Global analysis of mRNA decay and abundance in Escherichia coli at single-gene resolution using two-color fluorescent DNA microarrays

TEAL-Seq: targeted expression analysis sequencing

Metagenome sequencing enables the genetic characterization of complex microbial communities. However, determining the activity of isolates within a community presents several challenges, including the wide range of organismal and gene expression abundances, the presence of host RNA, and low microbial biomass at many sites. To address these limitations, we developed "targeted expression analysis sequencing" or TEAL-seq, enabling sensitive species-specific analyses of gene expression using highly multiplexed custom probe pools. For proof of concept, we targeted about 1,700 core and accessory genes of Staphylococcus aureus and S. epidermidis, two key species of the skin microbiome. Two targeting methods were applied to laboratory cultures and human nasal swab specimens. Both methods showed a high degree of specificity, with >90% reads on target, even in the presence of complex microbial or human background DNA/RNA. Targeting using molecular inversion probes demonstrated excellent correlation in inferred expression levels with bulk RNA-seq. Furthermore, we show that a linear pre-amplification step to increase the number of nucleic acids for analysis yielded consistent and predictable results when applied to complex samples and enabled profiling of expression from as little as 1 ng of total RNA. TEAL-seq is much less expensive than bulk metatranscriptomic profiling, enables detection across a greater dynamic range, and uses a strategy that is readily configurable for determining the transcriptional status of organisms in any microbial community.IMPORTANCEThe gene expression patterns of bacteria in microbial communities reflect their activity and interactions with other community members. Measuring gene expression in complex microbiome contexts is challenging, however, due to the large dynamic range of microbial abundances and transcript levels. Here we describe an approach to assessing gene expression for specific species of interest using highly multiplexed pools of targeting probes. We show that an isothermal amplification step enables the profiling of low biomass samples. TEAL-seq should be widely adaptable to the study of microbial activity in natural environments.

Dynamics of bacterial operons during genome-wide stresses is influenced by premature terminations and internal promoters

Bacterial gene networks have operons, each coordinating several genes under a primary promoter. Half of the operons in Escherichia coli have been reported to also contain internal promoters. We studied their role during genome-wide stresses targeting key transcription regulators, RNA polymerase (RNAP) and gyrase. Our results suggest that operons' responses are influenced by stress-related changes in premature elongation terminations and internal promoters' activity. Globally, this causes the responses of genes in the same operon to differ with the distance between them in a wave-like pattern. Meanwhile, premature terminations are affected by positive supercoiling buildup, collisions between elongating and promoter-bound RNAPs, and local regulatory elements. We report similar findings in E. coli under other stresses and in evolutionarily distant bacteria Bacillus subtilis, Corynebacterium glutamicum, and Helicobacter pylori. Our results suggest that the strength, number, and positioning of operons' internal promoters might have evolved to compensate for premature terminations, providing distal genes similar response strengths.

Designing biological network motif-based controllers by reverse engineering Hill function-type models from linear models

Perfect adaptation, the ability to regulate and maintain gene expression to its desired value despite disturbances, is important in the development of organisms. Building biological controllers to endow engineered biological systems with such perfect adaptation capability is a key goal in synthetic biology. Model-guided exploration of such synthetic circuits has been effective in designing such systems. However, theoretical analysis to guarantee controller properties with nonlinear models, such as Hill functions, remains challenging, while use of linear models fails to capture the inherent nonlinear dynamics of gene expression systems. Here, we propose a reverse engineering approach to infer the kinetic parameters for nonlinear Hill function-type models from analysis of linear models and apply our method to design controllers, which achieve perfect adaptation. Focusing on three biological network motif-based controllers, we demonstrate via simulation the efficacy of the proposed approach in combining linear system theories with nonlinear modelling, to design multiple gene circuits that could deliver perfect adaptation. Given the ubiquitous use of Hill functions in describing the dynamics of biological regulatory networks, we anticipate the proposed reverse engineering approach to benefit a wide range of systems and synthetic biology applications.

Information storage across a microbial community using universal RNA barcoding

Gene transfer can be studied using genetically encoded reporters or metagenomic sequencing but these methods are limited by sensitivity when used to monitor the mobile DNA host range in microbial communities. To record information about gene transfer across a wastewater microbiome, a synthetic catalytic RNA was used to barcode a highly conserved segment of ribosomal RNA (rRNA). By writing information into rRNA using a ribozyme and reading out native and modified rRNA using amplicon sequencing, we find that microbial community members from 20 taxonomic orders participate in plasmid conjugation with an Escherichia coli donor strain and observe differences in 16S rRNA barcode signal across amplicon sequence variants. Multiplexed rRNA barcoding using plasmids with pBBR1 or ColE1 origins of replication reveals differences in host range. This autonomous RNA-addressable modification provides information about gene transfer without requiring translation and will enable microbiome engineering across diverse ecological settings and studies of environmental controls on gene transfer and cellular uptake of extracellular materials.

Gene Regulation by a Kinetic Riboswitch with Negative Feedback Loop

Understanding the folding behaviors and cellular roles is important to fully illuminate functions of riboswitches in vivo. Since riboswitches act without the need for protein factors, RNA structure prediction methods are ideally suited for computationally analyzing their cellular activities. Here, a helix-based RNA folding theory is used to predict the cotranscriptional folding pathways of the flavin mononucleotide (FMN)-binding riboswitch from Bacillus subtilis (B. subtilis) under different conditions. The results show that the efficient function is determined by a balance between the transcription speed, pausing, and the binding rates of the metabolite. According to the predicted behaviors, a general kinetic model is established to investigate how the riboswitch couples sensing and regulatory functions to help bacteria respond to environmental changes at the system levels.

Anti-correlation of LacI association and dissociation rates observed in living cells

The rate at which transcription factors (TFs) bind their cognate sites has long been assumed to be limited by diffusion, and thus independent of binding site sequence. Here, we systematically test this assumption using cell-to-cell variability in gene expression as a window into the in vivo association and dissociation kinetics of the model transcription factor LacI. Using a stochastic model of the relationship between gene expression variability and binding kinetics, we performed single-cell gene expression measurements to infer association and dissociation rates for a set of 35 different LacI binding sites. We found that both association and dissociation rates differed significantly between binding sites, and moreover observed a clear anticorrelation between these rates across varying binding site strengths. These results contradict the long-standing hypothesis that TF binding site strength is primarily dictated by the dissociation rate, but may confer the evolutionary advantage that TFs do not get stuck in near-operator sequences while searching.

