Free RNA polymerase and modeling global transcription in Escherichia coli

Recycling of bacterial RNA polymerase by the Swi2/Snf2 ATPase RapA

Free-living bacteria have regulatory systems that can quickly reprogram gene transcription in response to changes in the cellular environment. The RapA ATPase, a prokaryotic homolog of the eukaryotic Swi2/Snf2 chromatin remodeling complex, may facilitate such reprogramming, but the mechanisms by which it does so are unclear. We used multiwavelength single-molecule fluorescence microscopy in vitro to examine RapA function in the Escherichia coli transcription cycle. In our experiments, RapA at <5 nM concentration did not appear to alter transcription initiation, elongation, or intrinsic termination. Instead, we directly observed a single RapA molecule bind specifically to the kinetically stable post termination complex (PTC)-consisting of core RNA polymerase (RNAP)-bound sequence nonspecifically to double-stranded DNA-and efficiently remove RNAP from DNA within seconds in an ATP-hydrolysis-dependent reaction. Kinetic analysis elucidates the process through which RapA locates the PTC and the key mechanistic intermediates that bind and hydrolyze ATP. This study defines how RapA participates in the transcription cycle between termination and initiation and suggests that RapA helps set the balance between global RNAP recycling and local transcription reinitiation in proteobacterial genomes.

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.

Recycling of Bacterial RNA Polymerase by the Swi2/Snf2 ATPase RapA.. [DOI: 10.1101/2023.03.22.533849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

Free-living bacteria have regulatory systems that can quickly reprogram gene transcription in response to changes in cellular environment. The RapA ATPase, a prokaryotic homolog of the eukaryote Swi2/Snf2 chromatin remodeling complex, may facilitate such reprogramming, but the mechanisms by which it does so is unclear. We used multi-wavelength single-molecule fluorescence microscopy in vitro to examine RapA function in theE. colitranscription cycle. In our experiments, RapA at < 5 nM concentration did not appear to alter transcription initiation, elongation, or intrinsic termination. Instead, we directly observed a single RapA molecule bind specifically to the kinetically stable post-termination complex (PTC) -- consisting of core RNA polymerase (RNAP) bound to dsDNA -- and efficiently remove RNAP from DNA within seconds in an ATP-hydrolysis-dependent reaction. Kinetic analysis elucidates the process through which RapA locates the PTC and the key mechanistic intermediates that bind and hydrolyze ATP. This study defines how RapA participates in the transcription cycle between termination and initiation and suggests that RapA helps set the balance between global RNAP recycling and local transcription re-initiation in proteobacterial genomes.

SIGNIFICANCE

RNA synthesis is an essential conduit of genetic information in all organisms. After transcribing an RNA, the bacterial RNA polymerase (RNAP) must be reused to make subsequent RNAs, but the steps that enable RNAP reuse are unclear. We directly observed the dynamics of individual molecules of fluorescently labeled RNAP and the enzyme RapA as they colocalized with DNA during and after RNA synthesis. Our studies show that RapA uses ATP hydrolysis to remove RNAP from DNA after the RNA is released from RNAP and reveal essential features of the mechanism by which this removal occurs. These studies fill in key missing pieces in our current understanding of the events that occur after RNA is released and that enable RNAP reuse.

Rapid modeling of experimental molecular kinetics with simple electronic circuits instead of with complex differential equations

Kinetic modeling has relied on using a tedious number of mathematical equations to describe molecular kinetics in interacting reactions. The long list of differential equations with associated abstract variables and parameters inevitably hinders readers’ easy understanding of the models. However, the mathematical equations describing the kinetics of biochemical reactions can be exactly mapped to the dynamics of voltages and currents in simple electronic circuits wherein voltages represent molecular concentrations and currents represent molecular fluxes. For example, we theoretically derive and experimentally verify accurate circuit models for Michaelis-Menten kinetics. Then, we show that such circuit models can be scaled via simple wiring among circuit motifs to represent more and arbitrarily complex reactions. Hence, we can directly map reaction networks to equivalent circuit schematics in a rapid, quantitatively accurate, and intuitive fashion without needing mathematical equations. We verify experimentally that these circuit models are quantitatively accurate. Examples include 1) different mechanisms of competitive, noncompetitive, uncompetitive, and mixed enzyme inhibition, important for understanding pharmacokinetics; 2) product-feedback inhibition, common in biochemistry; 3) reversible reactions; 4) multi-substrate enzymatic reactions, both important in many metabolic pathways; and 5) translation and transcription dynamics in a cell-free system, which brings insight into the functioning of all gene-protein networks. We envision that circuit modeling and simulation could become a powerful scientific communication language and tool for quantitative studies of kinetics in biology and related fields.

Relationship between the Chromosome Structural Dynamics and Gene Expression—A Chicken and Egg Dilemma?

Prokaryotic transcription was extensively studied over the last half-century. A great deal of data has been accumulated regarding the control of gene expression by transcription factors regulating their target genes by binding at specific DNA sites. However, there is a significant gap between the mechanistic description of transcriptional control obtained from in vitro biochemical studies and the complexity of transcriptional regulation in the context of the living cell. Indeed, recent studies provide ample evidence for additional levels of complexity pertaining to the regulation of transcription in vivo, such as, for example, the role of the subcellular localization and spatial organization of different molecular components involved in the transcriptional control and, especially, the role of chromosome configurational dynamics. The question as to how the chromosome is dynamically reorganized under the changing environmental conditions and how this reorganization is related to gene expression is still far from being clear. In this article, we focus on the relationships between the chromosome structural dynamics and modulation of gene expression during bacterial adaptation. We argue that spatial organization of the bacterial chromosome is of central importance in the adaptation of gene expression to changing environmental conditions and vice versa, that gene expression affects chromosome dynamics.

Analytical kinetic model of native tandem promoters in E. coli

Closely spaced promoters in tandem formation are abundant in bacteria. We investigated the evolutionary conservation, biological functions, and the RNA and single-cell protein expression of genes regulated by tandem promoters in E. coli. We also studied the sequence (distance between transcription start sites ‘d_TSS’, pause sequences, and distances from oriC) and potential influence of the input transcription factors of these promoters. From this, we propose an analytical model of gene expression based on measured expression dynamics, where RNAP-promoter occupancy times and d_TSS are the key regulators of transcription interference due to TSS occlusion by RNAP at one of the promoters (when d_TSS ≤ 35 bp) and RNAP occupancy of the downstream promoter (when d_TSS > 35 bp). Occlusion and downstream promoter occupancy are modeled as linear functions of occupancy time, while the influence of d_TSS is implemented by a continuous step function, fit to in vivo data on mean single-cell protein numbers of 30 natural genes controlled by tandem promoters. The best-fitting step is at 35 bp, matching the length of DNA occupied by RNAP in the open complex formation. This model accurately predicts the squared coefficient of variation and skewness of the natural single-cell protein numbers as a function of d_TSS. Additional predictions suggest that promoters in tandem formation can cover a wide range of transcription dynamics within realistic intervals of parameter values. By accurately capturing the dynamics of these promoters, this model can be helpful to predict the dynamics of new promoters and contribute to the expansion of the repertoire of expression dynamics available to synthetic genetic constructs.

