Stochastic antagonism between two proteins governs a bacterial cell fate switch

Active interface bulging in Bacillus subtilis swarms promotes self-assembly and biofilm formation

Microbial communities such as biofilms are commonly found at interfaces. However, it is unclear how the physical environment of interfaces may contribute to the development and behavior of surface-associated microbial communities. Combining multimode imaging, single-cell tracking, and numerical simulations, here, we found that activity-induced interface bulging promotes colony biofilm formation in Bacillus subtilis swarms presumably via segregation and enrichment of sessile cells in the bulging area. Specifically, the diffusivity of passive particles is ~50% lower inside the bulging area than elsewhere, which enables a diffusion-trapping mechanism for self-assembly and may account for the enrichment of sessile cells. We also uncovered a quasilinear relation between cell speed and surface-packing density that underlies the process of active interface bulging. Guided by the speed-density relation, we demonstrated reversible formation of liquid bulges by manipulating the speed and local density of cells with light. Over the course of development, the active bulges turned into striped biofilm structures, which eventually give rise to a large-scale ridge pattern. Our findings reveal a unique physical mechanism of biofilm formation at air-solid interface, which is pertinent to engineering living materials and directed self-assembly in active fluids.

Bacterial cell differentiation enables population level survival strategies

Clonal reproduction of unicellular organisms ensures the stable inheritance of genetic information. However, this means of reproduction lacks an intrinsic basis for genetic variation, other than spontaneous mutation and horizontal gene transfer. To make up for this lack of genetic variation, many unicellular organisms undergo the process of cell differentiation to achieve phenotypic heterogeneity within isogenic populations. Cell differentiation is either an inducible or obligate program. Induced cell differentiation can occur as a response to a stimulus, such as starvation or host cell invasion, or it can be a stochastic process. In contrast, obligate cell differentiation is hardwired into the organism's life cycle. Whether induced or obligate, bacterial cell differentiation requires the activation of a signal transduction pathway that initiates a global change in gene expression and ultimately results in a morphological change. While cell differentiation is considered a hallmark in the development of multicellular organisms, many unicellular bacteria utilize this process to implement survival strategies. In this review, we describe well-characterized cell differentiation programs to highlight three main survival strategies used by bacteria capable of differentiation: (i) environmental adaptation, (ii) division of labor, and (iii) bet-hedging.

Regulation of biofilm gene expression by DNA replication in Bacillus subtilis

Bacillus subtilis relies on biofilms for survival in harsh environments. Extracellular polymeric substance (EPS) is a crucial component of biofilms, yet the dynamics of EPS production in single cells remain elusive. To unveil the modulation of EPS synthesis, we built a minimal network model comprising the SinI-SinR-SlrR module, Spo0A, and EPS. Stochastic simulations revealed that antagonistic interplay between SinI and SinR enables EPS production in bursts. SlrR widens these bursts and increases their frequency by stabilizing SinR-SlrR complexes and depleting free SinR. DNA replication and chromosomal positioning of key genes dictate pulsatile changes in the slrR:sinR gene dosage ratio (gr) and Spo0A-P levels, each promoting EPS production in distinct phases of the cell cycle. As the cell cycle lengthens with nutrient stress, the duty cycle of gr pulsing decreases, whereas the amplitude of Spo0A-P pulses elevates. This coordinated response facilitates keeping a constant proportion of EPS-secreting cells within colonies across diverse nutrient conditions. Our results suggest that bacteria may 'encode' eps expression through strategic chromosomal organization. This work illuminates how stochastic protein interactions, gene copy number imbalance, and cell-cycle dynamics orchestrate EPS synthesis, offering a deeper understanding of biofilm formation.

A logic-incorporated gene regulatory network deciphers principles in cell fate decisions

Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.

