Audrey Cochard

Adham Safieddine

Pauline Combe

Marie-Noëlle Benassy

Dominique Weil

Zoher Gueroui
email: zoher.gueroui@ens.fr

Condensate functionalization with motors directs their nucleation in space and allows manipulating RNA localization

The localization of RNAs in cells is critical for many cellular processes. Whereas motor-driven transport of RNP condensates plays a prominent role in RNA localization in cells, their studies remain limited by the scarcity of available tools allowing to manipulate condensates in a spatial manner. To fill this gap, we reconstitute in cellula a minimal RNP transport system based on bioengineered condensates which were functionalized with kinesins and dynein-like motors, allowing for their positioning at either the cell periphery or centrosomes. This targeting mostly occurs through the active transport of the condensate scaffolds, which leads to localized nucleation of phase-separated condensates. Then, programming the condensates to recruit specific mRNAs is able to shift the localization of these mRNAs towards the cell periphery or the centrosomes. Our method opens novel perspectives to examine the role of RNA localization as a driver of cellular functions.

INTRODUCTION

The spatial organization of signaling network and biochemical reactions is of vital importance for many cellular functions. To organize the cell inner space, biomolecules and subcellular structures can be dispatched by active transport mechanisms. Long-range motorbased transport of cellular compartments along cytoskeletal networks is essential for rapid reorganization of the cellular space in response to environmental changes 1 . Microtubule-based transport is for instance necessary for the endocytic pathway, for long-distance transport of mitochondria and for lipid droplets contacts with organelles [START_REF] Granger | The role of the cytoskeleton and molecular motors in endosomal dynamics[END_REF][START_REF] Kilwein | Lipid Droplet Motility and Organelle Contacts[END_REF][START_REF] Melkov | Regulation of long-distance transport of mitochondria along microtubules[END_REF] . Although less documented than membrane-bound organelles, biomolecular condensates are also prone to interact with cytoskeletal fibers in various ways. As the main microtubule organizing center, the centrosome can be viewed as a condensate facilitating microtubule nucleation by concentrating tubulins [START_REF] Woodruff | The Centrosome Is a Selective Condensate that Nucleates Microtubules by Concentrating Tubulin[END_REF] . Other examples include RNA-containing condensates such as stress granules and P-bodies, whose growth by fusion and disassembly by fission involves by microtubule-based transport 6- 11 . The functional importance of condensate-microtubule interactions is also exemplified by the transport and localization of mRNAs through RNP granule transport.

Subcellular mRNA localization is a widespread process that involves mRNA transport as isolated molecules or as part of phase-separated RNP condensates [START_REF] Engel | Mechanisms and consequences of subcellular RNA localization across diverse cell types[END_REF][START_REF] Ryder | RNA localization regulates diverse and dynamic cellular processes[END_REF] . This localization is vital for many developmental and cellular processes, from the establishment of embryo polarization to local protein synthesis at the synapses [START_REF] Martin | mRNA Localization: Gene Expression in the Spatial Dimension[END_REF][START_REF] Eliscovich | RNP transport in cell biology: the long and winding road[END_REF] . Motor-based positioning of specific mRNAs and subsequent local translation has for instance been described during the establishment of asymmetrical processes such as morphogen gradients in developing embryo 16- 19 , cell migration [START_REF] Herbert | Sending messages in moving cells: mRNA localization and the regulation of cell migration[END_REF] , neural development and synaptic plasticity [START_REF] Holt | Local translation in neurons: visualization and function[END_REF][START_REF] Costa | The functional organization of axonal mRNA transport and translation[END_REF] . Additionally, disruption of axonal RNP granule transport is associated with a broad range of neurodegenerative diseases [START_REF] Mofatteh | Neurodegeneration and axonal mRNA transportation[END_REF][START_REF] Lin | Axonal mRNA translation in neurological disorders[END_REF] . Localizing mRNAs and RNP granules, rather than proteins, into subcellular compartments before translation favors spatially restricted protein synthesis and provides 'outposts' operating far from the soma [START_REF] Jansen | mRNA localization: message on the move[END_REF][START_REF] Holt | The Central Dogma Decentralized: New Perspectives on RNA Function and Local Translation in Neurons[END_REF] . In addition, localizing mRNAs is likely to be more energy-efficient than moving separately each protein to the right location [START_REF] Jansen | mRNA localization: message on the move[END_REF] .

Due to the critical importance of RNA localization to cell fate determination, numerous methods were recently developed to describe how RNAs find their way to distinct subcellular compartments, and how this impacts RNA functions and processing. For example, the direct visualization of RNA molecules in living cells and organisms has been instrumental to elaborate our current understanding of RNA localization mechanisms [START_REF] Weil | Making the message clear: visualizing mRNA localization[END_REF][START_REF] Pichon | A Growing Toolbox to Image Gene Expression in Single Cells: Sensitive Approaches for Demanding Challenges[END_REF] . Complementary to imaging approaches, transcriptomic RNA sequencing-based methods also described a variety of RNAs enriched in specific subcellular areas [START_REF] Lécuyer | Global Analysis of mRNA Localization Reveals a Prominent Role in Organizing Cellular Architecture and Function[END_REF][START_REF] Fazal | Atlas of Subcellular RNA Localization Revealed by APEX-Seq[END_REF][START_REF] Taliaferro | Genomic analysis of RNA localization[END_REF] . Motor proteins from all three families, i.e., kinesin, dynein, and myosin, have been identified as the drivers of short-and long-range mRNA transport along the cytoskeleton [START_REF] Kanai | Kinesin transports RNA: Isolation and characterization of an RNA-transporting granule[END_REF][START_REF] Gagnon | Molecular Motors: Directing Traffic during RNA Localization[END_REF] . Though further studies are necessary to decipher the building blocks required to recruit, direct and release specific mRNAs to a particular destination, one recurrent scenario involves RNA binding proteins (RBP) and motor adaptors, linking mRNAs and motor proteins [START_REF] Engel | Mechanisms and consequences of subcellular RNA localization across diverse cell types[END_REF][START_REF] Rodrigues | Mammalian Neuronal mRNA Transport Complexes: The Few Knowns and the Many Unknowns[END_REF][START_REF] Das | Intracellular mRNA transport and localized translation[END_REF][START_REF] Buxbaum | In the right place at the right time: visualizing and understanding mRNA localization[END_REF][START_REF] Baumann | A reconstituted mammalian APC-kinesin complex selectively transports defined packages of axonal mRNAs[END_REF] .

Beside its role in guiding long-range transport, the cytoskeleton also contributes to the mechanical integrity of cells. Due to its inherent heterogeneity and dynamic nature, determining how such a meshwork impacts RNP condensation remains difficult to quantify. Yet, some biophysical implications of the cytoskeleton meshwork on phase separation mechanisms have recently started to be investigated both theoretically or experimentally. For example, the cytoskeleton modeled as an elastic meshwork, and acting at length scales comparable to condensate sizes, has been seen to modify nucleation and coarsening of phase separation systems [START_REF]Elastic ripening and inhibition of liquid-liquid phase separation[END_REF][START_REF] Vidal-Henriquez | Cavitation controls droplet sizes in elastic media[END_REF][START_REF] Martin | Liquid demixing in elastic networks: Cavitation, permeation, or size selection?[END_REF] . In the very large Xenopus oocytes, the actin meshwork provides steric hindrance limiting nucleolar fusion as well as counter balancing sedimentation by gravity [START_REF] Feric | A nuclear F-actin scaffold stabilizes RNP droplets against gravity in large cells[END_REF] . In epithelial cells, it has been shown that weak and non-specific interactions between cytoskeleton elements and the condensate surface may account for mutual influences [START_REF] Böddeker | Non-specific adhesive forces between filaments and membraneless organelles[END_REF] . One missing element in this description is the effect of molecular motors on phase-separated condensates to explore how transport could shape condensate formation and localization. To fill this gap, and examine how motor proteins could impact RNP phase separation, we adopted an approach allowing the reconstitution in cells of motor-functionalized condensates.

Novel tools have been developed allowing the formation of artificial condensates with programmable properties in cells. Indeed, such technologies bring novel perspectives both for addressing new biological questions and for further biotechnological improvements [START_REF] Shin | Spatiotemporal Control of Intracellular Phase Transitions Using Light-Activated optoDroplets[END_REF][START_REF] Bracha | Mapping Local and Global Liquid Phase Behavior in Living Cells Using Photo-Oligomerizable Seeds[END_REF][START_REF] Nakamura | Intracellular production of hydrogels and synthetic RNA granules by multivalent molecular interactions[END_REF][START_REF] Navarro | RNA is a critical element for the sizing and the composition of phase-separated RNA-protein condensates[END_REF][START_REF] Zhao | Light-based control of metabolic flux through assembly of synthetic organelles[END_REF][START_REF] Reinkemeier | Designer membraneless organelles enable codon reassignment of selected mRNAs in eukaryotes[END_REF][START_REF] Heidenreich | Designer protein assemblies with tunable phase diagrams in living cells[END_REF][START_REF] Dzuricky | De novo engineering of intracellular condensates using artificial disordered proteins[END_REF][START_REF] Yoshikawa | Synthetic Protein Condensates That Inducibly Recruit and Release Protein Activity in Living Cells[END_REF][START_REF] Lasker | A modular platform for engineering function of natural and synthetic biomolecular condensates[END_REF][START_REF] Garabedian | Designer membraneless organelles sequester native factors for control of cell behavior[END_REF][START_REF] Cochard | RNA at the surface of phase-separated condensates impacts their size and number[END_REF] . In this context, we engineered artificial condensates made of protein scaffolds that are prone to phase separate and functionalized them to interact with microtubule-bound motor proteins. Our first aim was to examine how motor proteins would affect condensate formation and localization. A second goal was to build minimal RNP condensates recruiting a unique RNA, making it possible to explore condensate-mediated RNA delocalization.

Condensates are thought to form through liquid-liquid phase separation (LLPS) induced by weakly interacting multivalent biomolecules. Based on this observation, our system relies on a self-interacting multivalent protein driving the formation of the condensates and fused to microtubule-interacting domains (from either a motor protein or a motor adaptor). We previously developed the ArtiGranule system, which relies on multivalent cores of ferritin monomers cross-linked by the self-interacting domain F36M-FKBP (Fm) [START_REF] Navarro | RNA is a critical element for the sizing and the composition of phase-separated RNA-protein condensates[END_REF][START_REF] Cochard | RNA at the surface of phase-separated condensates impacts their size and number[END_REF] . Here, we replaced the ferritin core by a multimerization domain consisting of five consecutive Fm repeats (5Fm) [START_REF] Rollins | A ligand-reversible dimerization system for controlling protein-protein interactions[END_REF] . We investigated two plus-end motors (KIF1A and KIF5B), one minus-end motor (KIFC1) and one adaptor of the dynein motor protein (BICD2). We first showed that the resulting scaffold proteins underwent LLPS in cells and that condensates functionalized with plus-end kinesins (thereafter called plus-end motor-condensates) were robustly positioned at the edge of cells. In contrast, condensates functionalized with the minus-end kinesin or the dynein adaptor (thereafter called minus-end motor-condensates) eventually formed a unique body at the centrosome. Interestingly, the localization of condensates was determined at the nucleation step. Our observations support a two-step process; first, motors moved quickly either towards the cell periphery or the centrosome, depending on the motor; then this led to the local accumulation of the multivalent protein on microtubules, and eventually to the formation of asymmetrically positioned large condensates through phase separation. In the case of BICD2, we additionally observed some condensate nucleation throughout the cytosol, followed by their directed transport to the vicinity of the centrosome and their coalescence.

