Response of single bacterial cells to stress gives rise to complex history dependence at the population level

Phenotypic memory in quorum sensing

Quorum sensing (QS) is a regulatory mechanism used by bacteria to coordinate group behavior in response to high cell densities. During QS, cells monitor the concentration of external signals, known as autoinducers, as a proxy for cell density. QS often involves positive feedback loops, leading to the upregulation of genes associated with QS signal production and detection. This results in distinct steady-state concentrations of QS-related molecules in QS-ON and QS-OFF states. Due to the slow decay rates of biomolecules such as proteins, even after removal of the initial stimuli, cells can retain elevated levels of QS-associated biomolecules for extended periods of time. This persistence of biomolecules after the removal of the initial stimuli has the potential to impact the response to future stimuli, indicating a memory of past exposure. This phenomenon, which is a consequence of the carry-over of biomolecules rather than genetic inheritance, is known as "phenotypic" memory. This theoretical study aims to investigate the presence of phenotypic memory in QS and the conditions that influence this memory. Numerical simulations based on ordinary differential equations and analytical modeling were used to study gene expression in response to sudden changes in cell density and extracellular signal concentrations. The model examined the effect of various cellular parameters on the strength of QS memory and the impact on gene regulatory dynamics. The findings revealed that QS memory has a transient effect on the expression of QS-responsive genes. These consequences of QS memory depend strongly on how cell density was perturbed, as well as various cellular parameters, including the Fold Change in the expression of QS-regulated genes, the autoinducer synthesis rate, the autoinducer threshold required for activation, and the cell growth rate.

Microfluidic approaches in microbial ecology

Microbial life is at the heart of many diverse environments and regulates most natural processes, from the functioning of animal organs to the cycling of global carbon. Yet, the study of microbial ecology is often limited by challenges in visualizing microbial processes and replicating the environmental conditions under which they unfold. Microfluidics operates at the characteristic scale at which microorganisms live and perform their functions, thus allowing for the observation and quantification of behaviors such as growth, motility, and responses to external cues, often with greater detail than classical techniques. By enabling a high degree of control in space and time of environmental conditions such as nutrient gradients, pH levels, and fluid flow patterns, microfluidics further provides the opportunity to study microbial processes in conditions that mimic the natural settings harboring microbial life. In this review, we describe how recent applications of microfluidic systems to microbial ecology have enriched our understanding of microbial life and microbial communities. We highlight discoveries enabled by microfluidic approaches ranging from single-cell behaviors to the functioning of multi-cellular communities, and we indicate potential future opportunities to use microfluidics to further advance our understanding of microbial processes and their implications.

Dynamic responses of Salmonella Typhimurium to re-exposure to sublethal ciprofloxacin

This study was designed to evaluate the history-dependent behaviors of Salmonella Typhimurium re-exposed to sublethal levels of ciprofloxacin. The S. Typhimurium cells were pre-exposed to 0 (CON), 1/16 (LOW), 1/8 (MED), and 1/4 (HIGH) minimum inhibitory concentrations (MICs) of ciprofloxacin, followed by re-exposure to the same concentrations. The bacterial growth, postantibiotic effect (PAE), relative fitness, and swimming motility of treatments were evaluated in the absence of ciprofloxacin. The lag phase duration (LPD) was estimate to assess bacterial recovery under ciprofloxacin exposure. A disk diffusion assay was used to determine the cross-resistance and collateral sensitivity of CON, LOW, MED, and HIGH treatments to ciprofloxacin (CIP), ceftriaxone (CEF), erythromycin (ERY), gentamicin (GEN), and polymyxin B (POL). The S. Typhimurium cells pre-exposed to ciprofloxacin were susceptible in antibiotic-free media, showing delayed growth. The highest PAE (>1 h) and bacterial fluctuation (CV = 5%) were observed at the High treatment compared to the CON. The HIGH treatment had the lowest relative fitness levels (0.87) and swimming motility (55 mm). The LPD was significantly decreased at the LOW treatment (1.8 h) when re-exposed to 1/16 × MIC of ciprofloxacin. The LOW, MED, and HIGH treatments showed the cross-resistance to POL and the collateral sensitivity to CEF, ERY, and GEN. The pre-exposure to ciprofloxacin could induce phenotypic diversity, corresponding to the history-dependent behaviors. These results provide important insights for the dynamic nature of bacterial populations when re-exposed to sublethal concentrations of antibiotics.

Interspecies interactions determine growth dynamics of biopolymer-degrading populations in microbial communities

Microbial communities perform essential ecosystem functions such as the remineralization of organic carbon that exists as biopolymers. The first step in mineralization is performed by biopolymer degraders, which harbor enzymes that can break down polymers into constituent oligo- or monomeric forms. The released nutrients not only allow degraders to grow, but also promote growth of cells that either consume the degradation products, i.e., exploiters, or consume metabolites released by the degraders or exploiters, i.e., scavengers. It is currently not clear how such remineralizing communities assemble at the microscale-how interactions between the different guilds influence their growth and spatial distribution, and hence the development and dynamics of the community. Here, we address this knowledge gap by studying marine microbial communities that grow on the abundant marine biopolymer alginate. We used batch growth assays and microfluidics coupled to time-lapse microscopy to quantitatively investigate growth and spatial distribution of single cells. We found that the presence of exploiters or scavengers alters the spatial distribution of degrader cells. In general, exploiters and scavengers-which we collectively refer to as cross-feeder cells-slowed down the growth of degrader cells. In addition, coexistence with cross-feeders altered the production of the extracellular enzymes that break down polymers by degrader cells. Our findings reveal that ecological interactions by nondegrading community members have a profound impact on the functions of microbial communities that remineralize carbon biopolymers in nature.

Phenotypic heterogeneity in the bacterial oxidative stress response is driven by cell-cell interactions

Genetically identical bacterial cells commonly display different phenotypes. This phenotypic heterogeneity is well known for stress responses, where it is often explained as bet hedging against unpredictable environmental threats. Here, we explore phenotypic heterogeneity in a major stress response of Escherichia coli and find it has a fundamentally different basis. We characterize the response of cells exposed to hydrogen peroxide (H2O2) stress in a microfluidic device under constant growth conditions. A machine-learning model reveals that phenotypic heterogeneity arises from a precise and rapid feedback between each cell and its immediate environment. Moreover, we find that the heterogeneity rests upon cell-cell interaction, whereby cells shield each other from H2O2 via their individual stress responses. Our work shows how phenotypic heterogeneity in bacterial stress responses can emerge from short-range cell-cell interactions and result in a collective phenotype that protects a large proportion of the population.

