Xie Lusi

Liu Siyu

Chen Xi

Zhang Shuman

Chen Hui

Wang Jie

Wang Ze

Sun Zheng

Ju Xingming

Pan Teng

Xing Jia

Dang Chen

Yang Yang

Qu Jingang

Ma Xinxin

Liu Wei

Kang Ling

Li Kangkang

Du Wenqian

Wang Kun

Lexuan Liu

Oana Ilioaia

Bianca Sclavi

I would like to express my heartfelt thanks to my CSI

ABBREVIATIONS

Introduction

Chapter 1

When bacteria face environmental stress, the changes in their metabolic regulatory network are complex. However among these complex changes, changes in the transcription and translation process based on ppGpp regulation are particularly important. In this chapter, I introduce the basics of transcription, translation and ppGpp regulation.

Introduction 1.Transcription

From the central dogma of molecular biology, we know the way information flows in cells.

Regulation of gene expression is critical to the survival of bacteria and is accomplished through many steps, from transcription initiation to mRNA stability and translation. The basis of our understanding of gene expression relies on terminology and models derived from early research in Escherichia coli and bacteriophage λ [START_REF] Barnes | The construction of λ transducing phages containing deletions defining regulatory elements of the lac and trp operons in E. coli[END_REF][START_REF] Miller | Genetic Analysis of the lac Repressor[END_REF][START_REF] Reznikoff | The lactose operon-controlling elements: a complex paradigm[END_REF].

Gene expression depends on the flow of genetic information from gene to protein(Figure 1).

Transcription is the first step in the expression of genetic information and the first step in protein synthesis. Transcription is the process of decoding double-stranded DNA, in which RNA polymerase (RNAP) acts as a decoder to transfer DNA information to RNA. RNAP is very important in transcription. The first part in this thesis is a description of the transcription process.

History

In 1957, fragments of RNA were first observed in phage-infected E. coli [START_REF] Astrachan | Chromatographic Detection of Differences between Bacteriophage-related Deoxyribonucleic Acids 1[END_REF].

In 1959, Hurwitz found that ribonucleotides were incorporated into chains of deoxynucleotides in extracts of enzymatic reactions inside E. coli [START_REF] Hurwitz | The Enzymatic Incorporation of Ribonucleotides into Polydeoxynucleotide Material[END_REF].

In 1959, Jacob and Monod described the lac Operon in E. coli. This is the first example of transcriptional gene control in a biological system [START_REF] Gann | Jacob and Monod: From Operons to EvoDevo[END_REF].

In 1961, through the enzymatic reaction of galactosidase and the action process of bacteriophage, the same researchers predicted the role of RNAP in the information transfer between DNA and protein, and analyzed the principle of this process [START_REF] Jacob | Genetic regulatory mechanisms in the synthesis of proteins[END_REF].

In 1969, the polypeptide chains of RNA polymerase were separated and studied [START_REF] Burgess | Separation and Characterization of the Subunits of Ribonucleic Acid Polymerase[END_REF].

From1969-, discovery and simple functional studies of the σ family [START_REF] Burgess | Factor Stimulating Transcription by RNA Polymerase[END_REF][START_REF] Lonetto | The sigma 70 family: sequence conservation and evolutionary relationships[END_REF].

In 1969, described the Rho transcription termination factor based on its activity on in vitro transcription of λ DNA [START_REF] Roberts | Termination factor for RNA synthesis[END_REF].

From 1989-1998, three-dimensional structures of RNAP and its complexes with DNA, RNA and regulatory factors at different stages of the transcription cycle. Low-resolution structures (in the 25-12 Å range) of RNAPs, provided by electron microscopy (EM) and image processing, reveal a molecule shaped like a crab claw, with a groove or channel that is an appropriate size for accommodating double-helical DNA [START_REF] Darst | Insights into Escherichia coli RNA polymerase structure from a combination of x-ray and electron crystallography[END_REF][START_REF] Darst | Three-dimensional structure of yeast RNA polymerase II at 16 A resolution[END_REF][START_REF] Darst | Three-dimensional structure of Escherichia coli RNA polymerase holoenzyme determined by electron crystallography[END_REF][START_REF] Schultz | Three-dimensional model of yeast RNA polymerase I determined by electron microscopy of two-dimensional crystals[END_REF].

In 2002, the crystal structure of RNA polymerase holoenzyme was determined at highresolution (Murakami et al., 2002a(Murakami et al., , 2002b)).

RNA polymerase

RNAP is the enzyme responsible for the transcription process. The structure and function of the catalytic core part of RNAP are conserved in all cellular organisms (Archambault and Friesen, 1993;[START_REF] Cramer | Structural Basis of Transcription: RNA Polymerase II at 2.8 Ångstrom Resolution[END_REF][START_REF] Darst | Insights into Escherichia coli RNA polymerase structure from a combination of x-ray and electron crystallography[END_REF][START_REF] Ebright | RNA polymerase: structural similarities between bacterial RNA polymerase and eukaryotic RNA polymerase II[END_REF]. Understanding the structure and The RNAP core is catalytically active but unable to initiate transcription from the promoter.

It requires binding to one of several specific σ subunits leading to the formation of the RNAP holoenzyme, which recognizes the promoter and initiates transcription. Most of the σ factors belong to the σ 70 family, and some belong to the σ 54 family (Browning and Busby, 2016;Gruber and Gross, 2003). In E. coli, transcription of most genes utilizes σ 70 . Members of the σ 70 family direct RNA polymerase to specific promoter elements, typically 5-6 base pairs (bp) in length, located upstream of the transcription start site (positions -10 and -35 ), while they also play a role in the early stages of unwinding of promoter DNA and transcript elongation. The entire process is reversible [START_REF] Bae | Structure of a bacterial RNA polymerase holoenzyme open promoter complex[END_REF][START_REF] Browning | The regulation of bacterial transcription initiation[END_REF][START_REF] Feklistov | Structural basis for promoter-10 element recognition by the bacterial RNA polymerase σ subunit[END_REF][START_REF] Murakami | Bacterial RNA polymerases: the wholo story[END_REF][START_REF] Zhang | Structural basis of transcription initiation[END_REF][START_REF] Zuo | Crystal structures of the E. coli transcription initiation complexes with a complete bubble[END_REF].

The X-ray crystal structure of Thermus aquaticus core RNAP revealed a molecule shaped like a "crab claw", with an internal channel of 27 Å in diameter. Located on the back wall of the channel is a Mg2 + ion required for catalytic activity (Zhang et al., 1999). The overall shape and size is similar to yeast RNAP II, and the folds of highly conserved segments around the active site of these two enzymes are essentially identical [START_REF] Cramer | Multisubunit RNA polymerases[END_REF][START_REF] Cramer | Structural Basis of Transcription: RNA Polymerase II at 2.8 Ångstrom Resolution[END_REF][START_REF] Darst | Bacterial RNA polymerase[END_REF][START_REF] Ebright | RNA polymerase: structural similarities between bacterial RNA polymerase and eukaryotic RNA polymerase II[END_REF].

In the holoenzyme of Thermus aquaticus RNA polymerase, three σ domains are distributed on the upstream face of RNAP, where the COOH terminus of σ3 and the NH2 terminus of σ4 are separated by 45 Å. This distance mainly includes σ region 3.2, spanned by an extended 33residue linker that snakes through the RNAP active-site channel and effluxes through the RNA export channel, and continues into σ4, which is clamped on the α helix of the β tip (β flap-tip helix). The primary RNAP channel is relatively closed, allowing the β´ lid to interact with the inner surface of the β flap to form a protein tunnel through which the σ region 3.2 threads (Murakami et al., 2002b). The dissociation constant between σ and the RNAP core is estimated to be around 10 -9 M, and the interaction is very stable [START_REF] Gill | Escherichia coli sigma 70 and NusA proteins. I. Binding interactions with core RNA polymerase in solution and within the transcription complex[END_REF]. Each σ domain, and the linker connecting them, interacts with the core RNAP. However, the σ-factor is usually released when RNAP enters the transcriptional elongation phase [START_REF] Murakami | Bacterial RNA polymerases: the wholo story[END_REF].

The overall structure of the E. coli RNAP holoenzyme is similar to that of Thermus RNAP, resembling a crab claw with two pincers constituting the DNA-binding cleft and active site [START_REF] Murakami | X-ray crystal structure of Escherichia coli RNA polymerase σ70 holoenzyme[END_REF] (Figure 2). Both are shaped like a "clamp". The clamp changes its position by swinging between open and closed states [START_REF] Chakraborty | Opening and closing of the bacterial RNA polymerase clamp[END_REF]. The entire structure of the E. coli β subunit (Ecoβ) can be superimposed on the T. aquaticus β subunit (Taqβ) for comparison. There are biases around Eco βi4, Eco βi9 and Eco βi11. Ecoβ′ has several inserts that are not present in Taqβ′. Among them, there is a large insert (β′i6) in the middle of the trigger loop/helix (TLH), which divides TLH into two regions. Eco β′i6 plays an important role in the formation of the open complex of transcription, transcription pausing and termination.

Its location is thought to be close to the ω subunit jaw [START_REF] Artsimovitch | Co-overexpression of Escherichia coli RNA polymerase subunits allows isolation and analysis of mutant enzymes lacking lineage-specific sequence insertions[END_REF]. The ω subunit N-terminal tails in E. coli RNAP are folded differently than in Thermus RNAP. The E. coli sigma subunit C-terminal tail, including α4 and α5, is fully extended; it does not interact with the C-terminal tail of the ω subunit. Functionally, there is a clear link between ω subunits and ppGpp-dependent transcription [START_REF] Igarashi | Promoter selectivity of Escherichia coli RNA polymerase: omega factor is responsible for the ppGpp sensitivity[END_REF][START_REF] Mathew | The evolving story of the omega subunit of bacterial RNA polymerase[END_REF]. ppGpp is an important effector of the stringent response (see Section 3). The finding that subunit structures are so different in E. coli and Thermus RNAP may be related to the observation that E. coli RNAP responds to ppGpp only in the presence of the ω subunit [START_REF] Vrentas | Response of RNA polymerase to ppGpp: requirement for the omega subunit and relief of this requirement by DksA[END_REF].

The σ1.1 structure was refined in the E. coli RNAP holoenzyme. The final σ1.1 structure contains four helices with complete disorder in the electron density of residues from 65 to σ1.2. This region may also play an important role in bending DNA to form an early intermediate between closed and open promoter complexes [START_REF] Saecker | Mechanism of bacterial transcription initiation: RNA polymerase -promoter binding, isomerization to initiation-competent open complexes, and initiation of RNA synthesis[END_REF].

Introduction

Promoters

Promoter sequences are crucial for the regulation of transcription and display sequence heterogeneity. In 1964, Jacob and Monod proposed the definition of a promoter, which is located upstream of an expressed gene and is necessary to initiate gene expression. The transcription start site (TSS) is +1, which is where transcription begins. Bacterial promoters are relatively short, generally less than 150 bp. In E. coli, "TATAAT" and "TTGACA" are consensus sequences for the Pribnow box and -35 element, respectively. Prokaryotic promoters may also contain discriminator elements (positions -4 to -6), an extended -10 element (positions -14 to -16), and an upstream (UP) element (5' of the -35 element) (Feklístov et al., 2014).

The recognition of promoters by RNAP is particularly important for the transcription process.

The recognition regions of the promoters are respectively (Figure 3). Transcription initiation, which can be subdivided into promoter-RNAP complex formation, abortive initiation, and promoter escape, is the most heavily regulated stage of the transcription cycle.

First, the RNA polymerase (RNAP) holoenzyme (Eσ) is formed. When the Eσ binds the promoter to form a closed complex (RPc) (Figure 4), it covers from about -55 bp to about +15 bp of DNA relative to the transcription start site (TSS) (positive numbers represent bases downstream of the TSS, while negative numbers represent upstream locations) [START_REF] Li | Characterization of the closed complex intermediate formed during transcription initiation by Escherichia coli RNA polymerase[END_REF]. Upon formation of the RPc, DNA and Eσ undergo a series of conformational changes

resulting in an open complex (RPo), ultimately resulting in DNA strand separation from approximately -11 to +3 bp [START_REF] Saecker | Mechanism of bacterial transcription initiation: RNA polymerase -promoter binding, isomerization to initiation-competent open complexes, and initiation of RNA synthesis[END_REF]. The region where the DNA strands separate is often referred to as the "transcription bubble", which includes the base on the template strand, designated +1, which will serve as a template for the first nucleotide of the transcript (Haugen, Introduction 2008;[START_REF] Saecker | Mechanism of bacterial transcription initiation: RNA polymerase -promoter binding, isomerization to initiation-competent open complexes, and initiation of RNA synthesis[END_REF]. Transcription will initiate from a short, unstable region, which can lead to transcription failure, and Eσ will synthesize short products before transitioning to a stable elongation complex [START_REF] Revyakin | Abortive initiation and productive initiation by RNA polymerase involve DNA scrunching[END_REF], causing Eσ to escape from the promoter and enter transcriptional elongation. in the active center [START_REF] Vassylyev | Structural basis for substrate loading in bacterial RNA polymerase[END_REF].

Pauses occur during transcriptional elongation, and in prokaryotes, pausing is often combined with co-transcriptional translation (Irastortza-Olaziregi and Amster-Choder, 2020).

RNA polymerase can backtrack when it encounters DNA damage or transcriptional interference, or when it misincorporates nucleotides. Long pause events are associated with backtracking RNA polymerase [START_REF] Mohamed | Structural advances in transcription elongation[END_REF].

Termination

There are two mechanisms of transcription termination, intrinsic termination and Rhodependent termination, both of which can be involved in the control of gene expression. Both mechanisms act to disrupt the highly stable transcription elongation complex (EC), which includes RNAP, partially unwinds DNA forming a transcription bubble of approximately 12 residues, and the approximately 14 nucleotide (nt) newly transcribed RNA.

In intrinsic termination, the upstream region of the conserved DNA sequence is the stem- In genetics, attenuation is a regulatory mechanism for some bacterial operons that results in premature termination of transcription. In bacteria, transcriptional attenuation is frequently associated with transcription-coupled translation (see Section 3.5). This coupling is used to finely regulate gene expression in response to stress and nutrient levels [START_REF] Turnbough | Regulation of Bacterial Gene Expression by Transcription Attenuation[END_REF].

Transcription regulation

In the regulation of transcription, five distinct molecular mechanisms come into play, these are the promoter DNA sequences, sigma factors, small ligands, transcription factors, and the folded bacterial chromosome structure.

Transcription Factors

Transcription factors (TFs) are proteins that coordinate gene expression in a spatial and temporal manner in specific cell types. Transcription factors couple the expression of genes with environmental signals, and most transcription factors are sequence-specific DNA-binding proteins, which ensures that their action is directed to a specific promoter [START_REF] Madan Babu | Evolution of transcription factors and the gene regulatory network in Escherichia coli[END_REF][START_REF] Michelsen | Precise determinations of C and D periods by flow cytometry in Escherichia coli K-12 and B/r[END_REF]. As many as 50% of transcription factors in E. coli contain a domain that binds small molecules, allowing the induction of a broad but precisely controlled transcriptional program in response to multiple stimuli (Seshasayee et al., 2011).

Activating transcription factors (known as 'activators') increase the activity of promoters, often from low basal levels, by one of three mechanisms: class I activation, class II activation or activation by a conformational change. In type I activation, the activator binds to a site upstream of the promoter to recruit RNA polymerase to the promoter by contacting the α-subunit. In type II activation, the activator binds to a site in the promoter adjacent to (or overlapping) the -35 element, where it recruits RNA polymerase through direct interaction with sigma factor. The third class induces conformational changes in the promoter DNA to activate transcription.

These activators bind to or are close to the core RNA polymerase recognition elements of the promoter and often rearrange the -10 and -35 elements so that they can be recognized by RNA polymerase, allowing RNA polymerase to be recruited to the promoter and activate transcription [START_REF] Lee | Activating transcription in bacteria[END_REF].

There are two types of repression of repressive transcription factors, one is direct repression and the other is indirect repression. Repression of transcription initiation occurs exclusively through steric hindrance, in which the repressor binds to an operator that overlaps the -10 or -35 elements of the promoter, preventing RNA polymerase from entering the promoter.

Alternatively, protein-protein interactions are formed between repressors that bind sites upstream and downstream of a promoter, inducing DNA circularization between the two repressor binding sites [START_REF] Swint-Kruse | Allostery in the LacI/GalR family: variations on a theme[END_REF]. DNA circularization prevents RNA polymerase from recognizing the promoter element, thereby inhibiting transcription. Indirect repression, mediated by "anti-activator" repressors that counteract the function of activating transcription factors [START_REF] Valentin-Hansen | A flexible partnership: the CytR anti-activator and the cAMP-CRP activator protein, comrades in transcription control[END_REF].

