Activities of constitutive promoters in Escherichia coli

Single-cell level LasR-mediated quorum sensing response of Pseudomonas aeruginosa to pulses of signal molecules

Quorum sensing (QS) is a communication form between bacteria via small signal molecules that enables global gene regulation as a function of cell density. We applied a microfluidic mother machine to study the kinetics of the QS response of Pseudomonas aeruginosa bacteria to additions and withdrawals of signal molecules. We traced the fast buildup and the subsequent considerably slower decay of a population-level and single-cell-level QS response. We applied a mathematical model to explain the results quantitatively. We found significant heterogeneity in QS on the single-cell level, which may result from variations in quorum-controlled gene expression and protein degradation. Heterogeneity correlates with cell lineage history, too. We used single-cell data to define and quantitatively characterize the population-level quorum state. We found that the population-level QS response is well-defined. The buildup of the quorum is fast upon signal molecule addition. At the same time, its decay is much slower following signal withdrawal, and the quorum may be maintained for several hours in the absence of the signal. Furthermore, the quorum sensing response of the population was largely repeatable in subsequent pulses of signal molecules.

Global protein turnover quantification in Escherichia coli reveals cytoplasmic recycling under nitrogen limitation

Protein turnover is critical for proteostasis, but turnover quantification is challenging, and even in well-studied E. coli, proteome-wide measurements remain scarce. Here, we quantify the turnover rates of ~3200 E. coli proteins under 13 conditions by combining heavy isotope labeling with complement reporter ion quantification and find that cytoplasmic proteins are recycled when nitrogen is limited. We use knockout experiments to assign substrates to the known cytoplasmic ATP-dependent proteases. Surprisingly, none of these proteases are responsible for the observed cytoplasmic protein degradation in nitrogen limitation, suggesting that a major proteolysis pathway in E. coli remains to be discovered. Lastly, we show that protein degradation rates are generally independent of cell division rates. Thus, we present broadly applicable technology for protein turnover measurements and provide a rich resource for protein half-lives and protease substrates in E. coli, complementary to genomics data, that will allow researchers to study the control of proteostasis.

High-throughput, fluorescent-aptamer-based measurements of steady-state transcription rates for the Mycobacterium tuberculosis RNA polymerase

The first step in gene expression is the transcription of DNA sequences into RNA. Regulation at the level of transcription leads to changes in steady-state concentrations of RNA transcripts, affecting the flux of downstream functions and ultimately cellular phenotypes. Changes in transcript levels are routinely followed in cellular contexts via genome-wide sequencing techniques. However, in vitro mechanistic studies of transcription have lagged with respect to throughput. Here, we describe the use of a real-time, fluorescent-aptamer-based method to quantitate steady-state transcription rates of the Mycobacterium tuberculosis RNA polymerase. We present clear controls to show that the assay specifically reports on promoter-dependent, full-length RNA transcription rates that are in good agreement with the kinetics determined by gel-resolved, α-32P NTP incorporation experiments. We illustrate how the time-dependent changes in fluorescence can be used to measure regulatory effects of nucleotide concentrations and identity, RNAP and DNA concentrations, transcription factors, and antibiotics. Our data showcase the ability to easily perform hundreds of parallel steady-state measurements across varying conditions with high precision and reproducibility to facilitate the study of the molecular mechanisms of bacterial transcription.

High-throughput, fluorescent-aptamer-based measurements of steady-state transcription rates for Mycobacterium tuberculosis RNA polymerase

The first step in gene expression is the transcription of DNA sequences into RNA. Regulation at the level of transcription leads to changes in steady-state concentrations of RNA transcripts, affecting the flux of downstream functions and ultimately cellular phenotypes. Changes in transcript levels are routinely followed in cellular contexts via genome-wide sequencing techniques. However, in vitro mechanistic studies of transcription have lagged with respect to throughput. Here, we describe the use of a real-time, fluorescent-aptamer-based method to quantitate steady-state transcription rates of the Mycobacterium tuberculosis RNA polymerase. We present clear controls to show that the assay specifically reports on promoter-dependent, full-length RNA transcription rates that are in good agreement with the kinetics determined by gel-resolved, α- 32 P NTP incorporation experiments. We illustrate how the time-dependent changes in fluorescence can be used to measure regulatory effects of nucleotide concentrations and identity, RNAP and DNA concentrations, transcription factors, and antibiotics. Our data showcase the ability to easily perform hundreds of parallel steady-state measurements across varying conditions with high precision and reproducibility to facilitate the study of the molecular mechanisms of bacterial transcription.

Significance Statement

RNA polymerase transcription mechanisms have largely been determined from in vitro kinetic and structural biology methods. In contrast to the limited throughput of these approaches, in vivo RNA sequencing provides genome-wide measurements but lacks the ability to dissect direct biochemical from indirect genetic mechanisms. Here, we present a method that bridges this gap, permitting high-throughput fluorescence-based measurements of in vitro steady-state transcription kinetics. We illustrate how an RNA-aptamer-based detection system can be used to generate quantitative information on direct mechanisms of transcriptional regulation and discuss the far-reaching implications for future applications.

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

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

Dissecting the Fitness Costs of Complex Mutations

The fitness cost of complex pleiotropic mutations is generally difficult to assess. On the one hand, it is necessary to identify which molecular properties are directly altered by the mutation. On the other, this alteration modifies the activity of many genetic targets with uncertain consequences. Here, we examine the possibility of addressing these challenges by identifying unique predictors of these costs. To this aim, we consider mutations in the RNA polymerase (RNAP) in Escherichia coli as a model of complex mutations. Changes in RNAP modify the global program of transcriptional regulation, with many consequences. Among others is the difficulty to decouple the direct effect of the mutation from the response of the whole system to such mutation. A problem that we solve quantitatively with data of a set of constitutive genes, those on which the global program acts most directly. We provide a statistical framework that incorporates the direct effects and other molecular variables linked to this program as predictors, which leads to the identification that some genes are more suitable to determine costs than others. Therefore, we not only identified which molecular properties best anticipate fitness, but we also present the paradoxical result that, despite pleiotropy, specific genes serve as more solid predictors. These results have connotations for the understanding of the architecture of robustness in biological systems.

