Wide lag time distributions break a trade-off between reproduction and survival in bacteria

Microbial-mediated conversion of soil organic carbon co-regulates the evolution of antibiotic resistance

The influence of organic carbon on the proliferation of antibiotic resistance genes (ARGs) in the soil has been widely documented. However, it is unclear how soil organic carbon (SOC) interacts with the evolution of antibiotic resistance in bacteria. Here, we examined the variations in ARGs abundance during SOC mineralization and explored the microbiological mechanisms and key metabolic pathways involved in their coevolution. The results showed that the SOC mineralization rate was closely correlated with ARGs abundance (p < 0.05). High organic carbon (OC) mineralization was conducive to the occurrence of multidrug resistance genes. For example, multidrug_transporter and mexB increased 2.26 and 7.83 times from the initial level. The competitor (stress) evolutionary strategy model revealed that higher OC inputs drive environmental microorganisms to evolve from stress tolerant to high resistance and strong adaptation. Meta-genomic and transcriptomic analyses revealed that the conversion process of pyruvate to acetyl-CoA to acetate was the critical metabolic pathway for the co-regulation of antibiotic resistance. Gene deletion validation trials have demonstrated that the key functional genes (ackA and pta) involved in this process can modulate the development of vancomycin and multidrug resistance. This outcome provides a preliminary framework for microbial mechanisms that target the co-regulation of microbial OC conversion and the evolution of antibiotic resistance.

Impact of whole grain highland hull-less barley on the denaturing gradient gel electrophoresis profiles of gut microbial communities in rats fed high-fat diets

Polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) is a traditional non-culture technique that can provide a fingerprint of the microbial community. In the field of gut microbiota analysis, PCR-DGGE still holds potential for development. In the present study, we utilized an improved nested PCR-DGGE approach targeting the V3 region of 16S ribosomal DNA to investigate the impact of whole grain highland hull-less barley (WHLB), a cereal known for its significant hypocholesterolemic effect, on the gut microbiota profiles of high-fat diet rats. Seventy-two male Sprague-Dawley rats were divided into four groups and fed a normal control diet, a high-fat diet, or a high-fat diet supplemented with a low or high dose of WHLB for 4 or 8 weeks. The results revealed that the dominant bands varied among different dose groups and further changed with different treatment times. The compositions of bacterial communities in feces and cecal content were similar, but the dominant bacterial bands differed. After performing double DGGE, extracting the bands, sequencing the DNA, and aligning the sequences, a total of 19 bands were classified under the Firmicutes and Bacteroidetes phyla, while two bands were identified as unclassified uncultured bacteria. The relative abundance of Lactobacillus gasseri, Uncultured Prevotella sp., and Clostridium sp. increased following the administration of WHLB. Illumina-based sequencing was employed to assess the reliability of DGGE, demonstrating its reliability in analyzing the dominant taxonomic composition, although it may have limitations in accurately detecting the alpha diversity of bacterial species.

IMPORTANCE

While next-generation sequencing has overshadowed polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE), the latter still holds promise for advancing gut microbiota analysis due to its unique advantages. In this study, we used optimized nested PCR-DGGE to investigate the gut microbiota profile of high-fat diet rats after administering whole grain highland hull-less barley. High-throughput sequencing was employed to validate the DGGE results. Our results proved the reliability of PCR-DGGE for analyzing the dominant taxonomic composition while also providing visual evidence of a notable relationship between the composition of cecal and fecal microbial communities, highlighting substantial differences in both richness and abundance.

2-Stage microfermentations

Cell based factories can be engineered to produce a wide variety of products. Advances in DNA synthesis and genome editing have greatly simplified the design and construction of these factories. It has never been easier to generate hundreds or even thousands of cell factory strain variants for evaluation. These advances have amplified the need for standardized, higher throughput means of evaluating these designs. Toward this goal, we have previously reported the development of engineered E. coli strains and associated 2-stage production processes to simplify and standardize strain engineering, evaluation and scale up. This approach relies on decoupling growth (stage 1), from production, which occurs in stationary phase (stage 2). Phosphate depletion is used as the trigger to stop growth as well as induce heterologous expression. Here, we describe in detail the development of protocols for the evaluation of engineered E. coli strains in 2-stage microfermentations. These protocols are readily adaptable to the evaluation of strains producing a wide variety of protein as well as small molecule products. Additionally, by detailing the approach to protocol development, these methods are also adaptable to additional cellular hosts, as well as other 2-stage processes with various additional triggers.

Shaping of microbial phenotypes by trade-offs

Growth rate maximization is an important fitness strategy for microbes. However, the wide distribution of slow-growing oligotrophic microbes in ecosystems suggests that rapid growth is often not favored across ecological environments. In many circumstances, there exist trade-offs between growth and other important traits (e.g., adaptability and survival) due to physiological and proteome constraints. Investments on alternative traits could compromise growth rate and microbes need to adopt bet-hedging strategies to improve fitness in fluctuating environments. Here we review the mechanistic role of trade-offs in controlling bacterial growth and further highlight its ecological implications in driving the emergences of many important ecological phenomena such as co-existence, population heterogeneity and oligotrophic/copiotrophic lifestyles.

Rifampicin tolerance and growth fitness among isoniazid-resistant clinical Mycobacterium tuberculosis isolates: an in-vitro longitudinal study

Antibiotic tolerance in Mycobacterium tuberculosis leads to less effective bacterial killing, poor treatment responses and resistant emergence. Therefore, we investigated the rifampicin tolerance of M. tuberculosis isolates, with or without pre-existing isoniazid-resistance. We determined the in-vitro rifampicin survival fraction by minimum duration of killing assay in isoniazid susceptible (IS, n=119) and resistant (IR, n=84) M. tuberculosis isolates. Then we correlated the rifampicin tolerance with bacterial growth, rifampicin minimum inhibitory concentrations (MICs) and isoniazid-resistant mutations. The longitudinal IR isolates collected from patients were analyzed for changes in rifampicin tolerance and associated emergence of genetic variants. The median duration of rifampicin exposure reducing the M. tuberculosis surviving fraction by 90% (minimum duration of killing-MDK90) increased from 1.23 (95%CI 1.11; 1.37) and 1.31 (95%CI 1.14; 1.48) to 2.55 (95%CI 2.04; 2.97) and 1.98 (95%CI 1.69; 2.56) days, for IS and IR respectively, during 15 to 60 days of incubation. This indicated the presence of fast and slow growing tolerant sub-populations. A range of 6 log 10 -fold survival fraction enabled classification of tolerance as low, medium or high and revealed IR association with increased tolerance with faster growth (OR=2.68 for low vs. medium, OR=4.42 for low vs. high, P -trend=0.0003). The high tolerance in IR isolates was specific to those collected during rifampicin treatment in patients and associated with bacterial genetic microvariants. Furthermore, the high rifampicin tolerant IR isolates have survival potential similar to multi-drug resistant isolates. These findings suggest that IR tuberculosis needs to be evaluated for high rifampicin tolerance to improve treatment regimen and prevent the risk of MDR-TB emergence.