The global RNA-binding protein RbpB is a regulator of polysaccharide utilization in Bacteroides thetaiotaomicron

Paramount to human health, symbiotic bacteria in the gastrointestinal tract rely on the breakdown of complex polysaccharides to thrive in this sugar-deprived environment. Gut Bacteroides are metabolic generalists and deploy dozens of polysaccharide utilization loci (PULs) to forage diverse dietary and host-derived glycans. The expression of the multi-protein PUL complexes is tightly regulated at the transcriptional level. However, how PULs are orchestrated at translational level in response to the fluctuating levels of their cognate substrates is unknown. Here, we identify the RNA-binding protein RbpB and a family of noncoding RNAs as key players in post-transcriptional PUL regulation. We demonstrate that RbpB interacts with numerous cellular transcripts, including a paralogous noncoding RNA family comprised of 14 members, the FopS (family of paralogous sRNAs). Through a series of in-vitro and in-vivo assays, we reveal that FopS sRNAs repress the translation of SusC-like glycan transporters when substrates are limited-an effect antagonized by RbpB. Ablation of RbpB in Bacteroides thetaiotaomicron compromises colonization in the mouse gut in a diet-dependent manner. Together, this study adds to our understanding of RNA-coordinated metabolic control as an important factor contributing to the in-vivo fitness of predominant microbiota species in dynamic nutrient landscapes.

Candidatus Thiothrix phosphatis SCUT-1: A novel polyphosphate-accumulating organism abundant in the enhanced biological phosphorus removal system

A novel coccus Thiothrix-related polyphosphate-accumulating organism (PAO) was enriched in an acetate-fed enhanced biological phosphorus removal (EBPR) system. High EBPR performance was achieved for an extended period (>100 days). A high-quality draft genome (completeness 97.2 %, contamination 3.26 %) was retrieved, representing a novel Thiothrix species (with similarity<93.2 % to known Thiothrix species), and was denoted as 'Candidatus Thiothrix phosphatis SCUT-1'. Its acetate uptake rate (6.20 mmol C/g VSS/h) surpassed most Ca. Accumulibacter and known glycogen-accumulating organisms (GAOs), conferring their predominance in the acetate-fed system. Metatranscriptomic analysis suggested that Ca. Thiothrix phosphatis SCUT-1 employed both low- and high-affinity pathways for acetate activation, and both the conventional (PhaABC) pathway and the fatty acid β-oxidation pathway for PHA synthesis; additionally, a much more efficient FAD-dependent malate: quinone oxidoreductase (MQO) were encoded and employed than the traditional malate dehydrogenase (MDH) to oxidize malate to oxaloacetate in the TCA and glyoxylate cycle, collectively contributing to a higher acetate utilization and processing rate of this microorganism. Batch tests further demonstrated the versatile ability of this PAO in using VFA (acetate, propionate, and butyrate), lactate, amino acids (aspartate and glutamate), and glucose as carbon sources for EBPR, showing a partially overlapped but unique ecological niche of this microorganism comparing to Ca. Accumulibacter and known GAOs. A metabolic model was built for Ca. Thiothrix phosphatis SCUT-1 using the above-mentioned carbon sources for EBPR. Overall, this study represents the first comprehensive characterization of the physiology and metabolic characteristics of representative coccus Thiothrix-related PAOs, which are expected to provide new insights into PAO microbiology in EBPR systems.

The Escherichia coli ribB riboswitch senses flavin mononucleotide within a defined transcriptional window

Riboswitches are metabolite-binding RNA regulators that modulate gene expression at the levels of transcription and translation. One of the hallmarks of riboswitch regulation is that they undergo structural changes upon metabolite binding. While a lot of effort has been put to characterize how the metabolite is recognized by the riboswitch, there is still relatively little information regarding how ligand sensing is performed within a transcriptional context. Here, we study the ligand-dependent cotranscriptional folding of the FMN-sensing ribB riboswitch of Escherichia coli Using RNase H assays to study nascent ribB riboswitch transcripts, DNA probes targeting the P1 and sequestering stems indicate that FMN binding leads to the protection of these regions from RNase H cleavage, consistent with the riboswitch inhibiting translation initiation when bound to FMN. Our results show that ligand sensing is strongly affected by the position of elongating RNA polymerase, which is defining an FMN-binding transcriptional window that is bordered in its 3' extremity by a transcriptional pause site. Also, using successively overlapping DNA probes targeting a subdomain of the riboswitch, our data suggest the presence of a previously unsuspected helical region involving the 3' strand of the P1 stem. Our results show that this helical region is conserved across bacterial species, thus suggesting that this predicted structure, the anti*-P1 stem, is involved in the FMN-free conformation of the ribB riboswitch. Overall, our study further demonstrates that intricate folding strategies may be used by riboswitches to perform metabolite sensing during the transcriptional process.

Dynamics of transcription-coupled repair of cyclobutane pyrimidine dimers and (6-4) photoproducts in Escherichia coli

DNA repair processes modulate genotoxicity, mutagenesis, and adaption. Nucleotide excision repair removes bulky DNA damage, and in Escherichia coli, basal excision repair, carried out by UvrA, B, C, and D, with DNA PolI and DNA ligase, occurs genome-wide. In transcription-coupled repair (TCR), the Mfd protein targets template strand (TS) lesions that block RNA polymerase for accelerated repair by the basal repair enzymes. Accelerated repair is also seen with particular adducts. Notably, of the two major UV photoproducts, basal repair of (6-4) photoproducts [(6-4)PPs] is about 10× faster than repair of cyclobutane pyrimidine dimers (CPDs). To better understand repair prioritization in E. coli, we used XR-seq to measure TCR of UV photoproducts genome-wide. With CPDs, we found that TCR occurred at early time points, increased with transcription level, and was Mfd dependent; later, with completion of TS repair, nontranscribed strand (NTS) repair predominated. With (6-4)PP, when analyzing all genes, TCR was not observed; in fact, among the most highly transcribed genes, slightly more repair of (6-4)PPs in the NTS was evident. Thus, the very rapid basal repair of (6-4)PP in the NTS was faster than TCR of (6-4)PPs in the TS. Overall, TCR is of limited importance in (6-4)PP repair, and TCR of CPDs is limited to the TS of more highly transcribed genes. These results are consistent with the significant role of Mfd in mutagenesis and the modest effect of mfd deletion on UV survival and bear upon the response of E. coli to bulky DNA damage.

Exploring new dimensions of immune cell biology in Anopheles gambiae through genetic immunophenotyping

Mosquito immune cells, or hemocytes, are integral components of the innate immune responses that define vector competence. However, the lack of genetic resources has limited their characterization and our understanding of their functional roles in immune signaling. To overcome these challenges, we engineered transgenic Anopheles gambiae that express fluorescent proteins under the control of candidate hemocyte promoters. Following the characterization of five transgenic constructs through gene expression and microscopy-based approaches, we examine mosquito immune cell populations by leveraging advanced spectral imaging flow cytometry. Our results comprehensively map the composition of mosquito hemocytes, classifying them into twelve distinct populations based on size, granularity, ploidy, phagocytic capacity, and the expression of PPO6, SPARC, and LRIM15 genetic markers. Together, our novel use of morphological properties and genetic markers provides increased resolution into our understanding of mosquito hemocytes, highlighting the complexity and plasticity of these immune cell populations, while providing the foundation for deeper investigations into their roles in immunity and pathogen transmission.