The Dynamic SecYEG Translocon

The spatial and temporal coordination of protein transport is an essential cornerstone of the bacterial adaptation to different environmental conditions. By adjusting the protein composition of extra-cytosolic compartments, like the inner and outer membranes or the periplasmic space, protein transport mechanisms help shaping protein homeostasis in response to various metabolic cues. The universally conserved SecYEG translocon acts at the center of bacterial protein transport and mediates the translocation of newly synthesized proteins into and across the cytoplasmic membrane. The ability of the SecYEG translocon to transport an enormous variety of different substrates is in part determined by its ability to interact with multiple targeting factors, chaperones and accessory proteins. These interactions are crucial for the assisted passage of newly synthesized proteins from the cytosol into the different bacterial compartments. In this review, we summarize the current knowledge about SecYEG-mediated protein transport, primarily in the model organism Escherichia coli, and describe the dynamic interaction of the SecYEG translocon with its multiple partner proteins. We furthermore highlight how protein transport is regulated and explore recent developments in using the SecYEG translocon as an antimicrobial target.

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.

Effects of DNA Topology on Transcription from rRNA Promoters in Bacillus subtilis

The expression of rRNA is one of the most energetically demanding cellular processes and, as such, it must be stringently controlled. Here, we report that DNA topology, i.e., the level of DNA supercoiling, plays a role in the regulation of Bacillus subtilis σ^A-dependent rRNA promoters in a growth phase-dependent manner. The more negative DNA supercoiling in exponential phase stimulates transcription from rRNA promoters, and DNA relaxation in stationary phase contributes to cessation of their activity. Novobiocin treatment of B. subtilis cells relaxes DNA and decreases rRNA promoter activity despite an increase in the GTP level, a known positive regulator of B. subtilis rRNA promoters. Comparative analyses of steps during transcription initiation then reveal differences between rRNA promoters and a control promoter, Pveg, whose activity is less affected by changes in supercoiling. Additional data then show that DNA relaxation decreases transcription also from promoters dependent on alternative sigma factors σ^B, σ^D, σ^E, σ^F, and σ^H with the exception of σ^N where the trend is the opposite. To summarize, this study identifies DNA topology as a factor important (i) for the expression of rRNA in B. subtilis in response to nutrient availability in the environment, and (ii) for transcription activities of B. subtilis RNAP holoenzymes containing alternative sigma factors.

Cell Size Is Coordinated with Cell Cycle by Regulating Initiator Protein DnaA in E. coli

Sixty years ago, bacterial cell size was found to be an exponential function of growth rate. Fifty years ago, a more general relationship was proposed, in which cell mass was equal to the initiation mass multiplied by 2 to the power of the ratio of the total time of C and D periods to the doubling time. This relationship has recently been experimentally confirmed by perturbing doubling time, C period, D period, or initiation mass. However, the underlying molecular mechanism remains unclear. Here, we developed a theoretical model for initiator protein DnaA mediating DNA replication initiation in Escherichia coli. We introduced an initiation probability function for competitive binding of DnaA-ATP and DnaA-ADP at oriC. We established a kinetic description of regulatory processes (e.g., expression regulation, titration, inactivation, and reactivation) of DnaA. Cell size as a spatial constraint also participates in the regulation of DnaA. By simulating DnaA kinetics, we obtained a regular DnaA oscillation coordinated with cell cycle and a converged cell size that matches replication initiation frequency to the growth rate. The relationship between the simulated cell size and growth rate, C period, D period, or initiation mass reproduces experimental results. The model also predicts how DnaA number and initiation mass vary with perturbation parameters, comparable with experimental data. The results suggest that 1) when growth rate, C period, or D period changes, the regulation of DnaA determines the invariance of initiation mass; 2) ppGpp inhibition of replication initiation may be important for the growth rate independence of initiation mass because three possible mechanisms therein produce different DnaA dynamics, which is experimentally verifiable; and 3) perturbation of some DnaA regulatory process causes a changing initiation mass or even an abnormal cell cycle. This study may provide clues for concerted control of cell size and cell cycle in synthetic biology.

Functional reconstitution of a bacterial CO2 concentrating mechanism in Escherichia coli

Many photosynthetic organisms employ a CO₂ concentrating mechanism (CCM) to increase the rate of CO₂ fixation via the Calvin cycle. CCMs catalyze ≈50% of global photosynthesis, yet it remains unclear which genes and proteins are required to produce this complex adaptation. We describe the construction of a functional CCM in a non-native host, achieved by expressing genes from an autotrophic bacterium in an Escherichia coli strain engineered to depend on rubisco carboxylation for growth. Expression of 20 CCM genes enabled E. coli to grow by fixing CO₂ from ambient air into biomass, with growth in ambient air depending on the components of the CCM. Bacterial CCMs are therefore genetically compact and readily transplanted, rationalizing their presence in diverse bacteria. Reconstitution enabled genetic experiments refining our understanding of the CCM, thereby laying the groundwork for deeper study and engineering of the cell biology supporting CO₂ assimilation in diverse organisms.

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.

Growth-Optimized Aminoacyl-tRNA Synthetase Levels Prevent Maximal tRNA Charging

Aminoacyl-tRNA synthetases (aaRSs) serve a dual role in charging tRNAs. Their enzymatic activities both provide protein synthesis flux and reduce uncharged tRNA levels. Although uncharged tRNAs can negatively impact bacterial growth, substantial concentrations of tRNAs remain deacylated even under nutrient-rich conditions. Here, we show that tRNA charging in Bacillus subtilis is not maximized due to optimization of aaRS production during rapid growth, which prioritizes demands in protein synthesis over charging levels. The presence of uncharged tRNAs is alleviated by precisely tuned translation kinetics and the stringent response, both insensitive to aaRS overproduction but sharply responsive to underproduction, allowing for just enough aaRS production atop a "fitness cliff." Notably, we find that the stringent response mitigates fitness defects at all aaRS underproduction levels even without external starvation. Thus, adherence to minimal, flux-satisfying protein production drives limited tRNA charging and provides a basis for the sensitivity and setpoints of an integrated growth-control network.