The motility-matrix production switch in Bacillus subtilis-a modeling perspective

Phenotype switching can be triggered by external stimuli and by intrinsic stochasticity. Here, we focus on the motility-matrix production switch in Bacillus subtilis. We use modeling to describe the SinR-SlrR bistable switch and its regulation by SinI and to distinguish different sources of stochasticity. Our simulations indicate that intrinsic fluctuations in the synthesis of SinI are insufficient to drive spontaneous switching and suggest that switching is triggered by upstream noise from the Spo0A phosphorelay. IMPORTANCE The switch from motility to matrix production is the first step toward biofilm formation and, thus, to multicellular behavior in Bacillus subtilis. The transition is governed by a bistable switch based on the interplay of the regulators SinR and SlrR, while SinI transmits upstream signals to that switch. Quantitative modeling can be used to study the switching dynamics. Here, we build such a model step by step to describe the dynamics of the switch and its regulation and to study how spontaneous switching is triggered by upstream noise from the Spo0A phosphorelay.

Microbial models of development: Inspiration for engineering self-assembled synthetic multicellularity

While the field of synthetic developmental biology has traditionally focused on the study of the rich developmental processes seen in metazoan systems, an attractive alternate source of inspiration comes from microbial developmental models. Microbes face unique lifestyle challenges when forming emergent multicellular collectives. As a result, the solutions they employ can inspire the design of novel multicellular systems. In this review, we dissect the strategies employed in multicellular development by two model microbial systems: the cellular slime mold Dictyostelium discoideum and the biofilm-forming bacterium Bacillus subtilis. Both microbes face similar challenges but often have different solutions, both from metazoan systems and from each other, to create emergent multicellularity. These challenges include assembling and sustaining a critical mass of participating individuals to support development, regulating entry into development, and assigning cell fates. The mechanisms these microbial systems exploit to robustly coordinate development under a wide range of conditions offer inspiration for a new toolbox of solutions to the synthetic development community. Additionally, recreating these phenomena synthetically offers a pathway to understanding the key principles underlying how these behaviors are coordinated naturally.

The Slowdown of Growth Rate Controls the Single-Cell Distribution of Biofilm Matrix Production via an SinI-SinR-SlrR Network

In Bacillus subtilis, master regulator Spo0A controls several cell-differentiation pathways. Under moderate starvation, phosphorylated Spo0A (Spo0A~P) induces biofilm formation by indirectly activating genes controlling matrix production in a subpopulation of cells via an SinI-SinR-SlrR network. Under severe starvation, Spo0A~P induces sporulation by directly and indirectly regulating sporulation gene expression. However, what determines the heterogeneity of individual cell fates is not fully understood. In particular, it is still unclear why, despite being controlled by a single master regulator, biofilm matrix production and sporulation seem mutually exclusive on a single-cell level. In this work, with mathematical modeling, we showed that the fluctuations in the growth rate and the intrinsic noise amplified by the bistability in the SinI-SinR-SlrR network could explain the single-cell distribution of matrix production. Moreover, we predicted an incoherent feed-forward loop; the decrease in the cellular growth rate first activates matrix production by increasing in Spo0A phosphorylation level but then represses it via changing the relative concentrations of SinR and SlrR. Experimental data provide evidence to support model predictions. In particular, we demonstrate how the degree to which matrix production and sporulation appear mutually exclusive is affected by genetic perturbations. IMPORTANCE The mechanisms of cell-fate decisions are fundamental to our understanding of multicellular organisms and bacterial communities. However, even for the best-studied model systems we still lack a complete picture of how phenotypic heterogeneity of genetically identical cells is controlled. Here, using B. subtilis as a model system, we employ a combination of mathematical modeling and experiments to explain the population-level dynamics and single-cell level heterogeneity of matrix gene expression. The results demonstrate how the two cell fates, biofilm matrix production and sporulation, can appear mutually exclusive without explicitly inhibiting one another. Such a mechanism could be used in a wide range of other biological systems.