In addition to our assay based on constitutive interactions between condensates with microtubules, we also developed a system where condensate interaction with motors or dynein adaptors could be chemically triggered using a chemically-inducible dimerization strategy [START_REF] Fegan | Chemically Controlled Protein Assembly: Techniques and Applications[END_REF] . Here, we observed that, upon induction of their interaction with the cytoskeleton, preformed condensates re-localized at the cell periphery or at the centrosomes, depending on the directionality of the motors.

Finally, we engineered motor condensates programmed to recruit either exogenous or endogenous mRNAs, using the MS2-MCP (MS2 Coat Protein) system. We found that bifunctionalized condensates, with both MCP and motor proteins (motor/MCP condensates), were asymmetrical positioned in cells and recruited heterologous MS2-containing mRNAs. We then studied the ASPM mRNA, which normally localizes at the centrosome during mitosis [START_REF] Safieddine | A choreography of centrosomal mRNAs reveals a conserved localization mechanism involving active polysome transport[END_REF] and showed that our motor/MCP condensates successfully perturb the spatial distribution of endogenous MS2-tagged ASPM mRNA.

RESULTS

Plus-end motor condensates localize at the periphery of cells

To build model condensates functionalized with plus-end kinesin motors in living cells, we generated a chimeric construct composed of two functional parts: a multivalent protein domain triggering LLPS in cells, fused to a kinesin motor domain to ensure trafficking along microtubule tracks. As a multivalent protein domain, we designed the 5Fm module, composed of five repetitions of the dimerizable mutant F36M of the FKBP protein (Fm) (Fig. 1A) [START_REF] Rollins | A ligand-reversible dimerization system for controlling protein-protein interactions[END_REF] . Expression of emGFP-5Fm and mCh-5Fm in HeLa cells for 24h led to the formation of hybrid micrometric condensates composed of both emGFP and mCherry fusion proteins and randomly localized throughout the cytosolic space (Fig. 1B, left panel). For the kinesin motor domain, we first considered a truncation of the human kinesin-3 KIF1A (aa 1-383), which ensures the processivity of the motor (Fig. 1A) [START_REF] Nijenhuis | An optimized toolbox for the optogenetic control of intracellular transport[END_REF][START_REF] Hammond | Mammalian Kinesin-3 Motors Are Dimeric In Vivo and Move by Processive Motility upon Release of Autoinhibition[END_REF] . KIF1A(1-383) was fused to emGFP-5Fm (giving rise to the KIF1A-emGFP-5Fm plasmid), and the localization of the fusion protein was compared to the control LLPS scaffold emGFP-5Fm lacking any motor. Interestingly, when both the motor-LLPS scaffold (KIF1A-emGFP-5Fm) and the LLPS scaffold (mCh-5Fm) were coexpressed in HeLa cells during 24h, chimeric condensates were mostly found localized at the vicinity of the cell periphery, next to the membrane. In these conditions, almost all cells displayed highly asymmetrical localization patterns, often consisting of 3-5 micrometric condensates per cell (Fig. 1B, middle panel). To quantify the degree of asymmetry among cells, we measured the fraction of mCherry fluorescence, i.e. of the non-motor part of the scaffold, in the 25% peripheral area of the cells (I25) (Methods) [START_REF] Nijenhuis | An optimized toolbox for the optogenetic control of intracellular transport[END_REF] . Using the motor-less scaffold, as expected, condensates did not display any asymmetrical positioning and gave a I25 value of 20% +/-9% (mean +/-SD, Fig. 1C). In contrast, for the chimeric condensates containing the KIF1A(1-383) motor, the I25 value was higher (34 +/-9 %), in accordance with the visualization of asymmetric patterns. Therefore, KIF1A condensates are efficiently localized at the cell periphery.

In order to extend our assay, we next examined cells expressing a second plus-end directed motor domain fused to LLPS scaffolds, KIF5B(1-555)-emGFP-5Fm (Fig. 1A). The KIF5B(1-555) truncated proteins contains the motor and neck domains and part of the coiledcoil domain of mouse KIF5B [START_REF] Id | Reversible association with motor proteins (RAMP): A streptavidinbased method to manipulate organelle positioning[END_REF] . As with KIF1A-LLPS scaffolds, epifluorescence imaging of HeLa cells 24 h after co-transfection of KIF5B-LLPS scaffolds (KIF5B-emGFP-5Fm) and LLPS scaffolds (mCh-5Fm) showed an asymmetrical localization of condensates at the periphery of cells (Fig. 1B, right panel). In accordance with these observations, the I25 value was 32% +/-8% (mean +/-SD, Fig. 1C). Altogether our data showed that plus-end kinesin condensates are robustly positioned at the edge of cells.

To verify that the motor domain needs to be part of the LLPS scaffold for the condensate to be relocated, we examined the localization of non-functionalized LLPS scaffold (mCh-5Fm) in the presence of motor domains lacking the 5Fm multivalent domain (KIF1A-emGFP or KIF5B-emGFP). In these conditions, mCherry condensates were randomly dispersed throughout the cytosol, (Fig. S1A, red), whereas the motor domains accumulated in some regions of the cell periphery as expected (Fig. S1A, green). As a second control, we assessed the importance of multivalent LLPS scaffold interactions in the localization of plus-end motor condensates. By design, condensates should be disrupted by adding a competitive ligand of Fm dimerization (FK506). HeLa cells were transfected with KIF1A-emGFP-5Fm and mCh-5Fm, and FK506 was added at micromolar range either directly after transfection (to probe condensate formation) or 24 hours after transfection (to probe condensate dissociation). In both situations, after 26 hours of transfection, we found an absence of condensates (Fig. S1B,red) and a motor domain signal that either formed a gradient of concentration towards some regions of the cell periphery or was homogeneously diffuse in the cytoplasm (Fig. S1B, green). Timelapse microscopy following addition of FK506 24 h after transfection showed a very fast dissolution of the condensates, with the LLPS scaffold (mCherry signal) diffusing in the whole cell in a few seconds and the motor-LLPS scaffold (emGFP signal) losing its condensed state but remaining at the cell periphery. Our method thus allows for the controlled inhibition and disassembly of plus-end motor condensates upon drug addition.

Dynamics of formation and localization of plus-end motor condensates

While condensate positioning at the cell periphery is consistent with an active transport mediated by plus-end motors along microtubules, the localization kinetics remained to be determined. One possible chronology is, first, condensate nucleation throughout the cytosol, followed by condensate transport along microtubules. Alternatively, transport of LLPS scaffolds powered by motors could first induce their accumulation at peripherical sites, which would then trigger local condensate nucleation. To distinguish between the two scenarios, we monitored the early times of condensate formation using time-lapse microscopy (Supplementary movie 1). 4 h after co-transfection of KIF1A-LLPS and LLPS scaffolds (KIF1A-emGFP-5Fm and mCh-5Fm), we firstly noticed the strong accumulation of the motor scaffolds at the tips of the cells, illustrating the capacity of kinesins to localize within short time scales (Fig. 1D). Very often, the fast peripheral nucleation of KIF1A condensates occurred as soon as fluorescent KIF1A-LLPS scaffolds became detectable in the cytosol (Fig. 1E). These condensates tended to grow to eventually form large spherical bodies that could reach few micrometers. In addition, nearby condensates tended to coalesce (Fig. 1F).

Interestingly, we found that KIF1A-LLPS scaffolds condensed systematically ahead of LLPS scaffolds, with LLPS scaffolds then accumulating in preformed KIF1A condensates (Fig. 1D). This contrasts with the intrinsic ability of LLPS scaffolds to form randomly localized condensates, as seen in cells expressing KIF1A-emGFP lacking the LLPS domain (Fig. S1A).

Altogether, these observations indicate that KIF1A condensates recruit the non-functionalized LLPS scaffolds, thus preventing their independent phase separation. In addition to peripheral condensate nucleation, we also observed rare events of long-ranged (2 to 5 µm/min) condensate transports towards the periphery (Fig. S1C).

The same dynamic characteristics were found when observing the formation of KIF5B condensates (KIF5B-emGFP-5Fm and mCherry-5Fm) (Supplementary movie 2). Early observations of KIF5B-LLPS scaffolds showed an immediate asymmetrical pattern, with a sharp gradient of fluorescence forming at the membrane and shortly preceding nucleation events (Fig. 1G). The condensation of KIF5B-LLPS scaffolds at the cell periphery also occurred ahead, followed by the recruitment of LLPS scaffolds (Fig. 1H). Condensates in close proximity tended to coalesce (Fig. 1I). As for KIF1A condensates, rare directed transport events were observed (Fig. S1D).

Taken together, our observations showed that condensate positioning at the cell periphery occurred predominantly by nucleating phase separation directly at the final sites rather than by transporting already formed condensates to their destination.

Minus-end motor condensates localize at the centrosomes

We next examined the positioning of condensates using minus-end motors conjugated to LLPS scaffolds. We first used the human KIFC1(125-673) truncation that includes the coiled coil and motor domains required for motor processing [START_REF] Id | Reversible association with motor proteins (RAMP): A streptavidinbased method to manipulate organelle positioning[END_REF] . KIFC1(125-673) was fused to emGFP-5Fm, and the resulting emGFP-5Fm-KIFC1 scaffold was co-transfected along with the LLPS scaffold (mCh-5Fm) in HeLa cells (Fig. 2A). Strikingly, after 24 h of expression, most cells displayed a single condensate in the cytosol near the nucleus (mean number of condensates per cell = 1.4 +/-0.9, Fig. 2B, middle panel, and Fig. 2C). This contrasted with control cells transfected only with LLPS scaffolds (emGFP-5Fm and mCh-5Fm), which displayed in average 4 condensates per cell (mean +/-SD = 4.0 +/-3.0, Fig. 2B, left panel, and Fig. 2C). As an alternative to minus-end kinesin motor, we also assessed the mouse dynein adaptor BICD2 (aa 15-595) [START_REF] Id | Reversible association with motor proteins (RAMP): A streptavidinbased method to manipulate organelle positioning[END_REF] . We co-transfected BICD2-emGFP-5Fm along with the LLPS scaffold (mCh-5Fm) in HeLa cells (Fig. 2A). As observed with KIFC1, most cells displayed after 24 h a single condensate localized near the nucleus (mean number per cell = 1.2 +/-0.6, Fig. 2B, right panel, and Fig. 2C). Interestingly, for both KIFC1 and BICD2, the single condensates docked at the centrosomes, as demonstrated by immunostaining of pericentrin (Fig. 2D). Altogether, minusend motor functionalization of LLPS scaffold robustly led to the formation of a single condensate at the centrosome.

