was added to the media. As control, cells were pretreated for one hour with cycloheximide (CHX) to block translation.

Measurements of puromycin incorporation by Western-blot showed strong induction of proteins synthesis when cells were stimulated with 20 mM, while a minor but still significant induction was detected at 5.6 mM glucose in comparison to glucose-starved cells at 0.5 mM (Fig. 1A).

It has been recently described that glucose deprivation is sensed by the aldolases through sensing its glycolytic intermediate fructose . Reduction in FBP causes the formation of a membrane-associated lysosomal complex which in turn activates AMPK (Zhang et al., 2017). AMPK acts on both Raptor (subunit of the mTORC1 complex) and TSCcomplex, reducing mTORC1 signaling [START_REF] Corradetti | Regulation of the TSC pathway by LKB1: evidence of a molecular link between tuberous sclerosis complex and Peutz-Jeghers syndrome[END_REF]) (Gwinn et al., 2008). We thus tested the effect of rapamycin (RAPA), a known inhibitor of mTORC1 signaling, that acts as an allosteric inhibitor of mammalian TOR complex 1 (mTORC1) by blocking Raptor recruitment. Importantly, Inhibition of mTORC1 partially prevented the increase in translation (Fig. 1A). It is well established that mTORC1 regulates translation through the modulation of the phosphorylation status of both 4E-BP1 and p70 S6 kinase (S6K). Thus, to further validate that mTORC1 signaling is a key player in glucose stimulation, we tested the phosphorylation status of the ribosomal proteins S6 (RPS6) at Ser235/236, a known target of S6K. Indeed, increasing glucose concentration induced strong phosphorylation of RPS6 which was abrogated by rapamycin treatment (Fig. 1B top panel).

Another key control of translation initiation during metabolic adaptation is the phosphorylation of the eukaryotic initiation factor 2 alpha (eIF2α) on Ser-51, which inhibits assembly and recycling of the translational ternary complex (eIF2-GTP•Met-tRNAi). Since rapamycin did not completely inhibit the increase in translation observed upon glucose stimulation we hypothesized that eIF2α regulation could be implicated. We therefore examined the phosphorylation status of eIF2α at Ser-51. Western Blot analysis highlighted a gradual dephosphorylation of eIF2α upon glucose stimulation (Fig. 1B) indicating a release of the inhibition on the ternary complex. Taken together these results showed that short glucose stimulation can induce a strong translation activation in both mTOR and eIF2 dependent manner. We next quantified whether the global increase in translation was associated to modification of mRNA steady state levels by genome wide transcriptome analysis. We generate triplicates for both high and low glucose conditions, each library contained around 16-18 million reads out of which almost 80% were uniquely mapped to the human genome (Fig. 1C). Reads mapped to genes annotated as "protein coding genes" were kept for further analysis. Hierarchical clustering clearly separated the samples in two clusters each containing the replicates of the condition (Fig. 1D, TotL (1/2/3) correspond to 0.5 mM glucose, while TotH

(1/2/3) correspond to 20 mM glucose). We thus proceeded with differential gene expression analysis using Limma package (see material and methods). Importantly, the results, represented with an MA plot in Fig. 1E, clearly highlighted that mRNAs levels were not significantly affected by the glucose treatment for 30 minutes hence the increase in puromycin incorporation is completely independent from a transcriptional regulation. These results corroborate the recent work obtained in the EndoC-βH1 cell line, where 8 hours exposure to either low or high glucose had scarce effect on gene expression [START_REF] Richards | MondoA Is an Essential Glucose-Responsive Transcription Factor in Human Pancreatic β-Cells[END_REF]. Taken together, these results indicate a rapid induction of protein synthesis which is independent of changes in mRNA abundances (Fig. 1D)

Identification of genes which translation is affected by glucose stimulation in human βcells

In order to identify genes whose translation rates are regulated by glucose we performed polysome profiling, a gold standard technique which separates free mRNPs and ribosomal subunits from translation-engaged mRNAs, followed by RNA sequencing. Triplicates of EndoC-βH2 were starved for 24 hours at 0.5 mM glucose and then treated for 30 min with either 0.5 mM or 20 mM glucose. We observed, by analysis of the polysome profiles (Fig. 2A), that increasing glucose to 20 mM triggered an important decrease in the monosomes peak (80S) with a parallel increase in the content of polysomes which is classically observed with a global increase in translation. This result agreed with the global induction of translation observed by the SunSET experiment presented above (Fig. 1A).

We then evaluated the different possibilities to select the fractions of the polysome to use for RNA sequencing to obtain the best compromise between resolution and sensitivity. The commonly adopted strategy to identify differentially translated genes is usually to perform microarray analysis or RNA sequencing performed on mRNAs associated with more than 3 ribosomes. More recently. a new method employed RNA sequencing for each fraction of the profile from monosomes to the heavy polysome [START_REF] Floor | Tunable protein synthesis by transcript isoforms in human cells[END_REF]. In this study, hierarchical clustering of the sequenced fractions formed three cluster containing the monosomes (80S), light polysomes (2-4 ribosomes per mRNA) and heavy polysomes (> 4 ribosomes per mRNA), delineating transcript populations as efficiently translated (heavy polysomes) or less efficiently (light polysome). Considering these results, we decided to divide the polysome profiles in three parts: monosomes (fractions 5-6, light polysomes (fractions 7- 9) and heavy polysomes (fractions 10-13) indicated by a color code in Fig. 2A. It is interesting to note that the relatively short transcript of insulin, was shown to associate mainly to light polysomes in mouse models cells [START_REF] Greenman | Distinct glucosedependent stress responses revealed by translational profiling in pancreatic -cells[END_REF].

Libraries were prepared from three biological replicates for both conditions (0.5 mM and 20 mM). After sequencing and read quality control, reads were aligned to the human genome.

We obtained 60% to 80% uniquely mapped reads (Fig. 2B). We noticed that monosome samples had the lowest percentage of uniquely mapped reads. For further analysis genes, only reads mapping to genes annotated as protein coding were kept. Importantly low expression genes with high variability between replicates were also discarded (see material and methods). Hierarchical clustering of the samples (Fig. 2C) clustered biological replicates of each condition and fraction together thus validating the quality of our samples. Importantly, monosomes and light polysomes clustered together away from heavy polysomes (Fig 2C).

We thus proceeded to determine differences in the abundance of mRNA between low and high glucose concentration in the different fractions. The analysis revealed that the abundance of 352 mRNAs in heavy polysomes and 231 in light polysomes were significantly changed (adjusted p-value < 0.05). As expected, for the majority of identified genes, glucose caused an increase of their association with the polysomes, 282 in heavy and 188 in light, thus only a minority of genes decreased: 43 and 70 for light and heavy polysome respectively (Fig. 2D, in summarizing table and MAplots, in green mRNAs upregulated while in red downregulated).

Importantly, 56 genes were found upregulated in both fractions while 2 genes were down regulated in both (Fig 2D). Surprisingly, no genes were identified by the analysis of monosome fraction even though there is a striking tendency for some genes to be down-regulated by glucose (Fig. 1D, MA-plot Monosomes_HvsL, highlighted by a red circle). We are currently addressing the possible reasons that could be intra-replicates variability

Glucose regulates translation rates of mRNA involved in the insulin secretion pathway

As a first approach to investigate the differently translated genes, we decided to assess if glucose stimulation regulated biosynthesis of insulin and of known major players involved in insulin maturation secretion pathway such as prohormone convertases 1/3 (PC1/3) and 2 (PC2) [START_REF] Alarcón | The biosynthesis of the subtilisin-related proprotein convertase PC3, but no that of the PC2 convertase, is regulated by glucose in parallel to proinsulin biosynthesis in rat pancreatic islets[END_REF], chromogranin A (CHGA) [START_REF] Guest | Regulation of the biosynthesis of insulinsecretory-granule proteins. Co-ordinate translational control is exerted on some, but not all, granule matrix constituents[END_REF], and Islet cell autoantigen (ICA512) [START_REF] Ort | Dephosphorylation of beta2-syntrophin and Ca2+/mu-calpain-mediated cleavage of ICA512 upon stimulation of insulin secretion[END_REF]. Their biosynthesis was reported to be enhanced in response to glucose in rodent cells. As expected ICA512 was upregulated (Fig. 2E). On the contrary, CHGA mRNA was downregulated in heavy polysome. Unexpectedly, insulin, PC1/3 and PC2 were not among the identified genes (Fig. 2E). Taken together, these results indicate that the human EndoC-βH2 cell line quickly modify the translation rates of two mRNA that code for proteins involved in the insulin secretion pathway.

Clustering analysis of the differentially translated genes

To analyze the full set of identified genes (525 genes differentially expressed in light or heavy polysomes) we assessed if differentially expressed genes could be clustered based on similar behavior among the three fractions. To this end, we calculated for each gene the log2 ratio of the average expression in each fraction in high glucose condition over the corresponding average expression in low glucose condition. The generated matrix was then to subjected kmeans clustering where the number of clusters to obtain was set to 4 (Fig. 3A). We selected the number of clusters (k) for k-means by combining two criteria: a biological, based on the possible "behaviors" of genes in the 3 different fractions, and a statistical, by applying a within groups sum of squares curve for different sizes of k. The four-cluster generated have 4 different types of behaviors and we can distinguish them easily by the colored bar next to the heatmap (Fig. 3B). Genes of the bottom cluster, identified by the black bar, showed a clear pattern for 108 mRNAs shifting from the monosome (red corresponds to a decrease in mRNA level upon glucose treatment) to both light and heavy polysomes, which is the expected behavior for gene with increased translation. Instead, the mRNAs of the second cluster (red bar ,145 mRNAs), showed increased mRNA levels for all the 3 groups (monosome, light and heavy polysomes) with a more pronounced effect on the light polysomes: the translation of these mRNA also increased. The tendency to have higher levels also in the monosome was not expected, and we hypothesize that at low glucose concentration these mRNAs are in complexes that have a density smaller than one ribosome. The third cluster (green, 150 mRNAs) presented a behavior similar to cluster 1 but with no general increase in mRNA level in the light polysome. Finally, the last cluster (blue, 111 mRNAs) collected all those mRNAs whose levels in the polysome fractions decreases upon glucose stimulation which correspond to a decrease in their translation.

Then we hypothesized that the different patterns observed for the clusters could be a consequence of trans or cis-acting elements present on the mRNAs. To investigate this possibility, we first selected the two most expressed transcripts of the differentially translated genes based on the levels of expression in the heavy fraction of the polysomes calculated by RSEM [START_REF] Li | RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome[END_REF]. For that, we developed a RNA feature extraction tool (https://parisepigenetics.github.io/rna_feat_ext/) that is able to download, from the Ensembl database bioMart (https://www.ensembl.org/biomart/), the transcript sequences with additional annotations. Then, the software extracts the following features: length and GC content of the 5', 3' UTRs, and length of the coding sequence (CDS). The program also calculates, by calling the RNAfold tool of the Vienna suite [START_REF] Lorenz | ViennaRNA Package 2.0[END_REF], the minimum folding energy (MFE) which is a measure of the stability of the RNA secondary structure.

Thus, we proceeded by comparing these mRNA features between the different clusters.

Strikingly, the length of the CDS of the mRNAs assigned to cluster 1 (black) were significantly shorter, while in cluster 4 (blue) the CDS were longer. Thus, on average, down-regulated mRNAs coded for larger proteins than the upregulated mRNAs (Fig. 3C). Then, we analyzed the length of the UTRs (Fig. 3D). Notably, mRNAs of first cluster contained shorter UTRs than the other groups. Cluster 3 (green) showed similar tendencies towards shorter 5' UTRs.

Cluster 4 clearly contained mRNAs with longer 3' UTRs.

We then analyzed the GC-richness of the 5' and 3'UTRs, which is used as proxy to determine the complexity of secondary structures formed by the mRNA. Cluster 2 (red) contained mRNAs with higher GC content on both 5' and 3' UTRs than the others (Fig. 3E). Another method to analyze mRNA structure is to determine the minimum folding energy (MFE). Cluster 2, as expected due to the high GC-content, contained mRNAs with more structured 5' and 3'

UTRs than the other clusters. The mRNAs in cluster 1 had the lowest measurement for both 5' and 3' UTRs, due to intrinsic relationship of the minimum folding energy and the length.

Importantly, cluster 4, containing mRNA with longer 3'UTRs, also showed higher MFE.

Taken together, these results showed a correspondence between the differences in translation levels in the three fractions and particular features of the mRNA molecules.

Gene ontology

Next, we performed gene ontology enrichment analysis, using the R package ClusterProfiler [START_REF] Yu | clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters[END_REF], in order to assess if the mRNAs constituting the different clusters, were implicated in specific biological processes. Cluster 1 was enriched for categories related to translation but especially for ER related translation (Fig. 4A). Cluster 3 was enriched also for categories related to translation initiation and elongation, but also showed enrichment for regulation of the nucleocytoplasmic transport (Fig. 4B). We thus investigated if ribosomal proteins or eukaryotic translation factor were found in these two cluster. Indeed, cluster 1 contained 61 ribosomal proteins (RP) while cluster 3 contained 11 eukaryotic translation factors of which 4 were elongation factors (EEF1A1, EEF1A2, EEF1B2, EEF2) and the remaining where initiation factors (EIF2A, EIF2S3, EIF3E EIF3G, EIF3M, EIF4A2, EIF4B). The mRNAs that code for these proteins are known to contain a specific cis-regulatory element:

the 5′-terminal oligopyrimidine (TOP), defined as TOP-mRNAs [START_REF] Meyuhas | The race to decipher the top secrets of TOP mRNAs[END_REF].

Therefore, we compared the mRNAs found in cluster 1 and 3 with the list of mRNAs that were previously reported or proposed to be TOP-mRNA in at least two of already published articles: [START_REF] Thoreen | A unifying model for mTORC1-mediated regulation of mRNA translation[END_REF]) [START_REF] Markou | Regulation of the cardiomyocyte transcriptome vs translatome by endothelin-1 and insulin: translational regulation of 5' terminal oligopyrimidine tract (TOP) mRNAs by insulin[END_REF]) [START_REF] Huo | Stable isotope-labelling analysis of the impact of inhibition of the mammalian target of rapamycin on protein synthesis[END_REF] and [START_REF] Meyuhas | The race to decipher the top secrets of TOP mRNAs[END_REF] (Table 1). Overlap between the three set of genes showed that cluster 1 contained 67 known TOP-mRNA while cluster 3 contained 15 (Fig. 4C).

Two ribosomal proteins were found in cluster 2 (RPL35 and RPS28) while none in cluster 4. The mRNAs in cluster 2 were not enrich in any of gene ontology category neither for molecular function nor for biological process. This could be explained if single mRNAs involved in different pathways are activated.

Cluster 4, which contained the translationally repressed mRNAs, was enriched in mRNAs coding for proteins involved in regulation of metabolic and apoptotic (e.g. neuron death)

processes. We have previously established that eIF2α was hyperphosphorylated at low glucose (Fig. 1B), which is known to favor translation of mRNAs containing uORFs. Thus, we searched if, among the downregulated genes, we could find examples of mRNAs reported to contain uORFs. Indeed, some of the identified genes, have been previously reported to contain uORFs such as the cyclic AMP-dependent transcription factor (ATF4), C/EBP homologous protein (CHOP) and the activating transcription factor 5 (ATF5) [START_REF] Watatani | Stress-induced Translation of ATF5 mRNA Is Regulated by the 5′-Untranslated Region[END_REF], ATF5 has been recently shown to play an important role in regulating pancreatic βcells survival [START_REF] Juliana | ATF5 regulates β-cell survival during stress[END_REF] and [START_REF] Juliana | A PDX1-ATF transcriptional complex governs β cell survival during stress[END_REF]. ATF4 was the most translationally downregulated gene identified (log2 FC -1.5 in heavy polysomes). Importantly ATF4 is known to be the master regulator of metabolism in response to energetic stresses and depending on the intensity and length of the stress can either favor cell survival through upregulation of autophagy related genes and amino acid transporters or enhance expression of genes involved in apoptotic processes [START_REF] Lindqvist | Cross-talk between protein synthesis, energy metabolism and autophagy in cancer[END_REF]. We observed that the eEF2K was also found in cluster 4 and it was recently reported to contain an uORF which could act as a brake mechanism to avoid over repression of translation at the elongation step (Andreev et al., 2015). We then searched for mRNAs containing IRESs whose translation is enhanced in condition where general translation is silenced. To this end, we searched if, in the published literature, any of the translationally repressed mRNAs was reported to contain an IRES. We found the mRNA that codes for RRBP1 (Ribosome-binding protein 1), has been shown to contain an IRES in its 5' UTR [START_REF] Gao | La Autoantigen Induces Ribosome Binding Protein 1 (RRBP1) Expression through Internal Ribosome Entry Site (IRES)-Mediated Translation during Cellular Stress Condition[END_REF]. Importantly RRBP1 may be involved in the regulation of mRNA stability of UPR components including ATF6 and GRP78 with an antiapoptotic role [START_REF] Tsai | Endoplasmic reticulum ribosome-binding protein 1 (RRBP1) overexpression is frequently found in lung cancer patients and alleviates intracellular stress-induced apoptosis through the enhancement of GRP78[END_REF]) [START_REF] Sharma | Grp78 Is Critical for Beta-Cell Maturation and Survival[END_REF].

