Chromosomal Arrangement of Phosphorelay Genes Couples Sporulation and DNA Replication.

Genes encoding proteins in a common regulatory network are frequently located close to one another on the chromosome to facilitate co-regulation or couple gene expression to growth rate. Contrasting with these observations, here, we demonstrate a functional role for the arrangement of Bacillus subtilis sporulation network genes on opposite sides of the chromosome. We show that the arrangement of two sporulation network genes, one located close to the origin and the other close to the terminus, leads to a transient gene dosage imbalance during chromosome replication. This imbalance is detected by the sporulation network to produce cell-cycle coordinated pulses of the sporulation master regulator Spo0A∼P. This pulsed response allows cells to decide between sporulation and continued vegetative growth during each cell cycle spent in starvation. The simplicity of this coordination mechanism suggests that it may be widely applicable in a variety of gene regulatory and stress-response settings. VIDEO ABSTRACT.

Heterogeneity of Stop Codon Readthrough in Single Bacterial Cells and Implications for Population Fitness.

Gene expression noise (heterogeneity) leads to phenotypic diversity among isogenic individual cells. Our current understanding of gene expression noise is mostly limited to transcription, as separating translational noise from transcriptional noise has been challenging. It also remains unclear how translational heterogeneity originates. Using a transcription-normalized reporter system, we discovered that stop codon readthrough is heterogeneous among single cells, and individual cells with higher UGA readthrough grow faster from stationary phase. Our work also revealed that individual cells with lower protein synthesis levels exhibited higher UGA readthrough, which was confirmed with ribosome-targeting antibiotics (e.g., chloramphenicol). Further experiments and mathematical modeling suggest that varied competition between ternary complexes and release factors perturbs the UGA readthrough level. Our results indicate that fluctuations in the concentrations of translational components lead to UGA readthrough heterogeneity among single cells, which enhances phenotypic diversity of the genetically identical population and facilitates its adaptation to changing environments.

Bacteriophage self-counting in the presence of viral replication.

When host cells are in low abundance, temperate bacteriophages opt for dormant (lysogenic) infection. Phage lambda implements this strategy by increasing the frequency of lysogeny at higher multiplicity of infection (MOI). However, it remains unclear how the phage reliably counts infecting viral genomes even as their intracellular number increases because of replication. By combining theoretical modeling with single-cell measurements of viral copy number and gene expression, we find that instead of hindering lambda's decision, replication facilitates it. In a nonreplicating mutant, viral gene expression simply scales with MOI rather than diverging into lytic (virulent) and lysogenic trajectories. A similar pattern is followed during early infection by wild-type phage. However, later in the infection, the modulation of viral replication by the decision genes amplifies the initially modest gene expression differences into divergent trajectories. Replication thus ensures the optimal decision-lysis upon single-phage infection and lysogeny at higher MOI.

Kinetic control of stationary flux ratios for a wide range of biochemical processes.

One of the most intriguing features of biological systems is their ability to regulate the steady-state fluxes of the underlying biochemical reactions; however, the regulatory mechanisms and their physicochemical properties are not fully understood. Fundamentally, flux regulation can be explained with a chemical kinetic formalism describing the transitions between discrete states, with the reaction rates defined by an underlying free energy landscape. Which features of the energy landscape affect the flux distribution? Here we prove that the ratios of the steady-state fluxes of quasi-first-order biochemical processes are invariant to energy perturbations of the discrete states and are only affected by the energy barriers. In other words, the nonequilibrium flux distribution is under kinetic and not thermodynamic control. We illustrate the generality of this result for three biological processes. For the network describing protein folding along competing pathways, the probabilities of proceeding via these pathways are shown to be invariant to the stability of the intermediates or to the presence of additional misfolded states. For the network describing protein synthesis, the error rate and the energy expenditure per peptide bond is proven to be independent of the stability of the intermediate states. For molecular motors such as myosin-V, the ratio of forward to backward steps and the number of adenosine 5'-triphosphate (ATP) molecules hydrolyzed per step is demonstrated to be invariant to energy perturbations of the intermediate states. These findings place important constraints on the ability of mutations and drug perturbations to affect the steady-state flux distribution for a wide class of biological processes.

