Stochastic pulse regulation in bacterial stress response

Fluid flow drives phenotypic heterogeneity in bacterial growth and adhesion on surfaces

Bacteria often thrive in surface-attached communities, where they can form biofilms affording them multiple advantages. In this sessile form, fluid flow is a key component of their environments, renewing nutrients and transporting metabolic products and signaling molecules. It also controls colonization patterns and growth rates on surfaces, through bacteria transport, attachment and detachment. However, the current understanding of bacterial growth on surfaces neglects the possibility that bacteria may modulate their division behavior as a response to flow. Here, we employed single-cell imaging in microfluidic experiments to demonstrate that attached Escherichia coli cells can enter a growth arrest state while simultaneously enhancing their adhesion underflow. Despite utilizing clonal populations, we observed a non-uniform response characterized by bistable dynamics, with co-existing subpopulations of non-dividing and actively dividing bacteria. As the proportion of non-dividing bacteria increased with the applied flow rate, it resulted in a reduction in the average growth rate of bacterial populations on flow-exposed surfaces. Dividing bacteria exhibited asymmetric attachment, whereas non-dividing counterparts adhered to the surface via both cell poles. Hence, this phenotypic diversity allows bacterial colonies to combine enhanced attachment with sustained growth, although at a reduced rate, which may be a significant advantage in fluctuating flow conditions.

Variability in cell division among anatomical sites shapes Escherichia coli antibiotic survival in a urinary tract infection mouse model

Urinary tract infection (UTI), mainly caused by Escherichia coli, are frequent and have a recurrent nature even after antibiotic treatment. Potential bacterial escape mechanisms include growth defects, but probing bacterial division in vivo and establishing its relation to the antibiotic response remain challenging. Using a synthetic reporter of cell division, we follow the temporal dynamics of cell division for different E. coli clinical strains in a UTI mouse model with and without antibiotics. We show that more bacteria are actively dividing in the kidneys and urine compared with the bladder. Bacteria that survive antibiotic treatment are consistently non-dividing in three sites of infection. Additionally, we demonstrate how both the strain in vitro persistence profile and the microenvironment impact infection and treatment dynamics. Understanding the relative contribution of the host environment, growth heterogeneity, non-dividing bacteria, and antibiotic persistence is crucial to improve therapies for recurrent infections.

The RsfSR two-component system regulates SigF function by monitoring the state of the respiratory electron transport chain in Mycobacterium smegmatis

In Mycobacterium smegmatis, the transcriptional activity of the alternative sigma factor SigF is posttranslationally regulated by the partner switching system consisting of SigF, the anti-SigF RsbW1, and three anti-SigF antagonists (RsfA, RsfB, and RsbW3). We previously demonstrated that expression of the SigF regulon is strongly induced in the Δaa3 mutant of M. smegmatis lacking the aa3 cytochrome c oxidase, the major terminal oxidase in the respiratory electron transport chain. Here, we identified and characterized the RsfSR two-component system involved in regulating the phosphorylation state of the major anti-SigF antagonist RsfB. RsfS (MSMEG_6130) is a histidine kinase with the cyclase/histidine kinase-associated sensing extracellular 3 domain at its N terminus, and RsfR (MSMEG_6131) is a receiver domain-containing protein phosphatase 2C-type phosphatase that can dephosphorylate phosphorylated RsfB. We demonstrated that phosphorylation of RsfR on Asp74 by RsfS reduces the phosphatase activity of RsfR toward phosphorylated RsfB and that the cellular abundance of the active unphosphorylated RsfB is increased in the Δaa3 mutant relative to the WT strain. We also demonstrated that the RsfSR two-component system is required for induction of the SigF regulon under respiration-inhibitory conditions such as inactivation of the cytochrome bcc1 complex and aa3 cytochrome c oxidase, as well as hypoxia, electron donor-limiting, high ionic strength, and low pH conditions. Collectively, our results reveal a key regulatory element involved in regulating the SigF signaling system by monitoring the state of the respiratory electron transport chain.

Bacterial phenotypic heterogeneity through the lens of single-cell RNA sequencing

Bacterial transcription is not monolithic. Microbes exist in a wide variety of cell states that help them adapt to their environment, acquire and produce essential nutrients, and engage in both competition and cooperation with their neighbors. While we typically think of bacterial adaptation as a group behavior, where all cells respond in unison, there is often a mixture of phenotypic responses within a bacterial population, where distinct cell types arise. A primary phenomenon driving these distinct cell states is transcriptional heterogeneity. Given that bacterial mRNA transcripts are extremely short-lived compared to eukaryotes, their transcriptional state is closely associated with their physiology, and thus the transcriptome of a bacterial cell acts as a snapshot of the behavior of that bacterium. Therefore, the application of single-cell transcriptomics to microbial populations will provide novel insight into cellular differentiation and bacterial ecology. In this review, we provide an overview of transcriptional heterogeneity in microbial systems, discuss the findings already provided by single-cell approaches, and plot new avenues of inquiry in transcriptional regulation, cellular biology, and mechanisms of heterogeneity that are made possible when microbial communities are analyzed at single-cell resolution.

De novo hematopoietic (stem) cell generation - A differentiation or stochastic process?

The hematopoietic system is one of the earliest tissues to develop. De novo generation of hematopoietic progenitor and stem cells occurs through a transdifferentiation of (hemogenic) endothelial cells to hematopoietic identity, resulting in the formation of intra-aortic hematopoietic cluster (IAHC) cells. Heterogeneity of IAHC cell phenotypes and functions has stymied the field in its search for the transcriptional program of emerging hematopoietic stem cells (HSCs), given that an individual IAHC cannot be simultaneously examined for function and transcriptome. Several models could account for this heterogeneity, including a novel model suggesting that the transcriptomes of individual emerging IAHC cells are in an unstable/metastable state, with pivotal hematopoietic transcription factors expressed dynamically due to transcriptional pulsing and combinatorial activities. The question remains - how is functional hematopoietic cell fate established - is the process stochastic? This article touches upon these important issues, which may be relevant to the field's inability to make HSCs ex vivo.