Nonlinear classifiers for wet-neuromorphic computing using gene regulatory neural network

The gene regulatory network (GRN) of biological cells governs a number of key functionalities that enable them to adapt and survive through different environmental conditions. Close observation of the GRN shows that the structure and operational principles resemble an artificial neural network (ANN), which can pave the way for the development of wet-neuromorphic computing systems. Genes are integrated into gene-perceptrons with transcription factors (TFs) as input, where the TF concentration relative to half-maximal RNA concentration and gene product copy number influences transcription and translation via weighted multiplication before undergoing a nonlinear activation function. This process yields protein concentration as the output, effectively turning the entire GRN into a gene regulatory neural network (GRNN). In this paper, we establish nonlinear classifiers for molecular machine learning using the inherent sigmoidal nonlinear behavior of gene expression. The eigenvalue-based stability analysis, tailored to system parameters, confirms maximum-stable concentration levels, minimizing concentration fluctuations and computational errors. Given the significance of the stabilization phase in GRNN computing and the dynamic nature of the GRN, alongside potential changes in system parameters, we utilize the Lyapunov stability theorem for temporal stability analysis. Based on this GRN-to-GRNN mapping and stability analysis, three classifiers are developed utilizing two generic multilayer sub-GRNNs and a sub-GRNN extracted from the Escherichia coli GRN. Our findings also reveal the adaptability of different sub-GRNNs to suit different application requirements.

Diverse intrinsic properties shape transcript stability and stabilization in Mycolicibacterium smegmatis

Mycobacteria regulate transcript degradation to facilitate adaptation to environmental stress. However, the mechanisms underlying this regulation are unknown. Here we sought to gain understanding of the mechanisms controlling mRNA stability by investigating the transcript properties associated with variance in transcript stability and stress-induced transcript stabilization. We measured mRNA half-lives transcriptome-wide in Mycolicibacterium smegmatis in log phase growth and hypoxia-induced growth arrest. The transcriptome was globally stabilized in response to hypoxia, but transcripts of essential genes were generally stabilized more than those of non-essential genes. We then developed machine learning models that enabled us to identify the non-linear collective effect of a compendium of transcript properties on transcript stability and stabilization. We identified properties that were more predictive of half-life in log phase as well as properties that were more predictive in hypoxia, and many of these varied between leadered and leaderless transcripts. In summary, we found that transcript properties are differentially associated with transcript stability depending on both the transcript type and the growth condition. Our results reveal the complex interplay between transcript features and microenvironment that shapes transcript stability in mycobacteria.

Noise robustness and metabolic load determine the principles of central dogma regulation

The processes of gene expression are inherently stochastic, even for essential genes required for growth. How does the cell maximize fitness in light of noise? To answer this question, we build a mathematical model to explore the trade-off between metabolic load and growth robustness. The model provides insights for principles of central dogma regulation: Optimal protein expression levels for many genes are in vast overabundance. Essential genes are transcribed above a lower limit of one message per cell cycle. Gene expression is achieved by load balancing between transcription and translation. We present evidence that each of these regulatory principles is observed. These results reveal that robustness and metabolic load determine the global regulatory principles that govern gene expression processes, and these principles have broad implications for cellular function.

Unraveling RNA contribution to the molecular origins of bacterial surface-enhanced Raman spectroscopy (SERS) signals

Surface-enhanced Raman spectroscopy (SERS) is widely utilized in bacterial analyses, with the dominant SERS peaks attributed to purine metabolites released during sample preparation. Although adenosine triphosphate (ATP) and nucleic acids are potential molecular origins of these metabolites, research on their exact contributions remains limited. This study explored purine metabolite release from E. coli and RNA integrity following various sample preparation methods. Standard water washing generated dominant SERS signals within 10 s, a duration shorter than the anticipated RNA half-lives under starvation. Evaluating RNA integrity indicated that the most abundant ribosomal RNA species remained intact for hours post-washing, whereas messenger RNA and transfer RNA species degraded gradually. This suggests that bacterial SERS signatures observed after the typical washing step could originate from only a small fraction of endogenous purine-containing molecules. In contrast, acid depurination led to degradation of most RNA species, releasing about 40 times more purine derivatives than water washing. Mild heating also instigated the RNA degradation and released more purine derivatives than water washing. Notably, differences were also evident in the dominant SERS signals following these treatments. This work provides insights into SERS-based studies of purine metabolites released by bacteria and future development of methodologies.

Establishing a High-Yield Chloroplast Cell-Free System for Prototyping Genetic Parts

Plastid engineering offers the potential to carry multigene traits in plants; however, it requires reliable genetic parts to balance expression. The difficulty of chloroplast transformation and slow plant growth makes it challenging to build plants just to characterize genetic parts. To address these limitations, we developed a high-yield cell-free system from Nicotiana tabacum chloroplast extracts for prototyping genetic parts. Our cell-free system uses combined transcription and translation driven by T7 RNA polymerase and works with plasmid or linear template DNA. To develop our system, we optimized lysis, extract preparation procedures (e.g., runoff reaction, centrifugation, and dialysis), and the physiochemical reaction conditions. Our cell-free system can synthesize 34 ± 1 μg/mL luciferase in batch reactions and 60 ± 4 μg/mL in semicontinuous reactions. We apply our batch reaction system to test a library of 103 ribosome binding site (RBS) variants and rank them based on cell-free gene expression. We observe a 1300-fold dynamic range of luciferase expression when normalized by maximum mRNA expression, as assessed by the malachite green aptamer. We also find that the observed normalized gene expression in chloroplast extracts and the predictions made by the RBS Calculator are correlated. We anticipate that chloroplast cell-free systems will increase the speed and reliability of building genetic systems in plant chloroplasts for diverse applications.

Noise robustness and metabolic load determine the principles of central dogma regulation

The processes of gene expression are inherently stochastic, even for essential genes required for growth. How does the cell maximize fitness in light of noise? To answer this question, we build a mathematical model to explore the trade-off between metabolic load and growth robustness. The model predicts novel principles of central dogma regulation: Optimal protein expression levels for many genes are in vast overabundance. Essential genes are transcribed above a lower limit of one message per cell cycle. Gene expression is achieved by load balancing between transcription and translation. We present evidence that each of these novel regulatory principles is observed. These results reveal that robustness and metabolic load determine the global regulatory principles that govern gene expression processes, and these principles have broad implications for cellular function.

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.