Tandem promoters are common in nature, but investigations on their dynamics have so far largely relied on synthetic constructs. Thus, their regulation and potentially unique dynamics remain unexplored. We first performed a comprehensive exploration of the conservation of genes regulated by these promoters in E. coli and the properties of their input transcription factors. We then measured protein and RNA levels expressed by 30 Escherichia coli tandem promoters, to establish an analytical model of the expression dynamics of genes controlled by such promoters. We show that start site occlusion and downstream RNAP occupancy can be realistically captured by a model with RNAP binding affinity, the time length of open complex formation, and the nucleotide distance between transcription start sites. This study contributes to a better understanding of the unique dynamics tandem promoters can bring to the dynamics of gene networks and will assist in their use in synthetic genetic circuits.

Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression with cell volume

While most genes' expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiae's mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model.

The Context-Dependent Influence of Promoter Sequence Motifs on Transcription Initiation Kinetics and Regulation

The fitness of an individual bacterial cell is highly dependent upon the temporal tuning of gene expression levels when subjected to different environmental cues. Kinetic regulation of transcription initiation is a key step in modulating the levels of transcribed genes to promote bacterial survival. The initiation phase encompasses the binding of RNA polymerase (RNAP) to promoter DNA and a series of coupled protein-DNA conformational changes prior to entry into processive elongation. The time required to complete the initiation phase can vary by orders of magnitude and is ultimately dictated by the DNA sequence of the promoter. In this review, we aim to provide the required background to understand how promoter sequence motifs may affect initiation kinetics during promoter recognition and binding, subsequent conformational changes which lead to DNA opening around the transcription start site, and promoter escape. By calculating the steady-state flux of RNA production as a function of these effects, we illustrate that the presence/absence of a consensus promoter motif cannot be used in isolation to make conclusions regarding promoter strength. Instead, the entire series of linked, sequence-dependent structural transitions must be considered holistically. Finally, we describe how individual transcription factors take advantage of the broad distribution of sequence-dependent basal kinetics to either increase or decrease RNA flux.

Tunability enhancement of gene regulatory motifs through competition for regulatory protein resources

Gene regulatory networks (GRNs) orchestrate the spatiotemporal levels of gene expression, thereby regulating various cellular functions ranging from embryonic development to tissue homeostasis. Some patterns called "motifs" recurrently appear in the GRNs. Owing to the prevalence of these motifs they have been subjected to much investigation, both in the context of understanding cellular decision making and engineering synthetic circuits. Mounting experimental evidence suggests that (1) the copy number of genes associated with these motifs varies, and (2) proteins produced from these genes bind to decoy binding sites on the genome as well as promoters driving the expression of other genes. Together, these two processes engender competition for protein resources within a cell. To unravel how competition for protein resources affects the dynamical properties of regulatory motifs, we propose a simple kinetic model that explicitly incorporates copy number variation (CNV) of genes and decoy binding of proteins. Using quasi-steady-state approximations, we theoretically investigate the transient and steady-state properties of three of the commonly found motifs: Autoregulation, toggle switch, and repressilator. While protein resource competition alters the timescales to reach the steady state for all these motifs, the dynamical properties of the toggle switch and repressilator are affected in multiple ways. For toggle switch, the basins of attraction of the known attractors are dramatically altered if one set of proteins binds to decoys more frequently than the other, an effect which gets suppressed as the copy number of the toggle switch is enhanced. For repressilators, protein sharing leads to an emergence of oscillation in regions of parameter space that were previously nonoscillatory. Intriguingly, both the amplitude and frequency of oscillation are altered in a nonlinear manner through the interplay of CNV and decoy binding. Overall, competition for protein resources within a cell provides an additional layer of regulation of gene regulatory motifs.

Bacterial Vivisection: How Fluorescence-Based Imaging Techniques Shed a Light on the Inner Workings of Bacteria

The rise in fluorescence-based imaging techniques over the past 3 decades has improved the ability of researchers to scrutinize live cell biology at increased spatial and temporal resolution. In microbiology, these real-time vivisections structurally changed the view on the bacterial cell away from the "watery bag of enzymes" paradigm toward the perspective that these organisms are as complex as their eukaryotic counterparts. Capitalizing on the enormous potential of (time-lapse) fluorescence microscopy and the ever-extending pallet of corresponding probes, initial breakthroughs were made in unraveling the localization of proteins and monitoring real-time gene expression. However, later it became clear that the potential of this technique extends much further, paving the way for a focus-shift from observing single events within bacterial cells or populations to obtaining a more global picture at the intra- and intercellular level. In this review, we outline the current state of the art in fluorescence-based vivisection of bacteria and provide an overview of important case studies to exemplify how to use or combine different strategies to gain detailed information on the cell's physiology. The manuscript therefore consists of two separate (but interconnected) parts that can be read and consulted individually. The first part focuses on the fluorescent probe pallet and provides a perspective on modern methodologies for microscopy using these tools. The second section of the review takes the reader on a tour through the bacterial cell from cytoplasm to outer shell, describing strategies and methods to highlight architectural features and overall dynamics within cells.

A Decrease in Transcription Capacity Limits Growth Rate upon Translation Inhibition

Exposure of bacteria to sublethal concentrations of antibiotics can lead to bacterial adaptation and survival at higher doses of inhibitors, which in turn can lead to the emergence of antibiotic resistance. The presence of sublethal concentrations of antibiotics targeting translation results in an increase in the amount of ribosomes per cell but nonetheless a decrease in the cells’ growth rate. In this work, we have found that inhibition of ribosome activity can result in a decrease in the amount of free RNA polymerase available for transcription, thus limiting the protein expression rate via a different pathway than what was expected. This result can be explained by our observation that long genes, such as those coding for RNA polymerase subunits, have a higher probability of premature translation termination in the presence of ribosome inhibitors, while expression of short ribosomal genes is affected less, consistent with their increased concentration.

In bacterial cells, inhibition of ribosomes by sublethal concentrations of antibiotics leads to a decrease in the growth rate despite an increase in ribosome content. The limitation of ribosomal activity results in an increase in the level of expression from ribosomal promoters; this can deplete the pool of RNA polymerase (RNAP) that is available for the expression of nonribosomal genes. However, the magnitude of this effect remains to be quantified. Here, we use the change in the activity of constitutive promoters with different affinities for RNAP to quantify the change in the concentration of free RNAP. The data are consistent with a significant decrease in the amount of RNAP available for transcription of both ribosomal and nonribosomal genes. Results obtained with different reporter genes reveal an mRNA length dependence on the amount of full-length translated protein, consistent with the decrease in ribosome processivity affecting more strongly the translation of longer genes. The genes coding for the β and β' subunits of RNAP are among the longest genes in the Escherichia coli genome, while the genes coding for ribosomal proteins are among the shortest genes. This can explain the observed decrease in transcription capacity that favors the expression of genes whose promoters have a high affinity for RNAP, such as ribosomal promoters.