It has been estimated that CRP, FNR, IHF, Fis, ArcA, NarL and Lrp are seven transcription factors that control 50% of all regulated genes, whereas ~60 transcription factors control only a single promoter [START_REF] Martínez-Antonio | Identifying global regulators in transcriptional regulatory networks in bacteria[END_REF].

CRP is the cyclic AMP receptor protein, a gene regulatory protein that is activated by cyclic AMP. CRP is often also referred to as CAP, the catabolite gene activator protein, which is named after its role in catabolite repression. FNR was named as the factor necessary for induction of fumarate reductase and nitrite reductase, but it is now known to regulate many more genes in response to oxygen starvation. IHF and Fis denote integration host factor and factor for Introduction inversion stimulation, respectively. Arc and Nar denote anaerobic respiratory control and nitrate regulation, respectively, and ArcA and NarL are the products of particular genes that are involved in each process. Lrp denotes the leucine regulatory protein [START_REF] Browning | The regulation of bacterial transcription initiation[END_REF]. [START_REF] Azam | Twelve Species of the Nucleoid-associated Protein from Escherichia coli. Sequence recognition specificity and dna binding affinity[END_REF][START_REF] Dillon | Bacterial nucleoid-associated proteins, nucleoid structure and gene expression[END_REF].

1
Fis and H-NS are two important factors for regulation of gene expression as a function of growth phase and have been show to regulate the expression of ribosomal operons. H-NS forms filaments along AT-rich DNA fragments, and these filaments form bridges between different fragments to repress the activity of any associated promoters [START_REF] Brambilla | Gene regulation by H-NS as a function of growth conditions depends on chromosomal position in Escherichia coli[END_REF][START_REF] Dorman | H-NS: a universal regulator for a dynamic genome[END_REF]. Fis can directly activate transcription by interacting with the RNA polymerase holoenzyme using the activation domain, but is also capable of repressing transcription initiation through various mechanisms [START_REF] Aiyar | Architecture of Fis-activated transcription complexes at the Escherichia coli rrnB P1 and rrnE P1 promoters[END_REF][START_REF] Rossiter | Expression of different bacterial cytotoxins is controlled by two global transcription factors, CRP and Fis, that co-operate in a shared-recruitment mechanism[END_REF].

Global regulation

In E. coli, most promoters are regulated by more than one factor, and many transcription factors are expressed from promoters that are themselves regulated by other transcription factors. Regulation of promoters by transcription factors thus generates a complex regulatory network in which the coordinated activity of specific, global, and master regulators coordinates the growth state of the cell [START_REF] Dorman | Function of nucleoid-associated proteins in chromosome structuring and transcriptional regulation[END_REF][START_REF] Ishihama | Prokaryotic genome regulation: a revolutionary paradigm[END_REF].

Moreover, regulation of gene expression can take place through mechanisms that are independent of specific transcription factors. One important factor for global regulation of gene expression is DNA topology and its close coupling with NAPs [START_REF] Travers | DNA supercoiling -a global transcriptional regulator for enterobacterial growth?[END_REF]. As transcription elongation progresses, DNA downstream of the transcription complex becomes positively supercoiled, while DNA in regions upstream becomes negatively supercoiled, so DNA supercoiling and transcription are interdependent (see 1. or their isomerization of open complexes. This mechanism is linked in such a way that the generation of single-stranded bubbles in double-stranded DNA is essential during transcription [START_REF] Dorman | DNA supercoiling and transcription in bacteria: a two-way street[END_REF]. Different genes are expressed differently under both DNA relaxation and negative supercoiling conditions [START_REF] Travers | DNA supercoiling -a global transcriptional regulator for enterobacterial growth?[END_REF].

In E. coli, the distribution of RNAP is not uniform [START_REF] Cabrera | Active transcription of rRNA operons condenses the nucleoid in Escherichia coli: examining the effect of transcription on nucleoid structure in the absence of transertion[END_REF][START_REF] Sendy | RNA polymerase supply and flux through the lac operon in Escherichia coli[END_REF]. The changes in the concentration of RNAP affect transcription factor-independent gene expression (from a constitutive promoter) [START_REF] Patrick | Free RNA polymerase in Escherichia coli[END_REF]. It has been shown that the growth rate dependence of unsaturated constitutive promoters is directly proportional to that of free RNAP [START_REF] Klumpp | Growth-rate-dependent partitioning of RNA polymerases in bacteria[END_REF][START_REF] Liang | Activities of constitutive promoters in Escherichia coli[END_REF]. Transcriptional pausing, caused by ppGpp and by the hairpin structure of nascent RNA, can affects the concentration of active RNAP and alters transcriptional efficiency [START_REF] Artsimovitch | Pausing by bacterial RNA polymerase is mediated by mechanistically distinct classes of signals[END_REF][START_REF] Landick | The regulatory roles and mechanism of transcriptional pausing[END_REF]. At the same time, the distribution of free RNAP concentration in the cell can also affect gene expression. This effect is achieved by affecting transcription initiation frequency [START_REF] Patrick | Free RNA polymerase in Escherichia coli[END_REF].

During the stringent response, when cells enter stationary phase, ribosomal gene expression is repressed by ppGpp, and thus free RNAP increases, as cells shift their energy allocation from a strategy of producing large numbers of ribosomes to support rapid growth to maintain fundamental metabolism to ensure cell survival in a slow-growing environment [START_REF] Patrick | Free RNA polymerase in Escherichia coli[END_REF].

Global regulation is a complex process involving multiple physiological processes in bacteria, and the influence of these complex factors has so far remained elusive.

Translation

Translation is the last step in gene expression, during which the coding sequence of mRNA (messenger RNA) is translated into the amino acid sequence of a protein. The whole translation Introduction process includes four stages: initiation, elongation, termination and ribosome recycling.

The major building blocks of the translation process are codons, nucleotide triplets in mRNA that encode specific amino acids for incorporation into polypeptide chains. tRNA (transfer RNA) acts as a bridge between nucleotides and amino acids, matching codons and corresponding amino acids. The ribosome provides an environment that allows protein synthesis. It acts like a molecular scaffold that facilitates the interaction between the codons in the mRNA and the anticodons in the tRNA. Ribosomes also have peptidyl transferase activity that allows the formation of peptide bonds between adjacent amino acids.

History

In [1954][1955][1956][1957][1958][1959][1960][1961], three bases in a nucleic acid molecule determine an amino acid [START_REF] Crick | General nature of the genetic code for proteins[END_REF][START_REF] Gamow | Possible Relation between Deoxyribonucleic Acid and Protein Structures[END_REF].

In 1961-1966, the genetic code is deciphered [START_REF] Nirenberg | The RNA Code and Protein Synthesis[END_REF][START_REF] Nirenberg | The dependence of cell-free protein synthesis in E. coli upon naturally occurring or synthetic polyribonucleotides[END_REF].

In 1955, electron microscopy of stained thin sections of rat pancreas reveals an unusual pattern of granules -ribosomes -on the outer surface of the endoplasmic reticulum [START_REF] Palade | A small particulate component of the cytoplasm[END_REF].

In 1958, bacterial ribosomes consist of a 70S particle that can be broken down into two smaller components, the small and large subunits, while the 100S particles are aggregates of 70S [START_REF] Tissieres | Ribonucleoprotein particles from Escherichia coli[END_REF].

In 1958, the discovery of tRNA [START_REF] Hoagland | A soluble ribonucleic acid intermediate in protein synthesis[END_REF].

In 1968, an active 30S subunit can be assembled in vitro from free rRNA and ribosomal proteins without any additional components, and experiments have shown that all the information required for assembly is encoded in the rRNA and the protein itself [START_REF] Traub | Structure and function of E. coli ribosomes. V. Reconstitution of functionally active 30S ribosomal particles from RNA and proteins[END_REF].

In 1969, Elongation Factor G (EF-G) and Elongation Factor Tu (EF-Tu) were discovered [START_REF] Lipmann | Polypeptide chain elongation in protein biosynthesis[END_REF].

In 1974, the biologically active 50S subunit was successfully reconstituted under nonphysiological conditions [START_REF] Nierhaus | Total reconstitution of functionally active 50S ribosomal subunits from Escherichia coli[END_REF].

In 1978-1982, characterization of fully assembled ribosomal particles [START_REF] Bernabeu | Nascent polypeptide chains emerge from the exit domain of the large ribosomal subunit: immune mapping of the nascent chain[END_REF][START_REF] Brimacombe | Ribosome structure[END_REF][START_REF] Lake | Protein synthesis[END_REF].

In 1991, the first structure of the bacterial 70S ribosome under near-native conditions was obtained by cryo-EM [START_REF] Frank | Three-dimensional reconstruction of the 70S Escherichia coli ribosome in ice: the distribution of ribosomal RNA[END_REF].

Ribosome structure and organization

In prokaryotes, dispersed in the cytoplasm, ribosomes decode the genetic information contained in mRNA transcripts and synthesize nascent polypeptide chains (NCs) that fold into functional proteins. In all living organisms, ribosomes contain two ribonucleoprotein subunits. In bacteria, the subunits are designated 30S and 50S, and together make up the 70S ribosome [START_REF] Tissieres | Ribonucleoprotein particles from Escherichia coli[END_REF]) (Figure 5). Each subunit has three binding sites for tRNA, designated the A (aminoacyl), which accepts the incoming amino-acylated tRNA; P (peptidyl), which hold the tRNA with the nascent peptide chain; and E (exit), which holds the deacylated tRNA before it leaves the ribosome. The small subunit mediates base-pairing interactions between mRNA and tRNA, thereby determining the sequence of the polypeptide chain. The large subunit contains the peptidyl transferase center (PTC), a site that catalyzes peptide bond formation. It catalyzes the esterification of one tRNA to the transfer of the C-terminal carboxylic acid group of the nascent polypeptide to the α-amino group of a group of amino acids to another tRNA. This reaction converts a polypeptide of n amino acids long into a polypeptide of (n + 1) amino acids long.

Ribosome assembly is a central component of the overall program of ribosome biogenesis, which is a complex and highly coordinated process. The basic steps of ribosome assembly involve (a) the transcription, processing, and modification of rRNA; (b) the translation and modification of ribosomal proteins; (c) the proper folding of rRNA and ribosomal proteins; (d) the binding of ribosomal proteins; and (e) the binding and release of assembly factors. Many of these steps are coupled and occur in parallel during the transcription of the rRNAs. The assembly process is believed to progress through an alternating series of RNA conformational changes and protein-binding events, whereby RNA folding gains are stabilized by the binding of ribosomal proteins, incrementally driving the RNA structure to the final native state [START_REF] Shajani | Assembly of Bacterial Ribosomes[END_REF].

Introduction

Figure 5. The E. coli 70S ribosome.

Rendering of the E. coli 70S ribosome. The small subunit is on the left and the large subunit is on the right. 16S

rRNA is shown in blue, S-protein is shown in orange, 23S rRNA is shown in red, 5S rRNA is shown in pink, and L-protein is shown in green [START_REF] Shajani | Assembly of Bacterial Ribosomes[END_REF].

Transfer RNA

tRNA is an essential part of the protein biosynthesis machinery, mediating the transfer of amino acids to ribosomes (Figure 6). During translation, aminoacyl-tRNA synthetase (aaRS) catalyzes the attachment of amino acids to the 30-CCA terminus of tRNAs. After forming a ternary complex with GTP and elongation factors, the charged tRNA enters the ribosome, where its anticodon interacts with one of the messenger RNA (mRNA) codons (S. Wu et al., 2022).

Subsequently, the amino acid is covalently transferred to the C-terminus of the extended polypeptide. A typical tRNA consists of 76 nucleotides, but the number can be 72-96. The classic secondary structure, often referred to as the "clover" structure, consists of the CCA terminus, acceptor stem, anticodon loop, T-loop, D-loop, and variable loop. When folded up, tRNA adopts a near vertical angle geometry; where the CCA end is 75 angstroms away from the anticodon loop [START_REF] Guo | The Origin of Translation: Bridging the Nucleotides and Peptides[END_REF].

Messenger RNA

The true start codon in the mRNA is preceded by a purine-rich sequence that is complementary to and base-pairs to a sequence near the 3' end of the 16S rRNA [START_REF] Jacob | A single base change in the Shine-Dalgarno region of 16S rRNA of Escherichia coli affects translation of many proteins[END_REF][START_REF] Steitz | How ribosomes select initiator regions in mRNA: base pair formation between the 3' terminus of 16S rRNA and the mRNA during initiation of protein synthesis in Escherichia coli[END_REF]. This Shine-Dalgarno (SD) sequence in mRNA is typically 4 or 5 nt in length. The SD is usually located approximately 5-8 nt upstream of the start codon. An exhaustive analysis of E. coli genes documented the presence of all SD sequences with few exceptions [START_REF] Chen | Determination of the optimal aligned spacing Bibliography between the Shine-Dalgarno sequence and the translation initiation codon of Escherichia coli mRNAs[END_REF][START_REF] Shultzaberger | Anatomy of Escherichia coli ribosome binding sites[END_REF]. mRNA sequences are numbered by designating the A of the AUG codon as +1. The preceding base is position -1 and negative numbering proceeds upstream. The ribosome binding site (RBS), defined as the segment of mRNA that protects against RNase digestion, consists of ~15 nt on each side of the AUG codon.

The polycistronic structure of mRNA can lead to coupled translation, the type of regulation in which the expression of prokaryotic genes through polycistronic transcripts enables the coupling of translation of a downstream cistron to that of a preceding cistron. This is achieved through conformational constraints that are relieved as the ribosome translates upstream cistrons [START_REF] Butkus | Translocon "pulling" of nascent SecM controls the duration of its translational pause and secretion-responsive secA regulation[END_REF][START_REF] Chen | Features of a leader peptide coding region that regulate translation initiation for the anti-TRAP protein of B. subtilis[END_REF][START_REF] Gu | Anti-peptidyl transferase leader peptides of attenuation-regulated chloramphenicol-resistance genes[END_REF].

Introduction

The process of translation 1.2.4.1. Initiation

In prokaryotes, mRNAs contain an extended 5' untranslated region and a SD sequence located 8-10 nt upstream of the start codon. During translation initiation, the small subunit (30S,SSU)

is recruited to the ribosome-binding site (RBS) through the interaction between the SD sequence and the complementary anti-SD (aSD) sequence in 16S ribosomal RNA (rRNA). The initiation factors IF1, IF2, and IF3 promote SD-led mRNA initiation (Figure 7).

The roles of IF1, IF2 and IF3 are different. IF1 enhances the activities of IF2 and IF3. IF2 is a GTPase that recruits the promoter fMet-tRNA fMet . IF3 interferes with subunit binding, ensures fMet-tRNA fMet selection with higher fidelity than extended aminoacyl-tRNA (aa-tRNA), and helps distinguish mRNAs with unfavorable translation initiation regions (TIRs) [START_REF] Gualerzi | Initiation of mRNA translation in bacteria: structural and dynamic aspects[END_REF].

Elongation

The elongation process starts at the second codon of the ORF where the aa-tRNA read can be extended and ends when the ribosome reaches the stop codon. Dynamic repeated cycles of decoding, peptide bond formation, and translocation are required during elongation. In prokaryotes, the translation factors EF-Tu, EF-G, EF-P and SelB are involved in promoting the process.

During decoding, the ribosome translates the sequence of codons in an mRNA into the amino acid sequence of a protein. The codon at the A site is recognized by aa-tRNA in a ternary complex with EF-Tu and GTP. The interaction of the aa-tRNA anticodon with the mRNA codon in the SSU decoding site triggers the hydrolysis of GTP by EF-Tu. After Pi release, EF-Tu rearranges to a guanosine diphosphate (GDP)-bound form and releases aa-tRNA. aa-tRNA is accommodated at the A site of the Large subunit (LSU), whereas EF-Tu•GDP is segregated from ribosomes [START_REF] Rodnina | Ribosome dynamics during decoding[END_REF]. EF-Tu is a general translation factor that directs each elongating aa-tRNA to the A site, while SelB is a specialized elongation factor responsible for the delivery of the 21st natural proteinogenic amino acid selenocysteine [START_REF] Forchhammer | Identification of a novel translation factor necessary for the incorporation of selenocysteine into protein[END_REF].