Universal Actuator for Efficient Silencing of Escherichia coli Genes Based on Convergent Transcription Resistant to Rho-Dependent Termination

Dynamic control is a distinguished strategy in modern metabolic engineering, in which inducible convergent transcription is an attractive approach for conditional gene silencing. Instead of a simple strong "reverse" (r-) promoter, a three-component actuator has been developed for constitutive genes silencing. These actuators, consisting of r-promoters with different strengths, the ribosomal transcription antitermination-inducing sequence rrnG-AT, and the RNase III processing site, were inserted into the 3'-UTR of three E. coli metabolic genes. Second and third actuator components were important to improve the effectiveness and robustness of the approach. The maximal silencing folds achieved for gltA, pgi, and ppc were approximately 7, 11, and >100, respectively. Data were analyzed using a simple model that considered RNA polymerase (RNAP) head-on collisions as the unique reason for gene silencing and continued transcription after collision with only one of two molecules. It was previously established that forward (f-) RNAP with a trailing ribosome was approximately 13-times more likely to continue transcription after head-on collision than untrailed r-RNAP which is sensitive to Rho-dependent transcription termination (RhoTT). According to the current results, this bias in complex stabilities decreased to no more than (3.0-5.7)-fold if r-RNAP became resistant to RhoTT. Therefore, the developed constitutive actuator could be considered as an improved tool for controlled gene expression mainly due to the transfer of r-transcription into a state that is resistant to potential termination and used as the basis for the design of tightly regulated actuators for the achievement of conditional silencing.

Stochastic models coupling gene expression and partitioning in cell division in Escherichia coli

Regulation of future RNA and protein numbers is a key process by which cells continuously best fit the environment. In bacteria, RNA and proteins exist in small numbers and their regulatory processes are stochastic. Consequently, there is cell-to-cell variability in these numbers, even between sister cells. Traditionally, the two most studied sources of this variability are gene expression and RNA and protein degradation, with evidence suggesting that the latter is subject to little regulation, when compared to the former. However, time-lapse microscopy and single molecule fluorescent tagging have produced evidence that cell division can also be a significant source of variability due to asymmetries in the partitioning of RNA and proteins. Relevantly, the impact of this noise differs from noise in production and degradation since, unlike these, it is not continuous. Rather, it occurs at specific time points, at which moment it can introduce major fluctuations. Several models have now been proposed that integrate noise from cell division, in addition to noise in gene expression, to mimic the dynamics of RNA and protein numbers of cell lineages. This is expected to be particularly relevant in genetic circuits, where significant fluctuations in one component protein, at specific time moments, are expected to perturb near-equilibrium states of the circuits, which can have long-lasting consequences. Here we review stochastic models coupling these processes in Escherichia coli, from single genes to small circuits.

Positive and Negative Control of Enhancer-Promoter Interactions by Other DNA Loops Generates Specificity and Tunability

Enhancers are ubiquitous and critical gene-regulatory elements. However, quantitative understanding of the role of DNA looping in the regulation of enhancer action and specificity is limited. We used the Escherichia coli NtrC enhancer-σ54 promoter system as an in vivo model, finding that NtrC activation is highly sensitive to the enhancer-promoter (E-P) distance in the 300-6,000 bp range. DNA loops formed by Lac repressor were able to strongly regulate enhancer action either positively or negatively, recapitulating promoter targeting and insulation. A single LacI loop combining targeting and insulation produced a strong shift in specificity for enhancer choice between two σ54 promoters. A combined kinetic-thermodynamic model was used to quantify the effect of DNA-looping interactions on promoter activity and revealed that sensitivity to E-P distance and to control by other loops is itself dependent on enhancer and promoter parameters that may be subject to regulation.

The Impact of Global Transcriptional Regulation on Bacterial Gene Order

Bacterial gene expression depends on the allocation of limited transcriptional resources provided a particular growth rate and growth condition. Early studies in a few genes suggested this global regulation to generate a unifying hyperbolic expression pattern. Here, we developed a large-scale method that generalizes these experiments to quantify the response to growth of over 700 genes that a priori do not exhibit any specific control. We distinguish a core subset following a promoter-specific hyperbolic response. Within this group, we sort genes with regard to their responsiveness to the global regulatory program to show that those with a particularly sensitive linear response are located near the origin of replication. We then find evidence that this genomic architecture is biologically significant by examining position conservation of E. coli genes in 100 bacteria. The response to the transcriptional resources of the cell results in an additional feature contributing to bacterial genome organization.

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Cell physiology determines a global transcriptional regulatory program

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Constitutive genes show a differential response to this global regulation

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The most responsive constitutive genes are located near the origin of replication

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Global transcriptional regulation acts as a gene position conservation force

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.

Heterogeneity coordinates bacterial multi-gene expression in single cells

For a genetically identical microbial population, multi-gene expression in various environments requires effective allocation of limited resources and precise control of heterogeneity among individual cells. However, it is unclear how resource allocation and cell-to-cell variation jointly shape the overall performance. Here we demonstrate a Simpson’s paradox during overexpression of multiple genes: two competing proteins in single cells correlated positively for every induction condition, but the overall correlation was negative. Yet this phenomenon was not observed between two competing mRNAs in single cells. Our analytical framework shows that the phenomenon arises from competition for translational resource, with the correlation modulated by both mRNA and ribosome variability. Thus, heterogeneity plays a key role in single-cell multi-gene expression and provides the population with an evolutionary advantage, as demonstrated in this study.

Microbes perform multitasking for a wide range of purposes, including survival, adaptation, colonization, and evolution. Both modelling and experimental results at the ensemble level reveal trade-offs between different tasks due to resource competition, but it is unclear how single cells allocate limited intracellular resources to perform multitasking, and how does a population coordinate single cell performances during multitasking to maximize population efficiencies. In this study, we address this question by using bacterial multi-gene overexpression as the basic form of multitasking. We discovered and analyzed a statistical phenomenon called Simpson’s paradox, where competing proteins in single cells correlate positively at each constant condition, although the proteins correlate negatively when all conditions are combined. We demonstrate that the phenomenon arises from competition for translational resources, with the correlation modulated by heterogeneity of both mRNA and ribosomes. We further show that heterogeneity coordinates multiple functional modules, conferring an evolutionary advantage on the population. Our work discloses that heterogeneity in the form of Simpson’s paradox is an important phenomenon in coordinating multi-gene expression.

Production of recombinant extracellular cholesterol esterase using consistently active promoters in Burkholderia stabilis

Burkholderia stabilis FERMP-21014 produces highly active cholesterol esterase in the presence of fatty acids. To develop an overexpression system for cholesterol esterase production, we carried out RNA sequencing analyses to screen strongly active promoters in FERMP-21014. Based on gene expression consistency analysis, we selected nine genes that were consistently expressed at high levels, following which we constructed expression vectors using their promoter sequences and achieved overproduction of extracellular cholesterol esterase under fatty acid-free conditions. Of the tested promoters, the promoter of BSFP_0720, which encodes the alkyl hydroperoxide reductase subunit AhpC, resulted in the highest cholesterol esterase activity (24.3 U mL−1). This activity level was 243-fold higher than that of the wild-type strain under fatty acid-free conditions. We confirmed that cholesterol esterase was secreted without excessive accumulation within the cells. The gene expression consistency analysis will be useful to screen promoters applicable to the overexpression of other industrially important enzymes.