The Biofilm Regulatory Network from Bacillus subtilis: A Structure-Function Analysis

Bacterial biofilms are notorious for their ability to protect bacteria from environmental challenges, most importantly the action of antibiotics. Bacillus subtilis is an extensively studied model organism used to understand the process of biofilm formation. A complex network of principal regulatory proteins including Spo0A, AbrB, AbbA, Abh, SinR, SinI, SlrR, and RemA, work in concert to transition B. subtilis from the free-swimming planktonic state to the biofilm state. In this review, we explore, connect, and summarize decades worth of structural and biochemical studies that have elucidated this protein signaling network. Since structure dictates function, unraveling aspects of protein molecular mechanisms will allow us to devise ways to exploit critical features of the biofilm regulatory pathway, such as possible therapeutic intervention. This review pools our current knowledge base of B. subtilis biofilm regulatory proteins and highlights potential therapeutic intervention points.

Synthetic Micrographs of Bacteria (SyMBac) allows accurate segmentation of bacterial cells using deep neural networks

BACKGROUND

Deep-learning-based image segmentation models are required for accurate processing of high-throughput timelapse imaging data of bacterial cells. However, the performance of any such model strictly depends on the quality and quantity of training data, which is difficult to generate for bacterial cell images. Here, we present a novel method of bacterial image segmentation using machine learning models trained with Synthetic Micrographs of Bacteria (SyMBac).

RESULTS

We have developed SyMBac, a tool that allows for rapid, automatic creation of arbitrary amounts of training data, combining detailed models of cell growth, physical interactions, and microscope optics to create synthetic images which closely resemble real micrographs, and is capable of training accurate image segmentation models. The major advantages of our approach are as follows: (1) synthetic training data can be generated virtually instantly and on demand; (2) these synthetic images are accompanied by perfect ground truth positions of cells, meaning no data curation is required; (3) different biological conditions, imaging platforms, and imaging modalities can be rapidly simulated, meaning any change in one's experimental setup no longer requires the laborious process of manually generating new training data for each change. Deep-learning models trained with SyMBac data are capable of analysing data from various imaging platforms and are robust to drastic changes in cell size and morphology. Our benchmarking results demonstrate that models trained on SyMBac data generate more accurate cell identifications and precise cell masks than those trained on human-annotated data, because the model learns the true position of the cell irrespective of imaging artefacts. We illustrate the approach by analysing the growth and size regulation of bacterial cells during entry and exit from dormancy, which revealed novel insights about the physiological dynamics of cells under various growth conditions.

CONCLUSIONS

The SyMBac approach will help to adapt and improve the performance of deep-learning-based image segmentation models for accurate processing of high-throughput timelapse image data.

Intercellular interaction mechanisms promote diversity in intracellular ATP concentration in Escherichia coli populations

In fluctuating environments, many microorganisms acquire phenotypic heterogeneity as a survival tactic to increase the likelihood of survival of the overall population. One example of this interindividual heterogeneity is the diversity of ATP concentration among members of Escherichia coli populations under glucose deprivation. Despite the importance of such environmentally driven phenotypic heterogeneity, how the differences in intracellular ATP concentration emerge among individual E. coli organisms is unknown. In this study, we focused on the mechanism through which individual E. coli achieve high intracellular ATP concentrations. First, we measured the ATP retained by E. coli over time when cultured at low (0.1 mM) and control (22.2 mM) concentrations of glucose and obtained the chronological change in ATP concentrations. Then, by comparing these chronological change of ATP concentrations and analyzing whether stochastic state transitions, periodic oscillations, cellular age, and intercellular communication-which have been reported as molecular biological mechanisms for generating interindividual heterogeneity-are involved, we showed that the appearance of high ATP-holding individuals observed among E. coli can be explained only by intercellular transmission. By performing metabolomic analysis of post-culture medium, we revealed a significant increase in the ATP, especially at low glucose, and that the number of E. coli that retain significantly higher ATP can be controlled by adding large amounts of ATP to the medium, even in populations cultured under control glucose concentrations. These results reveal for the first time that ATP-mediated intercellular transmission enables some individuals in E. coli populations grown at low glucose to retain large amounts of ATP.