The σB alternative sigma factor circuit modulates noise to generate different types of pulsing dynamics

Single-cell approaches are revealing a high degree of heterogeneity, or noise, in gene expression in isogenic bacteria. How gene circuits modulate this noise in gene expression to generate robust output dynamics is unclear. Here we use the Bacillus subtilis alternative sigma factor σB as a model system for understanding the role of noise in generating circuit output dynamics. σB controls the general stress response in B. subtilis and is activated by a range of energy and environmental stresses. Recent single-cell studies have revealed that the circuit can generate two distinct outputs, stochastic pulsing and a single pulse response, but the conditions under which each response is generated are under debate. We implement a stochastic mathematical model of the σB circuit to investigate this and find that the system's core circuit can generate both response types. This is despite one response (stochastic pulsing) being stochastic in nature, and the other (single response pulse) being deterministic. We demonstrate that the main determinant for whichever response is generated is the degree with which the input pathway activates the core circuit, although the noise properties of the input pathway also biases the system towards one or the other type of output. Thus, our work shows how stochastic modelling can reveal the mechanisms behind non-intuitive gene circuit output dynamics.

gUMI-BEAR, a modular, unsupervised population barcoding method to track variants and evolution at high resolution

Cellular lineage tracking provides a means to observe population makeup at the clonal level, allowing exploration of heterogeneity, evolutionary and developmental processes and individual clones' relative fitness. It has thus contributed significantly to understanding microbial evolution, organ differentiation and cancer heterogeneity, among others. Its use, however, is limited because existing methods are highly specific, expensive, labour-intensive, and, critically, do not allow the repetition of experiments. To address these issues, we developed gUMI-BEAR (genomic Unique Molecular Identifier Barcoded Enriched Associated Regions), a modular, cost-effective method for tracking populations at high resolution. We first demonstrate the system's application and resolution by applying it to track tens of thousands of Saccharomyces cerevisiae lineages growing together under varying environmental conditions applied across multiple generations, revealing fitness differences and lineage-specific adaptations. Then, we demonstrate how gUMI-BEAR can be used to perform parallel screening of a huge number of randomly generated variants of the Hsp82 gene. We further show how our method allows isolation of variants, even if their frequency in the population is low, thus enabling unsupervised identification of modifications that lead to a behaviour of interest.

Regulation by cyclic di-GMP attenuates dynamics and enhances robustness of bimodal curli gene activation in Escherichia coli

Curli amyloid fibers are a major constituent of the extracellular biofilm matrix formed by bacteria of the Enterobacteriaceae family. Within Escherichia coli biofilms, curli gene expression is limited to a subpopulation of bacteria, leading to heterogeneity of extracellular matrix synthesis. Here we show that bimodal activation of curli gene expression also occurs in well-mixed planktonic cultures of E. coli, resulting in all-or-none stochastic differentiation into distinct subpopulations of curli-positive and curli-negative cells at the entry into the stationary phase of growth. Stochastic curli activation in individual E. coli cells could further be observed during continuous growth in a conditioned medium in a microfluidic device, which further revealed that the curli-positive state is only metastable. In agreement with previous reports, regulation of curli gene expression by the second messenger c-di-GMP via two pairs of diguanylate cyclase and phosphodiesterase enzymes, DgcE/PdeH and DgcM/PdeR, modulates the fraction of curli-positive cells. Unexpectedly, removal of this regulatory network does not abolish the bimodality of curli gene expression, although it affects dynamics of activation and increases heterogeneity of expression levels among individual cells. Moreover, the fraction of curli-positive cells within an E. coli population shows stronger dependence on growth conditions in the absence of regulation by DgcE/PdeH and DgcM/PdeR pairs. We thus conclude that, while not required for the emergence of bimodal curli gene expression in E. coli, this c-di-GMP regulatory network attenuates the frequency and dynamics of gene activation and increases its robustness to cellular heterogeneity and environmental variation.

Resonant learning in scale-free networks

Large networks of interconnected components, such as genes or machines, can coordinate complex behavioral dynamics. One outstanding question has been to identify the design principles that allow such networks to learn new behaviors. Here, we use Boolean networks as prototypes to demonstrate how periodic activation of network hubs provides a network-level advantage in evolutionary learning. Surprisingly, we find that a network can simultaneously learn distinct target functions upon distinct hub oscillations. We term this emergent property resonant learning, as the new selected dynamical behaviors depend on the choice of the period of the hub oscillations. Furthermore, this procedure accelerates the learning of new behaviors by an order of magnitude faster than without oscillations. While it is well-established that modular network architecture can be selected through evolutionary learning to produce different network behaviors, forced hub oscillations emerge as an alternative evolutionary learning strategy for which network modularity is not necessarily required.

Navigating Environmental Transitions: the Role of Phenotypic Variation in Bacterial Responses

The ability of bacteria to respond to changes in their environment is critical to their survival, allowing them to withstand stress, form complex communities, and induce virulence responses during host infection. A remarkable feature of many of these bacterial responses is that they are often variable across individual cells, despite occurring in an isogenic population exposed to a homogeneous environmental change, a phenomenon known as phenotypic heterogeneity. Phenotypic heterogeneity can enable bet-hedging or division of labor strategies that allow bacteria to survive fluctuating conditions. Investigating the significance of phenotypic heterogeneity in environmental transitions requires dynamic, single-cell data. Technical advances in quantitative single-cell measurements, imaging, and microfluidics have led to a surge of publications on this topic. Here, we review recent discoveries on single-cell bacterial responses to environmental transitions of various origins and complexities, from simple diauxic shifts to community behaviors in biofilm formation to virulence regulation during infection. We describe how these studies firmly establish that this form of heterogeneity is prevalent and a conserved mechanism by which bacteria cope with fluctuating conditions. We end with an outline of current challenges and future directions for the field. While it remains challenging to predict how an individual bacterium will respond to a given environmental input, we anticipate that capturing the dynamics of the process will begin to resolve this and facilitate rational perturbation of environmental responses for therapeutic and bioengineering purposes.

Bacillus subtilis Stressosome Sensor Protein Sequences Govern the Ability To Distinguish among Environmental Stressors and Elicit Different σB Response Profiles

Bacteria use a variety of systems to sense stress and mount an appropriate response to ensure fitness and survival. Bacillus subtilis uses stressosomes-cytoplasmic multiprotein complexes-to sense environmental stressors and enact the general stress response by activating the alternative sigma factor σ^B. Each stressosome includes 40 RsbR proteins, representing four paralogous (RsbRA, RsbRB, RsbRC, and RsbRD) putative stress sensors. Population-level analyses suggested that the RsbR paralogs are largely redundant, while our prior work using microfluidics-coupled fluorescence microscopy uncovered differences among the RsbR paralogs' σ^B response profiles with respect to timing and intensity when facing an identical stressor. Here, we use a similar approach to address the question of whether the σ^B responses mediated by each paralog differ in the presence of different environmental stressors: can they distinguish among stressors? Wild-type cells (with all four paralogs) and RsbRA-only cells activate σ^B with characteristic transient response timing irrespective of stressor but show various response magnitudes. However, cells with other individual RsbR paralogs show distinct timing and magnitude in their responses to ethanol, salt, oxidative, and acid stress, implying that RsbR proteins can distinguish among stressors. Experiments with hybrid fusion proteins comprising the N-terminal half of one paralog and the C-terminal half of another argue that the N-terminal identity influences response magnitude and that determinants in both halves of RsbRA are important for its stereotypical transient σ^B response timing. IMPORTANCE Bacterial survival depends on appropriate responses to diverse stressors. The general stress-response system in the environmental model bacterium Bacillus subtilis is constantly poised for an immediate response and uses unusual stress-sensing protein complexes called stressosomes. Stressosomes typically contain four different types of putative sensing protein. We asked whether each type of sensor has a distinct role in mediating response dynamics to different environmental stressors. We find that one sensor type always mediates a transient response, while the others show distinct response magnitude and timing to different stressors. We also find that a transient response is exceptional, as several engineered hybrid proteins did not show strong transient responses. Our work reveals functional distinctions among subunits of the stressosome complex and represents a step toward understanding how the general stress response of B. subtilis ensures its survival in natural environmental settings.