Adaptive laboratory evolution to hypersaline conditions of lactic acid bacteria isolated from seaweed

Seaweed biomass has been proposed as a promising alternative carbon source for fermentation processes using microbial factories. However, the high salinity content of seaweed biomass is a limiting factor in large scale fermentation processes. To address this shortcoming, three bacterial species (Pediococcus pentosaceus, Lactobacillus plantarum, and Enterococcus faecium) were isolated from seaweed biomass and evolved to increasing concentrations of NaCl. Following the evolution period, P. pentosaceus reached a plateau at the initial NaCl concentration, whereas L. plantarum, and E. faecium showed a 1.29 and 1.75-fold increase in their salt tolerance, respectively. The impact that salt evolution had on lactic acid production using hypersaline seaweed hydrolysate was investigated. Salinity evolved L. plantarum produced 1.18-fold more lactic acid than the wild type, and salinity evolved E. faecium was able to produce lactic acid, while the wild type could not. No differences in lactic acid production were observed between the P. pentosaceus salinity evolved and wild type strains. Evolved lineages were analyzed for the molecular mechanisms underlying the observed phenotypes. Mutations were observed in genes affecting the ion balance in the cell, the composition of the cell membrane and proteins acting as regulators. This study demonstrates that bacterial isolates from saline niches are promising microbial factories for the fermentation of saline substrates, without the requirement of previous desalination steps, while preserving high final product yields.

Changes in interactions over ecological time scales influence single-cell growth dynamics in a metabolically coupled marine microbial community

Microbial communities thrive in almost all habitats on earth. Within these communities, cells interact through the release and uptake of metabolites. These interactions can have synergistic or antagonistic effects on individual community members. The collective metabolic activity of microbial communities leads to changes in their local environment. As the environment changes over time, the nature of the interactions between cells can change. We currently lack understanding of how such dynamic feedbacks affect the growth dynamics of individual microbes and of the community as a whole. Here we study how interactions mediated by the exchange of metabolites through the environment change over time within a simple marine microbial community. We used a microfluidic-based approach that allows us to disentangle the effect cells have on their environment from how they respond to their environment. We found that the interactions between two species-a degrader of chitin and a cross-feeder that consumes metabolic by-products-changes dynamically over time as cells modify their environment. Cells initially interact positively and then start to compete at later stages of growth. Our results demonstrate that interactions between microorganisms are not static and depend on the state of the environment, emphasizing the importance of disentangling how modifications of the environment affects species interactions. This experimental approach can shed new light on how interspecies interactions scale up to community level processes in natural environments.

Characterizing Natural Organic Matter Transformations by Microbial Communities in Terrestrial Subsurface Ecosystems: A Critical Review of Analytical Techniques and Challenges

Determining the mechanisms, traits, and pathways that regulate microbial transformation of natural organic matter (NOM) is critical to informing our understanding of the microbial impacts on the global carbon cycle. The capillary fringe of subsurface soils is a highly dynamic environment that remains poorly understood. Characterization of organo-mineral chemistry combined with a nuanced understanding of microbial community composition and function is necessary to understand microbial impacts on NOM speciation in the capillary fringe. We present a critical review of the popular analytical and omics techniques used for characterizing complex carbon transformation by microbial communities and focus on how complementary information obtained from the different techniques enable us to connect chemical signatures with microbial genes and pathways. This holistic approach offers a way forward for the comprehensive characterization of the formation, transformation, and mineralization of terrestrial NOM as influenced by microbial communities.

Nutrient Gradients Mediate Complex Colony-Level Antibiotic Responses in Structured Microbial Populations

Antibiotic treatments often fail to eliminate bacterial populations due to heterogeneity in how individual cells respond to the drug. In structured bacterial populations such as biofilms, bacterial metabolism and environmental transport processes lead to an emergent phenotypic structure and self-generated nutrient gradients toward the interior of the colony, which can affect cell growth, gene expression and susceptibility to the drug. Even in single cells, survival depends on a dynamic interplay between the drug's action and the expression of resistance genes. How expression of resistance is coordinated across populations in the presence of such spatiotemporal environmental coupling remains elusive. Using a custom microfluidic device, we observe the response of spatially extended microcolonies of tetracycline-resistant E. coli to precisely defined dynamic drug regimens. We find an intricate interplay between drug-induced changes in cell growth and growth-dependent expression of resistance genes, resulting in the redistribution of metabolites and the reorganization of growth patterns. This dynamic environmental feedback affects the regulation of drug resistance differently across the colony, generating dynamic phenotypic structures that maintain colony growth during exposure to high drug concentrations and increase population-level resistance to subsequent exposures. A mathematical model linking metabolism and the regulation of gene expression is able to capture the main features of spatiotemporal colony dynamics. Uncovering the fundamental principles that govern collective mechanisms of antibiotic resistance in spatially extended populations will allow the design of optimal drug regimens to counteract them.

Rare and localized events stabilize microbial community composition and patterns of spatial self-organization in a fluctuating environment

Spatial self-organization is a hallmark of surface-associated microbial communities that is governed by local environmental conditions and further modified by interspecific interactions. Here, we hypothesize that spatial patterns of microbial cell-types can stabilize the composition of cross-feeding microbial communities under fluctuating environmental conditions. We tested this hypothesis by studying the growth and spatial self-organization of microbial co-cultures consisting of two metabolically interacting strains of the bacterium Pseudomonas stutzeri. We inoculated the co-cultures onto agar surfaces and allowed them to expand (i.e. range expansion) while fluctuating environmental conditions that alter the dependency between the two strains. We alternated between anoxic conditions that induce a mutualistic interaction and oxic conditions that induce a competitive interaction. We observed co-occurrence of both strains in rare and highly localized clusters (referred to as “spatial jackpot events”) that persist during environmental fluctuations. To resolve the underlying mechanisms for the emergence of spatial jackpot events, we used a mechanistic agent-based mathematical model that resolves growth and dispersal at the scale relevant to individual cells. While co-culture composition varied with the strength of the mutualistic interaction and across environmental fluctuations, the model provides insights into the formation of spatially resolved substrate landscapes with localized niches that support the co-occurrence of the two strains and secure co-culture function. This study highlights that in addition to spatial patterns that emerge in response to environmental fluctuations, localized spatial jackpot events ensure persistence of strains across dynamic conditions.