Peptide bond formation occurs at the peptidyl transferase center of the ribosome, where peptidyl-tRNA at the P site reacts with aa-tRNA at the A site to form a peptide bond. Protein synthesis sometimes needs the helps from elongation factors. For example, the presence of proline (pro) in the polypeptide chain can have a dramatic effect on translation efficiency, and ribosome stalling is due to the gap between the peptidyl-Pro-Pro-tRNA at the P site and the Pro-tRNA at the A site, occurs through the slow formation of peptide bonds. When synthesizing a polyproline sequence with three or more consecutive prolines or a different sequence with two prolines flanked by specific amino acids, ribosomes stall due to a low rate of peptide bond formation. Elongation Factor P (EF-P) can relieve the stalling of poly-Pro motifs [START_REF] Doerfel | EF-P is essential for rapid synthesis of proteins containing consecutive proline residues[END_REF]. EF-P binds to the 70S ribosome at a site located between the peptidyl tRNA (P site) and existing tRNA (E site) binding sites and appears to stabilize the localization of fMet-tRNAi fMet in the P site. They seem likely to increase the rate of peptide bond formation by facilitating the localization and stabilization of peptidyl-Pro-tRNA on the ribosome rather than directly participating in catalysis [START_REF] Blaha | Formation of the first peptide bond: the structure of EF-P bound to the 70S ribosome[END_REF].

Introduction

After peptide bond formation, the ribosomal subunits move relative to each other from a nonrotating state with the two tRNAs bound to the P and A sites on the SSU and LSU, to a rotated state with the bound tRNA in mixed P/E and A/P state [START_REF] Frank | Structure and dynamics of a processive Brownian motor: the translating ribosome[END_REF]. EF-G facilitates translocation at the expense of GTP hydrolysis. EF-G acts as a ratchet to aid ribosome directional movement and facilitates key conformational rearrangements of the SSU disrupting its interaction with tRNAs, thereby allowing rapid tRNA translocation. As ribosomes move along mRNA, stems may be encountered structures such as loops or pseudoknots, ribosomal helicases, composed of the ribosomal proteins uS3, uS4, and uS5, ensure mRNA unwinding through a combination of active and passive helicase mechanisms [START_REF] Takyar | mRNA helicase activity of the ribosome[END_REF].

Termination and recycling

Termination occurs when the ribosome encounters a stop codon in the mRNA. In bacteria, stop codons are recognized by the stop (or release) factors RF1 and RF2, which read the codons UAG/UAA and UGA/UAA, respectively. Another termination factor, RF3, promotes the turnover of RF1 and RF2 but is not required for peptidyl-tRNA hydrolysis [START_REF] Rodnina | Translation in Prokaryotes[END_REF].

After termination, ribosomes still contain mRNA and tRNA, which must be released to allow reuse of ribosomal subunits in the next round of priming. Ribosome recycling factor (RRF) and EF-G catalyze subunit fission. RRF binds to the ribosome's A site and stabilizes the fully rotated state of the ribosome, and hydrolysis of GTP by EF-G facilitates RRF's push to key intersubunit bridges, thereby promoting subunit splitting [START_REF] Dunkle | Structures of the bacterial ribosome in classical and hybrid states of tRNA binding[END_REF].

ppGpp

The "magic spots", which were identified as guanosine 5'-diphosphate 3'-diphosphate (ppGpp) referred to as "alarmones", were discovered by Cashel and Gallant in 1969. The alarmone ppGpp is a key secondary messenger involved in regulating various biochemical and physiological processes of bacterial cells. Intracellular concentrations of ppGpp are determined by a highly conserved and widely distributed family of proteins called RelA-SpoT Homologs (RSH). When cells encounter stressful conditions, RSH produces ppGpp, and high levels of ppGpp trigger a process known as the "stringent response." Under stringent responses, ppGpp remodels bacterial metabolism and physiology, slowing growth and reallocating cellular resources during nutrient stress. As a messenger molecule under stressful conditions, ppGpp has been found to play key roles in numerous biological processes such as virulence, antibiotic resistance and resistance, long-term persistence, biofilm formation, sporulation or symbiotic bacteria colonization of the intestinal tract (Potrykus and Cashel, 2008). In addition to stressful conditions, ppGpp can also act as a traditional regulator of metabolism or cell cycle progression, suggesting that basal levels of ppGpp also play an important role in cellular homeostasis.

Synthesis and hydrolysis of ppGpp

The synthesis and hydrolysis of ppGpp are controlled by the RelA-SpoT homologue (RSH) family of proteins (Figure 8). RelA can sense stress by directly detecting the translational capacity of cells. During normal growth, amino acids are delivered to the ribosome acceptor site (A site) in the form of aminoacylated tRNA molecules, where they are added to the nascent polypeptide during synthesis. Under translationally limited conditions, unconjugated deacylated tRNA accumulates and enters the A site, which strongly activates the ppGpp synthesis activity of RelA [START_REF] Haseltine | Synthesis of guanosine tetra-and pentaphosphate requires the presence of a codon-specific, uncharged transfer ribonucleic acid in the acceptor site of ribosomes[END_REF]. In addition to deacylated tRNA, ppGpp is another allosteric activator of RelA, thereby constructing a conditional positive feedback loop [START_REF] Shyp | Positive allosteric feedback regulation of the stringent response enzyme RelA by its product[END_REF]. In E. coli, SpoT has weak ppGpp synthetic activity and strong hydrolytic activity [START_REF] An | Cloning the spoT gene of Escherichia coli: identification of the spoT gene product[END_REF][START_REF] Xiao | Residual guanosine 3',5'-bispyrophosphate synthetic activity of relA null mutants can be eliminated by spoT null mutations[END_REF]. The hydrolytic function of SpoT is critical for balancing cellular ppGpp concentrations in the presence of RelA. Amino acid starvation leads to the accumulation of deacylated tRNAs in the cytosol that bind to the ribosomal Asite. This ribosomal state is recognized by RelA, which binds to the 50S subunit and adopts an active conformation.

Activation of RelA and consequent synthesis of (p)ppGpp leads to its dissociation from the ribosome, followed by numerous rounds of (p)ppGpp synthesis in the dissociated state. Increased (p)ppGpp levels direct cellular metabolic resources to amino acid synthesis, which restores normal levels of tRNA aminoacylation.

Aminoacylated tRNA is delivered to the ribosome by elongation factor Tu (EF-Tu) in direct competition with binding of RelA and deacylated tRNA (The figure is adapted from [START_REF] Hauryliuk | Recent functional insights into the role of (p)ppGpp in bacterial physiology[END_REF].

Introduction

ppGpp regulates the transcription process

In E.coli, ppGpp directly interacts with RNAP to destabilize short-lived open complexes formed at certain promoters, such as those of ribosomal RNA (rRNA) genes, thereby directly repressing transcription initiation [START_REF] Barker | Mechanism of regulation of transcription initiation by ppGpp. I. Effects of ppGpp on transcription initiation in vivo and in vitro[END_REF][START_REF] Paul | DksA: a critical component of the transcription initiation machinery that potentiates the regulation of rRNA promoters by ppGpp and the initiating NTP[END_REF]. The crystal structure of E. coli RNAP in complex with ppGpp was reported in 2013 and 2018. The structures show that ppGpp has two distinct binding sites for RNAP (Figure 9). Site 1 is located at the interface of the β′-ω subunit, without the involvement of DksA [START_REF] Mechold | Differential regulation by ppGpp versus pppGpp in Escherichia coli[END_REF][START_REF] Zuo | The mechanism of E. coli RNA polymerase regulation by ppGpp is suggested by the structure of their complex[END_REF], possibly preventing the hinge-like movement between domains. Site 2 is located at the interface of RNAP and the RNAP-binding transcription factor DksA, and since site 2 is partially composed of DksA, ppGpp may enhance the negative regulation proposed for DksA itself [START_REF] Molodtsov | Allosteric Effector ppGpp Potentiates the Inhibition of Transcript Initiation by DksA[END_REF].

It has been hypothesized that ppGpp binding may affect RNAP-promoter interactions by stabilizing the DkSA conformation involving the interaction of the C-terminal helix with nearby RNAP regions [START_REF] Parshin | DksA regulates RNA polymerase in Escherichia coli through a network of 92 interactions in the secondary channel that includes Sequence Insertion 1[END_REF][START_REF] Ross | ppGpp Binding to a Site at the RNAP-DksA Interface Accounts for Its Dramatic Effects on Transcription Initiation during the Stringent Response[END_REF].

In Escherichia coli, negative regulation of rRNA promoters by ppGpp and DksA is closely associated with G+C-rich discriminative regions in the promoters [START_REF] Travers | Promoter Sequence for Stringent Control of Bacterial Ribonucleic Acid Synthesis[END_REF]. Further studies showed that a guanine residue on the non-template strand just downstream from the -10 hexamer fits into a pocket in σ region 1.2, and it is the absence of this guanine residue in rRNA promoters that contributes to the short half-life needed for regulation of the promoter complex by ppGpp/DksA [START_REF] Haugen | rRNA promoter regulation by nonoptimal binding of sigma region 1.2: an additional recognition element for RNA polymerase[END_REF][START_REF] Zhang | Structural basis of transcription initiation[END_REF]. For the negatively regulated rrnB P1 promoter, its regulation by DksA and ppGpp occurs when it forms an unstable open complex with RNAP. ppGpp and DksA act at a step after the formation of the initial closed complex but before the formation of the first phosphodiester bond. However, once formed, their open complexes are relatively stable and insensitive to inhibition by DksA/ppGpp [START_REF] Barker | Mechanism of regulation of transcription initiation by ppGpp. I. Effects of ppGpp on transcription initiation in vivo and in vitro[END_REF][START_REF] Paul | DksA potentiates direct activation of amino acid promoters by ppGpp[END_REF][START_REF] Rutherford | Allosteric control of Escherichia coli rRNA promoter complexes by DksA[END_REF]. At the same time, ribosomal protein (r-protein) synthesis is also regulated by a translational feedback mechanism. When free rRNA is not available, the translational repressor protein r-protein binds to its mRNA target, inhibits translation of the upstream cistron in the r-protein operon leading to the formation of mRNA secondary structure, thereby preventing the translation of the downstream cistron, coordinating most (or all) the synthesis rates of r proteins to each other and rRNA [START_REF] Lemke | Direct regulation of Escherichia coli ribosomal protein promoters by the transcription factors ppGpp and DksA[END_REF][START_REF] Nomura | Regulation of the synthesis of ribosomes and ribosomal components[END_REF].

ppGpp regulates the translation process

Ribosomes are composed of 3 types of RNA (rRNA) and 52 proteins. These three rRNAs are processed from 35S primary transcripts derived from seven unlinked rrn transcription units (operons). Fifty-two different ribosomal proteins (r-proteins) are encoded by genes in about 20 different transcription units located at 14 different locations on the E. coli chromosome [START_REF] Bachmann | Linkage map of Escherichia coli K-12, edition 8[END_REF]. Each of the seven rRNA (rrn) operons is composed of two tandem promoters, P1 and P2, from which rRNA transcripts are expressed. The promoters of all seven P1 rrn promoters share the same GC-rich discriminator sequence and are sensitive to ppGpp [START_REF] Bremer | Modulation of Chemical Composition and Other Parameters of the Cell at Different Exponential Growth Rates[END_REF].

ppGpp/DksA directly inhibits rRNA and r-protein synthesis (Figure 10). The extent to which r-protein promoters are regulated by ppGpp/DksA varies by promoter, but some promoters are Introduction almost as repressed as rRNA promoters. At the same time, the r-protein genes also have a translation feedback mechanism (as described above). ppGpp directly represses the process of translation (Figure 11). In the initiation, IF2 associates with GTP, localizes initiator fMet-tRNAfMet in the 30S pre-initiation complex, and promotes the association of the 50S subunit, which is inhibited by ppGpp. During translation elongation and translocation, ppGpp inhibits the binding of the elongation factor EF-Tu to GTP to prevent aminoacyl-tRNA from binding to the A site of the 70S ribosome, and inhibits the binding of EF-G to the translocase GTP to prevent ammonia Acyl-tRNA translocation by ribosomes.

During termination and recycling, ppGpp inhibits RF3 to prevent ribosome recycling. RRF and EF-G can help recycle ribosome after termination, this process may be also inhibited by ppGpp interacting with EF-G.

ppGpp and DNA supercoiling

DNA supercoiling in the E. coli chromosome is largely controlled by topoisomerases, specifically DNA gyrase, which relax positive supercoils and introduce negative supercoils and DNA topoisomerase I which relaxes negative supercoils [START_REF] Vos | All tangled up: how cells direct, manage and exploit topoisomerase function[END_REF] (Figure 12).

Negatively supercoiled DNA is less wound and thus more easily melted, thereby facilitating formation of the open complex at promoters and replication initiation [START_REF] Magnan | Regulation of DNA Replication Initiation by Chromosome Structure[END_REF]. One of the major sources of negative supercoiling in bacterial chromosomes is transcription, especially rRNA, which can account for up to 80% of all transcription at fast growth rates [START_REF] Bremer | Modulation of Chemical Composition and Other Parameters of the Cell at Different Exponential Growth Rates[END_REF][START_REF] Rosenow | Prokaryotic RNA preparation methods useful for high density array analysis: comparison of two approaches[END_REF]. Furthermore, six of the seven rRNA loci in E. coli are within 300 kb of oriC (rrnC is only 12 kb away), and each is oriented in the same direction as replication [START_REF] Blattner | The complete genome sequence of Escherichia coli K-12[END_REF]. ppGpp affects supercoiling by repressing transcription of ribosomal operons directly and through its regulation of Fis expression. Fis in turn regulates the expression of the gyrase genes (Travers et al., 2001)(Figure 12). ppGpp therefore inhibits initiation of DNA replication in E. coli primarily by reducing negative supercoiling, a consequence of its inhibition of bulk transcription [START_REF] Kraemer | The Stringent Response Inhibits DNA Replication Initiation in E. coli by Modulating Supercoiling of oriC[END_REF]. At the same time, previous research has shown that the level of DNA supercoiling and Introduction the compaction of E. coli chromosomes is related to the growth rate. Chromosomes normally condense at high growth rates when ppGpp levels are lowest, but after acute starvation chromosomes become relaxed or decondensed in a ppGpp-dependent manner, possibly due to arrest of rRNA transcription [START_REF] Cabrera | Active transcription of rRNA operons condenses the nucleoid in Escherichia coli: examining the effect of transcription on nucleoid structure in the absence of transertion[END_REF][START_REF] Ferullo | The stringent response and cell cycle arrest in Escherichia coli[END_REF].

Transcription and Translation Coupling

Prokaryotic cells lack a nuclear envelope that physically separates chromosomal DNA from the cytosolic environment, and it is widely accepted that transcription and translation are spatiotemporally coupled in bacteria. Transcription-translation coupling occurs when ribosomes bind and begin to translate nascent mRNA whose transcription has not yet terminated.

The coupling of transcription and translation is a manifestation of the coordinated control of gene expression between the two molecular machineries, the one that synthesizes and the one that decodes prokaryotic mRNA.

One aspect of coupling is the synchronization of mRNA synthesis and translation rates [START_REF] Zhu | Disruption of transcription-translation coordination in Escherichia coli leads to premature transcriptional termination[END_REF]. This synchronization minimizes the excess energy of unused mRNA or ribosome queuing [START_REF] Chen | RNA polymerase's Relationship with the Ribosome: Not So Physical, Most of the Time[END_REF]. Ribosome regulation of transcription termination is another important aspect of coupling. It underlies polarity effects, a form of mRNA quality control in which increased distance between RNAP and trailing ribosomes leads to termination of transcription.

There are two ways of coupling of transcription and translation, one is physical coupling where RNA polymerase and ribosomes are directly connected by coupling factors. The other is indirect coupling mediated through a secondary messenger (ppGpp) (Figure 13).

Physical coupling occurs in two forms; one through the NusG and NusA transcription elongation factors and the other is the collided expressosome. When physical coupling is achieved through the NusG and NusA transcription factors, they form a molecular bridge between the ribosome and RNAP. NusG-and NusA-mediated coupling does not produce structural changes within the ribosome or RNAP [START_REF] Burmann | A NusE:NusG complex links transcription and translation[END_REF][START_REF] O'reilly | In-cell architecture of an actively transcribing-translating expressome[END_REF][START_REF] Saxena | Escherichia coli transcription factor NusG binds to 70S ribosomes[END_REF][START_REF] Wang | Structural basis of transcription-translation coupling[END_REF]. The structure of the collided expressosome is that the mRNA exit channel of the RNAP is adjacent to and aligned with the mRNA entry channel of the ribosome. The ribosome inhibits the pausing of RNAP, so the rate of translation affects the rate of transcription. Physical coupling also allows ribosomes to release stalled transcription complexes that can collide with the DNA replication machinery and cause genome instability (Dutta et al., 2011).

