Stochastic Switching of Cell Fate in Microbes

Do morphogenetic switching and intraspecies variation enhance virulence of Candida auris?

Intraspecies variations that affect pathogenicity and antifungal resistance traits pose a serious obstacle to efficient therapy of Candida auris infections. Recent reports indicate that mutations determine drug susceptibility and virulence. However, mutations alone cannot fully explain a bewildering variety of phenotypes in clinical isolates from known C. auris clades, suggesting an unprecedented complexity underlying virulence traits and antifungal resistance. Hence, we wish to discuss how phenotypic plasticity promotes morphogenetic switching and how that contributes to intraspecies variations in the human fungal pathogen C. auris. Further, we will also discuss how intraspecies variations and morphogenetic events can impact the progress in molecular mycology research that aims to find better treatments for C. auris infections. Finally, we will present our opinion as to the most relevant questions to be addressed when trying to better understand the pathophysiology of C. auris.

Dissecting cell heterogeneities in bacterial biofilms and their implications for antibiotic tolerance

Bacterial biofilms consist of large, self-formed aggregates where resident bacteria can exhibit very different physiological states and phenotypes. This heterogeneity of cell types is crucial for many structural and functional emergent properties of biofilms. Consequently, it becomes essential to understand what drives cells to differentiate and how they achieve it within the three-dimensional landscape of the biofilms. Here, we discuss recent advances in comprehending two forms of cell heterogeneity that, while recognized to coexist within biofilms, have proven challenging to distinguish. These two forms include cell heterogeneity arising as a consequence of bacteria physiologically responding to resource gradients formed across the biofilms and cell-to-cell phenotypic heterogeneity, which emerges locally within biofilm subzones among neighboring bacteria due to stochastic variations in gene expression. We describe the defining features and concepts related to both forms of cell heterogeneity and discuss their implications, with a particular focus on antibiotic tolerance.

Non-genetic adaptation by collective migration

Collective behaviors require coordination of individuals. Thus, a population must adjust its phenotypic distribution to adapt to changing environments. How can a population regulate its phenotypic distribution? One strategy is to utilize specialized networks for gene regulation and maintaining distinct phenotypic subsets. Another involves genetic mutations, which can be augmented by stress-response pathways. Here, we studied how a migrating bacterial population regulates its phenotypic distribution to traverse across diverse environments. We generated isogenic Escherichia coli populations with varying distributions of swimming behaviors and observed their phenotype distributions during migration in liquid and porous environments. Surprisingly, we found that during collective migration, the distributions of swimming phenotypes adapt to the environment without mutations or gene regulation. Instead, adaptation is caused by the dynamic and reversible enrichment of high-performing swimming phenotypes within each environment. This adaptation mechanism is supported by a recent theoretical study, which proposed that the phenotypic composition of a migrating population results from a balance between cell growth generating diversity and collective migration eliminating the phenotypes that are unable to keep up with the migrating group. Furthermore, by examining chemoreceptor abundance distributions during migration towards different attractants, we found that this mechanism acts on multiple chemotaxis-related traits simultaneously. Our findings reveal that collective migration itself can enable cell populations with continuous, multi-dimensional phenotypes to flexibly and rapidly adapt their phenotypic composition to diverse environmental conditions.

Significance statement

Conventional cell adaptation mechanisms, like gene regulation and random phenotypic switching, act swiftly but are limited to a few traits, while mutation-driven adaptations unfold slowly. By quantifying phenotypic diversity during bacterial collective migration, we discovered an adaptation mechanism that rapidly and reversibly adjusts multiple traits simultaneously. By dynamically balancing the elimination of phenotypes unable to keep pace with generation of diversity through growth, this process enables populations to tune their phenotypic composition based on the environment, without the need for gene regulation or mutations. Given the prevalence of collective migration in microbes, cancers, and embryonic development, non-genetic adaptation through collective migration may be a universal mechanism for populations to navigate diverse environments, offering insights into broader applications across various fields.

Collective production of hydrogen sulfide gas enables budding yeast lacking MET17 to overcome their metabolic defect

Assimilation of sulfur is vital to all organisms. In S. cerevisiae, inorganic sulfate is first reduced to sulfide, which is then affixed to an organic carbon backbone by the Met17 enzyme. The resulting homocysteine can then be converted to all other essential organosulfurs such as methionine, cysteine, and glutathione. This pathway has been known for nearly half a century, and met17 mutants have long been classified as organosulfur auxotrophs, which are unable to grow on sulfate as their sole sulfur source. Surprisingly, we found that met17Δ could grow on sulfate, albeit only at sufficiently high cell densities. We show that the accumulation of hydrogen sulfide gas underpins this density-dependent growth of met17Δ on sulfate and that the locus YLL058W (HSU1) enables met17Δ cells to assimilate hydrogen sulfide. Hsu1 protein is induced during sulfur starvation and under exposure to high sulfide concentrations in wild-type cells, and the gene has a pleiotropic role in sulfur assimilation. In a mathematical model, the low efficiency of sulfide assimilation in met17Δ can explain the observed density-dependent growth of met17Δ on sulfate. Thus, having uncovered and explained the paradoxical growth of a commonly used "auxotroph," our findings may impact the design of future studies in yeast genetics, metabolism, and volatile-mediated microbial interactions.

A heritable iron memory enables decision-making in Escherichia coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when Escherichia coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This "iron" memory preexists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, which tracks with its iron memory, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We demonstrate that cellular iron levels also track with biofilm formation and antibiotic tolerance, suggesting that iron memory may impact other physiologies.

Molecular Time Capsules Enable Transcriptomic Recording in Living Cells

Live-cell transcriptomic recording can help reveal hidden cellular states that precede phenotypic transformation. Here we demonstrate the use of protein-based encapsulation for preserving samples of cytoplasmic RNAs inside living cells. These molecular time capsules (MTCs) can be induced to create time-stamped transcriptome snapshots, preserve RNAs after cellular transitions, and enable retrospective investigations of gene expression programs that drive distinct developmental trajectories. MTCs also open the possibility to uncover transcriptomes in difficult-to-reach conditions.

Trade-offs between the instantaneous growth rate and long-term fitness: Consequences for microbial physiology and predictive computational models

Microbial systems biology has made enormous advances in relating microbial physiology to the underlying biochemistry and molecular biology. By meticulously studying model microorganisms, in particular Escherichia coli and Saccharomyces cerevisiae, increasingly comprehensive computational models predict metabolic fluxes, protein expression, and growth. The modeling rationale is that cells are constrained by a limited pool of resources that they allocate optimally to maximize fitness. As a consequence, the expression of particular proteins is at the expense of others, causing trade-offs between cellular objectives such as instantaneous growth, stress tolerance, and capacity to adapt to new environments. While current computational models are remarkably predictive for E. coli and S. cerevisiae when grown in laboratory environments, this may not hold for other growth conditions and other microorganisms. In this contribution, we therefore discuss the relationship between the instantaneous growth rate, limited resources, and long-term fitness. We discuss uses and limitations of current computational models, in particular for rapidly changing and adverse environments, and propose to classify microbial growth strategies based on Grimes's CSR framework.