Concept of Normativity in Multi-Omics Analysis of Axon Regeneration

Transcriptomes and proteomes can be normalized with a handful of RNAs or proteins (or their peptides), such as GAPDH, β-actin, RPBMS, and/or GAP43. Even with hundreds of standards, normalization cannot be achieved across different molecular mass ranges for small molecules, such as lipids and metabolites, due to the non-linearity of mass by charge ratio for even the smallest part of the spectrum. We define the amount (or range of amounts) of metabolites and/or lipids per a defined amount of a protein, consistently identified in all samples of a multiple-model organism comparison, as the normative level of that metabolite or lipid. The defined protein amount (or range) is a normalized value for one cohort of complete samples for which intrasample relative protein quantification is available. For example, the amount of citrate (a metabolite) per µg of aconitate hydratase (normalized protein amount) identified in the proteome is the normative level of citrate with aconitase. We define normativity as the amount of metabolites (or amount range) detected when compared to normalized protein levels. We use axon regeneration as an example to illustrate the need for advanced approaches to the normalization of proteins. Comparison across different pharmacologically induced axon regeneration mouse models entails the comparison of axon regeneration, studied at different time points in several models designed using different agents. For the normalization of the proteins across different pharmacologically induced models, we perform peptide doping (fixed amounts of known peptides) in each sample to normalize the proteome across the samples. We develop Regen V peptides, divided into Regen III (SEB, LLO, CFP) and II (HH4B, A1315), for pre- and post-extraction comparisons, performed with the addition of defined, digested peptides (bovine serum albumin tryptic digest) for protein abundance normalization beyond commercial labeled relative quantification (for example, 18-plex tandem mass tags). We also illustrate the concept of normativity by using this normalization technique on regenerative metabolome/lipidome profiles. As normalized protein amounts are different in different biological states (control versus axon regeneration), normative metabolite or lipid amounts are expected to be different for specific biological states. These concepts and standardization approaches are important for the integration of different datasets across different models of axon regeneration.

A library of reporters of the global regulators of gene expression in Escherichia coli

The topology of the transcription factor network (TFN) of Escherichia coli is far from uniform, with 22 global regulator (GR) proteins controlling one-third of all genes. So far, their production rates cannot be tracked by comparable fluorescent proteins. We developed a library of fluorescent reporters for 16 GRs for this purpose. Each consists of a single-copy plasmid coding for green fluorescent protein (GFP) fused to the full-length copy of the native promoter. We tracked their activity in exponential and stationary growth, as well as under weak and strong stresses. We show that the reporters have high sensitivity and specificity to all stresses tested and detect single-cell variability in transcription rates. Given the influence of GRs on the TFN, we expect that the new library will contribute to dissecting global transcriptional stress-response programs of E. coli. Moreover, the library can be invaluable in bioindustrial applications that tune those programs to, instead of cell growth, favor productivity while reducing energy consumption.IMPORTANCECells contain thousands of genes. Many genes are involved in the control of cellular activities. Some activities require a few hundred genes to run largely synchronous transcriptional programs. To achieve this, cells have evolved global regulator (GR) proteins that can influence hundreds of genes simultaneously. We have engineered a library of Escherichia coli strains to track the levels over time of these, phenotypically critical, GRs. Each strain has a single-copy plasmid coding for a fast-maturing green fluorescent protein whose transcription is controlled by a copy of the natural GR promoter. By allowing the tracking of GR levels, with sensitivity and specificity, this library should become of wide use in scientific research on bacterial gene expression (from molecular to synthetic biology) and, later, be used in applications in therapeutics and bioindustries.

Engineering an Escherichia coli based in vivo mRNA manufacturing platform

Synthetic mRNA is currently produced in standardized in vitro transcription systems. However, this one-size-fits-all approach has associated drawbacks in supply chain shortages, high reagent costs, complex product-related impurity profiles, and limited design options for molecule-specific optimization of product yield and quality. Herein, we describe for the first time development of an in vivo mRNA manufacturing platform, utilizing an Escherichia coli cell chassis. Coordinated mRNA, DNA, cell and media engineering, primarily focussed on disrupting interactions between synthetic mRNA molecules and host cell RNA degradation machinery, increased product yields >40-fold compared to standard "unengineered" E. coli expression systems. Mechanistic dissection of cell factory performance showed that product mRNA accumulation levels approached theoretical limits, accounting for ~30% of intracellular total RNA mass, and that this was achieved via host-cell's reallocating biosynthetic capacity away from endogenous RNA and cell biomass generation activities. We demonstrate that varying sized functional mRNA molecules can be produced in this system and subsequently purified. Accordingly, this study introduces a new mRNA production technology, expanding the solution space available for mRNA manufacturing.

Contribution of different macromolecules to the diffusion of a 40 nm particle in Escherichia coli

Due to the high concentration of proteins, nucleic acids, and other macromolecules, the bacterial cytoplasm is typically described as a crowded environment. However, the extent to which each of these macromolecules individually affects the mobility of macromolecular complexes, and how this depends on growth conditions, is presently unclear. In this study, we sought to quantify the crowding experienced by an exogenous 40 nm fluorescent particle in the cytoplasm of E. coli under different growth conditions. By performing single-particle tracking measurements in cells selectively depleted of DNA and/or mRNA, we determined the contribution to crowding of mRNA, DNA, and remaining cellular components, i.e., mostly proteins and ribosomes. To estimate this contribution to crowding, we quantified the difference of the particle's diffusion coefficient in conditions with and without those macromolecules. We found that the contributions of the three classes of components were of comparable magnitude, being largest in the case of proteins and ribosomes. We further found that the contributions of mRNA and DNA to crowding were significantly larger than expected based on their volumetric fractions alone. Finally, we found that the crowding contributions change only slightly with the growth conditions. These results reveal how various cellular components partake in crowding of the cytoplasm and the consequences this has for the mobility of large macromolecular complexes.

Selectively advantageous instability in biotic and pre-biotic systems and implications for evolution and aging

Rules of biology typically involve conservation of resources. For example, common patterns such as hexagons and logarithmic spirals require minimal materials, and scaling laws involve conservation of energy. Here a relationship with the opposite theme is discussed, which is the selectively advantageous instability (SAI) of one or more components of a replicating system, such as the cell. By increasing the complexity of the system, SAI can have benefits in addition to the generation of energy or the mobilization of building blocks. SAI involves a potential cost to the replicating system for the materials and/or energy required to create the unstable component, and in some cases, the energy required for its active degradation. SAI is well-studied in cells. Short-lived transcription and signaling factors enable a rapid response to a changing environment, and turnover is critical for replacement of damaged macromolecules. The minimal gene set for a viable cell includes proteases and a nuclease, suggesting SAI is essential for life. SAI promotes genetic diversity in several ways. Toxin/antitoxin systems promote maintenance of genes, and SAI of mitochondria facilitates uniparental transmission. By creating two distinct states, subject to different selective pressures, SAI can maintain genetic diversity. SAI of components of synthetic replicators favors replicator cycling, promoting emergence of replicators with increased complexity. Both classical and recent computer modeling of replicators reveals SAI. SAI may be involved at additional levels of biological organization. In summary, SAI promotes replicator genetic diversity and reproductive fitness, and may promote aging through loss of resources and maintenance of deleterious alleles.

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.