Impact of nutrients on the function of the chlamydial Rsb partner switching mechanism

The obligate intracellular bacterial pathogen Chlamydia trachomatis is a leading cause of sexually transmitted infections and infectious blindness. Chlamydia undergo a biphasic developmental cycle alternating between the infectious elementary body (EB) and the replicative reticulate body (RB). The molecular mechanisms governing RB growth and RB-EB differentiation are unclear. We hypothesize that the bacterium senses host cell and bacterial energy levels and metabolites to ensure that development and growth coincide with nutrient availability. We predict that a partner switching mechanism (PSM) plays a key role in the sensing and response process acting as a molecular throttle sensitive to metabolite levels. Using purified wild type and mutant PSM proteins, we discovered that metal type impacts enzyme activity and the substrate specificity of RsbU and that RsbW prefers ATP over GTP as a phosphate donor. Immunoblotting analysis of RsbV1/V2 demonstrated the presence of both proteins beyond 20 hours post infection and we observed that an RsbV1-null strain has a developmental delay and exhibits differential growth attenuation in response to glucose levels. Collectively, our data support that the PSM regulates growth in response to metabolites and further defines biochemical features governing PSM-component interactions which could help in the development of novel PSM-targeted therapeutics.

Quantitative Aspect of Bacillus subtilis σB Regulatory Network-A Computational Simulation

Bacillus subtilis is a model organism used to study molecular processes in prokaryotic cells. Sigma factor B, which associates with RNA polymerase, is one of the transcriptional regulators involved in the cell's response to environmental stress. This study addresses the key question of how the levels of free SigB, which acts as the actual regulator of gene expression, are controlled. A set of chemical equations describing the network controlling the levels of free SigB was designed, leading to a set of differential equations quantifying the dynamics of the network. Utilizing a microarray-measured gene expression time series then allowed the simulation of the kinetic behavior of the network in real conditions and investigation of the role of phosphatases RsbU/RsbP transmitting the environmental signal and controlling the amounts of free SigB. Moreover, the role of kinetic constants controlling the formation of the molecular complexes, which consequently influence the amount of free SigB, was investigated. The simulation showed that although the total amount of sigma B is relatively high in the unstressed population, the amount of free SigB, which actually controls its regulon, is quite low. The simulation also allowed determination of the proportion of all the network members that were free or bound in complexes. While previously the qualitative features of B. subtilis SigB have been studied in detail, the kinetics of the network have mostly been ignored. In summary, the computational results based on experimental data provide a quantitative insight into the functioning of the SigB-dependent circuit and provide a roadmap for its further exploration in this industrially important bacterium.

Optimal transcriptional regulation of dynamic bacterial responses to sudden drug exposures

Cellular responses to the presence of toxic compounds in their environment require prompt expression of the correct levels of the appropriate enzymes, which are typically regulated by transcription factors that control gene expression for the duration of the response. The characteristics of each response dictate the choice of regulatory parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about the dynamics of cellular responses, we still lack a framework to understand how different regulatory strategies evolved in natural systems relate to the selective pressures acting in each particular case. Here, we analyze a dynamical model of a typical antibiotic response in bacteria, where a transcriptionally repressed enzyme is induced by a sudden exposure to the drug that it processes. We identify strategies of gene regulation that optimize this response for different types of selective pressures, which we define as a set of costs associated with the drug, enzyme, and repressor concentrations during the response. We find that regulation happens in a limited region of the regulatory parameter space. While responses to more costly (toxic) drugs favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly favor the usage of constitutively expressed repressors. Only a very narrow range of selective pressures favor weakly self-regulated repressors. We use this framework to determine which costs and benefits are most critical for the evolution of a variety of natural cellular responses that satisfy the approximations in our model and to analyze how regulation is optimized in new environments with different demands.

Cost-efficient boundary-free surface patterning achieves high effective-throughput of time-lapse microscopy experiments

Time-lapse microscopy plays critical roles in the studies of cellular dynamics. However, setting up a time-lapse movie experiments is not only laborious but also with low output, mainly due to the cell-losing problem (i.e., cells moving out of limited field of view), especially in a long-time recording. To overcome this issue, we have designed a cost-efficient way that enables cell patterning on the imaging surfaces without any physical boundaries. Using mouse embryonic stem cells as an example system, we have demonstrated that our boundary-free patterned surface solves the cell-losing problem without disturbing their cellular phenotype. Statistically, the presented system increases the effective-throughput of time-lapse microscopy experiments by an order of magnitude.

Microfluidics for long-term single-cell time-lapse microscopy: Advances and applications

Cells are inherently dynamic, whether they are responding to environmental conditions or simply at equilibrium, with biomolecules constantly being made and destroyed. Due to their small volumes, the chemical reactions inside cells are stochastic, such that genetically identical cells display heterogeneous behaviors and gene expression profiles. Studying these dynamic processes is challenging, but the development of microfluidic methods enabling the tracking of individual prokaryotic cells with microscopy over long time periods under controlled growth conditions has led to many discoveries. This review focuses on the recent developments of one such microfluidic device nicknamed the mother machine. We overview the original device design, experimental setup, and challenges associated with this platform. We then describe recent methods for analyzing experiments using automated image segmentation and tracking. We further discuss modifications to the experimental setup that allow for time-varying environmental control, replicating batch culture conditions, cell screening based on their dynamic behaviors, and to accommodate a variety of microbial species. Finally, this review highlights the discoveries enabled by this technology in diverse fields, such as cell-size control, genetic mutations, cellular aging, and synthetic biology.

Frequency modulation of a bacterial quorum sensing response

In quorum sensing, bacteria secrete or release small molecules into the environment that, once they reach a certain threshold, trigger a behavioural change in the population. As the concentration of these so-called autoinducers is supposed to reflect population density, they were originally assumed to be continuously produced by all cells in a population. However, here we show that in the α-proteobacterium Sinorhizobium meliloti expression of the autoinducer synthase gene is realized in asynchronous stochastic pulses that result from scarcity and, presumably, low binding affinity of the key activator. Physiological cues modulate pulse frequency, and pulse frequency in turn modulates the velocity with which autoinducer levels in the environment reach the threshold to trigger the quorum sensing response. We therefore propose that frequency-modulated pulsing in S. meliloti represents the molecular mechanism for a collective decision-making process in which each cell's physiological state and need for behavioural adaptation is encoded in the pulse frequency with which it expresses the autoinducer synthase gene; the pulse frequencies of all members of the population are then integrated in the common pool of autoinducers, and only once this vote crosses the threshold, the response behaviour is initiated.