Discussion

We have observed that glucose stimulation rapidly enhances protein synthesis in a mTOR and eIF2 dependent manner. Gomez and co-workers [START_REF] Gomez | Glucose-stimulated Protein Synthesis in Pancreatic β-Cells Parallels an Increase in the Availability of the Translational Ternary Complex (eIF2-GTP•Met-tRNAi) and the Dephosphorylation of eIF2α[END_REF], studying glucose stimulation in murine MIN6 cells, concluded that translation regulation by glucose is largely independent of mTOR but mainly depends on availability of the ternary complex regulated by eIF2α phosphorylation status. In this human cellular model, instead, mTORC1 likely plays a more important role but these hypothesis needs further investigation. Next, we have shown that 30 minutes of glucose stimulation had no effect on mRNA abundance which is in agreement with a recent microarray study performed in EndoC-βH1 in which only few genes were affected after 8-hour of glucose stimulation [START_REF] Richards | MondoA Is an Essential Glucose-Responsive Transcription Factor in Human Pancreatic β-Cells[END_REF]. Next, to identify genes regulated at translation level we performed the first translatome study of a human pancreatic β-cell line upon glucose stimulation. We have identified 525 mRNAs whose association with different polysomal fractions changed upon glucose stimulation. We report that two important genes involved in the regulation of secretory granules, CHGA and ICA512 are translationally regulated in human pancreatic β-cells. Strikingly, in mouse models, glucose was reported to induce biosynthesis of the CHGA, instead in our experiment CHGA significantly decrease its association with heavy polysomes. CHGA is a member of the granin glycoprotein family and its main intracellular function is to sort proteins into the secretory granules. CHGA is also secreted and generate several cleaved products among which pancreastatin that have been shown to act in an autocrine and paracrine fashion by inhibiting glucose stimulated insulin secretion [START_REF] Ahren | Pancreastatin modulates glucosestimulated insulin secretion from the perfused rat pancreas[END_REF]. The biological meaning of the reduction of the biosynthesis CHGA needs validation and further investigation. Instead, the ICA512 translation increase was also reported in mouse models [START_REF] Ort | Dephosphorylation of beta2-syntrophin and Ca2+/mu-calpain-mediated cleavage of ICA512 upon stimulation of insulin secretion[END_REF]. ICA512 belongs to the receptor protein tyrosine phosphatase (RPTP) family and regulate basal and glucose induced insulin secretion in the mouse MIN6 cell line by increasing, presumably through stabilization, the number of insulin-containing dense core vesicles [START_REF] Harashima | The dense core transmembrane vesicle protein IA-2 is a regulator of vesicle number and insulin secretion[END_REF].

We have observed, by clustering analysis, that identified genes could be divided in four groups based on the different changes for their mRNA levels in the three polysomal sequenced fractions. We thus performed mRNA features analysis to identify possible mRNA features that could explained the observed different behaviors. Indeed, we have shown the transcripts of the four-different cluster possess different characteristics (Fig. 4). For example, we showed that most of cluster 1 mRNAs, are known as TOP-mRNA, possess short and unstructured UTRs but also short coding sequence confirming previous reports [START_REF] Thoreen | A unifying model for mTORC1-mediated regulation of mRNA translation[END_REF].

Importantly, 36 mRNAs of cluster 1 are not known to be TOP-mRNAs thus analysis of their 5'

UTRs could amplify the list of TOP mRNA or TOP-like mRNAs. Importantly some genes of cluster 3 were previously reported to be TOP mRNAs but the remaining 135 have not been associated to TOP mRNAs. By comparing the mRNA features of the two-mentioned cluster, we noticed similar characteristic but cluster 3 have in general mRNA with more complexes

UTRs and longer CDS. The mRNA that showed the strongest changes in the light polysome fraction were grouped in cluster 2. Notably this cluster showed a high GC content for both the UTRs regions. The GC content in the 5' UTR could render these mRNAs strongly dependent of the helicase activity of the eIF4A which is strongly activated by eIF4E. Importantly, these two proteins have shown to regulate translation of common targets but also regulated other independently of the other (Joyce et al., 2017). Thus, it will be worth to compare our set of mRNAs with other works to better understand the fine tuning behind them. As perspective, a possible strategy could be to cluster the identified mRNAs based on their mRNA features to discover all the possible different classes of regulated genes and then compare mRNAs clustered together have also similar translation patterns, thus proceeding in a reverse way that one described in this chapter. In conclusion, here we have described the first genome wide translatome study of a human pancreatic β-cell stimulated by glucose. The data generated can be a useful tool to understand β-cell gene expression regulation. Post-transcriptional coordinated regulation of functionally related genes by cis or trans acting factors, defined as RNA operons, has been postulated by Keene and Tanenbaum more than a decade ago [START_REF] Keene | Eukaryotic mRNPs May Represent Posttranscriptional Operons[END_REF]. Such coordinated expression is particularly important for macromolecular complexes on both regulating subunit and total complex abundances to allow quick regulations and adjustments and to maintain correct stichometry between the subunits.

In the work described in this chapter and presented in the format of published paper, we characterized a novel RNA operon under the control of hek2, a yeast hnRNP K-like protein.

We showed that hek2, binds to specific cis elements on a subset of mRNAs coding for part of the nucleoporins (Nups). Mono-SUMOylation of hek2 at two different sites causes a strong decrease in hek2 mRNA binding ability. Moreover, we identified Ulp1, a SUMO protease localized at nuclear side of the pore, as the modulator hek2 SUMOylation status. We further demonstrated that hek2 binding on Nups mRNA does not affect their localization nor their steady state level. In contrast, hek2 suppresses their translation rates as shown by the increased amount of target mRNA with translating ribosomes upon hek2 inactivation.

Importantly, the translation imbalance is counteracted by increase in degradation of proteins synthetized in excess helping the cell to maintain the correct stoichiometry between the nuclear pore components.

My contribution to this paper has been to show that some Nups mRNA, show an increase in translation in hek2 depleted cells compare to control. I also contributed to the reduction and corrections of the final manuscript.

ARTICLE

A SUMO-dependent feedback loop senses and controls the biogenesis of nuclear pore subunits Jérôme O. Rouvière 1,5 , Manuel Bulfoni 2 , Alex Tuck While the activity of multiprotein complexes is crucial for cellular metabolism, little is known about the mechanisms that collectively control the expression of their components. Here, we investigate the regulations targeting the biogenesis of the nuclear pore complex (NPC), the macromolecular assembly mediating nucleocytoplasmic exchanges. Systematic analysis of RNA-binding proteins interactomes, together with in vivo and in vitro assays, reveal that a subset of NPC mRNAs are specifically bound by Hek2, a yeast hnRNP K-like protein. Hek2dependent translational repression and protein turnover are further shown to finely tune the levels of NPC subunits. Strikingly, mutations or physiological perturbations altering pore integrity decrease the levels of the NPC-associated SUMO protease Ulp1, and trigger the accumulation of sumoylated versions of Hek2 unable to bind NPC mRNAs. Our results support the existence of a quality control mechanism involving Ulp1 as a sensor of NPC integrity and Hek2 as a repressor of NPC biogenesis. V irtually all cellular processes rely on the function of multiprotein assemblies. While their stoichiometry has to be tightly controlled to prevent an imbalance of subunits that could interfere with their assembly or titrate their targets, their global abundance has also to be adjusted in response to the cellular demand 1 . Multiple layers of mechanisms have been reported to partake in the accurate biogenesis of multisubunit complexes. First, all the steps in the gene expression pathway, including messenger RNA (mRNA) synthesis, processing, transport, stability and translation, can be regulated in a coordinate manner, either to lead to the proportional synthesis of the different subunits of multiprotein assemblies, a prominent strategy in prokaryotes 2 , or to respond to environmental or physiological cues, as exemplified by the ribosome biosynthesis pathway 3 . In this frame, a pivotal role has emerged for transcriptional regulators and RNA-binding proteins, the latter being in particular capable to tune the translation rate of their target messenger ribonucleoparticles (mRNPs). Second, molecular chaperones and assembly factors can further assist the assembly of multiprotein complexes, as also described for ribosomes 3 , in some cases in a cotranslational manner 4 . Finally, excess complexes or unassembled, orphan polypeptides can be targeted for degradation by the proteasome or the lysosome 5 , with these quality control processes being critical to adjust stoichiometry and to cope with altered protein dosage 6,7 . However, despite our improved knowledge in proteome dynamics, the specific mechanisms at play for most multiprotein complexes remain largely unknown.

The nuclear pore complex (NPC) provides a paradigmatic example of an essential multisubunit complex whose homeostasis is crucial yet poorly understood. NPCs are megadalton-sized proteinaceous assemblies embedded at the fusion points of the nuclear envelope and formed of modular repeats of ~30 distinct protein subunits-the nucleoporins (Nups)-which assemble within subcomplexes and organize with a 8-fold rotational symmetry 8 . The major task of NPCs is the selective nucleocytoplasmic transport of macromolecules, i.e., proteins and RNAcontaining particles, a process involving dynamic interactions between the cargo-transport factor complexes and the phenylalanine-glycine (FG) repeats-harboring nucleoporins that lie within the central channel and the peripheral extensions of the NPC 9 . The stepwise assembly of nucleoporins to build complete NPCs proceeds through defined pathways, either following mitosis in conjunction with nuclear envelope reformation or during interphase, the unique assembly mode compatible with the closed mitosis of fungi. Nucleoporins themselves are essential players in NPC assembly, either through scaffolding or by mediating interactions with chromatin and/or membranes. In addition, non-NPC factors, such as membrane bending proteins, also contribute to NPC biogenesis 10 . While multiple studies have depicted the choreography of NPC assembly, together with their structural organization, little is known about the mechanisms that sustain the timely production of stoichiometric amounts of Nups or that could possibly sense and adjust NPC biogenesis depending on cell physiology. The high connectivity observed between NPCs and several biological processes could place them in a strategical position to communicate their status to the cell. Indeed, NPCs have been described to contribute to multiple aspects of transcriptional regulation, genome stability and cell cycle progression 9 . In some situations, these connections are mediated by physical interactions between NPCs and enzymes of the small ubiquitin-related modifier (SUMO) pathway 11 . Sumoylation is a post-translational modification that can modulate the binding properties or the conformation of its targets, ultimately impacting their stability, their localization or their biological activity 12 . Among the distinct enzymes of the sumoylation/desumoylation machinery shown to associate with NPCs, the conserved SUMO protease Ulp1 has essential functions in SUMO processing and deconjugation in budding yeast. The docking of this enzyme to the nucleoplasmic side of NPCs is essential for viability 13,14 and is believed to involve its nuclear import through karyopherins, followed by its association with several nucleoporins 15-19 . Proper NPC localization of Ulp1 has been shown to be critical for the spatio-temporal control of the sumoylation of certain targets, some of them being important for genetic integrity or gene regulation 13,16,20,21 .

Here, we report an original mechanism by which the synthesis of NPC subunits is regulated in response to changes in NPC integrity in budding yeast. We show that a subset of Nupencoding mRNAs is defined by the specific binding of the translational regulator Hek2. Hek2-regulated NPC mRNA translation and protein turnover are further shown to finely tune the levels of the corresponding nucleoporins. Strikingly, Hek2 binding to NPC mRNAs is prevented by sumoylation, a process reversed by the SUMO protease Ulp1. Mutant or physiological situations in which NPC functionality is compromised are associated with the loss of Ulp1 activity and the subsequent accumulation of sumoylated Hek2 versions that are inactive for NPC mRNA translational repression. We propose that Ulp1 and Hek2 are respectively the sensor and the effector of a feedback loop maintaining nucleoporin homeostasis.

Results

A unique mRNP composition for a subset of NPC mRNAs. In order to unravel novel mechanisms regulating NPC biogenesis, we systematically analyzed the association of Nup-encoding (NPC) mRNAs with different RNA-binding proteins (RBPs) in budding yeast. For this purpose, we took advantage of previously published large-scale datasets obtained through RNA immunoprecipitation (RIP) 22-25 , crosslinking immunoprecipitation (CLIP) 26 or crosslinking and analysis of complementary DNA (CRAC) 27 . We collected the association data for 39 NPC mRNAs (encoding Nups and NPC-associated proteins, Fig. 1a and Supplementary Fig. 1a) with a panel of 10 mRNA-associated factors involved in different stages of mRNA metabolism, including assembly into mRNP (Sto1), processing (Npl3, Nab4/Hrp1), nuclear export (Yra1, Nab2, Mex67), degradation (Xrn1, Ski2, Mtr4) or mRNA localization/translation (Hek2) (Fig. 1a). This analysis revealed that NPC mRNAs have generally the same typical features of expressed, protein-coding RNAs, e.g., they readily associate with mRNA export factors (Mex67, Nab2), but not with the non-coding RNA degradation machinery (Mtr4) (Fig. 1a, bottom right panel). Strikingly however, a small subset of NPC mRNAs (namely NUP170, NUP59, NUP188, NUP116, NUP100, NSP1 and NUP1) appeared to specifically bind the conserved Heterogeneous nuclear ribonucleoprotein K-like factor Hek2 (a.k.a. Khd1 28,29 ), a feature detected in four independent datasets (Fig. 1a, bottom left panel). The enrichment of certain NPC mRNAs among Hek2-bound targets appeared significant in a Gene Set Enrichment Analysis (P = 0.02) and was neither a mere consequence of the different expression levels of these particular transcripts (Supplementary Fig. 1b) nor a general feature of any multiprotein complexes, since it was not observed when similar analyses were performed for mRNAs encoding proteasome or exosome subunits (Supplementary Fig. 1c).

To further validate this finding in vivo, we immunoprecipitated a protein A-tagged version of Hek2 from yeast cells and analyzed its interaction with NPC mRNAs by reverse transcriptionquantitative polymerase chain reaction (RT-qPCR). In agreement with our previous findings, Hek2 preferentially associated with NUP59, NUP116, NUP100, NSP1 and NUP1 mRNAs (Fig. 1b), to a similar extent as its prototypal target ASH1 28,29 , but not with NUP133, NUP57 or NUP2 mRNAs (Fig. 1b), for which Hek2 binding was in the same range as its reported, unclear association to rRNA 27 . Preferential binding to NUP170 and NUP188 mRNAs was not confirmed, with the previous finding from genome-wide studies possibly reflecting their different expression levels in other genetic backgrounds. In contrast, immunoprecipitation of Hpr1, a subunit of the mRNP packaging THO complex, did not reveal any similar preferred association to a subset of NPC mRNAs (Supplementary Fig. 1d).

We then asked whether Hek2 was directly associating to this subset of NPC mRNAs (i.e., NUP59, NUP116, NUP100, NSP1 and NUP1), as expected from CLIP/CRAC studies 26,27 . To this aim, we first delineated Hek2-binding sites on these mRNAs by mining CLIP/CRAC data (Fig. 1c) and by searching their sequences for common motifs using the MEME software (Fig. 1c,d). This in silico approach revealed that these mRNAs share a common CA-rich motif (Fig. 1d), similar to the two previously reported Hek2-binding sites, i.e. (CNN) 6 24 and CAUCAUCA 26 . As anticipated from a previous study 26 , this motif was overlapping some but not all in vivo Hek2-binding peaks as defined by CLIP or CRAC, allowing us to define putative minimal bound domains in NSP1 and NUP116 mRNAs (Fig. 1c, gray bars). In an in vitro binding assay, synthetic biotinylated RNA probes encompassing these Hek2-binding sequences were further found to specifically pull down recombinant, purified Hek2 (Fig. 1e,f), but not a control protein (Supplementary Fig. 1e).

Altogether, our data establish that a direct association with the hnRNP Hek2 specifically defines a subset of NPC mRNPs. Notably, the five Hek2-bound NPC mRNAs are coding for FG-Nups, which are critical for nucleocytoplasmic transport 30 . Control mRNAs 1 2 3 4 5 6 7 8 9 10 11 12 13 1 2 3 4 5 6 7 8 9 10 12 13 14 14 1 2 3 4 5 6 7 8 9 10 11 12 13 1 2 3 4 5 6 7 8 9 10 12 13 14 14 1 2 3 4 5 6 7 8 9 10 11 12 13 1 2 3 4 5 6 7 8 9 10 13 14 14 1 2 3 4 5 A role for Hek2 in the metabolism of NPC mRNAs. We further investigated how Hek2 binding impacts the fate of these particular NPC mRNAs. While previous studies have revealed that Hek2 associates with an important fraction of the transcriptome, the consequences of this recruitment for mRNA metabolism have only been documented in a few situations where Hek2 binding can cause increased mRNA stability 24 , asymmetrical localization 28 or translational repression 26,29 .

To determine whether Hek2 binding influences the steadystate levels of NPC mRNAs, we first profiled the transcriptome of hek2Δ mutant yeast cells (Fig. 2a). Genome-wide, Hek2bound mRNAs showed a tendency to be less abundant upon Hek2 inactivation (Supplementary Fig. 2a), a trend not observed for Nab2-associated transcripts (Supplementary Fig. 2b), highlighting the sensitivity and the specificity of our analysis. However, NPC mRNAs levels were not significantly affected by the absence of Hek2, whether or not they associate with this factor (Fig. 2a). We then compared the localization of NPC mRNAs in wt and hek2Δ cells using single-molecule fluorescence in situ hybridization (smFISH; Fig. 2b). Detection of NSP1, NUP100 and NUP133 mRNAs using specific sets of probes revealed a punctuate, cytoplasmic localization for these Nup-encoding transcripts in wt cells (Fig. 2b, top panels). Upon HEK2 deletion, this random distribution, as well as the total number of detected RNA dots, were unchanged for both Hek2bound (NSP1, NUP100) and Hek2-unbound (NUP133) mRNAs (Fig. 2b, bottom panels). This set of data therefore establishes that Hek2 binding modulates neither the levels nor the localization of NPC mRNAs.