Asynchronous abundance fluctuations can drive giant genotype frequency fluctuations

Large stochastic population abundance fluctuations are ubiquitous across the tree of life1-7, impacting the predictability of population dynamics and influencing eco-evolutionary outcomes. It has generally been thought that these large abundance fluctuations do not strongly impact evolution (in contrast to genetic drift), as the relative frequencies of alleles in the population will be unaffected if the abundance of all alleles fluctuate in unison. However, we argue that large abundance fluctuations can lead to significant genotype frequency fluctuations if different genotypes within a population experience these fluctuations asynchronously. By serially diluting mixtures of two closely related E. coli strains, we show that such asynchrony can occur, leading to giant frequency fluctuations that far exceed expectations from models of genetic drift. We develop a flexible, effective model that explains the abundance fluctuations as arising from correlated offspring numbers between individuals, and the large frequency fluctuations result from even slight decoupling in offspring numbers between genotypes. This model accurately describes the observed abundance and frequency fluctuation scaling behaviors. Our findings suggest chaotic dynamics underpin these giant fluctuations, causing initially similar trajectories to diverge exponentially; subtle environmental changes can be magnified, leading to batch correlations in identical growth conditions. Furthermore, we present evidence that such decoupling noise is also present in mixed-genotype S. cerevisiae populations. We demonstrate that such decoupling noise can strongly influence evolutionary outcomes, in a manner distinct from genetic drift. Given the generic nature of asynchronous fluctuations, we anticipate they are widespread in biological populations, significantly affecting evolutionary and ecological dynamics.

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.

C-di-AMP levels modulate Staphylococcus aureus cell wall thickness, response to oxidative stress, and antibiotic resistance and tolerance

IMPORTANCE

Antibiotic resistance and tolerance are substantial healthcare-related problems, hampering effective treatment of bacterial infections. Mutations in the phosphodiesterase GdpP, which degrades cyclic di-3', 5'-adenosine monophosphate (c-di-AMP), have recently been associated with resistance to beta-lactam antibiotics in clinical Staphylococcus aureus isolates. In this study, we show that high c-di-AMP levels decreased the cell size and increased the cell wall thickness in S. aureus mutant strains. As a consequence, an increase in resistance to cell wall targeting antibiotics, such as oxacillin and fosfomycin as well as in tolerance to ceftaroline, a cephalosporine used to treat methicillin-resistant S. aureus infections, was observed. These findings underline the importance of investigating the role of c-di-AMP in the development of tolerance and resistance to antibiotics in order to optimize treatment in the clinical setting.

First-passage-time statistics of growing microbial populations carry an imprint of initial conditions

In exponential population growth, variability in the timing of individual division events and environmental factors (including stochastic inoculation) compound to produce variable growth trajectories. In several stochastic models of exponential growth we show power-law relationships that relate variability in the time required to reach a threshold population size to growth rate and inoculum size. Population-growth experiments in E. coli and S. aureus with inoculum sizes ranging between 1 and 100 are consistent with these relationships. We quantify how noise accumulates over time, finding that it encodes-and can be used to deduce-information about the early growth rate of a population.

Minorities drive growth resumption in cross-feeding microbial communities

Microbial communities are fundamental to life on Earth. Different strains within these communities are often connected by a highly connected metabolic network, where the growth of one strain depends on the metabolic activities of other community members. While distributed metabolic functions allow microbes to reduce costs and optimize metabolic pathways, they make them metabolically dependent. Here, we hypothesize that such dependencies can be detrimental in situations where the external conditions change rapidly, as they often do in natural environments. After a shift in external conditions, microbes need to remodel their metabolism, but they can only resume growth once partners on which they depend have also adapted to the new conditions. It is currently not well understood how microbial communities resolve this dilemma and how metabolic interactions are reestablished after an environmental shift. To address this question, we investigated the dynamical responses to environmental perturbation by microbial consortia with distributed anabolic functions. By measuring the regrowth times at the single-cell level in spatially structured communities, we found that metabolic dependencies lead to a growth delay after an environmental shift. However, a minority of cells-those in the immediate neighborhood of their metabolic partners-can regrow quickly and come to numerically dominate the community after the shift. The spatial arrangement of a microbial community is thus a key factor in determining the communities' ability to maintain metabolic interactions and growth in fluctuating conditions. Our results suggest that environmental fluctuations can limit the emergence of metabolic dependencies between microorganisms.

Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs

RNA polymerase (RNAP) is emblematic of complex biological systems that control multiple traits involving trade-offs such as growth versus maintenance. Laboratory evolution has revealed that mutations in RNAP subunits, including RpoB, are frequently selected. However, we lack a systems view of how mutations alter the RNAP molecular functions to promote adaptation. We, therefore, measured the fitness of thousands of mutations within a region of rpoB under multiple conditions and genetic backgrounds, to find that adaptive mutations cluster in two modules. Mutations in one module favor growth over maintenance through a partial loss of an interaction associated with faster elongation. Mutations in the other favor maintenance over growth through a destabilized RNAP-DNA complex. The two molecular handles capture the versatile RNAP-mediated adaptations. Combining both interaction losses simultaneously improved maintenance and growth, challenging the idea that growth-maintenance tradeoff resorts only from limited resources, and revealing how compensatory evolution operates within RNAP.

Pleiotropic hubs drive bacterial surface competition through parallel changes in colony composition and expansion

Bacteria commonly adhere to surfaces where they compete for both space and resources. Despite the importance of surface growth, it remains largely elusive how bacteria evolve on surfaces. We previously performed an evolution experiment where we evolved distinct Bacilli populations under a selective regime that favored colony spreading. In just a few weeks, colonies of Bacillus subtilis showed strongly advanced expansion rates, increasing their radius 2.5-fold relative to that of the ancestor. Here, we investigate what drives their rapid evolution by performing a uniquely detailed analysis of the evolutionary changes in colony development. We find mutations in diverse global regulators, RicT, RNAse Y, and LexA, with strikingly similar pleiotropic effects: They lower the rate of sporulation and simultaneously facilitate colony expansion by either reducing extracellular polysaccharide production or by promoting filamentous growth. Combining both high-throughput flow cytometry and gene expression profiling, we show that regulatory mutations lead to highly reproducible and parallel changes in global gene expression, affecting approximately 45% of all genes. This parallelism results from the coordinated manner by which regulators change activity both during colony development-in the transition from vegetative growth to dormancy-and over evolutionary time. This coordinated activity can however also break down, leading to evolutionary divergence. Altogether, we show how global regulators function as major pleiotropic hubs that drive rapid surface adaptation by mediating parallel changes in both colony composition and expansion, thereby massively reshaping gene expression.