Live-cell imaging reveals single-cell and population-level infection strategies of Listeria monocytogenes in macrophages

Pathogens have developed intricate strategies to overcome the host's innate immune responses. In this paper we use live-cell microscopy with a single bacterium resolution to follow in real time interactions between the food-borne pathogen L. monocytogenes and host macrophages, a key event controlling the infection in vivo. We demonstrate that infection results in heterogeneous outcomes, with only a subset of bacteria able to establish a replicative invasion of macrophages. The fate of individual bacteria in the same host cell was independent from the host cell and non-cooperative, being independent from co-infecting bacteria. A higher multiplicity of infection resulted in a reduced probability of replication of the overall bacterial population. By use of internalisation assays and conditional probabilities to mathematically describe the two-stage invasion process, we demonstrate that the higher MOI compromises the ability of macrophages to phagocytose bacteria. We found that the rate of phagocytosis is mediated via the secreted Listeriolysin toxin (LLO), while the probability of replication of intracellular bacteria remained constant. Using strains expressing fluorescent reporters to follow transcription of either the LLO-encoding hly or actA genes, we show that replicative bacteria exhibited higher PrfA regulon expression in comparison to those bacteria that did not replicate, however elevated PrfA expression per se was not sufficient to increase the probability of replication. Overall, this demonstrates a new role for the population-level, but not single cell, PrfA-mediated activity to regulate outcomes of host pathogen interactions.

Crosstalk between hypoxic cellular micro-environment and the immune system: a potential therapeutic target for infectious diseases

There are overwhelming reports on the promotional effect of hypoxia on the malignant behavior of various forms of cancer cells. This has been proposed and tested exhaustively in the light of cancer immunotherapy. However, there could be more interesting functions of a hypoxic cellular micro-environment than malignancy. There is a highly intricate crosstalk between hypoxia inducible factor (HIF), a transcriptional factor produced during hypoxia, and nuclear factor kappa B (NF-κB) which has been well characterized in various immune cell types. This important crosstalk shares common activating and inhibitory stimuli, regulators, and molecular targets. Impaired hydroxylase activity contributes to the activation of HIFs. Inflammatory ligands activate NF-κB activity, which leads to the expression of inflammatory and anti-apoptotic genes. The eventual sequelae of the interaction between these two molecular players in immune cells, either bolstering or abrogating functions, is largely cell-type dependent. Importantly, this holds promise for interesting therapeutic interventions against several infectious diseases, as some HIF agonists have helped prevent immune-related diseases. Hypoxia and inflammation are common features of infectious diseases. Here, we highlighted the role of this crosstalk in the light of functional immunity against infection and inflammation, with special focus on various innate and adaptive immune cells. Particularly, we discussed the bidirectional effects of this crosstalk in the regulation of immune responses by monocytes/macrophages, dendritic cells, neutrophils, B cells, and T cells. We believe an advanced understanding of the interplay between HIFs and NF-kB could reveal novel therapeutic targets for various infectious diseases with limited treatment options.

Intrinsically disordered proteins and conformational noise: The hypothesis a decade later

Phenotypic plasticity is the ability of individual genotypes to produce different phenotypes in response to environmental perturbations. We previously postulated how conformational noise emanating from conformational dynamics of intrinsically disordered proteins (IDPs) which is distinct from transcriptional noise, can contribute to phenotypic switching by rewiring the cellular protein interaction network. Since most transcription factors are IDPs, we posited that conformational noise is an integral component of transcriptional noise implying that IDPs may amplify total noise in the system either stochastically or in response to environmental changes. Here, we review progress in elucidating the details of the hypothesis. We highlight empirical evidence supporting the hypothesis, discuss conceptual advances that underscore its fundamental importance and implications, and identify areas for future investigations.

Systematic analysis and optimization of early warning signals for critical transitions using distribution data

Abrupt shifts between alternative regimes occur in complex systems, from cell regulation to brain functions to ecosystems. Several model-free early warning signals (EWS) have been proposed to detect impending transitions, but failure or poor performance in some systems have called for better investigation of their generic applicability. Notably, there are still ongoing debates whether such signals can be successfully extracted from data in particular from biological experiments. In this work, we systematically investigate properties and performance of dynamical EWS in different deteriorating conditions, and we propose an optimized combination to trigger warnings as early as possible, eventually verified on experimental data from microbiological populations. Our results explain discrepancies observed in the literature between warning signs extracted from simulated models and from real data, provide guidance for EWS selection based on desired systems and suggest an optimized composite indicator to alert for impending critical transitions using distribution data.

Iron Memory in E. coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when E. coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This memory pre-exists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, whether low or high, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We also demonstrate that iron memory can integrate multiple stimuli, impacting other bacterial behaviors such as biofilm formation and antibiotic tolerance.

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

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

A reversible mutation in a genomic hotspot saves bacterial swarms from extinction

Microbial adaptation to changing environmental conditions is frequently mediated by hypermutable sequences. Here we demonstrate that such a hypermutable hotspot within a gene encoding a flagellar unit of Paenibacillus glucanolyticus generated spontaneous non-swarming mutants with increased stress resistance. These mutants, which survived conditions that eliminated wild-type cultures, could be carried by their swarming siblings when the colony spread, consequently increasing their numbers at the spreading edge. Of interest, the hypermutable nature of the aforementioned sequence enabled the non-swarming mutants to serve as "seeds" for a new generation of wild-type cells through reversion of the mutation. Using a mathematical model, we examined the survival dynamics of P. glucanolyticus colonies under fluctuating environments. Our experimental and theoretical results suggest that the non-swarming, stress-resistant mutants can save the colony from extinction. Notably, we identified this hypermutable sequence in flagellar genes of additional Paenibacillus species, suggesting that this phenomenon could be wide-spread and ecologically important.