We then monitored the possible influence of Hek2 on NPC mRNA translation using polysome fractionation on sucrose gradients, which resolve free mRNPs and ribosomal subunits from translation-engaged mRNAs (Fig. 2c, Supplementary Fig. 2c). RT-qPCR analysis of the fractions of the wt polysome gradient revealed a bimodal distribution for Hek2-bound (Fig. 2d, Supplementary Fig. 2d, black lines) and Hek2-unbound (Fig. 2e, Supplementary Fig. 2e, black lines) NPC mRNAs. The largest fraction of NPC mRNAs migrated in the lightest fractions (#1-6), corresponding to free, untranslated mRNPs and resembling the pattern observed for the repressed ASH1 mRNA (Fig. 2d). A less abundant fraction of NPC mRNAs peaked with polysomecontaining fractions (#9-13), similar to the peak of the welltranslated ACT1 mRNA (Fig. 2e). Further analysis of the polysome profile from hek2Δ cells did not reveal any differences in the distribution of ribosomal species as compared to wt cells (Fig. 2c, Supplementary Fig. 2c). Strikingly, HEK2 inactivation decreased the amounts of translationally repressed Hek2-bound NPC mRNAs (Fig. 2d, gray arrows) and triggered their redistribution in the translated population, with a peak in heavy polysomes fractions (≥4 ribosomes/mRNA; Fig. 2d, red arrows). This behavior was similar to the one reported for the Hek2repressed ASH1 mRNA 29 (see also Fig. 2d) and was not observed for mRNAs which are not bound by Hek2 (e.g., NUP133 and ACT1, Fig. 2e).

Having established that Hek2 binding onto its NPC target mRNAs contributes to their maintenance in a translationally repressed state, we wondered whether it would affect the raw levels of their cognate nucleoporins. Notably, HEK2 inactivation, while increasing the fraction of translated NUP59, NUP116, or NUP1 mRNAs (Fig. 2d), did not trigger any drastic changes in the steady-state levels of the corresponding nucleoporins (see t = 0 in Fig. 2f). Since excess synthesis of subunits of multiprotein complexes can be buffered by increased protein turnover 6 , we monitored the half-lives of these nucleoporins in wt and hek2Δ cells. Strikingly, the degradation rates of the three nucleoporins, as estimated from cycloheximide chase experiments, were higher in the absence of Hek2 (Fig. 2f), revealing that the enhanced synthesis of nucleoporins is attenuated by their increased turnover in these mutant cells. Consistently, the kinetics of degradation of Nup133, whose translation is independent from Hek2 activity, was unaffected in hek2Δ cells (Fig. 2f). The raw levels of this subset of nucleoporins are thereby tightly controlled by both Hek2-mediated translational control and protein degradation.

The latter results suggested that Hek2 function might become crucial in conditions of disturbed proteostasis. To test this hypothesis, we combined HEK2 inactivation with MG132mediated inhibition of proteasomal degradation in drugsensitive yeast strains, and further analyzed the cellular localization of Nup1, whose overexpression was previously reported to give rise to lethality 31 . Strikingly, simultaneous inhibition of Hek2 and proteasome functions enhanced the formation of abnormal cytoplasmic foci of this nucleoporin in a small fraction of cells (Supplementary Fig. 2f). The fine-tuning of nucleoporin amounts mediated by Hek2 translational repression and proteasomedependent turnover can thereby be critical to prevent the accumulation of mislocalized NPC subunits.

Hek2 can be modified by SUMO. Having established that Hek2 can prevent excess Nup production, we then wondered whether regulatory mechanisms could reverse this repressing activity in response to an increased cellular demand for nucleoporins. Yck1mediated phosphorylation of Hek2 was previously reported to disrupt its association with the ASH1 mRNA at the bud cortex where this asymmetrically localized mRNA is targeted 29 . However, this plasma membrane-anchored kinase is unlikely to Fig. 2 Hek2-dependent translational repression and protein turnover define nucleoporin levels. a Transcriptome analysis of the hek2Δ mutant. The y-axis is the averaged log2 of the hek2Δ/wt ratios calculated from two independent microarray hybridizations. The x-axis is the log2 of the averaged fluorescence intensities. mRNAs encoding NPCs components are colored depending on their association to Hek2 (from Fig. 1). b Single-molecule FISH was performed on wt and hek2Δ cells using set of probes specific for the indicated mRNAs. NSP1 and NUP100 probes were coupled to the Quasar570 fluorophore (red), and NUP133 probes to Quasar670 (far red). The z-projections are displayed, together with merged images with a nuclear staining (DAPI). Scale bar, 5 µm. c Polysome fractionation from wt and hek2Δ cells (W303 background). The absorbance at 254 nm (A 254 ) recorded during the collection of the fractions of the gradient is displayed. The positions of 40S, 60S, 80S ribosomal species are indicated, as well as the number of ribosomes per mRNA in polysomes fractions. d Relative distribution of the indicated mRNAs in polysome gradients from wt (black lines) and hek2Δ (red lines) cells. mRNAs amounts in each fraction were quantified by RT-qPCR, normalized to the sum of the fractions and to the distribution of a control spike RNA. Gray arrows indicate a decrease in the amounts of mRNAs found in the light fractions in hek2Δ cells, while red arrows point to an increase in the quantity of mRNAs found in the polysomes fractions. These results are representative of four independent experiments (two performed in the W303 background, two in the BY4742 background; see Supplementary Fig. 2). e Same as (d) for NUP133 and ACT1 control mRNAs. f Protein levels of the indicated nucleoporins (Nup116, Nup1, Nup133) and of a GFP-tagged version of Nup59 were scored in wt and hek2Δ cells treated with cycloheximide (CHX) for the indicated time (min). Top, Whole-cell extracts were analyzed by western blotting using anti-GFP, anti-GLFG, anti-FSFG or anti-Nup133 antibodies. Bottom, The relative amounts of the indicated proteins (mean and individual points; n = 3) were quantified over the time following CHX treatment and expressed relative to t = 0 similarly target cytoplasm-localized NPC mRNPs (Fig. 2b). In view of the functional relationships between sumoylation and NPCs 11 and of the multiple examples of nucleic acid-binding proteins whose activity is controlled by SUMO 32 , we rather wondered whether Hek2 could be regulated by this modification.

To answer this question, cellular SUMO conjugates were purified by denaturing Ni 2+ chromatography from strains expressing a poly-histidine-tagged version of SUMO and the hemagglutinin (HA)-tagged version of Hek2 (Fig. 3a). This assay specifically detected slower-migrating species of Hek2 in the SUMO-conjugate fraction of cells co-expressing Hek2-HA and His-SUMO (Fig. 3b). Importantly, these modified Hek2 forms were not detected upon inactivation of the unique SUMOconjugating enzyme Ubc9 (Supplementary Fig. 3a). Conversely, these species accumulated in cells carrying a thermosensitive allele of the NPC-associated SUMO-protease Ulp1 (ulp1-333 33 , reported to disturb both Ulp1 activity and NPC localization, and thereafter referred as ulp1; Fig. 3c). This pattern was not observed upon inactivation of Ulp2, the alternative yeast SUMOdeconjugating enzyme localized in the nucleoplasm 18,34 (Supplementary Fig. 3b). Furthermore, modified species accumulating in the ulp1 mutant migrated slightly slower when they were purified from cells expressing doubly tagged His-Flag-SUMO (Supplementary Fig. 3c). Taken together, these data demonstrate the existence of SUMO-modified versions of Hek2 that are deconjugated by Ulp1 in a specific manner.

The apparent molecular weights of these Hek2 forms are compatible with mono-sumoylations occurring on distinct lysine residues. To identify their positions, we generated several plasmid-based hek2 mutants where multiple lysines were mutated to arginines to prevent SUMO conjugation without disturbing the charge of the protein (Supplementary Fig. 3d), and expressed them in hek2Δ cells. While mutations of all Hek2 lysines (K1-30R) completely abolished sumoylation, mutations of residues 19 to 30 (K19-30R), 25 to 30 (K25-30R) or 29/30 (K29-30R) were found to prevent the formation of most of the lower sumoylated version of Hek2 (Supplementary Fig. 3e,lanes 5,15,32,35), and mutations of lysines 8 to 18 (K8-18R), 13 to 18 (K13-18R) or 15 alone (K15R) strongly decreased its major upper sumoylation band (Supplementary Fig. 3e,lanes 4,13,22,24). Consistently, the K15R K29-30R combined mutant strongly reduced Hek2 sumoylation (Fig. 3d). Importantly, the turnover of Hek2 was unaffected in conditions where its sumoylation was enhanced (ulp1 cells) or decreased (hek2-K15 K29-30R cells), demonstrating that this modification does not regulate its stability (Supplementary Fig. 3f).

Hek2 binding to NPC mRNAs requires desumoylation by Ulp1. In order to determine whether Hek2 sumoylation could rather regulate its interaction with its target mRNAs, we combined the following approaches. First, we purified two different subsets of mRNPs from wt and ulp1 cells and analyzed their association with Hek2 (Fig. 3e). mRNPs were isolated using as baits either Cbc2, a subunit of the nuclear cap-binding complex (Cbc2-pA, Fig. 3f), or Mlp2, which anchors mRNPs to NPCs prior to nuclear export (Mlp2-pA, Fig. 3g) 35 . Strikingly, ULP1 loss of function triggered a clear decrease in the amounts of Hek2 recovered in both mRNP populations (Fig. 3f,g), while it did not affect the recruitment of canonical mRNP components such as the poly-A-binding protein Pab1, in agreement with our previous study 35 . Second, we specifically looked at the association of Hek2 with NPC mRNAs in wt and ulp1 cells through Hek2-pA immunoprecipitation followed by RT-qPCR. This assay further confirmed that ULP1 inactivation leads to a decrease in the association of Hek2 with its target mRNAs (Supplementary Fig. 3g).

These two experiments demonstrate that the SUMO protease Ulp1 is required for both Hek2 desumoylation and binding to NPC mRNAs, suggesting that this association could be directly repressed by SUMO. To further challenge this hypothesis, we went on to compare the binding of unmodified and sumoylated Hek2 to NPC mRNAs in a reconstituted in vitro assay (Fig. 3h). For this purpose, we first achieved the in vitro sumoylation of recombinant Hek2 in the presence of purified versions of the SUMO-activating enzyme (Aos1-Uba2), the SUMO-conjugating enzyme (Ubc9) and SUMO, partly reproducing the observed in vivo sumoylation pattern (Supplementary Fig. 3h, first lane). When further used in the in vitro RNA-binding assay, the sumoylated version of Hek2 was unambiguously less prone to bind RNA that its unmodified counterpart (Fig. 3i,j). Altogether, our data thereby establish that Hek2 sumoylation negatively regulates its association to NPC mRNAs and that Ulp1 desumoylating activity is required for optimal binding.

Compromised NPC integrity alters Ulp1 and Hek2 activities. The fact that the SUMO protease that controls the binding of Hek2 to NPC mRNAs is itself associated to nuclear pores prompted us to test whether it could be part of a feedback mechanism sensing NPC integrity and further modulating Nups biogenesis. We therefore asked whether mutant or physiological situations associated with defects in nuclear pore functions would result in changes in the activity of Ulp1 towards Hek2.

Mutants of distinct NPC subcomplexes, e.g., the outer ring Nup84 complex and the nuclear basket Nup60-Mlp1/2 complex, were previously shown to exhibit decreased levels of Ulp1 at the nuclear envelope 15,16 . To complement these findings, we systematically analyzed the localization of Ulp1 in ΔFG mutants in which the genetic removal of FG domains from specific nucleoporins leads to defects in nucleocytoplasmic transport, including karyopherin-dependent import 30 . In wt cells, the green fluorescent protein (GFP)-tagged version of Ulp1 exhibited a discontinuous rim-like staining of the nuclear periphery typical of its NPC-associated localization (Fig. 4a). In most ΔFG mutants however, the Ulp1-GFP nuclear envelope staining was Fig. 3 Hek2 sumoylation prevents its association to mRNAs. a Principle of the purification of sumoylated Hek2. Extracts from cells expressing a His-tagged version of SUMO were used for denaturing nickel chromatography. b-d Extracts from wt and HEK2-HA cells (b), HEK2-HA and HEK2-HA ulp1 cells (c) or HEK2-HA ulp1 and HEK2 K15R K29-30R-HA ulp1 cells (d) expressing or not His 6 -SUMO (+/-) were used for nickel chromatography. Total lysates ("Inputs") and purified His-SUMO conjugates ("Eluates") were analyzed by western blotting using anti-HA antibodies. The positions of the sumoylated and unmodified versions of Hek2-HA, as well as molecular weights, are indicated. Note the non-specific binding of a fraction of non-sumoylated Hek2-HA (also observed in the absence of His-SUMO, second lanes in (b, c)), a classical issue in SUMO-conjugates purification. e Principle of the mRNP purification procedure. Cbc2 or Mlp2 are purified through a protein-A tag, and the protein content of the associated mRNPs is analyzed by western blot. Note that RNAse A treatment experiments confirmed the RNA dependence of the interactions scored in such assays 35 . f, g Top, Soluble extracts ("Input", left panels) and Cbc2-pA-associated mRNPs (f) or Mlp2-pA-associated mRNPs (g) ("Eluate", right panels) isolated from wt and ulp1 cells were analyzed by immunoblotting using the indicated antibodies. Bottom, The relative amounts of Hek2 associated to Cbc2-and Mlp2-bound mRNPs are represented (mean and individual points; n = 3 for Cbc2-pA, n = 2 for Mlp2-pA). h Principle of the in vitro RNA-binding assay. i An in vitro sumoylation mixture containing both unmodified and sumoylated Hek2 was incubated with streptavidin beads either naive (Φ) or previously coated with biotinylated RNA probes encompassing Hek2-binding sites from NSP1 or NUP116 or a sequence from NUP133. Decreasing amounts of input and eluate fractions were loaded to allow quantification. j Percentages of IP are the ratios between unmodified (or sumoylated) Hek2 amounts in the eluate and in the input fractions and were calculated from (i). Means and individual points (n = 3) are displayed. Note that sumoylated Hek2 was not detectable (n.d.) and thereby not quantified on control pull downs. *P < 0. | DOI: 10.1038/s41467-018-03673-3 | www.nature.com/naturecommunications significantly reduced (Fig. 4a,b). This phenotype was unlikely to be caused by a reduction in the number of NPCs, according to a previous characterization of these mutants 30 , but rather reflected a decrease in the karyopherin-dependent import step that precedes Ulp1 anchoring at NPCs. Consistently, we did not observe this reduced Ulp1 staining in the nup1ΔFG mutant (Fig. 4a,b) which is unexpected to impair karyopherin function 30 .

To further characterize this phenotype, we pursued the analysis of the nsp1ΔFGΔFxFG mutant in which removal of the FG domains from a single nucleoporin is sufficient to decrease Ulp1 levels at the nuclear envelope (Fig. 4a,b). In agreement with the previously reported interdependence between Ulp1 NPC localization and stability 15,16 , western blot analysis of this nsp1ΔFGΔFxFG mutant further revealed a reduction in the total The bands that are modified in the nsp1ΔFGΔFxFG mutant are also typically altered in ulp1 cells (arrows). e Hek2 sumoylation was detected in wt and nsp1ΔFGΔFxFG cells as in Fig. 3. Total lysates ("Inputs") and purified His-SUMO conjugates ("Eluates") were analyzed by western blotting using anti-HA antibodies. The pattern of Hek2 sumoylation in ulp1 cells was analyzed as a control. The positions of the sumoylated and unmodified versions of Hek2-HA, as well as molecular weights, are indicated. f Hek2 sumoylation was similarly detected in wt cells, either untreated, or treated with 10% ethanol for 1 h amounts of cellular Ulp1 as compared to wt cells (Fig. 4c). Consistently, analysis of the global pattern of cellular SUMO conjugation in this same mutant highlighted a number of discrete changes, in particular the accumulation of high-molecular-weight SUMO conjugates, resembling those caused by ULP1 inactivation (Fig. 4d, arrows). We then wondered whether the changes in Ulp1 levels and activity detected in this mutant were sufficient to modulate Hek2 sumoylation. Remarkably, nsp1ΔFGΔFxFG cells exhibited a clear increase in the levels of sumoylated Hek2 (Fig. 4e). Loss of NPC integrity upon genetic alteration of several distinct NPC components can therefore impact the levels of active Ulp1, which is sufficient to trigger the accumulation of sumoylated, inactive versions of Hek2.

We finally asked whether physiological changes in NPC integrity could also lead to the accumulation of inactive Hek2 in wt cells. Environmental stresses can trigger changes in NPC integrity, as exemplified by the specific delocalization of certain NPC components, including Ulp1, upon exposition to elevated alcohol levels 36-38 . We then analyzed the sumoylation levels of Hek2 in wt cells exposed to ethanol stress (Fig. 4f). Strikingly, increased levels of sumoylated Hek2 were detected in this situation (Fig. 4f). Changes in NPC integrity, triggered by either genetic alterations or physiological changes, can thereby translate into the accumulation of inactive versions of Hek2.