IMPORTANCE Exposure of bacteria to sublethal concentrations of antibiotics can lead to bacterial adaptation and survival at higher doses of inhibitors, which in turn can lead to the emergence of antibiotic resistance. The presence of sublethal concentrations of antibiotics targeting translation results in an increase in the amount of ribosomes per cell but nonetheless a decrease in the cells’ growth rate. In this work, we have found that inhibition of ribosome activity can result in a decrease in the amount of free RNA polymerase available for transcription, thus limiting the protein expression rate via a different pathway than what was expected. This result can be explained by our observation that long genes, such as those coding for RNA polymerase subunits, have a higher probability of premature translation termination in the presence of ribosome inhibitors, while expression of short ribosomal genes is affected less, consistent with their increased concentration.

Simultaneous cross-evaluation of heterogeneous E. coli datasets via mechanistic simulation

The extensive heterogeneity of biological data poses challenges to analysis and interpretation. Construction of a large-scale mechanistic model of Escherichia coli enabled us to integrate and cross-evaluate a massive, heterogeneous dataset based on measurements reported by various groups over decades. We identified inconsistencies with functional consequences across the data, including that the total output of the ribosomes and RNA polymerases described by data are not sufficient for a cell to reproduce measured doubling times, that measured metabolic parameters are neither fully compatible with each other nor with overall growth, and that essential proteins are absent during the cell cycle-and the cell is robust to this absence. Finally, considering these data as a whole leads to successful predictions of new experimental outcomes, in this case protein half-lives.

Clusters of bacterial RNA polymerase are biomolecular condensates that assemble through liquid-liquid phase separation

Bacterial cells are small and were long thought to have little to no internal structure. However, advances in microscopy have revealed that bacteria do indeed contain subcellular compartments. But how these compartments form has remained a mystery. Recent progress in larger, more complex eukaryotic cells has identified a novel mechanism for intracellular organization known as liquid–liquid phase separation. This process causes certain types of molecules to concentrate within distinct compartments inside the cell. Here, we demonstrate that the same process also occurs in bacteria. This work, together with a growing body of literature, suggests that liquid–liquid phase separation is a common mechanism for intracellular organization in both eukaryotic and prokaryotic cells.

Once described as mere “bags of enzymes,” bacterial cells are in fact highly organized, with many macromolecules exhibiting nonuniform localization patterns. Yet the physical and biochemical mechanisms that govern this spatial heterogeneity remain largely unknown. Here, we identify liquid–liquid phase separation (LLPS) as a mechanism for organizing clusters of RNA polymerase (RNAP) in Escherichia coli. Using fluorescence imaging, we show that RNAP quickly transitions from a dispersed to clustered localization pattern as cells enter log phase in nutrient-rich media. RNAP clusters are sensitive to hexanediol, a chemical that dissolves liquid-like compartments in eukaryotic cells. In addition, we find that the transcription antitermination factor NusA forms droplets in vitro and in vivo, suggesting that it may nucleate RNAP clusters. Finally, we use single-molecule tracking to characterize the dynamics of cluster components. Our results indicate that RNAP and NusA molecules move inside clusters, with mobilities faster than a DNA locus but slower than bulk diffusion through the nucleoid. We conclude that RNAP clusters are biomolecular condensates that assemble through LLPS. This work provides direct evidence for LLPS in bacteria and demonstrates that this process can serve as a mechanism for intracellular organization in prokaryotes and eukaryotes alike.

Small binding-site clearance delays are not negligible in gene expression modeling

During the templated biopolymerization processes of transcription and translation, a macromolecular machine, either an RNA polymerase or a ribosome, binds to a specific site on the template. Due to the sizes of these enzymes, there is a waiting time before one clears the binding site and another can bind. These clearance delays are relatively short, and one might think that they could be neglected. However, in the case of transcription, these clearance delays are associated with conservation laws, resulting in surprisingly large effects on the bifurcation diagrams in models of gene expression networks. We study an example of this phenomenon in a model of a gene regulated by a non-coding RNA displaying bistability. Neglecting the binding-site clearance delays in this model can only be compensated for by making ad hoc, unphysical adjustments to the model's kinetic constants.

Spatial organization of RNA polymerase and its relationship with transcription in Escherichia coli

Recent studies have shown that RNA polymerase (RNAP) is organized into distinct clusters in Escherichia coli and Bacillus subtilis cells. Spatially organized molecular components in prokaryotic systems imply compartmentalization without the use of membranes, which may offer insights into unique functions and regulations. It has been proposed that the formation of RNAP clusters is driven by active ribosomal RNA (rRNA) transcription and that RNAP clusters function as factories for highly efficient transcription. In this work, we examined these hypotheses by investigating the spatial organization and transcription activity of RNAP in E. coli cells using quantitative superresolution imaging coupled with genetic and biochemical assays. We observed that RNAP formed distinct clusters that were engaged in active rRNA synthesis under a rich medium growth condition. Surprisingly, a large fraction of RNAP clusters persisted in the absence of high rRNA transcription activities or when the housekeeping σ⁷⁰ was sequestered, and was only significantly diminished when all RNA transcription was inhibited globally. In contrast, the cellular distribution of RNAP closely followed the morphology of the underlying nucleoid under all conditions tested irrespective of the corresponding transcription activity, and RNAP redistributed into dispersed, smaller clusters when the supercoiling state of the nucleoid was perturbed. These results suggest that RNAP was organized into active transcription centers under the rich medium growth condition; its spatial arrangement at the cellular level, however, was not dependent on rRNA synthesis activity and was likely organized by the underlying nucleoid.

Quantitative modeling of transcription and translation of an all-E. coli cell-free system

Cell-free transcription-translation (TXTL) is expanding as a polyvalent experimental platform to engineer biological systems outside living organisms. As the number of TXTL applications and users is rapidly growing, some aspects of this technology could be better characterized to provide a broader description of its basic working mechanisms. In particular, developing simple quantitative biophysical models that grasp the different regimes of in vitro gene expression, using relevant kinetic constants and concentrations of molecular components, remains insufficiently examined. In this work, we present an ODE (Ordinary Differential Equation)-based model of the expression of a reporter gene in an all E. coli TXTL that we apply to a set of regulatory elements spanning several orders of magnitude in strengths, far beyond the T7 standard system used in most of the TXTL platforms. Several key biochemical constants are experimentally determined through fluorescence assays. The robustness of the model is tested against the experimental parameters, and limitations of TXTL resources are described. We establish quantitative references between the performance of E. coli and synthetic promoters and ribosome binding sites. The model and the data should be useful for the TXTL community interested either in gene network engineering or in biomanufacturing beyond the conventional platforms relying on phage transcription.

Distribution of Initiation Times Reveals Mechanisms of Transcriptional Regulation in Single Cells

Transcription is the dominant point of control of gene expression. Biochemical studies have revealed key molecular components of transcription and their interactions, but the dynamics of transcription initiation in cells is still poorly understood. This state of affairs is being remedied with experiments that observe transcriptional dynamics in single cells using fluorescent reporters. Quantitative information about transcription initiation dynamics can also be extracted from experiments that use electron micrographs of RNA polymerases caught in the act of transcribing a gene (Miller spreads). Inspired by these data, we analyze a general stochastic model of transcription initiation and elongation and compute the distribution of transcription initiation times. We show that different mechanisms of initiation leave distinct signatures in the distribution of initiation times that can be compared to experiments. We analyze published data from micrographs of RNA polymerases transcribing ribosomal RNA genes in Escherichia coli and compare the observed distributions of interpolymerase distances with the predictions from previously hypothesized mechanisms for the regulation of these genes. Our analysis demonstrates the potential of measuring the distribution of time intervals between initiation events as a probe for dissecting mechanisms of transcription initiation in live cells.

