Molecular Time Sharing through Dynamic Pulsing in Single Cells

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.

The alternative sigma factor SigN of Bacillus subtilis is intrinsically toxic

Sigma factors bind and direct the RNA polymerase core to specific promoter sequences, and alternative sigma factors direct transcription of different regulons of genes. Here, we study the pBS32 plasmid-encoded sigma factor SigN of Bacillus subtilis to determine how it contributes to DNA damage-induced cell death. We find that SigN causes cell death when expressed at high levels and does so in the absence of its regulon suggesting it is intrinsically toxic. One way toxicity was relieved was by curing the pBS32 plasmid, which eliminated a positive feedback loop that led to SigN hyper-accumulation. Another way toxicity was relieved was through mutating the chromosomally encoded transcriptional repressor protein AbrB, thereby derepressing a potent antisense transcript that antagonized SigN expression. SigN efficiently competed with the vegetative sigma factor SigA in vitro, and SigN accumulation in the absence of positive feedback reduced SigA-dependent transcription suggesting that toxicity may be due to competitive inhibition of one or more essential transcripts. Why B. subtilis encodes a toxic sigma factor is unclear but SigN may function in host-inhibition during lytic conversion, as phage lysogen genes are also encoded on pBS32. IMPORTANCE Alternative sigma factors activate entire regulons of genes to improve viability in response to environmental stimuli. The pBS32 plasmid-encoded alternative sigma factor SigN of Bacillus subtilis however, is activated by the DNA damage response and leads to cellular demise. Here we find that SigN impairs viability by hyper-accumulating and outcompeting the vegetative sigma factor for the RNA polymerase core. Why B. subtilis retains a plasmid with a deleterious alternative sigma factor is unknown.

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.

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.

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.

Signal Transduction Network Principles Underlying Bacterial Collective Behaviors

Bacteria orchestrate collective behaviors and accomplish feats that would be unsuccessful if carried out by a lone bacterium. Processes undertaken by groups of bacteria include bioluminescence, biofilm formation, virulence factor production, and release of public goods that are shared by the community. Collective behaviors are controlled by signal transduction networks that integrate sensory information and transduce the information internally. Here, we discuss network features and mechanisms that, even in the face of dramatically changing environments, drive precise execution of bacterial group behaviors. We focus on representative quorum-sensing and second-messenger cyclic dimeric GMP (c-di-GMP) signal relays. We highlight ligand specificity versus sensitivity, how small-molecule ligands drive discrimination of kin versus nonkin, signal integration mechanisms, single-input sensory systems versus coincidence detectors, and tuning of input-output dynamics via feedback regulation. We summarize how different features of signal transduction systems allow groups of bacteria to successfully interpret and collectively react to dynamically changing environments.

Phage-Encoded Sigma Factors Alter Bacterial Dormancy

By entering a reversible state of reduced metabolic activity, dormant microorganisms are able to tolerate suboptimal conditions that would otherwise reduce their fitness. Dormancy may also benefit bacteria by serving as a refuge from parasitic infections. Here, we focus on dormancy in the Bacillota, where endospore development is transcriptionally regulated by the expression of sigma factors. A disruption of this process could influence the survivorship or reproduction of phages that infect spore-forming hosts with implications for coevolutionary dynamics. We characterized the distribution of sigma factors in over 4,000 genomes of diverse phages capable of infecting hosts that span the bacterial domain. From this, we identified homologs of sporulation-specific sigma factors in phages that infect spore-forming hosts. Unlike sigma factors required for phage reproduction, we provide evidence that sporulation-like sigma factors are nonessential for lytic infection. However, when expressed in the spore-forming Bacillus subtilis, some of these phage-derived sigma factors can activate the bacterial sporulation gene network and lead to a reduction in spore yield. Our findings suggest that the acquisition of host-like transcriptional regulators may allow phages to manipulate a complex and ancient trait in one of the most abundant cell types on Earth.

IMPORTANCE As obligate parasites, phages exert strong top-down pressure on host populations with eco-evolutionary implications for community dynamics and ecosystem functioning. The process of phage infection, however, is constrained by bottom-up processes that influence the energetic and nutritional status of susceptible hosts. Many phages have acquired auxiliary genes from bacteria, which can be used to exploit host metabolism with consequences for phage fitness. In this study, we demonstrate that phages infecting spore-forming bacteria carry homologs of sigma factors, which their hosts use to orchestrate gene expression during spore development. By tapping into regulatory gene networks, phages may manipulate the physiology and survival strategies of nongrowing bacteria in ways that influence host-parasite coevolution.

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.