Discussion

By combining the analysis of genomic data with in vivo and in vitro interaction assays, we have established that a subset of the mRNAs that encode the subunits of nuclear pores display a unique mRNP composition characterized by the binding of the hnRNP Hek2/Khd1 (Fig. 1). This conserved RNA-binding protein was previously reported to have various effects on the metabolism of its target mRNAs 24,26,28,29 , possibly reflecting coregulations involving other RBPs 39 , including the Hek2 paralog Pbp2/Hek1, or transcript specificities, as in the case of the budlocalized mRNA ASH1. Here, we show that Hek2 binding to Nup-encoding mRNAs affects neither their steady-state levels nor their subcellular localization (Fig. 2a,b), in contrast with other target mRNAs (Supplementary Fig. 2a-b) 28 . However, Hek2 binding appears to regulate the translation of NPC mRNAs. Indeed, upon HEK2 inactivation, the percentage of translated Hek2 target mRNAs increases and peaks with the heavy polysomes containing the most actively translating ribosomes, a phenotype that is not observed for control transcripts (Fig. 2d,e). In this frame, the regulation of NPC mRNAs is reminiscent of the one scored for ASH1 and FLO11, two mRNAs for which Hek2 binding represses translation initiation (Fig. 2d) 26,29 . In the case of the ASH1 transcript, it was demonstrated that Hek2 directly binds to the translation factor eIF4G1, likely constraining its initiation-promoting activity 29 , a mechanism of repression possibly also at play on NPC mRNAs. Notably, our study uncovers that in wt cells, these mRNAs distribute in two populations, one being actively translated and the other translationally repressed. Such a bimodal distribution is rather uncommon in yeast, in which whole-genome polysomal profiles previously revealed that most mRNAs are associated with translating ribosomes during exponential growth 40 , and likely indicates undergoing translational controls. However, it has to be noted that Hek2 binding is unlikely to be the only determinant of this particular translational regulation. Indeed, a large fraction of each Hek2-bound mRNAs (e.g., NSP1 and NUP1, Fig. 2d) remains untranslated in the absence of Hek2. In addition, the NPC mRNAs that are not among Hek2 preferred targets (e.g., NUP133, Fig. 2e) also exist for the most part in a translation-inactive fraction. Whether alternate RBPs, specific for distinct subsets of NPC mRNAs, or other layers of regulations also partake in the fine-tuning of the translation of these transcripts remains to be investigated.

While Hek2 represses NPC mRNA translation, protein turnover also contributes to the definition of the cellular levels of nucleoporins. Indeed, excess Nups likely synthesized in the absence of Hek2-dependent translational repression appear to be buffered by an increase in their degradation rates (Fig. 2f). This mechanism is reminiscent of the post-translational attenuation described to occur for multiprotein complex subunits when they are naturally produced in super-stoichiometric amounts 7 , or overexpressed due to genomic amplification 6 . Excess subunits of NPCs, which do not assemble into stable complexes and could be possibly unfolded, are thereby expected to undergo increased ubiquitin-dependent, proteasome-mediated degradation. Several conserved ubiquitin ligases are susceptible to partake in this process, including (i) Hul5 and San1, which recognize misfolded proteins in the cytoplasm and the nucleus, respectively 41,42 ; (ii) Tom1, which couples ubiquitin to unassembled ribosomal proteins 43 ; or (iii) any yet-to-be characterized quality control factor specialized in the degradation of orphan polypeptides, as recently identified in mammals 44 . The fact that the cellular concentration of Hek2-regulated nucleoporins such as Nup59, Nup1 and Nup116 is tightly restricted by both translational repression and protein degradation suggests that their accumulation could be detrimental, with these hydrophobic proteins being potentially prone to form toxic aggregates. Consistently, we found that Nup1 can form cytoplasmic foci when Hek2 and proteasome functions are inhibited (Supplementary Fig. 2f), and overexpressed Nup59 was similarly reported to accumulate within cytoplasmic structures 45 . Interestingly, overproduction of Nup170, a direct partner of Nup59, was described to trigger the formation of cytoplasmic foci containing distinct unassembled NPC subunits 46 , suggesting that these excess, mislocalized nucleoporins might also interfere with the NPC assembly process.

In agreement with the physiological importance of such Hek2mediated regulations, it is not surprising that the activity of this protein is itself under control. We found that sumoylation of Hek2 occurs on two different domains, thus generating two distinct monosumoylated versions of the protein (Fig. 3b-d, Supplementary Fig. 3d,e). Both modified regions are located at the vicinity of the third K-homology (KH) domain (Supplementary Fig. 3d), the major RNA-interacting motif of the protein 24 , providing a possible molecular rationale for the SUMO-mediated decrease in RNA binding scored in vivo (Fig. 3f, g, Supplementary Fig. 3g) and in vitro (Fig. 3i,j). In this respect, inhibition of RNA recognition could be caused by steric hindrance, as already reported for several sumoylated DNA-or RNA-binding proteins 32 , or, alternatively, occurs through changes in the oligomerization status of the protein, as proposed in the case of human hnRNP C1 47 . Furthermore, the spatio-temporal control of Hek2 function is likely to depend on a combination of post-translational modifications including, besides its sumoylation, its reported phosphorylation by Yck1 29 and its ubiquitination detected in proteome-wide analyses 48 . Notably, Hek2 sumoylation appears to have significant effects at low stoichiometry, a paradox commonly observed for SUMO targets 12 . However, the real stoichiometry of Hek2 sumoylation may be under-estimated in view of the intrinsic difficulty to preserve this labile modification 49,50 . Alternatively, transient sumoylation may promote permanent changes in Hek2 association with RNA or yetto-be identified protein partners that would be maintained after removal of the modification, as already shown for other factors 51 . Finally, the stoichiometry of sumoylation may be much greater for the small pool of Hek2 actually involved in RNA binding. In support of this last hypothesis, Hek2 recruitment onto mRNAs primarily occurs prior to nuclear export, as shown by its association with nuclear, partly unprocessed mRNPs (Fig. 3f,g) 27 ; this Hek2 population, a minor fraction of this predominantly cytoplasmic protein (Supplementary Fig. 4a), would be the only one targeted by the nuclear sumoylation machinery 18 . Desumoylation by Ulp1 could then favor its binding onto mRNAs at the nucleoplasmic side of NPCs (Supplementary Fig. 4b). The cytoplasmic fate of certain mRNPs would then be determined prior to export, as in the case of ASH1 whose asymmetrical localization and translation depends on Hek2 binding. This molecular mechanism could also explain why ASH1 asymmetry requires Nup60 52 , since this nucleoporin is one of the major determinants of Ulp1 stability at NPCs 15,16 .

The control of Hek2 function through Ulp1-mediated desumoylation is also likely to adjust its RNA-binding activity in response to the status of nuclear pores in the cell. Since several distinct nucleoporin subcomplexes are indeed required to position and stabilize Ulp1 at the pore (Fig. 4a, b) 15,16 , the level of activity of this SUMO protease provides a readout for the number and the functionality of NPCs. Consistently, changes in NPC composition in mutant or perturbed physiological situations impact Ulp1 activity and trigger the accumulation of sumoylated, inactive versions of Hek2 (Fig. 4e,f). In view of the function of Hek2 in controlling NPC mRNA translation (Fig. 2), this could in turn result in the increased synthesis of nucleoporins in a feedback process (Supplementary Fig. 4c). Their recruitment into NPCs would then compete their proteasomal degradation and contribute to restore NPC integrity. Strikingly, some of the nucleoporins that are targeted by this mechanism appear to be the most limiting ones for completing fully assembled NPCs (Supplementary Fig. 4d). Among them, Nsp1 is also critical to define NPC number during the asymmetric division of budding yeast 53,54 . While the pathway described here could indeed connect the cellular availability of specific nucleoporins to the status of NPCs, other quality control mechanisms are known to control NPC homeostasis. In yeast, aberrant NPC assembly intermediates are cleared from the nuclear envelope by the activity of ESCRT-III/Vps4 complexes 55 , while in mammals, defects in the assembly of nuclear pore baskets triggers a cell cycle delay 56 .

Localization of SUMO proteases at NPCs has been conserved in all eukaryotes 11 and also involves several distinct NPCassociated determinants in mammalian cells 57,58 . Sumoylation of KH domain containing Hek2 orthologs such as hnRNP K, hnRNP E1 and hnRNP E2 has also been reported 59-61 . Strikingly, hnRNP K desumoylation involves SENP2, the NPC-localized ortholog of Ulp1 in mammals 62 . In view of the association between hnRNP K and a subset of NPC mRNAs in a genomewide survey of human RBPs 63 , the conservation of the pathway described here will certainly deserve further investigation.

Methods

Yeast strains and plasmids. Unless otherwise indicated, all the strains used in this study (listed in Supplementary Table 1) are isogenic to BY4742/BY4741 and were grown in standard culture conditions. Experiments using the ulp1 allele were performed at semi-permissive temperature (30 °C) as previously described 35 . Experiments with the ubc9 thermosensitive mutant were performed following 2 h of shift at 37 °C. When indicated, cycloheximide (0.1 mg per ml, Sigma), MG132 (100 µM, Sigma) or ethanol (10% v/v) were added to the medium for the indicated time. Drug-sensitive erg6Δ strains were used for MG132 treatment 16 . Construction of plasmids (listed in Supplementary Table 2) was performed using standard PCRbased molecular cloning techniques and was checked by sequencing.

Bioinformatic analysis of RNA immunoprecipitation datasets. RIP, CLIP or CRAC data were collected for the following RNA-binding proteins: Yra1 (RIP followed by microarray analysis, one replicate 22 ), Nab2 (CRAC, three replicates 27 ), Npl3 (RIP followed by microarray analysis, one replicate 23 ), Nab4/Hrp1 (RIP followed by microarray analysis, one replicate 23 ), Mex67 (CRAC, three replicates 27 ), Sto1 (CRAC, three replicates 27 ), Xrn1 (CRAC, two replicates 27 ), Ski2 (CRAC, four replicates 27 ), Mtr4 (CRAC, three replicates 27 ) and Hek2 (CRAC, one replicate 27 ; CLIP, one replicate 26 ; RIP followed by microarray analysis, one replicate in two distinct studies 24,25 ). For each dataset, all protein-coding RNAs were ranked and given a color according to their relative binding to the corresponding RBP. Scores available from microarray or sequencing analyses 22-25 were used to split the RNAs in four equally sized groups corresponding respectively to "high" (light yellow), "medium" (dark yellow), "low" (dark blue) and "very low/no" (light blue) binding. CLIP data were used to define bound (light yellow) and unbound (light blue) mRNAs according to the published peak calling analysis 26 . CRAC hits were first normalized by hits per million within each RBP CRAC dataset, then for each mRNA (∑i 2 = 1) to account for differences in mRNA abundances, and scaled to occupy the 0-1 range. Colors ranging from light blue (0) to light yellow (1) were used to depict the binding of a given mRNA to a RBP. Binding categories were further displayed for NPC mRNAs (Fig. 1a) or proteasome/exosome RNAs (Supplementary Fig. 1c). Gene set enrichment analyses were performed as previously described 64 . The MEME software (v4.11.3) 65 was applied to the sequences of NUP59, NUP116, NUP1, NSP1 and NUP100 mRNAs. Out of 6 retrieved motifs, 5 corresponded to FG-coding sequences, while one, found with an e-value of 4.8e-7, matched the known Hek2-binding site (Fig. 1d).

mRNP and RNA immunoprecipitation. Cbc2-pA-and Mlp2-pA-associated mRNPs complexes were purified as previously described 35 : cells were lysed by bead beating using a Fastprep (Qbiogene) in the following extraction buffer: 20 mM Hepes pH 7.5, 110 mM KOAc, 2 mM MgCl 2 , 0.1% Tween-20, 0.5% Triton X-100, 1 mM dithiothreitol (DTT), 1× protease inhibitors cocktail, complete EDTA-free, Roche, and antifoam B, Sigma, 1:5000. After 10,000 × g centrifugation at 4 °C for 5 min, the soluble extract was incubated with IgG-conjugated magnetic beads for 10 min at 4 °C. Beads were washed 3 times with extraction buffer and eluted with sodium dodecyl sulfate (SDS) sample buffer.

Hek2-pA-associated mRNA purifications were performed according to the same procedure in the presence of RNAsin (Promega, 40 U per ml of buffer). Hpr1 RNA immunoprecipitation was performed as previously described 35 : cells were crosslinked with 1% formaldehyde for 10 min at 25 °C. Cells were further lysed by bead beating in the following lysis buffer: 50 mM Hepes pH 7.5, 140 mM NaCl, 1 mM EDTA, 1% Triton X-100, 0.1% deoxycholate, 1× protease inhibitors cocktail, complete EDTA-free, Roche. Soluble extracts were recovered following centrifugation at 10,000 × g for 5 min at 4 °C and immunoprecipitated overnight at 4 °C in the presence of anti-Hpr1 antibodies 35 . Immuno-complexes were captured on protein-G sepharose beads (GE Healthcare) and washed as follows: twice with lysis buffer, twice with lysis buffer containing 360 mM NaCl; twice with 10 mM Tris pH 8, 250 mM LiCl, 0.5% Nonidet-P40, 0.5% deoxycholate, 1 mM EDTA and once with 10 mM Tris-HCl pH 8, 1 mM EDTA. Elution was achieved through 20 min of incubation at 65 °C in the presence of 50 mM Tris pH 8, 10 mM EDTA, 1% SDS. The eluate was deproteinized with proteinase K (Sigma, 0.2 mg per ml) and uncrosslinked for 30 min at 65 °C. Total and immunoprecipitated RNAs were purified with the Nucleospin RNAII kit (Macherey Nagel) and reverse transcribed with Superscript II reverse transcriptase (Life Technologies). cDNAs were further quantified by real-time PCR with a LightCycler 480 system (Roche) according to the manufacturer's instructions. The sequences of the primers used for qPCR in this study are listed in Supplementary Table 3. Controls without reverse transcriptase allowed estimating the lack of contaminating DNA.

Polysome profiling analysis. The protocol was adapted from a published procedure 40 . A total of 100 ml cultures were grown in YPD media to midlog phase (OD 600 = 0.4-0.6). Prior to harvest, cycloheximide (CHX) (Sigma) was added to final a concentration of 0.1 mg per ml. All subsequent procedures were carried out on ice with pre-chilled tubes and buffers. Cultures were cooled on ice and pelleted by centrifugation at 2600 × g for 5 min at 4 °C. Pellets were washed twice in 2.5 ml of ice-cold lysis buffer (20 mM Tris-HCl pH 8, 140 mM KCl, 1.5 mM MgCl 2 , 1% (v/v) Triton X-100, 0.5 mM DTT, 0.1 mg per ml CHX and 1 mg per ml heparin), resuspended in 0.7 ml of ice-cold lysis buffer and lysed by bead beating using a Fastprep (Qbiogene, 3 × 30 s). Cell debris and glass beads were removed by centrifugation at 2600 × g for 5 min at 4 °C. The supernatant was transferred to a 1.5 ml tube and clarified by centrifugation at 10,000 × g for 10 min at 4 °C. 10 A 254 units of extract were layered onto an 11 ml 20-50% (wt/vol) sucrose gradient prepared in the lysis buffer without Triton X-100. The samples were ultracentrifuged at 39,000 × g for 2.5 h at 4 °C in a SW41 rotor. The gradients were fractionated in 14 fractions of 0.9 ml using an ISCO fractionation system with concomitant measurement of A 254 . Total lysates and fractions were supplemented with 50 µl of 3 M NH 4 Ac, 5 ng of Luciferase RNA (Promega), 1 µl of Glycoblue (Ambion) and 1.2 ml of ethanol. Samples were vortexed and precipitated overnight at -20 °C. The pellets were collected by centrifugation at 10,000 × g for 10 min at 4 °C, washed once in 75% ethanol and resuspended in 100 µl DEPC-treated H 2 O. RNAs were further purified using the Nucleospin RNAII kit (Macherey Nagel) following the RNA clean-up procedure. Equal volumes of all samples were reverse transcribed with Superscript II reverse transcriptase (Life Technologies) and cDNAs were further quantified by real-time PCR as described above.

Recombinant protein production. His and GST fusion proteins were expressed in Rosetta (DE3) Escherichia coli cells transformed with the corresponding plasmids and grown in LB medium supplemented with the required antibiotics. Expression of the recombinant proteins was achieved by submitting bacterial cultures to cold and chemical shocks (4 °C, 2% ethanol), and inducing them with 0.2 mM isopropyl-β-D-thiogalactopyranoside at 23 °C for 4 h. Bacterial pellets were collected by centrifugation and frozen in liquid nitrogen. Pellets were resuspended either in His buffer (20 mM Na 2 HPO 4 pH 7.5, 500 mM NaCl, 10 mM imidazole, 0.2% (v/v) Triton X-100, 1 mM MgCl 2 , 1× protease inhibitors cocktail, Roche) or GST buffer (50 mM Tris-HCl pH 7.5, 0.1% (v/v) Triton X-100, 10 mM KCl, 10% glycerol, 1 mM DTT, 1× protease inhibitors cocktail, Roche), treated with 0.5 mg per ml lysosyme for 1 h at 4 °C and lysed by sonication. His-tagged proteins were further solubilized by adding 0.5% Sarkosyl for 15 min at 4 °C, followed by the addition of 0.8% Triton X-100. Lysates were cleared by centrifugation at 10,000 × g for 20 min at 4 °C. His-tagged proteins were purified on Ni-NTA agarose (Qiagen) for 2 h at 4 °C. Beads were then washed twice with His buffer and eluted four times with the same buffer containing 500 mM imidazole and 1% Triton X-100. GST fusion proteins were purified in the presence of 550 mM NaCl on Gluthatione sepharose (GE Healthcare) for 1 h and 30 min at 4 °C. Beads were then washed three times with GST buffer containing 500 mM NaCl, and eluted four times for 15 min in 50 mM Tris-HCl pH 8, 500 mM NaCl, 0.1% (v/v) Triton X-100, 10% glycerol and 15 mM gluthatione. Following purification, His and GST fusion proteins were dialyzed overnight at 4 °C against 20 mM Hepes KOH pH 7.9, 0.1 M KCl, 0.1 mM DTT, and 10% glycerol was added before storage at -80 °C.

In vitro RNA-binding assay. In vitro RNA-binding assays were performed according to a published procedure 66 Beads were then incubated in protein-binding buffer containing 1 mg per ml heparin and ~2 pmol of recombinant Hek2 for 30 min at 4 °C. Beads were then washed five times with protein-binding buffer containing 1 mg per ml heparin and eluted in SDS sample buffer.