Absolute quantification of translational regulation and burden using combined sequencing approaches

Translation of mRNAs into proteins is a key cellular process. Ribosome binding sites and stop codons provide signals to initiate and terminate translation, while stable secondary mRNA structures can induce translational recoding events. Fluorescent proteins are commonly used to characterize such elements but require the modification of a part's natural context and allow only a few parameters to be monitored concurrently. Here, we combine Ribo-seq with quantitative RNA-seq to measure at nucleotide resolution and in absolute units the performance of elements controlling transcriptional and translational processes during protein synthesis. We simultaneously measure 779 translation initiation rates and 750 translation termination efficiencies across the Escherichia coli transcriptome, in addition to translational frameshifting induced at a stable RNA pseudoknot structure. By analyzing the transcriptional and translational response, we discover that sequestered ribosomes at the pseudoknot contribute to a σ³²-mediated stress response, codon-specific pausing, and a drop in translation initiation rates across the cell. Our work demonstrates the power of integrating global approaches toward a comprehensive and quantitative understanding of gene regulation and burden in living cells.

Fundamental principles in bacterial physiology-history, recent progress, and the future with focus on cell size control: a review

Bacterial physiology is a branch of biology that aims to understand overarching principles of cellular reproduction. Many important issues in bacterial physiology are inherently quantitative, and major contributors to the field have often brought together tools and ways of thinking from multiple disciplines. This article presents a comprehensive overview of major ideas and approaches developed since the early 20th century for anyone who is interested in the fundamental problems in bacterial physiology. This article is divided into two parts. In the first part (sections 1-3), we review the first 'golden era' of bacterial physiology from the 1940s to early 1970s and provide a complete list of major references from that period. In the second part (sections 4-7), we explain how the pioneering work from the first golden era has influenced various rediscoveries of general quantitative principles and significant further development in modern bacterial physiology. Specifically, section 4 presents the history and current progress of the 'adder' principle of cell size homeostasis. Section 5 discusses the implications of coarse-graining the cellular protein composition, and how the coarse-grained proteome 'sectors' re-balance under different growth conditions. Section 6 focuses on physiological invariants, and explains how they are the key to understanding the coordination between growth and the cell cycle underlying cell size control in steady-state growth. Section 7 overviews how the temporal organization of all the internal processes enables balanced growth. In the final section 8, we conclude by discussing the remaining challenges for the future in the field.

Programming mRNA decay to modulate synthetic circuit resource allocation

Synthetic circuits embedded in host cells compete with cellular processes for limited intracellular resources. Here we show how funnelling of cellular resources, after global transcriptome degradation by the sequence-dependent endoribonuclease MazF, to a synthetic circuit can increase production. Target genes are protected from MazF activity by recoding the gene sequence to eliminate recognition sites, while preserving the amino acid sequence. The expression of a protected fluorescent reporter and flux of a high-value metabolite are significantly enhanced using this genome-scale control strategy. Proteomics measurements discover a host factor in need of protection to improve resource redistribution activity. A computational model demonstrates that the MazF mRNA-decay feedback loop enables proportional control of MazF in an optimal operating regime. Transcriptional profiling of MazF-induced cells elucidates the dynamic shifts in transcript abundance and discovers regulatory design elements. Altogether, our results suggest that manipulation of cellular resource allocation is a key control parameter for synthetic circuit design.

Synthetic circuits in host cells compete with endogenous processes for limited resources. Here the authors use MazF to funnel cellular resources to a synthetic circuit to increase product production and demonstrate how resource allocation can be manipulated.

Rapid Sampling of Escherichia coli After Changing Oxygen Conditions Reveals Transcriptional Dynamics

Escherichia coli is able to shift between anaerobic and aerobic metabolism by adapting its gene expression, e.g., of metabolic genes, to the new environment. The dynamics of gene expression that result from environmental shifts are limited, amongst others, by the time needed for regulation and transcription elongation. In this study, we examined gene expression dynamics after an anaerobic-to-aerobic shift on a short time scale (0.5, 1, 2, 5, and 10 min) by RNA sequencing with emphasis on delay times and transcriptional elongation rates (TER). Transient expression patterns and timing of differential expression, characterized by delay and elongation, were identified as key features of the dataset. Gene ontology enrichment analysis revealed early upregulation of respiratory and iron-related gene sets. We inferred specific TERs of 89 operons with a mean TER of 42.0 nt/s and mean delay time of 22.4 s. TERs correlate with sequence features, such as codon bias, whereas delay times correlate with the involvement of regulators. The presented data illustrate that at very short times after a shift in oxygenation, extensional changes of the transcriptome, such as temporary responses, can be observed. Besides regulation, TERs contribute to the dynamics of gene expression.

Isocost Lines Describe the Cellular Economy of Genetic Circuits

Genetic circuits in living cells share transcriptional and translational resources that are available in limited amounts. This leads to unexpected couplings among seemingly unconnected modules, which result in poorly predictable circuit behavior. In this study, we determine these interdependencies between products of different genes by characterizing the economy of how transcriptional and translational resources are allocated to the production of proteins in genetic circuits. We discover that, when expressed from the same plasmid, the combinations of attainable protein concentrations are constrained by a linear relationship, which can be interpreted as an isocost line, a concept used in microeconomics. We created a library of circuits with two reporter genes, one constitutive and the other inducible in the same plasmid, without a regulatory path between them. In agreement with the model predictions, experiments reveal that the isocost line rotates when changing the ribosome binding site strength of the inducible gene and shifts when modifying the plasmid copy number. These results demonstrate that isocost lines can be employed to predict how genetic circuits become coupled when sharing resources and provide design guidelines for minimizing the effects of such couplings.

Bacteria differently regulate mRNA abundance to specifically respond to various stresses

Environmental stress is detrimental to cell viability and requires an adequate reprogramming of cellular activities to maximize cell survival. We present a global analysis of the response of Escherichia coli to acute heat and osmotic stress. We combine deep sequencing of total mRNA and ribosome-protected fragments to provide a genome-wide map of the stress response at transcriptional and translational levels. For each type of stress, we observe a unique subset of genes that shape the stress-specific response. Upon temperature upshift, mRNAs with reduced folding stability up- and downstream of the start codon, and thus with more accessible initiation regions, are translationally favoured. Conversely, osmotic upshift causes a global reduction of highly translated transcripts with high copy numbers, allowing reallocation of translation resources to not degraded and newly synthesized mRNAs.

