Genome-wide study of mRNA degradation and transcript elongation in Escherichia coli

A high-resolution view of RNA endonuclease cleavage in Bacillus subtilis

RNA endonucleases are the rate-limiting initiator of decay for many bacterial mRNAs. However, the positions of cleavage and their sequence determinants remain elusive even for the well-studied Bacillus subtilis. Here we present two complementary approaches-transcriptome-wide mapping of endoribonucleolytic activity and deep mutational scanning of RNA cleavage sites-that reveal distinct rules governing the specificity among B. subtilis endoribonucleases. Detection of RNA terminal nucleotides in both 5'- and 3'-exonuclease-deficient cells revealed >103 putative endonucleolytic cleavage sites with single-nucleotide resolution. We found a surprisingly weak consensus for RNase Y targets, a contrastingly strong primary sequence motif for EndoA targets, and long-range intramolecular secondary structures for RNase III targets. Deep mutational analysis of RNase Y cleavage sites showed that the specificity is governed by many disjointed sequence features. Our results highlight the delocalized nature of mRNA stability determinants and provide a strategy for elucidating endoribonuclease specificity in vivo.

The membrane-targeting-sequence motif is required for exhibition of recessive resurrection in Escherichia coli RNase E

The essential homotetrameric endoribonuclease RNase E of Escherichia coli participates in global RNA turnover as well as stable RNA maturation. The protomer's N-terminal half (residues 1-529) bears the catalytic, allosteric, and tetramerization domains, including the active site residues D303 and D346. The C-terminal half (CTH, residues 530-1061) is dispensable for viability. We have previously described a phenomenon of recessive resurrection in RNase E that requires the CTH, wherein the wild-type homotetramer apparently displays nearly identical activity in vivo as a heterotetramer comprising three catalytically dead subunits (with D303A or D346A substitutions) and one wild-type subunit. Here, we show that recessive resurrection is exhibited even in dimeric RNase E with the CTH, and that it is largely dependent on the presence of a membrane-targeting-sequence motif (residues 565-582). A single F575E substitution also impaired recessive resurrection, whereas other CTH motifs (such as those for binding of RNA or of partner proteins) were dispensable. The phenomenon was independent of RNA 5'-monophosphate sensing by the enzyme. We propose that membrane-anchoring of RNase E renders it processive for endoribonucleolytic action, and that recessive resurrection and dominant negativity associated with mutant protomers are mutually exclusive manifestations of, respectively, processive and distributive catalytic mechanisms in a homo-oligomeric enzyme.

RNA stability is regulated by both RNA polyadenylation and ATP levels, linking RNA and energy metabolisms in Escherichia coli

The post-transcriptional process of RNA polyadenylation sits at the crossroads of energy metabolism and RNA metabolism. RNA polyadenylation is catalyzed by poly(A) polymerases, which use ATP as a substrate to add adenine to the 3' end of RNAs, which can alter their stability. In Escherichia coli, RNA polyadenylation mediated by the major poly(A) polymerase was previously shown to facilitate degradation of individual RNAs. In this study, we performed the first genome-wide study of RNA stability in the absence of PAP I. Inactivation of the pcnB gene coding for PAP I led to the stabilization of more than a thousand of E. coli RNAs in the form of full-length functional molecules or non-functional fragments. The absence of PAP I altered the energy metabolism, with an almost 20% reduction in ATP levels. To better understand how RNA and energy metabolisms are interconnected, we investigated the role of ATP levels in regulating RNA stability. When we lowered intracellular ATP levels below 0.5 mM, many RNAs were stabilized, demonstrating the causal link between ATP levels and RNA stability for the first time in E. coli. Above this concentration, changes in ATP levels had no impact on RNA stability. We also demonstrated that some RNAs were stabilized when PAP I was inactivated by low ATP availability. These results clearly demonstrate that PAP I mediates an energy-dependent RNA stabilization, which may contribute to cell energy homeostasis under energy-limited conditions.IMPORTANCEPoly(A) polymerases are prime targets for understanding the interactions between RNA polyadenylation, RNA stability, and cellular energy. These enzymes catalyze the process of RNA polyadenylation, which involves ATP hydrolysis and addition of poly(A) tails to the 3' end of RNAs. 3' end poly(A) extensions potentially facilitate RNA degradation in bacteria. In this study, we inactivated the pcnB gene encoding PAP I, the major poly(A) polymerase in E. coli, and investigated the effects on RNA stability and energy levels. Our results show for the first time in E. coli a genome-wide RNA stabilization in the absence of PAP I associated with a decrease in ATP levels. We provide the first evidence in E. coli of a link between ATP levels and RNA stabilization and demonstrate that this is mediated in some cases by PAP I. PAP I-mediated RNA stabilization at low ATP levels could be a means of energy conservation under energy-limited conditions.

Identification and genetic dissection of convergent persister cell states

Persister cells, rare phenotypic variants that survive normally lethal levels of antibiotics, present a major barrier to clearing bacterial infections1. However, understanding the precise physiological state and genetic basis of persister formation has been a longstanding challenge. Here we generated a high-resolution single-cell2 RNA atlas of Escherichia coli growth transitions, which revealed that persisters from diverse genetic and physiological models converge to transcriptional states that are distinct from standard growth phases and instead exhibit a dominant signature of translational deficiency. We then used ultra-dense CRISPR interference3 to determine how every E. coli gene contributes to persister formation across genetic models. Among critical genes with large effects, we found lon, which encodes a highly conserved protease4, and yqgE, a poorly characterized gene whose product strongly modulates the duration of post-starvation dormancy and persistence. Our work reveals key physiologic and genetic factors that underlie starvation-triggered persistence, a critical step towards targeting persisters in recalcitrant bacterial infections.

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning

mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried out massively parallel kinetic decay measurements on over 50,000 bacterial mRNAs, using a learn-by-design approach to develop and validate a predictive sequence-to-function model of mRNA stability. mRNAs were designed to systematically vary translation rates, secondary structures, sequence compositions, G-quadruplexes, i-motifs, and RppH activity, resulting in mRNA half-lives from about 20 seconds to 20 minutes. We combined biophysical models and machine learning to develop steady-state and kinetic decay models of mRNA stability with high accuracy and generalizability, utilizing transcription rate models to identify mRNA isoforms and translation rate models to calculate ribosome protection. Overall, the developed model quantifies the key interactions that collectively control mRNA stability in bacterial operons and predicts how changing mRNA sequence alters mRNA stability, which is important when studying and engineering bacterial genetic systems.

Bright and Stable Cyan Fluorescent RNA Enables Multicolor RNA Imaging in Live Escherichia coli

Fluorescent RNAs (FRs), which are RNA aptamers that bind and activate their cognate small fluorogenic dyes, have provided a particularly useful approach for imaging RNAs in live cells. Although the color palette of FRs is greatly expanded, a bright and stable cyan FR with good biocompatibility and biorthogonality with currently available FRs remains desirable but is not yet developed. Herein, the development of Myosotis is described, an RNA aptamer that emits bright cyan fluorescence upon binding a novel GFP chromophore-like fluorophore called DBT. Myosotis has a nanomolar affinity for DBT and shows a weak dependence on magnesium for folding. Further studies reveal that the Myosotis-DBT complex has a long fluorescence lifetime, good photostability, and enhance cellular brightness. It is further shown that Myosotis-DBT is biorthogonal to Pepper and Clivia FRs, allowing multiplex fluorescence imaging of RNA in live bacteria. Myosotis can also use to image mRNA in live bacteria, revealing potential coupling between mRNA translation and stability. It is believed that this cyan FR will be a useful tool for studying the functionality and mechanism of RNA underlying diverse biological processes.