Sumoylation assays. SUMO conjugates were isolated from yeast cells expressing a His-tagged version of SUMO using nickel agarose denaturing chromatography as previously described 35 : 100 OD 600 of cells were lysed by bead beating in 6 M guanidine HCl, 100 mM sodium phosphate pH 8, 10 mM Tris-HCl, 0.1% Triton X-100, 10 mM beta-mercaptoethanol and 50 mM N-ethylmaleimide (Sigma). Clarified lysates were incubated with Ni-NTA agarose beads (Qiagen) for 2 h at room temperature. Beads were washed twice with lysis buffer and three times with 8 M urea, 100 mM sodium phosphate, 10 mM Tris-HCl pH 6.3 before proceeding to elution in 8 M urea, 200 mM Tris-HCl pH 6.8, 1 mM EDTA, 5% (w/V) SDS, 0.1% (w/v) bromophenol blue and 1.5% (w/v) DTT.

In vitro sumoylation was performed as previously reported 50 : briefly, 3 μg of recombinant Hek2 was mixed with 300 nM of recombinant E1 enzyme (Aos1/ Uba2), 700 nM of recombinant E2 enzyme (Ubc9) and 10 mM of a mutated version of Smt3 (K11,15,19 R) less prone to form poly-SUMO chains, in the presence of 5 mM adenosine triphosphate in a sumoylation buffer (50 mM Bis-Tris pH 6.5, 100 mM NaCl, 10 mM MgCl 2 and 0.1 mM DTT). The reaction was then incubated for 3 h at 37 °C and either stopped by addition of SDS sample buffer or further used for in vitro RNA-binding assays.

Protein extraction and western blot analysis. Total protein extraction from yeast cells was performed by the NaOH-TCA lysis method 49 . Samples were separated on 10% or 4-12% SDS-polyacrylamide gel electrophoresis (SDS-PAGE) gels and transferred to nitrocellulose or polyvinylidene difluoride membranes. Western blot was performed using the following, previously validated antibodies: polyclonal anti-GLFG 67 (to detect Nup116), 1:500; polyclonal anti-FSFG 68 (to detect Nup1), 1:4000; polyclonal anti-Nup133 69 , 1:500; monoclonal anti-Pab1 (clone 1G1, sc-57953, Santa-Cruz), 1:1000; polyclonal anti-SUMO 70 Gene expression analyses. Total RNAs were extracted from yeast cultures using Nucleospin RNAII (Macherey Nagel). Reverse transcription and cDNA quantification were performed as described above for RNA immunoprecipitation. Transcriptome analysis was achieved using microarrays as previously reported 35 : the hek2Δ versus wt comparison was performed twice using independent samples and dye swap. The averaged log2 of the mutant/wild-type ratios and the standard deviation between the two replicates were calculated for each gene. The genes showing a standard deviation of >0.5 were removed from the dataset. Comparisons of hek2Δ transcriptome with Hek2 and Nab2 binding profiles were realized using published datasets 23,24 . Transcripts were split in four equally sized groups corresponding respectively to "strong", "medium", "low" and "very low/no" binding. For each category, the log2 of the mutant/wild-type ratios of the different transcripts were represented as a box plot.

Cell imaging. The smFISH was carried out on fixed cells using Stellaris Custom Probe Sets and RNA FISH buffers, according to the manufacturer's instructions (Biosearch Technologies). For Hek2-GFP localization, cells were fixed with 0.1 M KPO 4 pH 6.4, paraformaldehyde 4% for 15 min and nuclei were stained with 4,6diamidine-2-phenylindole (DAPI). Nup1-GFP and Ulp1-GFP localization was analyzed on live cells. Wide-field fluorescence images were acquired using a DM6000B Leica microscope with a 100×, NA 1.4 (HCX Plan-Apo) oil immersion objective and a CCD camera (CoolSNAP HQ; Photometrics). Z-stack sections of 0.2 μm were acquired using a piezo-electric motor (LVDT; Physik Instrument) mounted underneath the objective lens. Images were scaled equivalently and 3Dprojected using ImageJ, and further processed with Photoshop CS6 13.0 ×64 software (Adobe). Nuclear envelope intensities were determined with ImageJ following subtraction of the cytoplasmic background.

Statistics. The experiments were not randomized and the investigators were not blinded to allocation during experiments and outcome assessment. No statistical methods were used to predetermine sample sizes; (n) values were chosen in accordance with standard practices in RNA analyses in yeast, correspond to the number of biological replicates (e.g., independent yeast cultures) and are indicated in the corresponding figure legends. Error bars correspond to standard deviations. The two-tailed Welch's t-test, which allows unequal variance, was used to compare RNA-binding efficiencies in vitro or in vivo (Figs. 1f and3j; Supplementary Fig. 3g). The Mann-Whitney-Wilcoxon test was used to compare Ulp1 nuclear envelope intensities in different strains (Fig. 4b) and RNA expression fold changes upon HEK2 deletion (Supplementary Fig. 2a,b). Standard conventions for symbols indicating statistical significance were used: *P ≤ 0.05; **P ≤ 0.01; ***P ≤ 0.001; N.S., not significant.

III.Conclusion and perspectives

Regulation of translation plays a crucial role in gene expression. The objective of this thesis work has been to characterize new layers of regulation of translation: we characterize the role of Angel1, we uncovered a novel role for the yeast RNA binding protein Hek2 and finally we performed the first translatome analysis of human pancreatic β-cell upon glucose stimulation.

Discussion and perspective chapter 1: Functional characterization of an eIF4E interacting protein: Angel1

In the first chapter of my results, I characterized Angel1 functional role in Hela cells by showing its specific localization at level of the ER, which is mediated by the N-terminus. We showed that Angel1 does not colocalize neither with stress granules nor with known marker of the Pbodies. Moreover, we couldn't detect any deadenylase activity for Angel1 protein complex.

Accordingly, transcriptome analysis of Angel1 knock down cells showed that most of the identified targets have decreased mRNA levels that argues against its putative deadenylase function. Considering these results, we can conclude that Angel1 lost its deadenylase activity and is not involved in the mRNA decay pathway. Analysis of the mRNAs whose abundance is affected by Angel1 knock-down indicated that the majority codes for membranous proteins or secreted proteins and we can therefore speculate that they are translated by ER bound ribosomes.

Then, since Angel1 has been shown to interact with the cap binding protein eIF4E we investigated whether Angel1 downregulation affected the translation of a subset of mRNA. By Ribosome profiling we identified a set of genes whose translation is regulated by Angel1. As future perspective, validation of the identified genes is needed. The strategy to validate these mRNA could be at mRNA level by measuring their association with the polysomal fraction by polysome profiling. Moreover, we could assess, by cell fractionation, their site of translation: ER associated or cytosolic [START_REF] Jagannathan | De novo translation initiation on membrane-bound ribosomes as a mechanism for localization of cytosolic protein mRNAs to the endoplasmic reticulum[END_REF].

To identify Angel1 targets we adopted RIP seq strategy in which we precipitated exogenous Halo-tagged proteins. We validated that this approach is able to purify known targets for CELF1 a well-studied RBP. Despite the low quantity of available reads we could identify mRNAs enriched for Angel1 and its mutated form A1-YA.

Analysis of the mRNA features, of the possible common binding sites for RBPs or miRNA on the identified targets of the three datasets will help to describe Angel1 mRNP function.

Discussion and perspective chapter 2: Translatome analysis of glucose stimulated human pancreatic β-cells Pancreatic β cells play a central role in glycemic regulation. The role of glucose on insulin secretion and gene expression has been widely addressed in rodent model at transcriptome, traductome [START_REF] Greenman | Distinct glucosedependent stress responses revealed by translational profiling in pancreatic -cells[END_REF] and proteome (Waanders et al., 2009) levels, while in human β cell lines or islets from human donor, there is scarce data available and until now describing only the regulation at a transcriptome level [START_REF] Richards | MondoA Is an Essential Glucose-Responsive Transcription Factor in Human Pancreatic β-Cells[END_REF] where only mild effects were observed. For these reasons we performed the first translatome study on a human β cell line, EndoC-βH2, able to secrete insulin upon glucose stimulation [START_REF] Scharfmann | Development of a conditionally immortalized human pancreatic β cell line[END_REF]. We identified 525 genes whose mRNA levels in the polysomal fraction were affected. We have identified two genes, chromogranin A and ICA512 as glucose responsive at the translation level. We found no differences in translation rates of other genes involved in this pathway contrary to what was previously shown in rodent models. Importantly, in our hands, translation of chromogranin A decreases while in rodents it was previously reported to increase in response to glucose stimulation. Chromogranin A intracellular role is to selectively sort proteins into secreted granules while when secreted it is cleaved in different peptides that function in autocrine and paracrine way to regulate cellular processes (Herold et al., 2018). Among these peptides, pancreastatin have been shown to regulate glucose-stimulated and un-stimulated insulin secretion. Validation of down regulation of synthesis could be performed by a slight modification of the SunSET technique: after the incubation of the samples with puromycin it is possible to perform puromycin immunoprecipitation using specific antibodies.

Analysis by western blot of chromogranin A precipitated in the two samples in either high glucose or low glucose condition could be a valid strategy for validation. Nonetheless, we can discuss the effects of such phenotype. For example, intracellular decrease of chromogranin A would cause a decrease number of secreting granules and of the efficiency to form them, which it is surprising since cells would need more chromogranin A to restore the pools of secreted insulin. In this analysis, we focused mainly on genes closely related to the insulin maturation pathway but other events are equally important during insulin secretion (reviewed in (Rorsman and Braun, 2013). Thus, further investigations are needed to understand exactly which genes and pathways are readily upregulated at translational level in response to glucose to adapt the proteome to the increased request in insulin secretion.

To analyze the generated data focusing more on translation regulation we then associated specific mRNA features to their translational changes in the three different fractions. We have shown that genes with similar behavior do also have similar mRNA features. One of the most prominent cluster we identified was enriched in TOP mRNAs containing ribosomal proteins.

An intriguing question is why we do not find all the ribosomal proteins in our differentially translated list and why some showed stronger regulation than others. An interesting concept of the last years is the existence of specialized ribosome, in different cell types, with distinct protein composition and different protein interacting with the ribosome could explain our questions. Importantly, in our study we found upregulated by glucose mRNAs coding for proteins important for ER ribosome targeting and translation such as the component of heterodimeric nascent polypeptide associated complex (NAC), consisting of NACA and BTF3 [START_REF] Zhang | NAC functions as a modulator of SRP during the early steps of protein targeting to the endoplasmic reticulum[END_REF]. In conclusion, I think that this work amplifies our knowledge of regulation gene expression by glucose both regarding β cells and translation regulation.

Discussion and perspective chapter 3: A novel RNA regulon: Hek2 regulates translation of Nuclear Pore Proteins Hek2 is a conserved RNA binding protein and the most related mammalian orthologs are the mammalian heterogeneous nuclear ribonucleoprotein K (hnRNP K), hnRNP E1 and hnRNP E2. Hek2 have been also shown to have different effect on the fate of its targets mRNAs probably depending on the mRNP composition. In this published article we showed that hek2 is part of the mRNPs of a subset of the mRNAs coding for the components of the nuclear pore complex (Nups). We showed that the affinity of hek2 for these targets is regulated by sumoylation that inhibits the binding to these mRNAs. We showed that hek2 does not regulate their localization nor their stability as previously shown for other targets (Irie, 2002) (Ito et al., 2011). Instead, hek2 causes a translation repression in a similar manner to the one observed for ASH1 and FLO11 mRNAs [START_REF] Wolf | Feed-forward regulation of a cell fate determinant by an RNAbinding protein generates asymmetry in yeast[END_REF]. Interestingly, Paquin and colleagues showed that hek2 interacts with C-terminal domain of eIF4G1 (Paquin et al., 2007) and thus likely limiting the eIF4F complex activity. Whether this regulation is also valid for the Nups mRNAs could be interesting to investigate.

Another important phenotype that we highlighted during the polysome profile experiments of Hek2 depleted cells, was the formation of polysome half-mer (small peak on right side of some of the polysome peaks) in one of the two yeast strain tested (see annexes, figure 2c in the supplementary material of the article "A SUMO-dependent feedback loop senses and controls the biogenesis of nuclear pore subunits"). Half-mers indicate the presence of a small ribosomal subunit (40S) waiting for the large subunit (60S) joining. In our case half-mer were detectable from the peak corresponding to monosomes (80S) until the second polysome (3 ribosome associated to the mRNA). This phenotype is typically associated to defect in the ribosome biogenesis and assembly pathways (Li et al., 2009). Since this phenotype was prominent only on one of the two strain it suggests the dependency on the genetic background specific for this strain.

Nonetheless, it is tempting to speculate that half-mer formation could be related to Hek2-eIF4G interaction. We can propose a model where absence of Hek2 would increase the efficacy of the eIF4F complex thus enhance translation initiation of those mRNA that are normally kept in a silenced state by Hek2. Moreover, eIF4A interacts with eIF4G by two binding sites one at the C-terminal domain while the other is found in the central domain. Since also Hek2 interacts with eIF4G terminal domain we can hypothesized that Hek2 displaces eIF4A from the eIF4F complex thus forming a specialized cap-binding complex that repress efficiently translation initiation.

Next by performing RT-qPCR on the polysome profile fractions we showed that in Hek2 depleted cells, only a part of the mRNA found in the non-translating fractions of the polysome gradient shifted towards those containing highly translating polysome. Moreover, also Nups mRNAs not bound by hek2 showed similar mRNA distribution. Such bimodal distribution is uncommon in yeast exponentially growing [START_REF] Arava | Genome-wide analysis of mRNA translation profiles in Saccharomyces cerevisiae[END_REF]). An explanation of such behavior could be the presence of other layers of post-transcriptional regulation that allow only a part of the Nups mRNA to be available for translation.

One example of a similar bimodal distribution have been reported in the human PC-3 cell line for the ribosomal protein L4 (RPL4) [START_REF] Thomas | Identification of mRNAs that continue to associate with polysomes during hypoxia[END_REF] which is a known TOP-mRNAs. Dysregulation of the stoichiometric imbalance of the subunits of the nuclear pore complex could cause of aberrant phenotypes. Indeed, we also shown that, the imbalance caused increase of translation of Hek2 targets in Hek2 depleted cells is quickly counteracted by decrease in the half-life of the coded proteins underline their increase in protein degradation.

In conclusion, human hek2 orthologs have been shown to be also sumoylated and their desumoylation involves SENP2, the human ortholog of the yeast ulp1, which we have shown to be responsible for hek2 de-sumoylation. Thus, as perspective, would be interesting to investigate if this feedback loop that senses nuclear pore integrity is conserved in humans. This study (j) pET21b-His-UBC9 AmpR/His-UBC9 (for recombinant protein production) 18 pET11-His-UBA2 AmpR/His-UBA2 (for recombinant protein production) 18

Supplementary

pET-His-AOS1 KanR/His-AOS1 (for recombinant protein production) 18 pET21b-His-SMT3 AmpR/His-SMT3 (for recombinant protein production) 18 pET21b-His-SMT3 K11-15-19R AmpR/His-SMT3 K11- 15-19R (for recombinant protein production) This study (k)

Supplementary Table 2 (continued)

a. A genomic fragment encompassing HEK2 CDS ± 500bp was amplified from pGP564-ChromosomeII-152618-169095 and subcloned within pRS316. b. A genomic fragment encompassing the HEK2-3HA allele was amplified from the HEK2-3HA strain and subcloned within pRS316. c. The prot-A tag was amplified from pBXA and cloned in between AscI-PacI sites of pRS316-HEK2-3HA. d. A PCR fragment encompassing HEK2 CDS was amplified from pRS316-HEK2-3HA and cloned in between NcoI-XhoI sites of pET28b+. e. The TRP1 marker was swapped by homologous recombination with a disruption fragment from pTL7. This plasmid encodes a His-tagged version of Smt3 (yeast SUMO) under the control of the copper-inducible CUP1 promoter. f. The URA3 marker was swapped by homologous recombination with a disruption fragment from pUL9. This plasmid encodes a His-Flag doubly-tagged version of Smt3 under the control of the galactose-inducible GAL1/10 promoter. g. A genomic fragment encompassing the UBC9 complete CDS (+/-500bp) was PCR-amplified form yeast genomic DNA and cloned within pRS315. The ubc9-1 point mutation 7 was then introduced by site directed mutagenesis using the QuickChange XL Site-Directed Mutagenesis Kit (Agilent). h. The TRP1 marker from YCpLac22-ulp1-333 was swapped by homologous recombination with a disruption fragment from pTH4. i. A genomic fragment encompassing the SMT3 complete CDS (+/-500bp) was PCR-amplified form yeast genomic DNA and cloned within pRS316. j. Synthetic genes encompassing HEK2 sequences harboring stretches of lysines mutated to arginines were synthesized by ATG biosynthetics or Genecust. PCR-based techniques were used to combine wt and KR HEK2 fragments to express the different HA-tagged chimeras under the control of HEK2 natural promoter in the pRS316 backbone. k. Generated by site directed mutagenesis of pET21b-His-SMT3 using the QuickChange XL Site-Directed Mutagenesis Kit (Agilent).