Complex genetic and epigenetic regulation deviates gene expression from a unifying global transcriptional program

Environmental or genetic perturbations lead to gene expression changes. While most analyses of these changes emphasize the presence of qualitative differences on just a few genes, we now know that changes are widespread. This large-scale variation has been linked to the exclusive influence of a global transcriptional program determined by the new physiological state of the cell. However, given the sophistication of eukaryotic regulation, we expect to have a complex architecture of specific control affecting this program. Here, we examine this architecture. Using data of Saccharomyces cerevisiae expression in different nutrient conditions, we first propose a five-sector genome partition, which integrates earlier models of resource allocation, as a framework to examine the deviations from the global control. In this scheme, we recognize invariant genes, whose regulation is dominated by physiology, specific genes, which substantially depart from it, and two additional classes that contain the frequently assumed growth-dependent genes. Whereas the invariant class shows a considerable absence of specific regulation, the rest is enriched by regulation at the level of transcription factors (TFs) and epigenetic modulators. We nevertheless find markedly different strategies in how these classes deviate. On the one hand, there are TFs that act in a unique way between partition constituents, and on the other, the action of chromatin modifiers is significantly diverse. The balance between regulatory strategies ultimately modulates the action of the general transcription machinery and therefore limits the possibility of establishing a unifying program of expression change at a genomic scale.

How can we understand expression changes observed as a result of environmental or genetic perturbations? This issue has been conventionally answered by examining small groups of genes whose expression becomes qualitatively altered after these perturbations. But this approach is too simplistic, as we now know that extensive variation is typically observed. To explain this variation, recent works proposed a model in which genome-wide changes are explained by the action of a general program of transcription. Our manuscript reasons that given the complexity of eukaryotic transcriptional control, a unifying program of regulation cannot be achievable. Instead, we propose within an integrated framework of resource allocation that a rich structure of deviations from it exists and that by characterizing these deviations we can fully appreciate large-scale expression change.

WellInverter: a web application for the analysis of fluorescent reporter gene data

Background

Fluorescent reporter genes have become widely used for monitoring gene expression in living cells. When a microbial strain carrying a reporter gene is grown in a microplate reader, the fluorescence and the absorbance (optical density) of the culture can be automatically measured every few minutes in a highly parallelized way. The extraction of useful information from the resulting large amounts of data is not easy to achieve, because the fluorescence and absorbance measurements are only indirectly related to promoter activities and protein concentrations, requiring mathematical models of the expression of reporter genes for their interpretation. Although the principles of the analysis of reporter gene data are well-established today, there is a lack of general-purpose bioinformatics tools based on generic measurement models and sound inference procedures. This has motivated the development of WellInverter, a web application based on well-known methods for regularized linear inversion.

Results

We present a new version of WellInverter that considerably improves the performance and usability of the original application. In particular, we have put in place a parallel computing architecture with a load balancer to distribute analysis queries over several back-end servers, we have completely redesigned the graphical user interface to better support the different analysis steps, and we have developed a plug-in system for the parsing of data files produced by microplate readers from different manufacturers. We illustrate the functioning of WellInverter by analyzing data of the expression of a fluorescent reporter gene controlled by a phage promoter in growing Escherichia coli populations. We show that the expression pattern in different growth media, supporting different growth rates, corresponds to the pattern expected for a constitutive gene.

Conclusions

The new version of WellInverter is a robust, easy-to-use and scalable web application, which has been deployed on two publicly accessible web servers and which can also be installed locally. A demo version of the application with two sample datasets is available on-line.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2920-4) contains supplementary material, which is available to authorized users.

Transcriptional Bursts in a Nonequilibrium Model for Gene Regulation by Supercoiling

We analyze transcriptional bursting within a stochastic nonequilibrium model, which accounts for the coupling between the dynamics of DNA supercoiling and gene transcription. We find a clear signature of bursty transcription when there is a separation between the timescales of transcription initiation and supercoiling dissipation (the latter may either be diffusive or mediated by topological enzymes, such as type I or type II topoisomerases). In multigenic DNA domains, we observe either bursty transcription or transcription waves; the type of behavior can be selected for by controlling gene activity and orientation. In the bursty phase, the statistics of supercoiling fluctuations at the promoter are markedly non-Gaussian.

RNA polymerase pausing at a protein roadblock can enhance transcriptional interference by promoter occlusion

Convergent promoters exert transcriptional interference (TI) by several mechanisms including promoter occlusion, where elongating RNA polymerases (RNAPs) block access to a promoter. Here, we tested whether pausing of RNAPs by obstructive DNA‐bound proteins can enhance TI by promoter occlusion. Using the Lac repressor as a ‘roadblock’ to induce pausing over a target promoter, we found only a small increase in TI, with mathematical modelling suggesting that rapid termination of the stalled RNAP was limiting the occlusion effect. As predicted, the roadblock‐enhanced occlusion was significantly increased in the absence of the Mfd terminator protein. Thus, protein roadblocking of RNAP may cause pause‐enhanced occlusion throughout genomes, and the removal of stalled RNAP may be needed to minimize unwanted TI.

Added value of autoregulation and multi-step kinetics of transcription initiation

Bacterial gene expression regulation occurs mostly during transcription, which has two main rate-limiting steps: the close complex formation, when the RNA polymerase binds to an active promoter, and the subsequent open complex formation, after which it follows elongation. Tuning these steps' kinetics by the action of e.g. transcription factors, allows for a wide diversity of dynamics. For example, adding autoregulation generates single-gene circuits able to perform more complex tasks. Using stochastic models of transcription kinetics with empirically validated parameter values, we investigate how autoregulation and the multi-step transcription initiation kinetics of single-gene autoregulated circuits can be combined to fine-tune steady state mean and cell-to-cell variability in protein expression levels, as well as response times. Next, we investigate how they can be jointly tuned to control complex behaviours, namely, time counting, switching dynamics and memory storage. Overall, our finding suggests that, in bacteria, jointly regulating a single-gene circuit's topology and the transcription initiation multi-step dynamics allows enhancing complex task performance.