Co-transcriptional gene regulation in eukaryotes and prokaryotes

Many steps of RNA processing occur during transcription by RNA polymerases. Co-transcriptional activities are deemed commonplace in prokaryotes, in which the lack of membrane barriers allows mixing of all gene expression steps, from transcription to translation. In the past decade, an extraordinary level of coordination between transcription and RNA processing has emerged in eukaryotes. In this Review, we discuss recent developments in our understanding of co-transcriptional gene regulation in both eukaryotes and prokaryotes, comparing methodologies and mechanisms, and highlight striking parallels in how RNA polymerases interact with the machineries that act on nascent RNA. The development of RNA sequencing and imaging techniques that detect transient transcription and RNA processing intermediates has facilitated discoveries of transcription coordination with splicing, 3'-end cleavage and dynamic RNA folding and revealed physical contacts between processing machineries and RNA polymerases. Such studies indicate that intron retention in a given nascent transcript can prevent 3'-end cleavage and cause transcriptional readthrough, which is a hallmark of eukaryotic cellular stress responses. We also discuss how coordination between nascent RNA biogenesis and transcription drives fundamental aspects of gene expression in both prokaryotes and eukaryotes.

Detection of Mycoplasma hyopneumoniae viability using a PCR-based assay

Mycoplasma hyopneumoniae detection in clinical specimens is accomplished by PCR targeting bacterial DNA. However, the high stability of DNA and the lack of relationship between bacterial viability and DNA detection by PCR can lead to diagnostic interpretation issues. Bacterial messenger RNA is rapidly degraded after cell death, and consequently, assays targeting mRNA detection can be used for the exclusive detection of viable bacterial cells. Therefore, this study aimed at developing a PCR-based assay for the detection of M. hyopneumoniae mRNA and at validating its applicability to differentiate viable from inert bacteria. Development of the RNA-based PCR encompassed studies to determine its analytical sensitivity, specificity, and repeatability, as well as its diagnostic accuracy. Comparisons between DNA and mRNA detection for the same target gene were performed to evaluate the ability of the RNA-based PCR to detect exclusively viable M. hyopneumoniae after bacterial inactivation using various methods. The RNA-based PCR was also compared to the DNA-based PCR as a tool to monitor the growth of M. hyopneumoniae in vitro. Under the conditions of this study, the developed RNA-based PCR assay detected only viable or very recently inactivated M. hyopneumoniae, while the DNA-based PCR consistently detected cells irrespective of their viability status. Changes in growth activity over time were only observable via RNA-based PCR. This viability PCR assay could be directly applied to evaluate the clearance of M. hyopneumoniae or to determine the viability of the bacterium at late stages of eradication programs.

Re-defining how mRNA degradation is coordinated with transcription and translation in bacteria

In eukaryotic cells, transcription, translation, and mRNA degradation occur in distinct subcellular regions. How these mRNA processes are organized in bacteria, without employing membrane-bound compartments, remains unclear. Here, we present generalizable principles underlying coordination between these processes in bacteria. In Escherichia coli, we found that co-transcriptional degradation is rare for mRNAs except for those encoding inner membrane proteins, due to membrane localization of the main ribonuclease, RNase E. We further found, by varying ribosome binding sequences, that translation affects mRNA stability not because ribosomes protect mRNA from degradation, but because low translation leads to premature transcription termination in the absence of transcription-translation coupling. Extending our analyses to Bacillus subtilis and Caulobacter crescentus, we established subcellular localization of RNase E (or its homolog) and premature transcription termination in the absence of transcription-translation coupling as key determinants that explain differences in transcriptional and translational coupling to mRNA degradation across genes and species.

Improved RNA stability estimation through Bayesian modeling reveals most Salmonella transcripts have subminute half-lives

RNA decay is a crucial mechanism for regulating gene expression in response to environmental stresses. In bacteria, RNA-binding proteins (RBPs) are known to be involved in posttranscriptional regulation, but their global impact on RNA half-lives has not been extensively studied. To shed light on the role of the major RBPs ProQ and CspC/E in maintaining RNA stability, we performed RNA sequencing of Salmonella enterica over a time course following treatment with the transcription initiation inhibitor rifampicin (RIF-seq) in the presence and absence of these RBPs. We developed a hierarchical Bayesian model that corrects for confounding factors in rifampicin RNA stability assays and enables us to identify differentially decaying transcripts transcriptome-wide. Our analysis revealed that the median RNA half-life in Salmonella in early stationary phase is less than 1 min, a third of previous estimates. We found that over half of the 500 most long-lived transcripts are bound by at least one major RBP, suggesting a general role for RBPs in shaping the transcriptome. Integrating differential stability estimates with cross-linking and immunoprecipitation followed by RNA sequencing (CLIP-seq) revealed that approximately 30% of transcripts with ProQ binding sites and more than 40% with CspC/E binding sites in coding or 3' untranslated regions decay differentially in the absence of the respective RBP. Analysis of differentially destabilized transcripts identified a role for ProQ in the oxidative stress response. Our findings provide insights into posttranscriptional regulation by ProQ and CspC/E, and the importance of RBPs in regulating gene expression.

Gene expression in growing cells: A biophysical primer

Cell growth and gene expression, two essential elements of all living systems, have long been the focus of biophysical interrogation. Advances in experimental single-cell methods have invigorated theoretical studies into these processes. However, until recently, there was little dialog between the two areas of study. In particular, most theoretical models for gene regulation assumed gene activity to be oblivious to the progression of the cell cycle between birth and division. But, in fact, there are numerous ways in which the periodic character of all cellular observables can modulate gene expression. The molecular factors required for transcription and translation-RNA polymerase, transcription factors, ribosomes-increase in number during the cell cycle, but are also diluted due to the continuous increase in cell volume. The replication of the genome changes the dosage of those same cellular players but also provides competing targets for regulatory binding. Finally, cell division reduces their number again, and so forth. Stochasticity is inherent to all these biological processes, manifested in fluctuations in the synthesis and degradation of new cellular components as well as the random partitioning of molecules at each cell division event. The notion of gene expression as stationary is thus hard to justify. In this review, we survey the emerging paradigm of cell-cycle regulated gene expression, with an emphasis on the global expression patterns rather than gene-specific regulation. We discuss recent experimental reports where cell growth and gene expression were simultaneously measured in individual cells, providing first glimpses into the coupling between the two, and motivating several questions. How do the levels of gene expression products - mRNA and protein - scale with the cell volume and cell-cycle progression? What are the molecular origins of the observed scaling laws, and when do they break down to yield non-canonical behavior? What are the consequences of cell-cycle dependence for the heterogeneity ("noise") in gene expression within a cell population? While the experimental findings, not surprisingly, differ among genes, organisms, and environmental conditions, several theoretical models have emerged that attempt to reconcile these differences and form a unifying framework for understanding gene expression in growing cells.