Myxopyronin B inhibits growth of a Fidaxomicin-resistant Clostridioides difficile isolate and interferes with toxin synthesis

The anaerobic, gastrointestinal pathogen Clostridioides difficile can cause severe forms of enterocolitis which is mainly mediated by the toxins it produces. The RNA polymerase inhibitor Fidaxomicin is the current gold standard for the therapy of C. difficile infections due to several beneficial features including its ability to suppress toxin synthesis in C. difficile. In contrast to the Rifamycins, Fidaxomicin binds to the RNA polymerase switch region, which is also the binding site for Myxopyronin B. Here, serial broth dilution assays were performed to test the susceptibility of C. difficile and other anaerobes to Myxopyronin B, proving that the natural product is considerably active against C. difficile and that there is no cross-resistance between Fidaxomicin and Myxopyronin B in a Fidaxomicin-resistant C. difficile strain. Moreover, mass spectrometry analysis indicated that Myxopyronin B is able to suppress early phase toxin synthesis in C. difficile to the same degree as Fidaxomicin. Conclusively, Myxopyronin B is proposed as a new lead structure for the design of novel antibiotics for the therapy of C. difficile infections.

Progress and challenges in understanding the regulation and function of p53 dynamics

The dynamics of p53 expression provide a mechanism to increase differentiation between cellular stresses and specificity in appropriate responses. Here, we review recent advances in our understanding of the molecular mechanisms regulating p53 dynamics and the functions of the dynamics in the regulation of p53-dependent cell stress responses. We also compare dynamic encoding in the p53 system with that found in other important cell signaling systems, many of which can interact with the p53 network. Finally, we highlight some of the current challenges in understanding dynamic cell signaling within a larger cellular network context.

Single-Cell Analysis of Mycobacteria Using Microfluidics and Time-Lapse Microscopy

Studies on cell-to-cell phenotypic variation in microbial populations, with individuals sharing the same genetic background, provide insights not only on bacterial behavior but also on the adaptive spectrum of the population. Phenotypic variation is an innate property of microbial populations, and this can be further amplified under stressful conditions, providing a fitness advantage. Furthermore, phenotypic variation may also precede a latter step of genetic-based diversification, resulting in the transmission of the most beneficial phenotype to the progeny. While population-wide studies provide a measure of the collective average behavior, single-cell studies, which have expanded over the last decade, delve into the behavior of smaller subpopulations that would otherwise remain concealed. In this chapter, we describe approaches to carry out spatiotemporal analysis of individual mycobacterial cells using time-lapse microscopy. Our method encompasses the fabrication of a microfluidic device; the assembly of a microfluidic system suitable for long-term imaging of mycobacteria; and the quantitative analysis of single-cell behavior under varying growth conditions. Phenotypic variation is conceivably associated to the resilience and endurance of mycobacterial cells. Therefore, shedding light on the dynamics of this phenomenon, on the transience or stability of the given phenotype, on its molecular bases and its functional consequences, offers new scope for intervention.

A model explaining mRNA level fluctuations based on activity demands and RNA age

Cellular RNA levels typically fluctuate and are influenced by different transcription rates and RNA degradation rates. However, the understanding of the fundamental relationships between RNA abundance, environmental stimuli, RNA activities, and RNA age distributions is incomplete. Furthermore, the rates of RNA degradation and transcription are difficult to measure in transcriptomic experiments in living organisms, especially in studies involving humans. A model based on activity demands and RNA age was developed to explore the mechanisms of RNA level fluctuations. Using single-cell time-series gene expression experimental data, we assessed the transcription rates, RNA degradation rates, RNA life spans, RNA demand, accumulated transcription levels, and accumulated RNA degradation levels. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge.

Detected cellular RNA levels usually fluctuate. The understanding of the fundamental relationships between RNA level fluctuations, the rates of RNA degradation and transcription, environmental stimuli, RNA activities, and RNA age distributions is incomplete. In the present research, we developed a model based on the demands of RNA (related to intrinsic and/or extrinsic information), RNA age (determines the survival time and biological activity of an RNA), transcription, and RNA degradation to explain the mechanism underlying intracellular RNA level fluctuations. We also explored applicability of the model for analysing dynamic processes between interacting biomolecules, such as the relationship between RNA and protein level fluctuations. Using single-cell time-series gene expression experimental data, we assessed some biological parameters, such as transcription rates, RNA degradation rates, and RNA life spans. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge and provides a new perspective for future studies.

Tunable phenotypic variability through an autoregulatory alternative sigma factor circuit

Genetically identical individuals in bacterial populations can display significant phenotypic variability. This variability can be functional, for example by allowing a fraction of stress prepared cells to survive an otherwise lethal stress. The optimal fraction of stress prepared cells depends on environmental conditions. However, how bacterial populations modulate their level of phenotypic variability remains unclear. Here we show that the alternative sigma factor σV circuit in Bacillus subtilis generates functional phenotypic variability that can be tuned by stress level, environmental history and genetic perturbations. Using single-cell time-lapse microscopy and microfluidics, we find the fraction of cells that immediately activate σV under lysozyme stress depends on stress level and on a transcriptional memory of previous stress. Iteration between model and experiment reveals that this tunability can be explained by the autoregulatory feedback structure of the sigV operon. As predicted by the model, genetic perturbations to the operon also modulate the response variability. The conserved sigma-anti-sigma autoregulation motif is thus a simple mechanism for bacterial populations to modulate their heterogeneity based on their environment.

Non-Genetic Diversity in Chemosensing and Chemotactic Behavior

Non-genetic phenotypic diversity plays a significant role in the chemotactic behavior of bacteria, influencing how populations sense and respond to chemical stimuli. First, we review the molecular mechanisms that generate phenotypic diversity in bacterial chemotaxis. Next, we discuss the functional consequences of phenotypic diversity for the chemosensing and chemotactic performance of single cells and populations. Finally, we discuss mechanisms that modulate the amount of phenotypic diversity in chemosensory parameters in response to changes in the environment.

Yeast cell fate control by temporal redundancy modulation of transcription factor paralogs

Recent single-cell studies have revealed that yeast stress response involves transcription factors that are activated in pulses. However, it remains unclear whether and how these dynamic transcription factors temporally interact to regulate stress survival. Here we show that budding yeast cells can exploit the temporal relationship between paralogous general stress regulators, Msn2 and Msn4, during stress response. We find that individual pulses of Msn2 and Msn4 are largely redundant, and cells can enhance the expression of their shared targets by increasing their temporal divergence. Thus, functional redundancy between these two paralogs is modulated in a dynamic manner to confer fitness advantages for yeast cells, which might feed back to promote the preservation of their redundancy. This evolutionary implication is supported by evidence from Msn2/Msn4 orthologs and analyses of other transcription factor paralogs. Together, we show a cell fate control mechanism through temporal redundancy modulation in yeast, which may represent an evolutionarily important strategy for maintaining functional redundancy between gene duplicates.