A GFP-fusion coupling FACS platform for advancing the metabolic engineering of filamentous fungi

BACKGROUND

The filamentous fungus Trichoderma reesei, the most widely used cellulase producer, also has promising applications in lignocellulose-based biorefinery: consolidated bioprocessing for the production of high value-added products. However, such applications are thwarted by the time-consuming metabolic engineering processes (design-build-test-learn cycle) for T. reesei, resulted from (i) the spore separation-mediated purification as the multinucleate hyphae, (ii) transformant screening for high expression levels since unavailable of episomal expression system, and (iii) cases of inexpressible heterologous proteins.

RESULTS

In this study, a GFP-fusion coupled fluorescence-activated cell sorting (FACS) platform was established to speed up the build and test process of the DBTL cycle, by enabling rapid selection for expressible heterologous genes and bypassing both laborious spore separation and transformant screening. Here, the feasibility of flow cytometry in analyzing and sorting T. reesei cells harboring GFP-fused expressible protein was proven, as well as the application of the platform for constitutive promoter strength evaluation. As a proof-of-concept, the platform was employed to construct the first T. reesei strain producing fatty alcohol, resulting in up to 2 mg hexadecanol being produced per gram biomass. Pathway construction was enabled through rapid selection of functional fatty acyl-CoA reductase encoding gene Tafar1 from three candidate genes and strains with high expression level from spore pools. As a result of using this method, the total costed time for the build and test cycle using T. reesei, subsequently, reduced by approx. 75% from 2 months to 2 weeks.

CONCLUSION

This study established the GFP-fusion coupling FACS platform and the first filamentous fungal fatty alcohol-producing cell factory, and demonstrated versatile applications of the platform in the metabolic engineering of filamentous fungi, which can be harnessed to potentially advance the application of filamentous fungi in lignocellulose-based biorefinery.

Probing Intercell Variability Using Bulk Measurements

The measurement of noise is critical when assessing the design and function of synthetic biological systems. Cell-to-cell variability can be quantified experimentally using single-cell measurement techniques such as flow cytometry and fluorescent microscopy. However, these approaches are costly and impractical for high-throughput parallelized experiments, which are frequently conducted using plate-reader devices. In this paper we describe reporter systems that allow estimation of the cell-to-cell variability in a biological system's output using only measurements of a cell culture's bulk properties. We analyze one potential implementation of such a system that is based upon a fluorescent protein FRET reporter pair, finding that with typical parameters from the literature it is able to reliably estimate variability. We also briefly describe an alternate implementation based upon an activating sRNA circuit. The feasible region of parameter values for which the reporter system can function is assessed, and the dependence of its performance on both extrinsic and intrinsic noise is investigated. Experimental realization of these constructs can yield novel reporter systems that allow measurement of a synthetic gene circuit's output, as well as the intrapopulation variability of this output, at little added cost.

Non-equilibrium phase transition in a model for supercoiling-dependent DNA transcription

We study a variant of a recently proposed non-equilibrium stochastic model for supercoiling-dependent transcription in DNA. In the case of a circular DNA molecule with overall positive supercoiling, we find a non-equilibrium phase transition between an absorbing phase, where all genes are switched off due to the supercoiling, and an active phase with a non-zero transcription rate. Mean field theory predicts that the transition should be continuous at a critical value of the background supercoiling, and we focus our analysis on this case. Our simulations suggest that the switch between the transcribed and silent phases may actually be a fluctuation-induced discontinuous transition, where the jump in the transcription rate decreases with the number of genes in the system.

Rate-limiting steps in transcription dictate sensitivity to variability in cellular components

Cell-to-cell variability in cellular components generates cell-to-cell diversity in RNA and protein production dynamics. As these components are inherited, this should also cause lineage-to-lineage variability in these dynamics. We conjectured that these effects on transcription are promoter initiation kinetics dependent. To test this, first we used stochastic models to predict that variability in the numbers of molecules involved in upstream processes, such as the intake of inducers from the environment, acts only as a transient source of variability in RNA production numbers, while variability in the numbers of a molecular species controlling transcription of an active promoter acts as a constant source. Next, from single-cell, single-RNA level time-lapse microscopy of independent lineages of Escherichia coli cells, we demonstrate the existence of lineage-to-lineage variability in gene activation times and mean RNA production rates, and that these variabilities differ between promoters and inducers used. Finally, we provide evidence that this can be explained by differences in the kinetics of the rate-limiting steps in transcription between promoters and induction schemes. We conclude that cell-to-cell and consequent lineage-to-lineage variability in RNA and protein numbers are both promoter sequence-dependent and subject to regulation.

Modeling sRNA-Regulated Plasmid Maintenance

We study a theoretical model for the toxin-antitoxin (hok/sok) mechanism for plasmid maintenance in bacteria. Toxin-antitoxin systems enforce the maintenance of a plasmid through post-segregational killing of cells that have lost the plasmid. Key to their function is the tight regulation of expression of a protein toxin by an sRNA antitoxin. Here, we focus on the nonlinear nature of the regulatory circuit dynamics of the toxin-antitoxin mechanism. The mechanism relies on a transient increase in protein concentration rather than on the steady state of the genetic circuit. Through a systematic analysis of the parameter dependence of this transient increase, we confirm some known design features of this system and identify new ones: for an efficient toxin-antitoxin mechanism, the synthesis rate of the toxin’s mRNA template should be lower that of the sRNA antitoxin, the mRNA template should be more stable than the sRNA antitoxin, and the mRNA-sRNA complex should be more stable than the sRNA antitoxin. Moreover, a short half-life of the protein toxin is also beneficial to the function of the toxin-antitoxin system. In addition, we study a therapeutic scenario in which a competitor mRNA is introduced to sequester the sRNA antitoxin, causing the toxic protein to be expressed.