Supplementary Table 3: qPCR primers used in this study

NUP133-F CGCCCAGGTGCATACTAACT NUP133-R AATGATAAGCCCTCCGGTTT NUP170-F TGTGGATCATTCTGCTCTGC NUP170-R CGCAAGCCAATTTCTTTAGC NUP59-F CACCACAGACAACCCAGATG NUP59-R AATTGCAAGTGTTGCTGCTG NUP188-F CACAACATTTGGAGCAATGG NUP188-R GGCACGTCTCAGGTAAAACC NUP116-F CCTTTGGTCAGGTGAATCGT NUP116-R TTTGCGTTAGCGTTTGATTG NUP100-F GGGATCTTGTCACCTTTGGA NUP100-R ATTAATGCCTTCGCCCTTTT NSP1-F CCCTTTCATTTGGTTCAGGA NSP1-R GCTGGTTTTGCTGGTTCATT NUP57-F CGGCAATAGCACTCAAAACA NUP57-R CCAAATAGGCCTCCCGTAGT NUP1-F CTCTGAGGGAAGTGCGAAAC NUP1-R CGAAAACGAGGGTTTAGCTG NUP2-F CGCAAGATGCAACCAAAGTA NUP2-R AAGCCACTTCGTCTTCCTCA ASH1-F ACGAAAAGTGGCAAGATGAG ASH1-R TGATAATTGGGTGACCTTGG ACT1-F ACGTTACCCAATTGAACACG ACT1-R AGAACAGGGTGTTCTTCTGG rRNA 25S-F AACGTCTATGCGAGTGTTTGG rRNA 25S-R TTCCTCTGGCTTCACCCTATT

  publiquement à Paris le 29/11/2018 Président du jury : Janel, Nathalie, PR. HDR, UMR825, Paris Diderot, CNRS Rapporteurs : Morales, Julia, CR HDR, UMR8227, Sorbonne Université, CNRS Rapporteurs : Audic, Yann, CR HDR, UMR6290, Université Rennes 1, CNRS Directeur de thèse : Cosson, Bertrand, PR HDR, UMR7216, Paris Diderot, CNRS Examinateurs : Lelandais, Gaëlle, PR HDR, UMR9198, Université Paris Saclay, CNRS Examinateurs : Palancade, Benoit, DR2 HDR, UMR7592, Paris Diderot, CNRS Per Mamma e Papà

FIGURE 1 .

 1 FIGURE 1. GENE EXPRESSION REGULATION ..............................................................................................

FIGURE 2 .

 2 FIGURE 2. THE ARCHITECTURE OF THE YEAST NUCLEAR PORE COMPLEX ...................................................

FIGURE 3 .

 3 FIGURE 3. SCHEMATIC REPRESENTATION OF STRUCTURAL ORGANIZATION OF A MATURE MRNA ................

FIGURE 4 .

 4 FIGURE 4. CAP-DEPENDENT EUKARYOTIC TRANSLATION INITIATION ...........................................................

FIGURE 5 .

 5 FIGURE 5. POSSIBLE INITIATION COMPLEX FORMED BY EIF3D-DAP5 ON 5' CAP OF THE MRNAS .................

FIGURE 6 .

 6 FIGURE 6. SCHEMATIC VIEW OF THE REGULATION OF TERNARY COMPLEX FORMATION ...............................

FIGURE 7 .

 7 FIGURE 7. 4E-BP IS PHOSPHORYLATED BY MTORC1 TO BLOCK CAP-DEPENDENT TRANSLATION ...............

FIGURE 8 .

 8 FIGURE 8. REGULATION OF EIF4E1 AND EIF4E3 DRIVEN TRANSLATION .....................................................

FIGURE 9 .

 9 FIGURE 9. POSSIBLE MECHANISMS OF REGULATION BY UORFS .................................................................

FIGURE 10 .

 10 FIGURE 10. CLASSIFICATION OF THE IRESS BASED ON THE RECRUITED FACTORS ......................................

FIGURE 11 .

 11 FIGURE 11. LARP1 REGULATES TOP MRNAS IN A MTORC1 DEPENDENT MANNER ..................................

FIGURE 12 .

 12 FIGURE 12. CNOT1 SERVES AS SCAFFOLD PROTEIN TO ALLOW THE ASSEMBLY OF THE CCR4-NOT COMPLEX .........................................................................................................................................

FIGURE 13 .

 13 FIGURE 13. SCHEMATIC REPRESENTATION OF CCR4-NOT COMPLEX DEADENYLATION ACTIVITY ................

FIGURE 14 .

 14 FIGURE 14. ARCHITECTURE OF THE DOMAINS OF THE CCR4 DEADENYLASE FAMILY ...................................

FIGURE 15 .

 15 FIGURE 15. SCHEMA OF THE MAIN MTORC1 TARGETS IN TRANSLATION REGULATION ................................

Figure 1 .

 1 Figure 1. Gene expression regulation A network of transcription factors and epigenetic regulators, determine the transcriptional program of a cell. The nascent transcripts readily associate with different RNA biding proteins forming the messenger ribonucleoproteins (mRNPs). The generated mRNPs allow coupling of transcription with the pre-mRNA maturation steps such as 5' capping, splicing, 3' cleavage and polyadenylation. The mRNPs containing fully matured mRNAs are then transported to the cytosol where the mRNPs are remodeled in order to enter active translation or to form various type of granules regulating storage, transport and degradation of the mRNAs. Newly synthetized proteins can be regulated by post-translational modifications (PTMs) that alter the protein function and/or stability.

Figure 3 .

 3 Figure 3. Schematic representation of structural organization of a mature mRNA

Table 1 .

 1 Known phosphorylation site for the eIFsList of all known phosphorylation sites on each of the eIFs factors and possible function.

Figure 6 .

 6 Figure 6. Schematic view of the regulation of Ternary Complex formation Upon different stresses four different kinases (PERK, GCN2, HRI, PKR) can be activated and phosphorylate eIF2α subunit at Ser51 which increase its affinity for eIF2B. This conformation inhibits eIF2B activity, preventing the recycling of eIF2-GDP to eIF2-GTP. The phosphorylation status of eIF2α is counterbalanced by phosphatases recruited by NCK1 along with the phosphorylation of eIF2β by CK2 and possibly mTORC1.

Figure 7 .

 7 Figure 7. 4E-BP is phosphorylated by mTORC1 to block cap-dependent translation A. mTORC1 in normal conditions binds and phosphorylates the 4E-BPs impeding their binding to eIF4E. Upon cellular stress such as hypoxia, energetic stress (e.g. glucose deprivation), amino acid starvation and growth factors mTORC1 is sequestered or inactivated. 4E-BPs are then free to sequester eIF4E thus inhibiting cap-dependent translation. B. Overview of the protein structure of the 4E-BP family with representation of the various domains and phosphorylation sites.

Figure 8 .

 8 Figure 8. Regulation of eIF4E1 and eIF4E3 driven translation Phosphorylation of eIF4E1 by MNK1/2 increases association of eIF4E1 with the cap structure of the mRNAs promoting translation. In absence of activated MAPK signalling MNK1/2 do not phosphorylate eIF4E1 leading to eIF4E3 upregulation which favors its association with the cap thus enhancing its driven translation

Figure 10 .

 10 Figure 10. Classification of the IRESs based on the recruited factors Cellular IRES require different co-factor for recruitment of the ribosome: A. IRESs that require ITAFs and all the eIFs but eIF4E. B. A. IRESs that require only some of the eIFs (such as the eIF3 complex). C. IRESs that require that can recruit the ribosome only with the help of ITAFs.

Figure 11 .

 11 Figure 11. LARP1 regulates TOP mRNAs in a mTORC1 dependent manner When mTORC1 is active by phosphorylating both 4E-BPs and LARP1 it allows efficient translation of the TOP mRNAs. In response to stresses mTORC1 is inactivated thus the 4E-BPs sequester eIF4E and LARP1 binds to the 5' end of TOP mRNA blocking cap-dependent translation but also preventing degradation.

Figure 12 .

 12 Figure 12. CNOT1 serves as scaffold protein to allow the assembly of the CCR4-NOT complex

Figure 13 .

 13 Figure 13. Schematic representation of CCR4-NOT complex deadenylation activity CCR4-NOT complex interacts with PABPs proteins regulating polyA tail length. Cis-elements present on the 3'UTRs of the mRNA such as miRNA targets sites or AU rich elements enhance CCR4-NOT activity via trans-activator factor.

  regulated mRNA have not yet been described. Nocturnin deadenylase activity has been clearly demonstrated for the Xenopus ortholog both in vivo and by in vitro experiments. The in vivo deadenylase activity of the human ortholog has been only

Figure 14 .

 14 Figure 14. Architecture of the domains of the CCR4 deadenylase family Representation of the known domains of the deadenylases belonging to the CCR4 family.

Figure 15 .

 15 Figure 15. Schema of the main mTORC1 targets in translation regulation Energy stress regulates mTORC1 activity. mTORC1 regulates by phosphorylation the activity of the eIF4F complex by phosphorylating directly eIF4G, by phosphorylating LARP1 inhibiting its repression on TOP mRNAs, by regulating 4E-BP ability to sequester eIF4E and by activating S6Ks which in turn regulate the repressor of eIF4A, PDCD4, and phosphorylates eIF4B. S6Ks modulate translation elongation by modulating eEF2K activity.

  Antibodiesanti-Angel-1 (HPA000948, Atlas Antibodies); anti-calnexin C-term (Clone TO-5, Sigma); anti-Golgin-97 (CDF4, Thermo Fisher); anti-eIF4E (eukaryotic initiation factor 4E) (Sigma); anti-TRIP4 (ab 70627, Abcam); anti-HSF2 ( ab44824, Abcam); anti-Halotag (G9211, Promega); anti-GST (Santa Cruz Biotechnology, Inc); anti-tubullin (T9026 Sigma); anti-HA (H3663, Sigma)PlasmidsThe CMV-driven Flexi vector pFN21K HaloTag CMV and pFC14K Halotag (Promega) were used to generate an N-terminal and C-terminal Angel1-Halo following manufacturer instruction. C-terminal fusion CELF1 was obtained from Promega (A1-Halo-WT). A single point mutation of the residue Tyr506 (Angel1-Halo-YA (A1-Halo-YA)) was created from the pFN21A-Angel1-Halo-Tag construct using the Quick-changeTM site-directed mutagenesis kit (Stratagene) following the manufacturer's instructions. The following two primers were point mutation was created on the pFN21K-Angel1-Halo-Tag construct on the residue Glu298 (Angel1-Halo-WT-NUC -) using Quick-changeTM site-directed mutagenesis kit (Stratagene) following the manufacturer's instruction using following primers: forward Glu298-AlaF (AGATCAGAGAGACGCAAGGCTGGCCGAGACTTCCTGCTACG) and reverse Glu298-AlaR (CGTAGCAGGAAGTCTCGGCCAGCCTTGCGTCTCTCTGATCT). Starting from a Flexi vector pFN21A HaloTag CMV was generated a new vector expressing the Halo Tag protein alone (Halo*) using restriction sites sgf1 and pmel (Promega digestion kit) and then ligation of the two extremities. A stop codon was inserted after the TEV site in the Halo* vector using the Quick-changeTM site-directed mutagenesis kit (Stratagene) following the manufacturer's instructions. The following two primers were used for mutagenesis: Forward (GGATCTGTAACTTTC AGAGCTAAAACGCGAAACGAATTC) and Reverse (GAATTCGTTTCGCGTTTTGAGCTCTGAAAGT ACAGATCC). Plasmid containing CELF1, TRIP4 and HSF2 expressing Halo at C-terminal were purchased at Kazusa Collection (Promega). Correct protein expression and localization was validated by western-blot using anti-Halo antibody and live imaging using TMR Halo ligand (Promega) following manufacturer's instructions. Plasmids for Angel1-HA and Δ-Angel1-HA and were obtained

  1 M sodium tetraborate (Na2B4O7), pH 8.5, and re-pelleted by centrifugation. The pellet was resuspended in 200µl of FITC mouse anti-BrdU antibody (Becton Dickinson Pharmingen; 1 :100) in 1% Bovine Serum Albumin (BSA), 0.5% Tween 20, PBS pH 7.4. After 2 hours at room temperature, samples were washed with 5 ml 20 mM Hepes, 0.5% Tween 20 in PBS pH 7.4, and resuspended in 0.2-0.5 ml PBS pH 7.4 containing 5µg/ml propidium iodide and 200 µg/ml RNase A and incubated at least 2-3 hours at +4°C.Cells, which had undergone the whole process, but were not marked with the primary antibody and PI, were used as negative controls. The percentages of BrdU-positive cells and DNA contents were measured with flow cytometer (Becton Dickinson FACSAria II). Both fluorophores were excited by a 488 nm blue laser; Alexa Fluor 488 emission was captured through a 530/30 nm filter and propidium iodide emission was captured through a 610/20 nm filter.

5 .

 5 Uniquely mapped reads were kept for further analysis.

  which allows generation of data that represent a snapshot of what is being translated in the cells. As previously done for the transcriptome analysis, we compared the two Angel1 silenced cell lines to our control cell line. For each cell line we prepared two replicates collected in two different days in order to obtain independent replicates(Fig 5A). To identify genes specifically regulated at the translation level, during the data analysis, the transcriptome should be considered to normalized for variations of the mRNA abundance. Since in our transcriptome analysis we demonstrated that Angel1 affect abundance of a specific subset of mRNAs we decided to proceed with a "standard" differential gene expression analysis without integrating transcriptome data. The sequenced libraries contained for each sample around 20 million reads (Fig.5B, raw reads). Raw reads were trimmed for their 3' and 5' adapters. Then a size selection filter was applied and remaining reads (Fig 5B, filtered reads) were mapped on the human genome. Reads that mapped more than once were discarded hence analysis, uniquely mapped reads were kept for the analysis(Fig 4B). Hierarchical clustering of the samples highlighted the one replicate for SH-2 and one SCR clustered together away from the rest of the samples (Fig.5C), while the remaining samples formed cluster with the replicates of SH-3 grouped together. Principal component analysis (PCA) showed more precisely as one SH-2 and one SCR were separated from the rest of the samples(Fig 5D)

  assay in combination with Propidium Iodide (PI) staining on Angel1 knockdown cell lines (Sh-Angel1 #2 and #3 compared to control Sh-SCR). BrdU is thymidine analogue which is incorporated into nuclear DNA of proliferating cells reflecting the rate of proliferation, while PI is a fluorescent intercalating agent that can be used as proxy to measure DNA content and thus cell cycle stage. As shown in Fig 8. A and B (representative results for Sh-SCR and Sh-A1#2) we did not observe any difference in the rate of proliferation nor in cell cycle progression.Angel1 role in human pancreatic β-cellsHaving established that Angel1 is localized on the external surface of the ER in contact with others translation factors we hypothesized a physiological role of Angel1 in cell dedicated in synthesis of secreted proteins. Databases publicly available (GTEX, Protein Atlas) indicated that Angel1 is well expressed in pancreas but more interestingly immunohistochemistry experiments on human pancreatic samples showed strong expression of Angel1 in the islet of Langerhans and in pancreatic cancerous samples Angel1 expression is drastically reduced (http://www.proteinatlas.org/ ENSG00000013523/cancer). Moreover, by exploiting the transcriptome data generated by Xie and colleagues[START_REF] Xie | Dynamic Chromatin Remodeling Mediated by Polycomb Proteins Orchestrates Pancreatic Differentiation of Human Embryonic Stem Cells[END_REF], we could highlight that

  9C). Transfected cells (either siNT or si Angel1) were incubated with radioactive methionine ([35S]-Methionine). As negative control we treated cells with cycloheximide (Fig.9C CHX (+)) which inhibits translation elongation. As shown in Fig.9C, CHX treated samples effectively incubated 40% less methionine. Comparison between Angel1 silenced cells and control indicated that Angel1 depletion had no effect on protein synthesis rates. Taken together these results indicate that Angel1, does not play a role in the global rates of protein synthesis in EndoC-βH1 cell. A possible strategy will be to validate the Angel1 targets identified in HeLa cells.

  Figure 1

  Figure 6

Fig. 1 .

 1 Fig.1. Angel-1 is localized to the outer surface of the Endoplasmic Reticulum.A. Analysis of Angel1 subcellular distribution by centrifugation. Lysates of HeLa cells were prepared by Dounce homogenization and fractionated by consecutive steps of centrifugation at different speeds. TL (total) S100 and P100, the supernatants and pellets of the 100,000 X g centrifugation, respectively. The presence of Angel-1, the translational factor eIF4E and 4E-BP1 in the different fractions was determined by Western blot of equal total protein amounts with Angel1, eIF4E and 4E-BP1 antibodies, respectively. C-terminal calnexin was used as an Endoplasmic Reticulum marker, and Golgin-97 as an Golgi apparatus marker. B. Protease protection analysis of Angel1 localization. The P100 pellets were resuspended with incubated with increasing amounts of proteinase K (0, 1, 5 and 10 units). The reactions were stopped and analyzed by Western blot with the Angel-1, Calnexin, Golgin-97. C. Draw to depict the principle of the protease protection assay: proteins expressed on the cytosolic, face of the ER, represented in blue are accessible to digestion by the proteinase K while ER resident proteins are protected, represented in orange.

Fig 2 .

 2 Fig 2. Angel1 possess a N-terminal peptide responsible for Angel1 localization to the ER A. Schematic representation of the constructs used: wild type C-terminal HA tagged Angel1 (A1-HA) and Angel1 with deleted signal peptide (Δ-A1-HA). Immunofluorescence experiments were performed on Hela S3 cells transfected with Angel1-HA, ΔAngel1-HA (Fig. 2B), DCP1

Fig. 3 .

 3 Fig. 3. Angel1 does not possess deadenylase activity A. Deadenylation assay: Western-blot showing efficient purification of Angel1 after TEVcleavage. A polyA RNA associated with a fluorochrome was incubated with purified complexes for 2hr and the resolved on a 25% acrylamide gel. Last box showing results for Nocturnin (a CCR4 family member). After 30 min or 1-hour incubation target polyA RNA show shortening of the polyA tail.

Fig. 4 .

 4 Fig. 4. Angel1 regulates mRNA steady-state levels of a subset of mRNAs A. Western-blot and immunofluorescence against Angel1 to assess KD in ShA1#2 and #3. B.Schematic table summarizing experimental design (4 replicates per condition), raw reads and

Fig. 6 .