Predictive Population Dynamics of Escherichia coli O157:H7 and Salmonella enterica on Plants: a Mechanistic Mathematical Model Based on Weather Parameters and Bacterial State

Weather affects key aspects of bacterial behavior on plants but has not been extensively investigated as a tool to assess risk of crop contamination with human foodborne pathogens. A novel mechanistic model informed by weather factors and bacterial state was developed to predict population dynamics on leafy vegetables and tested against published data tracking Escherichia coli O157:H7 (EcO157) and Salmonella enterica populations on lettuce and cilantro plants. The model utilizes temperature, radiation, and dew point depression to characterize pathogen growth and decay rates. Additionally, the model incorporates the population level effect of bacterial physiological state dynamics in the phyllosphere in terms of the duration and frequency of specific weather parameters. The model accurately predicted EcO157 and S. enterica population sizes on lettuce and cilantro leaves in the laboratory under various conditions of temperature, relative humidity, light intensity, and cycles of leaf wetness and dryness. Importantly, the model successfully predicted EcO157 population dynamics on 4-week-old romaine lettuce plants under variable weather conditions in nearly all field trials. Prediction of initial EcO157 population decay rates after inoculation of 6-week-old romaine plants in the same field study was better than that of long-term survival. This suggests that future augmentation of the model should consider plant age and species morphology by including additional physical parameters. Our results highlight the potential of a comprehensive weather-based model in predicting contamination risk in the field. Such a modeling approach would additionally be valuable for timing field sampling in quality control to ensure the microbial safety of produce. IMPORTANCE Fruits and vegetables are important sources of foodborne disease. Novel approaches to improve the microbial safety of produce are greatly lacking. Given that bacterial behavior on plant surfaces is highly dependent on weather factors, risk assessment informed by meteorological data may be an effective tool to integrate into strategies to prevent crop contamination. A mathematical model was developed to predict the population trends of pathogenic E. coli and S. enterica, two major causal agents of foodborne disease associated with produce, on leaves. Our model is based on weather parameters and rates of switching between the active (growing) and inactive (nongrowing) bacterial state resulting from prevailing environmental conditions on leaf surfaces. We demonstrate that the model has the ability to accurately predict dynamics of enteric pathogens on leaves and, notably, sizes of populations of pathogenic E. coli over time after inoculation onto the leaves of young lettuce plants in the field.

Tradeoff between lag time and growth rate drives the plasmid acquisition cost

Conjugative plasmids drive genetic diversity and evolution in microbial populations. Despite their prevalence, plasmids can impose long-term fitness costs on their hosts, altering population structure, growth dynamics, and evolutionary outcomes. In addition to long-term fitness costs, acquiring a new plasmid introduces an immediate, short-term perturbation to the cell. However, due to the transient nature of this plasmid acquisition cost, a quantitative understanding of its physiological manifestations, overall magnitudes, and population-level implications, remains unclear. To address this, here we track growth of single colonies immediately following plasmid acquisition. We find that plasmid acquisition costs are primarily driven by changes in lag time, rather than growth rate, for nearly 60 conditions covering diverse plasmids, selection environments, and clinical strains/species. Surprisingly, for a costly plasmid, clones exhibiting longer lag times also achieve faster recovery growth rates, suggesting an evolutionary tradeoff. Modeling and experiments demonstrate that this tradeoff leads to counterintuitive ecological dynamics, whereby intermediate-cost plasmids outcompete both their low and high-cost counterparts. These results suggest that, unlike fitness costs, plasmid acquisition dynamics are not uniformly driven by minimizing growth disadvantages. Moreover, a lag/growth tradeoff has clear implications in predicting the ecological outcomes and intervention strategies of bacteria undergoing conjugation.

An Isotope-Labeled Single-Cell Raman Spectroscopy Approach for Tracking the Physiological Evolution Trajectory of Bacteria toward Antibiotic Resistance

Understanding evolution of antibiotic resistance is vital for containing its global spread. Yet our ability to in situ track highly heterogeneous and dynamic evolution is very limited. Here, we present a new single-cell approach integrating D₂ O-labeled Raman spectroscopy, advanced multivariate analysis, and genotypic profiling to in situ track physiological evolution trajectory toward resistance. Physiological diversification of individual cells from isogenic population with cyclic ampicillin treatment is captured. Advanced multivariate analysis of spectral changes classifies all individual cells into four subsets of sensitive, intrinsic tolerant, evolved tolerant and resistant. Remarkably, their dynamic shifts with evolution are depicted and spectral markers of each state are identified. Genotypic analysis validates the phenotypic shift and provides insights into the underlying genetic basis. The new platform advances rapid phenotyping resistance evolution and guides evolution control.

Breaking down microbial hierarchies

Microbial communities that degrade natural polysaccharides are thought to have a hierarchical organization and one-way positive interactions from higher to lower trophic levels. Daniels et al. have recently shown that reciprocal interactions between trophic levels can occur and that these interactions change over the duration of a batch culture.

Resuscitation dynamics reveal persister partitioning after antibiotic treatment

Bacteria can survive antibiotics by forming dormant, drug-tolerant persisters. Persisters can resuscitate from dormancy after treatment and prolong infections. Resuscitation is thought to occur stochastically, but its transient, single-cell nature makes it difficult to investigate. We tracked the resuscitation of individual persisters by microscopy after ampicillin treatment and, by characterizing their dynamics, discovered that Escherichia coli and Salmonella enterica persisters resuscitate exponentially rather than stochastically. We demonstrated that the key parameters controlling resuscitation map to the ampicillin concentration during treatment and efflux during resuscitation. Consistently, we observed many persister progeny have structural defects and transcriptional responses indicative of cellular damage, for both β-lactam and quinolone antibiotics. During resuscitation, damaged persisters partition unevenly, generating both healthy daughter cells and defective ones. This persister partitioning phenomenon was observed in S. enterica, Klebsiella pneumoniae, Pseudomonas aeruginosa, and an E. coli urinary tract infection (UTI) isolate. It was also observed in the standard persister assay and after in situ treatment of a clinical UTI sample. This study reveals novel properties of resuscitation and indicates that persister partitioning may be a survival strategy in bacteria that lack genetic resistance.