In addition, previous studies have proposed that there can be an indirect coupling by the activity of ppGpp affecting both transcription and translation rates (Irastortza-Olaziregi and Amster-Choder, 2020). ppGpp also regulates transcriptional elongation of mRNA and is a mechanism that synchronizes the rate of transcription with that of translation. Under nutrientpoor conditions, charged tRNA levels are restricted due to increased ppGpp, thereby reducing translation elongation rates. Translation speed is therefore dependent on the ppGpp pool. At the same time, increases of ppGpp also directly inhibit transcriptional elongation. The extent of this inhibitory interaction could in principle be tuned to match the relationship between ppGpp pool and translational extension velocity [START_REF] Zhu | Disruption of transcription-translation coordination in Escherichia coli leads to premature transcriptional termination[END_REF]. Thus, ppGpp can regulate the coordination between ribosome and RNAP rates without physical coupling. Translation and transcription can have independent regulatory mechanisms while being coupled. This mechanism poses a challenge to the generality of physical coupling.

Introduction

At the same time, some evidence of uncoupling of translation and transcription was also found, and the experiments that proved the coupling were only verified with a few genes, so it is still controversial whether there is a common event of coupling or an accidental event. There are several antibiotic-inhibited pathways: the synthesis of cell wall (β-lactam antibiotics, Glycopeptide antibiotics), the synthesis of protein (Macrolides, aminoglycosides, tetracycline's, and Chloramphenicol), the synthesis of nucleic acid (Fluoroquinolones), different metabolic pathways/bacterial enzymes (Sulphonamide, Diaminopyrimidine antibiotics), and the synthesis of the bacterial membrane (Polymyxins antibiotic) [START_REF] Abushaheen | Antimicrobial resistance, mechanisms and its clinical significance[END_REF].

Along with the discovery of antibiotics came the discovery of antibiotic resistance. With the passage of time and the overuse of antibiotics, antibiotic resistance poses a major threat to human health worldwide (Murray et al., 2022). The study of the interaction mechanism between antibiotics and bacteria is very valuable for understanding the formation of antibiotic resistance.

Mechanisms of bacterial resistance fall into three broad categories, (1) intrinsic resistance (eg, cell membranes and efflux pumps), (2) acquired resistance (eg, plasmid exchange or mutations to withstand higher antibiotic concentrations) (3) adaptive resistance (bacteria temporarily increase their ability to survive antibiotics due to changes in gene or protein expression) [START_REF] Fernández | Adaptive and mutational resistance: role of porins and Bibliography efflux pumps in drug resistance[END_REF][START_REF] Sandoval-Motta | Adaptive resistance to antibiotics in bacteria: a systems biology perspective[END_REF][START_REF] Suarez | Gene Amplification Uncovers Large Previously Unrecognized Cryptic Antibiotic Resistance Potential in E. coli[END_REF].

Antimicrobials produced and used by humans for medicine and agriculture are released in the environment, creating antibiotic gradients that expose bacteria to concentrations above and below the minimal inhibitory concentration (MIC).

An environment of sublethal concentrations of antibiotics may lead to an accelerated evolution of antibiotic resistance. Sublethal antibiotics act at three distinct levels: selection of resistant strains (enrichment of existing resistant bacteria and selection of new resistance); production of genetic and phenotypic variability of bacteria (acceleration of adaptation speed of sexual evolution); dissemination of biological signals (affecting physiological processes such as virulence, biofilm formation, and gene expression) (Andersson and Hughes, 2014;[START_REF] Lorian | Some effects of subinhibitory concentrations of antibiotics on bacteria[END_REF]. Therefore, the study of cell physiological regulation at sublethal antibiotic concentrations is of great significance for understanding antibiotic resistance.

Introduction

Translation as a target of antibiotics

Since the ribosome is one of the most important parts for bacterial growth, antibiotic inhibitors that target the ribosome are very effective. Antibiotics of the translation-inhibiting type account for more than half of all drugs clinically used for bacterial infections, where different antibiotics target different steps in the translation process [START_REF] Wilson | The A-Z of bacterial translation inhibitors[END_REF] (Figure 14).

In the initial stage of protein synthesis, the antibiotics edenine (Ede), kasugamycin (Ksg), pactamycin (Pct) and thermorubin (Thb), avilamycin (Avn), everimycin (Evn) and thiostrepton (Ths) inhibit translation initiation by preventing ribosome formation and stable interaction between the initiating tRNA and the P-site initiation codon [START_REF] Kavčič | Mechanisms of drug interactions between translation-inhibiting antibiotics[END_REF]Wilson, 2014a). formation [START_REF] Kavčič | Mechanisms of drug interactions between translation-inhibiting antibiotics[END_REF]Wilson, 2014a).

During the termination and recycling phases, peptidyl-transferase inhibitors (Bls, Cam, Pmn, and Spr) inhibit termination, while translocation inhibitors (Fus) inhibit recycling [START_REF] Polacek | The ribosomal peptidyl transferase center: structure, function, evolution, inhibition[END_REF].

Chloramphenicol

Chloramphenicol (CHL, Cam or Cm) is a classic ribosomal antibiotic inhibitor [START_REF] Hodgman | Chloramphenicol[END_REF]. On the one hand, researchers explore the mechanism of CHL as an antibiotic, as an inhibitor of cell physiology, and on the other hand, use it as a tool to change the physiological state of cells to study the mechanism of cell's own physiological regulation for adaptation. CHL functions as a competitive inhibitor, preventing the binding of the aminoacyl portion of any incoming aminoacyl-tRNA (aa-tRNA) to the ribosomal A-site, thereby inhibiting peptide bond formation (Drainas et al., 1987). However, while this is generally the accepted role of CHL, the model fails to account for differential suppression of template-specific translations [START_REF] Choi | Dynamics of the context-specific translation arrest by chloramphenicol and linezolid[END_REF].

The affinity of CHL for peptide-free ribosomes is not sufficient for drug molecules to effectively compete with incoming aminoacyl-tRNAs. However, once the emerging peptide reaches a certain length (3-6 amino acids), CHL is better anchored in the nascent peptide exit Introduction tunnel [START_REF] Marks | Context-specific inhibition of translation by ribosomal antibiotics targeting the peptidyl transferase center[END_REF]. The latest study elucidates in more detail how CHL inhibits the ribosome [START_REF] Syroegin | Structural basis for the context-specific action of the classic peptidyl transferase inhibitor chloramphenicol[END_REF] (Figure 15). Glycine, which does not interfere with the binding of CHL to the ribosome but also does not increase the affinity of CHL, loosely bound CHL is displaced from the ribosomal A site by incoming aa-tRNA [START_REF] Syroegin | Structural basis for the context-specific action of the classic peptidyl transferase inhibitor chloramphenicol[END_REF].

Cell size

During the growth of bacteria, they need to constantly make physiological adjustments according to the environment, and the adjustment of cell size is closely related to growth rate and nutrient absorption [START_REF] Young | The selective value of bacterial shape[END_REF]. Changes in cell volume or surface area will affect the cell's metabolic flux, biosynthetic capacity, and nutrient exchange (Marshall 2012). As early as 1958, researchers discovered that growth rate is proportional to cell size and growth rate determined by nutrient availability. This relationship is called the "growth law" [START_REF] Schaechter | Dependency on medium and temperature of cell size and chemical composition during balanced grown of Salmonella typhimurium[END_REF]). In bacteria, there are numerous examples confirming this result (e.g. Escherichia coli, Bacillus subtilis, and Sinorhizobium meliloti) (Dai 2018[START_REF] Taheri-Araghi | Cell-size control and homeostasis in bacteria[END_REF]. However, results from studies that disrupted cell growth rates and metabolic balance with antibiotics deviated from the " growth law " (Si 2017, Basan 2015). Therefore, the relationship between cell size and growth rate does not always simply follow the "growth law" and requires a deeper systems-level understanding of cell growth physiology.

The models of cell size regulation

Early proposals for the mechanism of cell size control were based on population average data from the model organisms bacteria and yeast. They are Timer, Sizer and Adder (Figure 16) [START_REF] Rhind | Cell-size control[END_REF].

The Sizer model assumes that cells sense cell size before dividing and trigger division when a fixed size is reached. This situation creates an inverse correlation between size at birth and the amount of growth during subsequent cell cycles. In this case, cells need a detection point to sense the size of the cell and trigger division when the detection point is met. The problem with this model is that if the cell is still too large after dividing, it is larger than its target size, then the cell will need to divide again as quickly as possible to reach the fixed size, however, the division time is not sufficient for DNA replication (Figure 16 a).

The Timer model assumes that the cell's growth cycle time is fixed. This model does not maintain cell size homeostasis. If cells are born the same size, cell size will depend on their growth rate. If birth sizes differ, generally larger cells grow faster and smaller cells grow slower.

Therefore, the gap between large cells and small cells will become wider and wider (Figure 16 b).

The Adder model assumes that cells increase in size by a fixed amount each growth cycle. When a cell divides, this added fixed size is added to the cell's birth size and then divides into two cells. So when the cell's birth size is greater than the added fixed size, the cell's daughter will be smaller than the birth size of the mother and gradually, one generation after the other, cell size at birth will approach the added size. When a cell's birth size is smaller than its added size, the cell will grow larger than its birth size while gradually approaching its added size as it

Cell size at the single cell level

To explain the regulatory process of the "Adder" model at the single cell level, researchers proposed two different regulatory modes.

The first is the replication-initiation-centric model : cell size control is set by the time period of chromosome replication (C-period) and the interval between the end of chromosome replication and cell division (D-period). In this model, cell divide after a fixed time interval (C+D period) since chromosome replication begins [START_REF] Ho | Simultaneous regulation of cell size and chromosome replication in bacteria[END_REF][START_REF] Wallden | The Synchronization of Replication and Division Cycles in Individual E. coli Cells[END_REF].

The second is the division-centric model : cell division is triggered by the accumulation of a threshold amount of division proteins (e.g. FtsZ) [START_REF] Harris | Surface Area to Volume Ratio: A Natural Variable for Bacterial Morphogenesis[END_REF][START_REF] Ojkic | Surface-to-volume scaling and aspect ratio preservation in rod-shaped bacteria[END_REF]Si et al., 2019) or by a threshold amount of cell envelope precursors (Harris and Theriot, 2016).

Cell size and shape

In a stressful environment, not only cell size but also cell morphology is an important adaptive characteristic (Cylke et al., 2022). Changes in cell morphology will affect cell growth, movement, nutrient absorption, and proliferation [START_REF] Young | The selective value of bacterial shape[END_REF].

Rod-shaped bacterial cells grow within a very narrow range of length and width under constant growth conditions [START_REF] Schaechter | Growth, cell and nuclear divisions in some bacteria[END_REF]. However, when comparing slow-growing bacteria with fast-growing bacteria, it was found that the fast-growing bacteria were much larger in length and width than the slow-growing bacteria [START_REF] Schaechter | Dependency on medium and temperature of cell size and chemical composition during balanced grown of Salmonella typhimurium[END_REF].

The mechanisms by which cells regulate cell shape in response to growth rate is largely unknown. The researchers proposed a condition-dependent regulation of cell surface area to volume ratio in the determination of cell size (Harris and Theriot, 2016).

Several findings have also shown that adaptation to sublethal levels of antibiotics is often associated not only with a reduction in growth rate but also a decoupling of cell division from growth rate, changes in cell size and surface area to volume ratio, contributing to a decrease in surface to volume ratio (Basan et al., 2015;Si et al., 2017). These morphological changes may result from a redistribution of resources among cell growth, cell division and repair processes and may also improve survival in the presence of stress by affecting the interactions with the cell's environment via changes in the surface to volume ratio.

The growth laws 1.6.1. Resource allocation and limited pool of resources

A model describing resource allocation in bacteria under different growing conditions increased the understanding of bacterial physiology (Scott et al., 2010). Terry Hwa and his team, They divided proteins into three parts, the "R class" of ribosome-associated proteins, the "Q class", unaffected by translation repression, and the "P class" which decreases when R increases.

When the growth rate of a cell increases as nutrients increase, the cell needs to produce an amount of ribosomes that is proportional to the amount of nutrients. In contrast, when cells are placed in a translationally inhibited environment, ribosome production increases and growth Introduction rate decreases. Hwa and collaborators propose that this is due to the fact that resources are finite, and if more resources are used to make ribosomes, less of the resources can be used to make other proteins for metabolism and growth (P sector). Growth-dependent regulation of protein translation in the P sector is tuned to complement growth-dependent changes in the R sector.

Expression of P sector proteins is directly negatively correlated with growth rate (Figure 17).

Using Cm as a way to limit translation capacity

Under sublethal concentrations of chloramphenicol, a series of physiological adjustments will be produced inside the cell to cope with this stress. Chloramphenicol's inhibition of ribosomes causes a series of chain reactions that affect both the transcriptional and translational processes of cells. At the same time, it also causes a change in the concentration of ppGpp, and the change of ppGpp concentration is very important for the global resource allocation and growth rate regulation of cells (Gourse et al., 2018;[START_REF] Patrick | Free RNA polymerase in Escherichia coli[END_REF][START_REF] Zhu | Disruption of transcription-translation coordination in Escherichia coli leads to premature transcriptional termination[END_REF]Zhu et al., 2019) Introduction to represent the fractional ribosome content. RNA/protein ratio increases with Cm concentration; Active ribosome fraction decreases as Cm concentration increases (Dai et al., 2016).

Both changes in transcription and translation can affect growth rate in the presence of Cm

In previous work in our laboratory, we have drawn some conclusions about changes in the physiological regulation of cells in response to environmental changes. Mia Panlilio's experiments were done during her PhD in Pietro Cicuta's laboratory in collaboration with Bianca Sclavi and other colleagues. They are about the study of cell size changes and cell division timing under upshift conditions (Panlilio et al., 2021). The upshift is when bacteria switch from slow growth conditions to fast growth conditions where they have more nutrients. The result of her work show that when a cell switches from a poor to a rich medium, the cell is expending its resources to produce more ribosomes to take advantage of the richer medium to grow faster, to the point where the expression from a constitutive promoter is lower than the growth rate, resulting in dilution of the gene product. At the same time, after the upshift, division time transiently increases and added size transiently increases. This result supports a model in which the protein that triggers cell division is possibly a protein of the "Pclass" of the proteome, the constitutive promoter protein, and when this protein accumulates to a threshold, it triggers cell division. The cell size changes in the upshift experiment are likely to be caused by the decrease in concentration of the division protein and therefore the prolongation of the cell division time [START_REF] Panlilio | Threshold accumulation of a constitutive protein explains E. coli cell-division behavior in nutrient upshifts[END_REF].

Qing Zhang's work during his postdoc with Bianca Sclavi in collaboration with Marco

Cosentino Lagomarsino used the ratio of activity of promoters with different affinities for RNAP to estimate changes in free RNAP under translational restriction [START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF].

The results of the study showed that in the environment of sublethal concentrations of chloramphenicol, the growth rate of cells decreased with the increase of Cm concentration, as shown before. In these conditions, ribosomal promoters and constitutive promoters with high affinity for RNAP exhibited similar behavior patterns: their gene expression increased with the concentration of chloramphenicol. While another constitutive promoter with a low affinity for RNAP showed a decrease of gene expression with the increase of chloramphenicol. These results cannot be explained within the current framework proposed by the resource allocation model (Scott et al., 2010). This suggests that at sublethal concentrations of translation inhibitors, RNAP redistribution dominated by the degree of promoter-RNAP affinity constitutes a novel regulatory mode of bacterial metabolism.

P1 is a promoter negatively regulated by ppGpp, while P5 is a constitutive promoter with a high affinity for RNAP. Using the ratio of P1 and P5 promoter activity it is possible to estimate changes in ppGpp as a function of growth rate and Cm concentration. The PLtet promoter is a constitutive promoter with a low affinity for RNAP. The ratio of the promoter activity of PLtet and P5 instead is used to estimate the change of the concentration of free RNAP. Using this measurement, it was shown that the concentration of free RNAP decreases with the increase of the concentration of chloramphenicol. The results showed that as the concentration of chloramphenicol increased, the concentration of free RNAP decreased, and this decrease was independent of ppGpp.

The probability of a ribosome reaching the end of a gene before stalling and falling off has been shown to decrease exponentially with gene length. RNAP subunits β and β' are among the longest genes in E. coli and are found consecutively in the same operon, whereas ribosomal proteins are among the shortest genes. It was therefore inferred that the reason for the reduction in the total amount of RNAPs is that ribosomes translating the longer RNAP genes are more likely to be hit by Cm relative to those translating ribosomal genes. Furthermore, ribosome arrest leads to asymmetric degradation of mRNAs and prevents further translation by other ribosomes. Based on this assumption a model was derived to calculate the probability of being hit by ribosomes of different lengths. The results showed that if the inhibitor reduced the processivity of ribosomes, the probability of completing translation of long genes was reduced more than that of shorter genes, reducing the rate of expression of longer genes to a greater extent. In conclusion, in the presence of sublethal concentrations of chloramphenicol, it is not translation, nor the ppGpp-dependent redistribution of RNAP between ribosomal and nonribosomal promoters, but rather a reduction in overall transcriptional capacity that limits the rate of cell growth [START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF] (Figure 19). inhibitor. There is a greater probability of stalling on longer genes during translation, resulting in a decrease in transcriptional capacity. The way RNAP is distributed in cells also changes according to a promoter's affinity [START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF].