 6 Fig. 6. RIP-seq results A. RIP-seq workflow: overexpressed Halo-tagged proteins are purified and eluted using a Halo-tagged TEV-protease that cleaves at the TEV site (yellow band) between the tag and the protein of interest. RNAs are extracted from the mRNPs purified complexes, under schematic representation of constructs used during RIPseq. B. Western-blots to assess pull down efficiency of Halo proteins. For each protein: firs lane non-transfected cells, 2° lane input of the pull-down, 3° lane eluates after Halo-tag cleavage (* indicates the band of the cleaved protein; in Halo pulldown, the Halo-TEV is recognized). Immunofluorescence against transfected proteins using Halotag TMR ligand highlights specific localization for each of the proteins. C.Table recapitulating RIP-seq: number of replicates, size of raw reads libraries, %

  Figure 1

  Figure 2

Figure 1 :Figure 2 :Figure 3

 123 Figure 1: Glucose induces increase in protein synthesis without affecting mRNA abundance A. SunSET experiment of EndoC-βH2 cells. Cells were starved for 24hr at 0.5 mM glucose and then treated with glucose for 30 min at 0,5 mM or 5.6 mM or 20 mM Puromycin was added in the last 10 minutes. Where indicated cell were pretreated for 1hr with rapamycin (RAPA) and cycloheximide (CHX). B. Western blot analysis of samples prepared as in A; the levels of phosphorylated and total forms of RPS6 and eIF2α were tested with specific antibodies. C. Table summarizing the transcriptome data. D. Hierarchical clustering of the replicates shows clear separation between low and high glucose samples. E. MA-plot of the transcriptome analysis: on the y-axis the log2 fold change while on the x-axis the average log expression (log CPM)

Fig. 1 3 2

 13 Fig.1The hnRNP K-like protein Hek2 specifically associates with a subset of NPC mRNAs. a Top, Representation of the yeast nuclear pore complex (NPC), showing subcomplexes as colored boxes. Bottom, mRNAs encoding NPC components are sorted by subcomplexes and the strength of their association to the different indicated RNA-binding proteins (RBP) is represented by a color code, as scored in distinct RIP, CLIP or CRAC datasets. Bright yellow indicates the preferred association of a given mRNA to the RBP of interest. For Sto1, Mtr4, Nab2, Mex67, Xrn1 and Ski2, multiple repetitions are displayed27 . For Hek2, the results from independent studies are represented: (1) 24 , (2) 26 , (3) 25 , (4)27 . FG-Nups appear in bold, underlined. The NUP145 mRNA gives rise to both Nup145-N and Nup145-C nucleoporins and is displayed for each of the according subcomplexes. b Hek2-pA-associated mRNAs were immunopurified and quantified by RT-qPCR using specific primer pairs. Percentages of IP are the ratios between purified and input RNAs, normalized to the amount of purified bait and set to 1 for the "no tag". Means and individual points (n = 3) are displayed. A schematic representation of the assay is shown. c Overview of Hek2-binding sites on NSP1 and NUP116 mRNAs. The number of CRAC hits (rpn (reads per nucleotide))27 , the position of CLIP fragments26 and the occurrences of the binding site found by the MEME analysis are indicated. The positions of the FG-coding region and of minimal Hek2-binding sites used for in vitro pull down (in gray) are represented. The broken line indicates the NSP1 intron. d MEME result from NUP59, NUP116, NUP1, NSP1 and NUP100 sequences.(1, 2): previously identified Hek2-binding sequences24,26 . e Left, Schematic representation of the assay. Recombinant HA-tagged Hek2 was incubated with streptavidin beads either naive (Φ) or coated with biotinylated RNA probes encompassing Hek2-binding sites from NSP1 or NUP116 (162-221) or a sequence from NUP133 (1429-1488). Right, Decreasing amounts of input and eluate fractions were loaded for quantification. f Percentages of IP are the ratios between Hek2 amounts in the eluate and input fractions, calculated from (e). Means and individual points (n = 3) are displayed. **P < 0.01 (Welch's t-test)

  10.1038/s41467-018-03673-3 | www.nature.com/naturecommunications

  10.1038/s41467-018-03673-3 | www.nature.com/naturecommunications

  Fig.3Hek2 sumoylation prevents its association to mRNAs. a Principle of the purification of sumoylated Hek2. Extracts from cells expressing a His-tagged version of SUMO were used for denaturing nickel chromatography. b-d Extracts from wt and HEK2-HA cells (b), HEK2-HA and HEK2-HA ulp1 cells (c) or HEK2-HA ulp1 and HEK2 K15R K29-30R-HA ulp1 cells (d) expressing or not His 6 -SUMO (+/-) were used for nickel chromatography. Total lysates ("Inputs") and purified His-SUMO conjugates ("Eluates") were analyzed by western blotting using anti-HA antibodies. The positions of the sumoylated and unmodified versions of Hek2-HA, as well as molecular weights, are indicated. Note the non-specific binding of a fraction of non-sumoylated Hek2-HA (also observed in the absence of His-SUMO, second lanes in (b, c)), a classical issue in SUMO-conjugates purification. e Principle of the mRNP purification procedure. Cbc2 or Mlp2 are purified through a protein-A tag, and the protein content of the associated mRNPs is analyzed by western blot. Note that RNAse A treatment experiments confirmed the RNA dependence of the interactions scored in such assays35 . f, g Top, Soluble extracts ("Input", left panels) and Cbc2-pA-associated mRNPs (f) or Mlp2-pA-associated mRNPs (g) ("Eluate", right panels) isolated from wt and ulp1 cells were analyzed by immunoblotting using the indicated antibodies. Bottom, The relative amounts of Hek2 associated to Cbc2-and Mlp2-bound mRNPs are represented (mean and individual points; n = 3 for Cbc2-pA, n = 2 for Mlp2-pA). h Principle of the in vitro RNA-binding assay. i An in vitro sumoylation mixture containing both unmodified and sumoylated Hek2 was incubated with streptavidin beads either naive (Φ) or previously coated with biotinylated RNA probes encompassing Hek2-binding sites from NSP1 or NUP116 or a sequence from NUP133. Decreasing amounts of input and eluate fractions were loaded to allow quantification. j Percentages of IP are the ratios between unmodified (or sumoylated) Hek2 amounts in the eluate and in the input fractions and were calculated from (i). Means and individual points (n = 3) are displayed. Note that sumoylated Hek2 was not detectable (n.d.) and thereby not quantified on control pull downs. *P < 0.05 (Welch's t-test)

Fig. 4

 4 Fig. 4 Defects in nuclear pore integrity impact Ulp1 activity and Hek2 sumoylation. a Fluorescence microscopy analysis of Ulp1-GFP in wt, nup145ΔGLFG nup100ΔGLFG nup57ΔGLFG, nup145ΔGLFG nup100ΔGLFG nsp1ΔFGΔFxFG, nsp1ΔFG•FxFG and nup1ΔFxFG cells grown at 30 °C. Scale bar, 5 µm. b Quantification of the Ulp1 nuclear envelope fluorescence intensity in the different strains. The numbers refer to the genotypes as depicted in (a). For each strain, at least 150 cells were analyzed. Boxplots were generated using KaleidaGraph (Synergy Software): each box encloses 50% of the measured values, the median is displayed as a line, and the bars extending from the top and bottom of each box mark the minimum and maximum values within the dataset falling within an acceptable range. Values falling outside of this range are displayed as individual points. ***P < 0.001 (Mann-Whitney-Wilcoxon test). c Ulp1-GFP amounts were measured in wt and nsp1ΔFGΔFxFG cells by western blotting using anti-GFP antibodies (top panel). Ponceau staining was used as a loading control (lower panel). A serial dilution of the wt sample was used for quantification. Ulp1-GFP amounts normalized to ponceau are represented (mean and individual points, n = 2). d Whole cell extracts of the indicated strains were analyzed by western blotting using anti-SUMO antibodies.The bands that are modified in the nsp1ΔFGΔFxFG mutant are also typically altered in ulp1 cells (arrows). e Hek2 sumoylation was detected in wt and nsp1ΔFGΔFxFG cells as in Fig.3. Total lysates ("Inputs") and purified His-SUMO conjugates ("Eluates") were analyzed by western blotting using anti-HA antibodies. The pattern of Hek2 sumoylation in ulp1 cells was analyzed as a control. The positions of the sumoylated and unmodified versions of Hek2-HA, as well as molecular weights, are indicated. f Hek2 sumoylation was similarly detected in wt cells, either untreated, or treated with 10% ethanol for 1 h

  . Streptavidin dynabeads (Invitrogen) were washed three times in 0.1 M NaOH, 0.05 M NaCl and once in 0.1 M NaCl. Then, 2 μg of biotinylated RNA (encompassing Hek2-binding sites on NSP1 (21-80) or NUP116 (162-221) mRNAs or a sequence from NUP133 (1429-1488); Integrated DNA Technologies) were bound to 10 μl of beads in RNA-binding buffer (5 mM Tris-HCl pH 7.5, 1 M NaCl, 40 U per ml RNAsin) for 30 min at room temperature. The conjugated beads were then washed four times in RNA-binding buffer and incubated in protein-binding buffer (50 mM Hepes pH 7.5, 100 mM NaCl, 1 mM MgCl 2 , 10% glycerol, 0.5 mM DTT, 0.1 mM phenylmethylsulfonyl fluoride, 0.1% bovine serum albumin, 40 U per ml RNAsin) for 15 min at 4 °C for saturation.

  , 1:2000; monoclonal anti-HA (clone 16B12, MMS-101P, Covance), 1:1000; monoclonal anti-GFP (clones 7.1 and 13.1, 11814460001, Roche Diagnostics), 1:500; monoclonal anti-GST (clone 4C10, MMS-112P, Covance), 1:1000; rabbit IgG-HRP polyclonal antibody (to detect protein-A-tagged proteins, Z0113, DakoCytomation), 1:5000. For Nup59-GFP and Ulp1-GFP detection, specificity of anti-GFP antibodies was confirmed using untagged strains. Quantification of signals was performed based on serial dilutions of reference samples using the ImageJ software.

Table of contents

 of List of figures and tables

Table 2 . eIF4Es interacting partners List of known proteins to interact with one or more eIF4E family members with known role.

 2 )

	Neuroguidin		eIF4E1 Neurogenesis		(Jung et al., 2006)
	(Ngd)
	Angel1		eIF4E1 Endo/exo-nuclease-phosphatase	(Gosselin et al., 2013)
			domain-containing protein; No
			known biological role.
	Promyelocytic		eIF4E1 Nuclear mRNA export and DNA	(Kentsis et al., 2001)
	leukemia protein	repair; Cell growth and apoptosis.
	(PML)
	GYGYF2 b		eIF4E2 GRB10-interacting GYF protein 2. (Morita et al., 2012)
	Cytoplasmic		eIF4E1 FMRP-interaction factor during	(Napoli et al., 2008)
	FMR1-interacting	neuronal	activity;	Actin
	protein	1	polymerization.
	(CYFIP1)
	Leucine-rich		eIF4E1 Mitochondrial RNA transport and	(Volpon et al., 2017)
	pentatricopeptide	expression;	Nuclear	mRNA
			metabolism;	Neurogenesis;

Table 3 .

 3 Main properties of the eIF4E family members

	Function

  Fluorescein isothiocyanate (FITC) (Eurogentec). Reaction was stopped with buffer (95% formamide, 10 mM EDTA et Bromophenol blue). Samples were then resolved into a 25%

	with some
	modifications. 8x10 6 cells were used for each replicate. Cells were washed in ice-cold PBS
	containing 100 µg/ml and lysed in 400 µl of lysis buffer (20 mM Tris, pH 7.4, 150 mM NaCl, 5
	mM MgCl2 and 1% Triton) supplemented with 1 mM DTT, 100 µg/ml, 0.1 U of TurboDNase
	Deadenylation assay
	Hela S3 were transiently transfected with Angel1-halo, Angel1-nuc-Halo and Halotag alone
	plasmids. Pull-down was performed as described for RIP with modifications in the buffers used
	to preserve possible deadenylase activity: lysis buffer (50 mM Hepes NaOH pH 7,6, 150 mM
	NaCl, 2 mM MgCl2, 0,5% Igepal cat630, Protease inhibitor 1X (Promega), 1 mM DTT); NT2

(ThermoFisher) and protease inhibitor cocktail

(Merck, ref#535140)

. Lysates were incubated for 10 min on ice, passed through a 26G needle 10 times and centrifuged at 13000 rpm for 10 min at 4°C. Sample were incubated for 45 min at room temperature with 1500 units of RNase I (Ambion) to digest polysomes into monosomes. Digestion was blocked by addition of 5 µl of SUPERaseIN (Ambion) and the 80S monosome fraction was isolated by ultracentrifugation (TLA 100.3 Rotor, Beckman) for 3 hours at 4°C at 50000 rpm, on 34% sucrose cushion prepared in Polysome buffer (20 mM Tris pH 7.4, 150 mM NaCl, 5 mM MgCl2 freshly supplemented with 1 mM DTT and 100 µg/ml CHX). Pellets were resuspended in 7M Guanidinium-HCl and RNA and RNA were isolated by acid phenol: chloroform and ethanol precipitation (supplemented with 50 µL 3M NaOAc pH 5.2, 1 µl of glycoblue). RNA fragments corresponding to Ribosome Footprints (RFs) were excised from a 15% acrylamide gel with 7M urea (markers with oligos of 25+34nt long). RPFs were eluted in 400µl GEL elution buffer (300 mM NaCl, 60 mM NaOAc pH5.2 and 0.2% SDS) and precipitated with ethanol supplemented with 1ul glycoblue. Libraries were then prepared as previously described

[START_REF] Ingolia | The ribosome profiling strategy for monitoring translation in vivo by deep sequencing of ribosomeprotected mRNA fragments[END_REF]

. The libraries were sequenced (read length 75 base pair) with the illumina HiSeq system following to the manufacturer's instructions. buffer (50 mM Hepes NaOH pH 7,6, 150 mM NaCl, 2 mM MgCl2, 0,05% Igepal cat630). After TEV digestion samples were incubated in a deadenylation buffer

(50 mM Hepes NaOH, 150

mM NaCl, 2 mM MgCl2, Glycerol 10%, 1mM DTT, 4U/ul RNAsin) supplemented with 0,2µM of a in polyA RNA (5'UCU-AAA-UAA-AAA-AAA-AAA-AAA-AAA-AAA-3') tagged at 5' with a

Table 1 MODEL

 1

	Figure 5
	A		B
			Rep	RIBO-seq	Raw Reads	Filtered Reads	Uniquely mapped
	DAY 1	SCR	1	Sh-SCR S2	23214277	6592879 (28.40%)	1579061 (23.95%)
		Sh-2	1	Sh-SCR S8	24500841	8104212 (33.08%)	1640304 (20.24%)
		Sh-3	1	Sh-A1#2 S4	20265840	5827727 (28.76%)	1219054 (20.92%)
	DAY 2	SCR	1	Sh-A1#2 S10	20885803	6698530 (32.07%)	1665037 (24.86%)
		Sh-2	1	Sh-A1#3 S6	19022343	8160410 (42.90%)	2373231 (29.08%)
		Sh-3	1	Sh-A1#3 S12	24840751	10440714 (42.03%)	2735549 (26.20%)
	C				D
						Principal Component Analysis	Variance explained
	E
	F				Babel (40)		RNAseq123 (47)
					90

Table 2

 2

	Trip4-HALO	2	19.5M; 14.5M	76%; 76%	400 K	179 K
	HALO*	2	18.2M; 19M	60.5%; 80%	830 K	82 K

Table 1 .

 1 List of targets identified by RNAseq123 RNAseq analysisTable of the differentially expressed RNAs in SH2 and SH3 compared to control SCR.

Fig 5. Traductome analysis of Angel1 KD cell lines by Ribosome profile sequencing A. 2 independent replicates prepared in two different days. B. Table with number and percentage of reads after each processing step (raw reads, filter, uniquely mapped) and boxplot of the normalized count distributions for each sample expressed in logCPM (counts per million reads). C Hierarchical clustering and Principal Component Analysis of the samples.

C. MA-plots of SCR vs SH2 and SCR vs SH3, the x-axis is the log2 of the averaged expression in CPM, differentially translated mRNAs are marked in red when downregulated in SH2 and green when upregulated. Significant genes are marked in red or green. E Venn diagram showing the overlap of the identified genes for SH2 and SH3. F

Table 2 .

 2 List of targets identified by Babel and RNAseq123 for Ribosome profiling analysis Table of differentially translated Angel1 targets for SH2 identified by Babel and RNAseq123.