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.

Community interactions drive the evolution of antibiotic tolerance in bacteria

The emergence of antibiotic tolerance (prolonged survival against exposure) in natural bacterial populations is a major concern. Since it has been studied primarily in isogenic populations, we do not yet understand how ecological interactions in a diverse community impact the evolution of tolerance. To address this, we studied the evolutionary dynamics of a synthetic bacterial community composed of two interacting strains. In this community, an antibiotic-resistant strain protected the other, susceptible strain by degrading the antibiotic ampicillin in the medium. Surprisingly, we found that in the presence of antibiotics, the susceptible strain evolved tolerance. Tolerance was typified by an increase in survival as well as an accompanying decrease in the growth rate, highlighting a trade-off between the two. A simple mathematical model explained that the observed decrease in the death rate, even when coupled with a decreased growth rate, is beneficial in a community with weak protective interactions. In the presence of strong interactions, the model predicted that the trade-off would instead be detrimental, and tolerance would not emerge, which we experimentally verified. By whole genome sequencing the evolved tolerant isolates, we identified two genetic hot spots which accumulated mutations in parallel lines, suggesting their association with tolerance. Our work highlights that ecological interactions can promote antibiotic tolerance in bacterial communities, which has remained understudied.

Understanding cellular growth strategies via optimal control

Evolutionary prediction and control are increasingly interesting research topics that are expanding to new areas of application. Unravelling and anticipating successful adaptations to different selection pressures becomes crucial when steering rapidly evolving cancer or microbial populations towards a chosen target. Here we introduce and apply a rich theoretical framework of optimal control to understand adaptive use of traits, which in turn allows eco-evolutionarily informed population control. Using adaptive metabolism and microbial experimental evolution as a case study, we show how demographic stochasticity alone can lead to lag time evolution, which appears as an emergent property in our model. We further show that the cycle length used in serial transfer experiments has practical importance as it may cause unintentional selection for specific growth strategies and lag times. Finally, we show how frequency-dependent selection can be incorporated to the state-dependent optimal control framework allowing the modelling of complex eco-evolutionary dynamics. Our study demonstrates the utility of optimal control theory in elucidating organismal adaptations and the intrinsic decision making of cellular communities with high adaptive potential.

Navigating Environmental Transitions: the Role of Phenotypic Variation in Bacterial Responses

The ability of bacteria to respond to changes in their environment is critical to their survival, allowing them to withstand stress, form complex communities, and induce virulence responses during host infection. A remarkable feature of many of these bacterial responses is that they are often variable across individual cells, despite occurring in an isogenic population exposed to a homogeneous environmental change, a phenomenon known as phenotypic heterogeneity. Phenotypic heterogeneity can enable bet-hedging or division of labor strategies that allow bacteria to survive fluctuating conditions. Investigating the significance of phenotypic heterogeneity in environmental transitions requires dynamic, single-cell data. Technical advances in quantitative single-cell measurements, imaging, and microfluidics have led to a surge of publications on this topic. Here, we review recent discoveries on single-cell bacterial responses to environmental transitions of various origins and complexities, from simple diauxic shifts to community behaviors in biofilm formation to virulence regulation during infection. We describe how these studies firmly establish that this form of heterogeneity is prevalent and a conserved mechanism by which bacteria cope with fluctuating conditions. We end with an outline of current challenges and future directions for the field. While it remains challenging to predict how an individual bacterium will respond to a given environmental input, we anticipate that capturing the dynamics of the process will begin to resolve this and facilitate rational perturbation of environmental responses for therapeutic and bioengineering purposes.

NtrC Increases Fitness of Salmonella enterica Serovar Typhimurium under Low and Fluctuating Nutrient Conditions

Enteric pathogens cycle between nutrient-rich host and nutrient-poor external environment. These pathogens compete for nutrients while cycling between host and external environment, and often experience starvation. In this context, we have studied the role of a global regulator (NtrC) of Salmonella Typhimurium. The ntrC knockout mutation caused extended lag phase (8 h) and slow growth in the minimal medium. In lag phase, the wild-type cells showed ~60-fold more expression of ntrC gene. Gene expression studies and biochemical assays showed that the extended lag phase and slow growth is due to slow metabolism, instead of nitrogen transport. Further, we observed that ntrC knockout mutation led extended lag phase and slow growth, made ΔntrC mutant unable to compete with wild-type S. Typhimurium in both static and fluctuating nutrient condition. In addition to this, ΔntrC knockout mutant was unable to survive long-term nitrogen starvation (150 days). The nutrient recycling assays and gene expression studies revealed that ntrC gene is essential for rapid recycling of nutrients from the dead cells. Moreover, in the absence of ntrC gene, magnesium limits the nutrient recycling efficiency of S. Typhimurium. Therefore, the ntrC gene, which is often studied with respect to nitrogen scavenging in a low nitrogen growing condition, is required even in the adequate supply of nitrogen to maintain optimal growth and fast exit from the lag phase. Hence, we conclude that, the ntrC expression is essential for competitive fitness of S. Typhimurium under the low and fluctuating nutrient condition. IMPORTANCE S. Typhimurium, both in host and external environment, faces enormous competition from other microorganisms. The competition may take place either in static or in fluctuating nutrient conditions. Thus, how S. Typhimurium survives under such overlapping stress conditions remained unclear. Therefore, using S. Typhimurium as model organism we report that a global regulator NtrC, found in enteric bacteria like Escherichia coli and Salmonella, activates the set of genes and operons involved in rapid adaptation and efficient nutrient recycling/scavenging. These properties enable cells to compete with other microbes under the characteristic feast-or-famine lifestyle of S. Typhimurium. Therefore, this work helps us to understand the starvation physiology of the enteric bacterial pathogen S. Typhimurium.

Recent functional insights into the magic role of (p)ppGpp in growth control

Rapid growth and survival are two key traits that enable bacterial cells to thrive in their natural habitat. The guanosine tetraphosphate and pentaphosphate [(p)ppGpp], also known as "magic spot", is a key second messenger inside bacterial cells as well as chloroplasts of plants and green algae. (p)ppGpp not only controls various stages of central dogma processes (replication, transcription, ribosome maturation and translation) and central metabolism but also regulates various physiological processes such as pathogenesis, persistence, motility and competence. Under extreme conditions such as nutrient starvation, (p)ppGpp-mediated stringent response is crucial for the survival of bacterial cells. This mini-review highlights some of the very recent progress on the key role of (p)ppGpp in bacterial growth control in light of cellular resource allocation and cell size regulation. We also briefly discuss some recent functional insights into the role of (p)ppGpp in plants and green algae from the angle of growth and development and further discuss several important open directions for future studies.