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.

Do microbes have a memory? History-dependent behavior in the adaptation to variable environments

Microbes are constantly confronted with changes and challenges in their environment. A proper response to these environmental cues is needed for optimal cellular functioning and fitness. Interestingly, past exposure to environmental cues can accelerate or boost the response when this condition returns, even in daughter cells that have not directly encountered the initial cue. Moreover, this behavior is mostly epigenetic and often goes hand in hand with strong heterogeneity in the strength and speed of the response between isogenic cells of the same population, which might function as a bet-hedging strategy. In this review, we discuss examples of history-dependent behavior (HDB) or “memory,” with a specific focus on HDB in fluctuating environments. In most examples discussed, the lag time before the response to an environmental change is used as an experimentally measurable proxy for HDB. We highlight different mechanisms already implicated in HDB, and by using HDB in fluctuating carbon conditions as a case study, we showcase how the metabolic state of a cell can be a key determining factor for HDB. Finally, we consider possible evolutionary causes and consequences of such HDB.

Biophysical aspects underlying the swarm to biofilm transition

Bacteria organize in a variety of collective states, from swarming-rapid surface exploration, to biofilms-highly dense immobile communities attributed to stress resistance. It has been suggested that biofilm and swarming are oppositely controlled, making this transition particularly interesting for understanding the ability of bacterial colonies to adapt to challenging environments. Here, the swarm to biofilm transition is studied in Bacillus subtilis by analyzing the bacterial dynamics both on the individual and collective scales. We show that both biological and physical processes facilitate the transition. A few individual cells that initiate the biofilm program cause nucleation of large, approximately scale-free, stationary aggregates of trapped swarm cells. Around aggregates, cells continue swarming almost unobstructed, while inside, trapped cells are added to the biofilm. While our experimental findings rule out previously suggested purely physical effects as a trigger for biofilm formation, they show how physical processes, such as clustering and jamming, accelerate biofilm formation.

Quantification of transcription noise’s impact on cell fate commitment with digital resolutions

Motivation

Gene transcription is a random and noisy process. Tremendous efforts in single cell studies have been mapping transcription noises to phenotypic variabilities between isogenic cells. However, the exact role of the noise in cell fate commitment remains largely descriptive or even controversial.

Results

For a specified cell fate, we define the jumping digit I of a critical gene as a statistical threshold that a single cell has approximately an equal chance to commit the fate as to have at least I transcripts of the gene. When the transcription is perturbed by a noise enhancer without changing the basal transcription level E  0, we find a crossing digit k such that the noise catalyzes cell fate change when I > k while stabilizes the current state when I < k; k remains stable against enormous variations of kinetic rates. We further test the reactivation of latent HIV in 22 integration sites by noise enhancers paired with transcriptional activators. Strong synergistic actions are observed when the activators increase transcription burst frequency, whereas no synergism, but antagonism, is often observed if activators increase burst size. The synergistic efficiency can be predicted accurately by the ratio I / E0. When the noise enhancers double the noise, the activators double the burst frequency, and I / E0 ≥ 7, their combination is 10 times more effective than their additive effects across all 22 sites.

Availability and implementation

The jumping digit I may provide a novel probe to explore the phenotypic consequences of transcription noise in cell functions. Code is freely available at http://cam.gzhu.edu.cn/info/1014/1223.htm.

Supplementary information

Supplementary data are available at Bioinformatics online.