Ribosome profiling reveals downregulation of UMP biosynthesis as the major early response to phage infection

Bacteria have evolved diverse defense mechanisms to counter bacteriophage attacks. Genetic programs activated upon infection characterize phage-host molecular interactions and ultimately determine the outcome of the infection. In this study, we applied ribosome profiling to monitor protein synthesis during the early stages of sk1 bacteriophage infection in Lactococcus cremoris. Our analysis revealed major changes in gene expression within 5 minutes of sk1 infection. Notably, we observed a specific and severe downregulation of several pyr operons which encode enzymes required for uridine monophosphate biosynthesis. Consistent with previous findings, this is likely an attempt of the host to starve the phage of nucleotides it requires for propagation. We also observed a gene expression response that we expect to benefit the phage. This included the upregulation of 40 ribosome proteins that likely increased the host's translational capacity, concurrent with a downregulation of genes that promote translational fidelity (lepA and raiA). In addition to the characterization of host-phage gene expression responses, the obtained ribosome profiling data enabled us to identify two putative recoding events as well as dozens of loci currently annotated as pseudogenes that are actively translated. Furthermore, our study elucidated alterations in the dynamics of the translation process, as indicated by time-dependent changes in the metagene profile, suggesting global shifts in translation rates upon infection. Additionally, we observed consistent modifications in the ribosome profiles of individual genes, which were apparent as early as 2 minutes post-infection. The study emphasizes our ability to capture rapid alterations of gene expression during phage infection through ribosome profiling.

IMPORTANCE

The ribosome profiling technology has provided invaluable insights for understanding cellular translation and eukaryotic viral infections. However, its potential for investigating host-phage interactions remains largely untapped. Here, we applied ribosome profiling to Lactococcus cremoris cultures infected with sk1, a major infectious agent in dairy fermentation processes. This revealed a profound downregulation of genes involved in pyrimidine nucleotide synthesis at an early stage of phage infection, suggesting an anti-phage program aimed at restricting nucleotide availability and, consequently, phage propagation. This is consistent with recent findings and contributes to our growing appreciation for the role of nucleotide limitation as an anti-viral strategy. In addition to capturing rapid alterations in gene expression levels, we identified translation occurring outside annotated regions, as well as signatures of non-standard translation mechanisms. The gene profiles revealed specific changes in ribosomal densities upon infection, reflecting alterations in the dynamics of the translation process.

Cross-evaluation of E. coli's operon structures via a whole-cell model suggests alternative cellular benefits for low- versus high-expressing operons

Many bacteria use operons to coregulate genes, but it remains unclear how operons benefit bacteria. We integrated E. coli's 788 polycistronic operons and 1,231 transcription units into an existing whole-cell model and found inconsistencies between the proposed operon structures and the RNA-seq read counts that the model was parameterized from. We resolved these inconsistencies through iterative, model-guided corrections to both datasets, including the correction of RNA-seq counts of short genes that were misreported as zero by existing alignment algorithms. The resulting model suggested two main modes by which operons benefit bacteria. For 86% of low-expression operons, adding operons increased the co-expression probabilities of their constituent proteins, whereas for 92% of high-expression operons, adding operons resulted in more stable expression ratios between the proteins. These simulations underscored the need for further experimental work on how operons reduce noise and synchronize both the expression timing and the quantity of constituent genes. A record of this paper's transparent peer review process is included in the supplemental information.

The dynamic-process characterization and prediction of synthetic gene circuits by dynamic delay model

Differential equation models are widely used to describe genetic regulations, predict multicomponent regulatory circuits, and provide quantitative insights. However, it is still challenging to quantitatively link the dynamic behaviors with measured parameters in synthetic circuits. Here, we propose a dynamic delay model (DDM) which includes two simple parts: the dynamic determining part and the doses-related steady-state-determining part. The dynamic determining part is usually supposed as the delay time but without a clear formula. For the first time, we give the detail formula of the dynamic determining function and provide a method for measuring all parameters of synthetic elements (include 8 activators and 5 repressors) by microfluidic system. Three synthetic circuits were built to show that the DDM can notably improve the prediction accuracy and can be used in various synthetic biology applications.

Repurposing the mammalian RNA-binding protein Musashi-1 as an allosteric translation repressor in bacteria

The RNA recognition motif (RRM) is the most common RNA-binding protein domain identified in nature. However, RRM-containing proteins are only prevalent in eukaryotic phyla, in which they play central regulatory roles. Here, we engineered an orthogonal post-transcriptional control system of gene expression in the bacterium Escherichia coli with the mammalian RNA-binding protein Musashi-1, which is a stem cell marker with neurodevelopmental role that contains two canonical RRMs. In the circuit, Musashi-1 is regulated transcriptionally and works as an allosteric translation repressor thanks to a specific interaction with the N-terminal coding region of a messenger RNA and its structural plasticity to respond to fatty acids. We fully characterized the genetic system at the population and single-cell levels showing a significant fold change in reporter expression, and the underlying molecular mechanism by assessing the in vitro binding kinetics and in vivo functionality of a series of RNA mutants. The dynamic response of the system was well recapitulated by a bottom-up mathematical model. Moreover, we applied the post-transcriptional mechanism engineered with Musashi-1 to specifically regulate a gene within an operon, implement combinatorial regulation, and reduce protein expression noise. This work illustrates how RRM-based regulation can be adapted to simple organisms, thereby adding a new regulatory layer in prokaryotes for translation control.

On the ever-growing functional versatility of the CRISPR-Cas13 system

CRISPR-Cas systems evolved in prokaryotes to implement a powerful antiviral immune response as a result of sequence-specific targeting by ribonucleoproteins. One of such systems consists of an RNA-guided RNA endonuclease, known as CRISPR-Cas13. In very recent years, this system is being repurposed in different ways in order to decipher and engineer gene expression programmes. Here, we discuss the functional versatility of the CRISPR-Cas13 system, which includes the ability for RNA silencing, RNA editing, RNA tracking, nucleic acid detection and translation regulation. This functional palette makes the CRISPR-Cas13 system a relevant tool in the broad field of systems and synthetic biology.

A conserved protein inhibitor brings under check the activity of RNase E in cyanobacteria

The bacterial ribonuclease RNase E plays a key role in RNA metabolism. Yet, with a large substrate spectrum and poor substrate specificity, its activity must be well controlled under different conditions. Only a few regulators of RNase E are known, limiting our understanding on posttranscriptional regulatory mechanisms in bacteria. Here we show that, RebA, a protein universally present in cyanobacteria, interacts with RNase E in the cyanobacterium Anabaena PCC 7120. Distinct from those known regulators of RNase E, RebA interacts with the catalytic region of RNase E, and suppresses the cleavage activities of RNase E for all tested substrates. Consistent with the inhibitory function of RebA on RNase E, depletion of RNase E and overproduction of RebA caused formation of elongated cells, whereas the absence of RebA and overproduction of RNase E resulted in a shorter-cell phenotype. We further showed that the morphological changes caused by altered levels of RNase E or RebA are dependent on their physical interaction. The action of RebA represents a new mechanism, potentially conserved in cyanobacteria, for RNase E regulation. Our findings provide insights into the regulation and the function of RNase E, and demonstrate the importance of balanced RNA metabolism in bacteria.