Avoiding the All-or-None Response in Gene Expression During E. coli Continuous Cultivation Based on the On-Line Monitoring of Cell Phenotypic Switching Dynamics

Different expression vectors are available for the effective production of recombinant proteins by bacterial populations. However, the productivity of such systems is limited by the inherent noise of the gene circuits used for the synthesis of recombinant products. An extreme case of cell-to-cell heterogeneity that has been previously reported for the ara- and lac-based expression systems in E. coli is the all-or-none response. According to this mode of response, two subpopulations of cells are generated, i.e., a "low-" subpopulation exhibiting a shallow expression level and a "high-" subpopulation exhibiting a high-expression level. The "low-" subpopulation can be considered as a cluster of non-producing cells contributing to the loss of productivity. Here we describe the setup, design, and operation of a continuous culture where inducer addition is operated based on microbial population dynamics. The determination of population dynamics is done based on an automated flow cytometry (FC) procedure previously denoted as segregostat. We illustrate how this setup can be used to control the activation of an ara-based expression system and avoid phenotypic diversification leading to an all-or-none response. Upon the determination of the natural frequency of the gene circuit used as an expression system, our current protocol can be set up without the requirement of a feedback controller.

Exposure to stressors and antimicrobials induces cell-autonomous ultrastructural heterogeneity of an intracellular bacterial pathogen

Despite their clonality, intracellular bacterial pathogens commonly show remarkable physiological heterogeneity during infection of host cells. Physiological heterogeneity results in distinct ultrastructural morphotypes, but the correlation between bacterial physiological state and ultrastructural appearance remains to be established. In this study, we showed that individual cells of Salmonella enterica serovar Typhimurium are heterogeneous in their ultrastructure. Two morphotypes based on the criterion of cytoplasmic density were discriminated after growth under standard culture conditions, as well as during intracellular lifestyle in mammalian host cells. We identified environmental conditions which affect cytoplasmic densities. Using compounds generating oxygen radicals and defined mutant strains, we were able to link the occurrence of an electron-dense ultrastructural morphotype to exposure to oxidative stress and other stressors. Furthermore, by combining ultrastructural analyses of Salmonella during infection and fluorescence reporter analyses for cell viability, we provided evidence that two characterized ultrastructural morphotypes with electron-lucent or electron-dense cytoplasm represent viable cells. Moreover, the presence of electron-dense types is stress related and can be experimentally induced only when amino acids are available in the medium. Our study proposes ultrastructural morphotypes as marker for physiological states of individual intracellular pathogens providing a new marker for single cell analyses.

Microbial degradation of polyethylene terephthalate: a systematic review

Plastic pollution levels have increased rapidly in recent years, due to the accumulation of plastic waste, including polyethylene terephthalate (PET). Both high production and the lack of efficient methods for disposal and recycling affect diverse aquatic and terrestrial ecosystems owing to the high accumulation rates of plastics. Traditional chemical and physical degradation techniques have caused adverse effects on the environment; hence, the use of microorganisms for plastic degradation has gained importance recently. This systematic review was conducted for evaluating the reported findings about PET degradation by wild and genetically modified microorganisms to make them available for future work and to contribute to the eventual implementation of an alternative, an effective, and environmentally friendly method for the management of plastic waste such as PET. Both wild and genetically modified microorganisms with the metabolic potential to degrade this polymer were identified, in addition to the enzymes and genes used for genetic modification. The most prevalent wild-type PET-degrading microorganisms were bacteria (56.3%, 36 genera), followed by fungi (32.4%, 30 genera), microalgae (1.4%; 1 genus, namely Spirulina sp.), and invertebrate associated microbiota (2.8%). Among fungi and bacteria, the most prevalent genera were Aspergillus sp. and Bacillus sp., respectively. About genetically modified microorganisms, 50 strains of Escherichia coli, most of them expressing PETase enzyme, have been used. We emphasize the pressing need for implementing biological techniques for PET waste management on a commercial scale, using consortia of microorganisms. We present this work in five sections: an Introduction that highlights the importance of PET biodegradation as an effective and sustainable alternative, a section on Materials and methods that summarizes how the search for articles and manuscripts in different databases was done, and another Results section where we present the works found on the subject, a final part of Discussion and analysis of the literature found and finally we present a Conclusion and prospects.

Assessing persister awakening dynamics following antibiotic treatment in E. coli

Given the low fraction of antibiotic-tolerant persisters and the transient nature of the persister phenotype, identifying molecular mechanisms underlying persister state exit, also called "awakening," is challenging. Here, we describe how persister awakening kinetics can be quantified at the single-cell level, enabling the identification of genes that are important for persister survival following antibiotic treatment. We report step-by-step sample preparation, dynamic recording, and data analysis. Although the setup is flexible, time-lapse microscopy requires a minimal number of persisters being present.

For complete details on the use and execution of this protocol, please refer to Wilmaerts et al. (2022).

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Protocol for assessing persister awakening dynamics via time-lapse microscopy

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Experimental procedures and explanation on how to identify persisters

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Guidelines on analyses and interpretation of awakening kinetics

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Integrative biology of persister cell formation: molecular circuitry, phenotypic diversification and fitness effects

Microbial populations often contain persister cells, which reduce the extinction risk upon sudden stresses. Persister cell formation is deeply intertwined with physiology. Due to this complexity, it cannot be satisfactorily understood by focusing only on mechanistic, physiological or evolutionary aspects. In this review, we take an integrative biology perspective to identify common principles of persister cell formation, which might be applicable across evolutionary-distinct microbes. Persister cells probably evolved to cope with a fundamental trade-off between cellular stress and growth tasks, as any biosynthetic resource investment in growth-supporting proteins is at the expense of stress tasks and vice versa. Natural selection probably favours persister cell subpopulation formation over a single-phenotype strategy, where each cell is prepared for growth and stress to a suboptimal extent, since persister cells can withstand harsher environments and their coexistence with growing cells leads to a higher fitness. The formation of coexisting phenotypes requires bistable molecular circuitry. Bistability probably emerges from growth-modulated, positive feedback loops in the cell's growth versus stress control network, involving interactions between sigma factors, guanosine pentaphosphate and toxin-antitoxin (TA) systems. We conclude that persister cell formation is most likely a response to a sudden reduction in growth rate, which can be achieved by antibiotic addition, nutrient starvation, sudden stresses, nutrient transitions or activation of a TA system.

PfARID Regulates P. falciparum Malaria Parasite Male Gametogenesis and Female Fertility and Is Critical for Parasite Transmission to the Mosquito Vector

Sexual reproduction of Plasmodium falciparum parasites is critical to the spread of malaria in the human population. The factors that regulate gene expression underlying formation of fertilization-competent gametes, however, remain unknown. Here, we report that P. falciparum expresses a protein with an AT-rich interaction domain (ARID) which, in other organisms, is part of chromatin remodeling complexes. P. falciparum ARID (PfARID) localized to the parasite nucleus and is critical for the formation of male gametes and fertility of female gametes. PfARID gene deletion (Pfarid-) gametocytes showed downregulation of gene expression important for gametogenesis, antigenic variation, and cell signaling and for parasite development in the mosquito. Our study identifies PfARID as a critical nuclear protein involved in regulating the gene expression landscape of mature gametocytes. This establishes fertility and also prepares the parasite for postfertilization events that are essential for infection of the mosquito vector. IMPORTANCE Successful completion of the Plasmodium life cycle requires formation of mature gametocytes and their uptake by the female Anopheles mosquito vector in an infected blood meal. Inside the mosquito midgut the parasite undergoes gametogenesis and sexual reproduction. In the present study, we demonstrate that PfARID is essential for male gametogenesis and female fertility and, thereby, transmission to the mosquito vector. PfARID possibly regulates the chromatin landscape of stage V gametocytes and targeting PfARID function may provide new avenues into designing interventions to prevent malaria transmission.