Bacillus subtilis Histidine Kinase KinC Activates Biofilm Formation by Controlling Heterogeneity of Single-Cell Responses

In Bacillus subtilis, biofilm and sporulation pathways are both controlled by a master regulator, Spo0A, which is activated by phosphorylation via a phosphorelay-a cascade of phosphotransfer reactions commencing with autophosphorylation of histidine kinases KinA, KinB, KinC, KinD, and KinE. However, it is unclear how the kinases, despite acting via the same regulator, Spo0A, differentially regulate downstream pathways, i.e., how KinA mainly activates sporulation genes and KinC mainly activates biofilm genes. In this work, we found that KinC also downregulates sporulation genes, suggesting that KinC has a negative effect on Spo0A activity. To explain this effect, with a mathematical model of the phosphorelay, we revealed that unlike KinA, which always activates Spo0A, KinC has distinct effects on Spo0A at different growth stages: during fast growth, KinC acts as a phosphate source and activates Spo0A, whereas during slow growth, KinC becomes a phosphate sink and contributes to decreasing Spo0A activity. However, under these conditions, KinC can still increase the population-mean biofilm matrix production activity. In a population, individual cells grow at different rates, and KinC would increase the Spo0A activity in the fast-growing cells but reduce the Spo0A activity in the slow-growing cells. This mechanism reduces single-cell heterogeneity of Spo0A activity, thereby increasing the fraction of cells that activate biofilm matrix production. Thus, KinC activates biofilm formation by controlling the fraction of cells activating biofilm gene expression. IMPORTANCE In many bacterial and eukaryotic systems, multiple cell fate decisions are activated by a single master regulator. Typically, the activities of the regulators are controlled posttranslationally in response to different environmental stimuli. The mechanisms underlying the ability of these regulators to control multiple outcomes are not understood in many systems. By investigating the regulation of Bacillus subtilis master regulator Spo0A, we show that sensor kinases can use a novel mechanism to control cell fate decisions. By acting as a phosphate source or sink, kinases can interact with one another and provide accurate regulation of the phosphorylation level. Moreover, this mechanism affects the cell-to-cell heterogeneity of the transcription factor activity and eventually determines the fraction of different cell types in the population. These results demonstrate the importance of intercellular heterogeneity for understanding the effects of genetic perturbations on cell fate decisions. Such effects can be applicable to a wide range of cellular systems.

Neurons as will and representation

Memory recollections and voluntary actions are often perceived as spontaneously generated irrespective of external stimuli. Although products of our neurons, they are only rarely accessible in humans at the neuronal level. Here I review insights gleaned from unique neurosurgical opportunities to record and stimulate single-neuron activity in people who can declare their thoughts, memories and wishes. I discuss evidence that the subjective experience of human recollection and that of voluntary action arise from the activity of two internal neuronal generators, the former from medial temporal lobe reactivation and the latter from frontoparietal preactivation. I characterize properties of these generators and their interaction, enabling flexible recruitment of memory-based choices for action as well as recruitment of action-based plans for the representation of conceptual knowledge in memories. Both internal generators operate on surprisingly explicit but different neuronal codes, which appear to arise with distinct single-neuron activity, often observed before participants' reports of conscious awareness. I discuss prediction of behaviour based on these codes, and the potential for their modulation. The prospects of editing human memories and volitions by enhancement, inception or deletion of specific, selected content raise therapeutic possibilities and ethical concerns.

Formation, collective motion, and merging of macroscopic bacterial aggregates

Chemotactic bacteria form emergent spatial patterns of variable cell density within cultures that are initially spatially uniform. These patterns are the result of chemical gradients that are created from the directed movement and metabolic activity of billions of cells. A recent study on pattern formation in wild bacterial isolates has revealed unique collective behaviors of the bacteria Enterobacter cloacae. As in other bacterial species, Enterobacter cloacae form macroscopic aggregates. Once formed, these bacterial clusters can migrate several millimeters, sometimes resulting in the merging of two or more clusters. To better understand these phenomena, we examine the formation and dynamics of thousands of bacterial clusters that form within a 22 cm square culture dish filled with soft agar over two days. At the macroscale, the aggregates display spatial order at short length scales, and the migration of cell clusters is superdiffusive, with a merging acceleration that is correlated with aggregate size. At the microscale, aggregates are composed of immotile cells surrounded by low density regions of motile cells. The collective movement of the aggregates is the result of an asymmetric flux of bacteria at the boundary. An agent-based model is developed to examine how these phenomena are the result of both chemotactic movement and a change in motility at high cell density. These results identify and characterize a new mechanism for collective bacterial motility driven by a transient, density-dependent change in motility.