Chapter 2

The combination of microscopy and microfluidic system can effectively track single cell growth changes. This real-time detection can further study the changes in intracellular transcription and translation processes under the influence of Cm. Therefore, more detailed experimental results and analysis are obtained. This chapter elaborates on my experimental results and proposes a corresponding systematic model framework.

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Based and cell size as in Mia's experiments. This is true if in this case the cell size is not related to the growth rate, but related to the concentration of ppGpp (Büke et al., 2022).

Through Qing's experiments we obtained more information about the changes in the Results regulation of cell growth in the sublethal Cm environment. Ribosomes increased, but growth rate decreased, and the decrease in growth rate was due to a decrease in the total amount of RNAP. In this case, non-ribosomal promoters with different RNAP affinities exhibit opposite changes in activity in the same context of sublethal translation inhibitors. The assignment of RNAP affinity dominates the resource allocation process. This is a new perspective for analyzing adaptive regulation during growth.

From this perspective, we hypothesized that RNAP-induced resource redistribution is the main factor affecting cell growth status after Cm addition. However, specific changes in the regulation of cell growth, as well as limited translational and transcriptional capacities, in the presence of sublethal translational inhibitors remain unclear. In the presence of translation growth rate changes. Thus, the mechanism of changes in transcriptional and translational abilities in adaptation to sublethal environments and their effect on the control of cell division can become clearer. We hope that elucidating this regulatory process can provide some useful information for the study of antibiotic resistance and complex growth regulation of cells.

Publication under preparation

Introduction

Sub-lethal levels of antibiotics are often found in the bacterial environment [START_REF] Davies | The world of subinhibitory antibiotic concentrations[END_REF].

Regulatory mechanisms allowing adaptation of cell growth in these conditions can improve fitness and even lead to improved growth and/or resistance once higher antibiotic concentrations are met [START_REF] Kohanski | Sublethal Antibiotic Treatment Leads to Multidrug Resistance via Radical-Induced Mutagenesis[END_REF][START_REF] Gutierrez | β-lactam antibiotics promote bacterial mutagenesis via an RpoS-mediated reduction in replication fidelity[END_REF]Andersson and Hughes, 2014;[START_REF] Mathieu | Discovery and Function of a General Core Hormetic Stress Response in E. coli Induced by Sublethal Concentrations of Antibiotics[END_REF]. Therefore, the adaptation to sub-lethal concentrations of antibiotics has clinical relevance, since antibiotic concentration gradients are present within patients during the course of treatment and can be particularly dangerous when the course of treatment is ended prematurely, when the pathogenic strain is still present.

Here we focus on the characterization of the adaptation to sub-lethal inhibition of ribosome activity.

Ribosome activity is maintained proportional to the amount of available nutrients via the stringent

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response, a feedback loop mediated by the ppGpp small signaling molecule (Irving et al., 2021). Upon a decrease in the amount of amino acids, and thus of charged tRNAs, the binding of the RelA enzyme to the ribosome's A-site results in an increase in ppGpp synthesis (Gourse et al., 2018). ppGpp decreases overall gene expression by binding to RNA polymerase (RNAP) and decreasing its elongation rate. However, it acts more specifically at the transcription initiation step to inhibit the expression of ribosomal operons, while favoring the expression of amino acid synthesis genes (Gourse et al., 2018;Zhu et al., 2019). In addition, ppGpp has been shown to bind several other cellular targets resulting in an overall slowdown of growth, these include the ribosomes themselves and enzymes of the DNA replication complex [START_REF] Zhang | Novel (p)ppGpp Binding and Metabolizing Proteins of Escherichia coli[END_REF]. ppGpp has been shown to have a positive effect on cell division, although the molecular mechanism remains to be identified (Büke et al., 2022;[START_REF] Anderson | The transcription factor DksA exerts opposing effects on cell division depending on the presence of ppGpp[END_REF].

The stringent response was first characterized as an adaptation to the depletion of nutrients and the entry into the stationary phase of growth (Potrykus and Cashel, 2008). However, it also plays an equally important role in the growth transition upon an upshift in nutrient availability. The rapid decrease in ppGpp levels from the activity of the SpoT hydrolase leads to an increase in translation rate due to the activation of dormant ribosomes and increased ribosome production rate [START_REF] Boyle | The relationship between the spoT gene, the synthesis of stable RNA, ribosomal proteins, and the beta beta' subunits of RNA polymerase following a nutritional shiftup of Escherichia coli[END_REF][START_REF] Murray | Control of rRNA Expression by Small Molecules Is Dynamic and Nonredundant[END_REF][START_REF] Mori | Quantifying the benefit of a proteome reserve in fluctuating environments[END_REF]Panlilio et al., 2021).

Similarly, the stringent response plays a key role in the adaptation to ribosome inhibition. In the presence of sublethal concentrations of antibiotics, inhibition of ribosome activity results in an increase in charged tRNAs and a decrease in ppGpp levels (Wu et al., 2022). This is accompanied by an increase in ribosomal operon expression as well as an increase in the elongation rate of translation (Dai et al., 2016;Zhu et al., 2019;[START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF]Wu et al., 2022). While this response could compensate for a decreased translation capacity, a decrease in growth rate is still observed in these conditions, which can be explained as a decrease in the fraction of active ribosomes (Dai et al., 2016).

Another possible factor affecting growth rate in these conditions is a decrease in the transcription capacity. Transcription and translation are tightly coupled processes, both physically, via protein-protein interactions, and indirectly via ppGpp (Kang et al., 2018;Zhu et al., 2019). Transcription in the absence of translation can be toxic for the cell due to the formation of R-loops, where the free mRNA can invade the DNA double helix, backtracking of RNAP and the ensuing transcription-replication conflicts [START_REF] Massé | Escherichia coli DNA topoisomerase I inhibits R-loop formation by relaxing transcription-induced negative supercoiling[END_REF]Dutta et al., 2011). Negative regulation by ppGpp of both translation and transcription rates ensures that transcription decreases whenever translation does. However, this is not the case when translation inhibition leads to an increase in translation rates.

Our previous results provide some evidence for an additional level of regulation, whereby the levels of free RNAP decrease when translation is inhibited. The concentration of free RNAP was estimated by measuring the differences in expression of a reporter protein from constitutive promoters with different affinity for RNAP [START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF]. We could show that gene expression from a low affinity promoter decreases with increasing antibiotic concentration, while expression from a high affinity promoter increases, mainly due to increasing translation rates. Moreover, the comparison of the expression of reporter proteins of different lengths from the same promoter showed very different behaviors, consistent with a model where, in the presence of translation inhibitors, translation of long genes has a higher probability to stop before reaching the end compared to short genes. A similar effect has been observed at the level of premature termination of transcription (Zhu et al., 2019) possibly mediated by degradation of untranslated mRNAs [START_REF] Duviau | When translation elongation is impaired, the mRNA is uniformly destabilized by the RNA degradosome, while the concentration of mRNA is altered along the molecule[END_REF]. RNAP's β and β' subunits are amongst the longest genes in the E. coli genome with a length of 4,029 bp and 4,224 bp respectively, compared to an average gene length of about 900 bp, suggesting that their expression might decrease when ribosome activity is inhibited by antibiotics.

Finally, adaptation to sublethal levels of antibiotics is often associated not only with a decrease in growth rate but also with a decoupling of cell division from growth rate, a change in cell size and of the surface to volume ratio (Basan et al., 2015;Harris and Theriot, 2016;Si et al., 2017;Cylke et al., 2022). These morphological changes may result from a redistribution of resources among cell growth, cell division and repair processes and may also improve survival in the presence of stress by affecting the interactions with the cell's environment via changes in the surface to volume ratio [START_REF] Serbanescu | Nutrient-Dependent Trade-Offs between Ribosomes and Division Protein Synthesis Control Bacterial Cell Size and Growth[END_REF]Cylke et al., 2022).

The frequency of cell division is regulated by the level of expression of one or more cell division factors (Si et al., 2019). In a previous study, we showed that, upon an upshift in growth rate, associated with a decrease in ppGpp, a delay of the division cycle was correlated with the expression of a reporter gene regulated by a constitutive promoter (Panlilio et al., 2021). The increased dilution rate resulting from induction of ribosome activity and expression resulted in a transiently lower concentration of the reporter

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gene, leading to the proposal that one or more key cell division factors might be expressed with a similar pattern.

In this study we applied the same approach to the study of adaptation to sub-lethal concentrations of antibiotics targeting translation. ppGpp decreases both upon an upshift and upon translation limitation.

We thus expect similar changes of repartition of resources in the short term. However, the following dynamics of gene expression and cell size control might differ significantly in these environments.

Notably, opposite changes in transcription and translation capacity compared to an upshift might reveal their coupling to cell growth and division, and give us more clues on the molecular mechanisms of cellular adaptation to translation limitation.

The study of the kinetics of the cellular response to the presence of antibiotics can reveal transient changes in cellular properties that may play an important role in cell survival. Furthermore, perturbation experiments can help determine the sequence of events leading to adaptation and thus address fundamental questions about the cellular processes coupling the changes in the gene expression machinery at both the transcription and translation levels with cell growth and division.

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An increase in cell size despite a decrease in growth rate results from a delay in cell division and an increase in cell width.

In this study we chose to study the cellular response to the presence of sublethal concentrations of chloramphenicol (Cm) which acts as a competitive inhibitor by binding to the ribosome's A-site and interfering with peptide bond formation (Drainas et al., 1987). The effects of this antibiotic on ribosome activity and cell growth have been extensively characterized and compared to other antibiotics targeting translation by both experimental approaches and theoretical models, but mainly in steady state conditions (Basan et al., 2015;[START_REF] Hui | Quantitative proteomic analysis reveals a simple strategy of global resource allocation in bacteria[END_REF][START_REF] Mathieu | Discovery and Function of a General Core Hormetic Stress Response in E. coli Induced by Sublethal Concentrations of Antibiotics[END_REF][START_REF] Greulich | Predicting the dynamics of bacterial growth inhibition by ribosome-targeting antibiotics[END_REF]Si et al., 2017). We have used microscopy coupled to microfluidics to explore in a quantitative fashion the timedependent changes in single cell growth rate and division as well as translation and transcription capacity via the use of reporter constructs whose expression is dependent on ppGpp or on changing free RNAP concentration (Figure 1) [START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF]. E. coli BW25311 cells were grown at 30°C in M9 growth medium supplemented with 0.2% glucose (M9glu) in a mother-machine type of microfluidic device where cells grow in channels that are 1 µm wide and 20 µm long (Long et al., 2013). In this kind of device one of the ends of the microchannels is open and the other is tapered to avoid bacteria escaping. The same growth medium flows in larger channels at both ends of the microchannels. Fluorescence images were obtained every 3 minutes. Segmentation and tracking of the cells were carried out using SuperSegger/Omnipose from the Wiggins Laboratory (https://github.com/tlo-bot/supersegger-omnipose) (Stylianidou et al., 2016) (see Materials and Methods for more details).

This kind of microscopy experiment allows for the concomitant measurement of the changes in cell size, cell division time (Tcyc) and gene expression at the single cell level. Figure 2 shows the changes in the division time, cell cycle mean growth rate, (log(Vd)-log(Vb))/Tcyc, cell size at birth (Vb) and added size between birth and division (Vd-Vb). This data is plotted as a function of the time of the cell's division.

The division time in the absence of Cm is on average 72 minutes, therefore the data of the first hour corresponds to cells that encountered Cm after cell birth, during their cell cycle. The cell-cycle mean growth rate and the frequency of cell division both decrease after the addition of Cm, however cell division time increases faster than the change in growth rate. This results in an increase in the amount of cell size added between birth and division and is associated with an increase in cell size at birth as these larger cells divide (Figure 2b,d). About two hours after the addition of Cm the cell-cycle mean growth rate starts to decrease, leading to a decrease in added size until it matches the new cell size at birth. After four hours, the added size remains constant and proportional to the cell size at birth, as the growth rate and division frequency both keep decreasing (see SFigure 3-5 for the ratio of added size to cell size at birth in the different strains).

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The increase in cell size results from the decoupling of the division frequency from the growth rate but also from an increase in cell width and a decrease in the aspect ratio (SFigures 3-5), further contributing to a decrease in surface to volume ratio. These morphological changes at sublethal concentrations of Cm are in agreement with earlier results of the effects of Cm at steady state (Basan et al., 2015;Harris and Theriot, 2016;Si et al., 2017) and as a function of time (Harris and Theriot, 2016), although the dynamics might differ between Caulobacter crescentus and Escherichia coli (see Discussion). The observation of a rapid increase in added cell size relative to growth rate is consistent with the effects of decreasing the concentration of ppGpp in vivo seen previously by the controlled expression of a ppGpp hydrolysis enzyme (Büke et al., 2022). In the presence of Cm, however, the added size increases transiently to then decrease to reach the new steady state (Figure 2b). This is similar to what is observed when ppGpp decreases upon an upshift (Panlilio et al., 2021). Compared to the Büke et al study, here the concentration of ppGpp is under control of its native regulators and can therefore increase again after ribosome levels have increased.

In order to gain an improved understanding of the molecular mechanisms behind cell size control we used different GFP reporter constructs to measure the changes in both transcription and translation capacity during the adaptation process.

Gene expression dynamics from the different promoters are

consistent with an early decrease in ppGpp and a long-term decrease in transcription capacity.

The addition of Cm has been shown to result in a decrease in ppGpp from the inhibition of ribosome activity and the accumulation of charged tRNAs. This in turn results in an increase in both ribosomal RNA expression rate and ribosomal elongation rate (Dai et al., 2016;Wu et al., 2022). In order to follow the changes in ppGpp concentration, translation rate and free RNAP concentration in real time we have measured the expression of a fast-folding GFP (mut2gfp) under control of three different promoter sequences (Figure 1). This construct was inserted in the chromosome between the convergent aidB and yjfN genes in the Ori macrodomain. The first promoter, P1, is a shortened version of the wellcharacterized rrnBP1 promoter lacking the upstream regulatory region containing the three Fis sites and the high affinity H-NS site. The P1 promoter contains a GC-rich discriminator region overlapping the transcription start site, necessary for negative regulation by ppGpp. We compared this to the GFP

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expression from two other promoters, neither of them regulated by ppGpp, P5 and PLtet. These are both highly expressed constitutive promoters that differ in their affinity for RNA polymerase. While P5 has consensus -10 and -35 sequences, PLtet differs from consensus at the -10 sequence (Figure 1). The expression rate of GFP will be a result of the specific promoter activity and the changes in total translation capacity. Its concentration will depend on the growth rate of the cell, setting the dilution rate. Our previous work showed an increase in GFP concentration from both the ribosomal, P1, and constitutive, P5, promoters as a function of Cm concentration while the expression from the low affinity constitutive promoter PLtet decreased or remained constant depending on the growth medium [START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF]. The time-resolved analysis of the cell's fluorescence reveals different dynamics for the change in GFP concentration from these promoters. Upon addition of Cm there is a rapid increase in the GFP concentration from P1 reaching a maximum after about 2 hours, this is followed by a slower increase in the GFP concentration from P5, from 1 until 4 hours post Cm addition, while expression from PLtet results in a small change in GFP concentration that remains more or less constant. These three constructs express the same gene, therefore the translation rate can be assumed to be the same in each case, the differences between them are due to the transcription rate. The rapid increase in P1 expression is consistent with the decrease in ppGpp following Cm addition. The increase in GFP expression from the P5 promoter however should not result from an increased transcription rate, since it is not regulated by ppGpp, and it is likely due to the increase in translation rate following the decrease in ppGpp. The GFP concentration from the other constitutive promoter, PLtet, remains more or less constant despite the increase in translation rate. Therefore, there must be a decrease in its transcription rate, which, in the absence of other known regulators of the PLtet promoter in this strain, we propose is due to a decrease in the amount of free RNAP. Moreover, the GFP concentration from PLtet remains constant, which means that its expression rate remains proportional to the decreasing growth rate.

In summary, upon the addition of Cm, a rapid decrease in ppGpp is followed by a slower increase in translation rate of GFP and a decrease in transcription rate of the lower affinity promoter.

In order to better understand the dynamic changes in growth rate and cell size and their possible correlation with gene expression we looked at the instantaneous rates instead of the cell cycle averaged values (Figure 4).