Mycobacterial RNase E cleaves with a distinct sequence preference and controls the degradation rates of most Mycolicibacterium smegmatis mRNAs

The mechanisms and regulation of RNA degradation in mycobacteria have been subject to increased interest following the identification of interplay between RNA metabolism and drug resistance. Mycobacteria encode multiple ribonucleases predicted to participate in mRNA degradation and/or processing of stable RNAs. RNase E is hypothesized to play a major role in mRNA degradation because of its essentiality in mycobacteria and its role in mRNA degradation in gram-negative bacteria. Here, we defined the impact of RNase E on mRNA degradation rates transcriptome-wide in the nonpathogenic model Mycolicibacterium smegmatis. RNase E played a rate-limiting role in degradation of the transcripts encoded by at least 89% of protein-coding genes, with leadered transcripts often being more affected by RNase E repression than leaderless transcripts. There was an apparent global slowing of transcription in response to knockdown of RNase E, suggesting that M. smegmatis regulates transcription in responses to changes in mRNA degradation. This compensation was incomplete, as the abundance of most transcripts increased upon RNase E knockdown. We assessed the sequence preferences for cleavage by RNase E transcriptome-wide in M. smegmatis and Mycobacterium tuberculosis and found a consistent bias for cleavage in C-rich regions. Purified RNase E had a clear preference for cleavage immediately upstream of cytidines, distinct from the sequence preferences of RNase E in gram-negative bacteria. We furthermore report a high-resolution map of mRNA cleavage sites in M. tuberculosis, which occur primarily within the RNase E-preferred sequence context, confirming that RNase E has a broad impact on the M. tuberculosis transcriptome.

Comprehensive quantitative modeling of translation efficiency in a genome-reduced bacterium

Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.

spotter: a single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes

Stochastic simulation models have played an important role in efforts to understand the mechanistic basis of prokaryotic transcription and translation. Despite the fundamental linkage of these processes in bacterial cells, however, most simulation models have been limited to representations of either transcription or translation. In addition, the available simulation models typically either attempt to recapitulate data from single-molecule experiments without considering cellular-scale high-throughput sequencing data or, conversely, seek to reproduce cellular-scale data without paying close attention to many of the mechanistic details. To address these limitations, we here present spotter (Simulation of Prokaryotic Operon Transcription & Translation Elongation Reactions), a flexible, user-friendly simulation model that offers highly-detailed combined representations of prokaryotic transcription, translation, and DNA supercoiling. In incorporating nascent transcript and ribosomal profiling sequencing data, spotter provides a critical bridge between data collected in single-molecule experiments and data collected at the cellular scale. Importantly, in addition to rapidly generating output that can be aggregated for comparison with next-generation sequencing and proteomics data, spotter produces residue-level positional information that can be used to visualize individual simulation trajectories in detail. We anticipate that spotter will be a useful tool in exploring the interplay of processes that are crucially linked in prokaryotes.

Methodologies for bacterial ribonuclease characterization using RNA-seq

Bacteria adjust gene expression at the post-transcriptional level through an intricate network of small regulatory RNAs and RNA-binding proteins, including ribonucleases (RNases). RNases play an essential role in RNA metabolism, regulating RNA stability, decay, and activation. These enzymes exhibit species-specific effects on gene expression, bacterial physiology, and different strategies of target recognition. Recent advances in high-throughput RNA sequencing (RNA-seq) approaches have provided a better understanding of the roles and modes of action of bacterial RNases. Global studies aiming to identify direct targets of RNases have highlighted the diversity of RNase activity and RNA-based mechanisms of gene expression regulation. Here, we review recent RNA-seq approaches used to study bacterial RNases, with a focus on the methods for identifying direct RNase targets.

Simulation-based Reconstructed Diffusion unveils the effect of aging on protein diffusion in Escherichia coli

We have developed Simulation-based Reconstructed Diffusion (SbRD) to determine diffusion coefficients corrected for confinement effects and for the bias introduced by two-dimensional models describing a three-dimensional motion. We validate the method on simulated diffusion data in three-dimensional cell-shaped compartments. We use SbRD, combined with a new cell detection method, to determine the diffusion coefficients of a set of native proteins in Escherichia coli. We observe slower diffusion at the cell poles than in the nucleoid region of exponentially growing cells, which is independent of the presence of polysomes. Furthermore, we show that the newly formed pole of dividing cells exhibits a faster diffusion than the old one. We hypothesize that the observed slowdown at the cell poles is caused by the accumulation of aggregated or damaged proteins, and that the effect is asymmetric due to cell aging.

Improved RNA stability estimation indicates that transcriptional interference is frequent in diverse bacteria

We used stochastic simulations and experimental data from E. coli, K. aerogenes, Synechococcus PCC 7002 and Synechocystis PCC 6803 to provide evidence that transcriptional interference via the collision mechanism is likely a prevalent mechanism for bacterial gene regulation. Rifampicin time-series data can be used to globally monitor and quantify collision between sense and antisense transcription-complexes. Our findings also highlight that transcriptional events, such as differential RNA decay, partial termination, and internal transcriptional start sites often deviate from gene annotations. Consequently, within a single gene annotation, there exist transcript segments with varying half-lives and transcriptional properties. To address these complexities, we introduce 'rifi', an R-package that analyzes transcriptomic data from rifampicin time series. 'rifi' employs a dynamic programming-based segmentation approach to identify individual transcripts, enabling accurate assessment of RNA stability and detection of diverse transcriptional events.

A trailing ribosome speeds up RNA polymerase at the expense of transcript fidelity via force and allostery

In prokaryotes, translation can occur on mRNA that is being transcribed in a process called coupling. How the ribosome affects the RNA polymerase (RNAP) during coupling is not well understood. Here, we reconstituted the E. coli coupling system and demonstrated that the ribosome can prevent pausing and termination of RNAP and double the overall transcription rate at the expense of fidelity. Moreover, we monitored single RNAPs coupled to ribosomes and show that coupling increases the pause-free velocity of the polymerase and that a mechanical assisting force is sufficient to explain the majority of the effects of coupling. Also, by cryo-EM, we observed that RNAPs with a terminal mismatch adopt a backtracked conformation, while a coupled ribosome allosterically induces these polymerases toward a catalytically active anti-swiveled state. Finally, we demonstrate that prolonged RNAP pausing is detrimental to cell viability, which could be prevented by polymerase reactivation through a coupled ribosome.

Genome-wide mapping of fluoroquinolone-stabilized DNA gyrase cleavage sites displays drug specific effects that correlate with bacterial persistence

Bacterial persisters are rare phenotypic variants that are suspected to be culprits of recurrent infections. Fluoroquinolones (FQs) are a class of antibiotics that facilitate bacterial killing by stabilizing bacterial type II topoisomerases when they are in a complex with cleaved DNA. In Escherichia coli, DNA gyrase is the primary FQ target, and previous work has demonstrated that persisters are not spared from FQ-induced DNA damage. Since DNA gyrase cleavage sites (GCSs) largely govern the sites of DNA damage from FQ treatment, we hypothesized that GCS characteristics (e.g. number, strength, location) may influence persistence. To test this hypothesis, we measured genome-wide GCS distributions after treatment with a panel of FQs in stationary-phase cultures. We found drug-specific effects on the GCS distribution and discovered a strong negative correlation between the genomic cleavage strength and FQ persister levels. Further experiments and analyses suggested that persistence was unlikely to be governed by cleavage to individual sites, but rather survival was a function of the genomic GCS distribution. Together, these findings demonstrate FQ-specific differences in GCS distribution that correlate with persister levels and suggest that FQs that better stabilize DNA gyrase in cleaved complexes with DNA will lead to lower levels of persistence.