Few regulatory metabolites coordinate expression of central metabolic genes in Escherichia coli

Transcription networks consist of hundreds of transcription factors with thousands of often overlapping target genes. While we can reliably measure gene expression changes, we still understand relatively little why expression changes the way it does. How does a coordinated response emerge in such complex networks and how many input signals are necessary to achieve it? Here, we unravel the regulatory program of gene expression in Escherichia coli central carbon metabolism with more than 30 known transcription factors. Using a library of fluorescent transcriptional reporters, we comprehensively quantify the activity of central metabolic promoters in 26 environmental conditions. The expression patterns were dominated by growth rate‐dependent global regulation for most central metabolic promoters in concert with highly condition‐specific activation for only few promoters. Using an approximate mathematical description of promoter activity, we dissect the contribution of global and specific transcriptional regulation. About 70% of the total variance in promoter activity across conditions was explained by global transcriptional regulation. Correlating the remaining specific transcriptional regulation of each promoter with the cell's metabolome response across the same conditions identified potential regulatory metabolites. Remarkably, cyclic AMP, fructose‐1,6‐bisphosphate, and fructose‐1‐phosphate alone explained most of the specific transcriptional regulation through their interaction with the two major transcription factors Crp and Cra. Thus, a surprisingly simple regulatory program that relies on global transcriptional regulation and input from few intracellular metabolites appears to be sufficient to coordinate E. coli central metabolism and explain about 90% of the experimentally observed transcription changes in 100 genes.

Stochastic Model of Supercoiling-Dependent Transcription

We propose a stochastic model for gene transcription coupled to DNA supercoiling, where we incorporate the experimental observation that polymerases create supercoiling as they unwind the DNA helix and that these enzymes bind more favorably to regions where the genome is unwound. Within this model, we show that when the transcriptionally induced flux of supercoiling increases, there is a sharp crossover from a regime where torsional stresses relax quickly and gene transcription is random, to one where gene expression is highly correlated and tightly regulated by supercoiling. In the latter regime, the model displays transcriptional bursts, waves of supercoiling, and up regulation of divergent or bidirectional genes. It also predicts that topological enzymes which relax twist and writhe should provide a pathway to down regulate transcription.

Dissecting the stochastic transcription initiation process in live Escherichia coli

We investigate the hypothesis that, in Escherichia coli, while the concentration of RNA polymerases differs in different growth conditions, the fraction of RNA polymerases free for transcription remains approximately constant within a certain range of these conditions. After establishing this, we apply a standard model-fitting procedure to fully characterize the in vivo kinetics of the rate-limiting steps in transcription initiation of the Plac/ara-1 promoter from distributions of intervals between transcription events in cells with different RNA polymerase concentrations. We find that, under full induction, the closed complex lasts ∼788 s while subsequent steps last ∼193 s, on average. We then establish that the closed complex formation usually occurs multiple times prior to each successful initiation event. Furthermore, the promoter intermittently switches to an inactive state that, on average, lasts ∼87 s. This is shown to arise from the intermittent repression of the promoter by LacI. The methods employed here should be of use to resolve the rate-limiting steps governing the in vivo dynamics of initiation of prokaryotic promoters, similar to established steady-state assays to resolve the in vitro dynamics.

Characterization of a natural triple-tandem c-di-GMP riboswitch and application of the riboswitch-based dual-fluorescence reporter

c-di-GMP riboswitches are structured RNAs located in the 5'-untranslated regions (5'-UTRs) of mRNAs that regulate expression of downstream genes in response to changing concentrations of the second messenger c-di-GMP. We discovered three complete c-di-GMP riboswitches (Bc3, Bc4 and Bc5 RNA) with similar structures, which are arranged in tandem to constitute a triple-tandem (Bc3-5 RNA) riboswitch in the 5'-UTR of the cspABCDE mRNA in Bacillus thuringiensis subsp. chinensis CT-43. Our results showed that this natural triple-tandem riboswitch controlled the expression of the reporter gene more stringently and digitally than the double-tandem or single riboswitch. A sandwich-like dual-fluorescence reporter was further constructed by fusing the Bc3-5 RNA gene between the two fluorescence protein genes amcyan and turborfp. This reporter strain was found to exhibit detectable fluorescence color changes under bright field in response to intracellular c-di-GMP level altered by induced expression of diguanylate cyclase (DGC) PleD. Using this system, two putative membrane-bound DGCs from B. thuringiensis and Xanthomonas oryzae were verified to be functional by replacing pleD with the corresponding DGC genes. This report represented the first native triple-tandem riboswitch that was applied to serve as a riboswitch-based dual-fluorescence reporter for the efficient and convenient verification of putative DGC activity in vivo.

Characterization of Intrinsic Properties of Promoters

Accurate characterization of promoter behavior is essential for the rational design of functional synthetic transcription networks such as logic gates and oscillators. However, transcription rates observed from promoters can vary significantly depending on the growth rate of host cells and the experimental and genetic contexts of the measurement. Furthermore, in vivo measurement methods must accommodate variation in translation, protein folding, and maturation rates of reporter proteins, as well as metabolic load. The external factors affecting transcription activity may be considered to be extrinsic, and the goal of characterization should be to obtain quantitative measures of the intrinsic characteristics of promoters. We have developed a promoter characterization method that is based on a mathematical model for cell growth and reporter gene expression and exploits multiple in vivo measurements to compensate for variation due to extrinsic factors. First, we used optical density and fluorescent reporter gene measurements to account for the effect of differing cell growth rates. Second, we compared the output of reporter genes to that of a control promoter using concurrent dual-channel fluorescence measurements. This allowed us to derive a quantitative promoter characteristic (ρ) that provides a robust measure of the intrinsic properties of a promoter, relative to the control. We imposed different extrinsic factors on growing cells, altering carbon source and adding bacteriostatic agents, and demonstrated that the use of ρ values reduced the fraction of variance due to extrinsic factors from 78% to less than 4%. This is a simple and reliable method to quantitatively describe promoter properties.

Antisense transcription as a tool to tune gene expression

A surprise that has emerged from transcriptomics is the prevalence of genomic antisense transcription, which occurs counter to gene orientation. While frequent, the roles of antisense transcription in regulation are poorly understood. We built a synthetic system in Escherichia coli to study how antisense transcription can change the expression of a gene and tune the response characteristics of a regulatory circuit. We developed a new genetic part that consists of a unidirectional terminator followed by a constitutive antisense promoter and demonstrate that this part represses gene expression proportionally to the antisense promoter strength. Chip‐based oligo synthesis was applied to build a large library of 5,668 terminator–promoter combinations that was used to control the expression of three repressors (PhlF, SrpR, and TarA) in a simple genetic circuit (NOT gate). Using the library, we demonstrate that antisense promoters can be used to tune the threshold of a regulatory circuit without impacting other properties of its response function. Finally, we determined the relative contributions of antisense RNA and transcriptional interference to repressing gene expression and introduce a biophysical model to capture the impact of RNA polymerase collisions on gene repression. This work quantifies the role of antisense transcription in regulatory networks and introduces a new mode to control gene expression that has been previously overlooked in genetic engineering.