Probabilistic Inference with Polymerizing Biochemical Circuits

Probabilistic inference—the process of estimating the values of unobserved variables in probabilistic models—has been used to describe various cognitive phenomena related to learning and memory. While the study of biological realizations of inference has focused on animal nervous systems, single-celled organisms also show complex and potentially “predictive” behaviors in changing environments. Yet, it is unclear how the biochemical machinery found in cells might perform inference. Here, we show how inference in a simple Markov model can be approximately realized, in real-time, using polymerizing biochemical circuits. Our approach relies on assembling linear polymers that record the history of environmental changes, where the polymerization process produces molecular complexes that reflect posterior probabilities. We discuss the implications of realizing inference using biochemistry, and the potential of polymerization as a form of biological information-processing.

A localized DNA finite-state machine with temporal resolution

The identity and timing of environmental stimulus play a pivotal role in living organisms in programming their signaling networks and developing specific phenotypes. The ability to unveil history-dependent signals will advance our understanding of temporally regulated biological processes. Here, we have developed a two-input, five-state DNA finite-state machine (FSM) to sense and record the temporally ordered inputs. The spatial organization of the processing units on DNA origami enables facile modulation of the energy landscape of DNA strand displacement reactions, allowing precise control of the reactions along predefined paths for different input orders. The use of spatial constraints brings about a simple, modular design for the FSM with a minimum set of orthogonal components and confers minimized leaky reactions and fast kinetics. The FSM demonstrates the capability of sensing the temporal orders of two microRNAs, highlighting its potential for temporally resolved biosensing and smart therapeutics.

A peptide derived from GAPDH enhances resistance to DNA damage in budding yeast

Social behaviors do not only exist in higher organisms but are also present in microbes that interact for the common good. Here, we report that budding yeast cells interact with their neighboring cells after exposure to DNA damage. Yeast cells irradiated with DNA-damaging ultraviolet light secrete signal peptides that can increase the survival of yeast cells exposed to DNA-damaging stress. The secreted peptide is derived from glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and it induced cell death of a fraction of yeast cells in the group. The data suggest that the GAPDH-derived peptide serves in budding yeast's social interaction in response to DNA-damaging stress. Importance Many studies have shown that microorganisms, including bacteria and yeast, display increased tolerance to stress after exposure to the same stressor. However, the mechanism remains unknown. In this manuscript, we report a striking finding that S. cerevisiae cells respond to DNA damage by secreting a peptide that facilitates resistance to DNA-damaging stress. Although it has been shown that GAPDH possesses many key functions in cells aside from its well-established role in glycolysis, this study demonstrated that GAPDH is also involved in the social behaviors response to DNA-damaging stress. The study opens the gate to an interesting research field about microbial social activity for adaptation to a harsh environment.

The cost of bacterial predation via type VI secretion system leads to predator extinction under environmental stress

As a common gut pathogen, Campylobacter jejuni (C. jejuni) harbors the Type VI Secretion System (T6SS) that injects toxic effectors into neighboring cells, modulating microbial competitions in the harsh gut environment. Using bile salt as a natural stressor and T6SS-positive C. jejuni as a predator, we show that T6SS activity could entail a cost during bacterial predation under environmental stress. Our data suggest bile salt influx and subsequent DNA damage due to the prey-driven activation of the T6SS. We further combined experiments and mathematical modeling to explore how the stress-induced “predation cost” determines ecological outcomes. Consistent with a population-dynamics model, we found predator extinction above a critical bile salt concentration and prey-predator coexistence below this level. Moreover, we utilized the predation cost as an effective strategy facilitating host defense against C. jejuni infection. Together, we elucidate how predator dominance versus extinction emerges from the interplay between environmental stress and the T6SS machinery.

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Campylobacter jejuni uses Type VI secretion system (T6SS) to kill prey bacteria

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Under bile salt stress, activated T6SS may promote bile salt uptake and DNA damage

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T6SS-dependent predation by C. jejuni thus entails a “predation cost” under stress

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The predation cost leads to predator extinction and host defense against C. jejuni

Causes and consequences of pattern diversification in a spatially self-organizing microbial community

Surface-attached microbial communities constitute a vast amount of life on our planet. They contribute to all major biogeochemical cycles, provide essential services to our society and environment, and have important effects on human health and disease. They typically consist of different interacting genotypes that arrange themselves non-randomly across space (referred to hereafter as spatial self-organization). While spatial self-organization is important for the functioning, ecology, and evolution of these communities, the underlying determinants of spatial self-organization remain unclear. Here, we performed a combination of experiments, statistical modeling, and mathematical simulations with a synthetic cross-feeding microbial community consisting of two isogenic strains. We found that two different patterns of spatial self-organization emerged at the same length and time scales, thus demonstrating pattern diversification. This pattern diversification was not caused by initial environmental heterogeneity or by genetic heterogeneity within populations. Instead, it was caused by nongenetic heterogeneity within populations, and we provide evidence that the source of this nongenetic heterogeneity is local differences in the initial spatial positionings of individuals. We further demonstrate that the different patterns exhibit different community-level properties; namely, they have different expansion speeds. Together, our results demonstrate that pattern diversification can emerge in the absence of initial environmental heterogeneity or genetic heterogeneity within populations and can affect community-level properties, thus providing novel insights into the causes and consequences of microbial spatial self-organization.

Endurance of extremely prolonged nutrient prevention across kingdoms of life

Numerous observations demonstrate that microorganisms can survive very long periods of nutrient deprivation and starvation. Moreover, it is evident that prolonged periods of starvation are a feature of many habitats, and many cells in all kingdoms of life are found in prolonged starvation conditions. Bacteria exhibit a range of responses to long-term starvation. These include genetic adaptations such as the long-term stationary phase and the growth advantage in stationary phase phenotypes characterized by mutations in stress-signaling genes and elevated mutation rates. Here, we suggest using the term "endurance of prolonged nutrient prevention" (EPNP phase), to describe this phase, which was also recently described in eukaryotes. Here, we review this literature and describe the current knowledge about the adaptations to very long-term starvation conditions in bacteria and eukaryotes, its conceptual and structural conservation across all kingdoms of life, and point out possible directions that merit further research.

Nongenetic individuality, changeability, and inheritance in bacterial behavior

Isogenic microbial populations in constant and homogeneous environments can display remarkable levels of phenotypic diversity. Quantitative understanding of how such diversity is generated and maintained in populations is, however, experimentally and theoretically challenging. We focus on the swimming behavior of Escherichia coli as a model system of phenotypic diversity and show that, despite temporal changes in behavior that each individual undergoes, significant differences between individuals persist throughout most of their lifetimes. While the behavior of even closely related bacteria can be remarkably different, the behavioral variations produced by nongenetic mechanisms are inherited across generations. The general experimental and theoretical framework developed here can be applied to study quantitative aspects of phenotypic diversity in many biological systems.