How bacteria navigate varying environments

Collective sensing and phenotypic diversification aid response to environmental fluctuations

Microfluidic dose-response platform to track the dynamics of drug response in single mycobacterial cells

Preclinical analysis of drug efficacy is critical for drug development. However, conventional bulk-cell assays statically assess the mean population behavior, lacking resolution on drug-escaping cells. Inaccurate estimation of efficacy can lead to overestimation of compounds, whose efficacy will not be confirmed in the clinic, or lead to rejection of valuable candidates. Time-lapse microfluidic microscopy is a powerful approach to characterize drugs at high spatiotemporal resolution, but hard to apply on a large scale. Here we report the development of a microfluidic platform based on a pneumatic operating principle, which is scalable and compatible with long-term live-cell imaging and with simultaneous analysis of different drug concentrations. We tested the platform with mycobacterial cells, including the tubercular pathogen, providing the first proof of concept of a single-cell dose-response assay. This dynamic in-vitro model will prove useful to probe the fate of drug-stressed cells, providing improved predictions of drug efficacy in the clinic.

A leader cell triggers end of lag phase in populations of Pseudomonas fluorescens

The relationship between the number of cells colonizing a new environment and time for resumption of growth is a subject of long-standing interest. In microbiology this is known as the "inoculum effect." Its mechanistic basis is unclear with possible explanations ranging from the independent actions of individual cells, to collective actions of populations of cells. Here, we use a millifluidic droplet device in which the growth dynamics of hundreds of populations founded by controlled numbers of Pseudomonas fluorescens cells, ranging from a single cell, to one thousand cells, were followed in real time. Our data show that lag phase decreases with inoculum size. The decrease of average lag time and its variance across droplets, as well as lag time distribution shapes, follow predictions of extreme value theory, where the inoculum lag time is determined by the minimum value sampled from the single-cell distribution. Our experimental results show that exit from lag phase depends on strong interactions among cells, consistent with a "leader cell" triggering end of lag phase for the entire population.

Noise in a Metabolic Pathway Leads to Persister Formation in Mycobacterium tuberculosis

Tuberculosis is difficult to treat due to dormant cells formed in response to immune stress and stochastically formed persisters, both of which are tolerant of antibiotics. Bactericidal antibiotics kill by corrupting their energy-dependent targets. We reasoned that stochastic variation, or noise, in the expression of an energy-generating component will produce rare persister cells. In sorted M. tuberculosis cells grown on acetate, there is considerable cell-to-cell variation in the level of mRNA coding for AckA, the acetate kinase. Quenching the noise by overexpressing ackA sharply decreases persisters, showing that it acts as the main persister gene under these conditions. This demonstrates that a low energy mechanism is responsible for the formation of M. tuberculosis persisters. Entrance into a low-energy state driven by noise in expression of energy-producing enzymes is likely a general mechanism by which bacteria produce persisters. IMPORTANCE M. tuberculosis infection requires the administration of multiple antibiotics for a prolonged period of time. Treatment difficulty is generally attributed to M. tuberculosis entrance into a nonreplicative, antibiotic-tolerant state. M. tuberculosis enters this nonreplicative state in response to immune stress. However, a small population of cells enter a nonreplicative, multidrug-tolerant state under normal growth conditions, absent any stress. These cells are termed persisters. The mechanisms by which persisters enter a nonreplicative state are largely unknown. Here, we show that, as with other bacteria, M. tuberculosis persisters are low-energy cells formed stochastically during normal growth. Additionally, we identify the natural variation in the expression of energy producing genes as a source of the stochastic entrance of M. tuberculosis into the low-energy persister state. These findings have important implications for understanding the heterogeneous nature of M. tuberculosis infection and will aid in designing better treatment regimens against this important human pathogen.

Hidden paths to endless forms most wonderful: ecology latently shapes evolution of multicellular development in predatory bacteria

Ecological causes of developmental evolution, for example from predation, remain much investigated, but the potential importance of latent phenotypes in eco-evo-devo has received little attention. Using the predatory bacterium Myxococcus xanthus, which undergoes aggregative fruiting body development upon starvation, we tested whether adaptation to distinct growth environments that do not induce development latently alters developmental phenotypes under starvation conditions that do induce development. In an evolution experiment named MyxoEE-3, growing M. xanthus populations swarmed across agar surfaces while adapting to conditions varying at factors such as surface stiffness or prey identity. Such ecological variation during growth was found to greatly impact the latent evolution of development, including fruiting body morphology, the degree of morphological trait correlation, reaction norms, degrees of developmental plasticity and stochastic diversification. For example, some prey environments promoted retention of developmental proficiency whereas others led to its systematic loss. Our results have implications for understanding evolutionary interactions among predation, development and motility in myxobacterial life cycles, and, more broadly, how ecology can profoundly shape the evolution of developmental systems latently rather than by direct selection on developmental features.

Harnessing plant-microbiome interactions for bioremediation across a freshwater urbanization gradient

Urbanization impacts land, air, and water, creating environmental gradients between cities and rural areas. Urban stormwater delivers myriad co-occurring, understudied, and mostly unregulated contaminants to aquatic ecosystems, causing a pollution gradient. Recipient ecosystems host interacting species that can affect each others' growth and responses to these contaminants. For example, plants and their microbiomes often reciprocally increase growth and contaminant tolerance. Here, we identified ecological variables affecting contaminant fate across an urban-rural gradient using 50 sources of the aquatic plant Lemna minor (duckweed) and associated microbes, and two co-occurring winter contaminants of temperate cities, benzotriazole and salt. We conducted experiments totalling >2,500 independent host-microbe-contaminant microcosms. Benzotriazole and salt negatively affected duckweed growth, but not microbial growth, and duckweeds maintained faster growth with their local, rather than disrupted, microbiota. Benzotriazole transformation products of plant, microbial, and phototransformation pathways were linked to duckweed and microbial growth, and were affected by salt co-contamination, microbiome disruption, and source sites of duckweeds and microbes. Duckweeds from urban sites grew faster and enhanced phytotransformation, but supported less total transformation of benzotriazole. Increasing microbial community diversity correlated with greater removal of benzotriazole, but taxonomic groups may explain shifts across transformation pathways: the genus Aeromonas was linked to increasing phototransformation. Because benzotriazole toxicity could depend on amount and type of in situ transformation, this variation across duckweeds and microbes could be harnessed for better management of urban stormwater. Broadly, our results demonstrate that plant-microbiome interactions harbour manipulable variation for bioremediation applications.

