Absolute quantitative measurement of transcriptional kinetic parameters in vivo

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

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

Whole-mount smFISH allows combining RNA and protein quantification at cellular and subcellular resolution

Multicellular organisms result from complex developmental processes largely orchestrated through the quantitative spatiotemporal regulation of gene expression. Yet, obtaining absolute counts of messenger RNAs at a three-dimensional resolution remains challenging, especially in plants, owing to high levels of tissue autofluorescence that prevent the detection of diffraction-limited fluorescent spots. In situ hybridization methods based on amplification cycles have recently emerged, but they are laborious and often lead to quantification biases. In this article, we present a simple method based on single-molecule RNA fluorescence in situ hybridization to visualize and count the number of mRNA molecules in several intact plant tissues. In addition, with the use of fluorescent protein reporters, our method also enables simultaneous detection of mRNA and protein quantity, as well as subcellular distribution, in single cells. With this method, research in plants can now fully explore the benefits of the quantitative analysis of transcription and protein levels at cellular and subcellular resolution in plant tissues.

Dissociation kinetics of small-molecule inhibitors in Escherichia coli is coupled to physiological state of cells

Bioactive small-molecule inhibitors represent a treasure chest for future drugs. In vitro high-throughput screening is a common approach to identify the small-molecule inhibitors that bind tightly to purified targets. Here, we investigate the inhibitor-target binding/unbinding kinetics in E. coli cells using a benzimidazole-derivative DNA inhibitor as a model system. We find that its unbinding rate is not constant but depends on cell growth rate. This dependence is mediated by the cellular activity, forming a feedback loop with the inhibitor's activity. In accordance with this feedback, we find cell-to-cell heterogeneity in inhibitor-target interaction, leading to co-existence of two distinct subpopulations: actively growing cells that dissociate the inhibitors from the targets and non-growing cells that do not. We find similar heterogeneity for other clinical DNA inhibitors. Our studies reveal a mechanism that couples inhibitor-target kinetics to cell physiology and demonstrate the significant effect of this coupling on drug efficacy.

Stringent response ensures the timely adaptation of bacterial growth to nutrient downshift

Timely adaptation to nutrient downshift is crucial for bacteria to maintain fitness during feast and famine cycle in the natural niche. However, the molecular mechanism that ensures the timely adaption of bacterial growth to nutrient downshift remains poorly understood. Here, we quantitatively investigated the adaptation of Escherichia coli to various kinds of nutrient downshift. We found that relA deficient strain, which is devoid of stringent response, exhibits a significantly longer growth lag than wild type strain during adapting to both amino acid downshift and carbon downshift. Quantitative proteomics show that increased (p)ppGpp level promotes the growth adaption of bacteria to amino acid downshift via triggering the proteome resource re-allocation from ribosome synthesis to amino acid biosynthesis. Such type of proteome re-allocation is significantly delayed in the relA-deficient strain, which underlies its longer lag than wild type strain during amino acid downshift. During carbon downshift, a lack of stringent response in relA deficient strain leads to disruption of the transcription-translation coordination, thus compromising the transcription processivity and further the timely expression of related catabolic operons for utilizing secondary carbon sources. Our studies shed light on the fundamental strategy of bacteria to maintain fitness under nutrient-fluctuating environments.

Slowest possible replicative life at frigid temperatures for yeast

Determining whether life can progress arbitrarily slowly may reveal fundamental barriers to staying out of thermal equilibrium for living systems. By monitoring budding yeast's slowed-down life at frigid temperatures and with modeling, we establish that Reactive Oxygen Species (ROS) and a global gene-expression speed quantitatively determine yeast's pace of life and impose temperature-dependent speed limits - shortest and longest possible cell-doubling times. Increasing cells' ROS concentration increases their doubling time by elongating the cell-growth (G1-phase) duration that precedes the cell-replication (S-G2-M) phase. Gene-expression speed constrains cells' ROS-reducing rate and sets the shortest possible doubling-time. To replicate, cells require below-threshold concentrations of ROS. Thus, cells with sufficiently abundant ROS remain in G1, become unsustainably large and, consequently, burst. Therefore, at a given temperature, yeast's replicative life cannot progress arbitrarily slowly and cells with the lowest ROS-levels replicate most rapidly. Fundamental barriers may constrain the thermal slowing of other organisms' lives.