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time between birth and division (Figure 2). It therefore incorporates information about both growth and division processes. The instantaneous growth rate on the other hand only describes the rate of change in cell size as a function of time (Figure 4). Similarly, the change in GFP concentration shown in Figure 2 summarizes how gene expression rate changes as a function of the rate of change of cell size, while the instantaneous change in cell fluorescence measures the changes in expression rate independently of cell growth. The measurement of growth rate and GFP expression rate moreover are obtained in a shorter time, from sliding 9 minute windows, and has therefore a better time resolution, important for the characterization of the dynamics. Indeed, the results in Figure 4 reveal rapid changes in both gene expression and growth rate that are markedly different between the three promoters.

Expression rate of GFP from the P1 promoter increases after addition of Cm and oscillates with decreasing amplitude until it reaches a steady state after about 5 hours. The main regulator of P1 expression is ppGpp. These oscillations may reflect the dynamics of the feedback loop between ppGpp levels and ribosome activity. Expression of GFP from the P5 promoter increases after the growth rate has started decreasing. The expression of this promoter is independent of ppGpp levels, suggesting that at this point the translation rate has increased from the faster production of new ribosomes relative to growth rate, as suggested by the P1 data, and the increased translation elongation rate observed previously (Dai et al., 2016). The growth rate however keeps decreasing. The expression rate of GFP from the PLtet promoter closely mirrors the decrease in growth rate. This is in agreement with the idea that growth rate may be limited by the expression of a gene that has a promoter similar to PLtet, with a low affinity for RNAP, and that the amount of free RNAP is decreasing with time.

The decrease in ppGpp rapidly increases both ribosome activity, which can directly influence growth rate, and transcription initiation from ribosomal promoters, as seen from the pattern of expression of the P1 promoter. The delay in the decrease in growth rate could result from the activation of dormant ribosomes by the decrease in ppGpp [START_REF] Brunschede | Establishment of exponential growth after a nutritional shift-up in Escherichia coli B/r: accumulation of deoxyribonucleic acid, ribonucleic acid, and protein[END_REF][START_REF] Koch | The inefficiency of ribosomes functioning in Escherichia coli growing at moderate rates[END_REF][START_REF] Gausing | Regulation of ribosome synthesis in E. coli[END_REF][START_REF] Mori | Quantifying the benefit of a proteome reserve in fluctuating environments[END_REF] which can compensate, for a limited amount of time, for the decreased fraction of active ribosomes caused by the Cm.

In every dataset, after the growth medium has been switched back to the one without Cm the growth rate rapidly decreases before increasing again. Expression from the P1 promoter follows a similar pattern but with a delay. This would be consistent with an increase in ppGpp as ribosome activity increases in the absence of the antibiotic, using up the available charged tRNAs. This increase in translation rate can be seen in the increased expression rate from the two promoters not regulated by ppGpp and the increase in growth rate (Figure 4). Following this second change in growth medium, the division time quickly decreases again, decreasing the added size (Figure 2). Future experiments will explore in more detail the dynamics of bacterial recovery from growth in the presence of translation limitation.

Discussion

It is interesting to compare these results to those obtained by other shifts that result in a decrease in ppGpp. The first is a study where ppGpp levels were decreased by the induction of an enzyme (Büke et al., 2022). In that case, division frequency and growth rate decrease, and the added size increases, but not transiently, because ppGpp remains low while the ppGpp hydrolysis enzyme is present. The second is a study where ppGpp levels decreased because of the switch to a richer growth medium that contains amino acids (Panlilio et al). In this case there is also a transient increase in added size associated with a transient increase in cell division time. The latter is consistent with a model where cell division is coupled to the accumulation of a gene product expressed from a constitutive promoter, which is transiently diluted by the increase in growth rate. The model found that expression from a site close to the terminus was a better predictor of cell division than expression from a site near the origin, likely due to its decreased expression from decreased gene dosage. In this study, we used the same constitutive promoter-GFP construct, P5, however, its gene product is not diluted in the presence of Cm, on the contrary, its concentration increases because its expression rate increases while growth rate decreases.

Upon addition of Cm division frequency decreases earlier than growth rate, with the increased ribosome production, as measured by P1. This results in a transient increase in added size and is consistent with the proposed repartition of resources between ribosome production and cell division [START_REF] Serbanescu | Nutrient-Dependent Trade-Offs between Ribosomes and Division Protein Synthesis Control Bacterial Cell Size and Growth[END_REF]. While the molecular mechanism for this repartition remains to be elucidated, we suggest that it may be mediated by the decrease in transcription capacity, as more RNAP is being used for ribosomal gene expression, resulting in gene expression of a division protein that decreases faster than growth

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rate in the first phase of the adaptation process.

The expression of GFP from the other constitutive promoter used here, PLtet, results in a constant concentration of GFP. Its production rate therefore changes at the same pace as growth rate (Figure 4).

Given that translation rate increases, its transcription rate must decrease. This promoter has a lower affinity for RNA polymerase than P5. We therefore propose that its transcription rate decreases in the presence of the antibiotic due to a decrease in the availability of free RNAP, and that this decrease becomes limiting for cell growth. The decreased availability of free RNAP can result from both its use for the sustained expression of ribosomal operons [START_REF] Patrick | Free RNA polymerase in Escherichia coli[END_REF], that is higher than the ribosomal expression in the absence of Cm, and the decrease in expression of long genes from early termination of both transcription and translation (Zhu et al., 2019;[START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF]. Two of the subunits of RNAP, rpoB and rpoC, coding for the β and β' subunits, are among the longest genes in the E. coli genome.

The comparison between P1, regulated by ppGpp like ribosomal promoters, and P5, reflects the discrepancy between the production rate of ribosomal RNA and the actual change in translation rate in the cell. The fraction of total RNA per protein (R/P) increases with increasing Cm concentration (Scott et al., 2010;Dai et al., 2016) however this does not reflect the translation capacity of the cell, as it does when it is measured as a function of growth rate. It is not easy to estimate the amount of active ribosomes from the R/P data since several different factors can come into play. The presence of Cm decreases the activity of a fraction of ribosomal population (Dai et al., 2016); the decrease in ppGpp activates the dormant, reserve, population of ribosomes; the translation elongation rate increases, however, ribosome assembly likely suffers from the decreased expression of ribosomal genes found at the end of long operons (Zhu et al., 2019). If we assume that transcription from the P5 promoter is relatively constant due to its high affinity for RNAP, the change in expression rate of GFP from the P5

promoter is likely to reflect the evolution of the change in translation rate of a protein of average size.

The oscillations in P1 expression rate are consistent with a damped oscillator that can result from the presence of a negative feedback loop. For example, it is possible that the decrease in ppGpp increases the expression of ribosomes. Once ribosome content has increased, the depletion of charged tRNAs leads to ppGpp concentration increasing again, which decreases ribosomal promoter expression and a

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decrease in utilization of charged tRNAs and therefore a new decrease in ppGpp. The delay required to observe the oscillation could result from the time required for ribosome assembly and its decreased activity in the presence of the antibiotic. The decrease in the amplitude of the oscillations could be due to the decrease in growth rate, decreasing the dilution rate and thus increasing ribosome concentration independently of gene expression. This oscillation in expression rate is mirrored by similar changes in growth rate, resulting in the attainment of a constant concentration of GFP.

These results reveal at least two different phases in E. coli's adaptation to translation limitation. In the first phase growth rate is maintained thanks to the ribosome reserve, however cell size increases, decreasing the surface to volume ratio and therefore decreasing the intake not only of nutrients but also of the inhibitor. In the second phase growth rate decreases, likely limited by the amount of free RNAP.

In the meantime the cell is accumulating an excess of ribosomes and other proteins relative to its growth rate. As soon as the inhibitor is washed away the cells are ready to increase translation rate and expression of the factors that were limiting growth and division to resume cell proliferation with little delay, increasing population size, followed by the restoration of growth rate according to the nutrient content of the environment. Finally, it is tempting to speculate that the accumulation of a reserve of ribosomes, and other key growth factors, during the adaptation to sublethal concentration of chloramphenicol can result in a memory effect, helping the cell survive the presence of a subsequent increase in antibiotic concentration. These hypotheses are the subject of the current work of our laboratory.

Microscope and microfluidics experiments

We used the reporter strains containing the promoters of P1, P5 and PLtet to record the growth and change process of bacteria by using a fluorescence microscope. An image was acquired every three minutes in the environment of continuous culture microfluidic circulation. The growth medium was allowed to switch rapidly from M9-glu to M9-glu with Cm (2µM) during bacterial growth so that we could collect cell growth data throughout the change.

The plate reader results show that PLtet-cynr decreases more than PLtet-ori as the Cm concentration increases (Figure 20). In my microscopy experiments I also compared PLtet-ori Green is P1-ori promoter, blue is P5-ori promoter, purple is PLtet-ori promoter and orange is PLtet-cynr promoter.

Y axis is normalized GFP concentration. 2 µM Cm was added at time zero. These are replicate experiments of the same conditions.

The growth rate under sub-sub lethal concentrations of Cm

I did MIC measurement experiments to determine the appropriate Cm concentration for the experiments. In these experiments I added Cm to either cells in exponential phase or cells still in stationary phase, at the same time as they were diluted into fresh growth medium. In the results of the cells in lag phase we found something unexpected. The results show that the growth rate of E. coli increases under sub-sub lethal concentrations of Cm and then decreases with the increase of Cm concentration (Figure 22). At very low Cm concentrations, the increase in growth rate was unexpected.

It can be seen from the results that in the M9-glu medium, when the Cm concentration is less than 1.5 µM, the growth rate is greater than that in the medium without Cm. While the growth rate decreased with the increase of Cm concentration after 1.5 µM concentration (Figure 22).

This does not happen in the M9-glu-CAA medium. In the M9-glu-CAA medium there no change in growth rate when very low concentrations of Cm are present. We make a simple interpretation: the increased growth rate is due to the activation of sleeping ribosomes in the presence of Cm. Because the proportion of dormant ribosomes relative to active ribosomes is

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greater in poor medium than in richer medium. Thus, we can observe the effect of Cm on the increase of growth rate in poor medium, but it is difficult to observe it in rich medium. At the same time, it is not clear why the sub sub-lethal concentration of Cm activates the dormant ribosome. This phenomenon needs further exploration.

Chapter 3

In our results, at sublethal antibiotic concentrations, an increase in ribosomes resulted in an increase in translational capacity. On the premise of increasing translation capacity, transcription capacity decreases. At the same time, the growth rate decreases. This is consistent with a model in which reduced transcriptional capacity leads to reduced growth rates. Based on the principle of resource allocation in Terence Hwa's papers, we use the P1 promoter to represent the "R-class" proteins, the ribosomal sector, and the constitutive promoters P5 and PLtet to represent the "P-class" proteins. As described in their model, when Cm is added, ribosomal production increases to compensate decreased ribosome activity, while the nonribosomal fraction decreases because ribosomes take up too many resources (Scott et al., 2010).

Conclusions and future perspectives

This process is based on the feedback mechanism of ppGpp. When Cm inhibits ribosomes, the concentration of charged tRNA in cells increases, causing the expression of ppGpp to decrease, so the inhibition of ribosomal gene expression slows down, resulting in increased ribosome production. The conclusion given in Terence Hwa's papers is that the reduction of "P-class" proteins is the reason for the reduction in growth rate.

In Qing's article, it was shown that the concentration of GFP increased from the P1 promoter, as expected because P1 is regulated by ppGpp. The P5 promoter and the PLtet promoter are constitutive and represent the non-ribosomal sector. Between them, the GFP concentration from the P5 promoter increased, while the GFP concentration from the PLtet promoter decreased. At the same time the growth rate decreased. Qing used the same promoters as we did, and our expression results of P1, P5 and PLtet are consistent with his results. Qing proposed that the different changes in P5 and PLtet expression are caused by the difference in RNAP affinity between the two, and the decrease in growth rate is due to the decrease in the total amount of free RNAP. For this conclusion, he gave his own model, in which longer genes are more likely to be terminated in the translation process in the presence of Cm, and RNAP subunit genes are the longest in bacteria, so Cm effectively reduces the expression of RNAP [START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF].

In our experiments, we use the GFP concentration of the P1 promoter to approximately represent the expression of ribosomes, and the GFP concentration of the P5 promoter to approximately represent the translational capacity of the cell, because the P5 promoter is not affected by the change in transcription capacity. The GFP concentration of the PLtet approximately represents the sum of the transcriptional capacity and the translational capacity.

In our results, it is shown that the expression of the P1 promoter increases, indicating that the expression of ribosomes increases. This result is consistent with Terence Hwa's model. The expression of the P5 promoter also increases, but the expression of the P5 promoter lags behind that of the P1 promoter. This shows that the increase of ribosomes leads to the increase of translational capacity. The GFP concentration of PLtet promoter is constant, which shows that the transcriptional capacity decreases under the premise of the increase of translational capacity, and the two complement each other to reflect the constant expression of PLtet promoter. At the same time the growth rate decreases. This agrees with the model where the decrease in transcriptional capacity is responsible for the decrease in growth rate.

The increase of translational capacity

In our results, we can separate the increase in ribosome production from the increase in translational capacity by comparing P1 and P5. However, how this process works in detail requires further discussion. In the Dai et al. paper, they found that ribosome elongation rate increases or remains unchanged with increasing Cm concentration (Dai et al., 2016). Despite the increase of the total amount of ribosomes and in the elongation rate, the growth rate decreases, so they introduced the concept of the fraction of active ribosomes. The decrease in growth rate was explained by the decrease in the fraction of active ribosomes and the resulting decrease in protein expression (Dai et al., 2016). While they measured the increase in total ribosomes they tried to calculate the fraction of active ribosomes with a model. We know that when Cm inhibits ribosomes, most ribosomes stall when they are "hit" by Cm, resulting in an abort of translation. Therefore, the reduction of the fraction of active ribosome is very likely.

Even though the fraction of active ribosomes is reduced, the translational capacity still increases in the end. It is likely that the number of active ribosomes increased compared the amount present before the addition of Cm.

The decrease of transcriptional capacity

Regarding the reduction of transcription capacity, the explanation given by Qing's paper is that the translation inhibitor Cm will cause longer genes to be more easily terminated during the translation process. The RNAP subunit genes are among the longest gene in E. coli, so the production of RNAP will decrease. Therefore, the decline in the total amount of RNAP will reduce the transcriptional capacity. According to Zhu et al.'s article, translation inhibitors lead to premature termination of transcription [START_REF] Zhu | Disruption of transcription-translation coordination in Escherichia coli leads to premature transcriptional termination[END_REF]. This also results in lower expression of proteins at the end of operons. Ribosomal proteins are expressed from very long operons.

Therefore, this phenomenon also increases the number of nonfunctional ribosomes, in addition to also affecting transcription of RNAP genes. Therefore, the reduction of transcriptional capacity may be caused by the reduction of the total RNAP amount resulting from the premature termination of both the transcription and translation processes.

The transient increase of cell size under sublethal concentration of Cm

In the upshift experiments of Mia, it is shown that ppGpp is decreased during the transition, the expression of ribosomes is increased and the cell size increases (Panlilio et al., 2021). These observations are similar to our experimental results: both have an instantaneous increment in the added size, but in her case the growth rate increases, while in our case the growth rate decreases. Therefore, we speculate that there is a close relationship between added size and ppGpp. The decrease in P5 expression in her results was due to the dilution effect of increased growth rate greater than the rate of increase in P5 expression. In our results the expression of P5 is increased, but we also see a transient increase in added cell size. Therefore, the protein that determines cell division may not be a protein with promoter similar to P5 in our results, maybe it has a promoter similar to PLtet at the cynR position.

Future perspectives

Our results show increased translational capacity and decreased transcriptional capacity.

Whether the decrease in transcriptional capacity is due to the decrease in the total amount of RNAP, whether other promoters in the cell behave in the same way as we hypothesize, remains to be established experimentally. Perhaps we can analyze it through prokaryotic transcriptome sequencing. In cell size regulation, whether the behavior pattern of the protein that controls cell division is really like that the PLtet promoter when it is far from the origin also needs further Of course, we can also try to study the effects of different concentrations of Cm on the physiological regulation of bacteria. It is also an interesting question whether the self-rescue modes of bacteria with different concentrations of Cm are the same. For this, the same growth medium can be used in microscopy experiments, but with different concentrations of Cm. We can compare whether the physiological regulation response is the same.

It will also be interesting to see whether there is a memory response by comparing when cells encounter the antibiotic for the first time and when they encounter it again. The medium of the experiment can be switched from with Cm to no Cm and back to with Cm to observe the difference between the first encounter and the second encounter. At the same time, the difference between the concentration of antibiotic encountered on the first encounter and the concentration of antibiotic on the second encounter can also be adjusted. The concentration of antibiotic in the first encounter is lower than that in the second encounter, or the antibiotic in the first encounter is higher than that in the second encounter. Of course, different antibiotics targeting translation can also be used to verify. These aspects are worthy of further exploration.