Evolutionary stability is sensitive on the conflict between reproduction and survival: proofs

Evolutionary game theory is a powerful mathematical framework to study how phenotypes evolve by natural selection. Both birth and death are key in classic models in evolutionary games. The conflict between the two is fundamental in life history theory. The conflict between birth and death has been shown to change the evolutionary outcome for continuous traits. However, it is not clear how the conflict reshapes the evolutionary outcome for discrete strategies. An allocation model is proposed, in which part of the payoff is mapped to reproduction and the rest is mapped to illness. For non-evolving allocation, it is proved that the allocation does not change the fixation probability if and only if the illness is an inverse exponential function and the product of reproduction function and illness function is a constant. The necessary and sufficient condition implies that the allocation dramatically alters the evolutionary stability for a wide class of evolutionary processes. This is also verified by alternative construction proofs and numerical examples. Furthermore, the illness and reproduction function also ensures that every allocation is a neutral stable regime, if the allocation evolves to maximize the invasion probability. A deviation can lead to a non-trivial evolutionary branching. These results explicitly show that the reproduction and illness functions are restrictive to ensure the invariance of evolutionary outcome. Thus it implies that the demographic and life history need to be considered together to understand patterns of evolutionary dynamics.

Formulation of Chemically Defined Media and Growth Evaluation of Ligilactobacillus salivarius ZJ614 and Limosilactobacillus reuteri ZJ625

Lactic acid bacteria are increasingly becoming important dietary supplements due to their health benefits when consumed in adequate quantity. The increasing attention on these important microbes has necessitated an in-depth understanding of their physiological processes, such as nutritional requirements and growth patterns, to better harness their probiotic potentials. This study was carried out to determine the nutritional requirements for the growth of L. salivarius ZJ614 and L. reuteri ZJ625 from a chemically defined medium and evaluate growth kinetics by fitting different sigmoidal growth models. The complete CDM contains 49 nutritional ingredients such as glucose, Tween 80^®, mineral salts, buffers, amino acids, vitamins, and nucleotides at defined concentrations. In addition, the minimal nutritional requirements of the isolates were determined in a series of single-omission experiments (SOEs) to compose the MDM. Growth curve data were generated by culturing in an automated 96-well micro-plate reader at 37°C for 36 h, and photometric readings (optical density: OD₆₀₀) were taken. The data were summarized in tables and charts using Microsoft Excel, while growth evaluation was carried out using open-source software (Curveball) on Python. The results revealed that omission of the amino acids, vitamins, and nucleotides groups resulted in 2.0, 20.17, and 60.24% (for L. salivarius ZJ614) and 0.95, 42.7, and 70.5% (for L. reuteri ZJ625) relative growths, respectively. Elimination of the individual CDM components also indicates varying levels of growth by the strains. The growth curve data revealed LogisticLag2 and Baranyi–Roberts models as the best fits for L. reuteri ZJ625 and L. salivarius ZJ614, respectively. All the strains showed appreciable growth on the CDM and MDM as observed in de Man–Rogosa–Sharpe (MRS) broth. We also described the growth kinetics of L. reuteri ZJ625 and L. salivarius ZJ614 in the CDM, and the best models revealed the estimated growth parameters.

Distinct Survival, Growth Lag, and rRNA Degradation Kinetics during Long-Term Starvation for Carbon or Phosphate

The stationary phase is the general term for the state a bacterial culture reaches when no further increase in cell mass occurs due to exhaustion of nutrients in the growth medium. Depending on the type of nutrient that is first depleted, the metabolic state of the stationary phase cells may vary greatly, and the subsistence strategies that best support cell survival may differ. As ribosomes play a central role in bacterial growth and energy expenditure, ribosome preservation is a key element of such strategies. To investigate the degree of ribosome preservation during long-term starvation, we compared the dynamics of rRNA levels of carbon-starved and phosphorus-starved Escherichia coli cultures for up to 28 days. The starved cultures' contents of full-length 16S and 23S rRNA decreased as the starvation proceeded in both cases, and phosphorus starvation resulted in much more rapid rRNA degradation than carbon starvation. Bacterial survival and regrowth kinetics were also quantified. Upon replenishment of the nutrient in question, carbon-starved cells resumed growth faster than cells starved for phosphate for the equivalent amount of time, and for both conditions, the lag time increased with the starvation time. While these results are in accordance with the hypothesis that cells with a larger ribosome pool recover more readily upon replenishment of nutrients, we also observed that the lag time kept increasing with increasing starvation time, also when the amount of rRNA per viable cell remained constant, highlighting that lag time is not a simple function of ribosome content under long-term starvation conditions. IMPORTANCE The exponential growth of bacterial populations is punctuated by long or short periods of starvation lasting from the point of nutrient exhaustion until nutrients are replenished. To understand the consequences of long-term starvation for Escherichia coli cells, we performed month-long carbon and phosphorus starvation experiments and measured three key phenotypes of the cultures, namely, the survival of the cells, the time needed for them to resume growth after nutrient replenishment, and the levels of intact rRNA preserved in the cultures. The starved cultures' concentration of rRNA dropped with starvation time, as did cell survival, while the lag time needed for regrowth increased. While all three phenotypes were more severely affected during starvation for phosphorus than for carbon, our results demonstrate that neither survival nor lag time is correlated with ribosome content in a straightforward manner.

Photothermal Therapy may be a Double-edge Sword by Inducing the Formation of Bacterial Antibiotic Tolerance

Photothermal nanoparticles are thought to be the most potential candidates against infectious disease, by disrupting cell membrane and inhibiting metabolism. However, subpopulation survived with this low-activity state may be endowed...

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

Modeling host-associating microbes under selection

The concept of fitness is often reduced to a single component, such as the replication rate in a given habitat. For species with multi-step life cycles, this can be an unjustified oversimplification, as every step of the life cycle can contribute to the overall reproductive success in a specific way. In particular, this applies to microbes that spend part of their life cycles associated to a host. In this case, there is a selection pressure not only on the replication rates, but also on the phenotypic traits associated to migrating from the external environment to the host and vice-versa (i.e., the migration rates). Here, we investigate a simple model of a microbial lineage living, replicating, migrating and competing in and between two compartments: a host and an environment. We perform a sensitivity analysis on the overall growth rate to determine the selection gradient experienced by the microbial lineage. We focus on the direction of selection at each point of the phenotypic space, defining an optimal way for the microbial lineage to increase its fitness. We show that microbes can adapt to the two-compartment life cycle through either changes in replication or migration rates, depending on the initial values of the traits, the initial distribution across the two compartments, the intensity of competition, and the time scales involved in the life cycle versus the time scale of adaptation (which determines the adequate probing time to measure fitness). Overall, our model provides a conceptual framework to study the selection on microbes experiencing a host-associated life cycle.