Dynamic gene expression and growth underlie cell-to-cell heterogeneity in Escherichia coli stress response

Individual bacteria that share identical genomes and growth environments can display substantial cell-to-cell differences in expression of stress-response genes and single-cell growth rates. This phenotypic heterogeneity can impact the survival of single cells facing sudden stress. However, the windows of time that cells spend in vulnerable or tolerant states are often unknown. We quantify the temporal expression of a suite of stress-response reporters, while simultaneously monitoring growth. We observe pulsatile expression across genes with a range of stress-response functions, finding that single-cell growth rates are often anticorrelated with reporter levels. These dynamic phenotypic differences have a concrete link to function, in which individual cells undergoing a pulse of elevated expression and slow growth are predisposed to survive antibiotic exposure.

Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is important because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress-response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found several examples of pulsatile expression. Single-cell growth rates were often anticorrelated with reporter levels, with changes in growth preceding changes in expression. These dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that fluctuations in both gene expression and growth dynamics in stress-response networks have direct consequences on survival.

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.

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.

Microbial single-cell RNA sequencing by split-pool barcoding

Single-cell RNA sequencing (scRNA-seq) has become an essential tool for characterizing gene expression in eukaryotes, but current methods are incompatible with bacteria. Here, we introduce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for Gram-negative and Gram-positive bacteria that can resolve heterogeneous transcriptional states. We applied microSPLiT to >25,000 Bacillus subtilis cells sampled at different growth stages, creating an atlas of changes in metabolism and lifestyle. We retrieved detailed gene expression profiles associated with known, but rare, states such as competence and prophage induction and also identified unexpected gene expression states, including the heterogeneous activation of a niche metabolic pathway in a subpopulation of cells. MicroSPLiT paves the way to high-throughput analysis of gene expression in bacterial communities that are otherwise not amenable to single-cell analysis, such as natural microbiota.

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.

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.

Stochastic antagonism between two proteins governs a bacterial cell fate switch

Cell fate decision circuits must be variable enough for genetically identical cells to adopt a multitude of fates, yet ensure that these states are distinct, stably maintained, and coordinated with neighboring cells. A long-standing view is that this is achieved by regulatory networks involving self-stabilizing feedback loops that convert small differences into long-lived cell types. We combined regulatory mutants and in vivo reconstitution with theory for stochastic processes to show that the marquee features of a cell fate switch in Bacillus subtilis-discrete states, multigenerational inheritance, and timing of commitments-can instead be explained by simple stochastic competition between two constitutively produced proteins that form an inactive complex. Such antagonistic interactions are commonplace in cells and could provide powerful mechanisms for cell fate determination more broadly.

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.

Isolating live cells after high-throughput, long-term, time-lapse microscopy

Single-cell genetic screens can be incredibly powerful, but current high-throughput platforms do not track dynamic processes, and even for non-dynamic properties they struggle to separate mutants of interest from phenotypic outliers of the wild-type population. Here we introduce SIFT, single-cell isolation following time-lapse imaging, to address these limitations. After imaging and tracking individual bacteria for tens of consecutive generations under tightly controlled growth conditions, cells of interest are isolated and propagated for downstream analysis, free of contamination and without genetic or physiological perturbations. This platform can characterize tens of thousands of cell lineages per day, making it possible to accurately screen complex phenotypes without the need for barcoding or genetic modifications. We applied SIFT to identify a set of ultraprecise synthetic gene oscillators, with circuit variants spanning a 30-fold range of average periods. This revealed novel design principles in synthetic biology and demonstrated the power of SIFT to reliably screen diverse dynamic phenotypes.

Preexisting variation in DNA damage response predicts the fate of single mycobacteria under stress

Clonal microbial populations are inherently heterogeneous, and this diversification is often considered as an adaptation strategy. In clinical infections, phenotypic diversity is found to be associated with drug tolerance, which in turn could evolve into genetic resistance. Mycobacterium tuberculosis, which ranks among the top ten causes of mortality with high incidence of drug-resistant infections, exhibits considerable phenotypic diversity. In this study, we quantitatively analyze the cellular dynamics of DNA damage responses in mycobacteria using microfluidics and live-cell fluorescence imaging. We show that individual cells growing under optimal conditions experience sporadic DNA-damaging events manifested by RecA expression pulses. Single-cell responses to these events occur as transient pulses of fluorescence expression, which are dependent on the gene-network structure but are triggered by extrinsic signals. We demonstrate that preexisting subpopulations, with discrete levels of DNA damage response, are associated with differential susceptibility to fluoroquinolones. Our findings reveal that the extent of DNA integrity prior to drug exposure impacts the drug activity against mycobacteria, with conceivable therapeutic implications.