Strength and Regulation of Seven rRNA Promoters in Escherichia coli

The model prokaryote Escherichia coli contains seven copies of the rRNA operon in the genome. The presence of multiple rRNA operons is an advantage for increasing the level of ribosome, the key apparatus of translation, in response to environmental conditions. The complete sequence of E. coli genome, however, indicated the micro heterogeneity between seven rRNA operons, raising the possibility in functional heterogeneity and/or differential mode of expression. The aim of this research is to determine the strength and regulation of the promoter of each rRNA operon in E. coli. For this purpose, we used the double-fluorescent protein reporter pBRP system that was developed for accurate and precise determination of the promoter strength of protein-coding genes. For application of this promoter assay vector for measurement of the rRNA operon promoters devoid of the signal for translation, a synthetic SD sequence was added at the initiation codon of the reporter GFP gene, and then approximately 500 bp-sequence upstream each 16S rRNA was inserted in front of this SD sequence. Using this modified pGRS system, the promoter activity of each rrn operon was determined by measuring the rrn promoter-directed GFP and the reference promoter-directed RFP fluorescence, both encoded by a single and the same vector. Results indicated that: the promoter activity was the highest for the rrnE promoter under all growth conditions analyzed, including different growth phases of wild-type E. coli grown in various media; but the promoter strength of other six rrn promoters was various depending on the culture conditions. These findings altogether indicate that seven rRNA operons are different with respect to the regulation mode of expression, conferring an advantage to E. coli through a more fine-tuned control of ribosome formation in a wide range of environmental situations. Possible difference in the functional role of each rRNA operon is also discussed.

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].

Cis-Antisense Transcription Gives Rise to Tunable Genetic Switch Behavior: A Mathematical Modeling Approach

Antisense transcription has been extensively recognized as a regulatory mechanism for gene expression across all kingdoms of life. Despite the broad importance and extensive experimental determination of cis-antisense transcription, relatively little is known about its role in controlling cellular switching responses. Growing evidence suggests the presence of non-coding cis-antisense RNAs that regulate gene expression via antisense interaction. Recent studies also indicate the role of transcriptional interference in regulating expression of neighboring genes due to traffic of RNA polymerases from adjacent promoter regions. Previous models investigate these mechanisms independently, however, little is understood about how cells utilize coupling of these mechanisms in advantageous ways that could also be used to design novel synthetic genetic devices. Here, we present a mathematical modeling framework for antisense transcription that combines the effects of both transcriptional interference and cis-antisense regulation. We demonstrate the tunability of transcriptional interference through various parameters, and that coupling of transcriptional interference with cis-antisense RNA interaction gives rise to hypersensitive switches in expression of both antisense genes. When implementing additional positive and negative feed-back loops from proteins encoded by these genes, the system response acquires a bistable behavior. Our model shows that combining these multiple-levels of regulation allows fine-tuning of system parameters to give rise to a highly tunable output, ranging from a simple-first order response to biologically complex higher-order response such as tunable bistable switch. We identify important parameters affecting the cellular switch response in order to provide the design principles for tunable gene expression using antisense transcription. This presents an important insight into functional role of antisense transcription and its importance towards design of synthetic biological switches.

Constitutive expression of Campylobacter jejuni truncated hemoglobin CtrHb improves the growth of Escherichia coli cell under aerobic and anaerobic conditions

Bacteria hemoglobin could bind to the oxygen, transfer it from the intracellular microenvironment to the respiration process and sustain the energy for the metabolism and reproduction of cells. Heterologous expression of bacteria hemoglobin gene could improve the capacity of the host on oxygen-capturing and allow it to grow even under microaerophilic condition. To develop a system based on hemoglobin to help bacteria cells overcome the oxygen shortage in fermentation, in this study, Campylobacter jejuni truncated hemoglobin (CtrHb) gene was synthesized and expressed under the control of constitutive expression promoters P2 and P(SPO1-II) in Escherichia coli. As showed by the growth curves of the two recombinants P2-CtrHb and P(SPO1-II)-CtrHb, constitutive expression of CtrHb improved cell growth under aerobic shaking-flasks, anaerobic capped-bottles and bioreactor conditions. According to the NMR analysis, this improvement might come from the expression of hemoglobin which could boost the metabolism of cells by supplying more oxygen to the respiratory chain processes. Through semi-quantitative RT-PCR and CO differential spectrum assays, we further discussed the connection between the growth patterns of the recombinants, the expression level of CtrHb and oxygen binding capacity of CtrHb in cells. Based on the growth patterns of these recombinants in bioreactor, a possible choice on different type of recombinants under specific fermentation conditions was also suggested in this study.

Distinct Paths for Basic Amino Acid Export in Escherichia coli: YbjE (LysO) Mediates Export of L-Lysine

In Escherichia coli, argO encodes an exporter for L-arginine (Arg) and its toxic analogue canavanine (CAN), and its transcriptional activation and repression, by Arg and L-lysine (Lys), respectively, are mediated by the regulator ArgP. Accordingly argO and argP mutants are CAN supersensitive (CAN(ss)). We report the identification of ybjE as a gene encoding a predicted inner membrane protein that mediates export of Lys, and our results confirm the previous identification with a different approach of YbjE as a Lys exporter, reported by Ueda and coworkers (T. Ueda, Y. Nakai, Y. Gunji, R. Takikawa, and Y. Joe, U.S. patents 7,629,142 B2 [December 2009] and 8,383,363 B1 [February 2013] and European patent 1,664,318 B1 [September 2009]). ybjE was isolated as a multicopy suppressor of the CAN(ss) phenotype of a strain lacking ArgO. The absence of YbjE did not confer a CAN(ss) phenotype but instead conferred hypersensitivity to the lysine antimetabolite thialysine and led to growth inhibition by the dipeptide lysylalanine, which is associated with elevated cellular Lys content. YbjE overproduction resulted in Lys excretion and syntrophic cross-feeding of a Lys auxotroph. Constitutive overexpression of argO promoted Lys cross-feeding that is indicative of a latent Lys export potential of ArgO. Arg modestly repressed ybjE transcription in an ArgR-dependent manner, and ArgR displayed Arg-sensitive binding to the ybjE promoter region in vitro. Our studies suggest that the reciprocal repression of argO and ybjE, respectively, by Lys and Arg confers the specificity for basic amino acid export by distinct paths and that such cross-repression contributes to maintenance of cytoplasmic Arg/Lys balance. We propose that YbjE be redesignated LysO.