Crucial role and mechanism of transcription-coupled DNA repair in bacteria

Transcription-coupled DNA repair (TCR) is presumed to be a minor sub-pathway of nucleotide excision repair (NER) in bacteria. Global genomic repair is thought to perform the bulk of repair independently of transcription. TCR is also believed to be mediated exclusively by Mfd-a DNA translocase of a marginal NER phenotype^1-3. Here we combined in cellulo cross-linking mass spectrometry with structural, biochemical and genetic approaches to map the interactions within the TCR complex (TCRC) and to determine the actual sequence of events that leads to NER in vivo. We show that RNA polymerase (RNAP) serves as the primary sensor of DNA damage and acts as a platform for the recruitment of NER enzymes. UvrA and UvrD associate with RNAP continuously, forming a surveillance pre-TCRC. In response to DNA damage, pre-TCRC recruits a second UvrD monomer to form a helicase-competent UvrD dimer that promotes backtracking of the TCRC. The weakening of UvrD-RNAP interactions renders cells sensitive to genotoxic stress. TCRC then recruits a second UvrA molecule and UvrB to initiate the repair process. Contrary to the conventional view, we show that TCR accounts for the vast majority of chromosomal repair events; that is, TCR thoroughly dominates over global genomic repair. We also show that TCR is largely independent of Mfd. We propose that Mfd has an indirect role in this process: it participates in removing obstructive RNAPs in front of TCRCs and also in recovering TCRCs from backtracking after repair has been completed.

Quantitative analysis of asynchronous transcription-translation and transcription processivity in Bacillus subtilis under various growth conditions

Tight coordination between transcription and translation has long been recognized as the hallmark of gene expression in bacteria. In Escherichia coli cells, disruption of the transcription-translation coordination leads to the loss of transcription processivity via triggering Rho-mediated premature transcription termination. Here we quantitatively characterize the transcription and translation kinetics in Gram-positive model bacterium Bacillus subtilis. We found that the speed of transcription elongation is much faster than that of translation elongation in B. subtilis under various growth conditions. Moreover, a Rho-independent loss of transcription processivity occurs constitutively in several genes/operons but is not subject to translational control. When the transcription elongation is decelerated under poor nutrients, low temperature, or nucleotide depletion, the loss of transcription processivity is strongly enhanced, suggesting that its degree is modulated by the speed of transcription elongation. Our study reveals distinct design principles of gene expression in E. coli and B. subtilis.

Single-cell measurement of plasmid copy number and promoter activity

Accurate measurements of promoter activities are crucial for predictably building genetic systems. Here we report a method to simultaneously count plasmid DNA, RNA transcripts, and protein expression in single living bacteria. From these data, the activity of a promoter in units of RNAP/s can be inferred. This work facilitates the reporting of promoters in absolute units, the variability in their activity across a population, and their quantitative toll on cellular resources, all of which provide critical insights for cellular engineering.

Fluorescence lifetime probes for detection of RNA degradation

To investigate RNA degradation in live cells, detection methods that do not require RNA extraction from cells are necessary. In this study, we examined the utility of fluorescence lifetime measurements using a probe attached to the end of an RNA molecule for detecting RNA degradation. We optimized a short fluorescein-labeled RNA sequence whose fluorescence lifetime varied significantly before and after degradation. The selected HHG-fluorescein sequence (H = U, C, or A) is a promising RNA labeling unit (fluorescence lifetime probe) for live cell imaging of RNA degradation.