As expected, the control co-expression of motor constructs lacking the LLPS multivalent domain (emGFP-KIFC1 or BICD2-emGFP) and non-functionalized LLPS scaffold (mCh-5Fm) led to cells displaying mCherry condensates randomly distributed though the cytosol (Fig. S2A). Of note, unlike the efficient peripheric localization of KIF1A-emGFP and KIF5B-emGFP, we observed little centrosomal accumulation of emGFP-KIFC1 or BICD2-emGFP. As for the plus-end kinesin scaffolds, adding the Fm competitor ligand FK506, immediately or 24h after transfection, suppressed condensates (Fig. S2B). These controls demonstrated the requirement of motor-LLPS scaffolds to localize condensates, as well as the need of a multivalent scaffold to trigger LLPS.

Dynamics of formation and localization of minus-end motor condensates

To examine the pathway leading to the emergence of single condensates at the centrosomes, we monitored the early steps of their formation, starting 4 hours after transfection of emGFP-5Fm-KIFC1 or BICD2-emGFP-5Fm along with mCh-5Fm (Supplementary movies 3 and 4). In both cases, we found that condensates primarily nucleated at the vicinity of the nucleus (Fig. 2E-F). This led to the emergence of a single condensate that kept on growing, including by coalescence of smaller condensates appearing nearby. As observed with the plusend motors, the non-functionalized scaffold accumulated exclusively at the site of motor condensates (Fig. 2E-F). In the case of BICD2 condensates, we also observed long-range transport of condensates nucleated far from the nucleus, coalescing into one large condensate during transport (Fig. 2F andS2C).

Taken together, our observations showed that minus-end motor condensates mainly nucleate at the vicinity of the nucleus, and then recruit non-functionalized scaffolds.

The timing of non-functionalized scaffold enrichment into motor condensates depends on their localization in cells

One interesting feature shared by the four motor condensates is their ability to capture the non-functionalized LLPS scaffolds. Yet, the intracellular space being very heterogenous in term of physical properties, such as crowding and geometry, condensates' subcellular location may impact some of their characteristics. To examine further this aspect, we studied more closely the enrichment of non-functionalized scaffolds into condensates depending on their localization in cells. We quantified the delay between the initial nucleation of motor condensates and the first discernible enrichment of the non-functionalized LLPS scaffold. We found that co-localization occurred after 1 to 2 hours using the plus-end motors (mean 83 min with a coefficient of variation CV of 40% and 74 min with a CV of 39% for KIF1A and KIF5B, respectively, Fig. 3A and3B), contrasting with less than 20 min using the minus-end motors (mean 8 min with CV of 163% and 18 min with CV of 89% for KIFC1 and BICD2, respectively, Fig. 3A and3C). Therefore, the delay of LLPS scaffold enrichment into preformed motor condensates was much longer for plus-end than minus-end motors. This difference in temporality may result from two non-exclusives factors: first, plus-end and minus-end motor condensates localized in two different areas of the cell where the pool of available LLPS scaffold may strongly differ because of the cell geometry, narrower at the periphery than close to the nucleus (Fig. 3D). Additionally, molecular crowding may strongly vary between the centrosome and the cell membrane area. Secondly, the processivity of our plus-end and minusend motor differ, with only the plus-end motor scaffolds leading a rapid leap in concentration and condensate nucleation (Fig. 1E and1G). Nucleation could thus occur before the nonfunctionalized LLPS scaffold reaches a sufficient concentration for enrichment. Altogether our data show that the timing of the enrichment of non-functionalized scaffolds into motor condensates depends on their localization in cells.

Chemical induction of condensate transport and localization

Several endogenous condensates were found to interact and undergo transport along the cytoskeleton tracks [START_REF] Rajgor | RNA granules and cytoskeletal links[END_REF] . Our motor-LLPS scaffolds could, by design, constitutively interact with microtubule fibers as soon as they are translated. We thus sought to examine the consequence of a sudden induction of the interaction between condensates randomly distributed through the cytosol and molecular motors. To this end, we devised an assay based on the rapamycindependent heterodimerization of FRB and FKBP (Fig. 4A). On one side we fused plus-end and minus-end motors to mCh-FRB (giving rise to KIF1A-mCh-FRB and BICD2-mCh-FRB, respectively) (Fig. 4A). On the other side, we fused our LLPS scaffold emGFP-5Fm to FKBP (FKBP-emGFP-5Fm) (Fig. 4A). We first analyzed the behavior of these proteins in the absence of rapamycin. After 24 h co-expression of FKBP-emGFP-5Fm and either KIF1A-mCh-FRB or BICD2-mCh-FRB, cells displayed several FKBP condensates, randomly dispersed in the cytosol and coexisting without interactions with FRB-fused motors (Fig. 4B). In some cells KIF1A-mCh-FRB accumulated at the cell periphery, while no particular enrichment of BICD2-mCh-FRB could be observed close to the nucleus (Fig. 4B).

We then added rapamycin (24 h after transfection) to induce interaction between the FKBP-condensates and KIF1A-mCh-FRB, and monitored the consequences using time-lapse microscopy. Within a couple of minutes, we could observe some events of long-range condensate transport toward the cell periphery. On Fig. 4C, we report an example of converging motions of condensates, which coalesced together at the cell extremity within a few minutes (Fig. 4D). The other cells, however, did not display obvious transport of condensates, which may be explained if initially the distribution of KIF1A motors was highly polarized towards the plasma membrane, making them unavailable for interaction with disperse condensates.

With BICD2-mCh-FRB, upon addition of rapamycin, we first observed the recruitment of the FRB-fused motor on the surface of the FKBP-emGFP-5Fm condensates, with a distinct mCherry corona forming in less than 1 min (Fig. 4E). Then, BICD2-mCh-FRB diffused towards the inner part of the FKBP condensates, driven by an internal mixing of the components, which occurred within 10 to 30 minutes (depending on the condensate size) (Fig. 4E and4F). Subsequently, two types of directed motions towards the cell center were observed: some condensates were transported in a few minutes with no morphological change (Fig. 4G), while others underwent a striking deformation consistent with the rheological properties of a cytoplasm acting as a stiff and porous meshwork (Fig. 4H) [START_REF] Moeendarbary | The cytoplasm of living cells behaves as a poroelastic material[END_REF] .

In conclusion, this assay allowed to chemically induce the rapid transport of condensates to either the cell periphery or the cell center.

Localizing exogenous RNAs through the spatial positioning of condensates

The co-assembly of RNAs and RBPs into membrane-less organelles could potentially play a role in RNA trafficking to specific subcompartments or distal positions. Using a biomimetic approach, we thus sought to localize mRNAs by engineering motor condensates programmed to recruit a specific mRNA. Our strategy consisted of fusing MCP to our LLPS scaffold to enable the recruitment of RNAs with MS2 stem loops (Fig. 5A) [START_REF] Martin | Liquid demixing in elastic networks: Cavitation, permeation, or size selection?[END_REF] . MCP scaffolds (MCP-5Fm) were then co-transfected with motor-LLPS scaffolds (KIF1A-emGFP-5Fm or BICD2-emGFP-5Fm), and with a plasmid expressing an RNA containing four MS2 repeats (RNA-MS2) (Fig. 5A).

We found that after 24 h of expression, bi-functionalized motor/MCP condensates were efficiently positioned at the cell periphery or at the centrosome depending on the motor's directionality. Using single molecule FISH (smFISH), we demonstrated the recruitment of RNA-MS2 molecules in the motor condensates (each Cy3 dot corresponds to individual RNA molecule) (Fig. 5B). As specificity controls, the endogenous β-actin mRNA lacking MS2 stem loops was not recruited to MCP condensates (Fig. 5C), and the RNA-MS2 was not recruited on condensates lacking MCP (Fig. 5D). Therefore, condensates formed using a combination of motor-and MCP-LLPS scaffolds efficiently and specifically recruit MS2-containing RNAs.

Overall, these results demonstrate the specific localization of RNA via artificial condensates.

Delocalizing endogenously tagged ASPM mRNA using motor condensates

To highlight a second application of our condensates, we aimed to use them as a tool to alter the subcellular localization of an endogenous RNA. To this end, we used a HeLa cell line in which 24 MS2 repeats were inserted in the 3'UTR of the Abnormal Spindle-like Microcephaly-associated (ASPM) gene using CRISPR-Cas9 (HeLa/ASPM-MS2). The resulting clone thus expresses the ASPM-MS2 mRNA in a stable manner, under the control of its endogenous promoter, which can be visualized by smFISH using a probe directed against the MS2 sequence 57 . Like untagged ASPM mRNA, ASPM-MS2 mRNA was weakly expressed during interphase and its expression increased during mitosis, with the mRNA localizing to centrosomes, particularly from early mitotic stages till metaphase (Fig. 6A) [START_REF] Safieddine | A choreography of centrosomal mRNAs reveals a conserved localization mechanism involving active polysome transport[END_REF][START_REF] Chouaib | A Dual Protein-mRNA Localization Screen Reveals Compartmentalized Translation and Widespread Co-translational RNA Targeting[END_REF] . This created a striking local concentration of ASPM-MS2 mRNA on centrosomes making it an ideal candidate for delocalization attempts.

To test this delocalization, we transiently transfected HeLa/ASPM-MS2 cells with our MCP and KIF1A scaffolds (MCP-5Fm with KIF1A-emGFP-5Fm). Remarkably, the KIF1A/MCP condensates successfully delocalized ASPM-MS2 mRNAs away from centrosomes towards the cell membrane across mitosis (Fig. 6B). As a negative control, we expressed condensates without MCP (5Fm only) functionalized with the KIF1A motor (KIF1A-emGFP-5Fm). In this condition, condensates localized at the cell periphery without recruiting ASPM-MS2 mRNA (Fig. 6C,D), thus confirming the specificity of the system. Moreover, we observed three patterns of KIF1A condensates in mitotic cells: local clustering of condensates at the membrane (i); or condensates distributed under the cell membrane producing either a half (ii) or a full (iii) crown pattern (Fig. S3). Interestingly, the ASPM-MS2 mRNA tended to distribute like the condensates, demonstrating the robustness of this tool (Fig. S3).

Conversely, we tested the possibility of forcing centrosomal localization of ASPM-MS2 mRNA in interphasic cells. First, as expected, condensates without motor (formed using emGFP-5Fm) were randomly localized in the cytoplasm and were able to recruit ASPM-MS2 mRNAs only in the presence of MCP-5Fm (Fig. S4A,B). In contrast, the BICD2 scaffold (BICD2-emGFP-5Fm) led to a single condensate at the centrosome, which was able to artificially localize some ASPM-MS2 mRNAs at the vicinity of centrosomes during interphase (Fig. S4C,D), at a time where the mRNA should not localize there.

Taken together, motor condensates are a versatile tool for altering the subcellular localization of RNA in living cells.

DISCUSSION

How is the spatial positioning of biomolecular condensates orchestrated in cells? Whereas many mechanisms of spatial regulation have been described for membrane-bound organelles and other cargos, much less is known for condensates. Yet, despite the diversity of cytoplasmic RNP condensates, including RNA transport granules, stress granules, and P-bodies, one common feature relies on their interactions with microtubule-based cytoskeleton. In this study, we engineered artificial condensates functionalized with kinesin motor and dynein adaptor domains in order to examine their interplay with microtubules and its consequences on condensate formation and localization. We found that motor condensates were robustly positioned at the periphery of cells or at the vicinity of the centrosomes, as predicted from the direction of processivity of the motors. Next, we asked whether one could reconstitute a minimal RNP transport system to localize RNAs in cells. By incorporating MCP proteins into our motor condensates, we succeeded in recruiting MS2-tagged RNAs in asymmetrically positioned condensates.