Isogenic populations often display remarkable levels of phenotypic diversity even in constant, homogeneous environments. Such diversity results from differences between individuals (“nongenetic individuality”) as well as changes during individuals’ lifetimes (“changeability”). Yet, studies that capture and quantify both sources of diversity are scarce. Here we measure the swimming behavior of hundreds of Escherichia coli bacteria continuously over two generations and use a model-independent method for quantifying behavior to show that the behavioral space of E. coli is low-dimensional, with variations occurring mainly along two independent and interpretable behavioral traits. By statistically decomposing the diversity in these two traits, we find that individuality is the main source of diversity, while changeability makes a smaller but significant contribution. Finally, we show that even though traits of closely related individuals can be remarkably different, they exhibit positive correlations across generations that imply nongenetic inheritance. The model-independent experimental and theoretical framework developed here paves the way for more general studies of microbial behavioral diversity.

Nutrient complexity triggers transitions between solitary and colonial growth in bacterial populations

Microbial populations often experience fluctuations in nutrient complexity in their natural environment such as between high molecular weight polysaccharides and simple monosaccharides. However, it is unclear if cells can adopt growth behaviors that allow individuals to optimally respond to differences in nutrient complexity. Here, we directly control nutrient complexity and use quantitative single-cell analysis to study the growth dynamics of individuals within populations of the aquatic bacterium Caulobacter crescentus. We show that cells form clonal microcolonies when growing on the polysaccharide xylan, which is abundant in nature and degraded using extracellular cell-linked enzymes; and disperse to solitary growth modes when the corresponding monosaccharide xylose becomes available or nutrients are exhausted. We find that the cellular density required to achieve maximal growth rates is four-fold higher on xylan than on xylose, indicating that aggregating is advantageous on polysaccharides. When collectives on xylan are transitioned to xylose, cells start dispersing, indicating that colony formation is no longer beneficial and solitary behaviors might serve to reduce intercellular competition. Our study demonstrates that cells can dynamically tune their behaviors when nutrient complexity fluctuates, elucidates the quantitative advantages of distinct growth behaviors for individual cells and indicates why collective growth modes are prevalent in microbial populations.

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.

Reciprocal growth control by competitive binding of nucleotide second messengers to a metabolic switch in Caulobacter crescentus

Bacteria use small signalling molecules such as (p)ppGpp or c-di-GMP to tune their physiology in response to environmental changes. It remains unclear whether these regulatory networks operate independently or whether they interact to optimize bacterial growth and survival. We report that (p)ppGpp and c-di-GMP reciprocally regulate the growth of Caulobacter crescentus by converging on a single small-molecule-binding protein, SmbA. While c-di-GMP binding inhibits SmbA, (p)ppGpp competes for the same binding site to sustain SmbA activity. We demonstrate that (p)ppGpp specifically promotes Caulobacter growth on glucose, whereas c-di-GMP inhibits glucose consumption. We find that SmbA contributes to this metabolic switch and promotes growth on glucose by quenching the associated redox stress. The identification of an effector protein that acts as a central regulatory hub for two global second messengers opens up future studies on specific crosstalk between small-molecule-based regulatory networks.

Cognition in some surprising places

The most widely accepted view in the biopsychological sciences is that the cognitive functions that are diagnostic of mental operations, sentience or, more commonly, consciousness emerged fairly late in evolution, most likely in the Cambrian period. Our position dovetails with James's below - subjectivity, feeling, consciousness has a much longer evolutionary history, one that goes back to the first appearance of life. The Cellular Basis of Consciousness (CBC) model is founded on the presumption that sentience and life are coterminous; that all organisms, based on inherent cellular activities via processes that take place in excitable membranes of their cells, are sentient, have subjective experiences and feelings. These, in turn, guide the context-relevant behaviors essential for their survival in often hostile environments in constant flux. The CBC framework is reductionistic, mechanistic, and calls for bottom-up research programs into the evolutionary origin of biological consciousness.

Quantifying plasmid dynamics using single-cell microfluidics and image bioinformatics

Multicopy plasmids play an important role in bacterial ecology and evolution by accelerating the rate of adaptation and providing a platform for rapid gene amplification and evolutionary rescue. Despite the relevance of plasmids in bacterial evolutionary dynamics, evaluating the population-level consequences of randomly segregating and replicating plasmids in individual cells remains a challenging problem, both in theory and experimentally. In recent years, technological advances in fluorescence microscopy and microfluidics have allowed studying temporal changes in gene expression by quantifying the fluorescent intensity of individual cells under controlled environmental conditions. In this paper, we will describe the manufacture, experimental setup, and data analysis pipeline of different microfluidic systems that can be used to study plasmid dynamics, both in single-cells and in populations. To illustrate the benefits and limitations of microfluidics to study multicopy plasmid dynamics, we will use an experimental model system consisting on Escherichia coli K12 carrying non-conjugative, multicopy plasmids (19 copies per cell, in average) encoding different fluorescent markers and β-lactam resistance genes. First, we will use an image-based flow cytometer to estimate changes in the allele distribution of a heterogeneous population under different selection regimes. Then we will use a mothermachine microfluidic device to obtain time-series of fluorescent intensity of individual cells to argue that plasmid segregation and replication dynamics are inherently stochastic processes. Finally, using a microchemostat, we track thousands of cells in time to reconstruct bacterial lineages and evaluate the allele frequency distributions that emerge in response to a range of selective pressures.

A phenotypic screening bioassay for Escherichia coli stress and antibiotic responses based on Fourier-transform infrared (FTIR) spectroscopy and multivariate analysis

AIMS

To develop and optimize a Fourier-transform infrared spectroscopy (FTIRS) phenotypic screening bioassay for stress responses, regarding the effect of nutrient content, bacterial growth phase and stress agent exposure time.

METHODS AND RESULTS

A high-throughput FTIRS bioassay was developed to distinguish the stress responses of Escherichia coli to sodium hydroxide, hydrochloric acid, sodium chloride, sodium hypochlorite and ethanol. Principal component analysis and hierarchical clustering were used to quantify the effect of each parameter on bioassay performance, namely its reproducibility and metabolic resolution. Bioassay performance varied greatly, ranging from poor to very good. Spectra were partitioned into biologically relevant regions to evaluate their contributions to bioassay performance, but further improvements were not observed. Bioassay optimization was validated against empirical parameters, which confirmed a closer representation of known mechanisms on the antibiotic-induced stress responses.

CONCLUSIONS

The optimized bioassay used standard nutrient content, cells in the late-stationary growth phase and a one-shift exposure duration. Only the optimized bioassay adequately and reproducibly distinguished the E. coli stress and antibiotic responses. The absence of performance improvements using partitioned spectra indicated that stress responses are imprinted on the whole-spectra metabolic signature.