Genome-Wide Analysis of Gene Expression Noise Brought About by Transcriptional Regulation in Pseudomonas aeruginosa

The part of expression noise that is brought about by transcriptional regulation (represented here as NTR) is an important criterion for estimating the regulatory mode of a gene. However, characterization of NTR is an under-explored area, and there is little knowledge regarding the genome-wide NTR in the model pathogen Pseudomonas aeruginosa. Here, with a library of dual-color transcriptional reporters, we estimated the NTR for over 90% of the promoters in P. aeruginosa. Most promoters exhibit low NTR, while 42 and 115 promoters with high NTR were screened out in the exponential and the stationary growth phases, respectively. Specifically, a rearrangement of NTR was found in promoters involved in amino acid metabolism when bacteria enter the exponential phase. In addition, during the stationary phase, high NTR was found in a wide range of iron-related promoters involving siderophore synthesis and heme uptake, ExsA-regulated promoters involving bacterial virulence, and FleQ-regulated promoters involving biofilm development. We also found a large-scale negative dependence of transcriptional regulation between high-NTR promoters belonging to different functional categories. Our findings offer a global view of transcriptional heterogeneity in P. aeruginosa. IMPORTANCE The phenotypic diversity of Pseudomonas aeruginosa is frequently observed in research, suggesting that bacteria adopt strategies such as bet-hedging to survive ever-changing environments. Gene expression noise (GEN) is the major source of phenotypic diversity. Large GEN from transcriptional regulation (represented as NTR) represent an evolutionary necessity to maintain the copy number diversity of certain proteins in the population. Here, we provide a system-wide view of NTR in P. aeruginosa under nutrient-rich and stressed conditions. High NTR was found in genes involved in flagella biosynthesis and amino acid metabolism under both conditions. Specially, iron acquisition genes exhibited high NTR in the stressed condition, suggesting a great diversity of iron physiology in P. aeruginosa. We further revealed a global negative dependence of transcriptional regulation between those high-NTR genes under the stressed condition, suggesting a mutually exclusive relationship between different bacterial survival strategies.

Principles of gene regulation quantitatively connect DNA to RNA and proteins in bacteria

Protein concentrations are set by a complex interplay between gene-specific regulatory processes and systemic factors, including cell volume and shared gene expression machineries. Elucidating this interplay is crucial for discerning and designing gene regulatory systems. We quantitatively characterized gene-specific and systemic factors that affect transcription and translation genome-wide for Escherichia coli across many conditions. The results revealed two design principles that make regulation of gene expression insulated from concentrations of shared machineries: RNA polymerase activity is fine-tuned to match translational output, and translational characteristics are similar across most messenger RNAs (mRNAs). Consequently, in bacteria, protein concentration is set primarily at the promoter level. A simple mathematical formula relates promoter activities and protein concentrations across growth conditions, enabling quantitative inference of gene regulation from omics data.

A spatially resolved stochastic model reveals the role of supercoiling in transcription regulation

In Escherichia coli, translocation of RNA polymerase (RNAP) during transcription introduces supercoiling to DNA, which influences the initiation and elongation behaviors of RNAP. To quantify the role of supercoiling in transcription regulation, we developed a spatially resolved supercoiling model of transcription. The integrated model describes how RNAP activity feeds back with the local DNA supercoiling and how this mechanochemical feedback controls transcription, subject to topoisomerase activities and stochastic topological domain formation. This model establishes that transcription-induced supercoiling mediates the cooperation of co-transcribing RNAP molecules in highly expressed genes, and this cooperation is achieved under moderate supercoiling diffusion and high topoisomerase unbinding rates. It predicts that a topological domain could serve as a transcription regulator, generating substantial transcriptional noise. It also shows the relative orientation of two closely arranged genes plays an important role in regulating their transcription. The model provides a quantitative platform for investigating how genome organization impacts transcription.

Alteration of DNA supercoiling serves as a trigger of short-term cold shock repressed genes of E. coli

Cold shock adaptability is a key survival skill of gut bacteria of warm-blooded animals. Escherichia coli cold shock responses are controlled by a complex multi-gene, timely-ordered transcriptional program. We investigated its underlying mechanisms. Having identified short-term, cold shock repressed genes, we show that their responsiveness is unrelated to their transcription factors or global regulators, while their single-cell protein numbers' variability increases after cold shock. We hypothesized that some cold shock repressed genes could be triggered by high propensity for transcription locking due to changes in DNA supercoiling (likely due to DNA relaxation caused by an overall reduction in negative supercoiling). Concomitantly, we found that nearly half of cold shock repressed genes are also highly responsive to gyrase inhibition (albeit most genes responsive to gyrase inhibition are not cold shock responsive). Further, their response strengths to cold shock and gyrase inhibition correlate. Meanwhile, under cold shock, nucleoid density increases, and gyrases and nucleoid become more colocalized. Moreover, the cellular energy decreases, which may hinder positive supercoils resolution. Overall, we conclude that sensitivity to diminished negative supercoiling is a core feature of E. coli's short-term, cold shock transcriptional program, and could be used to regulate the temperature sensitivity of synthetic circuits.

Getting Closer to Decrypting the Phase Transitions of Bacterial Biomolecules

Liquid-liquid phase separation (LLPS) of biomolecules has emerged as a new paradigm in cell biology, and the process is one proposed mechanism for the formation of membraneless organelles (MLOs). Bacterial cells have only recently drawn strong interest in terms of studies on both liquid-to-liquid and liquid-to-solid phase transitions. It seems that these processes drive the formation of prokaryotic cellular condensates that resemble eukaryotic MLOs. In this review, we present an overview of the key microbial biomolecules that undergo LLPS, as well as the formation and organization of biomacromolecular condensates within the intracellular space. We also discuss the current challenges in investigating bacterial biomacromolecular condensates. Additionally, we highlight a summary of recent knowledge about the participation of bacterial biomolecules in a phase transition and provide some new in silico analyses that can be helpful for further investigations.

Suboptimal resource allocation in changing environments constrains response and growth in bacteria

To respond to fluctuating conditions, microbes typically need to synthesize novel proteins. As this synthesis relies on sufficient biosynthetic precursors, microbes must devise effective response strategies to manage depleting precursors. To better understand these strategies, we investigate the active response of Escherichia coli to changes in nutrient conditions, connecting transient gene expression to growth phenotypes. By synthetically modifying gene expression during changing conditions, we show how the competition by genes for the limited protein synthesis capacity constrains cellular response. Despite this constraint cells substantially express genes that are not required, trapping them in states where precursor levels are low and the genes needed to replenish the precursors are outcompeted. Contrary to common modeling assumptions, our findings highlight that cells do not optimize growth under changing environments but rather exhibit hardwired response strategies that may have evolved to promote fitness in their native environment. The constraint and the suboptimality of the cellular response uncovered provide a conceptual framework relevant for many research applications, from the prediction of evolution to the improvement of gene circuits in biotechnology.

DNA Supercoiling Drives a Transition between Collective Modes of Gene Synthesis

Transcription of genes can be affected by both biochemical and mechanical factors. Recent experiments suggested that the mechanical stress associated with transcription-induced DNA supercoiling is responsible for the transition from cooperative to antagonistic group dynamics of RNA polymerases (RNAPs) upon promoter repression. To underpin the mechanism behind this drastic transition, we developed a continuum deterministic model for transcription under torsion. In our model, the speed of an RNAP is affected by the local DNA supercoiling, as well as two global factors: (i) the number of RNAPs on the gene affecting the torsional stress experienced by individual RNAPs and (ii) transcription factors blocking the diffusion of DNA supercoils. Our minimal model can successfully reproduce the experimental findings and helps elucidate the interplay of mechanical and biological factors in the collective dynamics of molecular machines involved in gene expression.