Suboptimal resource allocation in changing environments constrains response and growth in bacteria

To respond to fluctuating conditions, microbes typically need to synthesize novel proteins. As this synthesis relies on sufficient biosynthetic precursors, microbes must devise effective response strategies to manage depleting precursors. To better understand these strategies, we investigate the active response of Escherichia coli to changes in nutrient conditions, connecting transient gene expression to growth phenotypes. By synthetically modifying gene expression during changing conditions, we show how the competition by genes for the limited protein synthesis capacity constrains cellular response. Despite this constraint cells substantially express genes that are not required, trapping them in states where precursor levels are low and the genes needed to replenish the precursors are outcompeted. Contrary to common modeling assumptions, our findings highlight that cells do not optimize growth under changing environments but rather exhibit hardwired response strategies that may have evolved to promote fitness in their native environment. The constraint and the suboptimality of the cellular response uncovered provide a conceptual framework relevant for many research applications, from the prediction of evolution to the improvement of gene circuits in biotechnology.

Evolutionary trade-offs between growth and survival: The delicate balance between reproductive success and longevity in bacteria

All living cells strive to allocate cellular resources in a way that promotes maximal evolutionary fitness. While there are many competing demands for resources the main decision making process centres on whether to proceed with growth and reproduction or to "hunker down" and invest in protection and survival (or to strike an optimal balance between these two processes). The transcriptional programme active at any given time largely determines which of these competing processes is dominant. At the top of the regulatory hierarchy are the sigma factors that commandeer the transcriptional machinery and determine which set of promoters are active at any given time. The regulatory inputs controlling their activity are therefore often highly complex, with multiple layers of regulation, allowing relevant environmental information to produce the most beneficial response. The tension between growth and survival is also evident in the developmental programme necessary to promote biofilm formation, which is typically associated with low growth rates and enhanced long-term survival. Nucleotide second messengers and energy pools (ATP/ADP levels) play critical roles in determining the fate of individual cells. Regulatory small RNAs frequently play important roles in the decision making processes too. In this review we discuss the trade-off that exists between reproduction and persistence in bacteria and discuss some of the recent advances in this fascinating field.

Observation of universal ageing dynamics in antibiotic persistence

Stress responses allow cells to adapt to changes in external conditions by activating specific pathways¹. Here we investigate the dynamics of single cells that were subjected to acute stress that is too strong for a regulated response but not lethal. We show that when the growth of bacteria is arrested by acute transient exposure to strong inhibitors, the statistics of their regrowth dynamics can be predicted by a model for the cellular network that ignores most of the details of the underlying molecular interactions. We observed that the same stress, applied either abruptly or gradually, can lead to totally different recovery dynamics. By measuring the regrowth dynamics after stress exposure on thousands of cells, we show that the model can predict the outcome of antibiotic persistence measurements. Our results may account for the ubiquitous antibiotic persistence phenotype², as well as for the difficulty in attempts to link it to specific genes³. More generally, our approach suggests that two different cellular states can be observed under stress: a regulated state, which prepares cells for fast recovery, and a disrupted cellular state due to acute stress, with slow and heterogeneous recovery dynamics. The disrupted state may be described by general properties of large random networks rather than by specific pathway activation. Better understanding of the disrupted state could shed new light on the survival and evolution of cells under stress.

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.

Microbial effects on plant phenology and fitness

Plant development and the timing of developmental events (phenology) are tightly coupled with plant fitness. A variety of internal and external factors determine the timing and fitness consequences of these life-history transitions. Microbes interact with plants throughout their life history and impact host phenology. This review summarizes current mechanistic and theoretical knowledge surrounding microbe-driven changes in plant phenology. Overall, there are examples of microbes impacting every phenological transition. While most studies have focused on flowering time, microbial effects remain important for host survival and fitness across all phenological phases. Microbe-mediated changes in nutrient acquisition and phytohormone signaling can release plants from stressful conditions and alter plant stress responses inducing shifts in developmental events. The frequency and direction of phenological effects appear to be partly determined by the lifestyle and the underlying nature of a plant-microbe interaction (i.e., mutualistic or pathogenic), in addition to the taxonomic group of the microbe (fungi vs. bacteria). Finally, we highlight biases, gaps in knowledge, and future directions. This biotic source of plasticity for plant adaptation will serve an important role in sustaining plant biodiversity and managing agriculture under the pressures of climate change.

Contribution of single-cell omics to microbial ecology

Micro-organisms play key roles in various ecosystems, but many of their functions and interactions remain undefined. To investigate the ecological relevance of microbial communities, new molecular tools are being developed. Among them, single-cell omics assessing genetic diversity at the population and community levels and linking each individual cell to its functions is gaining interest in microbial ecology. By giving access to a wider range of ecological scales (from individual to community) than culture-based approaches and meta-omics, single-cell omics can contribute not only to micro-organisms' genomic and functional identification but also to the testing of concepts in ecology. Here, we discuss the contribution of single-cell omics to possible breakthroughs in concepts and knowledge on microbial ecosystems and ecoevolutionary processes.

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.

Microbiota-derived metabolites inhibit Salmonella virulent subpopulation development by acting on single-cell behaviors

Salmonella spp. express Salmonella pathogenicity island 1 Type III Secretion System 1 (T3SS-1) genes to mediate the initial phase of interaction with their host. Prior studies indicate short-chain fatty acids, microbial metabolites at high concentrations in the gastrointestinal tract, limit population-level T3SS-1 gene expression. However, only a subset of Salmonella cells in a population express these genes, suggesting short-chain fatty acids could decrease T3SS-1 population-level expression by acting on per-cell expression or the proportion of expressing cells. Here, we combine single-cell, theoretical, and molecular approaches to address the effect of short-chain fatty acids on T3SS-1 expression. Our in vitro results show short-chain fatty acids do not repress T3SS-1 expression by individual cells. Rather, these compounds act to selectively slow the growth of T3SS-1-expressing cells, ultimately decreasing their frequency in the population. Further experiments indicate slowed growth arises from short-chain fatty acid-mediated depletion of the proton motive force. By influencing the T3SS-1 cell-type proportions, our findings imply gut microbial metabolites act on cooperation between the two cell types and ultimately influence Salmonella's capacity to establish within a host.