SIGNIFICANCE AND IMPACT OF THE STUDY

Highly optimized FTIRS bioassay parameters are vital in capturing whole-spectra metabolic signatures that can be used for satisfactory and reproducible phenotypic screening of stress and antibiotic responses.

Light-dependent single-cell heterogeneity in the chloroplast redox state regulates cell fate in a marine diatom

Diatoms are photosynthetic microorganisms of great ecological and biogeochemical importance, forming vast blooms in aquatic ecosystems. However, we are still lacking fundamental understanding of how individual cells sense and respond to diverse stress conditions, and what acclimation strategies are employed during bloom dynamics. We investigated cellular responses to environmental stress at the single-cell level using the redox sensor roGFP targeted to various organelles in the diatom Phaeodactylum tricornutum. We detected cell-to-cell variability using flow cytometry cell sorting and a microfluidics system for live imaging of oxidation dynamics. Chloroplast-targeted roGFP exhibited a light-dependent, bi-stable oxidation pattern in response to H₂O₂ and high light, revealing distinct subpopulations of sensitive oxidized cells and resilient reduced cells. Early oxidation in the chloroplast preceded commitment to cell death, and can be used for sensing stress cues and regulating cell fate. We propose that light-dependent metabolic heterogeneity regulates diatoms’ sensitivity to environmental stressors in the ocean.

Microscopic algae, such as diatoms, are widely spread throughout the oceans, and are responsible for half of the oxygen we breathe. At certain times of the year these algae grow very rapidly to form large “blooms” that can be detected by satellites in space. These blooms are generally short-lived because the algae are either eaten by other marine organisms, run out of nutrients, or die as a result of being infected by viruses or bacteria. However, some diatom cells survive the end of the bloom and go on to generate new blooms in the future, but it is still not clear how.

As the bloom collapses, diatoms experience many stressful conditions which can cause active molecules known as reactive oxygen species, or ROS for short, to accumulate inside cells. Normally growing cells also produce low amounts of ROS, which regulate various processes that are important for maintaining a cell’s health. However, high amounts of ROS can cause damage, which may lead to a cell’s death. Now, Mizrachi et al. investigated why some algae survive while others die in response to stressful conditions, focusing on the amount of ROS that accumulates within the diatom Phaeodactylum tricornutum.

Laboratory experiments showed that individual cells of P. tricornutum respond differently to environmental stress, forming two distinct groups of either sensitive or resilient cells. Sensitive cells accumulated high levels of ROS within a cell compartment known as the chloroplast and eventually died. Whereas resilient cells were able to maintain low levels of ROS in the chloroplast and survived long after the other cells perished. Populations of genetically identical diatom cells also formed distinct groups of sensitive and resilient cells, demonstrating that these two opposing reactions to stress are not caused by genetic differences between cells.

Lastly, Mizrachi et al. showed that how diatoms acclimate to stress depends on the amount of light they are exposed to. When in the dark, all cells became sensitive to oxidative stress, without forming distinct groups. But, when exposed to strong light that mimics the ocean surface, cells formed distinct groups within the population. This suggests that light regulates how susceptible these microscopic algae are to environmental stress.

The different responses within a population may serve as a “bet-hedging” strategy, enabling at least some of the cells to survive unpredicted stressful conditions. The next challenge will be to find out whether algae growing in the oceans also use the same strategy and investigate what impact this has on diatom blooms.

Disentangling bacterial invasiveness from lethality in an experimental host-pathogen system

Quantifying virulence remains a central problem in human health, pest control, disease ecology, and evolutionary biology. Bacterial virulence is typically quantified by the LT50 (i.e., the time taken to kill 50% of infected hosts); however, such an indicator cannot account for the full complexity of the infection process, such as distinguishing between the pathogen's ability to colonize versus kill the hosts. Indeed, the pathogen needs to breach the primary defenses in order to colonize, find a suitable environment to replicate, and finally express the virulence factors that cause disease. Here, we show that two virulence attributes, namely pathogen lethality and invasiveness, can be disentangled from the survival curves of a laboratory population of Caenorhabditis elegans nematodes exposed to three bacterial pathogens: Pseudomonas aeruginosa, Serratia marcescens, and Salmonella enterica We first show that the host population eventually experiences a constant mortality rate, which quantifies the lethality of the pathogen. We then show that the time necessary to reach this constant mortality rate regime depends on the pathogen growth rate and colonization rate, and thus determines the pathogen invasiveness. Our framework reveals that Serratia marcescens is particularly good at the initial colonization of the host, whereas Salmonella enterica is a poor colonizer yet just as lethal once established. Pseudomonas aeruginosa, on the other hand, is both a good colonizer and highly lethal after becoming established. The ability to quantitatively characterize the ability of different pathogens to perform each of these steps has implications for treatment and prevention of disease and for the evolution and ecology of pathogens.

On-Chip Isoniazid Exposure of Mycobacterium smegmatis Penicillin-Binding Protein (PBP) Mutant Using Time-Lapse Fluorescent Microscopy

Antibiotic resistance has been one of the biggest threats to global health. Despite the available prevention and control strategies and efforts in developing new antibiotics, the need remains for effective approaches against antibiotic resistance. Efficient strategies to cope with antimicrobial resistance require a quantitative and deeper understanding of microbial behavior, which can be obtained using different techniques to provide the missing pieces of the current antibiotic-resistance puzzle. Microfluidic-microscopy techniques are among the most promising methods that contribute modernization of traditional assays in microbiology. They provide monitoring and manipulation of cells at micro-scale volumes. Here, we combined population-level, culture-based assays with single-cell resolution, microfluidic-microscopy systems to investigate isoniazid response of Mycobacterium smegmatis penicillin-binding protein (PBP) mutant. This mutant exhibited normal growth in plain medium and sensitivity to stress responses when treated with thermal stress (45 °C), detergent stress (0.1% sodium dodecyl sulfate), acid stress (pH 4.5), and nutrient starvation (1XPBS). The impact of msm0031 transposon insertion on drug-mediated killing was determined for isoniazid (INH, 50 µg/mL), rifampicin (RIF, 200 µg/mL), ethionamide (ETH, 200 µg/mL), and ethambutol (EMB, 5 µg/mL). The PBP mutant demonstrated remarkable isoniazid-killing phenotype in batch culture. Therefore, we hypothesized that single-cell analysis will show increased lysis kinetics and fewer intact cells after drug treatment. However, the single-cell analysis data showed that upon isoniazid exposure, the percentage of the intact PBP mutant cells was 24%, while the percentage of the intact wild-type cells was 4.6%. The PBP mutant cells exhibited decreased cell-lysis profile. Therefore, the traditional culture-based assays were not sufficient to provide insights about the subpopulation of viable but non-culture cells. Consequently, we need more adequate tools to be able to comprehend and fight the antibiotic resistance of bacteria.