Metabolic stress promotes stop-codon readthrough and phenotypic heterogeneity.

Accurate protein synthesis is a tightly controlled biological process with multiple quality control steps safeguarded by aminoacyl-transfer RNA (tRNA) synthetases and the ribosome. Reduced translational accuracy leads to various physiological changes in both prokaryotes and eukaryotes. Termination of translation is signaled by stop codons and catalyzed by release factors. Occasionally, stop codons can be suppressed by near-cognate aminoacyl-tRNAs, resulting in protein variants with extended C termini. We have recently shown that stop-codon readthrough is heterogeneous among single bacterial cells. However, little is known about how environmental factors affect the level and heterogeneity of stop-codon readthrough. In this study, we have combined dual-fluorescence reporters, mass spectrometry, mathematical modeling, and single-cell approaches to demonstrate that a metabolic stress caused by excess carbon substantially increases both the level and heterogeneity of stop-codon readthrough. Excess carbon leads to accumulation of acid metabolites, which lower the pH and the activity of release factors to promote readthrough. Furthermore, our time-lapse microscopy experiments show that single cells with high readthrough levels are more adapted to severe acid stress conditions and are more sensitive to an aminoglycoside antibiotic. Our work thus reveals a metabolic stress that promotes translational heterogeneity and phenotypic diversity.

Overlaid positive and negative feedback loops shape dynamical properties of PhoPQ two-component system.

Bacteria use two-component systems (TCSs) to sense environmental conditions and change gene expression in response to those conditions. To amplify cellular responses, many bacterial TCSs are under positive feedback control, i.e. increase their expression when activated. Escherichia coli Mg2+ -sensing TCS, PhoPQ, in addition to the positive feedback, includes a negative feedback loop via the upregulation of the MgrB protein that inhibits PhoQ. How the interplay of these feedback loops shapes steady-state and dynamical responses of PhoPQ TCS to change in Mg2+ remains poorly understood. In particular, how the presence of MgrB feedback affects the robustness of PhoPQ response to overexpression of TCS is unclear. It is also unclear why the steady-state response to decreasing Mg2+ is biphasic, i.e. plateaus over a range of Mg2+ concentrations, and then increases again at growth-limiting Mg2+. In this study, we use mathematical modeling to identify potential mechanisms behind these experimentally observed dynamical properties. The results make experimentally testable predictions for the regime with response robustness and propose a novel explanation of biphasic response constraining the mechanisms for modulation of PhoQ activity by Mg2+ and MgrB. Finally, we show how the interplay of positive and negative feedback loops affects the network's steady-state sensitivity and response dynamics. In the absence of MgrB feedback, the model predicts oscillations thereby suggesting a general mechanism of oscillatory or pulsatile dynamics in autoregulated TCSs. These results improve the understanding of TCS signaling and other networks with overlaid positive and negative feedback.

A synthetic system for asymmetric cell division in Escherichia coli.

We describe a synthetic genetic circuit for controlling asymmetric cell division in Escherichia coli in which a progenitor cell creates a differentiated daughter cell while retaining its original phenotype. Specifically, we engineered an inducible system that can bind and segregate plasmid DNA to a single position in the cell. Upon cell division, colocalized plasmids are kept by one and only one of the daughter cells. The other daughter cell receives no plasmid DNA and is irreversibly differentiated from its sibling. In this way, we achieved asymmetric cell division through asymmetric plasmid partitioning. We then used this system to achieve physical separation of genetically distinct cells by tying motility to differentiation. Finally, we characterized an orthogonal inducible circuit that enables the simultaneous asymmetric partitioning of two plasmid species, resulting in cells that have four distinct differentiated states. These results point the way toward the engineering of multicellular systems from prokaryotic hosts.

Elucidating interplay of speed and accuracy in biological error correction.