Allostery through DNA drives phenotype switching

Allostery is a pervasive principle to regulate protein function. Growing evidence suggests that also DNA is capable of transmitting allosteric signals. Yet, whether and how DNA-mediated allostery plays a regulatory role in gene expression remained unclear. Here, we show that DNA indeed transmits allosteric signals over long distances to boost the binding cooperativity of transcription factors. Phenotype switching in Bacillus subtilis requires an all-or-none promoter binding of multiple ComK proteins. We use single-molecule FRET to demonstrate that ComK-binding at one promoter site increases affinity at a distant site. Cryo-EM structures of the complex between ComK and its promoter demonstrate that this coupling is due to mechanical forces that alter DNA curvature. Modifications of the spacer between sites tune cooperativity and show how to control allostery, which allows a fine-tuning of the dynamic properties of genetic circuits.

Most insights on DNA-mediated allostery upon transcription factor (TF) binding were either based on artificial promoters or found to be short-ranged. Here authors use single-molecule FRET and cryo-EM to show that Bacillus subtilis bacteria utilize long-range allostery in a stochastic and reversible phenotype switch.

Spurious regulatory connections dictate the expression-fitness landscape of translation factors

During steady-state cell growth, individual enzymatic fluxes can be directly inferred from growth rate by mass conservation, but the inverse problem remains unsolved. Perturbing the flux and expression of a single enzyme could have pleiotropic effects that may or may not dominate the impact on cell fitness. Here, we quantitatively dissect the molecular and global responses to varied expression of translation termination factors (peptide release factors, RFs) in the bacterium Bacillus subtilis. While endogenous RF expression maximizes proliferation, deviations in expression lead to unexpected distal regulatory responses that dictate fitness reduction. Molecularly, RF depletion causes expression imbalance at specific operons, which activates master regulators and detrimentally overrides the transcriptome. Through these spurious connections, RF abundances are thus entrenched by focal points within the regulatory network, in one case located at a single stop codon. Such regulatory entrenchment suggests that predictive bottom-up models of expression-fitness landscapes will require near-exhaustive characterization of parts.

Pulses and delays, anticipation and memory: seeing bacterial stress responses from a single-cell perspective

Stress responses are crucial for bacteria to survive harmful conditions that they encounter in the environment. Although gene regulatory mechanisms underlying stress responses in bacteria have been thoroughly characterised for decades, recent advances in imaging technologies helped to uncover previously hidden dynamics and heterogeneity that become visible at the single-cell level. Despite the diversity of stress response mechanisms, certain dynamic regulatory features are frequently seen in single cells, such as pulses, delays, stress anticipation and memory effects. Often, these dynamics are highly variable across cells. While any individual cell may not achieve an optimal stress response, phenotypic diversity can provide a benefit at the population level. In this review, we highlight microscopy studies that offer novel insights into how bacteria sense stress, regulate protective mechanisms, cope with response delays and prepare for future environmental challenges. These studies showcase developments in the single-cell imaging toolbox including gene expression reporters, FRET, super-resolution microscopy and single-molecule tracking, as well as microfluidic techniques to manipulate cells and create defined stress conditions.

A conserved allosteric element controls specificity and activity of functionally divergent PP2C phosphatases from Bacillus subtilis

Reversible phosphorylation relies on highly regulated kinases and phosphatases that target specific substrates to control diverse cellular processes. Here, we address how protein phosphatase activity is directed to the correct substrates under the correct conditions. The serine/threonine phosphatase SpoIIE from Bacillus subtilis, a member of the widespread protein phosphatase 2C (PP2C) family of phosphatases, is activated by movement of a conserved α-helical element in the phosphatase domain to create the binding site for the metal cofactor. We hypothesized that this conformational switch could provide a general mechanism for control of diverse members of the PP2C family of phosphatases. The B. subtilis phosphatase RsbU responds to different signals, acts on a different substrates, and produces a more graded response than SpoIIE. Using an unbiased genetic screen, we isolated mutants in the α-helical switch region of RsbU that are constitutively active, indicating conservation of the switch mechanism. Using phosphatase activity assays with phosphoprotein substrates, we found that both phosphatases integrate substrate recognition with activating signals to control metal-cofactor binding and substrate dephosphorylation. This integrated control provides a mechanism for PP2C family of phosphatases to produce specific responses by acting on the correct substrates, under the appropriate conditions.

Biphasic regulation of transcriptional surge generated by the gene feedback loop in a two-component system

MOTIVATION

Transcriptional surges generated by two-component systems (TCSs) have been observed experimentally in various bacteria. Suppression of the transcriptional surge may reduce the activity, virulence, and drug resistance of bacteria. In order to investigate the general mechanisms, we use a PhoP/PhoQ TCS as a model system to derive a comprehensive mathematical modeling that governs the surge. PhoP is a response regulator, which serves as a transcription factor under a phosphorylation-dependent modulation by PhoQ, a histidine kinase.

RESULTS

Our model reveals two major signaling pathways to modulate the phosphorylated PhoP (P-PhoP) level, one of which promotes the generation of P-PhoP, while the other depresses the level of P-PhoP. The competition between the P-PhoP-promoting and the P-PhoP-depressing pathways determines the generation of the P-PhoP surge. Furthermore, besides PhoQ, PhoP is also a bifunctional modulator that contributes to the dynamic control of P-PhoP state, leading to a biphasic regulation of the surge by the gene feedback loop. In summary, the mechanisms derived from the PhoP/PhoQ system for the transcriptional surges provide a better understanding on such a sophisticated signal transduction system and aid to develop new antimicrobial strategies targeting TCSs.

AVAILABILITY

https://github.com/jianweishuai/TCS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Kinetic Modeling and Meta-Analysis of the Bacillus subtilis SigB Regulon during Spore Germination and Outgrowth

The exponential increase in the number of conducted studies combined with the development of sequencing methods have led to an enormous accumulation of partially processed experimental data in the past two decades. Here, we present an approach using literature-mined data complemented with gene expression kinetic modeling and promoter sequence analysis. This approach allowed us to identify the regulon of Bacillus subtilis sigma factor SigB of RNA polymerase (RNAP) specifically expressed during germination and outgrowth. SigB is critical for the cell's response to general stress but is also expressed during spore germination and outgrowth, and this specific regulon is not known. This approach allowed us to (i) define a subset of the known SigB regulon controlled by SigB specifically during spore germination and outgrowth, (ii) identify the influence of the promoter sequence binding motif organization on the expression of the SigB-regulated genes, and (iii) suggest additional sigma factors co-controlling other SigB-dependent genes. Experiments then validated promoter sequence characteristics necessary for direct RNAP-SigB binding. In summary, this work documents the potential of computational approaches to unravel new information even for a well-studied system; moreover, the study specifically identifies the subset of the SigB regulon, which is activated during germination and outgrowth.