A Single-Domain Response Regulator Functions as an Integrating Hub To Coordinate General Stress Response and Development in Alphaproteobacteria

The alphaproteobacterial general stress response is governed by a conserved partner-switching mechanism that is triggered by phosphorylation of the response regulator PhyR. In the model organism Caulobacter crescentus, PhyR was proposed to be phosphorylated by the histidine kinase PhyK, but biochemical evidence in support of such a role of PhyK is missing. Here, we identify a single-domain response regulator, MrrA, that is essential for general stress response activation in C. crescentus We demonstrate that PhyK does not function as a kinase but accepts phosphoryl groups from MrrA and passes them on to PhyR, adopting the role of a histidine phosphotransferase. MrrA is phosphorylated by at least six histidine kinases that likely serve as stress sensors. MrrA also transfers phosphate to LovK, a histidine kinase involved in C. crescentus holdfast production and attachment, which also negatively regulates the general stress response. We show that LovK together with the response regulator LovR acts as a phosphate sink to redirect phosphate flux away from the PhyKR branch. In agreement with the biochemical data, an mrrA mutant is unable to activate the general stress response and shows a hyperattachment phenotype, which is linked to decreased expression of the major holdfast inhibitory protein HfiA. We propose that MrrA serves as a central phosphorylation hub that coordinates the general stress response with C. crescentus development and other adaptive behaviors. The characteristic bow-tie architecture of this phosphorylation network with MrrA as the central knot may expedite the evolvability and species-specific niche adaptation of this group of bacteria.IMPORTANCE Two-component systems (TCSs) consisting of a histidine kinase and a cognate response regulator are predominant signal transduction systems in bacteria. To avoid cross talk, TCSs are generally thought to be highly insulated from each other. However, this notion is based largely on studies of the HisKA subfamily of histidine kinases, while little information is available for the HWE and HisKA2 subfamilies. The latter have been implicated in the alphaproteobacterial general stress response. Here, we show that in the model organism Caulobacter crescentus an atypical FATGUY-type single-domain response regulator, MrrA, is highly promiscuous in accepting and transferring phosphoryl groups from and to multiple up- and downstream kinases, challenging the current view of strictly insulated TCSs. Instead, we propose that FATGUY response regulators have evolved in alphaproteobacteria as central phosphorylation hubs to broadly sample information and distribute phosphoryl groups between the general stress response pathway and other TCSs, thereby coordinating multiple cellular behaviors.

Sulfur Isotope Fractionation by Sulfate-Reducing Microbes Can Reflect Past Physiology

Sulfur (S) isotope fractionation by sulfate-reducing microorganisms is a direct manifestation of their respiratory metabolism. This fractionation is apparent in the substrate (sulfate) and waste (sulfide) produced. The sulfate-reducing metabolism responds to variability in the local environment, with the response determined by the underlying genotype, resulting in the expression of an "isotope phenotype". Sulfur isotope phenotypes have been used as a diagnostic tool for the metabolic activity of sulfate-reducing microorganisms in the environment. Our experiments with Desulfovibrio vulgaris Hildenborough (DvH) grown in batch culture suggest that the S isotope phenotype of sulfate respiring microbes may lag environmental changes on time scales that are longer than generational. When inocula from different phases of growth are assayed under the same environmental conditions, we observed that DvH exhibited different net apparent fractionations of up to -9‰. The magnitude of fractionation was weakly correlated with physiological parameters but was strongly correlated to the age of the initial inoculum. The S isotope fractionation observed between sulfate and sulfide showed a positive correlation with respiration rate, contradicting the well-described negative dependence of fractionation on respiration rate. Quantitative modeling of S isotope fractionation shows that either a large increase (≈50×) in the abundance of sulfate adenylyl transferase (Sat) or a smaller increase in sulfate transport proteins (≈2×) is sufficient to account for the change in fractionation associated with past physiology. Temporal transcriptomic studies with DvH imply that expression of sulfate permeases doubles over the transition from early exponential to early stationary phase, lending support to the transport hypothesis proposed here. As it is apparently maintained for multiple generations (≈1-6) of subsequent growth in the assay environment, we suggest that this fractionation effect acts as a sort of isotopic "memory" of a previous physiological and environmental state. Whatever its root cause, this physiological hysteresis effect can explain variations in fractionations observed in many environments. It may also enable new insights into life at energetic limits, especially if its historical footprint extends deeper than generational.

Phenotypic memory in Bacillus subtilis links dormancy entry and exit by a spore quantity-quality tradeoff

Some bacteria, such as Bacillus subtilis, withstand starvation by forming dormant spores that revive when nutrients become available. Although sporulation and spore revival jointly determine survival in fluctuating environments, the relationship between them has been unclear. Here we show that these two processes are linked by a phenotypic “memory” that arises from a carry-over of molecules from the vegetative cell into the spore. By imaging life histories of individual B. subtilis cells using fluorescent reporters, we demonstrate that sporulation timing controls nutrient-induced spore revival. Alanine dehydrogenase contributes to spore memory and controls alanine-induced outgrowth, thereby coupling a spore’s revival capacity to the gene expression and growth history of its progenitors. A theoretical analysis, and experiments with signaling mutants exhibiting altered sporulation timing, support the hypothesis that such an intrinsically generated memory leads to a tradeoff between spore quantity and spore quality, which could drive the emergence of complex microbial traits.

Bacillus subtilis withstands starvation by forming dormant spores that revive when nutrients become available. Here, Mutlu et al. show that sporulation timing controls spore revival through a phenotypic ‘memory’ that arises from the carry-over of a metabolic enzyme from the vegetative cell into the spore.