One of the most fascinating features of biological systems is the ability to sustain high accuracy of all major cellular processes despite the stochastic nature of underlying chemical processes. It is widely believed that such low error values are the result of the error-correcting mechanism known as kinetic proofreading. However, it is usually argued that enhancing the accuracy should result in slowing down the process, leading to the so-called speed-accuracy trade-off. We developed a discrete-state stochastic framework that allowed us to investigate the mechanisms of the proofreading using the method of first-passage processes. With this framework, we simultaneously analyzed the speed and accuracy of the two fundamental biological processes, DNA replication and tRNA selection during the translation. The results indicate that these systems tend to optimize speed rather than accuracy, as long as the error level is tolerable. Interestingly, for these processes, certain kinetic parameters lay in the suboptimal region where their perturbations can improve both speed and accuracy. Additional constraints due to the energetic cost of proofreading also play a role in the error correcting process. Our theoretical findings provide a microscopic picture of how complex biological processes are able to function so fast with high accuracy.

Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development.

Collective cell movement is critical to the emergent properties of many multicellular systems, including microbial self-organization in biofilms, embryogenesis, wound healing, and cancer metastasis. However, even the best-studied systems lack a complete picture of how diverse physical and chemical cues act upon individual cells to ensure coordinated multicellular behavior. Known for its social developmental cycle, the bacterium Myxococcus xanthus uses coordinated movement to generate three-dimensional aggregates called fruiting bodies. Despite extensive progress in identifying genes controlling fruiting body development, cell behaviors and cell-cell communication mechanisms that mediate aggregation are largely unknown. We developed an approach to examine emergent behaviors that couples fluorescent cell tracking with data-driven models. A unique feature of this approach is the ability to identify cell behaviors affecting the observed aggregation dynamics without full knowledge of the underlying biological mechanisms. The fluorescent cell tracking revealed large deviations in the behavior of individual cells. Our modeling method indicated that decreased cell motility inside the aggregates, a biased walk toward aggregate centroids, and alignment among neighboring cells in a radial direction to the nearest aggregate are behaviors that enhance aggregation dynamics. Our modeling method also revealed that aggregation is generally robust to perturbations in these behaviors and identified possible compensatory mechanisms. The resulting approach of directly combining behavior quantification with data-driven simulations can be applied to more complex systems of collective cell movement without prior knowledge of the cellular machinery and behavioral cues.

On the mechanism of long-range orientational order of fibroblasts.

Long-range alignment ordering of fibroblasts have been observed in the vicinity of cancerous tumors and can be recapitulated with in vitro experiments. However, the mechanisms driving their ordering are not understood. Here, we show that local collision-driven nematic alignment interactions among fibroblasts are insufficient to explain observed long-range alignment. One possibility is that there exists another orientation field coevolving with the cells and reinforcing their alignment. We propose that this field reflects the mechanical cross-talk between the fibroblasts and the underlying fibrous material on which they move. We show that this long-range interaction can give rise to high nematic order and to the observed patterning of the cancer microenvironment.

Agent-Based Modeling Reveals Possible Mechanisms for Observed Aggregation Cell Behaviors.

Myxococcus xanthus is a soil bacterium that serves as a model system for biological self-organization. Cells form distinct, dynamic patterns depending on environmental conditions. An agent-based model was used to understand how M. xanthus cells aggregate into multicellular mounds in response to starvation. In this model, each cell is modeled as an agent represented by a point particle and characterized by its position and moving direction. At low agent density, the model recapitulates the dynamic patterns observed by experiments and a previous biophysical model. To study aggregation at high cell density, we extended the model based on the recent experimental observation that cells exhibit biased movement toward aggregates. We tested two possible mechanisms for this biased movement and demonstrate that a chemotaxis model with adaptation can reproduce the observed experimental results leading to the formation of stable aggregates. Furthermore, our model reproduces the experimentally observed patterns of cell alignment around aggregates.

Mechanism of Kin-Discriminatory Demarcation Line Formation between Colonies of Swarming Bacteria.