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

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

Filtering input fluctuations in intensity and in time underlies stochastic transcriptional pulses without feedback

Stochastic pulsatile dynamics have been observed in an increasing number of biological circuits with known mechanism involving feedback control and bistability. Surprisingly, recent single-cell experiments in Escherichia coli flagellar synthesis showed that flagellar genes are activated in stochastic pulses without the means of feedback. However, the mechanism for pulse generation in these feedbackless circuits has remained unclear. Here, by developing a system-level stochastic model constrained by a large set of single-cell E. coli flagellar synthesis data from different strains and mutants, we identify the general underlying design principles for generating stochastic transcriptional pulses without feedback. Our study shows that an inhibitor (YdiV) of the transcription factor (FlhDC) creates a monotonic ultrasensitive switch that serves as a digital filter to eliminate small-amplitude FlhDC fluctuations. Furthermore, we find that the high-frequency (fast) fluctuations of FlhDC are filtered out by integration over a timescale longer than the timescale of the input fluctuations. Together, our results reveal a filter-and-integrate design for generating stochastic pulses without feedback. This filter-and-integrate mechanism enables a general strategy for cells to avoid premature activation of the expensive downstream gene expression by filtering input fluctuations in both intensity and time so that the system only responds to input signals that are both strong and persistent.

Functional roles of microbial cell-to-cell heterogeneity and emerging technologies for analysis and control

Clonal cell populations often display significant cell-to-cell phenotypic heterogeneity, even when maintained under constant external conditions. This variability can result from the inherently stochastic nature of transcription and translation processes, which leads to varying numbers of transcripts and proteins per cell. Here, we showcase studies that reveal links between stochastic cellular events and biological functions in isogenic microbial populations. Then, we highlight emerging tools from engineering, computation, and synthetic and molecular biology that enable precise measurement, control, and analysis of gene expression noise in microorganisms. The capabilities offered by this sophisticated toolbox will shape future directions in the field and generate insight into the behavior of living systems at the single-cell level.

Experimental evidence for constraints in amplitude-timescale co-variation of a biomolecular pulse generating circuit design

Understanding constraints on the functional properties of biomolecular circuit dynamics, such as the possible variations of amplitude and timescale of a pulse, is an important part of biomolecular circuit design. While the amplitude-timescale co-variations of the pulse in an incoherent feedforward loop have been investigated computationally using mathematical models, experimental support for any such constraints is relatively unclear. Here, the authors address this using experimental measurement of an existing pulse generating incoherent feedforward loop circuit realisation in the context of a standard mathematical model. They characterise the trends of co-variation in the pulse amplitude and rise time computationally by randomly exploring the parameter space. They experimentally measured the co-variation by varying inducers and found that larger amplitude pulses have a slower rise time. They discuss the gap between the experimental measurements and predictions of the standard model, highlighting model additions and other biological factors that might bridge the gap.

The Stress-Responsive Alternative Sigma Factor SigB of Bacillus subtilis and Its Relatives: An Old Friend With New Functions

Alternative sigma factors have led the core RNA polymerase (RNAP) to recognize different sets of promoters to those recognized by the housekeeping sigma A-directed RNAP. This change in RNAP promoter selectivity allows a rapid and flexible reformulation of the genetic program to face environmental and metabolic stimuli that could compromise bacterial fitness. The model bacterium Bacillus subtilis constitutes a matchless living system in the study of the role of alternative sigma factors in gene regulation and physiology. SigB from B. subtilis was the first alternative sigma factor described in bacteria. Studies of SigB during the last 40 years have shown that it controls a genetic universe of more than 150 genes playing crucial roles in stress response, adaption, and survival. Activation of SigB relies on three separate pathways that specifically respond to energy, environmental, and low temperature stresses. SigB homologs, present in other Gram-positive bacteria, also play important roles in virulence against mammals. Interestingly, during recent years, other unexpected B. subtilis responses were found to be controlled by SigB. In particular, SigB controls the efficiencies of spore and biofilm formation, two important features that play critical roles in adaptation and survival in planktonic and sessile B. subtilis communities. In B. subtilis, SigB induces the expression of the Spo0E aspartyl-phosphatase, which is responsible for the blockage of sporulation initiation. The upregulated activity of Spo0E connects the two predominant adaptive pathways (i.e., sporulation and stress response) present in B. subtilis. In addition, the RsbP serine-phosphatase, belonging to the energy stress arm of the SigB regulatory cascade, controls the expression of the key transcription factor SinR to decide whether cells residing in the biofilm remain in and maintain biofilm growth or scape to colonize new niches through biofilm dispersal. SigB also intervenes in the recognition of and response to surrounding microorganisms, a new SigB role that could have an agronomic impact. SigB is induced when B. subtilis is confronted with phytopathogenic fungi (e.g., Fusarium verticillioides) and halts fungal growth to the benefit of plant growth. In this article, we update and review literature on the different regulatory networks that control the activation of SigB and the new roles that have been described the recent years.

The σB-Mediated General Stress Response of Listeria monocytogenes: Life and Death Decision Making in a Pathogen

Sensing and responding to environmental cues is critical for the adaptability and success of the food-borne bacterial pathogen Listeria monocytogenes. A supramolecular multi-protein complex known as the stressosome, which acts as a stress sensing hub, is responsible for orchestrating the activation of a signal transduction pathway resulting in the activation of σ^B, the sigma factor that controls the general stress response (GSR). When σ^B is released from the anti-sigma factor RsbW, a rapid up-regulation of the large σ^B regulon, comprised of ≥ 300 genes, ensures that cells respond appropriately to the new environmental conditions. A diversity of stresses including low pH, high osmolarity, and blue light are known to be sensed by the stressosome, resulting in a generalized increase in stress resistance. Appropriate activation of the stressosome and deployment of σ^B are critical to fitness as there is a trade-off between growth and stress protection when the GSR is deployed. We review the recent developments in this field and describe an up-to-date model of how this sensory organelle might integrate environmental signals to produce an appropriate activation of the GSR. Some of the outstanding questions and challenges in this fascinating field are also discussed.

Membrane potentials, oxidative stress and the dispersal response of bacterial biofilms to 405 nm light

The majority of chronic infections are caused by biofilms, which have higher levels of antibiotic resistance than planktonic growth. Violet-blue 405 nm light has recently emerged as a novel bactericide, but limited studies have been conducted on its effectiveness against biofilms. We found that in response to 405 nm light both Pseudomonas aeruginosa and Bacillus subtilis biofilms exhibited cell dispersal and membrane potential hyperpolarisations. The response to 405 nm light depended on the stage of biofilm growth. The use of reactive oxygen species scavengers reduced membrane hyperpolarisation and biofilm dispersal in response to 405 nm light. This is the first time that membrane potential hyperpolarisations have been linked with photooxidative stress in bacteria and with biofilm dispersal. These results provide a new insight into the role of membrane potentials in the bacterial stress response and could be used in the development of 405 nm light based biofilm treatments.