  3,6 , Bertrand Cosson 2 , Frédéric Devaux 4 & Benoit Palancade 1

Table 1 :

 1 Yeast strains used in this study

	Strain code	Name	Relevant genotype	Source/Reference
	BY4742 / BY4741	wt		Euroscarf
	Y13058	hek2∆	hek2::kanMX	Euroscarf
	JR154	HEK2-pA	hek2::kanMX pRS316-HEK2-protA	This study *
	Y14072	hpr1∆	hpr1::kanMX	Euroscarf
	K5552	wt	(W303) ASH1-MYC9	12
	YV1862	hek2∆	(W303) ASH1-MYC9 hek2::kanMX	This study (a)
	YV2083	NUP59-GFP	NUP59-GFP::HIS3MX	Invitrogen
	YV2084	NUP59-GFP hek2∆	NUP59-GFP::HIS3MX hek2::kanMX	This study *
	YV2056	NUP1-GFP	NUP1-GFP::HIS3MX	Invitrogen
	Y10568	erg6∆	erg6::kanMX	Euroscarf
	YV2092	NUP1-GFP erg6∆	NUP1-GFP::HIS3MX erg6::kanMX	This study *
	YV2093	NUP1-GFP erg6∆ hek2∆	NUP1-GFP::HIS3MX erg6 ::kanMX hek2::kanMX	This study *
	YV1593	HEK2-3HA	HEK2-3HA::kanMX	This study (b)
	YV1262	ulp1	ulp1::kanMX YCpLac111-ulp1-333 (LEU2)	1, 13
	YV1432 / YV1433	ulp1	ulp1::kanMX YCpLac22-HIS3-ulp1-333 (HIS3)	This study (c)

14 Supplementary Table 2 :

 Supplementary2 Plasmids used in this study

	Name	Description	Source/Reference
	pBXA	for prot-A tagging	15
	pTH4	trp1::HIS3 disruption fragment	16
	pTL7	trp1::LEU2 disruption fragment	16
	pUL9	ura3::LEU2 disruption fragment	16
			Dharmacon yeast
	pGP564-ChromosomeII-152618-		genomic tilling
	169095	contains a genomic fragment encompassing the HEK2 gene	collection
	pRS316-HEK2±500pb	CEN/URA3/HEK2±500pb	This study (a)
	pRS316-HEK2-3HA	CEN/URA3/HEK2-3HA (HEK2 natural promoter)	This study (b)
	pRS316-HEK2-pA	CEN/URA3/HEK2-protA (HEK2 natural promoter)	This study (c)
	pET28b-HEK2-3HA-His6	AmpR/HEK2-3HA-His6 (for recombinant protein production)	This study (d)
	pGEX-6p-1	AmpR/TACprom-GST (for recombinant protein production)	Addgene
	pFA6a-kanMX	for deletion	17
	pYEP96-6His-SMT3	CEN/TRP1/CUP1prom-6His-SMT3	1
	pYEP96-LEU2-6His-SMT3	CEN/LEU2/CUP1prom-6His-SMT3	This study (e)
	pYES2-His-Flag-SMT3	2µ/URA3/GALprom-His-Flag-SMT3	a gift from V. Géli
	pYES2-LEU2-His-Flag-SMT3	2µ/LEU2/GALprom-His-Flag-SMT3	This study (f)
	pFA6a-3HA-kanMX6	for 3-HA tagging	17
		CEN/LEU2/ubc9-1 (a thermosensitive ubc9 allele ; UBC9 natural
	pRS315-ubc9-1	promoter)	This study (g)
		CEN/TRP1/ulp1-333 (thermosensitive ulp1 allele ; ULP1 natural
	YCpLac22-ulp1-333	promoter)	8, 13
		CEN/LEU2/ulp1-333 (thermosensitive ulp1 allele ; ULP1 natural
	YCpLac111-ulp1-333	promoter)	1
		CEN/HIS3/ulp1-333 (thermosensitive ulp1 allele ; ULP1 natural
	YCpLac22-HIS3-ulp1-333	promoter)	This study (h)
	pRS316-SMT3	CEN/URA3/SMT3 (SMT3 natural promoter)	This study (i)
	pRS316-hek2-3HA K1-30R	CEN/URA3/hek2-3HA K1-30R	This study (j)
	pRS316-hek2-3HA K1-7R	CEN/URA3/hek2-3HA K1-7R	This study (j)
	pRS316-hek2-3HA K8-18R	CEN/URA3/hek2-3HA K8-18R	This study (j)
	pRS316-hek2-3HA K19-30R	CEN/URA3/hek2-3HA K19-30R	This study (j)
	pRS316-hek2-3HA K8-12R	CEN/URA3/hek2-3HA K8-12R	This study (j)
	pRS316-hek2-3HA K13-18R	CEN/URA3/hek2-3HA K13-18R	This study (j)
	pRS316-hek2-3HA K19-24R	CEN/URA3/hek2-3HA K19-24R	This study (j)
	pRS316-hek2-3HA K25-30R	CEN/URA3/hek2-3HA K25-30R	This study (j)
	pRS316-hek2-3HA K13-14R	CEN/URA3/hek2-3HA K13-14R	This study (j)
	pRS316-hek2-3HA K15R	CEN/URA3/hek2-3HA K15R	This study (j)
	pRS316-hek2-3HA K16-18R	CEN/URA3/hek2-3HA K16-18R	This study (j)
	pRS316-hek2-3HA K25-26R	CEN/URA3/hek2-3HA K25-26R	This study (j)
	pRS316-hek2-3HA K27-28R	CEN/URA3/hek2-3HA K27-28R	This study (j)
	pRS316-hek2-3HA K29-30R	CEN/URA3/hek2-3HA K29-30R	This study (j)
	pRS316-hek2-3HA K15R K29-30R	CEN/URA3/hek2-3HA K15R K29-30R

NATURE COMMUNICATIONS | (2018) 9:1665 | DOI: 10.1038/s41467-018-03673-3 | www.nature.com/naturecommunications

Acknowledgements I would like to start by thanking Julia Morales and Yann Audic to have accepted to judge my PhD work. I would also like to thank Nathalie Janel, Gaëlle Lelandais and Benoît Palancade to have to have accepted to be part of my jury. I also would like to thank the members of my committee Vincent Anquetil, David Garrick and Slimane AIT-SI-ALI that have helped me with useful advices during these year I would like to thank my team: Bertrand Cosson for the guidance and presence during these three years, Costas for the time spent trying to teach me a bit of bioinformatic and Fabienne for all the big laughs in the lab. I would like to thank all the people of the unit for the help and the useful advices during these Acknowledgements .................................................................................................... Abstract ......................................................................................................................

64

II. Results

Acknowledgements

We thank P. Chartrand, C. Dargemont, V. Doye, V. Géli, M. Hochstrasser, E. Johnson, S. Wente and X. Zhao for reagents; H. Bretes, L. Fusée and G. Lelandais for help with strain construction, in vitro experiments and data normalization, respectively; D. Tollervey for CRAC analyses; A. Babour, V. Doye, T.H. Jensen and R. Rothstein for discussion and critical reading of the manuscript. This work was supported by: CNRS (to B.P.); Fondation ARC pour la Recherche sur le Cancer (to B.P.); Ligue Nationale contre le Cancer (to B.P.; fellowship to J.O.R.); Ecole Doctorale "Structure et Dynamique des Systèmes Vivants" (#576), Université Paris-Sud, Université Paris-Saclay (fellowship to J.O.R.); and the "Who am I?" laboratory of excellence (grant numbers ANR-11-LABX-0071, ANR-11-IDEX-0005-02, fellowship to J.O.R.).

Data availability. The complete microarray data are available in the ArrayExpress database under accession number E-MTAB-6065 (https://www.ebi.ac.uk/ arrayexpress/experiments/E-MTAB-6065/). The uncropped scans of the blot images shown in Figures are provided in the Supplementary Fig. 5. All the other data supporting the findings of this study are available within the paper and its supplementary information files, or from the corresponding author upon request.

of read mapped to Luciferase control RNA (Promega) and final library size. D. Venn diagrams of identified genes before and after removing Halo genes. E. Celf1 targets (inBulfoni) were compared with one CLIP experiment (inLeTonqueze) and one RIP (inHeng) both performed in HeLa cells. F. Overlap between Angel1-WT and Angel1-YALA targets after Halo removal.

G. Analysis of RBPs that bind to the 5' and 3' UTR of the transcripts of the targets shared by Angel1 and Angel1 YA. Analysis of Angel1 expression during cell differentiation from embryonic stem cells to pancreatic endoderm.

SunSET

Sunsets experiment were performed in two biological independent replicates. Cells treated as described above were then pulsed with 10 µg/ml puromycin for 10 minutes, lysed and equal amounts of proteins were analyzed by Western-blot analysis.

Western-blot & Antibodies

Protein concentrations were quantified using a Pierce BCA Protein Assay Kit (Thermo Fisher Scientific). Proteins (20 μg) were resolved by SDS-PAGE and transferred to a membrane using an iBlot2 Gel Transfer Device (Thermo Fisher Scientific). Membranes were incubated with specific primary antibodies: anti puromycin (MABE343 Merck-millipore), anti phospho-Ser52-eIF2α (SAB4300221 Sigma), anti eIF2α (SAB4500729 Sigma), anti rps6 (2217 Cell signaling) anti phospho-Ser235/6-rps6 (2211 Cell signaling) and anti-tubulin (T9026 Sigma).

Membranes were incubated with species-specific horseradish peroxidase-linked secondary antibodies (1:10,000) and visualized after enhanced chemiluminescence exposure.

Polysome profiling

Polysome profiling was performed on three independent cell cultures both in high (20 mM glucose) or low (0.5 mM glucose) and each replicate corresponded to approximately 30 million cells. After the glucose treatment, cells were washed once in ice cold PBS containing 100 µg/ml Cycloheximide. The PBS was then removed and the Lysis buffer (80 mM KCl, 10 mM Tris pH7.4, 5 mM MgCl2, 0.5% Triton X 100, 0.5% Na-Deoxycholate, 40U/ µL RNAsin, 1 mM DTT) was added directly to the plate and cells were scraped and collected. After 10 minutes incubation on ice, the lysates were centrifuge at 10000 Xg for 5 min at 4°C. 10 A254 units of lysates were layered onto a 11 ml 20-50% (wt/vol) sucrose gradient prepared in the lysis buffer without Triton X-100. The samples were ultra-centrifuged at 39,000 × g for 2.5 h at 4 °C in a SW41 rotor. The gradients were fractionated in 14 fractions of 0.9 ml using an ISCO fractionation system with concomitant measurement of A254. Total lysates and fractions were supplemented with 50 µl of 3 M NH4Ac, 10 ng of Luciferase RNA (Promega), 1 µl of Glycoblue (Ambion) and 1.2 ml of ethanol. Samples were vortexed and precipitated overnight at -20 °C.

The pellets were collected by centrifugation at 10,000 × g for 10 min at 4 °C, washed once in 75% ethanol and resuspended in 100 µl DEPC-treated H2O. Sample were then treated for 1 hour at 37°C with RQ1 DNase (Promega) to remove possible contaminations by DNA. RNAs were isolated by acid phenol: chloroform and precipitated in 1 ml Ethanol supplemented with (supplemented with 50 µL 3M NaOAc pH 5.2, 1 µl of glycoblue). Pellets were resuspended in 20 ul DEPC-treated H2O. For sequencing equal volumes of fractions were pooled: fractions 5-6 (Monosomes), fractions 7-9 (Light polysomes) and fractions 10-13 (Heavy polysomes).

Quality and quantity of pooled fraction was tested by the bioanalyzer RNA 6000 Pico kit 105 (Agilent). Sequencing was performed by the Genom'ic platform (Institut Cochin, Paris).

Libraries were prepared using TruSeq RNA Library Preparation Kit (Illumina) with rRNA depletion using Ribo-zero rRNA removal kit (illumina) following manufacturer's instruction.

High-throughput sequencing was performed using Hiseq 2000 (Illumina) system for 75nt single-end sequencing.

Equal volumes of all samples were reverse transcribed with Superscript IV reverse transcriptase (Life Technologies) and cDNAs were further quantified by real-time PCR.

Bioinformatic analysis of Transcriptome and Polysome sequencing

Preprocessing

Raw fastq file obtained from the sequencer were firstly checked for their quality using MultiQC v1.6 [START_REF] Ewels | MultiQC: summarize analysis results for multiple tools and samples in a single report[END_REF]. No reads were discarded nor trimmed.

Mapping and read counts and TPM calculation

Quality controlled reads were then mapped to the human genome (GRCh38 from Ensembl 92) using STAR 2.6 (Dobin et al., 2013) by using the parameter --quantMode GeneCounts to generate gene counts tables. STAR aligner was further instructed to generate an output (--quantMode TranscriptomeSAM) suitable as an input for RSEM [START_REF] Li | RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome[END_REF]. RSEM reports tables with transcript per million (TPM) for both genes and mRNA isoforms [START_REF] Wagner | Measurement of mRNA abundance using RNAseq data: RPKM measure is inconsistent among samples[END_REF]. For all the rest of downstream analyses, genes were filtered to retain only the genes which are annotated as protein coding in the Ensembl 93 annotation tables.

Filtering of lowly expressed genes

Gene counts table were transformed in log CPM (Counts per Million base). Genes whose CPM values were smaller than 1 at least in one sample were discarded. Then a customized R function further filtered genes whose coefficient of variation (defined as the ratio of the standard deviation over the mean CV = ) intra replicates was lower than 0.75 and the mean CPM expression intra-replicates was higher than 4. As a first step for quality control of our datasets we performed a hierarchical clustering analysis by using the TPM tables for each sample. Clustering was performed on the Euclidean distance matrix and the Ward's minimum variance method was used for forming clusters (option Ward.D2 in the hclust () function of R).

Differential expression analysis and clustering

Analyses were performed using EdgeR (Robinson et al., 2010) and Limma [START_REF] Ritchie | limma powers differential expression analyses for RNA-sequencing and microarray studies[END_REF] Bioconductor packages. Differentially expressed genes (DEGs) were identified applying the Ebayes Only genes with adjusted p-value ≤ 0.05 were selected. A unique list containing the TPM (transcripts per million reads) values was used for downstream analysis. The average expression of each gene was calculated in each fraction (monosomes, light polysome and heavy polysomes) and condition (low or high glucose) was calculated. Then for each of

Additional information

Supplementary Information accompanies this paper at https://doi.org/10.1038/s41467-018-03673-3.

Competing interests: The authors declare no competing interests.

Reprints and permission information is available online at http://npg.nature.com/ reprintsandpermissions/ Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Annexes

As annex you will find:

-A review where I participated in describing our knowledge about the eIF4E Interacting

Partners by describing Angel1 function.

-The supplementary material of the article in chapter 3: A SUMO-dependent feedback loop senses and controls the biogenesis of nuclear pore subunits.

SUPPLEMENTARY INFORMATION

A SUMO-dependent feedback loop senses and controls the biogenesis of nuclear pore subunits

Rouvière et al.

Supplementary Information includes:

Supplementary Figures 12345Supplementary INM, inner nuclear membrane. b, NPC mRNAs levels (mean ± SD; n=3; relative to rRNA) were measured by RT-qPCR in HEK2-pA strains. Hek2-bound NPC mRNAs appear in yellow. c, RBP binding was analyzed as in Fig. 1a for mRNAs encoding proteasome or exosome subunits. d, Hpr1-associated mRNAs were immunopurified using anti-Hpr1

antibodies 1 and quantified by RT-qPCR using specific primer pairs. Percentages of IP (mean ± SD; n=3) are the ratios between purified and input RNAs, set to 1 for hpr1∆ control cells. e, Recombinant GST was incubated with streptavidin beads either naïve (Φ) or previously coated with biotinylated RNA probes encompassing Hek2-binding sites from NSP1 or NUP116. Decreasing amounts of input and eluate fractions were loaded to allow comparison as in Fig. 1e.

Supplementary Figure 2 (see legend on next page).

Supplementary Figure 2. Hek2 binding does not affect the levels of NPC mRNA but rather modulates their ribosome occupancy. a, mRNAs were split in four categories depending on their binding to Hek2 2 . For each group of transcripts, the averaged log2 of the hek2∆/wt ratios calculated from two independent microarray hybridizations were plotted. Boxplots were generated using KaleidaGraph (Synergy Software): each box encloses 50% of the values, the median is displayed as a line, and the bars extending from the top and bottom of each box mark the minimum and maximum values within the dataset falling within an acceptable range. Values falling outside of this range are displayed as individual points.

mRNAs encoding NPCs components are highlighted in two different colors depending on their association to Hek2.

Note that mRNAs strongly bound by Hek2 tend to be less abundant in the absence of this protein. * P<0.5; ***P<0.001

(Mann-Whitney-Wilcoxon test). b, The same analysis as in a. was performed after grouping the transcripts according to their binding to Nab2 3 . Note the absence of correlation between Nab2 binding and the changes in mRNA levels scored upon HEK2 inactivation. N.S, not significant. c, Polysome fractionation from wt and hek2∆ cells from the BY4742 background. The absorbance at 254nm (A 254 ) recorded during the collection of the different fractions of the sucrose gradient is displayed. The positions of 40S, 60S, 80S ribosomal species and polysomes are indicated, as well as the number of ribosomes per mRNA in the polysomes fractions. Note that polysome profiles from these hek2∆ mutant cells exhibit reproducible discontinuities typical of half-mer formation, i.e. polysomes lacking stoichiometric amounts of both 60S and 40S ribosomal subunits. While this phenotype could reflect impaired 60S biogenesis, defective coupling of 60S subunits to 40S-mRNA complexes or general translational derepression 4,5,6 , it was not observed in hek2∆ mutant cells of an alternate genetic background (W303, Fig. 2c), suggesting that it is not solely caused by HEK2 inactivation. Note that this analysis does not include the nucleoporins that are part of other cellular complexes (i.e. Ndc1, Sec13, Seh1) or those for which abundances data were not available (Nup116, Nup145, Nup120, Nup2, Nup42, Pom34). Homozygous and heterozygous deletion strains were obtained from the Euroscarf deletion collection (www.euroscarf.de). GFP-tagged strains were purchased from Invitrogen.

Supplementary

* obtained by transformation and/or successive crosses. a. HEK2 was deleted by homologous recombination with a cassette amplified from pFA6a-kanMX6. b. HEK2 was C-terminally tagged with 3 HA repeats by homologous recombination with a cassette amplified from pFA6a-3HA-kanMX6. c. Segregant of a heterozygous diploid ulp1::kanMX/ULP1+ transformed with the YCpLac22-HIS3-ulp1-333 construct. d. Segregant of a heterozygous diploid ubc9::kanMX/UBC9+ transformed with the pRS315-ubc9-1 construct. e. Segregant of a heterozygous diploid smt3::kanMX/SMT3+ transformed with the pRS316-SMT3 construct. f. Segregant of a diploid obtained by mating ulp1 and SMT3 shuffle strains, transforming with the pYES2-LEU2-His-Flag-SMT3 construct and further growing on 5FOA to counterselect the SMT3-URA3 plasmid. g. ULP1 was C-terminally tagged with GFP by homologous recombination with a cassette amplified from the ULP1-GFP strain (Invitrogen).

Supplementary References