IMPORTANCE

This work ascribes a lysine export function to the product of the ybjE gene of Escherichia coli, leading to a physiological scenario wherein two proteins, ArgO and YbjE, perform the task of separately exporting arginine and lysine, respectively, which is distinct from that seen for Corynebacterium glutamicum, where the ortholog of ArgO, LysE, mediates export of both arginine and lysine. Repression of argO transcription by lysine is thought to effect this separation. Accordingly, ArgO mediates lysine export when repression of its transcription by lysine is bypassed. Repression of ybjE transcription by arginine via the ArgR repressor, together with the lysine repression of argO effected by ArgP, is indicative of a mechanism of maintenance of arginine/lysine balance in E. coli.

Microbial biofilm as a smart material

Microbial biofilm colonies will in many cases form a smart material capable of responding to external threats dependent on their size and internal state. The microbial community accordingly switches between passive, protective, or attack modes of action. In order to decide which strategy to employ, it is essential for the biofilm community to be able to sense its own size. The sensor designed to perform this task is termed a quorum sensor, since it only permits collective behaviour once a sufficiently large assembly of microbes have been established. The generic quorum sensor construct involves two genes, one coding for the production of a diffusible signal molecule and one coding for a regulator protein dedicated to sensing the signal molecules. A positive feedback in the signal molecule production sets a well-defined condition for switching into the collective mode. The activation of the regulator involves a slow dimerization, which allows low-pass filtering of the activation of the collective mode. Here, we review and combine the model components that form the basic quorum sensor in a number of Gram-negative bacteria, e.g., Pseudomonas aeruginosa.

Inference of quantitative models of bacterial promoters from time-series reporter gene data

The inference of regulatory interactions and quantitative models of gene regulation from time-series transcriptomics data has been extensively studied and applied to a range of problems in drug discovery, cancer research, and biotechnology. The application of existing methods is commonly based on implicit assumptions on the biological processes under study. First, the measurements of mRNA abundance obtained in transcriptomics experiments are taken to be representative of protein concentrations. Second, the observed changes in gene expression are assumed to be solely due to transcription factors and other specific regulators, while changes in the activity of the gene expression machinery and other global physiological effects are neglected. While convenient in practice, these assumptions are often not valid and bias the reverse engineering process. Here we systematically investigate, using a combination of models and experiments, the importance of this bias and possible corrections. We measure in real time and in vivo the activity of genes involved in the FliA-FlgM module of the E. coli motility network. From these data, we estimate protein concentrations and global physiological effects by means of kinetic models of gene expression. Our results indicate that correcting for the bias of commonly-made assumptions improves the quality of the models inferred from the data. Moreover, we show by simulation that these improvements are expected to be even stronger for systems in which protein concentrations have longer half-lives and the activity of the gene expression machinery varies more strongly across conditions than in the FliA-FlgM module. The approach proposed in this study is broadly applicable when using time-series transcriptome data to learn about the structure and dynamics of regulatory networks. In the case of the FliA-FlgM module, our results demonstrate the importance of global physiological effects and the active regulation of FliA and FlgM half-lives for the dynamics of FliA-dependent promoters.

A wide variety of methods for the reverse engineering of regulatory networks and the identification of quantitative regulation functions are available. We investigate some common assumptions that are made in the application of these methods to time-series transcriptomics data, in the context of a central module in the motility network of E. coli. We show that these assumptions, which hypothesize that mRNA concentrations are good proxies for protein concentrations and that the gene expression machinery is equally active across different physiological conditions, are often not valid and may lead to biased inference results. We also show how models of gene expression can be used in combination with suitable experimental controls to correct for this bias and improve the inference process. The contribution of our work is thus not the addition of another method to the rich store of available reverse engineering algorithms, but lies in the critical examination of the information provided by the experimental data and new ways to exploit this information in the algorithms. The proposed approach is relevant for a wide range of applications using time-series transcriptomics data. For the motility system under study, it has underlined the importance of global physiological effects, the active degradation of the transcription factor FliA as well as the secretion of the anti-sigma factor FlgM for the network dynamics.

A dual reporter system for detecting RNA interactions in bacterial cells

Detecting RNA-partner interactions in cells is often difficult due to a lack of suitable tools. Here we describe a dual reporter system capable of detecting intracellular interactions in which one of the partners is an RNA. The system utilizes two fluorescent proteins with similar maturation rates but distinct spectral properties, specifically cyan fluorescent protein (CFP) and yellow fluorescent protein (YFP). By placing the CFP gene upstream and the YFP gene downstream of an RNA gene of interest, the production of YFP becomes sensitive to RNA-partner interaction, whereas the synthesis of CFP is not disturbed. Therefore, the RNA-partner interaction can be simply measured by the change in the ratio of fluorescence of YFP over CFP. The utility of our approach is demonstrated through verification of three known RNA-partner interactions in the model bacterium Escherichia coli. Our two-reporter strategy should be broadly useful to the study of RNA-targeted interactions in bacteria.

Stochastic cellular fate decision making by multiple infecting lambda phage

Bacteriophage lambda is a classic system for the study of cellular decision making. Both experiments and mathematical models have demonstrated the importance of viral concentration in the lysis-lysogeny decision outcome in lambda phage. However, a recent experimental study using single cell and single phage resolution reported that cells with the same viral concentrations but different numbers of infecting phage (multiplicity of infection) can have markedly different rates of lysogeny. Thus the decision depends on not only viral concentration, but also directly on the number of infecting phage. Here, we attempt to provide a mechanistic explanation of these results using a simple stochastic model of the lambda phage genetic network. Several potential factors including intrinsic gene expression noise, spatial dynamics and cell-cycle effects are investigated. We find that interplay between the level of intrinsic noise and viral protein decision threshold is a major factor that produces dependence on multiplicity of infection. However, simulations suggest spatial segregation of phage particles does not play a significant role. Cellular image processing is used to re-analyse the original time-lapse movies from the recent study and it is found that higher numbers of infecting phage reduce the cell elongation rate. This could also contribute to the observed phenomena as cellular growth rate can affect transcription rates. Our model further predicts that rate of lysogeny is dependent on bacterial growth rate, which can be experimentally tested. Our study provides new insight on the mechanisms of individual phage decision making. More generally, our results are relevant for the understanding of gene-dosage compensation in cellular systems.