Long-Distance Cooperative and Antagonistic RNA Polymerase Dynamics via DNA Supercoiling

Genes are often transcribed by multiple RNA polymerases (RNAPs) at densities that can vary widely across genes and environmental conditions. Here, we provide in vitro and in vivo evidence for a built-in mechanism by which co-transcribing RNAPs display either collaborative or antagonistic dynamics over long distances (>2 kb) through transcription-induced DNA supercoiling. In Escherichia coli, when the promoter is active, co-transcribing RNAPs translocate faster than a single RNAP, but their average speed is not altered by large variations in promoter strength and thus RNAP density. Environmentally induced promoter repression reduces the elongation efficiency of already-loaded RNAPs, causing premature termination and quick synthesis arrest of no-longer-needed proteins. This negative effect appears independent of RNAP convoy formation and is abrogated by topoisomerase I activity. Antagonistic dynamics can also occur between RNAPs from divergently transcribed gene pairs. Our findings may be broadly applicable given that transcription on topologically constrained DNA is the norm across organisms.

Stochastic simulation and statistical inference platform for visualization and estimation of transcriptional kinetics

Recent advances in single-molecule fluorescent imaging have enabled quantitative measurements of transcription at a single gene copy, yet an accurate understanding of transcriptional kinetics is still lacking due to the difficulty of solving detailed biophysical models. Here we introduce a stochastic simulation and statistical inference platform for modeling detailed transcriptional kinetics in prokaryotic systems, which has not been solved analytically. The model includes stochastic two-state gene activation, mRNA synthesis initiation and stepwise elongation, release to the cytoplasm, and stepwise co-transcriptional degradation. Using the Gillespie algorithm, the platform simulates nascent and mature mRNA kinetics of a single gene copy and predicts fluorescent signals measurable by time-lapse single-cell mRNA imaging, for different experimental conditions. To approach the inverse problem of estimating the kinetic parameters of the model from experimental data, we develop a heuristic optimization method based on the genetic algorithm and the empirical distribution of mRNA generated by simulation. As a demonstration, we show that the optimization algorithm can successfully recover the transcriptional kinetics of simulated and experimental gene expression data. The platform is available as a MATLAB software package at https://data.caltech.edu/records/1287.

Bacterial growth physiology and RNA metabolism

Bacteria are sophisticated systems with high capacity and flexibility to adapt to various environmental conditions. Each prokaryote however possesses a defined metabolic network, which sets its overall metabolic capacity, and therefore the maximal growth rate that can be reached. To achieve optimal growth, bacteria adopt various molecular strategies to optimally adjust gene expression and optimize resource allocation according to the nutrient availability. The resulting physiological changes are often accompanied by changes in the growth rate, and by global regulation of gene expression. The growth-rate-dependent variation of the abundances in the cellular machineries, together with condition-specific regulatory mechanisms, affect RNA metabolism and fate and pose a challenge for rational gene expression reengineering of synthetic circuits. This article is part of a Special Issue entitled: RNA and gene control in bacteria, edited by Dr. M. Guillier and F. Repoila.

Disruption of transcription-translation coordination in Escherichia coli leads to premature transcriptional termination

Tight coordination between transcription and translation is crucial to maintaining the integrity of gene expression in bacteria, yet how bacteria manage to coordinate these two processes remains unclear. Possible direct physical coupling between the RNA polymerase and ribosome has been thoroughly investigated in recent years. Here, we quantitatively characterize the transcriptional kinetics of Escherichia coli under different growth conditions. Transcriptional and translational elongation remain coordinated under various nutrient conditions, as previously reported. However, transcriptional elongation was not affected under antibiotics that slowed down translational elongation. This result was also found by introducing nonsense mutation that completely dissociated transcription from translation. Our data thus provide direct evidence that translation is not required to maintain the speed of transcriptional elongation. In cases where transcription and translation are dissociated, our study provides quantitative characterization of the resulting process of premature transcriptional termination (PTT). PTT-mediated polarity caused by translation-targeting antibiotics substantially affected the coordinated expression of genes in several long operons, contributing to the key physiological effects of these antibiotics. Our results also suggest a model in which the coordination between transcriptional and translational elongation under normal growth conditions is implemented by guanosine tetraphosphate.