In a first setting, LLPS scaffolds were directly fused to plus-end motors (KIF1A or KIF5B), or to minus-end motor / motor adaptor (KIFC1 or BICD2) and constitutively expressed in cells. Using this approach, we could investigate the formation of condensates made of proteins prone to phase-separate while interacting with microtubule fibers. Indeed, at early stage, motor-LLPS scaffolds underwent phase separation on microtubule fibers due to motor accumulation at the cell periphery or near the centrosome. One hypothesis is that the accumulation of motor-LLPS scaffolds on microtubule increases their local concentration which may account for their local condensation on microtubule surface lattice. The cooperative binding of the motor-LLPS scaffold on fibers, mediated by the repetitive nature of the LLPS scaffolds, could therefore favor prewetting on microtubules and phase separation below the expected saturation concentration [START_REF] Wiegand | Drops and fibers -how biomolecular condensates and cytoskeletal filaments influence each other[END_REF] . This process has recently been proposed for Tau and TPX2, two microtubule-associated proteins involved in the stabilization/nucleation of microtubule fibers [START_REF] Wiegand | Drops and fibers -how biomolecular condensates and cytoskeletal filaments influence each other[END_REF] , or in a different context for the condensation of the transcription factor Klf4 on DNA molecules [START_REF] Morin | Sequence-dependent surface condensation of a pioneer transcription factor on DNA[END_REF] .

To infer how nucleation of condensates was dependent on the capacity of the scaffolds to interact with microtubules, we monitored both motor-functionalized and non-functionalized LLPS scaffolds. Interestingly, we found that the condensation of the two LLPS scaffolds was sequential, with motor-LLPS scaffolds condensing systematically ahead of non-functionalized LLPS scaffolds. Non-functionalized scaffolds predominately accumulated at the sites of preformed motor condensates (Fig. 1D,1F,2E,2F).

Classical nucleation theory predicts that phase-separated condensates can either form with no specific localization or, in contrast, at specific sites acting as seeds overcoming the kinetic barrier of nucleation. Recent studies showed how specific biomolecules can act as seeds and govern condensate nucleation at specific sites, such as DNA break sites 66 , the membrane 67- 69 , or the apical side of the nucleus for nucleolus [START_REF] Falahati | Nucleation by rRNA Dictates the Precision of Nucleolus Assembly[END_REF] . Our study provides an alternative scheme for the spatial positioning of nucleation. Here, we highlighted the positioning of condensates at polarity sites powered by microtubule-based motor proteins. In our system, condensate positioning occurred predominantly by nucleating phase separation at the destination sites of transported molecules rather than by transporting already formed condensates to their destination. This suggests a two-step mechanism (Fig. 7A): (i) active transport of the condensate scaffolds leading to their localization at polarity sites (microtubules extremities), (ii) nucleation of motor condensates through a mechanism possibly mediated by prewetting or cooperative binding. The pathway to such condensate localization is similar for the four motor domains studied. However, and in contrast to kinesin condensates, we also observed some events of nucleation of BICD2 condensates dispersed throughout the cytosol, which then were transported to the cell centrosome to eventually coalesce into a large condensate (Fig. 2F andS2C). This formation of BICD2 condensates in the cytosol prior to their transportation may be due to the requirement to assemble a high number of dyneins on the condensate surface to generate large collective forces and efficient transport [START_REF] Rai | Molecular adaptations allow dynein to generate large collective forces inside cells[END_REF] . Subsequently, recruitment of nonfunctionalized scaffolds in the preformed condensates could be observed.

Coalescence of smaller BICD2 condensates into one larger condensate is reminiscent of the coalescence of stress granules upon transport along microtubules mediated by the dynein adaptor BICD1 [START_REF] Chernov | Role of microtubules in stress granule assembly: Microtubule dynamical instability favors the formation of micrometric stress granules in cells[END_REF][START_REF] Tsai | STRESS GRANULE DYNAMICS IN PRIMARY NEURONS[END_REF][START_REF] Loschi | Dynein and kinesin regulate stressgranule and P-body dynamics[END_REF][START_REF] Perez-Pepe | Life and Work of Stress Granules and Processing Bodies: New Insights into Their Formation and Function[END_REF] . Previous studies on stress granules emphasized that their assembly follows distinct temporal steps, with first the formation of stable cores through multiple stable interactions, and secondly evolution into larger assemblies by recruiting a less dense shell [START_REF] Wheeler | Distinct stages in stress granule assembly and disassembly[END_REF] . Here, our studies highlight a simple mechanism based on LLPS where compositional complexity of granules builds during assembly processes in a sequential fashion. In our system, the localized nucleation of motor condensates provides a platform for the subsequent enrichment of non-functionalized LLPS scaffolds. This is reminiscent of the sequential localization of mRNAs observed during P-body formation in yeast [START_REF] Simpson | mRNA localization to P-bodies in yeast is bi-phasic with many mRNAs captured in a late Bfr1p-dependent wave[END_REF] . Interestingly, in our system, the timing of enrichment of non-functionalized scaffolds into motor condensates depends on their localization in cells (Fig. 3). Therefore, site-specific nucleation combined with sequential enrichment provides a simple mechanism to build, in an ordered fashion, multicomponent condensates.

Other the last years, several chemical and optogenetic tools have been developed to perturb and control organelles positioning, interactions, and trafficking. Here, inspired by repositioning assays of membrane-bound organelles using chemically-induced dimerization strategy [START_REF] Passmore | From observing to controlling: Inducible control of organelle dynamics and interactions[END_REF] , we extended our system to chemically trigger the interactions between dispersed condensates and microtubule motor proteins. With this approach, we obtained a temporal control of induction of condensate transport and localization at the cell periphery or at the vicinity of the centrosome (Fig. 4). Harnessing the trafficking of artificial condensates is a first step towards the assembly of biomimetic RNP transport system in cells.

Many RNAs are found localized in specific area of cells, and local translation is thought to participate to many functions dictating cell fate [START_REF] Ryder | RNA localization regulates diverse and dynamic cellular processes[END_REF] . Complementary, mislocalization of RNA is reported to be associated with disease development [START_REF] Lin | Axonal mRNA translation in neurological disorders[END_REF] . There is consequently a strong emphasis to enlarge the current toolbox to analyze and study RNA localization and translation. The methodologies developed so far range from the visualization of RNP transport and translation with single molecule resolution, to spatial transcriptomics to map RNP interactomes [START_REF] Holt | Local translation in neurons: visualization and function[END_REF][START_REF] Weil | Making the message clear: visualizing mRNA localization[END_REF][START_REF] Pichon | A Growing Toolbox to Image Gene Expression in Single Cells: Sensitive Approaches for Demanding Challenges[END_REF][START_REF] Fazal | Atlas of Subcellular RNA Localization Revealed by APEX-Seq[END_REF][START_REF] Turner-Bridger | Single-molecule analysis of endogenous β-actin mRNA trafficking reveals a mechanism for compartmentalized mRNA localization in axons[END_REF][START_REF] Cassella | Subcellular spatial transcriptomics identifies three mechanistically different classes of localizing RNAs[END_REF] . In this context, we extended our assay to use it for the spatial manipulation of RNAs in cells. We showed that artificial condensates, functionalized with both motor domains and MCP proteins could be used as minimal RNP condensates recruiting a unique RNA, making it possible to explore condensate-mediated RNA delocalization. As a first proof-of-concept, we demonstrated the efficient recruitment of exogenous RNAs on motor condensates that were positioned at the cell periphery or at the centrosome depending on the motor directionality (Fig. 5). Combined with a temporal control of assembly/disassembly, one could anticipate future developments, where these artificial structures could act as platform organizing biochemistry in space and time.

Then, we demonstrated the ability of our system to strongly perturb the spatial distribution of endogenously tagged mRNAs. Artificial condensates drove the delocalization of individual ASPM-MS2 mRNAs at the cell periphery (Fig. 6,7B). This demonstrates how our system could outperform endogenous mRNA localization mechanisms by rewiring the transport machinery between the cytoplasm, the centrosome and the cell periphery. Competing with endogenous ASPM mRNA localization using artificial condensates provides interesting insights. On one hand, it has been shown that the ASPM RNA (as well as other centrosomal transcripts) naturally localizes to centrosomes through an active transport mechanism involving the microtubules and molecular motors [START_REF] Safieddine | A choreography of centrosomal mRNAs reveals a conserved localization mechanism involving active polysome transport[END_REF] . This trafficking is dependent on the encoded nascent peptide and occurs rapidly at the onset of mitosis: within a couple of minutes, scattered RNA readily concentrates on centrosomes, as revealed by live imaging [START_REF] Safieddine | A choreography of centrosomal mRNAs reveals a conserved localization mechanism involving active polysome transport[END_REF] . On the other hand, KIF1A condensates traffic away from the centrosomes and thus drag ASPM-MS2 mRNA. Since both the natural and artificial transport systems share microtubules for transit, the location where the RNA ends up provides an estimation of which localization process is more efficient. In most cells, the artificial condensates won the contest.

Several non-exclusive processes, that all rely on the capacity of KIF1A condensates to generate mechanical forces, could account for ASPM mRNA delocalization at the cell periphery: (i) Pulling forces applied by the condensates on individual ASPM mRNAs accumulated at the centrosome, allowing to convey RNAs along microtubule tracks. This suggests KIF1A forces are stronger than the cohesive forces bridging ASPM mRNA to centrosomal material. (ii) A tug-of-war between the KIF1A condensates and the endogenous transport machinery of ASPM mRNA to the centrosomes. For instance, KIF1A condensates can link individual RNAs to many more motors than a single nascent peptide or an endogenous adapter canonically would. They can be seen as a transport particle pulled by several molecular motors in a cooperative manner, allowing them to surpass the natural mechanism of ASPM mRNA transport. (iii) The direct capture and transportation of freely-diffusing ASMP RNAs by KIF1A condensates, upstream of their transport to the centrosome.

Interestingly, ASMP mRNA delocalization experiments provide a first benchmarking of the performance of our artificial condensates. This approach could open novel perspectives to examine the importance of RNA localization for cellular functions and may be extended to rewire the trafficking of other biomolecules of interest.

MATERIAL AND METHODS

Experimental model

Human epithelioid carcinoma HeLa cells (ATCC, ccl-2) were kept in Dulbecco's modified Eagle's medium (with 4.5 g/L D-glucose, HyClone) with 10% fetal bovine serum (Gibco, 10,270,106) and 1% Penicillin-Streptomycin (Sigma, P4333), at 37°C in a 5% CO2 humidified atmosphere. Tests for mycoplasma contamination were routinely carried out.

