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.

The microbiota conditions a gut milieu that selects for wild-type Salmonella Typhimurium virulence.

Salmonella Typhimurium elicits gut inflammation by the costly expression of HilD-controlled virulence factors. This inflammation alleviates colonization resistance (CR) mediated by the microbiota and thereby promotes pathogen blooms. However, the inflamed gut-milieu can also select for hilD mutants, which cannot elicit or maintain inflammation, therefore causing a loss of the pathogen's virulence. This raises the question of which conditions support the maintenance of virulence in S. Typhimurium. Indeed, it remains unclear why the wild-type hilD allele is dominant among natural isolates. Here, we show that microbiota transfer from uninfected or recovered hosts leads to rapid clearance of hilD mutants that feature attenuated virulence, and thereby contributes to the preservation of the virulent S. Typhimurium genotype. Using mouse models featuring a range of microbiota compositions and antibiotic- or inflammation-inflicted microbiota disruptions, we found that irreversible disruption of the microbiota leads to the accumulation of hilD mutants. In contrast, in models with a transient microbiota disruption, selection for hilD mutants was prevented by the regrowing microbiota community dominated by Lachnospirales and Oscillospirales. Strikingly, even after an irreversible microbiota disruption, microbiota transfer from uninfected donors prevented the rise of hilD mutants. Our results establish that robust S. Typhimurium gut colonization hinges on optimizing its manipulation of the host: A transient and tempered microbiota perturbation is favorable for the pathogen to both flourish in the inflamed gut and also minimize loss of virulence. Moreover, besides conferring CR, the microbiota may have the additional consequence of maintaining costly enteropathogen virulence mechanisms.

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.

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

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

Second messenger-mediated adjustment of bacterial swimming velocity.

Bacteria swim by means of rotating flagella that are powered by ion influx through membrane-spanning motor complexes. Escherichia coli and related species harness a chemosensory and signal transduction machinery that governs the direction of flagellar rotation and allows them to navigate in chemical gradients. Here, we show that Escherichia coli can also fine-tune its swimming speed with the help of a molecular brake (YcgR) that, upon binding of the nucleotide second messenger cyclic di-GMP, interacts with the motor protein MotA to curb flagellar motor output. Swimming velocity is controlled by the synergistic action of at least five signaling proteins that adjust the cellular concentration of cyclic di-GMP. Activation of this network and the resulting deceleration coincide with nutrient depletion and might represent an adaptation to starvation. These experiments demonstrate that bacteria can modulate flagellar motor output and thus swimming velocity in response to environmental cues.

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.

Global dynamics of microbial communities emerge from local interaction rules.

Most microbes live in spatially structured communities (e.g., biofilms) in which they interact with their neighbors through the local exchange of diffusible molecules. To understand the functioning of these communities, it is essential to uncover how these local interactions shape community-level properties, such as the community composition, spatial arrangement, and growth rate. Here, we present a mathematical framework to derive community-level properties from the molecular mechanisms underlying the cell-cell interactions for systems consisting of two cell types. Our framework consists of two parts: a biophysical model to derive the local interaction rules (i.e. interaction range and strength) from the molecular parameters underlying the cell-cell interactions and a graph based model to derive the equilibrium properties of the community (i.e. composition, spatial arrangement, and growth rate) from these local interaction rules. Our framework shows that key molecular parameters underlying the cell-cell interactions (e.g., the uptake and leakage rates of molecules) determine community-level properties. We apply our model to mutualistic cross-feeding communities and show that spatial structure can be detrimental for these communities. Moreover, our model can qualitatively recapitulate the properties of an experimental microbial community. Our framework can be extended to a variety of systems of two interacting cell types, within and beyond the microbial world, and contributes to our understanding of how community-level properties emerge from microscopic interactions between cells.