Multiplex RNA single molecule FISH of inducible mRNAs in single yeast cells

Transcript levels powerfully influence cell behavior and phenotype and are carefully regulated at several steps. Recently developed single cell approaches such as RNA single molecule fluorescence in-situ hybridization (smFISH) have produced advances in our understanding of how these steps work within the cell. In comparison to single-cell sequencing, smFISH provides more accurate quantification of RNA levels. Additionally, transcript subcellular localization is directly visualized, enabling the analysis of transcription (initiation and elongation), RNA export and degradation. As part of our efforts to investigate how this type of analysis can generate improved models of gene expression, we used smFISH to quantify the kinetic expression of STL1 and CTT1 mRNAs in single Saccharomyces cerevisiae cells upon 0.2 and 0.4 M NaCl osmotic stress. In this Data Descriptor, we outline our procedure along with our data in the form of raw images and processed mRNA counts. We discuss how these data can be used to develop single cell modelling approaches, to study fundamental processes in transcription regulation and develop single cell image processing approaches.

Contributions of regulated transcription and mRNA decay to the dynamics of gene expression

Organisms have acquired sophisticated regulatory networks that control gene expression in response to cellular perturbations. Understanding of the mechanisms underlying the coordinated changes in gene expression in response to external and internal stimuli is a fundamental issue in biology. Recent advances in high-throughput technologies have enabled the measurement of diverse biological information, including gene expression levels, kinetics of gene expression, and interactions among gene expression regulatory molecules. By coupling these technologies with quantitative modeling, we can now uncover the biological roles and mechanisms of gene regulation at the system level. This review consists of two parts. First, we focus on the methods using uridine analogs that measure synthesis and decay rates of RNAs, which demonstrate how cells dynamically change the regulation of gene expression in response to both internal and external cues. Second, we discuss the underlying mechanisms of these changes in kinetics, including the functions of transcription factors and RNA-binding proteins. Overall, this review will help to clarify a system-level view of gene expression programs in cells. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Turnover and Surveillance > Regulation of RNA Stability RNA Methods > RNA Analyses in vitro and In Silico.

Distinct mechanisms coordinate transcription and translation under carbon and nitrogen starvation in Escherichia coli

Bacteria adapt to environmental stress by producing proteins that provide stress protection. However, stress can severely perturb the kinetics of gene expression, disrupting protein production. Here, we characterized how Escherichia coli mitigates such perturbations under nutrient stress through the kinetic coordination of transcription and translation. We observed that, when translation became limiting under nitrogen starvation, transcription elongation slowed accordingly. This slowdown was mediated by (p)ppGpp, the alarmone whose primary role is thought to be promoter regulation. This kinetic coordination by (p)ppGpp was critical for the robust synthesis of gene products. Surprisingly, under carbon starvation, (p)ppGpp was dispensable for robust synthesis. Characterization of the underlying kinetics revealed that under carbon starvation, transcription became limiting, and translation aided transcription elongation. This mechanism naturally coordinated transcription with translation, alleviating the need for (p)ppGpp as a mediator. These contrasting mechanisms for coordination resulted in the condition-dependent effects of (p)ppGpp on global protein synthesis and starvation survival. Our findings reveal a kinetic aspect of gene expression plasticity, establishing (p)ppGpp as a condition-dependent global effector of gene expression.

The emergence of metabolic heterogeneity and diverse growth responses in isogenic bacterial cells

Microorganisms adapt to frequent environmental changes through population diversification. Previous studies demonstrated phenotypic diversity in a clonal population and its important effects on microbial ecology. However, the dynamic changes of phenotypic composition have rarely been characterized. Also, cellular variations and environmental factors responsible for phenotypic diversity remain poorly understood. Here, we studied phenotypic diversity driven by metabolic heterogeneity. We characterized metabolic activities and growth kinetics of starved Escherichia coli cells subject to nutrient upshift at single-cell resolution. We observed three subpopulations with distinct metabolic activities and growth phenotypes. One subpopulation was metabolically active and immediately grew upon nutrient upshift. One subpopulation was metabolically inactive and non-viable. The other subpopulation was metabolically partially active, and did not grow upon nutrient upshift. The ratio of these subpopulations changed dynamically during starvation. A long-term observation of cells with partial metabolic activities indicated that their metabolism was later spontaneously restored, leading to growth recovery. Further investigations showed that oxidative stress can induce the emergence of a subpopulation with partial metabolic activities. Our findings reveal the emergence of metabolic heterogeneity and associated dynamic changes in phenotypic composition. In addition, the results shed new light on microbial dormancy, which has important implications in microbial ecology and biomedicine.