Visualization and Quantification of Genetically Adapted Microbial Cells During Preculture

As culture history is known to affect the length of the lag phase and microbial cell growth, precultures are often grown in the same medium as the main culture for physiological adaptation and to reduce a prolonged lag time in some microbial cells. To understand the adaptation process of microbial cells during transfer from Luria-Bertani medium to minimal medium, we used the growth of Escherichia coli BL21(DE3) in succinate minimal medium as a model system. We observed that only one or two sequential transfers from minimal medium to fresh minimal medium accelerated the growth rate of BL21(DE3) cells. In addition, the number of large colonies (diameter ≥0.1 cm) on succinate agar increased with the number of transfers. Genome and transcript analyses showed that the C-to-T point mutation in large colony cells converted the inactive promoter of kgtP (known to encode α-ketoglutarate permease) to the active form, allowing efficient uptake of exogenous succinate. Moreover, we visualized the occurrence of genetically adapted cells with better fitness in real time and quantified the number of those cells in the microbial population during transfer to the same medium. Fluorescence microscopy showed the occurrence and increase of adapted mutant cells, which contain intracellular KgtP-fused green fluorescent proteins, as a result of the C-to-T mutation in the promoter of a fused kgtP-sfgfp during transfer to fresh medium. Flow cytometry revealed that the proportion of mutant cells increased from 1.75% (first transfer) to 12.16% (second transfer) and finally 70.79% (third transfer), explaining the shortened lag time and accelerated growth rate of BL21(DE3) cells during adaptation to the minimal medium. This study provides new insights into the genetic heterogeneity of microbial populations that aids microbial adaptability in new environments.

Multi-stable bacterial communities exhibit extreme sensitivity to initial conditions

Microbial communities can have dramatically different compositions even among similar environments. This might be due to the existence of multiple alternative stable states, yet there exists little experimental evidence supporting this possibility. Here, we gathered a large collection of absolute population abundances capturing population dynamics in one- to four-strain communities of soil bacteria with a complex life cycle in a feast-or-famine environment. This dataset led to several observations: (i) some pairwise competitions resulted in bistability with a separatrix near a 1:1 initial ratio across a range of population densities; (ii) bistability propagated to multi-stability in multispecies communities; and (iii) replicate microbial communities reached different stable states when starting close to initial conditions separating basins of attraction, indicating finite-sized regions where the dynamics are unpredictable. The generalized Lotka-Volterra equations qualitatively captured most competition outcomes but were unable to quantitatively recapitulate the observed dynamics. This was partly due to complex and diverse growth dynamics in monocultures that ranged from Allee effects to nonmonotonic behaviors. Overall, our results highlight that multi-stability might be generic in multispecies communities and, combined with ecological noise, can lead to unpredictable community assembly, even in simple environments.

Stress responses across the scales of life: Towards a universal theory of biological stress

Although biological systems are more complex and can actively respond to their environment, an effective entry point to the development of a universal theory of biological stress are the physical concepts of stress and strain. If you apply stress to the end of a beam of steel, strain will accumulate within that steel beam. If the stress is weak, that strain will disappear when the force is removed and the beam will return to its original state of form and functionality. If the stress is more severe, the strain becomes permanent and the beam will be deformed, potentially losing some degree of functionality. In extremely stressful situations, the beam will break and lose most or all of its original functional capabilities. Although this stress-strain theory applies to the abiotic, stress and strain are also rules of life and directly relate to the form and function of living organisms. The main difference is that life can react and adjust to stress and strain to maintain homeostasis within a range of limits. Here, we summarize the rules of stress and strain in living systems ranging from microbes to multicellular organisms to ecosystems with the goal of identifying common features that may underlie a universal biological theory of stress. We then propose to establish a range of experimental, observational, and analytical approaches to study stress across scales, including synthetic microbial communities that mimic many of the essential characteristics of living systems, thereby enabling a universal theory of biological stress to be experimentally validated without the constraints of timescales, ethics, or cost found when studying other species or scales of life. Although the range of terminology, theory, and methodology used to study stress and strain across the scales of life presents a formidable challenge to creating a universal theory of biological stress, working towards such a theory that informs our understanding of the simultaneous and interconnected unicellular, multicellular, organismal, and ecosystem stress responses is critical as it will improve our ability to predict how living systems respond to change, thus informing solutions to current and future environmental and human health challenges.

Diversity in Starvation Survival Strategies and Outcomes among Heterotrophic Proteobacteria

Heterotrophic Proteobacteria are versatile opportunists that have been extensively studied as model organisms in the laboratory, as both pathogens and beneficial symbionts of plants and animals, and as ubiquitous organisms found free-living in many environments. Succeeding in these niches requires an ability to persist for potentially long periods of time in growth-arrested states when essential nutrients become limiting. The tendency of these bacteria to grow in dense biofilm communities frequently leads to the development of steep nutrient gradients and deprivation of interior cells even when the environment is nutrient rich. Surviving within host environments also likely requires tolerating growth arrest due to the host limiting access to nutrients and transitioning between hosts may require a period of survival in a nutrient-poor environment. Interventions to maximise plant-beneficial activities and minimise infections by bacteria will require a better understanding of metabolic and regulatory networks that contribute to starvation survival, and how these networks function in diverse organisms. Here we focus on carbon starvation as a growth-arresting condition that limits availability not only of substrates for biosynthesis but also of energy for ongoing maintenance of the electrochemical gradient across the cell envelope and cellular integrity. We first review models for studying bacterial starvation and known strategies that contribute to starvation survival. We then present the results of a survey of carbon starvation survival strategies and outcomes in ten bacterial strains, including representatives from the orders Enterobacterales and Pseudomonadales (both Gammaproteobacteria) and Burkholderiales (Betaproteobacteria). Finally, we examine differences in gene content between the highest and lowest survivors to identify metabolic and regulatory adaptations that may contribute to differences in starvation survival.

Recovery of Unicellular Cyanobacteria from Nitrogen Chlorosis: A Model for Resuscitation of Dormant Bacteria

Nitrogen starvation induces developmental transitions in cyanobacteria. Whereas complex multicellular cyanobacteria of the order Nostocales can differentiate specialized cells that perform nitrogen fixation in the presence of oxygenic photosynthesis, non-diazotrophic unicellular strains, such as Synechococcus elongatus or Synechocystis PCC 6803, undergo a transition into a dormant non-growing state. Due to loss of pigments during this acclimation, the process is termed chlorosis. Cells maintain viability in this state for prolonged periods of time, until they encounter a useable nitrogen source, which triggers a highly coordinated awakening process, termed resuscitation. The minimal set of cellular activity that maintains the viability of cells during chlorosis and ensures efficient resuscitation represents the organism's equivalent of the BIOS, the basic input/output system of a computer, that helps "booting" the operation system after switching on. This review summarizes the recent research in the resuscitation of cyanobacteria, representing a powerful model for the awakening of dormant bacteria.