Estimation of kinetic parameters of transcription from temporal single-RNA measurements

Gene expression dynamics in prokaryotes is largely controlled by the multi-step process of transcription initiation whose kinetics is subject to regulation. Since the number and duration of these steps cannot be currently measured in vivo, we propose a novel method for estimating them from time series of RNA numbers in individual cells. We demonstrate the method's applicability on measurements of fluorescence-tagged RNA molecules in Escherichia coli cells, and compare with a previous method. We show that the results of the two methods agree for equal data. We also show that, when incorporating additional data, the new method produces significantly different estimates, which are in closer agreement with qPCR measurements. Unlike the previous method, the new method requires no preprocessing of the RNA numbers, using maximal information from the RNA time series. In addition, it can use data outside of the observed RNA productions. Overall, the new method characterizes the transcription initiation process with enhanced detail.

Free RNA polymerase in Escherichia coli

The frequencies of transcription initiation of regulated and constitutive genes depend on the concentration of free RNA polymerase holoenzyme [Rf] near their promoters. Although RNA polymerase is largely confined to the nucleoid, it is difficult to determine absolute concentrations of [Rf] at particular locations within the nucleoid structure. However, relative concentrations of free RNA polymerase at different growth rates, [Rf]rel, can be estimated from the activities of constitutive promoters. Previous studies indicated that the rrnB P2 promoter is constitutive and that [Rf]rel in the vicinity of rrnB P2 increases with increasing growth rate. Recently it has become possible to directly visualize Rf in growing Escherichia coli cells. Here we examine some of the important issues relating to gene expression based on these new observations. We conclude that: (i) At a growth rate of 2 doublings/h, there are about 1000 free and 2350 non-specifically DNA-bound RNA polymerase molecules per average cell (12 and 28%, respectively, of 8400 total) which are in rapid equilibrium. (ii) The reversibility of the non-specific binding generates more than 1000 free RNA polymerase molecules every second in the immediate vicinity of the DNA. Of these, most rebind non-specifically to the DNA within a few ms; the frequency of non-specific binding is at least two orders of magnitude greater than specific binding and transcript initiation. (iii) At a given amount of RNA polymerase per cell, [Rf] and the density of non-specifically DNA-bound RNA polymerase molecules along the DNA both vary reciprocally with the amount of DNA in the cell. (iv) At 2 doublings/h an E. coli cell contains, on the average, about 1 non-specifically bound RNA polymerase per 9 kbp of DNA and 1 free RNA polymerase per 20 kbp of DNA. However some DNA regions (i.e. near active rRNA operons) may have significantly higher than average [Rf].

An integrated approach reveals regulatory controls on bacterial translation elongation

Ribosomes elongate at a nonuniform rate during translation. Theoretical models and experiments disagree on the in vivo determinants of elongation rate and the mechanism by which elongation rate affects protein levels. To resolve this conflict, we measured transcriptome-wide ribosome occupancy under multiple conditions and used it to formulate a whole-cell model of translation in E. coli. Our model predicts that elongation rates at most codons during nutrient-rich growth are not limited by the intracellular concentrations of aminoacyl-tRNAs. However, elongation pausing during starvation for single amino acids is highly sensitive to the kinetics of tRNA aminoacylation. We further show that translation abortion upon pausing accounts for the observed ribosome occupancy along mRNAs during starvation. Abortion reduces global protein synthesis, but it enhances the translation of a subset of mRNAs. These results suggest a regulatory role for aminoacylation and abortion during stress, and our study provides an experimentally constrained framework for modeling translation.

Bacterial responses to antibiotics and their combinations

Antibiotics affect bacterial cell physiology at many levels. Rather than just compensating for the direct cellular defects caused by the drug, bacteria respond to antibiotics by changing their morphology, macromolecular composition, metabolism, gene expression and possibly even their mutation rate. Inevitably, these processes affect each other, resulting in a complex response with changes in the expression of numerous genes. Genome-wide approaches can thus help in gaining a comprehensive understanding of bacterial responses to antibiotics. In addition, a combination of experimental and theoretical approaches is needed for identifying general principles that underlie these responses. Here, we review recent progress in our understanding of bacterial responses to antibiotics and their combinations, focusing on effects at the levels of growth rate and gene expression. We concentrate on studies performed in controlled laboratory conditions, which combine promising experimental techniques with quantitative data analysis and mathematical modeling. While these basic research approaches are not immediately applicable in the clinic, uncovering the principles and mechanisms underlying bacterial responses to antibiotics may, in the long term, contribute to the development of new treatment strategies to cope with and prevent the rise of resistant pathogenic bacteria.

A model for sigma factor competition in bacterial cells

Sigma factors control global switches of the genetic expression program in bacteria. Different sigma factors compete for binding to a limited pool of RNA polymerase (RNAP) core enzymes, providing a mechanism for cross-talk between genes or gene classes via the sharing of expression machinery. To analyze the contribution of sigma factor competition to global changes in gene expression, we develop a theoretical model that describes binding between sigma factors and core RNAP, transcription, non-specific binding to DNA and the modulation of the availability of the molecular components. The model is validated by comparison with in vitro competition experiments, with which excellent agreement is found. Transcription is affected via the modulation of the concentrations of the different types of holoenzymes, so saturated promoters are only weakly affected by sigma factor competition. However, in case of overlapping promoters or promoters recognized by two types of sigma factors, we find that even saturated promoters are strongly affected. Active transcription effectively lowers the affinity between the sigma factor driving it and the core RNAP, resulting in complex cross-talk effects. Sigma factor competition is not strongly affected by non-specific binding of core RNAPs, sigma factors and holoenzymes to DNA. Finally, we analyze the role of increased core RNAP availability upon the shut-down of ribosomal RNA transcription during the stringent response. We find that passive up-regulation of alternative sigma-dependent transcription is not only possible, but also displays hypersensitivity based on the sigma factor competition. Our theoretical analysis thus provides support for a significant role of passive control during that global switch of the gene expression program.

Bacteria respond to changing environmental conditions by switching the global pattern of expressed genes. A key mechanism for global switches of the transcriptional program depends on alternative sigma factors that bind the RNA polymerase core enzyme and direct it towards the appropriate stress response genes. Competition of different sigma factors for a limited amount of RNA polymerase is believed to play a central role in this global switch. Here, a theoretical approach is used towards a quantitative understanding of sigma factor competition and its effects on gene expression. The model is used to quantitatively describe in vitro competition assays and to address the question of indirect or passive control in the stringent response upon amino acids starvation. We show that sigma factor competition provides a mechanism for a passive up-regulation of the stress specific sigma-driven genes due to the increased availability of RNA polymerase in the stringent response. Moreover, we find that active separation of sigma factor from the RNA polymerase during early transcript elongation weakens the sigma factor-RNA polymerase equilibrium constant, raising the question of how their in vitro measure is relevant in the cell.