Deciphering the essentiality and function of the anti-σM factors in Bacillus subtilis

Bacteria use alternative sigma factors to adapt to different growth and stress conditions. The Bacillus subtilis extracytoplasmic function sigma factor SigM regulates genes for cell wall synthesis and is crucial for maintaining cell wall homeostasis under stress conditions. The activity of SigM is regulated by its anti-sigma factor, YhdL, and the accessory protein YhdK. Here, we show that dysregulation of SigM caused by the absence of either component of the anti-sigma factor complex leads to toxic levels of SigM and severe growth defects. High SigM activity results from a dysregulated positive feedback loop, and can be suppressed by overexpression of the housekeeping sigma, SigA. Using a sigM merodiploid strain, we selected for suppressor mutations that allow survival of yhdL depletion strain. The recovered suppressor mutations map to the beta and beta-prime subunits of RNA polymerase core enzyme and selectively reduce SigM activity, and in some cases increase the activity of other alternative sigma factors. This work highlights the ability of mutations in RNA polymerase that remodel the sigma-core interface to differentially affect sigma factor activity, and thereby alter the transcriptional landscape of the cell.

Sigma Factor-Mediated Tuning of Bacterial Cell-Free Synthetic Genetic Oscillators

Cell-free transcription–translation provides a simplified prototyping environment to rapidly design and study synthetic networks. Despite the presence of a well characterized toolbox of genetic elements, examples of genetic networks that exhibit complex temporal behavior are scarce. Here, we present a genetic oscillator implemented in an E. coli-based cell-free system under steady-state conditions using microfluidic flow reactors. The oscillator has an activator–repressor motif that utilizes the native transcriptional machinery of E. coli: the RNAP and its associated sigma factors. We optimized a kinetic model with experimental data using an evolutionary algorithm to quantify the key regulatory model parameters. The functional modulation of the RNAP was investigated by coupling two oscillators driven by competing sigma factors, allowing the modification of network properties by means of passive transcriptional regulation.

Escherichia coli can survive stress by noisy growth modulation

Gene expression can be noisy, as can the growth of single cells. Such cell-to-cell variation has been implicated in survival strategies for bacterial populations. However, it remains unclear how single cells couple gene expression with growth to implement these strategies. Here, we show how noisy expression of a key stress-response regulator, RpoS, allows E. coli to modulate its growth dynamics to survive future adverse environments. We reveal a dynamic positive feedback loop between RpoS and growth rate that produces multi-generation RpoS pulses. We do so experimentally using single-cell, time-lapse microscopy and microfluidics and theoretically with a stochastic model. Next, we demonstrate that E. coli prepares for sudden stress by entering prolonged periods of slow growth mediated by RpoS. This dynamic phenotype is captured by the RpoS-growth feedback model. Our synthesis of noisy gene expression, growth, and survival paves the way for further exploration of functional phenotypic variability.

Noisy gene expression leading to phenotypic variability can help organisms to survive in changing environments. Here, Patange et al. show that noisy expression of a stress response regulator, RpoS, allows E. coli cells to modulate their growth rates to survive future adverse environments.

Engineered dCas9 with reduced toxicity in bacteria: implications for genetic circuit design

Large synthetic genetic circuits require the simultaneous expression of many regulators. Deactivated Cas9 (dCas9) can serve as a repressor by having a small guide RNA (sgRNA) direct it to bind a promoter. The programmability and specificity of RNA:DNA basepairing simplifies the generation of many orthogonal sgRNAs that, in theory, could serve as a large set of regulators in a circuit. However, dCas9 is toxic in many bacteria, thus limiting how high it can be expressed, and low concentrations are quickly sequestered by multiple sgRNAs. Here, we construct a non-toxic version of dCas9 by eliminating PAM (protospacer adjacent motif) binding with a R1335K mutation (dCas9*) and recovering DNA binding by fusing it to the PhlF repressor (dCas9*_PhlF). Both the 30 bp PhlF operator and 20 bp sgRNA binding site are required to repress a promoter. The larger region required for recognition mitigates toxicity in Escherichia coli, allowing up to 9600 ± 800 molecules of dCas9*_PhlF per cell before growth or morphology are impacted, as compared to 530 ± 40 molecules of dCas9. Further, PhlF multimerization leads to an increase in average cooperativity from n = 0.9 (dCas9) to 1.6 (dCas9*_PhlF). A set of 30 orthogonal sgRNA-promoter pairs are characterized as NOT gates; however, the simultaneous use of multiple sgRNAs leads to a monotonic decline in repression and after 15 are co-expressed the dynamic range is <10-fold. This work introduces a non-toxic variant of dCas9, critical for its use in applications in metabolic engineering and synthetic biology, and exposes a limitation in the number of regulators that can be used in one cell when they rely on a shared resource.