Bacteria growing and swimming in soft agar often aggregate to form elaborate spatial patterns. Here we examine the patterns formed by the bacteria Enterobacter cloacae. An unusual behavior of these bacteria is the collective movement of cells after the initial aggregation into a tiny spot. Despite the majority of the cells within an aggregate being immotile at any point in the time, the flux of cells entering and leaving the aggregate, as motility is lost and regained in individual cells, led to a net, collective movement of the aggregate. These spots sometimes run into each other and combine. By looking at the cells within these spots under a microscope, we find that cells within each spot stop swimming. The process of switching back and forth between swimming and not swimming causes the movement and fusion of the spots. A numerical simulation shows that the migration and merging of these spots can be expected if the cells swim towards regions of space with high concentrations of attractant molecules and stop swimming in locations crowded with many cells. This work identifies a novel process through which populations of bacteria cooperate and control the movement of large groups of cells.

Volumetric compression develops noise-driven single-cell heterogeneity

Recent studies have revealed that extensive heterogeneity of biological systems arises through various routes ranging from intracellular chromosome segregation to spatiotemporally varying biochemical stimulations. However, the contribution of physical microenvironments to single-cell heterogeneity remains largely unexplored. Here, we show that a homogeneous population of non-small-cell lung carcinoma develops into heterogeneous subpopulations upon application of a homogeneous physical compression, as shown by single-cell transcriptome profiling. The generated subpopulations stochastically gain the signature genes associated with epithelial-mesenchymal transition (EMT; VIM, CDH1, EPCAM, ZEB1, and ZEB2) and cancer stem cells (MKI67, BIRC5, and KLF4), respectively. Trajectory analysis revealed two bifurcated paths as cells evolving upon the physical compression, along each path the corresponding signature genes (epithelial or mesenchymal) gradually increase. Furthermore, we show that compression increases gene expression noise, which interplays with regulatory network architecture and thus generates differential cell-fate outcomes. The experimental observations of both single-cell sequencing and single-molecule fluorescent in situ hybridization agrees well with our computational modeling of regulatory network in the EMT process. These results demonstrate a paradigm of how mechanical stimulations impact cell-fate determination by altering transcription dynamics; moreover, we show a distinct path that the ecology and evolution of cancer interplay with their physical microenvironments from the view of mechanobiology and systems biology, with insight into the origin of single-cell heterogeneity.

Memory shapes microbial populations

Correct decision making is fundamental for all living organisms to thrive under environmental changes. The patterns of environmental variation and the quality of available information define the most favourable strategy among multiple options, from randomly adopting a phenotypic state to sensing and reacting to environmental cues. Cellular memory—the ability to track and condition the time to switch to a different phenotypic state—can help withstand environmental fluctuations. How does memory manifest itself in unicellular organisms? We describe the population-wide consequences of phenotypic memory in microbes through a combination of deterministic modelling and stochastic simulations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that memory in individual cells generates patterns at the population level coherent with overshoots and non-exponential lag times distributions experimentally observed in phenotypically heterogeneous populations. We emphasise the implications of our work in understanding antibiotic tolerance and, in general, bacterial survival under fluctuating environments.

While being genetically the same, a population of cells can show phenotypic variability even under homogeneous environments. Often advantageous under heterogeneous environments, this phenotypic heterogeneity is highly relevant in the studies of antibiotic resistance evolution and cancer resurgence. Numerous theoretical models exist applying a simple model of phenotypic switching. Experimental measurements on phenotypic heterogeneity have increased in precision over the past decade, and the simple models are inadequate to explain the new observations. In this paper, we explore the role of cellular memory as a crucial component of phenotypic switching. We see that memory helps account for the hitherto unexplained observations and fundamentally extend our understanding of phenotypic heterogeneity.