Stress-Induced Mutagenesis, Gambler Cells, and Stealth Targeting Antibiotic-Induced Evolution

Mechanisms of evolution and evolution of antibiotic resistance are both fundamental and world health problems. Stress-induced mutagenesis defines mechanisms of mutagenesis upregulated by stress responses, which drive adaptation when cells are maladapted to their environments—when stressed. Work in mutagenesis induced by antibiotics had produced tantalizing clues but not coherent mechanisms. We review recent advances in antibiotic-induced mutagenesis that integrate how reactive oxygen species (ROS), the SOS and general stress responses, and multichromosome cells orchestrate a stress response-induced switch from high-fidelity to mutagenic repair of DNA breaks. Moreover, while sibling cells stay stable, a mutable “gambler” cell subpopulation is induced by differentially generated ROS, which signal the general stress response. We discuss other evolvable subpopulations and consider diverse evolution-promoting molecules as potential targets for drugs to slow evolution of antibiotic resistance, cross-resistance, and immune evasion. An FDA-approved drug exemplifies “stealth” evolution-slowing drugs that avoid selecting resistance to themselves or antibiotics.

Collective behavior and nongenetic inheritance allow bacterial populations to adapt to changing environments

Collective behaviors require coordination among a group of individuals. As a result, individuals that are too phenotypically different from the rest of the group can be left out, reducing heterogeneity, but increasing coordination. If individuals also reproduce, the offspring can have different phenotypes from their parent(s). This raises the question of how these two opposing processes-loss of diversity by collective behaviors and generation of it through growth and inheritance-dynamically shape the phenotypic composition of an isogenic population. We examine this question theoretically using collective migration of chemotactic bacteria as a model system, where cells of different swimming phenotypes are better suited to navigate in different environments. We find that the differential loss of phenotypes caused by collective migration is environment-dependent. With cell growth, this differential loss enables migrating populations to dynamically adapt their phenotype compositions to the environment, enhancing migration through multiple environments. Which phenotypes are produced upon cell division depends on the level of nongenetic inheritance, and higher inheritance leads to larger composition adaptation and faster migration at steady state. However, this comes at the cost of slower responses to new environments. Due to this trade-off, there is an optimal level of inheritance that maximizes migration speed through changing environments, which enables a diverse population to outperform a nondiverse one. Growing populations might generally leverage the selection-like effects provided by collective behaviors to dynamically shape their own phenotype compositions, without mutations.

Multiple molecular events underlie stochastic switching between 2 heritable cell states in fungi

Eukaryotic transcriptional networks are often large and contain several levels of feedback regulation. Many of these networks have the ability to generate and maintain several distinct transcriptional states across multiple cell divisions and to switch between them. In certain instances, switching between cell states is stochastic, occurring in a small subset of cells of an isogenic population in a seemingly homogenous environment. Given the scarcity and unpredictability of switching in these cases, investigating the determining molecular events is challenging. White-opaque switching in the fungal species Candida albicans is an example of stably inherited cell states that are determined by a complex transcriptional network and can serve as an experimentally accessible model system to study characteristics important for stochastic cell fate switching in eukaryotes. In standard lab media, genetically identical cells maintain their cellular identity (either "white" or "opaque") through thousands of cell divisions, and switching between the states is rare and stochastic. By isolating populations of white or opaque cells, previous studies have elucidated the many differences between the 2 stable cell states and identified a set of transcriptional regulators needed for cell type switching and maintenance of the 2 cell types. Yet, little is known about the molecular events that determine the rare, stochastic switching events that occur in single cells. We use microfluidics combined with fluorescent reporters to directly observe rare switching events between the white and opaque states. We investigate the stochastic nature of switching by beginning with white cells and monitoring the activation of Wor1, a master regulator and marker for the opaque state, in single cells and throughout cell pedigrees. Our results indicate that switching requires 2 stochastic steps; first an event occurs that predisposes a lineage of cells to switch. In the second step, some, but not all, of those predisposed cells rapidly express high levels of Wor1 and commit to the opaque state. To further understand the rapid rise in Wor1, we used a synthetic inducible system in Saccharomyces cerevisiae into which a controllable C. albicans Wor1 and a reporter for its transcriptional control region have been introduced. We document that Wor1 positive autoregulation is highly cooperative (Hill coefficient > 3), leading to rapid activation and producing an "all or none" rather than a graded response. Taken together, our results suggest that reaching a threshold level of a master regulator is sufficient to drive cell type switching in single cells and that an earlier molecular event increases the probability of reaching that threshold in certain small lineages of cells. Quantitative molecular analysis of the white-opaque circuit can serve as a model for the general understanding of complex circuits.

Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations

Microbial populations can adapt to adverse environmental conditions either by appropriately sensing and responding to the changes in their surroundings or by stochastically switching to an alternative phenotypic state. Recent data point out that these two strategies can be exhibited by the same cellular system, depending on the amplitude/frequency of the environmental perturbations and on the architecture of the genetic circuits involved in the adaptation process. Accordingly, several mitigation strategies have been designed for the effective control of microbial populations in different contexts, ranging from biomedicine to bioprocess engineering. Technically, such control strategies have been made possible by the advances made at the level of computational and synthetic biology combined with control theory. However, these control strategies have been applied mostly to synthetic gene circuits, impairing the applicability of the approach to natural circuits. In this review, we argue that it is possible to expand these control strategies to any cellular system and gene circuits based on a metric derived from this information theory, i.e., mutual information (MI). Indeed, based on this metric, it should be possible to characterize the natural frequency of any gene circuits and use it for controlling gene circuits within a population of cells.