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

Many microorganisms face a fundamental trade-off between reproduction and survival: Rapid growth boosts population size but makes microorganisms sensitive to external stressors. Here, we show that starved bacteria encountering new resources can break this trade-off by evolving phenotypic heterogeneity in lag time. We quantify the distribution of single-cell lag times of populations of starved Escherichia coli and show that population growth after starvation is primarily determined by the cells with shortest lag due to the exponential nature of bacterial population dynamics. As a consequence, cells with long lag times have no substantial effect on population growth resumption. However, we observe that these cells provide tolerance to stressors such as antibiotics. This allows an isogenic population to break the trade-off between reproduction and survival. We support this argument with an evolutionary model which shows that bacteria evolve wide lag time distributions when both rapid growth resumption and survival under stressful conditions are under selection. Our results can explain the prevalence of antibiotic tolerance by lag and demonstrate that the benefits of phenotypic heterogeneity in fluctuating environments are particularly high when minorities with extreme phenotypes dominate population dynamics.

Stochastic Gene Expression Influences the Selection of Antibiotic Resistance Mutations.

Bacteria can resist antibiotics by expressing enzymes that remove or deactivate drug molecules. Here, we study the effects of gene expression stochasticity on efflux and enzymatic resistance. We construct an agent-based model that stochastically simulates multiple biochemical processes in the cell and we observe the growth and survival dynamics of the cell population. Resistance-enhancing mutations are introduced by varying parameters that control the enzyme expression or efficacy. We find that stochastic gene expression can cause complex dynamics in terms of survival and extinction for these mutants. Regulatory mutations, which augment the frequency and duration of resistance gene transcription, can provide limited resistance by increasing mean expression. Structural mutations, which modify the enzyme or efflux efficacy, provide most resistance by improving the binding affinity of the resistance protein to the antibiotic; increasing the enzyme's catalytic rate alone may contribute to resistance if drug binding is not rate limiting. Overall, we identify conditions where regulatory mutations are selected over structural mutations, and vice versa. Our findings show that stochastic gene expression is a key factor underlying efflux and enzymatic resistances and should be taken into consideration in future antibiotic research.

Effective polyploidy causes phenotypic delay and influences bacterial evolvability.

Whether mutations in bacteria exhibit a noticeable delay before expressing their corresponding mutant phenotype was discussed intensively in the 1940s to 1950s, but the discussion eventually waned for lack of supportive evidence and perceived incompatibility with observed mutant distributions in fluctuation tests. Phenotypic delay in bacteria is widely assumed to be negligible, despite the lack of direct evidence. Here, we revisited the question using recombineering to introduce antibiotic resistance mutations into E. coli at defined time points and then tracking expression of the corresponding mutant phenotype over time. Contrary to previous assumptions, we found a substantial median phenotypic delay of three to four generations. We provided evidence that the primary source of this delay is multifork replication causing cells to be effectively polyploid, whereby wild-type gene copies transiently mask the phenotype of recessive mutant gene copies in the same cell. Using modeling and simulation methods, we explored the consequences of effective polyploidy for mutation rate estimation by fluctuation tests and sequencing-based methods. For recessive mutations, despite the substantial phenotypic delay, the per-copy or per-genome mutation rate is accurately estimated. However, the per-cell rate cannot be estimated by existing methods. Finally, with a mathematical model, we showed that effective polyploidy increases the frequency of costly recessive mutations in the standing genetic variation (SGV), and thus their potential contribution to evolutionary adaptation, while drastically reducing the chance that de novo recessive mutations can rescue populations facing a harsh environmental change such as antibiotic treatment. Overall, we have identified phenotypic delay and effective polyploidy as previously overlooked but essential components in bacterial evolvability, including antibiotic resistance evolution.

Dissection of the mutation accumulation process during bacterial range expansions.