Swarming bacteria use kin discrimination to preferentially associate with their clonemates for certain cooperative behaviors. Kin discrimination can manifest as an apparent demarcation line (a region lacking cells or with much lower cell density) between antagonist strains swarming toward each other. In contrast, two identical strains merge with no demarcation. Experimental studies suggest contact-dependent killing between different strains as a mechanism of kin discrimination, but it is not clear whether this killing is sufficient to explain the observed patterns. Here, we investigate the formation of demarcation line with a mathematical model. First, using data from competition experiments between kin discriminating strains of Myxococcus xanthus and Proteus mirabilis, we found the rates of killing between the strains to be highly asymmetric, i.e., one strain kills another at a much higher rate. Then, to investigate how such asymmetric interactions can lead to a stable demarcation line, we construct reaction-diffusion models for colony expansion of kin-discriminatory strains. Our results demonstrate that a stable demarcation line can form when both cell movement and cell growth cease at low nutrient levels. Further, our study suggests that, depending on the initial separation between the inoculated colonies, the demarcation line may move transiently before stabilizing. We validated these model predictions by observing dynamics of merger between two M. xanthus strains, where one strain expresses a toxin protein that kills a second strain lacking the corresponding antitoxin. Our study therefore provides a theoretical understanding of demarcation line formation between kin-discriminatory populations, and can be used for analyzing and designing future experiments.

Slowdown of growth controls cellular differentiation.

How can changes in growth rate affect the regulatory networks behavior and the outcomes of cellular differentiation? We address this question by focusing on starvation response in sporulating Bacillus subtilis We show that the activity of sporulation master regulator Spo0A increases with decreasing cellular growth rate. Using a mathematical model of the phosphorelay-the network controlling Spo0A-we predict that this increase in Spo0A activity can be explained by the phosphorelay protein accumulation and lengthening of the period between chromosomal replication events caused by growth slowdown. As a result, only cells growing slower than a certain rate reach threshold Spo0A activity necessary for sporulation. This growth threshold model accurately predicts cell fates and explains the distribution of sporulation deferral times. We confirm our predictions experimentally and show that the concentration rather than activity of phosphorelay proteins is affected by the growth slowdown. We conclude that sensing the growth rates enables cells to indirectly detect starvation without the need for evaluating specific stress signals.

Modeling mechanical interactions in growing populations of rod-shaped bacteria.

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell's environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

Role of Autoregulation and Relative Synthesis of Operon Partners in Alternative Sigma Factor Networks.

Despite the central role of alternative sigma factors in bacterial stress response and virulence their regulation remains incompletely understood. Here we investigate one of the best-studied examples of alternative sigma factors: the σB network that controls the general stress response of Bacillus subtilis to uncover widely relevant general design principles that describe the structure-function relationship of alternative sigma factor regulatory networks. We show that the relative stoichiometry of the synthesis rates of σB, its anti-sigma factor RsbW and the anti-anti-sigma factor RsbV plays a critical role in shaping the network behavior by forcing the σB network to function as an ultrasensitive negative feedback loop. We further demonstrate how this negative feedback regulation insulates alternative sigma factor activity from competition with the housekeeping sigma factor for RNA polymerase and allows multiple stress sigma factors to function simultaneously with little competitive interference.

Colony Expansion of Socially Motile Myxococcus xanthus Cells Is Driven by Growth, Motility, and Exopolysaccharide Production.

Myxococcus xanthus, a model organism for studies of multicellular behavior in bacteria, moves exclusively on solid surfaces using two distinct but coordinated motility mechanisms. One of these, social (S) motility is powered by the extension and retraction of type IV pili and requires the presence of exopolysaccharides (EPS) produced by neighboring cells. As a result, S motility requires close cell-to-cell proximity and isolated cells do not translocate. Previous studies measuring S motility by observing the colony expansion of cells deposited on agar have shown that the expansion rate increases with initial cell density, but the biophysical mechanisms involved remain largely unknown. To understand the dynamics of S motility-driven colony expansion, we developed a reaction-diffusion model describing the effects of cell density, EPS deposition and nutrient exposure on the expansion rate. Our results show that at steady state the population expands as a traveling wave with a speed determined by the interplay of cell motility and growth, a well-known characteristic of Fisher's equation. The model explains the density-dependence of the colony expansion by demonstrating the presence of a lag phase-a transient period of very slow expansion with a duration dependent on the initial cell density. We propose that at a low initial density, more time is required for the cells to accumulate enough EPS to activate S-motility resulting in a longer lag period. Furthermore, our model makes the novel prediction that following the lag phase the population expands at a constant rate independent of the cell density. These predictions were confirmed by S motility experiments capturing long-term expansion dynamics.