The role of sigma factor competition in bacterial adaptation under prolonged starvation

The study of adaptive microbial evolution in the laboratory can illuminate the genetic mechanisms of gaining fitness under a pre-defined set of selection factors. Laboratory evolution of bacteria under long-term starvation has gained importance in recent years because of its ability to uncover adaptive strategies that overcome prolonged nutrient limitation, a condition often encountered by natural microbes. In this evolutionary paradigm, bacteria are maintained in an energy-restricted environment in a growth phase called long-term stationary phase (LTSP). This phase is characterized by a stable, viable population size and highly dynamic genetic changes. Multiple independent iterations of LTSP evolution experiments have given rise to mutants that are slow-growing compared to the ancestor. Although the antagonistic regulation between rapid growth and the stress response is well-known in bacteria (especially Escherichia coli), the growth deficit of many LTSP-adapted mutants has not been explored in detail. In this review, I pinpoint the trade-off between growth and stress response as a dominant driver of evolutionary strategies under prolonged starvation. Focusing on mainly E. coli-based research, I discuss the various affectors and regulators of the competition between sigma factors to occupy their targets on the genome, and assess its effect on growth advantage in stationary phase (GASP). Finally, I comment on some crucial issues that hinder the progress of the field, including identification of novel metabolites in nutrient-depleted media, and the importance of using multidisciplinary research to resolve them.

Transcription-coupled DNA repair underlies variation in persister awakening and the emergence of resistance

Persisters constitute a population of temporarily antibiotic-tolerant variants in an isogenic bacterial population and are considered an important cause of relapsing infections. It is currently unclear how cellular damage inflicted by antibiotic action is reversed upon persister state exit and how this relates to antibiotic resistance development at the molecular level. We demonstrate that persisters, upon fluoroquinolone treatment, accumulate oxidative DNA damage, which is repaired through nucleotide excision repair. Detection of the damage occurs via transcription-coupled repair using UvrD-mediated backtracking or Mfd-controlled displacement of the RNA polymerase. This competition results in heterogeneity in persister awakening lags. Most persisters repair the oxidative DNA damage, displaying a mutation rate equal to the untreated population. However, the promutagenic factor Mfd increases the mutation rate in a persister subpopulation. Our data provide in-depth insight into the molecular mechanisms underlying persister survival and pinpoint Mfd as an important molecular factor linking persistence to resistance development.

The transcriptional regulator HDP1 controls expansion of the inner membrane complex during early sexual differentiation of malaria parasites

Transmission of Plasmodium falciparum and other malaria parasites requires their differentiation from asexual blood stages into gametocytes, the non-replicative sexual stage necessary to infect the mosquito vector. This transition involves changes in gene expression and chromatin reorganization that result in the activation and silencing of stage-specific genes. However, the genomes of malaria parasites have been noted for their limited number of transcriptional and chromatin regulators, and the molecular mediators of these changes remain largely unknown. We recently identified homeodomain protein 1 (HDP1) as a DNA-binding protein, first expressed in gametocytes, that enhances the expression of key genes critical for early sexual differentiation. The discovery of HDP1 marks a new class of transcriptional regulator in malaria parasites outside of the better-characterized ApiAP2 family. Here, using molecular biology, biochemistry and microscopy techniques, we show that HDP1 is essential for gametocyte maturation, facilitating the necessary upregulation of inner membrane complex components during early gametocytogenesis that gives P. falciparum gametocytes their characteristic shape.

Bet-hedging in innate and adaptive immune systems

Immune system evolution is shaped by the fitness costs and trade-offs associated with mounting an immune response. Costs that arise mainly as a function of the magnitude of investment, including energetic and immunopathological costs, are well-represented in studies of immune system evolution. Less well considered, however, are the costs of immune cell plasticity and specialization. Hosts in nature encounter a large diversity of microbes and parasites that require different and sometimes conflicting immune mechanisms for defense, but it takes precious time to recognize and correctly integrate signals for an effective polarized response. In this perspective, we propose that bet-hedging can be a viable alternative to plasticity in immune cell effector function, discuss conditions under which bet-hedging is likely to be an advantageous strategy for different arms of the immune system, and present cases from both innate and adaptive immune systems that suggest bet-hedging at play.

Silent transcription intervals and translational bursting lead to diverse phenotypic switching

For complex process of gene expression, we use theoretical analysis and stochastic simulations to study the phenotypic diversity induced by silent transcription intervals and translational bursting.

SOS-Independent Pyocin Production in P. aeruginosa Is Induced by XerC Recombinase Deficiency

Pyocins are phage tail-like protein complexes that can be used by Pseudomonas aeruginosa to enact intraspecies competition by killing competing strains. The pyocin gene cluster also encodes holin and lysin enzymes that lyse producer cells to release the pyocins. The best-known inducers of pyocin production under laboratory conditions are DNA-damaging agents, including fluoroquinolone antibiotics, that activate the SOS response. Here, we report the discovery of an alternate, RecA-independent pathway of strong pyocin induction that is active in cells deficient for the tyrosine recombinase XerC. When ΔxerC cells were examined at the single-cell level, only a fraction of the cell population strongly expressed pyocins before explosively lysing, suggesting a that a built-in heterogenous response system protects the cell population from widespread lysis. Disabling the holin and lysin enzymes or deleting the entire pyocin gene cluster blocked explosive lysis and delayed but did not prevent the death of pyocin-producing cells, suggesting that ΔxerC cells activate other lysis pathways. Mutating XerC to abolish its recombinase activity induced pyocin expression to a lesser extent than the full deletion, suggesting that XerC has multiple functions with respect to pyocin activation. Our studies uncover a new pathway for pyocin production and highlight its response across a genetically identical population. Moreover, our finding that ΔxerC populations are hypersensitive to fluoroquinolones raises the intriguing possibility that XerC inhibition may potentiate the activity of these antibiotics against P. aeruginosa infections. IMPORTANCE Pseudomonas aeruginosa is a versatile and ubiquitous bacterium that frequently infects humans as an opportunistic pathogen. P. aeruginosa competes with other strains within the species by producing killing complexes termed pyocins, which are only known to be induced by cells experiencing DNA damage and the subsequent SOS response. Here, we discovered that strains lacking a recombinase enzyme called XerC strongly produce pyocins independently of the SOS response. We also show that these strains are hypersensitive to commonly used fluoroquinolone antibiotic treatment and that fluoroquinolones further stimulate pyocin production. Thus, XerC is an attractive target for future therapies that simultaneously sensitize P. aeruginosa to antibiotics and stimulate the production of bactericidal pyocins.