Plasmids

To generate the constructs containing 5 repeats of FKPB-F36M, a first plasmid puCIDT-Amp-5Fm was designed containing five repeats of FKBP-F36M separated by sequences coding for linkers of four GGS repeats (12 amino acids total). To avoid recombination, degenerate repeats were used. The first repeat was preceded by a Nhe and an AfeI restriction sites and the last one was followed by a Xba1 restriction site. This plasmid was purchased from IDT. To obtain the pcDNA3.1-5Fm plasmid (called hereafter 5Fm), puCIDT-Amp-5Fm was digested with NheI and XbaI, and the 5Fm containing fragment was subcloned between NheI and XbaI sites in the pcDNA3.1 (+) vector (Invitrogen). pcDNA3.1-emGFP-5Fm, pcDNA3.1-mCh-5Fm (called hereafter mCh-5Fm) and pcDNA3.1-MCP-5Fm (called hereafter MCP-5Fm) were then obtained by inserting emGFP, mCherry or a tandem MCP coding sequence, respectively, between HindIII and AfeI restriction sites. Coding sequences for human KIF1A(1-383), mouse KIF5B(1-555), human KIFC1(125-673) and mouse BICD2(15-595) were obtained from Addgene (plasmids #133242, #120170 #120169, and #120168 respectively) [START_REF] Id | Reversible association with motor proteins (RAMP): A streptavidinbased method to manipulate organelle positioning[END_REF][START_REF] Chiba | Disease-associated mutations hyperactivate KIF1A motility and anterograde axonal transport of synaptic vesicle precursors[END_REF] . KIF1A and KIF5B coding sequences were inserted in pcDNA3.1-5Fm between NheI and AfeI restriction sites, with respectively EcoR1 and Not1 restriction sites ahead of AfeI for subsequent sub-cloning. Then emGFP was inserted in pcDNA3.1-KIF1A-5Fm between EcoRI and AfeI, and in pcDNA3.1-KIF5B-5Fm between NotI and AfeI restriction sites. KIFC1 coding sequence was inserted in pcDNA3.1-emGFP-5Fm between XbaI and AgeI restriction sites. pcDNA3.1-BICD2-emGFP-5Fm plasmid was obtained by adding a NheI restriction site ahead of emGFP in pcDNA3.1-emGFP-5Fm, and inserting the BICD2 coding sequence between HindIII and NheI restriction sites. The four pcDNA3.1 constructs KIF1A-emGFP-5Fm, KIF5B-emGFP-5Fm, emGFP-KIFC1-5Fm and BICD2-emGFP-5Fm, are hereafter called the motor-LLPS scaffolds.

Transfection

For imaging after cell fixation, HeLa cells were cultured on 22x22 mm glass coverslips (VWR) in 6-well plates (Falcon, 3.5x10 5 cells per well). For live imaging, HeLa cells were seeded on 35-mm-dishes with polymer coverslip bottom (Ibidi, 1.5x10 5 cells per dish). For both, cells were transfected 24 hours later using Lipofectamine 2000 (Invitrogen) according to the manufacturer's protocol. For fixed cell imaging, cells were transfected with a 2:1:1 ratio of 5Fm, mCh-5Fm and motor-LLPS scaffold (2 µg total per well). The same conditions were followed for control experiments with motors lacking the LLPS 5Fm domain. In the case of KIFC1, cells were transfected with a modified ratio of 2.5:1:0.5. For live imaging (formation, dissolution and induction acquisitions), cells were transfected with a 1:1 ratio of motor-LLPS and 5Fm scaffolds (800 ng total per µ-dish). For smFISH experiments, cells were transfected with a 1:1:2 ratio of motor-5Fm scaffold, 5Fm, and MCP-5Fm (2 µg total per well) and 50 ng of RNA-MS2 plasmid. The ratio was modified to 0.5:1.5:2 in the case of KIFC1. To probe condensate inhibition and dissolution (Fig. S1 andS2), FK506 (Sigma, F4679) was used at 2.5 µM. For chemical induction experiments of condensate transport (Fig. 3), rapamycin was used at 0.4 µM.

ASPM-MS2 cell line generation

HeLa Kyoto cells were transfected with a combination of plasmids expressing the Cas9-nickase protein, two guide RNAs targeting the end of the ASPM gene, and a repair template harbouring 500 nucleotide homology arms. Homology arms flanked 3 HA tags, a stop codon, 24 MS2 repeats and an IRES-NeoR-stop codon sequence. This repair template was designed to allow insertion at the endogenous ASPM stop codon. Following neomycin selection at 400 μg/ml for 7-10 days, clones were isolated and characterized by PCR genotyping and smFISH to ensure proper cassette insertion and edited RNA localization. The clone used in this study is heterozygous as described in detail in Safieddine et al [START_REF] Safieddine | A choreography of centrosomal mRNAs reveals a conserved localization mechanism involving active polysome transport[END_REF]

Single-molecule fluorescence in situ hybridization

Single RNA molecule detection of the heterelogously expressed RNA-MS2 was performed according to the previously described smiFISH (single-molecule inexpensive FISH) method [START_REF] Tsanov | smiFISH and FISH-quant -a flexible single RNA detection approach with super-resolution capability[END_REF] . Briefly, cells were fixed in 4% paraformaldehyde (PFA) for 20 min at RT, and permeabilized with 70% ethanol in phosphate buffer saline (PBS) at 4°C overnight. A mix of gene specific (described previously [START_REF] Cochard | RNA at the surface of phase-separated condensates impacts their size and number[END_REF] ) and Cy3 FLAP probes in hybridization buffer (50 µl/coverslip) was used for overnight hybridization at 37°C in a humidity chamber. After washing twice for 30 min at 37°C in 15% formamide in SSC buffer and rinsing twice in PBS, cells were either mounted with VECTASHIELD mounting medium containing DAPI (Vector Laboratories, H-1200) or processed through immunofluorescence steps. smFISH against the MS2 sequence in HeLa/ASPM-MS2 cells was done using a single probe (25 ng of probe per 100 μl of hybridization mixture) that had the following sequence: 5'AT*GTCGACCTGCAGACAT*GGGTGATCCTCAT*GTTTTCTAGGCAATT*A where * denotes a thymidine conjugated with a Cy3 molecule. Hybridization was done on cells grown on a glass coverslip in a buffer containing 20% formamide (Sigma-Aldrich), 1x SSC, 0.34 mg/ml tRNA (Sigma-Aldrich), 2 mM VRC (Sigma-Aldrich), 0.2 mg/ml RNAse-free bovine serum albumin (BSA, Roche Diagnostics) and 10% dextran sulfate (MP Biomedicals). Hybridization was done overnight at 37°C and coverslips were washed the next day in a 20% formamide 1x SSC solution twice, each at least for 40 mins at 37°C. Coverslips were then mounted using VECTASHIELD containing DAPI (Vector Laboratories, H-1200).

Immunofluorescence

For centrosome imaging in Figure 2, cells were fixed 24 h after transfection in methanol at -20°C for 10 minutes. They were then permeabilized with a solution of 0.2% Triton X-100 and 0.1% BSA in PBS for 30 min, incubated for 1 h with the primary antibody (rabbit anti-pericentrin, Covance PRB-432C, 1:500 dilution), washed three times with PBS at RT for 5 min, incubated for 1 h with the secondary antibody (AffiniPure Goat Anti-Rabbit conjugated with Alexa Fluor 488 dye), washed three times with PBS at RT for 5 min, and finally mounted with VECTASHIELD containing DAPI (Vector Laboratories, H-1200).

Imaging

For live imaging, cells were imaged on a Zeiss LSM 710 META laser scanning confocal microscope using an x63 oil-immersion objective (PlanApochromatic, numerical aperture (NA) 1.4), at 37°C in a 5% CO2 humidified atmosphere, starting 4 h after transfection (formation). Microscope hardware and image acquisition were controlled with LSM Software Zen 2012. For fixed experiments, cells were imaged using an IX81 microscope (Olympus) and 60x oil immersion objective (PlanApo, NA 1.42), equipped with a CMOS camera, Orca-Fusion (Hamamatsu, Corporation), and a LED system of illumination (Spectra X, Lumencor). Microscope settings were controlled using Micro-manager on ImageJ. Images were analyzed using Fiji.

Data analysis

To quantify the degree of asymmetry of the condensate distribution, the fraction of mCh-5Fm fluorescence in the peripheral 25% of the cells (I25) was measured by adapting a previously published method [START_REF] Nijenhuis | An optimized toolbox for the optogenetic control of intracellular transport[END_REF] . For each cell, a first circle encompassing the entire cell and having for center a point in the nucleus was drawn. A concentric circle with a 10-pixel diameter was then drawn, from which a series of concentric circles were derived by iteratively enlarging the diameter by 10 pixels until reaching the first circle size. 5-pixel rings were then built by subtracting each circle to the next one in the series. Final regions of interest (ROI) were defined as the overlap between each ring and the cytoplasm. The images were subsequently processed by applying Gaussian blur (5-pixel radius) to eliminate strong local variations in intensity. For each ROI, the area and the mean and minimal intensities were measured. Minimal intensities were subtracted to mean values to remove background, and integrated intensity were calculated for each ROI. The peripheral 25% of a cell was defined as the sum of consecutive ROI, starting from the most peripheral one, reaching 25% of the total cell area. For each cell, I25 was obtained by calculating the ratio between the integrated fluorescence of the mCherry signal in the peripheral 25% over the integrated fluorescence of the entire cell.

Statistical analysis

For Fig. 1C and3A, Wilcoxon rank-sum tests (nonparametric test to compare two distributions) were performed using the ranksum MATLAB function (MathWorks). For Fig. 2C,Pearson's chi-squared tests (nonparametric test for nominal variables) were performed using the Python's chi2_contingency function.

  . The sequences targeted by the guide RNAs are: TCTCTTCTCAAAACCCAATCtgg for guide 1, and GCAAGCTATTCAAATGGTGAtgg for guide 2, where lowercase corresponds to PAM sequences.

Figure 1 :

 1 Figure 1: Functionalization of artificial condensates with plus-end motors drives their localization at the cell periphery. A. Schematic of the expected peripheral localization of condensates following transfection of mCh-5Fm and KIF1A-emGFP-5Fm or KIF5B-emGFP-5Fm (Fm = F36M-FKBP) in HeLa cells. B. Representative epifluorescence imaging of three cells expressing non-functionalized condensates (left panel), and KIF1A of KIF5B condensates (middle

F

  , respectively). Nuclei were stained with DAPI (blue). Grayscales inserts correspond to the red (mCh) and green (emGFP) channels of the regions delineated by dashed squares. Scale bar, 10 µm. C. Distribution of the fraction of mCherry fluorescence in the peripheral 25% of the cell (I25) for cells displaying non-functionalized condensates (left), and KIF1A or KIF5B condensates (middle and right, respectively), with each dot representing one cell (N = 87, 67and 53, respectively). Differences between no motor and KIF1A or KIF5B were statistically significant using a Wilcoxon rank-sum test (****: p-values < 10 -11 ). D. Time-lapse confocal imaging of the formation of KIF1A condensates in a cell (delineated by a dashed line), starting 4 h after transfection. The dashed squares indicate the region enlarged in the time-lapse images below (separate red and green channels). Scale bar, 20 µm. E. Epifluorescence imaging of the early time points of KIF1A-LLPS scaffold expression. Scale bar, 10 µm. F. Confocal imaging of coalescence events of KIF1A condensates. Scale bar, 2 µm. G. Epifluorescence imaging of the early time points of KIF5B-LLPS scaffold expression. Scale bar, 10 µm. H. Same as (D) for KIF5B condensates. I. Confocal imaging of coalescence events of KIF5B condensates. Scale bar, 2 µm.