A pathogen-specific sRNA influences enterohemorrhagic Escherichia coli fitness and virulence in part by direct interaction with the transcript encoding the ethanolamine utilization regulatory factor EutR

Enterohemorrhagic Escherichia coli (EHEC) O157:H7 relies on sRNAs to coordinate expression of metabolic and virulence factors to colonize the host. Here, we focus on the sRNA, named MavR (metabolism and virulence regulator), that is conserved among pathogenic Enterobacteriaceae. MavR is constitutively expressed under in vitro conditions that promote EHEC virulence gene expression. Using MS2-affinity purification coupled with RNA sequencing, the eutR transcript was identified as a putative target of MavR. EutR is a transcription factor that promotes expression of genes required for ethanolamine metabolism as well as virulence factors important for host colonization. MavR binds to the eutR coding sequence to protect the eutR transcript from RNase E-mediated degradation. Ultimately, MavR promotes EutR expression and in turn ethanolamine utilization and ethanolamine-dependent growth. RNAseq analyses revealed that MavR also affected expression of genes important for other metabolic pathways, motility, oxidative stress and attaching and effacing lesion formation, which contribute to EHEC colonization of the gastrointestinal tract. In support of the idea that MavR-dependent gene expression affects fitness during infection, deletion of mavR resulted in significant (∼10- to 100-fold) attenuation in colonization of the mammalian intestine. Altogether, these studies reveal an important, extensive, and robust phenotype for a bacterial sRNA in host-pathogen interactions.

β-CASP proteins removing RNA polymerase from DNA: when a torpedo is needed to shoot a sitting duck

During the first step of gene expression, RNA polymerase (RNAP) engages DNA to transcribe RNA, forming highly stable complexes. These complexes need to be dissociated at the end of transcription units or when RNAP stalls during elongation and becomes an obstacle (‘sitting duck’) to further transcription or replication. In this review, we first outline the mechanisms involved in these processes. Then, we explore in detail the torpedo mechanism whereby a 5′–3′ RNA exonuclease (torpedo) latches itself onto the 5′ end of RNA protruding from RNAP, degrades it and upon contact with RNAP, induces dissociation of the complex. This mechanism, originally described in Eukaryotes and executed by Xrn-type 5′–3′ exonucleases, was recently found in Bacteria and Archaea, mediated by β-CASP family exonucleases. We discuss the mechanistic aspects of this process across the three kingdoms of life and conclude that 5′–3′ exoribonucleases (β-CASP and Xrn families) involved in the ancient torpedo mechanism have emerged at least twice during evolution.

Design of time-delayed safety switches for CRISPR gene therapy

CRISPR system is a powerful gene editing tool which has already been reported to address a variety of gene relevant diseases in different cell lines. However, off-target effect and immune response caused by Cas9 remain two fundamental problems. Inspired by previously reported Cas9 self-elimination systems, time-delayed safety switches are designed in this work. Firstly, ultrasensitive relationship is constructed between Cas9-sgRNA (enzyme) and Cas9 plasmids (substrate), which generates the artificial time delay. Then intrinsic time delay in biomolecular activities is revealed by data fitting and utilized in constructing safety switches. The time-delayed safety switches function by separating the gene editing process and self-elimination process, and the tunable delay time may ensure a good balance between gene editing efficiency and side effect minimization. By addressing gene therapy efficiency, off-target effect, immune response and drug accumulation, we hope our safety switches may offer inspiration in realizing safe and efficient gene therapy in humans.

Quantitative Control for Stoichiometric Protein Synthesis

Bacterial protein synthesis rates have evolved to maintain preferred stoichiometries at striking precision, from the components of protein complexes to constituents of entire pathways. Setting relative protein production rates to be well within a factor of two requires concerted tuning of transcription, RNA turnover, and translation, allowing many potential regulatory strategies to achieve the preferred output. The last decade has seen a greatly expanded capacity for precise interrogation of each step of the central dogma genome-wide. Here, we summarize how these technologies have shaped the current understanding of diverse bacterial regulatory architectures underpinning stoichiometric protein synthesis. We focus on the emerging expanded view of bacterial operons, which encode diverse primary and secondary mRNA structures for tuning protein stoichiometry. Emphasis is placed on how quantitative tuning is achieved. We discuss the challenges and open questions in the application of quantitative, genome-wide methodologies to the problem of precise protein production. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Interplay between Nucleoid-Associated Proteins and Transcription Factors in Controlling Specialized Metabolism in Streptomyces

Lsr2 is a small nucleoid-associated protein found throughout the actinobacteria. Lsr2 functions similarly to the well-studied H-NS, in that it preferentially binds AT-rich sequences and represses gene expression. In Streptomyces venezuelae, Lsr2 represses the expression of many specialized metabolic clusters, including the chloramphenicol antibiotic biosynthetic gene cluster, and deleting lsr2 leads to significant upregulation of chloramphenicol cluster expression. We show here that Lsr2 likely exerts its repressive effects on the chloramphenicol cluster by polymerizing along the chromosome and by bridging sites within and adjacent to the chloramphenicol cluster. CmlR is a known activator of the chloramphenicol cluster, but expression of its associated gene is not upregulated in an lsr2 mutant strain. We demonstrate that CmlR is essential for chloramphenicol production, and further reveal that CmlR functions to “countersilence” Lsr2’s repressive effects by recruiting RNA polymerase and enhancing transcription, with RNA polymerase effectively clearing bound Lsr2 from the chloramphenicol cluster DNA. Our results provide insight into the interplay between opposing regulatory proteins that govern antibiotic production in S. venezuelae, which could be exploited to maximize the production of bioactive natural products in other systems.

The essential role of mRNA degradation in understanding and engineering E. coli metabolism

Metabolic engineering strategies are crucial for the development of bacterial cell factories with improved performance. Until now, optimal metabolic networks have been designed based on systems biology approaches integrating large-scale data on the steady-state concentrations of mRNA, protein and metabolites, sometimes with dynamic data on fluxes, but rarely with any information on mRNA degradation. In this review, we compile growing evidence that mRNA degradation is a key regulatory level in E. coli that metabolic engineering strategies should take into account. We first discuss how mRNA degradation interacts with transcription and translation, two other gene expression processes, to balance transcription regulation and remove poorly translated mRNAs. The many reciprocal interactions between mRNA degradation and metabolism are also highlighted: metabolic activity can be controlled by changes in mRNA degradation and in return, the activity of the mRNA degradation machinery is controlled by metabolic factors. The mathematical models of the crosstalk between mRNA degradation dynamics and other cellular processes are presented and discussed with a view towards novel mRNA degradation-based metabolic engineering strategies. We show finally that mRNA degradation-based strategies have already successfully been applied to improve heterologous protein synthesis. Overall, this review underlines how important mRNA degradation is in regulating E. coli metabolism and identifies mRNA degradation as a key target for innovative metabolic engineering strategies in biotechnology.

Dynamics of transcriptional and post-transcriptional regulation

Despite gene expression programs being notoriously complex, RNA abundance is usually assumed as a proxy for transcriptional activity. Recently developed approaches, able to disentangle transcriptional and post-transcriptional regulatory processes, have revealed a more complex scenario. It is now possible to work out how synthesis, processing and degradation kinetic rates collectively determine the abundance of each gene's RNA. It has become clear that the same transcriptional output can correspond to different combinations of the kinetic rates. This underscores the fact that markedly different modes of gene expression regulation exist, each with profound effects on a gene's ability to modulate its own expression. This review describes the development of the experimental and computational approaches, including RNA metabolic labeling and mathematical modeling, that have been disclosing the mechanisms underlying complex transcriptional programs. Current limitations and future perspectives in the field are also discussed.