Stochastic pulsing of gene expression enables the generation of spatial patterns in Bacillus subtilis biofilms

Stochastic pulsing of gene expression can generate phenotypic diversity in a genetically identical population of cells, but it is unclear whether it has a role in the development of multicellular systems. Here, we show how stochastic pulsing of gene expression enables spatial patterns to form in a model multicellular system, Bacillus subtilis bacterial biofilms. We use quantitative microscopy and time-lapse imaging to observe pulses in the activity of the general stress response sigma factor σ^B in individual cells during biofilm development. Both σ^B and sporulation activity increase in a gradient, peaking at the top of the biofilm, even though σ^B represses sporulation. As predicted by a simple mathematical model, increasing σ^B expression shifts the peak of sporulation to the middle of the biofilm. Our results demonstrate how stochastic pulsing of gene expression can play a key role in pattern formation during biofilm development.

Stochastic pulsing of gene expression can generate phenotypic diversity in a genetically identical population of cells. Here, the authors show that stochastic pulsing in the expression of a sigma factor enables the formation of spatial patterns in a multicellular system, Bacillus subtilis bacterial biofilms.

Microfluidic Single-Cell Analytics

What is the impact of cellular heterogeneity on process performance? How do individual cells contribute to averaged process productivity? Single-cell analysis is a key technology for answering such key questions of biotechnology, beyond bulky measurements with populations. The analysis of cellular individuality, its origins, and the dependency of process performance on cellular heterogeneity has tremendous potential for optimizing biotechnological processes in terms of metabolic, reaction, and process engineering. Microfluidics offer unmatched environmental control of the cellular environment and allow massively parallelized cultivation of single cells. However, the analytical accessibility to a cell's physiology is of crucial importance for obtaining the desired information on the single-cell production phenotype. Highly sensitive analytics are required to detect and quantify the minute amounts of target analytes and small physiological changes in a single cell. For their application to biotechnological questions, single-cell analytics must evolve toward the measurement of kinetics and specific rates of the smallest catalytic unit, the single cell. In this chapter, we focus on an introduction to the latest single-cell analytics and their application for obtaining physiological parameters in a biotechnological context from single cells. We present and discuss recent advancements in single-cell analytics that enable the analysis of cell-specific growth, uptake, and production kinetics, as well as the gene expression and regulatory mechanisms at a single-cell level.

The Design Principles of Biochemical Timers: Circuits that Discriminate between Transient and Sustained Stimulation

Many cellular responses for which timing is critical display temporal filtering-the ability to suppress response until stimulated for longer than a given minimal time. To identify biochemical circuits capable of kinetic filtering, we comprehensively searched the space of three-node enzymatic networks. We define a metric of "temporal ultrasensitivity," the steepness of activation as a function of stimulus duration. We identified five classes of core network motifs capable of temporal filtering, each with distinct functional properties such as rejecting high-frequency noise, committing to response (bistability), and distinguishing between long stimuli. Combinations of the two most robust motifs, double inhibition (DI) and positive feedback with AND logic (PF_AND), underlie several natural timer circuits involved in processes such as cell cycle transitions, T cell activation, and departure from the pluripotent state. The biochemical network motifs described in this study form a basis for understanding common ways cells make dynamic decisions.

Cross Talk between SigB and PrfA in Listeria monocytogenes Facilitates Transitions between Extra- and Intracellular Environments

The foodborne pathogen Listeria monocytogenes can modulate its transcriptome and proteome to ensure its survival during transmission through vastly differing environmental conditions. While L. monocytogenes utilizes a large array of regulators to achieve survival and growth in different intra- and extrahost environments, the alternative sigma factor σ^B and the transcriptional activator of virulence genes protein PrfA are two key transcriptional regulators essential for responding to environmental stress conditions and for host infection. Importantly, emerging evidence suggests that the shift from extrahost environments to the host gastrointestinal tract and, subsequently, to intracellular environments requires regulatory interplay between σ^B and PrfA at transcriptional, posttranscriptional, and protein activity levels. Here, we review the current evidence for cross talk and interplay between σ^B and PrfA and their respective regulons and highlight the plasticity of σ^B and PrfA cross talk and the role of this cross talk in facilitating successful transition of L. monocytogenes from diverse extrahost to diverse extra- and intracellular host environments.

Non-normality can facilitate pulsing in biomolecular circuits

Non-normality can underlie pulse dynamics in many engineering contexts. However, its role in pulses generated in biomolecular contexts is generally unclear. Here, the authors address this issue using the mathematical tools of linear algebra and systems theory on simple computational models of biomolecular circuits. They find that non-normality is present in standard models of feedforward loops. They used a generalised framework and pseudospectrum analysis to identify non-normality in larger biomolecular circuit models, finding that it correlates well with pulsing dynamics. Finally, they illustrate how these methods can be used to provide analytical support to numerical screens for pulsing dynamics as well as provide guidelines for design.

An Engineered B. subtilis Inducible Promoter System with over 10 000-Fold Dynamic Range

Bacillus subtilis is the leading model Gram-positive bacterium, and a widely used chassis for industrial protein production. However, B. subtilis research is limited by a lack of inducible promoter systems with low leakiness and high dynamic range. Here, we engineer an inducible promoter system based on the T7 RNA Polymerase (T7 RNAP), the lactose repressor LacI, and the chimeric promoter P_T7lac, integrated as a single copy in the B. subtilis genome. In the absence of IPTG, LacI strongly represses T7 RNAP and P_T7lac and minimizes leakiness. Addition of IPTG derepresses P_T7lac and simultaneously induces expression of T7RNAP, which results in very high output expression. Using green fluorescent and β-galactosidase reporter proteins, we estimate that this LacI-T7 system can regulate expression with a dynamic range of over 10 000, by far the largest reported for an inducible B. subtilis promoter system. Furthermore, LacI-T7 responds to similar IPTG concentrations and with similar kinetics as the widely used P_hy-spank IPTG-inducible system, which we show has a dynamic range of at most 300 in a similar genetic context. Due to its superior performance, our LacI-T7 system should have broad applications in fundamental B. subtilis biology studies and biotechnology.

Optogenetic control of Bacillus subtilis gene expression

The Gram-positive bacterium Bacillus subtilis exhibits complex spatial and temporal gene expression signals. Although optogenetic tools are ideal for studying such processes, none has been engineered for this organism. Here, we port a cyanobacterial light sensor pathway comprising the green/red photoreversible two-component system CcaSR, two metabolic enzymes for production of the chromophore phycocyanobilin (PCB), and an output promoter to control transcription of a gene of interest into B. subtilis. Following an initial non-functional design, we optimize expression of pathway genes, enhance PCB production via a translational fusion of the biosynthetic enzymes, engineer a strong chimeric output promoter, and increase dynamic range with a miniaturized photosensor kinase. Our final design exhibits over 70-fold activation and rapid response dynamics, making it well-suited to studying a wide range of gene regulatory processes. In addition, the synthetic biology methods we develop to port this pathway should make B. subtilis easier to engineer in the future.