Figure S1 :

 S1 Figure S1: Cells expressing plus-end motors lacking the LLPS domain; chemical inhibition of condensates; and directed transport of condensates. A. Representative epifluorescence imaging of HeLa cells transfected with KIF1A-emGFP or KIF5B-emGFP (without LLPS domain) and mCh-5Fm. Nuclei were stained with DAPI (blue in merge). Scale bar, 20 µm. B. Epifluorescence imaging of HeLa cells expressing KIF1A-or KIF5B-emGFP-5Fm and mCh-5Fm after FK506 addition either right after transfection to forestall the formation of condensates (left) or 24 h after transfection to dissolve the condensates (right) (two examples for each condition). Nuclei were stained with DAPI (blue in merge). Scale bar, 20 µm. C. Directed transport of a KIF1A condensate. Scale bar, 10 µm. D. Directed transport of a KIF5B condensate (white arrows). More time points are given below for the area delimited by the white dashed rectangle. The dashed yellow line represents the condensate trajectory. Scale bar, 10 µm. E. Kymograph analysis along the condensate trajectory shown in (C). Scale bar, 10 µm.

Figure 2 :Figure S2 :

 2S2 Figure 2: Functionalization of artificial condensates with a minus-end motor or a dynein adaptor drives their localization at the centrosome. A. Schematic of the expected centrosomal localization of condensates following transfection of mCh-5Fm and emGFP-5Fm-KIFC1 or BICD2-emGFP-5Fm (Fm = F36M-FKBP) in HeLa cells. B. Representative epifluorescence imaging of three cells expressing non-functionalized condensates (left panel), and KIFC1 or BICD2 condensates (middle and right panel, respectively). Nuclei were stained with DAPI (blue). Grayscale inserts correspond to the red (mCh) and green (emGFP) channels of the region delineated by dashed squares. Scale bar, 10 µm. C. Percentage of cells displaying 1, 2, 3, 4 or more than 5 condensates, for cells expressing non-functionalized condensates (left, N = 89 cells), and KIFC1 or BICD2 condensates (middle, N = 85, and right, N = 73, respectively). Differences between no motor and KIFC1 or BICD2 were statistically significant using a Pearson's chi-squared test (****: p-values < 10 -25 ). D. Epifluorescence imaging of cells displaying a KIFC1 or BiCD2 functionalized condensate (red, left and right, respectively) after immunostaining of pericentrin (green) as a centrosome marker. Nuclei were stained with DAPI (blue). Scale bar, 10 µm. E. Time-lapse confocal imaging of the formation of a KIFC1 condensate in a cell, starting 4 h after transfection. The dashed squares indicate the region enlarged on the right. Scale bar, 10 µm. F. Same as (E) for a BICD2 condensate. Scale bar, 10 µm.

Figure 3 :

 3 Figure 3: The enrichment of non-functionalized scaffolds in motor condensates differs depending on their cellular localization. A. Top: Delays between nucleation of the motor-LLPS scaffold and first detectable non-functionalized scaffold (mCherry signal) enrichment in condensates, for plus-end motors KIF1A (N = 12 cells) and KIF5B (N = 5), minusend motor KIFC1 (N = 12) and dynein adaptor BICD2 (N = 6). Differences between plus-end motors and minus-end motor / motor adaptor were statistically significant using a Wilcoxon rank-sum test (**: p < 10 -2 ; ***: p < 10 -3 ; ****: p < 10 -4 ). Bottom: Schematic of the subcellular location of condensates at the centrosome and at the cell periphery. B. Time lapse epifluorescence images of the delayed enrichment of mCh-5Fm in KIF1A condensates in a representative cell. The green and red arrows correspond to the nucleation of the condensate and the first visible enrichment of mCh-5Fm, respectively. Scale bar, 10 µm. C. Same as (B) for a KIFC1 condensate.

Figure 4 :

 4 Figure 4: Chemically-induced binding of non-functionalized condensates to molecular motors led to their repositioning in cells. A. Schematic of the expected transport of FKBP condensates upon induction of their interaction with plus-end (KIF1A) or minus-end motors (dynein through BICD2) using Rapamycin (RAP) in HeLa cells. B. Representative epifluorescence imaging of cells expressing the FKBP-emGFP-5Fm LLPS scaffold and KIF1A-mCh-FRB (left) or BICD2-mCh-FRB (right) in the absence of rapamycin. Nuclei were stained with DAPI (blue). Grayscale inserts correspond to the green (emGFP) and red (mCh) channels of the region delineated by dashed squares. Scale bar, 10 µm. C. Time-lapse epifluorescence imaging of FKBP-emGFP-5Fm condensates undergoing transport towards the cell periphery and coalescence after addition of rapamycin at time 0. Scale bar, 10 µm. D. For the cell shown in (C), kymograph analysis along the 200 px-wide strip delineated by the arrows (~ 21.7 µm), showing the coalescence of condensates over time. Scale bar,

Figure 5 :

 5 Figure 5: Motor/MCP condensates recruit RNA-MS2 and are efficiently positioned at the cell periphery or at the centrosome. A. Schematic of the formation of KIF1A/MCP condensates able to recruit the heterologous RNA-MS2. B. Representative epifluorescence imaging of cells containing KIF1A/MCP or BICD2/MCP condensates (green, left and right panels, respectively) following RNA-MS2 analysis by smiFISH (Cy3 probe, red). Nuclei were stained with DAPI (blue). The red channel setup allows for the visualization of dispersed RNA molecules while saturating the signal in the condensate. Grayscale inserts (1) correspond to the non-saturated green (emGFP) and red (Cy3) channels of the regions delineated by dashed squares. Insert 2 shows isolated RNA-MS2 molecules. Scale bar, 10 µm. C. Epifluorescence imaging of cells containing MCP condensates (green) following β-actin mRNA analysis by smiFISH (Cy3 probe, red). Scale bar, 10 µm. D. Epifluorescence imaging of cells containing condensates lacking MCP (green) following RNA-MS2 analysis by smiFISH (Cy3 probe, red). Scale bar, 10 µm.

Figure 6 :+

 6 Figure 6: KIF1A condensates can efficiently delocalize ASPM-MS2 RNA towards the cell membrane during mitosis. A. Epifluorescence imaging of HeLa/ASPM-MS2 cells at different stages of mitosis after immunostaining of FOP (green) as a centrosome marker. The RNA was revealed by smFISH using a MS2 probe (red). DNA was stained with DAPI (blue). Scale bar, 10 µm. White arrows point to centrosomal mRNA accumulation. B. Epifluorescence imaging of HeLa/ASPM-

Figure S3 :Figure S4 :

 S3S4 Figure S3: KIF1A/MCP condensates delocalized ASPM-MS2 mRNAs away from centrosomes and display three patterns in mitotic cells. Epifluorescence imaging of prometaphasic HeLa/ASPM-MS2 cells containing KIF1A/MCP condensates. Left panels show the merged channels with DAPI-stained DNA in blue. Left and middle panels show the ASPM-MS2 mRNA revealed by smFISH (red channel) and the GFP condensates (green channel), respectively. Scale bar, 10 µm. Squares depicting areas near the cell membrane where granules and RNA co-localize are enlarged below. Scale bar, 1 µm.

Acknowledgments

We thank M.A. Plamont for her help along the project and C. Amari for his help in the implementation of the quantification process. We thank A. Meunier for providing the pericentrin antibodies and E. Bertrand for sharing HeLa/ASPM-MS2 cells.

Funding A.C was supported by an IPV-SU PhD fellowship. A. S. was supported by ANR (ANR-19-CE12-0024-01). P.C was supported by a FRM (MND202003011470) grant. This work was supported by the CNRS, Ecole Normale Supérieure, and ARC (20181208003) to Z.G, FRM (MND202003011470) and iBio (SU) to Z.G and D.W, and ANR (ANR-19-CE12-0024-01) to D.W.

Author Contributions

A.C and Z.G conceived the project. A.C and P.C designed the motor condensate toolbox, as well as performed and analyzed motor-condensate experiments. A.S, M-N.B and D.W performed and analyzed ASPM-related experiments. A.C and Z.G prepared the manuscript with contributions from A.S, P.C and D.W. All authors discussed the results and commented on the manuscript.

Declaration of Interests

The authors declare that they have no competing interests.

Supporting Information 4 Supplementary Figures and 4 Supplementary


Raphaël Bricout

Dominique Weil

David Stroebel

Auguste Genovesio
email: auguste.genovesio@ens.psl.eu

Roest Hugues

Crollius

Evolution is not uniform along protein sequences

Amino acids evolve at different speeds within protein sequences, because their functional and structural roles are different. However, the position of an amino-acid within the sequence is not known to influence this evolutionary speed. Here we discovered that amino-acid evolve almost twice faster at protein termini than in their centre, hinting at a strong topological bias along the sequence length. We further show that the distribution of functional domains and of solvent-accessible residues in proteins readily explain how functional constrains are weaker at their termini, leading to the observed excess of amino-acid substitutions. Finally, we show that methods inferring sites under positive selection are strongly biased towards protein termini, suggesting that they may confound positive selection with weak negative selection.

These results suggest that accounting for positional information should improve evolutionary models.

Main text

. Accounting for such heterogeneity in evolutionary models is critical to accurately infer phylogenies and estimate cases of positive selection, and elaborate models have been developed to achieve this (8), generally by estimating sitespecific rates in a maximum likelihood framework employing Markov models of sequence evolution (9-11).

Surprisingly, the impact of the position of a given amino-acid in the sequence relative to the protein start and end on the rate of molecular evolution has not yet been investigated. To address this question, we measured the rates of amino-acid changing substitutions (nonsynonymous, dN) and silent substitutions (synonymous, dS) at individual codons positions and average them over thousands of CDS sequences. Specifically, we computed multiple sequence alignments (MSA) of CDS from 16,810 primate gene families to identify fixed mutations (substitutions, insertions and deletions) that took place in these sequences during the evolution of 26 primate species. The results show a strong excess of such changes towards the sequence extremities (Fig. 1A), leading to a distinctive U-shaped pattern.

Looking further into substitutions at each individual codon position, we computed positionspecific codon average evolutionary rates (Fig. S1) to examine separately the dN and the dS.

While the dS remains remarkably constant along the CDS length (average dS=0.052), the dN increases significantly in the region spanning the first and last 50 codons (Fig. 1B). We observe a similar bias when computing dN and dS along the CDS of 7,513 plant (Fabids) gene families, which were subjected to an approximately 8-fold higher divergence rate than primates (Fig. 1C). In summary, the dN appears to be driving the distinctive U-shaped pattern of total substitutions and dN/dS in gene coding sequences (Fig. 1D). Computing substitutions in a multiple alignment of coding sequences is a multi-step process, with many potential sources of technical biases which could potentially explain this pattern (12,13). We conducted a series of experiments to exclude annotation errors, multiple alignment artefacts and compositional biases (Supplementary material, Fig. S2), showing that our observations are robust to controls designed to address possible technical artefacts in the process from CDS annotation to substitution calculations.