Interconnecting solvent quality, transcription, and chromosome folding in Escherichia coli

All cells fold their genomes, including bacterial cells, where the chromosome is compacted into a domain-organized meshwork called the nucleoid. How compaction and domain organization arise is not fully understood. Here, we describe a method to estimate the average mesh size of the nucleoid in Escherichia coli. Using nucleoid mesh size and DNA concentration estimates, we find that the cytoplasm behaves as a poor solvent for the chromosome when the cell is considered as a simple semidilute polymer solution. Monte Carlo simulations suggest that a poor solvent leads to chromosome compaction and DNA density heterogeneity (i.e., domain formation) at physiological DNA concentration. Fluorescence microscopy reveals that the heterogeneous DNA density negatively correlates with ribosome density within the nucleoid, consistent with cryoelectron tomography data. Drug experiments, together with past observations, suggest the hypothesis that RNAs contribute to the poor solvent effects, connecting chromosome compaction and domain formation to transcription and intracellular organization.

Gene expression profile analysis and target gene discovery of Mycobacterium tuberculosis biofilm

Tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) is a fatal infectious disease to human health, and the drug tolerance and immune evasion of M. tuberculosis were reported to be related to its biofilm formation; however, the difficulty of M. tuberculosis biofilm culture and its unknown global mechanism impede its further research. Here, we developed a modified in vitro M. tuberculosis biofilm model with shorter culture time. Then we used Illumina RNA-seq technology to determine the global gene expression profile of M. tuberculosis H37Rv biofilms. Over 437 genes are expressed at significantly different levels in biofilm cells than in planktonic cells; among them, 153 were downregulated and 284 were upregulated. Go enrichment analysis and KEGG pathway analysis showed that genes involved in biosynthesis and metabolism of sulfur metabolism, steroid degradation, atrazine degradation, mammalian cell entry protein complex, etc. are involved in M. tuberculosis biofilm cells. Especially, ATP-binding cassette (ABC) transporters Rv1217c and Rv1218c were significantly upregulated in biofilm, whereas efflux pump inhibitors (EPIs) piperine and 1-(1-naphthylmethyl)-piperazine (NMP) inhibited biofilm formation and the expression of the Rv1217c and Rv1218c genes in a concentration-dependent manner, respectively, indicating Rv1217c and Rv1218c are potential target genes of M. tuberculosis biofilm. This study is the first RNA-Seq-based transcriptome profiling of M. tuberculosis biofilms and provides insights into a potential strategy for M. tuberculosis biofilm inhibition. KEY POINTS: • Characterize M. tuberculosis transcriptomes in biofilm cells by RNA-seq. • Inhibit the expression of Rv1217c and Rv1218c repressed biofilm formation.

Comparison of bias and resolvability in single-cell and single-transcript methods

Single-cell and single-transcript measurement methods have elevated our ability to understand and engineer biological systems. However, defining and comparing performance between methods remains a challenge, in part due to the confounding effects of experimental variability. Here, we propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is shared between methods. We demonstrate the utility of this framework by performing 12 different methods in parallel to measure the same underlying reference system for cellular response. We compare method performance using quantitative evaluations of bias and resolvability. We attribute differences in method performance to steps along the measurement process such as sample preparation, signal detection, and choice of measurand. Finally, we demonstrate how this framework can be used to benchmark different methods for single-transcript detection. The framework we present here provides a practical way to compare performance of any methods.

Neural network aided approximation and parameter inference of non-Markovian models of gene expression

Non-Markovian models of stochastic biochemical kinetics often incorporate explicit time delays to effectively model large numbers of intermediate biochemical processes. Analysis and simulation of these models, as well as the inference of their parameters from data, are fraught with difficulties because the dynamics depends on the system's history. Here we use an artificial neural network to approximate the time-dependent distributions of non-Markovian models by the solutions of much simpler time-inhomogeneous Markovian models; the approximation does not increase the dimensionality of the model and simultaneously leads to inference of the kinetic parameters. The training of the neural network uses a relatively small set of noisy measurements generated by experimental data or stochastic simulations of the non-Markovian model. We show using a variety of models, where the delays stem from transcriptional processes and feedback control, that the Markovian models learnt by the neural network accurately reflect the stochastic dynamics across parameter space.

Synthetic protein quality control to enhance full-length translation in bacteria

Coupled transcription and translation processes in bacteria cause indiscriminate translation of intact and truncated messenger RNAs, inevitably generating nonfunctional polypeptides. Here, we devised a synthetic protein quality control (ProQC) system that enables translation only when both ends of mRNAs are present and followed by circularization based on sequence-specific RNA-RNA hybridization. We demonstrate that the ProQC system dramatically improved the fraction of full-length proteins among all synthesized polypeptides by selectively translating intact mRNA and reducing abortive translation. As a result, full-length protein synthesis increased up to 2.5-fold without changing the transcription or translation efficiency. Furthermore, we applied the ProQC system for 3-hydroxypropionic acid, violacein and lycopene production by ensuring full-length expression of enzymes in biosynthetic pathways, resulting in 1.6- to 2.3-fold greater biochemical production. We believe that our ProQC system can be universally applied to improve not only the quality of recombinant protein production but also efficiencies of metabolic pathways.

Hierarchy in Hfq Chaperon Occupancy of Small RNA Targets Plays a Major Role in Their Regulation

Bacterial small RNAs (sRNAs) are posttranscriptional regulators of gene expression that base pair with complementary sequences on target mRNAs, often in association with the chaperone Hfq. Here, using experimentally identified sRNA-target pairs, along with gene expression measurements, we assess basic principles of regulation by sRNAs. We show that the sRNA sequence dictates the target repertoire, as point mutations in the sRNA shift the target set correspondingly. We distinguish two subsets of targets: targets showing changes in expression levels under overexpression of their sRNA regulator and unaffected targets that interact more sporadically with the sRNA. These differences among targets are associated with their Hfq occupancy, rather than with the sRNA-target base-pairing potential. Our results suggest that competition among targets over Hfq binding plays a major role in the regulatory outcome, possibly awarding targets with higher Hfq binding efficiency an advantage in the competition over binding to the sRNA.

•

Basic concepts of regulation by small RNAs are revealed from large-scale data

•

Small changes in the small RNA sequence shift the target repertoire accordingly

•

A regulatory sRNA affects the expression levels of only a subset of its targets

•

Competition among targets over Hfq binding plays a major role in their regulation

Dynamic interactions between the RNA chaperone Hfq, small regulatory RNAs, and mRNAs in live bacterial cells

RNA-binding proteins play myriad roles in regulating RNAs and RNA-mediated functions. In bacteria, the RNA chaperone Hfq is an important post-transcriptional gene regulator. Using live-cell super-resolution imaging, we can distinguish Hfq binding to different sizes of cellular RNAs. We demonstrate that under normal growth conditions, Hfq exhibits widespread mRNA-binding activity, with the distal face of Hfq contributing mostly to the mRNA binding in vivo. In addition, sRNAs can either co-occupy Hfq with the mRNA as a ternary complex, or displace the mRNA from Hfq in a binding face-dependent manner, suggesting mechanisms through which sRNAs rapidly access Hfq to induce sRNA-mediated gene regulation. Finally, our data suggest that binding of Hfq to certain mRNAs through its distal face can recruit RNase E to promote turnover of these mRNAs in a sRNA-independent manner, and such regulatory function of Hfq can be decoyed by sRNA competitors that bind strongly at the distal face.