In addition, it will be interesting to further investigate the effects seen with the sub sublethal concentration of Cm mentioned in the previous results section, where Cm can induce an increase in the growth rate of cells in poor media. I have done some additional experiments before, but the experimental results still need to be verified. Previous experiments showed that sub sublethal concentrations of antibiotics induced growth rate increases only in cells in the lag phase. It does not appear for cells already in the exponential phase. The results are not shown here as I am still validating these results. In the following experiments, I will use the medium from poor to rich, like M9-gly, and M9-glycaa, to verify the effect of growth rate on cells with different amounts of dormant ribosomes. I will also verify the difference between adding antibiotics in the lag phase and adding antibiotics in the exponential phase.

There is still a lot of work to be done in the future, and we hope that our results can make these issues clearer and help future research.

. E.coli strains and Promoters

The Wild Type BW25113 [START_REF] Grenier | Complete Genome Sequence of Escherichia coli BW25113[END_REF] is used in my experiments (in this thesis it is called WT). This WT strain and its mutants were also used by previous researchers in our laboratory (Panlilio et al., 2021;[START_REF] Zhang | A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition[END_REF]. We chose three different promoters to measure the adaptation process when E. coli bacteria shift to sub-lethal concentrations of Chloramphenicol (Figure 23).

E.coli reporter strains

The reporter strains I used are BW-P1-ori, BW-P1-ter, BW-P5-ter, BW-P5-ori, BW-Pltet-ori, BW-Pltet-ter and BW-PLtet-cynr. Each of the seven reporter strains contained one of P1-gfpmut2, P5-gfpmut2 and PLtet-gfpmut2. There are three types of insertion sites (Figure 24).

The first site is ori3, it is near the origin between the two convergent genes aidB and yjfN. The second site is ter3, it is close the terminus and between two convergent genes ynaJ and uspE.

The last one is in the middle of the chromosome, it is between cynR and codA, called cynr.

Growth media composition

We use different version of the M9 minimal growth medium supplemented with two the following: 0.5% glucose (M9+Glu) and 0.5% glucose 0.2% Casamino Acids (M9+GluCAA).

The growth rate of E. coli in these two media was different. Growth is faster in M9+Glu CAA than M9+Glu. The growth rate of BW25113 is 0.7 (db/hr) in M9-glu and 1.14 (db/hr) in M9glu-CAA (see Fig. 20)

Culture transfer conditions

On the first day, a single bacterial strain was picked from a fresh plate and inoculated it into 5ml of M9 culture medium added with 1/1000 of kanamycin (50 mg/ml) for overnight culture.

On the second day, the OD value of the bacteria was measured and diluted to an OD of 0.00375 or 0.2 in fresh medium. The same temperature was maintained during the two incubations. The incubation time of the bacteria before being used in the microscope experiment is three hours.

After the bacteria enter the exponential growth phase, the bacteria solution is used for the microscope experiment. In the plate reader experiment, if the detected bacteria need to be in the lag phase, the bacterial solution should be diluted to an OD of 0.002 and used directly. If the bacteria need to be in the exponential growth phase, it is necessary to select an appropriate incubation time according to the growth rate of the bacteria in different media.

Microscope experiments

Experiment overview and workflow

On the first day, the bacteria were inoculated in the prepared bacterial culture in M9 medium, with 1/1000 antibiotics, and cultured overnight. The next day, the stock solution was diluted to an OD of 0.00375 (this value was calculated based on the doubling time of 90 minutes) and then incubated for 3 hours shaking at 30°C. When the bacteria entered the exponential growth phase, they were added to the PDMS device.

During the incubation of the diluted stock solutions, the growth medium M9+glu and M9+glu

Cell data filtration

After SuperSegger processing, we obtain two sets of data. The information of one set of data includes the characteristic values of all identified cells at each time point. We call this set of data "lineage". Another set of data only collects the characteristic values of cells at birth and division time points, which we call "flat". Based on these two sets of data, we set filtering to reduce the noise of the data.

The parameters of the filter are Growth Rate > 0, Division time >10 min and 0.6 > daughter/mother > 0.4.

The number of cells that passed the filter ranged from 704 to 11990. The experimental results of each promoter were repeated twice.

Time series parameters

We used the values in the lineage dataset to calculate the instantaneous quantities, and calculated the derivatives with the values of each single cell from birth to division, rolling in groups of three points, and smoothing the data using a 30-minute rolling average window. For the flat dataset, each value represents the birth and division information of a single cell. Again, we choose 30 minutes as the rolling average window to smooth the data. We use R language for data processing and making graphics.

Plate reader experiments

Plate reader

We picked a single colony on the LB plate and inoculated it in the growth medium. All the strains were grown overnight. The parameters of the constant-temperature shaker are 37 °C and 190 rpm. We then used the BioMek3000 pipetting station to aliquot the diluted bacteria into 96 plates. The liquid in each well is 150 μl. Finally, we added 70 µl of mineral oil (sigma) to stop the liquid from evaporating. The plates were incubated at 37 °C shaking in the plate reader (Tecan Infinity Pro). The optical density at 610 nm and the GFP fluorescence at 535 nm were measured every 5 minutes over 21 hours. The blank controls were wild-type strain BW25113

or culture medium only.

Data analysis

From the experimental results of the plate reader, we use the growth curve to calculate the derivatives of OD as a function of time, select the largest derivative value as the midpoint, and then take a time period of one hour on both sides of this time point. We calculated the cell growth rate in the exponential growth phase based on the OD value in the range of two hours, and then compared the different growth rates to draw conclusions.

Figure 1 .

 1 Figure 1. Gene expression process. ......................................................................................

Figure 2 .

 2 Figure 2. E. coli RNA polymerase. .....................................................................................

Figure 3 .

 3 Figure 3. Promoter sequence and its interactions with the RNA polymerase holoenzyme.

Figure 4 .

 4 Figure 4. Schematics of bacterial transcription initiation. ..................................................Figure 5. The E. coli 70S ribosome. ..................................................................................

Figure 6

 6 Figure 6 Structure and dissections of a type I tRNA from E. coli .....................................

Figure 7 .

 7 Figure 7. The duty cycle of the bacterial ribosome. ..........................................................

Figure 8 .

 8 Figure 8. Mechanism of action of RelA . ..........................................................................

Figure 9 .

 9 Figure 9. Structural model for ppGpp Site 1 and Site 2. ...................................................

Figure 10 .

 10 Figure 10. Transcriptional and translational contributions to regulation of ribosome synthesis. ......................................................................................................................

Figure 11 .

 11 Figure 11. Control of protein translation by ppGpp. .........................................................

Figure 12 .

 12 Figure 12. Regulation of negative superhelicity by fis and crp. ........................................

Figure 13 .

 13 Figure 13. Physical and indirect coupling of transcription and translation. .......................

Figure 14 .

 14 Figure 14. Antibiotic target sites during bacterial protein synthesis. ................................

Figure 15 .

 15 Figure 15. Schematic diagram illustrating the increased affinity model. ..........................

Figure 16 .

 16 Figure 16. Three different models of cell size regulation. ................................................

Figure 17 .

 17 Figure 17. Resource allocation models and the impact of translational inhibitors. ..........

Figure 18 .

 18 Figure 18. Changes in ppGpp and ribosome content under chloramphenicol. .................

Figure 19

 19 Figure 19 Effect of Cm on RNAP .....................................................................................

Figure 20 .

 20 Figure 20. Gene expression of promoters under different concentrations of Cm. .............

Figure 21 .

 21 Figure 21. The GFP concentration of different promoters. ................................................

Figure 22 .

 22 Figure 22. Changes of growth rate under sub sub-lethal concentrations of Cm. ...............

Figure 23 .

 23 Figure 23. The promoters used for the experiments in this project. ...................................

Figure 24 .

 24 Figure 24. The reporter strains. ..........................................................................................Figure 25. The microfluidic chemostat. .............................................................................

Figure 26 .

 26 Figure 26. microfluidic circulation machine. .....................................................................

Figure 1 .

 1 Figure 1. Gene expression process.

  function of RNAP is important for the study of the basic principles and regulatory mechanisms of gene expression and for the development of new antibiotics. As a classical model, RNAP of Escherichia coli has already had many research results. Core RNAP from Escherichia coli contains five polypeptides: β′ (1407 amino acids), β (1342 amino acids), a dimer of α (329 Introduction amino acids) and the ω subunit (91 amino acids).

Figure 2 .

 2 Figure 2. E. coli RNA polymerase. a and b: Each subunit of RNAP is denoted by a unique color: yellow, αI; green, αII; cyan, β; pink, β ; gray, ω; and orange, σ 70 . c, linear maps of the β ́ (upper) and β (lower) subunits. Conserved regions of the β ́ subunit (A-H) and the β subunit (A-I) are shown as black boxes with the structural domains of RNAP[START_REF] Murakami | X-ray crystal structure of Escherichia coli RNA polymerase σ70 holoenzyme[END_REF].

  (i) the full upstream (UP) element, contacting the carboxyl terminal domain of the α-subunits (αCTDs), (ii) the consensus -35 hexamer contacting σ4 , (iii) the spacer region between -35 and -10 sites with an optimal length of 17 bp containing both (iv) the zipper (Z) element contacting β ́ and (v) an optimal extended (Ext) -10 element contacting σ3, (vi) the consensus -10 hexamer contacting σ2, where the -12 bp remains double stranded, (vii) an optimal discriminator (Dis) element contacting σ1.2, and (viii) the core recognition element (CRE) contacting β (Fig3).

Figure 3 .

 3 Figure 3. Promoter sequence and its interactions with the RNA polymerase holoenzyme. Shown is a promoter under the control of the E. coli σ 70 holoenzyme. The promoter recognition region (PRR) and the initially transcribed sequence (ITS) are delineated by the transcription start site (TSS) at nucleotide position +1 (arrow) (The figure is adapted from Jensen and Galburt, 2021).

Figure 4 .

 4 Figure 4. Schematics of bacterial transcription initiation.

  3.4). At the same time, the topology of DNA can affect the structure of promoters and the binding sites of transcriptional regulatory proteins associated with RNA polymerases and transcription factors, respectively. Twisting and circularization of DNA can bring molecular binding sites in DNA closer together, thereby enhancing or inhibiting the formation of closed transcription complexes

Figure 6

 6 Figure 6 Structure and dissections of a type I tRNA from E. coli Typical cloverleaf 2D and ribbon diagram 3D structure, different loops and stem are colored accordingly (Guo and Su, 2022).

Figure 7 .

 7 Figure 7. The duty cycle of the bacterial ribosome. The small subunit is shown in gold, and the large subunit is shown in blue. tRNAs and protein factors are consistently color coded. Abbreviations: EF, elongation factor; RRF, ribosomal release factor; IF, initiation factor (Moore, 2012).

Figure 8 .

 8 Figure 8. Mechanism of action of RelA .

Figure 9 .

 9 Figure 9. Structural model for ppGpp Site 1 and Site 2.

Figure 10 .

 10 Figure 10. Transcriptional and translational contributions to regulation of ribosome synthesis.Schematic diagram illustrating transcriptional and translational contributions to regulation of ribosome synthesis in E. coli. Many r-protein promoters and all rRNA promoters are directly regulated by ppGpp/DksA. In addition, r-protein expression is translationally regulated by binding of excess repressor r-proteins to r-protein mRNAs[START_REF] Lemke | Direct regulation of Escherichia coli ribosomal protein promoters by the transcription factors ppGpp and DksA[END_REF].

Figure 11 .

 11 Figure 11. Control of protein translation by ppGpp. ppGpp directly binds and represses many proteins responsible for different stages of translation (The figure is adapted from Irving et al., 2021).

Figure 12 .

 12 Figure 12. Regulation of negative superhelicity by fis and crp. DNA topoisomerase I (TopA), DNA gyrase (gyrA and gyrB), CRP and Fis regulate each other and the supercoiling levels.

Figure 13 .

 13 Figure 13. Physical and indirect coupling of transcription and translation. The close correlation between transcription and translation rates observed in some bacteria has led to the hypothesis of physical and indirect coupling mechanisms, respectively (The figure is adapted from Webster and Weixlbaumer, 2021).

  During the elongation cycle, streptomycin (Stp), tetracycline (Tet), tigecycline (Tig) inhibit elongation factor Tu (EF-Tu); blasticidin S (Bls), chloramphenicol (Cam), lincosamides (clindamycin (Cln)), oxazolidinones (linezolid (Lnz)), pleuromutilin (Plu), puromycin (Pmn), streptomycin A (SA), and sparsomycin (Spr) inhibit peptide bond formation between A-site and P-site tRNAs; the tuberculin capreomycin (Cap) and puromycin (Vio) , the aminoglycosides hygromycin B (HygB), neomycin (Neo), paromomycin (Par), fusidic acid (Fus), spectinomycin (Spt) and Ths inhibit the translocation of tRNA Catalyzed by EF-G; the macrolides (erythromycin (Ery)), streptomycin B (SB), ketolides (telithromycin (Tel)) inhibit nascent chain

Figure 14 .

 14 Figure 14. Antibiotic target sites during bacterial protein synthesis. During protein synthesis, different stages have different antibiotic targets. Antibiotics use different blocking conditions to inhibit the protein synthesis process (Wilson, 2014b).

Figure 15 .

 15 Figure 15. Schematic diagram illustrating the increased affinity model.Alanine, serine, or threonine are blue circles, CHL is the yellow hexagon, and small and large ribosomal subunits are highlighted in shades of gray. A and P sites are highlighted in magenta and green, respectively. Amino acids of the growing polypeptide chain are indicated by gray circles, with the penultimate amino acid residue highlighted in blue. a, when the penultimate position of the extended polypeptide chain is alanine, threonine, or serine, their side chains interact with CHL to enhance the affinity of CHL to ribosomes, preventing the regulation of the aminoacyl portion of the aa-tRNA enters the A site, thereby inhibiting the peptidyl transferase reaction and causing ribosome arrest. b, the amino acid at the penultimate position of the peptide chain has a larger residue, and steric incompatibility prevents CHL from binding to the ribosome. c, the penultimate position of the peptide chain is

  Introduction continues to divide (Figure 16 c). The development of high-throughput microfluidics technology allows simultaneous monitoring of the size and cell cycle of many individual bacterial cells. Extensive data collected from thousands of cells were combined with mathematical modeling to validate the Adder model (Taheri-Araghi et al., 2015).

Figure 16 .

 16 Figure 16. Three different models of cell size regulation. (a) "Sizer" model: bacteria cells divide after reaching defined size; (b) "Timer": model is cells divide after a certain period of time since birth; (c) "Adder": model is cells add a constant amount of volume between subsequent divisions. Adapted from[START_REF] Willis | Sizing up the bacterial cell cycle[END_REF]

Figure 17 .

 17 Figure 17. Resource allocation models and the impact of translational inhibitors. A. Relationship between RNA/protein ratio and growth rate in the presence of chloramphenicol B. Resource Allocation Model C. Relationship between β-galactosidase (constitutively expressed proteins) and growth rate in the presence of chloramphenicol(Scott et al., 2010).

IntroductionFigure 19

 19 Figure 19 Effect of Cm on RNAP Orange arrows in the figure represent translation effects, and blue arrows represent transcription effects. (A) Partitioning of ppGpp-mediated RNAP in the absence of translational inhibition (B) RNAP, made from longer genes compared to ribosomes made from shorter genes in the presence of chloramphenicol (Cm) translation

  on the research results of Qing Zhang and Mia Panlilio, the purpose of my work is to further study the changes of intracellular transcription and translation processes under the influence of Cm by tracking single cells. Cm is a translation inhibitor that limits translational capacity while at the same time increasing ribosomal expression. I started to use a fluorescence microscope and a microfluidic device to culture E. coli cells. The microfluidic circulation can ensure the rapid change of the culture environment during the experiment, and realize the rapid transition from M9-glu medium to M9-glu medium containing chloramphenicol. This experimental setup allowed me to continuously collect gene expression and cell size data from a large number of single cells during media changes. In Mia's upshift experiments, she observed a series of physiological regulatory changes in cells after the concentration of ppGpp decreased. In my experiments, I use the addition of Cm to change the physiological properties of the cells, and the addition of Cm has been shown to also reduce the concentration of ppGpp. The growth rate decreases with Cm but increases after an upshift. Increased ribosomal production in the presence of Cm takes up resources from nonribosomal proteins, leading to altered internal resource allocation. We proposed that reducing ppGpp by adding Cm in our experiments would result in similar changes in gene expression

  inhibitors, ribosome expression increases to compensate the decrease in its activity. How does increased ribosome concentration alter the translational capacity of cells? Is the decrease in GFP concentration expressed by the PLtet promoter caused by the redistribution of RNAP? And what is the relationship between the reduction of GFP concentration expressed from the PLtet promoter and the growth rate? Based on these questions, my experimental plan was to show the regulation process of transcription and translation in cells under sublethal translation inhibitors, and the temporal sequence of translation and transcription changes as well as cell size and

Figure 1 .