We next examined biological or evolutionary explanations. We eliminated the possibility that a stronger mutation rate at CDS extremities would fuel the increased dN because the dS, which would be much more sensitive to the mutation rate, is essentially constant along CDS length (Fig. 1B,C). We next reasoned that a weaker negative selection at protein termini might be caused by weaker functional constraints. Predicted protein domains capture a large fraction of amino acids involved in structural and functional roles in protein sequences, and their prediction relies on sequence similarity and structural information (14). Both of these features make them good proxies for sites under evolutionary constraints. We computed the distribution of protein domains predicted by different methods along the 12,067 human protein sequences involved in our set of primate gene families, and we show that domains are strongly depleted at protein edges (Fig. 2A and fig. S3A-C). This dome-like shape is caused by the lower probability of domains overlapping amino acids immediately adjacent to these termini, since they cannot physically overlap the termini themselves. The distribution of domains decreases sharply towards protein edges regardless of the length of the protein sequences (Fig. S3D-E), supporting a scenario where all proteins are similarly affected by a deficit of domain-induced negative constraints at their edges. The dome-shaped distribution of domains mirrors the distinctive U-shaped distribution of the dN/dS ratio (Fig. 1A), consistent with our initial hypothesis that a depletion of domains at the edges of proteins would make them more permissive to non-synonymous changes and indels because of weaker selective constraints. To test this more directly, we distinguished codons that code for amino acids involved in a domain from those that do not, and computed the dN/dS for each category separately (Fig. 2B). In line with the above expectation, the dN/dS bias disappears when computed exclusively inside domains. Again, the difference in dN/dS behaviour is largely caused by the dN, since the dS remains constant both inside and outside of domains and is almost identical in both categories throughout the protein lengths (Fig. S4).

These results strongly support a model in which selective constraints are significantly weaker at protein edges.

We next investigated how structural constrains, or lack thereof, may also influence evolutionary rates at protein termini. A protein sequence is folded in space through both local and distant amino-acid interactions. Amino acids which are free of those interactions are conversely accessible to solvents, and typically found on the surface of the folded protein. Because such structural interactions are linked to the function of a protein, it is wellestablished that evolutionary rates differ between residues depending on their solvent accessibility (15)(16)(17). The precise relationship between solvent accessibility, evolutionary rates and amino-acid position along the sequence has however never been ascertained, mostly because N-and C-terminal regions of proteins are often removed to facilitate crystallisation prior to structure solving, or are generally poorly resolved in electron density maps. To circumvent this issue, we analysed 23,391 structures predicted by Alphafold (18) on complete human protein sequence to compute the relative solvent accessibility (RSA) of each residue (Fig. S5A). We note that RSA values follow a bimodal distribution with a distinctive peak above 0.7 depleted in residues included in protein domains. Conversely, residues with RSA below 0.3 are enriched in functional domains. We took residues from these two extremes categories to compute their distribution along protein sequences, and we find that solvent accessibility increases sharply at protein termini, consistent with weak structural constraints in these regions (Fig. 2C). Critically, the dN/dS rate is low and constant along protein length in sites with low accessibility, while it is high in highly accessible regions (Fig. 2D). In both categories, the marked increase in dN/dS at sequence extremities shown in Figure 1 is absent, indicating that solvent accessibility is likely a strong marker of the decrease in selective pressure observed in the N-and C-terminal region of proteins.

Because both functional domains and RSA seem to drive dN/dS variation at protein termini, we applied a model where the average dN/dS at a given residue is the sum of the average dN/dS in domains and in high RSA (RSA > 0.7), each weighted by the proportion of residues in their category (Supplementary Material). The model reproduces the observed dN/dS with remarkable accuracy in human proteins (mean difference = 5.9%, Fig. 2E), suggesting that functional domains and RSA are two variable that are sufficient to explain the bias in average dN/dS along proteins sequences. The slight asymmetry in dN/dS bias between N-and Ctermini observed in the model, reminiscent of the asymmetry observed in Figure 1B, largely disappears when we remove the 15.8% of proteins labelled with a signal peptide at the Nterminus (Fig. S5B). Signal peptide, which are known to be highly variable in sequence (19) are therefore likely to provide additional relief from the evolutionary pressure measured in this region.

The dN/dS bias at protein ends is measurable by averaging thousands of sites at any given position. Is it also significant at the level of individual sequence alignments? This is important if evolutionary models applied to single gene families are likely to be affected. To address this, we computed a correlation between codon position and dN/dS for 12,322 multiple sequence alignments, separately for the 50 codons at beginning and at the end of coding sequences (Fig. 3A). This reflects the existence of a measurable increase in dN/dS towards CDS edges, even in individual sequences. We propose that this pattern is caused by the same factors as for the average sequences analysed previously (Fig. 1B), respectively the biased domain distribution and solvent accessibility.

These results immediately raise questions for the identification of positive selection in proteins sequences, because a significantly elevated dN compared to some background rate is generally taken as evidence of adaptive changes [START_REF] Nei | Molecular Evolution and Phylogenetics[END_REF]. The U-shaped bias in dN observed in our study suggests that relaxation of constraints at protein edges might confound tests of positive selection. To investigate this, we estimated sites under positive selection in a set of 12,170 Rodent gene trees using a site model (methods). We found that sites estimated under positive selection are strikingly enriched at protein edges (Fig. 3B), and that this enrichment is specifically attributed to sites located outside of functional domains (Fig. 3C) and to residues with high solvent accessibility (Figure 3D). Notably, the same bias towards coding sequence extremities can be observed in several recent published scans for positive selection (Figure S6). Interestingly, while this bias is conspicuous for sites estimated to have been subject to positive selection using bioinformatic methods, it is not the case for experimentally verified sites, although our compilation of cases for this category is too small to draw general conclusions.

We reveal a pattern of evolutionary rate along coding sequences that has so far remained concealed: the average amino acid substitution rate (dN) increases towards the extremities of the sequence. We found this pattern by assembling observations that were sometimes known quantitively or intuitively in the field but never connected with respect to codon or amino-acid positions in sequences. This patterns provide insights into the elusive mechanism driving evolutionary rate heterogeneities (7). First noted by Perutz and colleagues on haemoglobin [START_REF] Perutz | [END_REF] and confirmed by many studies since, protein surfaces evolve faster than their interior, where structural constraints, residue interactions and functional sites are most enriched and solvent accessibility is very low (15,16). Attempts at explaining evolutionary rate heterogeneity have thus mainly focused on this paradigm, that structural constraints governed by complex spatial interactions create a range of selective pressures on amino acids, but these are still hard to predict from the sequence itself.

We note that in the present study molecular rates are not dependent on a substitution model, as they do not rely on ancestral state inferences in coding sequences, and molecular rates are computed on MSA without gaps, which are known to introduce biases. Also, our finding that the average dS is constant along CDS length (Figs. 1B,1C) should not be interpreted as meaning that dS does not vary or is not subject to site heterogeneity in individual genes, as this has been shown in many studies [START_REF] Rubinstein | Codon evolution:mechanisms and models[END_REF].

If protein termini are under lower evolutionary pressure, why are they not cropped by microdeletions in the course of evolution? The example of signal peptides, but also of amino-acids carrying specific epigenetic marks (e.g. methyl or acetyl groups) in histones, illustrate why maintaining structurally flexible regions may be functionally important.

Methods designed to identify positive selection are sensitive to false positives, potentially caused by factors such as variable effective population size [START_REF] Rousselle | [END_REF], biased gene-conversion (24), multi-nucleotide mutations (25) and punctual relaxation of selective pressure in a lineage (5,26). Here we show that sites inferred as having experienced a period of positive selection are conspicuously enriched in regions with high dN caused by low selective pressure, suggesting that they may contain a high proportion of false positives. This is consistent with the observation that experimentally tested positively selected sites are, on the contrary, depleted at sequence extremities. Of note, we observed that the synonymous rate dS is constant along protein length, thus providing little leverage for background model adjustments to counteract this effect in statistical tests of positive selection. Considering the excess of positive selection inferences at protein extremities as false positives would also be consistent with expectations that selection for advantageous traits would operate predominantly where functional domains and structural constraints are most frequent, i.e. away from the extremities (27). It has also been previously shown that non-adaptive changes as well as positively selected sites are significantly enriched on the surface of proteins where solvent accessibility is high, emphasizing the difficulty in distinguishing them in these regions (17). Altogether, we propose that intervals between functional domains display a neutrally evolving size and weaker structural constraints, largely causing lower selective pressure at protein termini. Accounting for this bias in models of molecular evolution should improve their handling of site heterogeneity and accuracy of adaptive evolution inference.

Fig. 1 .

 1 Fig. 1. (A). Frequency of amino acid substitutions, insertion and deletions computed in 16,810 primate multiple sequence (CDS) alignments (MSA), rescaled from 0 to 100% of the coding sequence length. (B). Distribution of silent (dS) and non-synonymous (dN) substitution rates computed at each codon position from random pairs of sequences sampled from 16,248 primate MSA without alignment gaps and shown here for the first 50 codons (left panel), the central 50 codons (middle panel) and the last 50 codons (right panel). (C). Same as in B but for pairs of CDS sampled from 7,513 plant MSA. (D). The distribution of dN/dS ratio for dN and dS values shown in B but across the entire CDS length rescaled from 0 to 100%. In all panels the shaded the area represents the 95% confidence interval.

Fig. 2 .

 2 Fig. 2. (A) The distribution of protein domains from the PFAM database in 12,067 human proteins rescaled from 0-100% of their length (blue line). The red line shows the distribution of the same domains in random non-overlapping positions in the same sequences. (B) dN/dS computed in 16,248 alignments of at least 2 CDS sequences from 26 primate genomes, where sites inside (dark red line) and outside (green line) PFAM domains are distinguished. (C) The distribution of frequency of amino acids with high (blue line) and low (red line) Relative Solvent Accessibility (RSA) computed by pCASA on 3D structure predicted by AlphaFold on 23,391 human protein sequences, rescaled to 0-100% of the length. (D) dN/dS computed on 7,614 sequences common to the AlphaFold and Ensembl primate CDS datasets, where sites with high (green line) and low (dark red line) RSA are distinguished. (E) Proposed model were the mean dN/dS in domains and in highly accessible regions (RSA > 0.7) are weighted according respectively to the percent of codons overlapping domains and residues with RSA > 0.7. The Mean Absolute Error (MAE) and percent average error are indicated for each panel. In all panels the shaded the area represents the 95% confidence interval.

Figure 3 .

 3 Figure 3. (A) Distribution of Pearson correlation coefficients between dN/dS values and their position in mouse CDS from 12,322 alignments of 5 to 20 rodent sequences. Positions are either the first 50 (filled blue bars) or the last 50 (filled pink bars) codons. The blue line shows the distribution for the first and last 50 codons in the same mouse sequences but where their positions were randomized. (B) Distribution of the frequency of sites under positive selection in 12,170 rodent CDS rescaled to 0-100% of their length (C) Distribution of the frequency of sites under positive selection in the first, middle and last 50 codons of 12,170 rodent CDS, distinguishing sites inside (blue line) and outside (red line) PFAM domains. (D) Distribution of the frequency of sites under positive selection in the first, middle and last 50 codons of 5,893 rodent CDS, distinguishing sites with high (red line) and low (blue line) RSA.