Quantifying the effect of genetic, environmental and individual demographic stochastic variability for population dynamics in Plantago lanceolata

Simple demographic events, the survival and reproduction of individuals, drive population dynamics. These demographic events are influenced by genetic and environmental parameters, and are the focus of many evolutionary and ecological investigations that aim to predict and understand population change. However, such a focus often neglects the stochastic events that individuals experience throughout their lives. These stochastic events also influence survival and reproduction and thereby evolutionary and ecological dynamics. Here, we illustrate the influence of such non-selective demographic variability on population dynamics using population projection models of an experimental population of Plantago lanceolata. Our analysis shows that the variability in survival and reproduction among individuals is largely due to demographic stochastic variation with only modest effects of differences in environment, genes, and their interaction. Common expectations of population growth, based on expected lifetime reproduction and generation time, can be misleading when demographic stochastic variation is large. Large demographic stochastic variation exhibited within genotypes can lower population growth and slow evolutionary adaptive dynamics. Our results accompany recent investigations that call for more focus on stochastic variation in fitness components, such as survival, reproduction, and functional traits, rather than dismissal of this variation as uninformative noise.

A virtual sequencer reveals the dephasing patterns in error-correction code DNA sequencing

An error-correction code (ECC) sequencing approach has recently been reported to effectively reduce sequencing errors by interrogating a DNA fragment with three orthogonal degenerate sequencing-by-synthesis (SBS) reactions. However, similar to other non-single-molecule SBS methods, the reaction will gradually lose its synchronization within a molecular colony in ECC sequencing. This phenomenon, called dephasing, causes sequencing error, and in ECC sequencing, induces distinctive dephasing patterns. To understand the characteristic dephasing patterns of the dual-base flowgram in ECC sequencing and to generate a correction algorithm, we built a virtual sequencer in silico. Starting from first principles and based on sequencing chemical reactions, we simulated ECC sequencing results, identified the key factors of dephasing in ECC sequencing chemistry and designed an effective dephasing algorithm. The results show that our dephasing algorithm is applicable to sequencing signals with at least 500 cycles, or 1000-bp average read length, with acceptably low error rate for further parity checks and ECC deduction. Our virtual sequencer with our dephasing algorithm can further be extended to a dichromatic form of ECC sequencing, allowing for a potentially much more accurate sequencing approach.

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.

Detecting Persister Awakening Determinants

For long, persistence research has focused primarily on disentangling mechanisms of persister state entry. Due to the rapid advances in the field of single-cell techniques and newly obtained insights in the persister phenotype, studying persister awakening has been unlocked and it has gained much interest in the scientific community. However, a framework on how this research should be conducted is currently lacking. Therefore, we here present a method to detect and validate genes important for persister awakening.

Phenotypic-dependent variability and the emergence of tolerance in bacterial populations

Ecological and evolutionary dynamics have been historically regarded as unfolding at broadly separated timescales. However, these two types of processes are nowadays well-documented to intersperse much more tightly than traditionally assumed, especially in communities of microorganisms. Advancing the development of mathematical and computational approaches to shed novel light onto eco-evolutionary problems is a challenge of utmost relevance. With this motivation in mind, here we scrutinize recent experimental results showing evidence of rapid evolution of tolerance by lag in bacterial populations that are periodically exposed to antibiotic stress in laboratory conditions. In particular, the distribution of single-cell lag times-i.e., the times that individual bacteria from the community remain in a dormant state to cope with stress-evolves its average value to approximately fit the antibiotic-exposure time. Moreover, the distribution develops right-skewed heavy tails, revealing the presence of individuals with anomalously large lag times. Here, we develop a parsimonious individual-based model mimicking the actual demographic processes of the experimental setup. Individuals are characterized by a single phenotypic trait: their intrinsic lag time, which is transmitted with variation to the progeny. The model-in a version in which the amplitude of phenotypic variations grows with the parent's lag time-is able to reproduce quite well the key empirical observations. Furthermore, we develop a general mathematical framework allowing us to describe with good accuracy the properties of the stochastic model by means of a macroscopic equation, which generalizes the Crow-Kimura equation in population genetics. Even if the model does not account for all the biological mechanisms (e.g., genetic changes) in a detailed way-i.e., it is a phenomenological one-it sheds light onto the eco-evolutionary dynamics of the problem and can be helpful to design strategies to hinder the emergence of tolerance in bacterial communities. From a broader perspective, this work represents a benchmark for the mathematical framework designed to tackle much more general eco-evolutionary problems, thus paving the road to further research avenues.

Bacillus subtilis: a bacterium for all seasons

Microbes inhabit ever-changing environments in which the conditions for propagation, whether they be favorable or unfavorable, are often transient. Plants and animals are able to cope with changing circumstances in their external environment by maintaining homeostasis for internal cells, tissues and organs. Microbes do not have this luxury. Instead, they have evolved mechanisms for adapting to change by being versatile. In some cases, these adaptations involve the expression of a limited set of genes that exploit the availability of a food source or provide protection against chemical, radiation or thermal stress. In other cases, however, microbes adapt in a more elaborate manner by entering a specialized state that enables them to exploit a particular niche or protects them against environmental extremes. Entry into such a state can occur as a direct response to an external cue or stochastically (by chance) as part of a bet-hedging strategy, or sometimes a combination of the two. An example of a versatile microbe that exhibits a wide variety of states is the bacterium Bacillus subtilis, the subject of this Primer. Many of the states exhibited by B. subtilis are similar to states observed in other bacteria. What is special about B. subtilis is the unusually rich repertoire of alternative states exhibited by one bacterium, enabling it to cope with a wide range of environmental challenges.

Noise suppression in stochastic genetic circuits using PID controllers

Inside individual cells, protein population counts are subject to molecular noise due to low copy numbers and the inherent probabilistic nature of biochemical processes. We investigate the effectiveness of proportional, integral and derivative (PID) based feedback controllers to suppress protein count fluctuations originating from two noise sources: bursty expression of the protein, and external disturbance in protein synthesis. Designs of biochemical reactions that function as PID controllers are discussed, with particular focus on individual controllers separately, and the corresponding closed-loop system is analyzed for stochastic controller realizations. Our results show that proportional controllers are effective in buffering protein copy number fluctuations from both noise sources, but this noise suppression comes at the cost of reduced static sensitivity of the output to the input signal. In contrast, integral feedback has no effect on the protein noise level from stochastic expression, but significantly minimizes the impact of external disturbances, particularly when the disturbance comes at low frequencies. Counter-intuitively, integral feedback is found to amplify external disturbances at intermediate frequencies. Next, we discuss the design of a coupled feedforward-feedback biochemical circuit that approximately functions as a derivate controller. Analysis using both analytical methods and Monte Carlo simulations reveals that this derivative controller effectively buffers output fluctuations from bursty stochastic expression, while maintaining the static input-output sensitivity of the open-loop system. In summary, this study provides a systematic stochastic analysis of biochemical controllers, and paves the way for their synthetic design and implementation to minimize deleterious fluctuations in gene product levels.