Partitioning of RNA polymerase activity in live Escherichia coli from analysis of single-molecule diffusive trajectories

Superresolution fluorescence microscopy is used to locate single copies of RNA polymerase (RNAP) in live Escherichia coli and track their diffusive motion. On a timescale of 0.1-1 s, most copies separate remarkably cleanly into two diffusive states. The "slow" RNAPs, which move indistinguishably from DNA loci, are assigned to specifically bound copies (with fractional population ftrxn) that are initiating transcription, elongating, pausing, or awaiting termination. The "mixed-state" RNAP copies, with effective diffusion constant Dmixed = 0.21 μm(2) s(-1), are assigned as a rapidly exchanging mixture of nonspecifically bound copies (fns) and copies undergoing free, three-dimensional diffusion within the nucleoids (ffree). Longer trajectories of 7-s duration reveal transitions between the slow and mixed states, corroborating the assignments. Short trajectories of 20-ms duration enable direct observation of the freely diffusing RNAP copies, yielding Dfree = 0.7 μm(2) s(-1). Analysis of single-particle trajectories provides quantitative estimates of the partitioning of RNAP into different states of activity: ftrxn = 0.54 ± 0.07, fns = 0.28 ± 0.05, ffree = 0.12 ± 0.03, and fnb = 0.06 ± 0.05 (fraction unable to bind to DNA on a 1-s timescale). These fractions disagree with earlier estimates.

Spatial organization of transcription in bacterial cells

Prokaryotic transcription has been extensively studied over the past half a century. However, there often exists a gap between the structural, mechanistic description of transcription obtained from in vitro biochemical studies, and the cellular, phenomenological observations from in vivo genetic studies. It is now accepted that a living bacterial cell is a complex entity; the heterogeneous cellular environment is drastically different from the homogenous, well-mixed situation in vitro. Where molecules are inside a cell may be important for their function; hence, the spatial organization of different molecular components may provide a new means of transcription regulation in vivo, possibly bridging this gap. In this review, we survey current evidence for the spatial organization of four major components of transcription [genes, transcription factors, RNA polymerase (RNAP) and RNAs] and critically analyze their biological significance.

Modular composition of gene transcription networks

Predicting the dynamic behavior of a large network from that of the composing modules is a central problem in systems and synthetic biology. Yet, this predictive ability is still largely missing because modules display context-dependent behavior. One cause of context-dependence is retroactivity, a phenomenon similar to loading that influences in non-trivial ways the dynamic performance of a module upon connection to other modules. Here, we establish an analysis framework for gene transcription networks that explicitly accounts for retroactivity. Specifically, a module's key properties are encoded by three retroactivity matrices: internal, scaling, and mixing retroactivity. All of them have a physical interpretation and can be computed from macroscopic parameters (dissociation constants and promoter concentrations) and from the modules' topology. The internal retroactivity quantifies the effect of intramodular connections on an isolated module's dynamics. The scaling and mixing retroactivity establish how intermodular connections change the dynamics of connected modules. Based on these matrices and on the dynamics of modules in isolation, we can accurately predict how loading will affect the behavior of an arbitrary interconnection of modules. We illustrate implications of internal, scaling, and mixing retroactivity on the performance of recurrent network motifs, including negative autoregulation, combinatorial regulation, two-gene clocks, the toggle switch, and the single-input motif. We further provide a quantitative metric that determines how robust the dynamic behavior of a module is to interconnection with other modules. This metric can be employed both to evaluate the extent of modularity of natural networks and to establish concrete design guidelines to minimize retroactivity between modules in synthetic systems.

Biological modules are inherently context-dependent as the input/output behavior of a module often changes upon connection with other modules. One source of context-dependence is retroactivity, a loading phenomenon by which a downstream system affects the behavior of an upstream system upon interconnection. This fact renders it difficult to predict how modules will behave once connected to each other. In this paper, we propose a general modeling framework for gene transcription networks to accurately predict how retroactivity affects the dynamic behavior of interconnected modules, based on salient physical properties of the same modules in isolation. We illustrate how our framework predicts surprising and counter-intuitive dynamic properties of naturally occurring network structures, which cannot be captured by existing models of the same dimension. We describe implications of our findings on the bottom-up approach to designing synthetic circuits, and on the top-down approach to identifying functional modules in natural networks, revealing trade-offs between robustness to interconnection and dynamic performance. Our framework carries substantial conceptual analogies with electrical network theory based on equivalent representations. We believe that the framework we have proposed, also based on equivalent network representations, can be similarly useful for the analysis and design of biological networks.

Quantitative influence of macromolecular crowding on gene regulation kinetics

We introduce macromolecular crowding quantitatively into the model for kinetics of gene regulation in Escherichia coli. We analyse and compute the specific-site searching time for 180 known transcription factors (TFs) regulating 1300 operons. The time is between 160 s (e.g. for SoxS M_w = 12.91 kDa) and 1550 s (e.g. for PepA₆ of M_w = 329.28 kDa). Diffusion coefficients for one-dimensional sliding are between for large proteins up to for small monomers or dimers. Three-dimensional diffusion coefficients in the cytoplasm are 2 orders of magnitude larger than 1D sliding coefficients, nevertheless the sliding enhances the binding rates of TF to specific sites by 1–2 orders of magnitude. The latter effect is due to ubiquitous non-specific binding. We compare the model to experimental data for LacI repressor and find that non-specific binding of the protein to DNA is activation- and not diffusion-limited. We show that the target location rate by LacI repressor is optimized with respect to microscopic rate constant for association to non-specific sites on DNA. We analyse the effect of oligomerization of TFs and DNA looping effects on searching kinetics. We show that optimal searching strategy depends on TF abundance.

External conditions inversely change the RNA polymerase II elongation rate and density in yeast

Elongation speed is a key parameter in RNA polymerase II (RNA pol II) activity. It affects the transcription rate, while it is conditioned by the physicochemical environment it works in at the same time. For instance, it is well-known that temperature affects the biochemical reactions rates. Therefore in free-living organisms that are able to grow at various environmental temperatures, such as the yeast Saccharomyces cerevisiae, evolution should have not only shaped the structural and functional properties of this key enzyme, but should have also provided mechanisms and pathways to adapt its activity to the optimal performance required. We studied the changes in RNA pol II elongation speed caused by alternations in growth temperature in yeast to find that they strictly follow the Arrhenius equation, and that they also provoke an almost inverse proportional change in RNA pol II density within the optimal growth temperature range (26-37 °C). Moreover, we discovered that yeast cells control the transcription initiation rate by changing the total amount of available RNA pol II.

A proximal promoter element required for positive transcriptional control by guanosine tetraphosphate and DksA protein during the stringent response

The alarmone guanosine tetraphosphate (ppGpp) acts as both a positive and a negative regulator of gene expression in the presence of DksA, but the underlying mechanisms of this differential control are unclear. Here, using uspA hybrid promoters, we show that an AT-rich discriminator region is crucial for positive control by ppGpp/DksA. The AT-rich discriminator makes the RNA polymerase-promoter complex extremely stable and therefore easily saturated with RNA polymerase. A more efficient transcription is achieved when the RNA polymerase-promoter complex is destabilized with ppGpp/DksA. We found that exchanging the AT-rich discriminator of uspA with the GC-rich rrnB-P1 discriminator made the uspA promoter negatively regulated by ppGpp/DksA both in vivo and in vitro. In addition, the GC-rich discriminator destabilized the RNA polymerase-promoter complex, and the effect of ppGpp/DksA on the kinetic properties of the promoter was reversed. We propose that the transcription initiation rate from promoters with GC-rich discriminators, in contrast to the uspA-promoter, is not limited by the stability of the open complex. The findings are discussed in view of models for both direct and indirect effects of ppGpp/DksA on transcriptional trade-offs.