Acknowledgements

We thank P. Vincens and the informatics service at IBENS for support, and Alexandra Louis, Guillaume Louvel, François Giudiucelli and Nicolas Lartillot for helpful discussions. This work has received support under the program « Investissements d'Avenir » launched by the French Government and implemented by ANR with the references ANR-10-LABX-54 MEMOLIFE and ANR-10-IDEX-0001-02 PSL* Université Paris. R.B. received funding from the French Ministry for Education, Research and Innovation.

Funding

Data and material availability

The scripts and data necessary to generate all figures, including in supplementary Information, have been deposited in Zenodo (doi:10.5281/zenodo.6472876).

Competing interest

The authors declare no competing interests.

Supplementary Materials

Material and Methods

Fig S1 to S6

Table S1 References


Florian Lucasson

Andra Balanescu

Uta Kiltz

Ying-Ying Leung

Sibel Zehra Aydin

Inna Gaydukova

Ennio Lubrano

Laura Coates

Maarten De Wit

Residual patient-reported burden in 444 patients with psoriatic arthritis in remission or low disease: A cross-sectional analysis

à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Amgen.

The objective of treatment in psoriatic arthritis (PsA) is remission or low disease activity (REM/LDA).( 1) However, there may remain a residual patient burden in patients where inflammation is controlled. This residual burden is often linked to pain or fatigue. (2)[START_REF] Lubrano | Residual Disease Activity and Associated Factors in Psoriatic Arthritis[END_REF][START_REF] Palominos | Determinants of sleep impairment in psoriatic arthritis: An observational study with 396 patients from 14 countries[END_REF] Moreover, residual burden may differ according to the definition of REM/LDA used.( 3)

The objective of this analysis was to explore patient-perceived burden of disease in PsA patients in REM/LDA, when using different definitions of REM/LDA.

This was a post-hoc analysis of the ReFlaP study (NCT03119805), an observational study in 14 countries of consecutive adult patients with definite PsA and >2 years of disease duration.( 5) REM/LDA status was defined using Minimal Disease Activity (MDA), and Disease Activity in PSoriatic Arthritis (DAPSA)≤14. [START_REF] Schoels | Disease activity in psoriatic arthritis (PsA): defining remission and treatment success using the DAPSA score[END_REF][START_REF] Coates | Validation of minimal disease activity criteria for psoriatic arthritis using interventional trial data[END_REF] Patient-perceived burden of disease was assessed through the PsA Impact of Disease (PsAID12) composite score and its individual components assessing physical and psychological impact (0-10 where 0 is the optimal status). [START_REF] Queiro | Structural damage is not a major driver of disease impact in patients with long-standing psoriatic arthritis undergoing systemic therapy[END_REF][START_REF] Pardo | Disease Activity in Psoriatic Arthritis Index and Psoriatic Arthritis Impact of Disease Questionnaire: correlation and sensitivity to change in a real clinical setting[END_REF] Mean and median levels of patientreported symptoms were assessed in REM/LDA status.

Of 444 patients: 220 (50.5%) were male, mean age was 52.2±12.6 years, mean disease duration was 10.1±8.1 years; 261 (58.8%) were taking a conventional DMARD and 255 (57.4%) a biologic (Table 1). Disease activity was moderate overall (Table 1).

REM/LDA was more frequent when defined by DAPSA: 251 (56.5%) patients, than by MDA: 171 (38.5%) patients.( 5) As expected, objective measures of disease activity were minimal in the good status categories (data not shown). In REM/LDA patients, mean PsAID12 was 1.4 (standard deviation, SD, 1.3) in patients in MDA, and 2.1 (SD 1.7) in the DAPSA-defined REM/LDA group. Residual disease impact (assessed with components of the PsAID12) in REM/LDA patients was lower when using MDA to define REM/LDA (Figure 1): each median level of symptoms was below 1 in REM/LDA patients according to MDA whereas in DAPSA-defined REM/LDA, 5 aspects of impact had a median level of 2, with fatigue being the aspect with the highest mean score (Figure 1).

In this unselected population, residual symptoms were of low magnitude for patients in REM/LDA confirming the patient relevance of REM/LDA as a treatment objective. The predominant aspect of residual impact was fatigue. [START_REF] Gudu | Quality of life in psoriatic arthritis[END_REF] The residual burden of disease was lower in patients in MDA than in DAPSA-REM/LDA, which could indicate that MDA corresponds to a 'deeper' form of disease control, though the clinical relevance of the differences observed should be further explored. It has been suggested that remission may be 'deeper' with bDMARDs; however, this study did not explore the role of treatments and in particular, bDMARDs, in residual disease burden. A holistic approach should be implemented when evaluating people with PsA, including when disease control has been obtained. Residual burden are the components of the PsAID12 questionnaire.

Each bar represents mean value of a component: in blue, mean value for patients in MDA and in orange, mean value for patients in REM/LDA based on DAPSA. The black dots represent the medians of each component.

Figure 1 .

 1 Figure 1. Residual burden of disease in 171 PsA patients reaching MDA and 251 patients reaching DAPSA-defined remission or low disease activity

  11. Pitié Salpétrière hospital, AP-HP, Rheumatology department, Paris, France

	(NIHR) Oxford Biomedical Research Centre (BRC). The views expressed are those of
	the author(s) and not necessarily those of the NHS, the NIHR or the Department of
	Health.
	Ana-Maria Orbai is a Jerome L. Greene Foundation Scholar and is supported in part Key Indexing Terms: Arthritis, Psoriatic; Quality of life; Health Status; Disease Activity by a research grant from the US National Institute of Arthritis and Musculoskeletal and
	Skin Diseases of the US National Institutes of Health under award number P30-
	Corresponding author: AR070254 (Core B), and by an investigator-initiated research grant from Celgene and
	For submission
	Dr. Florian LUCASSON, Hôpital Pitié-Salpêtrière, Service de Rhumatologie, 47-83 bd
	de l'hôpital, 75013 PARIS France
	Email: flo.lucasson@hotmail.fr
	For reprints
	Pr. Laure GOSSEC, Hôpital Pitié-Salpêtrière, Service de Rhumatologie, 47-83 bd de
	l'hôpital, 75013 PARIS France
	Email: laure.gossec@aphp.fr	Tel=+33 142178421
	Word count: 439/500 words, 10/10 references, 1 table and 1 figure
	Disclosures:
	Florian Lucasson: none
	Andra Balanescu: SPEAKERS FEES: Abbvie, Amgen, Astra-Zeneca, Angellini, BMS,
	Berlin-Chemie, MSD, Novartis, Pfizer, Roche, Sandoz, Teva, UCB, Zentiva.
	CONSULTANCIES: Akros, Abbvie, Amgen, AlphaSigma, Biogen, Lilly, Mylan, MSD,
	Novartis, Pfizer, Roche, Sandoz, UCB. INVESTIGATOR IN CLINICAL TRIALS: Akros,
	MSD, Sanofi, Pfizer, Astra-Zeneca, Novartis, BMS, GSK, Roche, UCB, Sandoz

Table 1 . Characteristics of 444 PsA patients

 1

	Characteristics	Number (%) or mean (SD)
	Men, n (%)	220 (50.5)
	Age (years), mean (SD)	52.2 (12.6)
	Disease duration, mean (SD)	10.1 (8.1)
	Current smoking, n (%)	79 (19.6)
	Number of comorbidities (Groll index), mean	1.1 (1.3)
	(SD)
	Conventional synthetic DMARD intake, n (%)	261 (58.8)
	Biological DMARD intake, n (%)	255 (57.4)
	Oral glucocorticoids intake, n (%)	70 (15.8)
	Any current psoriasis skin lesions, n (%)	271 (63.8)
	Swollen joint count, mean (SD) [0-66]	2.2 (7.0)
	Tender joint count, mean (SD) [0-68]	4.7 (9.5)
	Leeds enthesis count, mean (SD) [0-6]	0.6 (1.4)
	DAPSA, mean (SD)	16.6 (17.2)
	DAPSA remission, n (%)	86 (19.4)
	DAPSA low disease activity, n (%)	165 (37.2)
	MDA, n (%)	171 (38.5)
	Data were missing for: smoking status (n=41, 9.2%), number of comorbidities (n=24, 5.4%),
	skin psoriasis (n=19, 4.3%), age (n=18, 4.1%), disease duration (n=14, 3.2%), sex (n=8,
	1.8%).

Acknowledgment:

We gratefully acknowledge the participation of co-investigators in ReFlaP : Stéphanie Rouanet, statistician, France; Clémence Gorlier, France; Déborah Puyraimond-Zemmour, France; Umut Kalyoncu, Turkey ; Penelope Palominos, Brazil ; Juan D Cañete, Spain ; Rossana Scrivo, Italy ; Emmanuelle Dernis, France; Sandra Meisalu, Estonia ; Adeline Ruyssen-Witrand, France; Martin Soubrier, France; Lihi Eder, Canada ; Pascal Richette, France; M. Elaine Husni, Canada; and Josef S. Smolen, Austria


The evolution of the Galactic discs revealed by the Gaia APOGEE Kepler giant stars N. Lagarde -Laboratoire d'Astrophysique de Bordeaux -France In this study, we use observational properties coming from:

• Asteroseismology: accurate ages deduced from the aster-seismic measurements are available for all stars in our sample. We consider the APOKASC catalog published by Pinsonneault et al. (2018) as well as the seismic sample based on Miglio et al (2021, hereafter M21) • Spectroscopy: we use the spectroscopic parameters ([Fe/H] et [𝛂/Fe]) from APOKASC which are taken from APOGEE DR14.

• Astrometry and Photometry: the Galactic velocities and coordinates have been computed using the StarHorse distances computed by Queiroz et al ( 2020) and following the same method developed by Gaia Collaboration et al. (2018b).

DATA

Galactic stellar populations synthesis models can be used to provide a foward modelling allows to make mock catalogue simulations where selection bias on observable parameters can be accurately reproduced, allowing to identify possible bias in inferred distributions. We use the comprehensive description of Galactic stellar populations provided by BGM (e.g., Lagarde et al. 2017) to produce a realistic data simulation. More details on the model description in Lagarde et al. (2021)

Forward modelling using Besançon Galaxy Model

The following selection are applied on both the BGM-simulation and the observations. APOKASC sample ★ APOKASC sample shows a peak around 1-2 Gyr that is not seen in the M21 age distribution, as well as not simulated by the BGM (Fig. 1). => We suggest that this peak is created by the strong dependency of the age determination for red clump stars on the physics included in stellar models (e.g., hydrodynamical processes, mass loss or accretion, binarity).

• 7.4 ≤ H < 10.8 • T eff < 5300 K • 0.4 < ∆ν < 20
★ We find a good agreement between the age distribution of M21 and the BGM simulation within small statistical fluctuations.

★ A small hint for SFR enhancement between 2-5.5 Gyr in both samples remains to be confirmed with larger seismic samples. The comparison with the BGM simulations cannot explain these differences. This suggests that important processes such as radial migration and accretion due to mergers do play an important role in shaping our Galaxy.

Age metallicity relations

•

  Fig. 4: The dispersion of the vertical velocity as a function of stellar ages from BGM (left panel) and from observations using the APOKASC sample (right panel). The whole thick disc (hαmp + hαmr thick discs) is also shown with the green dashed line.

Fig. 2 :

 2 Fig.2: Distribution of stars in the [𝛂/Fe] vs. [Fe/H] plane. The dashed lines show the limits used