Counterbalancing Regulation in Response Memory of a Positively Autoregulated Two-Component System

Fluctuations in nutrient availability often result in recurrent exposures to the same stimulus conditions. The ability to memorize the past event and use the "memory" to make adjustments to current behaviors can lead to a more efficient adaptation to the recurring stimulus. A short-term phenotypic memory can be conferred via carryover of the response proteins to facilitate the recurrent response, but the additional accumulation of response proteins can lead to a deviation from response homeostasis. We used the Escherichia coli PhoB/PhoR two-component system (TCS) as a model system to study how cells cope with the recurrence of environmental phosphate (Pi) starvation conditions. We discovered that "memory" of prior Pi starvation can exert distinct effects through two regulatory pathways, the TCS signaling pathway and the stress response pathway. Although carryover of TCS proteins can lead to higher initial levels of transcription factor PhoB and a faster initial response in prestarved cells than in cells not starved, the response enhancement can be overcome by an earlier and greater repression of promoter activity in prestarved cells due to the memory of the stress response. The repression counterbalances the carryover of the response proteins, leading to a homeostatic response whether or not cells are prestimulated. A computational model based on sigma factor competition was developed to understand the memory of stress response and to predict the homeostasis of other PhoB-regulated response proteins. Our insight into the history-dependent PhoBR response may provide a general understanding of how TCSs respond to recurring stimuli and adapt to fluctuating environmental conditions.IMPORTANCE Bacterial cells in their natural environments experience scenarios that are far more complex than are typically replicated in laboratory experiments. The architectures of signaling systems and the integration of multiple adaptive pathways have evolved to deal with such complexity. In this study, we examined the molecular "memory" that is generated by previous exposure to stimulus. Under our experimental conditions, activating effects of autoregulated two-component signaling and inhibitory effects of the stress response counterbalanced the transcriptional output to approach response homeostasis whether or not cells had been preexposed to stimulus. Modeling allows prediction of response behavior in different scenarios and demonstrates both the robustness of the system output and its sensitivity to historical parameters such as timing and levels of exposure to stimuli.

Learning from Adversity?

Many two-component regulatory systems, including Escherichia coli PhoRB, are positively autoregulated, so stimuli result in an increase in the concentration of signaling proteins. When the quantity of signaling proteins depends on exposure history, how do past conditions affect future responses to stimuli? Hoffer et al. (J. Bacteriol. 183:4914-4917, 2001, https://doi.org/doi:10.1128/JB.183.16.4914-4917.2001) previously reported that E. coli bacteria "learn" from phosphate starvation and respond more rapidly to subsequent episodes of starvation. Gao et al. (J. Bacteriol. 199:e00390-17, 2017, https://doi.org/doi:10.1128/JB.00390-17) describe another aspect of hysteresis in the PhoRB regulon. Phosphate starvation also leads to a global decline in transcription, counteracting the effects of positive autoregulation and resulting in a similar net pho response (homeostasis), regardless of exposure history.

Rapid phenotypic individualization of bacterial sister cells

A growing bacterium typically divides into two genetically identical and morphologically similar sister cells and eventually gives rise to a clonal population. Nevertheless, significant phenotypic differentiation among isogenic cells frequently occurs, with the resulting heterogeneity in cellular behavior often ensuring population level growth and survival in complex and unpredictable environments. Although several mechanisms underlying the generation of phenotypic heterogeneity have been elucidated, the speed with which identical sister cells tend to phenotypically diverge from each other has so far remained unaddressed. Using Escherichia coli as a model organism, we therefore examined the timing and dynamics of phenotypic individualization among sister cells by scrutinizing and modeling microscopically tracked clonally growing populations before and after a semi-lethal heat challenge. This analysis revealed that both survival probability and post-stress physiology of sister cells shift from highly similar to uncorrelated within the first decile of their cell cycles. This nearly-immediate post-fission randomization of sister cell fates highlights the potential of stochastic fluctuations during clonal growth to rapidly generate phenotypically independent individuals.

History of antibiotic adaptation influences microbial evolutionary dynamics during subsequent treatment

Antibiotic regimens often include the sequential changing of drugs to limit the development and evolution of resistance of bacterial pathogens. It remains unclear how history of adaptation to one antibiotic can influence the resistance profiles when bacteria subsequently adapt to a different antibiotic. Here, we experimentally evolved Pseudomonas aeruginosa to six 2-drug sequences. We observed drug order-specific effects, whereby adaptation to the first drug can limit the rate of subsequent adaptation to the second drug, adaptation to the second drug can restore susceptibility to the first drug, or final resistance levels depend on the order of the 2-drug sequence. These findings demonstrate how resistance not only depends on the current drug regimen but also the history of past regimens. These order-specific effects may allow for rational forecasting of the evolutionary dynamics of bacteria given knowledge of past adaptations and provide support for the need to consider the history of past drug exposure when designing strategies to mitigate resistance and combat bacterial infections.

Taking chances and making mistakes: non-genetic phenotypic heterogeneity and its consequences for surviving in dynamic environments

Natural selection has shaped the strategies for survival and growth of microorganisms. The success of microorganisms depends not only on slow evolutionary tuning but also on the ability to adapt to unpredictable changes in their environment. In principle, adaptive strategies range from purely deterministic mechanisms to those that exploit the randomness intrinsic to many cellular and molecular processes. Depending on the environment and selective pressures, particular strategies can lie somewhere along this continuum. In recent years, non-genetic cell-to-cell differences have received a lot of attention, not least because of their potential impact on the ability of microbial populations to survive in dynamic environments. Using several examples, we describe the origins of spontaneous and induced mechanisms of phenotypic adaptation. We identify some of the commonalities of these examples and consider the potential role of chance and constraints in microbial phenotypic adaptation.

Survival and Adaptation of the Thermophilic Species Geobacillus thermantarcticus in Simulated Spatial Conditions

Astrobiology studies the origin and evolution of life on Earth and in the universe. According to the panspermia theory, life on Earth could have emerged from bacterial species transported by meteorites, that were able to adapt and proliferate on our planet. Therefore, the study of extremophiles, i.e. bacterial species able to live in extreme terrestrial environments, can be relevant to Astrobiology studies. In this work we described the ability of the thermophilic species Geobacillus thermantarcticus to survive after exposition to simulated spatial conditions including temperature's variation, desiccation, X-rays and UVC irradiation. The response to the exposition to the space conditions was assessed at a molecular level by studying the changes in the morphology, the lipid and protein patterns, the nucleic acids. G. thermantarcticus survived to the exposition to all the stressing conditions examined, since it was able to restart cellular growth in comparable levels to control experiments carried out in the optimal growth conditions. Survival was elicited by changing proteins and lipids distribution, and by protecting the DNA's integrity.