Non-monotonic Response to Monotonic Stimulus: Regulation of Glyoxylate Shunt Gene-Expression Dynamics in Mycobacterium tuberculosis.

Understanding how dynamical responses of biological networks are constrained by underlying network topology is one of the fundamental goals of systems biology. Here we employ monotone systems theory to formulate a theorem stating necessary conditions for non-monotonic time-response of a biochemical network to a monotonic stimulus. We apply this theorem to analyze the non-monotonic dynamics of the σB-regulated glyoxylate shunt gene expression in Mycobacterium tuberculosis cells exposed to hypoxia. We first demonstrate that the known network structure is inconsistent with observed dynamics. To resolve this inconsistency we employ the formulated theorem, modeling simulations and optimization along with follow-up dynamic experimental measurements. We show a requirement for post-translational modulation of σB activity in order to reconcile the network dynamics with its topology. The results of this analysis make testable experimental predictions and demonstrate wider applicability of the developed methodology to a wide class of biological systems.

The Psp system of Mycobacterium tuberculosis integrates envelope stress-sensing and envelope-preserving functions.

The bacterial envelope integrates essential stress-sensing and adaptive functions; thus, envelope-preserving functions are important for survival. In Gram-negative bacteria, envelope integrity during stress is maintained by the multi-gene Psp response. Mycobacterium tuberculosis was thought to lack the Psp system since it encodes only pspA and no other psp ortholog. Intriguingly, pspA maps downstream from clgR, which encodes a transcription factor regulated by the MprAB-σ(E) envelope-stress-signaling system. clgR inactivation lowered ATP concentration during stress and protonophore treatment-induced clgR-pspA expression, suggesting that these genes express Psp-like functions. We identified a four-gene set - clgR, pspA (rv2744c), rv2743c, rv2742c - that is regulated by clgR and in turn regulates ClgR activity. Regulatory and protein-protein interactions within the set and a requirement of the four genes for functions associated with envelope integrity and surface-stress tolerance indicate that a Psp-like system has evolved in mycobacteria. Among Actinobacteria, the four-gene module occurred only in tuberculous mycobacteria and was required for intramacrophage growth, suggesting links between its function and mycobacterial virulence. Additionally, the four-gene module was required for MprAB-σ(E) stress-signaling activity. The positive feedback between envelope-stress-sensing and envelope-preserving functions allows sustained responses to multiple, envelope-perturbing signals during chronic infection, making the system uniquely suited to tuberculosis pathogenesis.

Mechanism for Collective Cell Alignment in Myxococcus xanthus Bacteria.

Myxococcus xanthus cells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized that M. xanthus cells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individual M. xanthus cell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversing M. xanthus mutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species.

Unraveling the regulatory connections between two controllers of breast cancer cell fate.

Estrogen receptor alpha (ERα) expression is critical for breast cancer classification, high ERα expression being associated with better prognosis. ERα levels strongly correlate with that of GATA binding protein 3 (GATA3), a major regulator of ERα expression. However, the mechanistic details of ERα-GATA3 regulation remain incompletely understood. Here we combine mathematical modeling with perturbation experiments to unravel the nature of regulatory connections in the ERα-GATA3 network. Through cell population-average, single-cell and single-nucleus measurements, we show that the cross-regulation between ERα and GATA3 amounts to overall negative feedback. Further, mathematical modeling reveals that GATA3 positively regulates its own expression and that ERα autoregulation is most likely absent. Lastly, we show that the two cross-regulatory connections in the ERα-GATA3 negative feedback network decrease the noise in ERα or GATA3 expression. This may ensure robust cell fate maintenance in the face of intracellular and environmental fluctuations, contributing to tissue homeostasis in normal conditions, but also to the maintenance of pathogenic states during cancer progression.