Protozoan predation enhances stress resistance and antibiotic tolerance in Burkholderia cenocepacia by triggering the SOS response

Bacterivorous protists are thought to serve as training grounds for bacterial pathogens by subjecting them to the same hostile conditions that they will encounter in the human host. Bacteria that survive intracellular digestion exhibit enhanced virulence and stress resistance after successful passage through protozoa but the underlying mechanisms are unknown. Here we show that the opportunistic pathogen Burkholderia cenocepacia survives phagocytosis by ciliates found in domestic and hospital sink drains, and viable bacteria are expelled packaged in respirable membrane vesicles with enhanced resistance to oxidative stress, desiccation, and antibiotics, thereby contributing to pathogen dissemination in the environment. Reactive oxygen species generated within the protozoan phagosome promote the formation of persisters tolerant to ciprofloxacin by activating the bacterial SOS response. In addition, we show that genes encoding antioxidant enzymes are upregulated during passage through ciliates increasing bacterial resistance to oxidative radicals. We prove that suppression of the SOS response impairs bacterial intracellular survival and persister formation within protists. This study highlights the significance of protozoan food vacuoles as niches that foster bacterial adaptation in natural and built environments and suggests that persister switch within phagosomes may be a widespread phenomenon in bacteria surviving intracellular digestion.

Analysis of sRNAs and Their mRNA Targets in Sinorhizobium meliloti: Focus on Half-Life Determination

Regulation of gene expression at the level of RNA and/or by regulatory RNA is an integral part of the regulatory circuits in all living cells. In bacteria, transcription and translation can be coupled, enabling regulation by transcriptional attenuation, a mechanism based on mutually exclusive structures in nascent mRNA. Transcriptional attenuation gives rise to small RNAs that are well suited to act in trans by either base pairing or ligand binding. Examples of 5'-UTR-derived sRNAs in the alpha-proteobacterium Sinorhizobium meliloti are the sRNA rnTrpL of the tryptophan attenuator and SAM-II riboswitch sRNAs. Analyses addressing RNA-based gene regulation often include measurements of steady-state levels and of half-lives of specific sRNAs and mRNAs. Using such measurements, recently we have shown that the tryptophan attenuator responds to translation inhibition by tetracycline and that SAM-II riboswitches stabilize RNA. Here we discuss our experience in using alternative RNA purification methods for analysis of sRNA and mRNA of S. meliloti. Additionally, we show that other translational inhibitors (besides tetracycline) also cause attenuation giving rise to the rnTrpL sRNA. Furthermore, we discuss the importance of considering RNA stability changes under different conditions and describe in detail a robust and fast method for mRNA half-life determination. The latter includes rifampicin treatment, RNA isolation using commercially available columns, and mRNA analysis by reverse transcription followed by quantitative PCR (RT-qPCR). The latter can be performed as a one-step procedure or in a strand-specific manner using the same commercial kit and a spike-in transcript as a reference.

Decoding stoichiometric protein synthesis in E. coli through translation rate parameters

E. coli is one of the most widely used organisms for understanding the principles of cellular and molecular genetics. However, we are yet to understand the origin of several experimental observations related to the regulation of gene expression in E. coli. One of the prominent examples in this context is the proportional synthesis in multiprotein complexes where all of their obligate subunits are produced in proportion to their stoichiometry. In this work, by combining the next-generation sequencing data with the stochastic simulations of protein synthesis, we explain the origin of proportional protein synthesis in multicomponent complexes. We find that the estimated initiation rates for the translation of all subunits in those complexes are proportional to their stoichiometry. This constraint on protein synthesis kinetics enforces proportional protein synthesis without requiring any feedback mechanism. We also find that the translation initiation rates in E. coli are influenced by the coding sequence length and the enrichment of A and C nucleotides near the start codon. Thus, this study rationalizes the role of conserved and nonrandom features of genes in regulating the translation kinetics and unravels a key principle of the regulation of protein synthesis.

Frequency of change determines effectiveness of microbial response strategies

Nature challenges microbes with change at different frequencies and demands an effective response for survival. Here, we used controlled laboratory experiments to investigate the effectiveness of different response strategies, such as post-translational modification, transcriptional regulation, and specialized versus adaptable metabolisms. For this, we inoculated replicated chemostats with an enrichment culture obtained from sulfidic stream microbiomes 16 weeks prior. The chemostats were submitted to alternatingly oxic and anoxic conditions at three frequencies, with periods of 1, 4 and 16 days. The microbial response was recorded with 16S rRNA gene amplicon sequencing, shotgun metagenomics, transcriptomics and proteomics. Metagenomics resolved provisional genomes of all abundant bacterial populations, mainly affiliated with Proteobacteria and Bacteroidetes. Almost all these populations maintained a steady growth rate under both redox conditions at all three frequencies of change. Our results supported three conclusions: (1) Oscillating oxic/anoxic conditions selected for generalistic species, rather than species specializing in only a single condition. (2) A high frequency of change selected for strong codon usage bias. (3) Alignment of transcriptomes and proteomes required multiple generations and was dependent on a low frequency of change.

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.

Proteome efficiency of metabolic pathways in Escherichia coli increases along the nutrient flow

IMPORTANCE

Protein translation is the most expensive cellular process in fast-growing bacteria, and efficient proteome usage should thus be under strong natural selection. However, recent studies show that a considerable part of the proteome is unneeded for instantaneous cell growth in Escherichia coli. We still lack a systematic understanding of how this excess proteome is distributed across different pathways as a function of the growth conditions. We estimated the minimal required proteome across growth conditions in E. coli and compared the predictions with experimental data. We found that the proteome allocated to the most expensive internal pathways, including translation and the synthesis of amino acids and cofactors, is near the minimally required levels. In contrast, transporters and central carbon metabolism show much higher proteome levels than the predicted minimal abundance. Our analyses show that the proteome fraction unneeded for instantaneous cell growth decreases along the nutrient flow in E. coli.

Physical modeling of ribosomes along messenger RNA: Estimating kinetic parameters from ribosome profiling experiments using a ballistic model

Gene expression is the synthesis of proteins from the information encoded on DNA. One of the two main steps of gene expression is the translation of messenger RNA (mRNA) into polypeptide sequences of amino acids. Here, by taking into account mRNA degradation, we model the motion of ribosomes along mRNA with a ballistic model where particles advance along a filament without excluded volume interactions. Unidirectional models of transport have previously been used to fit the average density of ribosomes obtained by the experimental ribo-sequencing (Ribo-seq) technique in order to obtain the kinetic rates. The degradation rate is not, however, accounted for and experimental data from different experiments are needed to have enough parameters for the fit. Here, we propose an entirely novel experimental setup and theoretical framework consisting in splitting the mRNAs into categories depending on the number of ribosomes from one to four. We solve analytically the ballistic model for a fixed number of ribosomes per mRNA, study the different regimes of degradation, and propose a criterion for the quality of the inverse fit. The proposed method provides a high sensitivity to the mRNA degradation rate. The additional equations coming from using the monosome (single ribosome) and polysome (arbitrary number) ribo-seq profiles enable us to determine all the kinetic rates in terms of the experimentally accessible mRNA degradation rate.