Forecasting cell fate during antibiotic exposure using stochastic gene expression

Antibiotic killing does not occur at a single, precise time for all cells within a population. Variability in time to death can be caused by stochastic expression of genes, resulting in differences in endogenous stress-resistance levels between individual cells in a population. Here we investigate whether single-cell differences in gene expression prior to antibiotic exposure are related to cell survival times after antibiotic exposure for a range of genes of diverse function. We quantified the time to death of single cells under antibiotic exposure in combination with expression of reporters. For some reporters, including genes involved in stress response and cellular processes like metabolism, the time to cell death had a strong relationship with the initial expression level of the genes. Our results highlight the single-cell level non-uniformity of antibiotic killing and also provide examples of key genes where cell-to-cell variation in expression is strongly linked to extended durations of antibiotic survival.

Cell Heterogeneity in Staphylococcal Communities

The human pathogen Staphylococcus aureus is a gram-positive bacterium that causes difficult-to-treat infections. One of the reasons why S. aureus is such as successful pathogen is due to the cell-to-cell physiological variability that exists within microbial communities. Many laboratories around the world study the genetic mechanisms involved in S. aureus cell heterogeneity to better understand infection mechanism of this bacterium. It was recently shown that the Agr quorum-sensing system, which antagonistically regulates biofilm-associated or acute bacteremia infections, is expressed in a subpopulation of specialized cells. In this review, we discuss the different genetic mechanism for bacterial cell differentiation and the physiological properties of the distinct cell types that are already described in S. aureus communities, as well as the role that these cell types play during an infection process.

RNA Regulatory Networks as a Control of Stochasticity in Biological Systems

The discovery that the non-protein coding part of human genome, dismissed as "junk DNA," is actively transcripted and carries out crucial functions is probably one of the most important discoveries of the past decades. These transcripts are becoming the rising stars of modern biology. In this review, we have casted a new light on RNAs. We have placed these molecules in the context of life origins, evolution with a big emphasize on the "RNA networks" concept. We discuss how this view can help us to understand the global role of RNA networks in modern cells, and can change our perception of the cell biology and therapy. Finally, although high-throughput methods as well as traditional case-to-case studies have laid the groundwork for our current knowledge of transcriptomes, we would like to discuss new strategies that are better suited to uncover and tackle these integrated and complex RNA networks.

A modular degron library for synthetic circuits in mammalian cells

Tight control over protein degradation is a fundamental requirement for cells to respond rapidly to various stimuli and adapt to a fluctuating environment. Here we develop a versatile, easy-to-handle library of destabilizing tags (degrons) for the precise regulation of protein expression profiles in mammalian cells by modulating target protein half-lives in a predictable manner. Using the well-established tetracycline gene-regulation system as a model, we show that the dynamics of protein expression can be tuned by fusing appropriate degron tags to gene regulators. Next, we apply this degron library to tune a synthetic pulse-generating circuit in mammalian cells. With this toolbox we establish a set of pulse generators with tailored pulse lengths and magnitudes of protein expression. This methodology will prove useful in the functional roles of essential proteins, fine-tuning of gene-expression systems, and enabling a higher complexity in the design of synthetic biological systems in mammalian cells.

Tuning of mRNA stability through altering 3'-UTR sequences generates distinct output expression in a synthetic circuit driven by p53 oscillations

Synthetic biological circuits that can generate outputs with distinct expression dynamics are useful for a variety of biomedical and industrial applications. We present a method to control output dynamics by altering output mRNA decay rates. Using oscillatory expression of the transcription factor p53 as the circuit regulator, we use two approaches for controlling target gene transcript degradation rates based on the output gene's 3'-untranslated region (3'-UTR): introduction of copies of destabilizing AU-rich elements into the 3'-UTR or swapping in naturally occurring 3'-UTRs conferring different transcript stabilities. As a proof of principle, we apply both methods to control the expression dynamics of a fluorescent protein and visualize the circuit output dynamics in single living cells. We then use the naturally occurring 3'-UTR approach to restore apoptosis in a tunable manner in a cancer cell line deficient for caspase-3 expression. Our method can be readily adapted to regulate multiple outputs each with different expression dynamics under the control of a single naturally occurring or synthetically constructed biological oscillator.

Tuning the Mycobacterium tuberculosis Alternative Sigma Factor SigF through the Multidomain Regulator Rv1364c and Osmosensory Kinase Protein Kinase D

Bacterial alternative sigma factors are mostly regulated by a partner-switching mechanism. Regulation of the virulence-associated alternative sigma factor SigF of Mycobacterium tuberculosis has been an area of intrigue, with SigF having more predicted regulators than other sigma factors in this organism. Rv1364c is one such predicted regulator, the mechanism of which is confounded by the presence of both anti-sigma factor and anti-sigma factor antagonist functions in a single polypeptide. Using protein binding and phosphorylation assays, we demonstrate that the anti-sigma factor domain of Rv1364c mediates autophosphorylation of its antagonist domain and binds efficiently to SigF. Furthermore, we identified a direct role for the osmosensor serine/threonine kinase PknD in regulating the SigF-Rv1364c interaction, adding to the current understanding about the intersection of these discrete signaling networks. Phosphorylation of SigF also showed functional implications in its DNA binding ability, which may help in activation of the regulon. In M. tuberculosis, osmotic stress-dependent induction of espA, a SigF target involved in maintaining cell wall integrity, is curtailed upon overexpression of Rv1364c, showing its role as an anti-SigF factor. Overexpression of Rv1364c led to induction of another target, pks6, involved in lipid metabolism. This induction was, however, curtailed in the presence of osmotic stress conditions, suggesting modulation of SigF target gene expression via Rv1364c. These data provide evidence that Rv1364c acts an independent SigF regulator that is sensitive to the osmosensory signal, mediating the cross talk of PknD with the SigF regulon.IMPORTANCE Mycobacterium tuberculosis, capable of latently infecting the host and causing aggressive tissue damage during active tuberculosis, is endowed with a complex regulatory capacity built of several sigma factors, protein kinases, and phosphatases. These proteins regulate expression of genes that allow the bacteria to adapt to various host-derived stresses, like nutrient starvation, acidic pH, and hypoxia. The cross talk between these systems is not well understood. SigF is one such regulator of gene expression that helps M. tuberculosis to adapt to stresses and imparts virulence. This work provides evidence for its inhibition by the multidomain regulator Rv1364c and activation by the kinase PknD. The coexistence of negative and positive regulators of SigF in pathogenic bacteria reveals an underlying requirement for tight control of virulence factor expression.