Medium-dependent control of the bacterial growth rate

By combining results from previous studies of nutritional up-shifts we here re-investigate how bacteria adapt to different nutritional environments by adjusting their macromolecular composition for optimal growth. We demonstrate that, in contrast to a commonly held view the macromolecular composition of bacteria does not depend on the growth rate as an independent variable, but on three factors: (i) the genetic background (i.e. the strain used), (ii) the physiological history of the bacteria used for inoculation of a given growth medium, and (iii) the kind of nutrients in the growth medium. These factors determine the ribosome concentration and the average rate of protein synthesis per ribosome, and thus the growth rate. Immediately after a nutritional up-shift, the average number of ribosomes in the bacterial population increases exponentially with time at a rate which eventually is attained as the final post-shift growth rate of all cell components. After a nutritional up-shift from one minimal medium to another minimal medium of higher nutritional quality, ribosome and RNA polymerase syntheses are co-regulated and immediately increase by the same factor equal to the increase in the final growth rate. However, after an up-shift from a minimal medium to a medium containing all 20 amino acids, RNA polymerase and ribosome syntheses are no longer coregulated; a smaller rate of synthesis of RNA polymerase is compensated by a gradual increase in the fraction of free RNA polymerase, possibly due to a gradual saturation of mRNA promoters. We have also analyzed data from a recent publication, in which it was concluded that the macromolecular composition in terms of RNA/protein and RNA/DNA ratios is solely determined by the effector molecule ppGpp. Our analysis indicates that this is true only in special cases and that, in general, medium adaptation also depends on factors other than ppGpp.

Effects of gene length on the dynamics of gene expression

In Escherichia coli, the nucleotide length of a gene is bound to affect its expression dynamics. From simulations of a stochastic model of gene expression at the nucleotide and codon levels we show that, within realistic parameter values, the nucleotide length affects RNA and protein mean levels, as well as the expected transient time for RNA and protein numbers to change, following a signal. Fluctuations in RNA and protein numbers are found to be minimized for a small range of lengths, which matches the means of the distributions of lengths found in E. coli of both essential and non-essential genes. The variance of the length distribution for essential genes is found to be smaller than for non-essential genes, implying that these distributions are far from random. Finally, gene lengths are shown to affect the kinetics of a genetic switch, namely, the correlation between temporal proteins numbers, the stability of the two noisy attractors of the switch, and how biased is the choice of noisy attractor. The stability increases with gene length due to increased 'memory' about the previous states of the switch. We argue that, by affecting the dynamics of gene expression and of genetic circuits, gene lengths are subject to selection.

Detection of transcriptional triggers in the dynamics of microbial growth: application to the respiratorily versatile bacterium Shewanella oneidensis

The capacity of microorganisms to respond to variable external conditions requires a coordination of environment-sensing mechanisms and decision-making regulatory circuits. Here, we seek to understand the interplay between these two processes by combining high-throughput measurement of time-dependent mRNA profiles with a novel computational approach that searches for key genetic triggers of transcriptional changes. Our approach helped us understand the regulatory strategies of a respiratorily versatile bacterium with promising bioenergy and bioremediation applications, Shewanella oneidensis, in minimal and rich media. By comparing expression profiles across these two conditions, we unveiled components of the transcriptional program that depend mainly on the growth phase. Conversely, by integrating our time-dependent data with a previously available large compendium of static perturbation responses, we identified transcriptional changes that cannot be explained solely by internal network dynamics, but are rather triggered by specific genes acting as key mediators of an environment-dependent response. These transcriptional triggers include known and novel regulators that respond to carbon, nitrogen and oxygen limitation. Our analysis suggests a sequence of physiological responses, including a coupling between nitrogen depletion and glycogen storage, partially recapitulated through dynamic flux balance analysis, and experimentally confirmed by metabolite measurements. Our approach is broadly applicable to other systems.

Dynamics of transcription of closely spaced promoters in Escherichia coli, one event at a time

Many pairs of genes in Escherichia coli are driven by closely spaced promoters. We study the dynamics of expression of such pairs of genes driven by a model at the molecule and nucleotide level with delayed stochastic dynamics as a function of the binding affinity of the RNA polymerase to the promoter region, of the geometry of the promoter, of the distance between transcription start sites (TSSs) and of the repression mechanism. We find that the rate limiting steps of transcription at the TSS, the closed and open complex formations, strongly affect the kinetics of RNA production for all promoter configurations. Beyond a certain rate of transcription initiation events, we find that the interference between polymerases correlates the dynamics of production of the two RNA molecules from the two TSS and affects the distribution of intervals between consecutive productions of RNA molecules. The degree of correlation depends on the geometry, the distance between TSSs and repressors. Small changes in the distance between TSSs can cause abrupt changes in behavior patterns, suggesting that the sequence between adjacent promoters may be subject to strong selective pressure. The results provide better understanding on the sequence level mechanisms of transcription regulation in bacteria and may aid in the genetic engineering of artificial circuits based on closely spaced promoters.

Functional characterization of alternate optimal solutions of Escherichia coli's transcriptional and translational machinery

The constraint-based reconstruction and analysis approach has recently been extended to describe Escherichia coli's transcriptional and translational machinery. Here, we introduce the concept of reaction coupling to represent the dependency between protein synthesis and utilization. These coupling constraints lead to a significant contraction of the feasible set of steady-state fluxes. The subset of alternate optimal solutions (AOS) consistent with maximal ribosome production was calculated. The majority of transcriptional and translational reactions were active for all of these AOS, showing that the network has a low degree of redundancy. Furthermore, all calculated AOS contained the qualitative expression of at least 92% of the known essential genes. Principal component analysis of AOS demonstrated that energy currencies (ATP, GTP, and phosphate) dominate the network's capability to produce ribosomes. Additionally, we identified regulatory control points of the network, which include the transcription reactions of sigma70 (RpoD) as well as that of a degradosome component (Rne) and of tRNA charging (ValS). These reactions contribute significant variance among AOS. These results show that constraint-based modeling can be applied to gain insight into the systemic properties of E. coli's transcriptional and translational machinery.

Dynamical effects of transcriptional pause-prone sites

We study how long pause-prone sites, commonly sequence-dependent, affect transcription and RNA temporal levels in a delayed stochastic model of transcription at the single nucleotide level. We vary pause propensity, duration and the probability of premature termination of elongation at the pause site. We also study the effects of multiple pause sites. We show that pause sites can be used to fine-tune noise strength and burst size distribution of RNA levels. Varying pause rate and duration alone affects bursting but noise is not significantly affected. Noise strength can be changed by varying both parameters and, even more pronouncedly, by varying the probability of premature termination. Adding multiple pause sites amplifies the increase in noise and bursting. This regulatory mechanism of noise and bursting, being evolvable, may partially explain how different genes exhibit a wide spectrum of different behaviors. The results might assist the engineering of genes with a desired degree of noise.