Allosteric activation of RhlB by RNase E induces partial duplex opening in substrate RNA

The E. coli DEAD-Box helicase RhlB is responsible for ATP-dependent unwinding of structured mRNA to facilitate RNA degradation by the protein complex degradosome. The allosteric interaction with complex partner RNase E is necessary to stimulate both, RhlB's ATPase and RNA unwinding activity to levels comparable with other DEAD-Box helicases. However, the structural changes of the helicase RhlB induced by binding of RNase E have not been characterized and how those lead to increased reaction rates has remained unclear. We investigated the origin of this activation for RNA substrates with different topologies. Using NMR spectroscopy and an RNA centered approach, we could show that RNase E binding increases the affinity of RhlB towards a subset of RNA substrates, which leads to increased ATP turnover rates. Most strikingly, our studies revealed that in presence of RNase E (694-790) RhlB induces a conformational change in an RNA duplex with 5'- overhang even in absence of ATP, leading to partial duplex opening. Those results indicate a unique and novel activation mode of RhlB among DEAD-Box helicases, as ATP binding is thought to be an essential prerequisite for RNA unwinding.

The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists: a minimum transcription level of one message per cell cycle is conserved between three model organisms: Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists: a minimum transcription level of one message per cell cycle is conserved between three model organisms: Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

Strain-specific quorum-sensing responses determine virulence properties in Vibrio anguillarum

Bacterial populations communicate using quorum-sensing (QS) molecules and switch on QS regulation to engage in coordinated behaviour such as biofilm formation or virulence. The marine fish pathogen Vibrio anguillarum harbours several QS systems, and our understanding of its QS regulation is still fragmentary. Here, we identify the VanT-QS regulon and explore the diversity and trajectory of traits under QS regulation in Vibrio anguillarum through comparative transcriptomics of two wildtype strains and their corresponding mutants artificially locked in QS-on (ΔvanO) or QS-off (ΔvanT) states. Intriguingly, the two wildtype populations showed different QS responses to cell density changes and operated primarily in the QS-on and QS-off spectrum, respectively. Examining 27 V. anguillarum strains revealed that ~11% were QS-negative, and GFP-reporter measurements of nine QS-positive strains revealed a highly strain-specific nature of the QS responses. We showed that QS controls a plethora of genes involved in processes such as central metabolism, biofilm formation, competence, T6SS, and virulence properties in V. anguillarum, with large strain-specific differences. Moreover, we demonstrated that the QS state is an important driver of virulence towards fish larvae in one of two V. anguillarum strains. We speculate that infections by mixed-strain communities spanning diverse QS strategies optimize the infection efficiency of the pathogen.

Nearly maximal information gain due to time integration in central dogma reactions

Living cells process information about their environment through the central dogma processes of transcription and translation, which drive the cellular response to stimuli. Here, we study the transfer of information from environmental input to the transcript and protein expression levels. Evaluation of both experimental and analogous simulation data reveals that transcription and translation are not two simple information channels connected in series. Instead, we demonstrate that the central dogma reactions often create a time-integrating information channel, where the translation channel receives and integrates multiple outputs from the transcription channel. This information channel model of the central dogma provides new information-theoretic selection criteria for the central dogma rate constants. Using the data for four well-studied species we show that their central dogma rate constants achieve information gain because of time integration while also keeping the loss because of stochasticity in translation relatively low (<0.5 bits).

Understanding spatiotemporal coupling of gene expression using single molecule RNA imaging technologies

Across all kingdoms of life, gene regulatory mechanisms underlie cellular adaptation to ever-changing environments. Regulation of gene expression adjusts protein synthesis and, in turn, cellular growth. Messenger RNAs are key molecules in the process of gene expression. Our ability to quantitatively measure mRNA expression in single cells has improved tremendously over the past decades. This revealed an unexpected coordination between the steps that control the life of an mRNA, from transcription to degradation. Here, we provide an overview of the state-of-the-art imaging approaches for measurement and quantitative understanding of gene expression, starting from the early visualizations of single genes by electron microscopy to current fluorescence-based approaches in single cells, including live-cell RNA-imaging approaches to FISH-based spatial transcriptomics across model organisms. We also highlight how these methods have shaped our current understanding of the spatiotemporal coupling between transcriptional and post-transcriptional events in prokaryotes. We conclude by discussing future challenges of this multidisciplinary field.Abbreviations: mRNA: messenger RNA; rRNA: ribosomal rDNA; tRNA: transfer RNA; sRNA: small RNA; FISH: fluorescence in situ hybridization; RNP: ribonucleoprotein; smFISH: single RNA molecule FISH; smiFISH: single molecule inexpensive FISH; HCR-FISH: Hybridization Chain-Reaction-FISH; RCA: Rolling Circle Amplification; seqFISH: Sequential FISH; MERFISH: Multiplexed error robust FISH; UTR: Untranslated region; RBP: RNA binding protein; FP: fluorescent protein; eGFP: enhanced GFP, MCP: MS2 coat protein; PCP: PP7 coat protein; MB: Molecular beacons; sgRNA: single guide RNA.

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.

Unraveling the small proteome of the plant symbiont Sinorhizobium meliloti by ribosome profiling and proteogenomics

The soil-dwelling plant symbiont Sinorhizobium meliloti is a major model organism of Alphaproteobacteria. Despite numerous detailed OMICS studies, information about small open reading frame (sORF)-encoded proteins (SEPs) is largely missing, because sORFs are poorly annotated and SEPs are hard to detect experimentally. However, given that SEPs can fulfill important functions, identification of translated sORFs is critical for analyzing their roles in bacterial physiology. Ribosome profiling (Ribo-seq) can detect translated sORFs with high sensitivity, but is not yet routinely applied to bacteria because it must be adapted for each species. Here, we established a Ribo-seq procedure for S. meliloti 2011 based on RNase I digestion and detected translation for 60% of the annotated coding sequences during growth in minimal medium. Using ORF prediction tools based on Ribo-seq data, subsequent filtering, and manual curation, the translation of 37 non-annotated sORFs with ≤ 70 amino acids was predicted with confidence. The Ribo-seq data were supplemented by mass spectrometry (MS) analyses from three sample preparation approaches and two integrated proteogenomic search database (iPtgxDB) types. Searches against standard and 20-fold smaller Ribo-seq data-informed custom iPtgxDBs confirmed 47 annotated SEPs and identified 11 additional novel SEPs. Epitope tagging and Western blot analysis confirmed the translation of 15 out of 20 SEPs selected from the translatome map. Overall, by combining MS and Ribo-seq approaches, the small proteome of S. meliloti was substantially expanded by 48 novel SEPs. Several of them are part of predicted operons and/or are conserved from Rhizobiaceae to Bacteria, suggesting important physiological functions.