Model-based genome-wide determination of RNA chain elongation rates in Escherichia coli

Dynamics in the process of transcription are often simplified, yet they play an important role in transcript folding, translation into functional protein and DNA supercoiling. While the modulation of the speed of transcription of individual genes and its role in regulation and proper protein folding has been analyzed in depth, the functional relevance of differences in transcription speeds as well as the factors influencing it have not yet been determined on a genome-wide scale. Here we determined transcription speeds for the majority of E. coli genes based on experimental data. We find large differences in transcription speed between individual genes and a strong influence of both cellular location as well as the relative importance of genes for cellular function on transcription speeds. Investigating factors influencing transcription speeds we observe both codon composition as well as factors associated to DNA topology as most important factors influencing transcription speeds. Moreover, we show that differences in transcription speeds are sufficient to explain the timing of regulatory responses during environmental shifts and highlight the importance of the consideration of transcription speeds in the design of experiments measuring transcriptomic responses to perturbations.

Efficient and flexible implementation of Langevin simulation for gene burst production

Gene expression involves bursts of production of both mRNA and protein, and the fluctuations in their number are increased due to such bursts. The Langevin equation is an efficient and versatile means to simulate such number fluctuation. However, how to include these mRNA and protein bursts in the Langevin equation is not intuitively clear. In this work, we estimated the variance in burst production from a general gene expression model and introduced such variation in the Langevin equation. Our approach offers different Langevin expressions for either or both transcriptional and translational bursts considered and saves computer time by including many production events at once in a short burst time. The errors can be controlled to be rather precise (<2%) for the mean and <10% for the standard deviation of the steady-state distribution. Our scheme allows for high-quality stochastic simulations with the Langevin equation for gene expression, which is useful in analysis of biological networks.

mRNA detection in budding yeast with single fluorophores

Quantitative measurement of mRNA levels in single cells is necessary to understand phenotypic variability within an otherwise isogenic population of cells. Single-molecule mRNA Fluorescence In Situ Hybridization (FISH) has been established as the standard method for this purpose, but current protocols require a long region of mRNA to be targeted by multiple DNA probes. Here, we introduce a new single-probe FISH protocol termed sFISH for budding yeast, Saccharomyces cerevisiae using a single DNA probe labeled with a single fluorophore. In sFISH, we markedly improved probe specificity and signal-to-background ratio by using methanol fixation and inclined laser illumination. We show that sFISH reports mRNA changes that correspond to protein levels and gene copy number. Using this new FISH protocol, we can detect >50% of the total target mRNA. We also demonstrate the versatility of sFISH using FRET detection and mRNA isoform profiling as examples. Our FISH protocol with single-fluorophore sensitivity significantly reduces cost and time compared to the conventional FISH protocols and opens up new opportunities to investigate small changes in RNA at the single cell level.

Illuminating Messengers: An Update and Outlook on RNA Visualization in Bacteria

To be able to visualize the abundance and spatiotemporal features of RNAs in bacterial cells would permit obtaining a pivotal understanding of many mechanisms underlying bacterial cell biology. The first methods that allowed observing single mRNA molecules in individual cells were introduced by Bertrand et al. (1998) and Femino et al. (1998). Since then, a plethora of techniques to image RNA molecules with the aid of fluorescence microscopy has emerged. Many of these approaches are useful for the large eukaryotic cells but their adaptation to study RNA, specifically mRNA molecules, in bacterial cells progressed relatively slow. Here, an overview will be given of fluorescent techniques that can be used to reveal specific RNA molecules inside fixed and living single bacterial cells. It includes a critical evaluation of their caveats as well as potential solutions.