 1 Figure 1. Promoter sequences in the constructs used to regulate the expression of the mut2-gfp gene. The -10 and -35 sequences recognized by RNA polymerase are underlined, the first nucleotide of the transcript is shown in bold. The P5 promoter has both sequences matching the consensus. The -10 sequence of the PLtet promoter differs from the consensus, thus decreasing its affinity for RNAP. The P1 promoter includes a GC-rich discriminator region, shown in red, which results in a decreased stability of the RNAP-promoter complex and its inhibition by the binding of ppGpp to RNAP. The constructs include a divergently expressed KanR gene and are inserted in the chromosome between the two convergent genes aidB and yjfN in the Ori macrodomain.

Figure 2 .

 2 Figure 2. Changes in growth rate, division time and cell size during the adaptation to translation limitation. a. The mean cell cycle growth rate is measured as the difference in the log of cell volume between birth and division divided by the interdivision time ((log(Vd)-log(Vb))/Tcyc). b. The added size is the difference between cell volume at division and cell volume at birth. c. Time from cell birth to cell division. d. Cell volume at birth. The line is a moving average over a window of 60 minutes, the shaded portion is the 95% confidence interval. The black vertical line shows the time when the growth medium was switched from M9-glu to M9_glu with 2 µM Cm. The red vertical line shows the time when the growth medium was switched back to the one lacking the antibiotic. These are the results obtained for the strain containing the P1-GFP construct. Results obtained for P5 and PLtet-GFP strains are shown in SFigures 1 and 2.

Figure 3 .

 3 Figure 3. Changes in GFP concentration as a function of time from a promoter regulated by ppGpp (P1) and from constitutive promoters with different RNAP affinities (P5 and PLtet). GFP concentration from expression under control of different promoter sequences was measured as the total cell fluorescence divided by the cell's area. The line shows the average for all the cells at a given time point. The shaded part shows the SE of the data at that time. The black vertical line shows the time when 2 µM Cm was added to the growth medium (M9-glu). The red vertical line shows the time when the growth medium was switched back to the one lacking the antibiotic. (The results from a second set of experiments can be seen in SFigure 6).

Figure 4 .

 4 Figure 4. Instantaneous change in growth rate (dArea/dt) and GFP expression rate (dFluor/dt) for the three promoter constructs. The derivative of cell area and cell fluorescence was measured in sliding windows of 3 points, 9 minutes, along each cell cycle. The line shows a 30 minute sliding window average and the shadow is the SE of the data at that time point. (The results from a second set of experiments can be seen in SFigure 7).

SFigure 3 .

 3 Changes in cell size parameters during adaptation to translation limitation obtained with the strain with the P1-GFP construct. a. Average cell width at the time of birth. b. Cell length at the time of birth. c. Ratio of cell length to cell width at the time of birth. d. Ratio of added size to cell size at birth. The line is a moving average over a window of 60 minutes, the shaded portion is the 95% confidence interval. The black vertical line shows the time when the growth medium was switched from M9-glu to M9_glu with 2 µM Cm. The red vertical line shows the time when the growth medium was switched back to the one lacking the antibiotic. SFigure 4. Changes in cell size parameters during adaptation to translation limitation obtained with the strain with the P5-GFP construct. a. Average cell width at the time of birth. b. Cell length at the time of birth. 61 Results c. Ratio of cell length to cell width at the time of birth. d. Ratio of added size to cell size at birth. The line is a moving average over a window of 60 minutes, the shaded portion is the 95% confidence interval. The black vertical line shows the time when the growth medium was switched from M9-glu to M9_glu with 2 µM Cm. The red vertical line shows the time when the growth medium was switched back to the one lacking the antibiotic. SFigure 5. Changes in cell size parameters during adaptation to translation limitation obtained with the strain with the PLtet-GFP construct. a. Average cell width at the time of birth. b. Cell length at the time of birth. c. Ratio of cell length to cell width at the time of birth. d. Ratio of added size to cell size at birth. The line is a moving average over a window of 60 minutes, the shaded portion is the 95% confidence interval. The black vertical line shows the time when the growth medium was switched from M9-glu to M9_glu with 2 µM Cm. The red vertical line shows the time when the growth medium was switched back to the one lacking the antibiotic. P1-GFP Width 62 SFigure 6. Changes in GFP concentration as a function of time from a promoter regulated by ppGpp (P1) and from constitutive promoters with different RNAP affinities (P5 and PLtet). GFP concentration from expression under control of different promoter sequences was measured as the total cell fluorescence divided by the cell's area. The line shows the average for all the cells at a given time point. The shaded part shows the SE of the data at that time. The black vertical line shows the time when 2 µM Cm was added to the growth medium (M9-glu). The red vertical line shows the time when the growth medium was switched back to the one lacking the antibiotic. SFigure 7. Instantaneous change in growth rate (dArea/dt) and GFP expression rate (dFluor/dt) for the three promoter constructs. The derivative of cell area and cell fluorescence was measured in sliding windows of 3 points, 9 minutes, along each cell cycle. The line shows a 30 minute sliding window average and the shadow is the SE of the data at that time point.

Figure 20 .

 20 Figure 20. Gene expression of promoters under different concentrations of Cm. a. Schematic diagram of different sites on the chromosome, b. The GFP concentration of P1, P5 and PLtet promoters under different concentrations of Cm. The concentrations of Cm are 0 µM, 2 µM and 4 µM. The experimental temperature is 37°C, and the growth medium is M9-glu.

Figure 21 .

 21 Figure 21. The GFP concentration of different promoters.

Figure 22 .

 22 Figure 22. Changes of growth rate under sub sub-lethal concentrations of Cm. a. Growth curves of cells grown in M9-glu. b. Growth curves of cells grown in M9-glu-CAA. c. Average growth rate of three independent experiments for cells grown in M9-glu. d. Average growth rate of three independent experiments for vells grown in M9-glu-CAA. Different concentrations of Cm were added during the lag phase after a preculture in the same growth medium. The experimental temperature is 37°C. The lowest concentration is 0 µM. The error bars are the SEM.

  previous experiments, the study of the expression of the same promoter at different sites could be extended. I can use reporter strains with the same promoter but at different locations on the chromosome for microscopy experiments, switching from M9-glu to M9-glu with Cm. The effect of different positions on the expression of the promoter can then be obtained. The different promoters can be used at the same site, and the effect of the same position on the expressions of different promoters can be obtained by comparing the changes in GFP concentrations. These results can help us understand the changes of transcription and translation in different chromosome locations, and further understand the global regulation of protein expressions.

  The first promoter is the P1 promoter. The P1 promoter is a shortened version of the ribosomal RNA operon promoter rrnBP1. P1 omits Fis and H-NS binding sites by including the sequence from -69 to +6 relative to the transcription start site. It contains a GC-rich, discriminator region, so the P1 promoter is sensitive to ppGpp and negative supercoiling. The P1 promoter was used to approximate the effect of ppGpp on ribosomal expression.The second promoter used here is a constitutive promoter, P5, derived from the phage T5, that has consensus -10 and -35 sequences and no discriminator region. It has a high affinity for RNAP. This means that the concentration of RNAP does not change the P5 promoter activity much. So P5 is affected almost exclusively by changes in translational capacity. The third promoter is PLtet. It is a constitutive promoter. It does not have the GC rich discriminator region. It has a low affinity for RNAP, so when the RNAP concentration changes the production of GFP under control of PLtet changes. By comparing the change in GFP expression from P5 and PLtet we can measure the change of RNAP concentration. The PLtet promoter is affected by both transcription capacity and translation capacity.

Figure 23 .

 23 Figure 23. The promoters used for the experiments in this project.

Figure 24 .

 24 Figure 24. The reporter strains.

  and 2 µm Chloramphenicol are prepared for the microscopy experiments. BSA (50mg/ml) is added to the chip (prepared in advance) one hour in advance. The instrument is turned on and the temperature set to 30 degrees Celsius. The microfluidic cycle to load the chip to adjust the focus, and start washing the BSA in the chip, Rinse for half an hour and then add the cultured bacteria solution, use the medium liquid flow to push the bacteria into the channel, and then load the microfluidic circulation system to adjust the flow rate to start the experiment.

  Introduction loop structure of the terminator hairpin. The stem of the terminator hairpin is rich in GC and usually contains at least 8 bp. The use of terminator hairpins disrupts the stable structure of EC[START_REF] Ray-Soni | Mechanisms of Bacterial Transcription Termination: All Good Things Must End[END_REF].

	Rho-dependent termination requires a factor called Rho (the bacterial RNA helicase ρ). It
	consists of a hexamer of six identical monomers arranged in an open circle. It is estimated to
	terminate ~20% of E. coli transcripts (Peters et al., 2009). Rho is highly conserved and nearly
	ubiquitous in bacteria. Rho is an RNA-dependent ATPase with RNA:DNA helicase activity
	(Lowery-Goldhammer and Richardson, 1974). In addition to Rho, there are two other elements
	needed for termination: an approximately 80-to 90-nucleotide-long Rho-binding site called the

rut (Rho utilization) site in the nascent RNA transcript and a transcription pause site specified by downstream DNA. During transcription elongation, Rho can engage with NusG, NusA and RNAP. When RNAP slows, Rho causes NusG to dissociate and RNAP to transition into a "moribund" state that results in RNAP dissociation from DNA

(Hao et al., 2021; Said et al., 2021)

.

.1.4.2. NAPs

	Nucleoid-associated proteins are abundant in cells, and most of these proteins bind DNA with
	less sequence specificity than classical TFs. Bacterial chromosome compaction is primarily due
	to supercoiling and nucleoid-associated proteins (NAP)-induced distortions in DNA, which
	alter bacterial chromosomes by bending, wrapping, circularizing, and twisting DNA. In E. coli,
	more than a dozen important proteins are involved in this compaction, including Fis (inversion
	stimulator factor), IHF (integrating host factor), H-NS (histone-like nuclear-like structural
	protein) and HU (histone-like protein), StpA (an H-NS homologue) and Dps (DNA protein from
	starved cells)

Acknowledgements

Acknowledgments

The authors would like to thank Tulio Fernandez de Almeida for help with the data analysis. This work was carried out with the support of the CNRS Miti Program (BS) and a PhD fellowship from the Chinese Scholarship Council (LL).

criticism, and encouragement. I sincerely thank the defense committee for their valuable comments and suggestions on my doctoral thesis. I sincerely thank the China Scholarship Council (No.201908610193) for funding my doctoral project and providing me with the opportunity to study in France.

When chloramphenicol binds to ribosomes, the ribosomes come to a complete standstill. This reduces the number of ribosomes available and reduces the translational capacity of the cell (Dai et al., 2016). Uncoordinated pacing between stalled ribosomes and RNAP activity leads to premature transcriptional termination [START_REF] Zhu | Disruption of transcription-translation coordination in Escherichia coli leads to premature transcriptional termination[END_REF]. At the same time, the binding effect of chloramphenicol on ribosomes leads to an increase in the expression of ribosomal genes in cells, which may be the result of a decrease in the concentration of ppGpp due to the increased amount of unused amino acids (C. Wu et al., 2022). Therefore, in the presence of Cm, the elongation process of ribosomes is suspended, the number of changed tRNA increases, the concentration of ppGpp decreases, and the expression of ribosomes increases. At the same time, Cm reduces the number of available active ribosomes, which further leads to a decrease in translational capacity and a decrease in growth rate (Figure 18).

Results

The effect of genome position on gene expression in the presence of Cm

Plate reader experiments

Our project was based on Qing's results, so we first repeated Qing's experiments with our reporter strains. I choose M9-glu as the medium for my experiments because in Qing's experimental results, when different concentrations of chloramphenicol were added, the change of GFP expression under different promoters was more obvious in M9-glu medium, and the change process was easier to capture.

Our experimental results are highly similar to those of Qing. The P1 promoter is a ribosomal promoter, and P5 and PLtet are constitutive promoters. But we also added a comparison of the expression intensity of the same promoter at different positions in the chromosome (Figure 20). Among them, both P1-ori and P1-ter increased GFP concentration with the increase of Cm concentration. The overall GFP concentration of P1-ori is higher than that of P1-ter, perhaps because of the higher gene copy number near the origin. P5-ori and P5-ter increased with the increase of Cm concentration, and the GFP concentration of P5-ori was slightly higher than that of P5-ter. PLtet-ori and PLtet-cynr decreased with the increase of Cm concentration, and the overall level of GFP concentration in PLtet-cynr was higher than that in PLtet-ori. This is surprising because PLtet-ori has a higher gene copy number than PLtet-cynr. The GFP concentration of PLtet-ter hardly changed with the increase of Cm concentration, but the GFP concentration of PLtet-ter was very low and difficult to measure (Figure 20).

Unexpectedly, we see that the GFP concentration of PLtet-cynr is higher than that of PLtetori. The concentration of RNAP could be higher near the origin because there is a high gene copy number of ribosomal operons, but it is possible that most of the RNAP is used for ribosome expression, so the expression of PLtet-ori near the origin is lower than that of PLtet-cynr.

Results

and PLtet-cynr. The results are consistent with results of the plate reader (Figure 20). In the PLtet promoter results, when the medium is changed to M9-glu-Cm, the concentration of GFP in PLtet-ori is unchanged and the concentration of PLtet-cynr decreases. The GFP concentration from P5 on the other hand increases.

PLtet is different from P5 even though they are both constitutive promoters because PLtet has a lower affinity for RNAP. We can explain the difference in GFP concentration by a decrease in transcription capacity. Because it has a high affinity for RNAP, P5 expression is not affected by transcription capacity therefore its expression increases with translational capacity. However, PLtet expression is mainly regulated by a decrease in transcriptional capacity.

When Cm is added, the reduction of ppGpp causes compensatory expression of ribosomes.

Most of the RNAP is used to express ribosomes, and only a small part is used for the expression of other non-ribosomal genes. In addition, Cm can more effectively interrupt the translation of longer genes like those of RNAP, thereby further reducing the total amount of RNAP. This series of chain reactions reduces the expression of promoters with low affinity for RNAP, like PLtet promoters.

The results of microscopy experiments show that when Cm is added, the GFP concentration of PLtet-cynr strain decreases. From our experimental results, P5 expression, we can know that the translation capacity increases. This result shows that the transcription rate of PLtet-cynr far away from the origin decreases faster than that of PLtet-ori near the origin. The increased translation capacity is not enough to make up for the reduced transcription rate, so the GFP concentration of PLtet-cynr is decreased. The decreased transcriptional rate PLtet-ori and increased translational capacity compensate each other, so the GFP concentration from PLtetori remains unchanged. The reasons for the differences in the expression levels of the same promoter located at different locations on the chromosome deserve further study.

Chip preparation

Use a 10:1 mixture of resin and plasticizer to mix evenly and stir vigorously for five to ten minutes to ensure that the mixture is even. Then use a vacuum device to remove the air, pour the mixture on the template, cover it evenly, and then put it in a baking oven at 70 degrees for three hours to wait for molding. After molding and cooling down, take off the template, cut the chip, and then use an ion bonder to fix the PDMS to the glass coverslip. The parameter is 30% energy, 30 seconds. After the end, put it in a box to protect it from dust (Figure 25).

Microfluidic circuit

After loading the medium into the feed port of the microfluidic instrument, each side channel has two different channels, we need to degas the tube first, select the channel on one side, turn on the pump to exhaust the gas, and then switch to the other channel to repeat Operation, in my experiment we wash the side with antibiotic first and then the side without antibiotic to ensure that there is no antibiotic left in the tube at the beginning of the experiment (Figure 26).

When the experiment starts, we only need to set up the program and then execute it.

Materials and methods

Figure 26. microfluidic circulation machine.

Optical microscopy and image acquisition

We select the image of the parameters (need to be verified and added) and choose a good position to start the perfect focus system. The program will take a photo record every three minutes until the end of the experiment. Exposure parameters and the distance of taking pictures for each exposure need to be adjusted and determined experimentally to ensure a good growth state of bacteria. This device configuration enables high-throughput without sacrificing spatiotemporal resolution, allowing us to examine cellular responses to environmental perturbations at both the population and single-cell level. Thousands of single cells are tracked before and after media shifts.

Image processing

We use MATLAB to run the SuperSegger program to process images. The details of the method used and the analysis can refer to the website and the paper [START_REF] Cass | Escherichia coli Chromosomal Loci Segregate from Midcell with Universal Dynamics[END_REF]Stylianidou et al., 2016).

The website is http://mtshasta.phys.washington.edu/website/SuperSegger.php.