Design of microaerobically inducible miniR1 plasmids

Plasmid DNA manufacture is an essential step to produce gene therapy agents and next-generation vaccines. However, little attention has been paid toward developing alternative replicons that can be coupled with large-scale production conditions. Our results demonstrate that the miniR1 replicon can be efficiently induced by oxygen limitation when a copy of the regulatory protein RepA under control of a microaerobic promoter is used. The results are potentially attractive for industrial applications.

tRNAs Are Stable After All: Pitfalls in Quantification of tRNA from Starved Escherichia coli Cultures Exposed by Validation of RNA Purification Methods

tRNAs and ribosomal RNAs are often considered stable RNAs. In contrast to this view, we recently proposed that tRNAs are degraded during amino acid starvation and drug-induced transcription inhibition. However, reevaluation of our experimental approach revealed that common RNA extraction methods suffer from alarming extraction and size biases that can lead to gross underestimation of RNA levels in starved Escherichia coli populations. Quantification of tRNAs suffers additional biases due to differing fractions of tRNAs with base modifications in growing versus starved bacteria. Applying an improved methodology, we measured tRNA levels after starvation for amino acids, glucose, phosphate, or ammonium and transcription inhibition by rifampicin. We report that tRNA levels remain largely unaffected in all tested conditions, including several days of starvation. This confirms that tRNAs are remarkably stable RNAs and serves as a cautionary tale about quantification of RNA from cells cultured outside the steady-state growth regime. rRNA, conversely, is extensively degraded during starvation. Thus, E. coli downregulates the translation machinery in response to starvation by reducing the ribosome pool through rRNA degradation, while a high concentration of tRNAs available to supply amino acids to the remaining ribosomes is maintained. IMPORTANCE We show that E. coli tRNAs are remarkably stable during several days of nutrient starvation, although rRNA is degraded extensively under these conditions. The levels of these two major RNA classes are considered to be strongly coregulated at the level of transcription. We demonstrate that E. coli can control the ratio of tRNAs per ribosome under starvation by means of differential degradation rates. The question of tRNA stability in stressed E. coli cells has become subject to debate. Our in-depth analysis of RNA quantification methods reveals hidden technical pitfalls at every step of the analysis, from RNA extraction to target detection and normalization. Most importantly, starved E. coli populations were more resilient to RNA extraction than unstarved populations. The current results underscore that the seemingly trivial task of quantifying an abundant RNA species is not straightforward for cells cultured outside the exponential growth regime.

Staying below the Radar: Unraveling a New Family of Ubiquitous "Cryptic" Non-Tailed Temperate Vibriophages and Implications for Their Bacterial Hosts

Bacteriophages are the most abundant biological entities in the oceans and play key roles in bacterial activity, diversity and evolution. While extensive research has been conducted on the role of tailed viruses (Class: Caudoviricetes), very little is known about the distribution and functions of the non-tailed viruses (Class: Tectiliviricetes). The recent discovery of the lytic Autolykiviridae family demonstrated the potential importance of this structural lineage, emphasizing the need for further exploration of the role of this group of marine viruses. Here, we report the novel family of temperate phages under the class of Tectiliviricetes, which we propose to name "Asemoviridae" with phage NO16 as a main representative. These phages are widely distributed across geographical regions and isolation sources and found inside the genomes of at least 30 species of Vibrio, in addition to the original V. anguillarum isolation host. Genomic analysis identified dif-like sites, suggesting that NO16 prophages recombine with the bacterial genome based on the XerCD site-specific recombination mechanism. The interactions between the NO16 phage and its V. anguillarum host were linked to cell density and phage-host ratio. High cell density and low phage predation levels were shown to favor the temperate over the lytic lifestyle for NO16 viruses, and their spontaneous induction rate was highly variable between different V. anguillarum lysogenic strains. NO16 prophages coexist with the V. anguillarum host in a mutualistic interaction by rendering fitness properties to the host, such as increased virulence and biofilm formation through lysogenic conversion, likely contributing to their global distribution.

Relaxed Cleavage Specificity of Hyperactive Variants of Escherichia coli RNase E on RNA I

RNase E is an essential enzyme in Escherichia coli. The cleavage site of this single-stranded specific endoribonuclease is well-characterized in many RNA substrates. Here, we report that the upregulation of RNase E cleavage activity by a mutation that affects either RNA binding (Q36R) or enzyme multimerization (E429G) was accompanied by relaxed cleavage specificity. Both mutations led to enhanced RNase E cleavage in RNA I, an antisense RNA of ColE1-type plasmid replication, at a major site and other cryptic sites. Expression of a truncated RNA I with a major RNase E cleavage site deletion at the 5'-end (RNA I_-5) resulted in an approximately twofold increase in the steady-state levels of RNA I_-5 and the copy number of ColE1-type plasmid in E. coli cells expressing wild-type or variant RNase E compared to those expressing RNA I. These results indicate that RNA I_-5 does not efficiently function as an antisense RNA despite having a triphosphate group at the 5'-end, which protects the RNA from ribonuclease attack. Our study suggests that increased cleavage rates of RNase E lead to relaxed cleavage specificity on RNA I and the inability of the cleavage product of RNA I as an antisense regulator in vivo does not stem from its instability by having 5'-monophosphorylated end.

Escherichia coli protein synthesis is limited by mRNA availability rather than ribosomal capacity during phosphate starvation

Protein synthesis is the most energetically costly process in the cell. Consequently, it is a tightly regulated process, and regulation of the resources allocated to the protein synthesis machinery is at the heart of bacterial growth optimization theory. However, the molecular mechanisms that result in dynamic downregulation of protein synthesis in response to nutrient starvation are not well described. Here, we first quantify the Escherichia coli response to phosphate starvation at the level of accumulation rates for protein, RNA and DNA. Escherichia coli maintains a low level of protein synthesis for hours after the removal of phosphate while the RNA contents decrease, primarily as a consequence of ribosomal RNA degradation combined with a reduced RNA synthesis rate. To understand the molecular basis for the low protein synthesis rate of phosphate-starved cells, template mRNA for translation was overproduced in the form of a highly induced long-lived mRNA. Remarkably, starved cells increased the rate of protein synthesis and reduced the rate of ribosomal RNA degradation upon mRNA induction. These observations suggest that protein synthesis in phosphate-starved cells is primarily limited by the availability of template, and does not operate at the maximum capacity of the ribosomes. We suggest that mRNA limitation is an adaptive response to phosphate starvation that prevents the deleterious consequences of overcommitting resources to protein synthesis. Moreover, our results support the model that degradation of ribosomal RNA occurs as a consequence of the availability of idle ribosomal subunits.