In the noisy cellular environment, biochemical species such as genes, RNAs and proteins that often occur at low molecular counts, are subject to considerable stochastic fluctuations in copy numbers over time. How cellular biochemical processes function reliably in the face of such randomness is an intriguing fundamental problem. Increasing evidence suggests that random fluctuations (noise) in protein copy numbers play important functional roles, such as driving genetically identical cells to different cell fates. Moreover, many disease states have been attributed to elevated noise levels in specific proteins. Here we systematically investigate design of biochemical systems that function as proportional, integral and derivative-based feedback controllers to suppress protein count fluctuations arising from bursty expression of the protein and external disturbance in protein synthesis. Our results show that different controllers are effective in buffering different noise components, and identify ranges of feedback gain for minimizing deleterious fluctuations in protein levels.

Non-Genetic Diversity in Chemosensing and Chemotactic Behavior

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

Cryptic surface-associated multicellularity emerges through cell adhesion and its regulation

The repeated evolution of multicellularity led to a wide diversity of organisms, many of which are sessile, including land plants, many fungi, and colonial animals. Sessile organisms adhere to a surface for most of their lives, where they grow and compete for space. Despite the prevalence of surface-associated multicellularity, little is known about its evolutionary origin. Here, we introduce a novel theoretical approach, based on spatial lineage tracking of cells, to study this origin. We show that multicellularity can rapidly evolve from two widespread cellular properties: cell adhesion and the regulatory control of adhesion. By evolving adhesion, cells attach to a surface, where they spontaneously give rise to primitive cell collectives that differ in size, life span, and mode of propagation. Selection in favor of large collectives increases the fraction of adhesive cells until a surface becomes fully occupied. Through kin recognition, collectives then evolve a central-peripheral polarity in cell adhesion that supports a division of labor between cells and profoundly impacts growth. Despite this spatial organization, nascent collectives remain cryptic, lack well-defined boundaries, and would require experimental lineage tracking technologies for their identification. Our results suggest that cryptic multicellularity could readily evolve and originate well before multicellular individuals become morphologically evident.

Quasi-robust control of biochemical reaction networks via stochastic morphing

One of the main objectives of synthetic biology is the development of molecular controllers that can manipulate the dynamics of a given biochemical network that is at most partially known. When integrated into smaller compartments, such as living or synthetic cells, controllers have to be calibrated to factor in the intrinsic noise. In this context, biochemical controllers put forward in the literature have focused on manipulating the mean (first moment) and reducing the variance (second moment) of the target molecular species. However, many critical biochemical processes are realized via higher-order moments, particularly the number and configuration of the probability distribution modes (maxima). To bridge the gap, we put forward the stochastic morpher controller that can, under suitable timescale separations, morph the probability distribution of the target molecular species into a predefined form. The morphing can be performed at a lower-resolution, allowing one to achieve desired multi-modality/multi-stability, and at a higher-resolution, allowing one to achieve arbitrary probability distributions. Properties of the controller, such as robustness and convergence, are rigorously established, and demonstrated on various examples. Also proposed is a blueprint for an experimental implementation of stochastic morpher.

Searching for principles of microbial physiology

Why do evolutionarily distinct microorganisms display similar physiological behaviours? Why are transitions from high-ATP yield to low(er)-ATP yield metabolisms so widespread across species? Why is fast growth generally accompanied with low stress tolerance? Do these regularities occur because most microbial species are subject to the same selective pressures and physicochemical constraints? If so, a broadly-applicable theory might be developed that predicts common microbiological behaviours. Microbial systems biologists have been working out the contours of this theory for the last two decades, guided by experimental data. At its foundations lie basic principles from evolutionary biology, enzyme biochemistry, metabolism, cell composition and steady-state growth. The theory makes predictions about fitness costs and benefits of protein expression, physicochemical constraints on cell growth and characteristics of optimal metabolisms that maximise growth rate. Comparisons of the theory with experimental data indicates that microorganisms often aim for maximisation of growth rate, also in the presence of stresses; they often express optimal metabolisms and metabolic proteins at optimal concentrations. This review explains the current status of the theory for microbiologists; its roots, predictions, experimental evidence and future directions.

Comparative genomics of white and opaque cell states supports an epigenetic mechanism of phenotypic switching in Candida albicans

Several Candida species can undergo a heritable and reversible transition from a 'white' state to a mating proficient 'opaque' state. This ability relies on highly interconnected transcriptional networks that control cell-type-specific gene expression programs over multiple generations. Candida albicans, the most prominent pathogenic Candida species, provides a well-studied paradigm for the white-opaque transition. In this species, a network of at least eight transcriptional regulators controls the balance between white and opaque states that have distinct morphologies, transcriptional profiles, and physiological properties. Given the reversible nature and the high frequency of white-opaque transitions, it is widely assumed that this switch is governed by epigenetic mechanisms that occur independently of any changes in DNA sequence. However, a direct genomic comparison between white and opaque cells has yet to be performed. Here, we present a whole-genome comparative analysis of C. albicans white and opaque cells. This analysis revealed rare genetic changes between cell states, none of which are linked to white-opaque switching. This result is consistent with epigenetic mechanisms controlling cell state differentiation in C. albicans and provides direct evidence against a role for genetic variation in mediating the switch.

Discerning the role of polymicrobial biofilms in the ascent, prevalence, and extent of heteroresistance in clinical practice

Antimicrobial therapy is facing a worrisome and underappreciated challenge, the phenomenon of heteroresistance (HR). HR has been gradually documented in clinically relevant pathogens (e.g. Pseudomonas aeruginosa, Staphylococcus aureus, Burkholderia spp., Acinetobacter baumannii, Klebsiella pneumoniae, Candida spp.) towards several drugs and is believed to complicate the clinical picture of chronic infections. This type of infections are typically mediated by polymicrobial biofilms, wherein microorganisms inherently display a wide range of physiological states, distinct metabolic pathways, diverging refractory levels of stress responses, and a complex network of chemical signals exchange. This review aims to provide an overview on the relevance, prevalence, and implications of HR in clinical settings. Firstly, related terminologies (e.g. resistance, tolerance, persistence), sometimes misunderstood and overlapped, were clarified. Factors generating misleading HR definitions were also uncovered. Secondly, the recent HR incidences reported in clinically relevant pathogens towards different antimicrobials were annotated. The potential mechanisms underlying such occurrences were further elucidated. Finally, the link between HR and biofilms was discussed. The focus was to recognize the presence of heterogeneous levels of resistance within most biofilms, as well as the relevance of polymicrobial biofilms in chronic infectious diseases and their role in resistance spreading. These topics were subject of a critical appraisal, gaining insights into the ascending clinical implications of HR in antimicrobial resistance spreading, which could ultimately help designing effective therapeutic options.

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.

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.