Messenger RNAs or mRNAs are molecules that the cell uses to transfer the information stored in the cell’s DNA so it can be used to make proteins. Bacteria can regulate their levels of mRNA molecules, and they can therefore control how many proteins are being made, by producing a different type of RNA called small regulatory RNAs or sRNAs. Each sRNA can bind to several specific mRNA targets, and lead to their degradation by an enzyme called RNase E. Certain bacterial RNA-binding proteins, such as Hfq, protect sRNAs from being degraded, and help them find their mRNA targets.

Hfq is abundant in bacteria. It is critical for bacterial growth under harsh conditions and it is involved in the process through which pathogenic bacteria infect cells. However, it is outnumbered by the many different RNA molecules in the cell, which compete for binding to the protein. It is not clear how Hfq prioritizes the different RNAs, or how binding to Hfq alters RNA regulation. Park, Prévost et al. imaged live bacterial cells to see how Hfq binds to RNA strands of different sizes.

The experiments revealed that, when bacteria are growing normally, Hfq is mainly bound to mRNA molecules, and it can recruit RNase E to speed up mRNA degradation without the need for sRNAs. Park, Prévost et al. also showed that sRNAs could bind to Hfq by either replacing the bound mRNA or co-binding alongside it. The sRNA molecules that strongly bind Hfq can compete against mRNA for binding, and thus slow down the degradation of certain mRNAs.

Hfq could be a potential drug target for treating bacterial infections. Understanding how it interacts with other molecules in bacteria could provide help in the development of new therapeutics. These findings suggest that a designed RNA that binds strongly to Hfq could disrupt its regulatory roles in bacteria, killing them. This could be a feasible drug design opportunity to counter the emergence of antibiotic-resistant bacteria.

Systematic Quantification of Sequence and Structural Determinants Controlling mRNA stability in Bacterial Operons

mRNA degradation is a central process that affects all gene expression levels, and yet, the determinants that control mRNA decay rates remain poorly characterized. Here, we applied a synthetic biology, learn-by-design approach to elucidate the sequence and structural determinants that control mRNA stability in bacterial operons. We designed, constructed, and characterized 82 operons in Escherichia coli, systematically varying RNase binding site characteristics, translation initiation rates, and transcriptional terminator efficiencies in the 5' untranslated region (UTR), intergenic, and 3' UTR regions, followed by measuring their mRNA levels using reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays during exponential growth. We show that introducing long single-stranded RNA into 5' UTRs reduced mRNA levels by up to 9.4-fold and that lowering translation rates reduced mRNA levels by up to 11.8-fold. We also found that RNase binding sites in intergenic regions had much lower effects on mRNA levels. Surprisingly, changing the transcriptional termination efficiency or introducing long single-stranded RNA into 3' UTRs had no effect on upstream mRNA levels. From these measurements, we developed and validated biophysical models of ribosome protection and RNase activity with excellent quantitative agreement. We also formulated design rules to rationally control a mRNA's stability, facilitating the automated design of engineered genetic systems with desired functionalities.

Ultrasensitive molecular controllers for quasi-integral feedback

Feedback control has enabled the success of automated technologies by mitigating the effects of variability, unknown disturbances, and noise. While it is known that biological feedback loops reduce the impact of noise and help shape kinetic responses, many questions remain about how to design molecular integral controllers. Here, we propose a modular strategy to build molecular quasi-integral feedback controllers, which involves following two design principles. The first principle is to utilize an ultrasensitive response, which determines the gain of the controller and influences the steady-state error. The second is to use a tunable threshold of the ultrasensitive response, which determines the equilibrium point of the system. We describe a reaction network, named brink controller, that satisfies these conditions by combining molecular sequestration and an activation/deactivation cycle. With computational models, we examine potential biological implementations of brink controllers, and we illustrate different example applications.

Coupled Transcription-Translation in Prokaryotes: An Old Couple With New Surprises

Coupled transcription-translation (CTT) is a hallmark of prokaryotic gene expression. CTT occurs when ribosomes associate with and initiate translation of mRNAs whose transcription has not yet concluded, therefore forming "RNAP.mRNA.ribosome" complexes. CTT is a well-documented phenomenon that is involved in important gene regulation processes, such as attenuation and operon polarity. Despite the progress in our understanding of the cellular signals that coordinate CTT, certain aspects of its molecular architecture remain controversial. Additionally, new information on the spatial segregation between the transcriptional and the translational machineries in certain species, and on the capability of certain mRNAs to localize translation-independently, questions the unanimous occurrence of CTT. Furthermore, studies where transcription and translation were artificially uncoupled showed that transcription elongation can proceed in a translation-independent manner. Here, we review studies supporting the occurrence of CTT and findings questioning its extent, as well as discuss mechanisms that may explain both coupling and uncoupling, e.g., chromosome relocation and the involvement of cis- or trans-acting elements, such as small RNAs and RNA-binding proteins. These mechanisms impact RNA localization, stability, and translation. Understanding the two options by which genes can be expressed and their consequences should shed light on a new layer of control of bacterial transcripts fate.

Reconciling kinetic and thermodynamic models of bacterial transcription

The study of transcription remains one of the centerpieces of modern biology with implications in settings from development to metabolism to evolution to disease. Precision measurements using a host of different techniques including fluorescence and sequencing readouts have raised the bar for what it means to quantitatively understand transcriptional regulation. In particular our understanding of the simplest genetic circuit is sufficiently refined both experimentally and theoretically that it has become possible to carefully discriminate between different conceptual pictures of how this regulatory system works. This regulatory motif, originally posited by Jacob and Monod in the 1960s, consists of a single transcriptional repressor binding to a promoter site and inhibiting transcription. In this paper, we show how seven distinct models of this so-called simple-repression motif, based both on thermodynamic and kinetic thinking, can be used to derive the predicted levels of gene expression and shed light on the often surprising past success of the thermodynamic models. These different models are then invoked to confront a variety of different data on mean, variance and full gene expression distributions, illustrating the extent to which such models can and cannot be distinguished, and suggesting a two-state model with a distribution of burst sizes as the most potent of the seven for describing the simple-repression motif.

Competitive effects in bacterial mRNA decay

In living organisms, the same enzyme catalyses the degradation of thousands of different mRNAs, but the possible influence of competing substrates has been largely ignored so far. We develop a simple mechanistic model of the coupled degradation of all cell mRNAs using the total quasi-steady-state approximation of the Michaelis-Menten framework. Numerical simulations of the model using carefully chosen parameters and analyses of rate sensitivity coefficients show how substrate competition alters mRNA decay. The model predictions reproduce and explain a number of experimental observations on mRNA decay following transcription arrest, such as delays before the onset of degradation, the occurrence of variable degradation profiles with increased non linearities and the negative correlation between mRNA half-life and concentration. The competition acts at different levels, through the initial concentration of cell mRNAs and by modifying the enzyme affinity for its targets. The consequence is a global slow down of mRNA decay due to enzyme titration and the amplification of its apparent affinity. Competition happens to stabilize weakly affine mRNAs and to destabilize the most affine ones. We believe that this mechanistic model is an interesting alternative to the exponential models commonly used for the determination of mRNA half-lives. It allows analysing regulatory mechanisms of mRNA degradation and its predictions are directly comparable to experimental data.