Perfect adaptation in biology

A distinctive feature of many biological systems is their ability to adapt to persistent stimuli or disturbances that would otherwise drive them away from a desirable steady state. The resulting stasis enables organisms to function reliably while being subjected to very different external environments. This perspective concerns a stringent type of biological adaptation, robust perfect adaptation (RPA), that is resilient to certain network and parameter perturbations. As in engineered control systems, RPA requires that the regulating network satisfy certain structural constraints that cannot be avoided. We elucidate these ideas using biological examples from systems and synthetic biology. We then argue that understanding the structural constraints underlying RPA allows us to look past implementation details and offers a compelling means to unravel regulatory biological complexity.

Regulator-dependent temporal dynamics of a restriction-modification system's gene expression upon entering new host cells: single-cell and population studies

Restriction-modification (R-M) systems represent a first line of defense against invasive DNAs, such as bacteriophage DNAs, and are widespread among bacteria and archaea. By acquiring a Type II R-M system via horizontal gene transfer, the new hosts generally become more resistant to phage infection, through the action of a restriction endonuclease (REase), which cleaves DNA at or near specific sequences. A modification methyltransferase (MTase) serves to protect the host genome against its cognate REase activity. The production of R-M system components upon entering a new host cell must be finely tuned to confer protective methylation before the REase acts, to avoid host genome damage. Some type II R-M systems rely on a third component, the controller (C) protein, which is a transcription factor that regulates the production of REase and/or MTase. Previous studies have suggested C protein effects on the dynamics of expression of an R-M system during its establishment in a new host cell. Here, we directly examine these effects. By fluorescently labelling REase and MTase, we demonstrate that lack of a C protein reduces the delay of REase production, to the point of being simultaneous with, or even preceding, production of the MTase. Single molecule tracking suggests that a REase and a MTase employ different strategies for their target search within host cells, with the MTase spending much more time diffusing in proximity to the nucleoid than does the REase. This difference may partially ameliorate the toxic effects of premature REase expression.

MicroRNA governs bistable cell differentiation and lineage segregation via a noncanonical feedback

Positive feedback driven by transcriptional regulation has long been considered a key mechanism underlying cell lineage segregation during embryogenesis. Using the developing spinal cord as a paradigm, we found that canonical, transcription-driven feedback cannot explain robust lineage segregation of motor neuron subtypes marked by two cardinal factors, Hoxa5 and Hoxc8. We propose a feedback mechanism involving elementary microRNA-mRNA reaction circuits that differ from known feedback loop-like structures. Strikingly, we show that a wide range of biologically plausible post-transcriptional regulatory parameters are sufficient to generate bistable switches, a hallmark of positive feedback. Through mathematical analysis, we explain intuitively the hidden source of this feedback. Using embryonic stem cell differentiation and mouse genetics, we corroborate that microRNA-mRNA circuits govern tissue boundaries and hysteresis upon motor neuron differentiation with respect to transient morphogen signals. Our findings reveal a previously underappreciated feedback mechanism that may have widespread functions in cell fate decisions and tissue patterning.

Microfluidic Single-Cell Phenotyping of the Activity of Peptide-Based Antimicrobials

Antibiotic resistance is a major challenge for modern medicine, and there is a dire need to refresh the antibiotic development pipeline to treat infections that are resistant to currently available drugs. Peptide-based antimicrobials represent a promising source of novel anti-infectives, but their development is severely impeded due to the lack of suitable techniques to accurately quantify their antimicrobial efficacy. A major problem involves the heterogeneity of cellular phenotypes in response to these peptides, even within a clonal population of bacteria. There is thus a need to develop single-cell resolution assays to quantify drug efficacy for these novel therapeutics. We present here a detailed microfluidics-microscopy protocol for testing the efficacy of peptide-based antimicrobials on hundreds to thousands of individual bacteria in well-defined microenvironments. This enables the study of cell-to-cell differences in drug response within a clonal population. It is a highly versatile tool, which can be used to quantify drug efficacy, including the number of individual survivors at defined drug doses; it even enables the potential exploration of the molecular mechanisms of action of the drug, which are often unknown in the early stages of drug development. We present here protocols for working with Escherichia coli, but organisms of different geometric shapes and sizes may also be tested with suitable modifications of the microfluidic device.