The origins of time-delay in template biopolymerization processes

Time-delays are common in many physical and biological systems and they give rise to complex dynamic phenomena. The elementary processes involved in template biopolymerization, such as mRNA and protein synthesis, introduce significant time delays. However, there is not currently a systematic mapping between the individual mechanistic parameters and the time delays in these networks. We present here the development of mathematical, time-delay models for protein translation, based on PDE models, which in turn are derived through systematic approximations of first-principles mechanistic models. Theoretical analysis suggests that the key features that determine the time-delays and the agreement between the time-delay and the mechanistic models are ribosome density and distribution, i.e., the number of ribosomes on the mRNA chain relative to their maximum and their distribution along the mRNA chain. Based on analytical considerations and on computational studies, we show that the steady-state and dynamic responses of the time-delay models are in excellent agreement with the detailed mechanistic models, under physiological conditions that correspond to uniform ribosome distribution and for ribosome density up to 70%. The methodology presented here can be used for the development of reduced time-delay models of mRNA synthesis and large genetic networks. The good agreement between the time-delay and the mechanistic models will allow us to use the reduced model and advanced computational methods from nonlinear dynamics in order to perform studies that are not practical using the large-scale mechanistic models.

Effects of transcriptional pausing on gene expression dynamics

Stochasticity in gene expression affects many cellular processes and is a source of phenotypic diversity between genetically identical individuals. Events in elongation, particularly RNA polymerase pausing, are a source of this noise. Since the rate and duration of pausing are sequence-dependent, this regulatory mechanism of transcriptional dynamics is evolvable. The dependency of pause propensity on regulatory molecules makes pausing a response mechanism to external stress. Using a delayed stochastic model of bacterial transcription at the single nucleotide level that includes the promoter open complex formation, pausing, arrest, misincorporation and editing, pyrophosphorolysis, and premature termination, we investigate how RNA polymerase pausing affects a gene's transcriptional dynamics and gene networks. We show that pauses' duration and rate of occurrence affect the bursting in RNA production, transcriptional and translational noise, and the transient to reach mean RNA and protein levels. In a genetic repressilator, increasing the pausing rate and the duration of pausing events increases the period length but does not affect the robustness of the periodicity. We conclude that RNA polymerase pausing might be an important evolvable feature of genetic networks.

Effects of the promoter open complex formation on gene expression dynamics

Little is known about the biological mechanisms that shape the distribution of intervals between the completion of RNA molecules (T(p)RNA) , and thus transcriptional noise. We characterize numerically and analytically how the promoter open complex delay (tau(P)) and the transcription initiation rate (k(t)) shape T(p)RNA. From this, we assess the noise and mean of transcript levels and show that these can be tuned both independently and simultaneously by tau(P) and k(t). Finally, we characterize how tau(P) affects bursting in RNA production and show that the tau(P) measured for a lac promoter best fits independent measurements of the burst distribution of the same promoter. Since tau(P) affects noise in gene expression, and given that it is sequence dependent, it is likely to be evolvable.

Quantifying cytosolic messenger RNA concentrations in Escherichia coli using real-time polymerase chain reaction for a systems biology approach

Current messenger RNA (mRNA) quantification methods are sophisticated tools for the analysis of gene regulation. However, these methods are not suitable for more complex quantitative approaches such as the mathematical modeling of the in vivo regulation of transcription where dynamic cytosolic mRNA concentrations need to be taken into consideration. In the current study, the "standard curve method" for quantitative reverse transcription real-time polymerase chain reaction (qRT-PCR) was extended by including an internal RNA standard. This standard enables transcript losses that occur during the process, as well as variations resulting from nonquantitative processes, to be accounted for. The use of an internal standard yielded transcript concentration estimates that were on average seven times higher than those in cases where an internal standard is omitted. Choosing the cra modulon in Escherichia coli as an example, the method applied shows that the regulation of the Cra protein, as well as the growth rate-dependent regulation, need to be taken into consideration. The new method, which enables the determination of cytosolic mRNA concentrations, allows the quantitative representation of transcriptional dynamics. This is an important aspect of the analysis of the complex interactions of metabolism and regulation and in the application of mathematical modeling for systems biology.

Maximum rrn promoter activity in Escherichia coli at saturating concentrations of free RNA polymerase

During fast growth, the rrn P1 promoters of Escherichia coli operate at their maximum strength, but below their maximum activity (V(max)), since they are not saturated with RNA polymerase. Since higher concentrations of free RNA polymerase are expected to be found in strains carrying rrn deletions, we have analyzed reported electron micrographs of rrn operons from rrn deletion strains growing at maximal rates (at 37 degrees C) in LB medium [1]. We conclude that, in a strain with four of the seven rrn operons inactivated by partial deletions, transcripts are initiated at rrn P1 promoters 1.6-fold more rapidly than in the wild-type strain and the entirety of the rrn operon is transcribed at a 1.5-fold higher average elongation rate due to shortened pauses in the 16S and 23S regions. Under this condition, traffic congestion occurs in front of a pause site in the 5' leader region of the rrn operon near the beginning of the 16S gene; the congestion extends all the way back to the promoter, impedes promoter clearance and limits the promoter activity to one initiation per 0.56 s. This corresponds to a promoter activity of 107 transcripts/min and is assumed to be close to the V(max) of rrn P1 promoters.

Increased RNA polymerase availability directs resources towards growth at the expense of maintenance

Nutritionally induced changes in RNA polymerase availability have been hypothesized to be an evolutionary primeval mechanism for regulation of gene expression and several contrasting models have been proposed to explain how such 'passive' regulation might occur. We demonstrate here that ectopically elevating Escherichia coli RNA polymerase (Esigma(70)) levels causes an increased expression and promoter occupancy of ribosomal genes at the expense of stress-defense genes and amino acid biosynthetic operons. Phenotypically, cells overproducing Esigma(70) favours growth and reproduction at the expense of motility and damage protection; a response reminiscent of cells with no or diminished levels of the alarmone guanosine tetraphosphate (ppGpp). Consistently, we show that cells lacking ppGpp displayed markedly elevated levels of free Esigma(70) compared with wild-type cells and that the repression of ribosomal RNA expression and reduced growth rate of mutants with constitutively elevated levels of ppGpp can be suppressed by overproducing Esigma(70). We conclude that ppGpp modulates the levels of free Esigma(70) and that this is an integral part of the alarmone's means of regulating a trade-off between growth and maintenance.

Delayed stochastic model of transcription at the single nucleotide level

We present a delayed stochastic model of transcription at the single nucleotide level. The model accounts for the promoter open complex formation and includes alternative pathways to elongation, namely pausing, arrest, misincorporation and editing, pyrophosphorolysis, and premature termination. We confront the dynamics of this detailed model with a single-step multi-delayed stochastic model and with measurements of expression of a repressed gene at the single molecule level. At low expression rates both models match the experiments but, at higher rates the two models differ significantly, with consequences to cell-to-cell phenotypic variability. The alternative pathway reactions, due to, for example, causing polymerases to collide more often on the template, are the cause for the difference in dynamical behaviors. Next, we confront the model with measurements of the transcriptional dynamics at the single RNA level of an induced gene and show that RNA production, besides its bursting dynamics, also exhibits pulses (2 or more RNAs produced in intervals smaller than the smallest interval between initiations). The distribution of occurrences and amplitudes of pulses match the experimental measurements. This pulsing and the noise at the elongation stage are shown to play a role in the dynamics of a genetic switch.