Switching behaviour in vascular smooth muscle cell-matrix adhesion during oscillatory loading

Integrins regulate mechanotransduction between smooth muscle cells (SMCs) and the extracellular matrix (ECM). SMCs resident in the walls of airways or blood vessels are continuously exposed to dynamic mechanical forces due to breathing or pulsatile blood flow. However, the resulting effects of these forces on integrin dynamics and associated cell-matrix adhesion are not well understood. Here we present experimental results from atomic force microscopy (AFM) experiments, designed to study the integrin response to external oscillatory loading of varying amplitudes applied to live aortic SMCs, together with theoretical results from a mathematical model. In the AFM experiments, a fibronectin-coated probe was used cyclically to indent and retract from the surface of the cell. We observed a transition between states of firm adhesion and of complete detachment as the amplitude of oscillatory loading increased, revealed by qualitative changes in the force timecourses. Interestingly, for some of the SMCs in the experiments, switching behaviour between the two adhesion states is observed during single timecourses at intermediate amplitudes. We obtain two qualitatively similar adhesion states in the mathematical model, where we simulate the cell, integrins and ECM as an evolving system of springs, incorporating local integrin binding dynamics. In the mathematical model, we observe a region of bistability where both the firm adhesion and detachment states can occur depending on the initial adhesion state. The differences are seen to be a result of mechanical cooperativity of integrins and cell deformation. Switching behaviour is a phenomenon associated with bistability in a stochastic system, and bistability in our deterministic mathematical model provides a potential physical explanation for the experimental results. Physiologically, bistability provides a means for transient mechanical stimuli to induce long-term changes in adhesion dynamics-and thereby the cells' ability to transmit force-and we propose further experiments for testing this hypothesis.

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

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

Bacillus subtilis Nucleoid-Associated Protein YlxR Is Involved in Bimodal Expression of the Fructoselysine Utilization Operon (frlBONMD-yurJ) Promoter

Bacteria must survive harsh environmental fluctuations at times and have evolved several strategies. “Collective” behaviors have been identified due to recent progress in single-cell analysis. Since most bacteria exist as single cells, bacterial populations are often considered clonal. However, accumulated evidence suggests this is not the case. Gene expression and protein expression are often not homogeneous, resulting in phenotypic heterogeneity. In extreme cases, this leads to bistability, the existence of two stable states. In many cases, expression of key master regulators is bimodal via positive feedback loops causing bimodal expression of the target genes. We observed bimodal expression of metabolic genes for alternative carbon sources. Expression profiles of the frlBONMD-yurJ operon driven by the frlB promoter (PfrlB), which encodes degradation enzymes and a transporter for amino sugars including fructoselysine, were investigated using transcriptional lacZ and gfp, and translational fluorescence reporter mCherry fusions. Disruption effects of genes encoding CodY, FrlR, RNaseY, and nucleoid-associated protein YlxR, four known regulatory factors for PfrlB, were examined for expression of each fusion construct. Expression of PfrlB-gfp and PfrlB-mCherry, which were located at amyE and its original locus, respectively, was bimodal; and disruption of ylxR resulted in the disappearance of the clear bimodal expression pattern in flow cytometric analyses. This suggested a role for YlxR on the bimodal expression of PfrlB. The data indicated that YlxR acted on the bimodal expression of PfrlB through both transcription and translation. YlxR regulates many genes, including those related to translation, supporting the above notion. Depletion of RNaseY abolished heterogenous expression of transcriptional PfrlB-gfp but not bimodal expression of translational PfrlB-mCherry, suggesting the role of RNaseY in regulation of the operon through mRNA stability control and regulatory mechanism for PfrlB-mCherry at the translational level. Based on these results, we discuss the meaning and possible cause of bimodal PfrlB expression.

Metabolic stress promotes stop-codon readthrough and phenotypic heterogeneity

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

An analog to digital converter controls bistable transfer competence development of a widespread bacterial integrative and conjugative element

Conjugative transfer of the integrative and conjugative element ICEclc in Pseudomonas requires development of a transfer competence state in stationary phase, which arises only in 3–5% of individual cells. The mechanisms controlling this bistable switch between non-active and transfer competent cells have long remained enigmatic. Using a variety of genetic tools and epistasis experiments in P. putida, we uncovered an ‘upstream’ cascade of three consecutive transcription factor-nodes, which controls transfer competence initiation. One of the uncovered transcription factors (named BisR) is representative for a new regulator family. Initiation activates a feedback loop, controlled by a second hitherto unrecognized heteromeric transcription factor named BisDC. Stochastic modelling and experimental data demonstrated the feedback loop to act as a scalable converter of unimodal (population-wide or ‘analog’) input to bistable (subpopulation-specific or ‘digital’) output. The feedback loop further enables prolonged production of BisDC, which ensures expression of the ‘downstream’ functions mediating ICE transfer competence in activated cells. Phylogenetic analyses showed that the ICEclc regulatory constellation with BisR and BisDC is widespread among Gamma- and Beta-proteobacteria, including various pathogenic strains, highlighting its evolutionary conservation and prime importance to control the behaviour of this wide family of conjugative elements.

Mobile DNA elements are pieces of genetic material that can jump from one bacterium to another, and even across species. They are often useful to their host, for example carrying genes that allow bacteria to resist antibiotics.

One example of bacterial mobile DNA is the ICEclc element. Usually, ICEclc sits passively within the bacterium’s own DNA, but in a small number of cells, it takes over, hijacking its host to multiply and to get transferred to other bacteria. Cells that can pass on the elements cannot divide, and so this ability is ultimately harmful to individual bacteria. Carrying ICEclc can therefore be positive for a bacterium but passing it on is not in the cell’s best interest. On the other hand, mobile DNAs like ICEclc have evolved to be disseminated as efficiently as possible. To shed more light on this tense relationship, Carraro et al. set out to identify the molecular mechanisms ICEclc deploys to control its host.

Experiments using mutant bacteria revealed that for ICEclc to successfully take over the cell, a number of proteins needed to be produced in the correct order. In particular, a protein called BisDC triggers a mechanism to make more of itself, creating a self-reinforcing ‘feedback loop’.

Mathematical simulations of the feedback loop showed that it could result in two potential outcomes for the cell. In most of the ‘virtual cells’, ICEclc ultimately remained passive; however, in a few, ICEclc managed to take over its hosts. In this case, the feedback loop ensured that there was always enough BisDC to maintain ICEclc’s control over the cell. Further analyses suggested that this feedback mechanism is also common in many other mobile DNA elements, including some that help bacteria to resist drugs.

These results are an important contribution to understand how mobile DNAs manipulate their bacterial host in order to propagate and disperse. In the future, this knowledge could help develop new strategies to combat the spread of antibiotic resistance.