From deterministic to fuzzy decision-making in artificial cells

Building autonomous artificial cells capable of homeostasis requires regulatory networks to gather information and make decisions that take time and cost energy. Decisions based on few molecules may be inaccurate but are cheap and fast. Realizing decision-making with a few molecules in artificial cells has remained a challenge. Here, we show decision-making by a bistable gene network in artificial cells with constant protein turnover. Reducing the number of gene copies from 10⁵ to about 10 per cell revealed a transition from deterministic and slow decision-making to a fuzzy and rapid regime dominated by small-number fluctuations. Gene regulation was observed at lower DNA and protein concentrations than necessary in equilibrium, suggesting rate enhancement by co-expressional localization. The high-copy regime was characterized by a sharp transition and hysteresis, whereas the low-copy limit showed strong fluctuations, state switching, and cellular individuality across the decision-making point. Our results demonstrate information processing with low-power consumption inside artificial cells.

The human gut microbiota is neither an organ nor a commensal

The recent explosive increase in the number of works on gut microbiota has been accompanied by the spread of rather vague or improper definitions, chosen more for common use than for experimental evidence. Among them are those defining the human gut microbiota as an organ of our body or as a commensal. But, is the human gut microbiota an organ or a commensal? Here, we address this issue to spearhead a reflection on the real roles of the human gut microbiota in our life. Actually, the misuse of the vocabulary used to describe the properties and functions of the gut microbiota may generate confusion and cause misunderstandings both in the scientific community and among the general public.

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.

Negative Interplay between Biofilm Formation and Competence in the Environmental Strains of Bacillus subtilis

The soil bacterium Bacillus subtilis can form robust biofilms, which are important for its survival in the environment. B. subtilis also exhibits natural competence. By investigating competence development in B. subtilisin situ during biofilm formation, we reveal that robust biofilm formation often greatly reduces the frequency of competent cells within the biofilm. We then characterize a cross-pathway regulation that allows cells in these two developmental events to undergo mutually exclusive cell differentiation during biofilm formation. Finally, we discuss potential biological implications of limiting competence in a bacterial biofilm.

Environmental strains of the soil bacterium Bacillus subtilis have valuable applications in agriculture, industry, and biotechnology; however, environmental strains are genetically less accessible. This reduced accessibility is in sharp contrast to laboratory strains, which are well known for their natural competence, and a limitation in their applications. In this study, we observed that robust biofilm formation by environmental strains of B. subtilis greatly reduced the frequency of competent cells in the biofilm. By using model strain 3610, we revealed a cross-pathway regulation that allows biofilm matrix producers and competence-developing cells to undergo mutually exclusive cell differentiation. We further demonstrated that the competence activator ComK represses the key biofilm regulatory gene sinI by directly binding to the sinI promoter, thus blocking competent cells from simultaneously becoming matrix producers. In parallel, the biofilm activator SlrR represses competence through three distinct mechanisms involving both genetic regulation and cell morphological changes. Finally, we discuss the potential implications of limiting competence in a bacterial biofilm.

IMPORTANCE The soil bacterium Bacillus subtilis can form robust biofilms, which are important for its survival in the environment. B. subtilis also exhibits natural competence. By investigating competence development in B. subtilisin situ during biofilm formation, we reveal that robust biofilm formation often greatly reduces the frequency of competent cells within the biofilm. We then characterize a cross-pathway regulation that allows cells in these two developmental events to undergo mutually exclusive cell differentiation during biofilm formation. Finally, we discuss potential biological implications of limiting competence in a bacterial biofilm.