Coarse-graining bacteria colonies for modelling critical solute distributions in picolitre bioreactors for bacterial studies on single-cell level

Microfluidic single‐cell bioreactors have found widespread application to investigate growth and gene expression of microbial model organisms, but yet there are few attempts to systematically characterize different design and cultivation concepts. Quantitative measurements of critical solute concentrations, e.g. limiting nutrients, are not yet feasible within the typical volumes in the range of picolitres. A way to gain new insights about the mass transport within those volumes is by simulation, but the complex geometry resulting from the multitude of cells within a colony leads to time and resource consuming computational challenges. In this work, six different concepts for the model representation of cellular microcolonies within microfluidic monolayer growth chamber devices are compared. The Gini coefficient is proposed as new measure for inhomogeneity within cellular colonies. An example cell colony is represented by a single point source, a cylindrical volume with homogeneous reaction rates with and without adjusted diffusion coefficient, as point sources for each single cell and as rod‐shaped, diffusion blocking, three‐dimensional cells with varying shapes. Simulated concentration profiles across the chambers depended strongly on the chosen cell representation. The representation with the lowest degree of abstraction, three‐dimensional cells, leads to complex geometries and high computational effort, but also gives a conservative and therefore preferable estimate for the cultivation conditions within a given cultivation chamber geometry. Interestingly, the cylindrical volume with adjusted diffusion coefficient gives similar results but requires far less computational effort. Therefore, it is proposed to use the three‐dimensional cells for detailed studies and to determine parameters for the cylindrical volume with adjusted diffusion coefficient, which can then be used for experimental design, screening of parameter spaces, and similar applications.

Asymmetric cellular memory in bacteria exposed to antibiotics

Background

The ability to form a cellular memory and use it for cellular decision-making could help bacteria to cope with recurrent stress conditions. We analyzed whether bacteria would form a cellular memory specifically if past events are predictive of future conditions. We worked with the asymmetrically dividing bacterium Caulobacter crescentus where past events are expected to only be informative for one of the two cells emerging from division, the sessile cell that remains in the same microenvironment and does not migrate.

Results

Time-resolved analysis of individual cells revealed that past exposure to low levels of antibiotics increases tolerance to future exposure for the sessile but not for the motile cell. Using computer simulations, we found that such an asymmetry in cellular memory could be an evolutionary response to situations where the two cells emerging from division will experience different future conditions.

Conclusions

Our results raise the question whether bacteria can evolve the ability to form and use cellular memory conditionally in situations where it is beneficial.

Electronic supplementary material

The online version of this article (doi:10.1186/s12862-017-0884-4) contains supplementary material, which is available to authorized users.

Hysteresis in myo-inositol utilization by Salmonella Typhimurium

Growth of Salmonella enterica serovar Typhimurium strain 14028 with myo‐inositol (MI) as the sole carbon and energy source is characterized by a bistable phenotype that manifests in a growth phenotype with an extraordinarily long and length‐variable lag phase. However, in the presence of hydrogen carbonate, in the absence of IolR that represses the MI degradation pathway, or if cells are already adapted to minimal medium (MM) with MI, the lag phase is drastically shortened, and the bistable phenotype is abolished. We hypothesized that memory development or hysteresis is a further characteristic of MI degradation by S. Typhimurium; therefore, we investigated the transition from a short to a long lag phase in more detail. Growth experiments demonstrated that memory on the population level is successively lost within approximately 8 hr after cells, which had been adapted to MI utilization, were transferred to lysogeny broth (LB) medium. Flow cytometry (FC) analysis using a chromosomal fusion to P_iolE, a promoter controlling the expression of the enzymatic genes iolE and iolG involved in MI degradation, indicated a gradual reversion within a few hours from a population in the “ON” status with respect to iolE transcription to one that is mainly in the “OFF” status. Growth and FC experiments revealed that IolR does not affect hysteresis.

A Kinase-Phosphatase Switch Transduces Environmental Information into a Bacterial Cell Cycle Circuit

The bacterial cell cycle has been extensively studied under standard growth conditions. How it is modulated in response to environmental changes remains poorly understood. Here, we demonstrate that the freshwater bacterium Caulobacter crescentus blocks cell division and grows to filamentous cells in response to stress conditions affecting the cell membrane. Our data suggest that stress switches the membrane-bound cell cycle kinase CckA to its phosphatase mode, leading to the rapid dephosphorylation, inactivation and proteolysis of the master cell cycle regulator CtrA. The clearance of CtrA results in downregulation of division and morphogenesis genes and consequently a cell division block. Upon shift to non-stress conditions, cells quickly restart cell division and return to normal cell size. Our data indicate that the temporary inhibition of cell division through the regulated inactivation of CtrA constitutes a growth advantage under stress. Taken together, our work reveals a new mechanism that allows bacteria to alter their mode of proliferation in response to environmental cues by controlling the activity of a master cell cycle transcription factor. Furthermore, our results highlight the role of a bifunctional kinase in this process that integrates the cell cycle with environmental information.

Free-living bacteria are frequently exposed to various environmental stress conditions. To survive under such adverse conditions, cells must induce pathways that prevent and alleviate cellular damages, but they must also adjust their cell cycle to guarantee cellular integrity. It has long been observed that various bacteria transform into filamentous cells under certain conditions in nature, indicating that they dynamically modulate cell division and the cell cycle in response to environmental cues. The molecular bases that allow bacteria to regulate cell division in response to fluctuating environmental conditions remain poorly understood. Here, we describe a new mechanism by which Caulobacter crescentus blocks division and transforms into filamentous cells under stress. We find that the observed cell division block depends on precise regulation of the key cell cycle regulator CtrA. Under optimal conditions, the membrane-bound cell cycle kinase CckA activates CtrA in response to spatiotemporal cues to induce expression of genes required for cell division. Our data suggest that external stress triggers CckA to dephosphorylate and inactivate CtrA, thus ensuring the downregulation of CtrA-regulated functions, including cell division. Given that CckA and CtrA are highly conserved among alphaproteobacteria, the mechanism found here, might operate in diverse bacteria, including those that are medically and agriculturally relevant.

A population-based temporal logic gate for timing and recording chemical events

Engineered bacterial sensors have potential applications in human health monitoring, environmental chemical detection, and materials biosynthesis. While such bacterial devices have long been engineered to differentiate between combinations of inputs, their potential to process signal timing and duration has been overlooked. In this work, we present a two‐input temporal logic gate that can sense and record the order of the inputs, the timing between inputs, and the duration of input pulses. Our temporal logic gate design relies on unidirectional DNA recombination mediated by bacteriophage integrases to detect and encode sequences of input events. For an E. coli strain engineered to contain our temporal logic gate, we compare predictions of Markov model simulations with laboratory measurements of final population distributions for both step and pulse inputs. Although single cells were engineered to have digital outputs, stochastic noise created heterogeneous single‐cell responses that translated into analog population responses. Furthermore, when single‐cell genetic states were aggregated into population‐level distributions, these distributions contained unique information not encoded in individual cells. Thus, final differentiated sub‐populations could be used to deduce order, timing, and duration of transient chemical events.