Phase-separated bacterial ribonucleoprotein bodies organize mRNA decay

In bacteria, mRNA decay is controlled by megadalton scale macromolecular assemblies called, "RNA degradosomes," composed of nucleases and other RNA decay associated proteins. Recent advances in bacterial cell biology have shown that RNA degradosomes can assemble into phase-separated structures, termed bacterial ribonucleoprotein bodies (BR-bodies), with many analogous properties to eukaryotic processing bodies and stress granules. This review will highlight the functional role that BR-bodies play in the mRNA decay process through its organization into a membraneless organelle in the bacterial cytoplasm. This review will also highlight the phylogenetic distribution of BR-bodies across bacterial species, which suggests that these phase-separated structures are broadly distributed across bacteria, and in evolutionarily related mitochondria and chloroplasts. This article is categorized under: RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes RNA Export and Localization > RNA Localization RNA Turnover and Surveillance > Regulation of RNA Stability.

Data-driven in silico prediction of regulation heterogeneity and ATP demands of Escherichia coli in large-scale bioreactors

Escherichia coli exposed to industrial-scale heterogeneous mixing conditions respond to external stress by initiating short-term metabolic and long-term strategic transcriptional programs. In native habitats, long-term strategies allow survival in severe stress but are of limited use in large bioreactors, where microenvironmental conditions may change right after said programs are started. Related on/off switching of genes causes additional ATP burden that may reduce the cellular capacity for producing the desired product. Here, we present an agent-based data-driven model linked to computational fluid dynamics, finally allowing to predict additional ATP needs of Escherichia coli K12 W3110 exposed to realistic large-scale bioreactor conditions. The complex model describes transcriptional up- and downregulation dynamics of about 600 genes starting from subminute range covering 28 h. The data-based approach was extracted from comprehensive scale-down experiments. Simulating mixing and mass transfer conditions in a 54 m³ stirred bioreactor, 120,000 E. coli cells were tracked while fluctuating between different zones of glucose availability. It was found that cellular ATP demands rise between 30% and 45% of growth decoupled maintenance needs, which may limit the production of ATP-intensive product formation accordingly. Furthermore, spatial analysis of individual cell transcriptional patterns reveal very heterogeneous gene amplifications with hot spots of 50%-80% messenger RNA upregulation in the upper region of the bioreactor. The phenomenon reflects the time-delayed regulatory response of the cells that propagate through the stirred tank. After 4.2 h, cells adapt to environmental changes but still have to bear an additional 6% ATP demand.

Prokaryotic single-cell RNA sequencing by in situ combinatorial indexing

Despite longstanding appreciation of gene expression heterogeneity in isogenic bacterial populations, affordable and scalable technologies for studying single bacterial cells have been limited. Although single-cell RNA sequencing (scRNA-seq) has revolutionized studies of transcriptional heterogeneity in diverse eukaryotic systems1-13, the application of scRNA-seq to prokaryotes has been hindered by their extremely low mRNA abundance14-16, lack of mRNA polyadenylation and thick cell walls17. Here, we present prokaryotic expression profiling by tagging RNA in situ and sequencing (PETRI-seq)-a low-cost, high-throughput prokaryotic scRNA-seq pipeline that overcomes these technical obstacles. PETRI-seq uses in situ combinatorial indexing11,12,18 to barcode transcripts from tens of thousands of cells in a single experiment. PETRI-seq captures single-cell transcriptomes of Gram-negative and Gram-positive bacteria with high purity and low bias, with median capture rates of more than 200 mRNAs per cell for exponentially growing Escherichia coli. These characteristics enable robust discrimination of cell states corresponding to different phases of growth. When applied to wild-type Staphylococcus aureus, PETRI-seq revealed a rare subpopulation of cells undergoing prophage induction. We anticipate that PETRI-seq will have broad utility in defining single-cell states and their dynamics in complex microbial communities.

The RNase J-Based RNA Degradosome Is Compartmentalized in the Gastric Pathogen Helicobacter pylori

Posttranscriptional regulation is a major level of gene expression control in any cell. In bacteria, multiprotein machines called RNA degradosomes are central for RNA processing and degradation, and some were reported to be compartmentalized inside these organelleless cells. The minimal RNA degradosome of the important gastric pathogen Helicobacter pylori is composed of the essential ribonuclease RNase J and RhpA, its sole DEAD box RNA helicase, and plays a major role in the regulation of mRNA decay and adaptation to gastric colonization. Here, the subcellular localization of the H. pylori RNA degradosome was investigated using cellular fractionation and both confocal and superresolution microscopy. We established that RNase J and RhpA are peripheral inner membrane proteins and that this association was mediated neither by ribosomes nor by RNA nor by the RNase Y membrane protein. In live H. pylori cells, we observed that fluorescent RNase J and RhpA protein fusions assemble into nonpolar foci. We identified factors that regulate the formation of these foci without affecting the degradosome membrane association. Flotillin, a bacterial membrane scaffolding protein, and free RNA promote focus formation in H. pylori Finally, RNase J-GFP (RNase J-green fluorescent protein) molecules and foci in cells were quantified by three-dimensional (3D) single-molecule fluorescence localization microscopy. The number and size of the RNase J foci were found to be scaled with growth phase and cell volume as previously reported for eukaryotic ribonucleoprotein granules. In conclusion, we propose that membrane compartmentalization and the regulated clustering of RNase J-based degradosome hubs represent important levels of control of their activity and specificity.IMPORTANCE Helicobacter pylori is a bacterial pathogen that chronically colonizes the stomach of half of the human population worldwide. Infection by H. pylori can lead to the development of gastric pathologies such as ulcers and adenocarcinoma, which causes up to 800,000 deaths in the world each year. Persistent colonization by H. pylori relies on regulation of the expression of adaptation-related genes. One major level of such control is posttranscriptional regulation, which, in H. pylori, largely relies on a multiprotein molecular machine, an RNA degradosome, that we previously discovered. In this study, we established that the two protein partners of this machine are associated with the membrane of H. pylori Using cutting-edge microscopy, we showed that these complexes assemble into hubs whose formation is regulated by free RNA and scaled with bacterial size and growth phase. Organelleless cellular compartmentalization of molecular machines into hubs emerges as an important regulatory level in bacteria.

Regulation of mRNA Stability During Bacterial Stress Responses

Bacteria have a remarkable ability to sense environmental changes, swiftly regulating their transcriptional and posttranscriptional machinery as a response. Under conditions that cause growth to slow or stop, bacteria typically stabilize their transcriptomes in what has been shown to be a conserved stress response. In recent years, diverse studies have elucidated many of the mechanisms underlying mRNA degradation, yet an understanding of the regulation of mRNA degradation under stress conditions remains elusive. In this review we discuss the diverse mechanisms that have been shown to affect mRNA stability in bacteria. While many of these mechanisms are transcript-specific, they provide insight into possible mechanisms of global mRNA stabilization. To that end, we have compiled information on how mRNA fate is affected by RNA secondary structures; interaction with ribosomes, RNA binding proteins, and small RNAs; RNA base modifications; the chemical nature of 5' ends; activity and concentration of RNases and other degradation proteins; mRNA and RNase localization; and the stringent response. We also provide an analysis of reported relationships between mRNA abundance and mRNA stability, and discuss the importance of stress-associated mRNA stabilization as a potential target for therapeutic development.