BACKGROUND: Recent experimental work has shown that the evolutionary dynamics of bacteria expanding across space can differ dramatically from what we expect under well-mixed conditions. During spatial expansion, deleterious mutations can accumulate due to inefficient selection on the expansion front, potentially interfering with and modifying adaptive evolutionary processes. RESULTS: We used whole genome sequencing to follow the genomic evolution of 10 mutator Escherichia coli lines during 39 days ( ~ 1650 generations) of a spatial expansion, which allowed us to gain a temporal perspective on the interaction of adaptive and non-adaptive evolutionary processes during range expansions. We used elastic net regression to infer the positive or negative effects of mutations on colony growth. The colony size, measured after three day of growth, decreased at the end of the experiment in all 10 lines, and mutations accumulated at a nearly constant rate over the whole experiment. We find evidence that beneficial mutations accumulate primarily at an early stage of the experiment, leading to a non-linear change of colony size over time. Indeed, the rate of colony size expansion remains almost constant at the beginning of the experiment and then decreases after ~ 12 days of evolution. We also find that beneficial mutations are enriched in genes encoding transport proteins, and genes coding for the membrane structure, whereas deleterious mutations show no enrichment for any biological process. CONCLUSIONS: Our experiment shows that beneficial mutations target specific biological functions mostly involved in inter or extra membrane processes, whereas deleterious mutations are randomly distributed over the whole genome. It thus appears that the interaction between genetic drift and the availability or depletion of beneficial mutations determines the change in fitness of bacterial populations during range expansion.

Mutational and Selective Processes Involved in Evolution during Bacterial Range Expansions.

Bacterial populations have been shown to accumulate deleterious mutations during spatial expansions that overall decrease their fitness and ability to grow. However, it is unclear if and how they can respond to selection in face of this mutation load. We examine here if artificial selection can counteract the negative effects of range expansions. We examined the molecular evolution of 20 mutator lines selected for fast expansions (SEL) and compared them to 20 other mutator lines freely expanding without artificial selection (CONTROL). We find that the colony size of all 20 SEL lines have increased relative to the ancestral lines, unlike CONTROL lines, showing that enough beneficial mutations are produced during spatial expansions to counteract the negative effect of expansion load. Importantly, SEL and CONTROL lines have similar numbers of mutations indicating that they evolved for the same number of generations and that increased fitness is not due to a purging of deleterious mutations. We find that loss of function mutations better explain the increased colony size of SEL lines than nonsynonymous mutations or a combination of the two. Interestingly, most loss of function mutations are found in simple sequence repeats (SSRs) located in genes involved in gene regulation and gene expression. We postulate that such potentially reversible mutations could play a major role in the rapid adaptation of bacteria to changing environmental conditions by shutting down expensive genes and adjusting gene expression.

Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations.

While we have good understanding of bacterial metabolism at the population level, we know little about the metabolic behavior of individual cells: do single cells in clonal populations sometimes specialize on different metabolic pathways? Such metabolic specialization could be driven by stochastic gene expression and could provide individual cells with growth benefits of specialization. We measured the degree of phenotypic specialization in two parallel metabolic pathways, the assimilation of glucose and arabinose. We grew Escherichia coli in chemostats, and used isotope-labeled sugars in combination with nanometer-scale secondary ion mass spectrometry and mathematical modeling to quantify sugar assimilation at the single-cell level. We found large variation in metabolic activities between single cells, both in absolute assimilation and in the degree to which individual cells specialize in the assimilation of different sugars. Analysis of transcriptional reporters indicated that this variation was at least partially based on cell-to-cell variation in gene expression. Metabolic differences between cells in clonal populations could potentially reduce metabolic incompatibilities between different pathways, and increase the rate at which parallel reactions can be performed.

The rate of environmental fluctuations shapes ecological dynamics in a two-species microbial system.

Species interactions change when the external conditions change. How these changes affect microbial community properties is an open question. We address this question using a two-species consortium in which species interactions change from exploitation to competition depending on the carbon source provided. We built a mathematical model and calibrated it using single-species growth measurements. This model predicted that low frequencies of change between carbon sources lead to species loss, while intermediate and high frequencies of change maintained both species. We experimentally confirmed these predictions by growing co-cultures in fluctuating environments. These findings complement more established concepts of a diversity peak at intermediate disturbance frequencies. They also provide a mechanistic understanding for how the dynamics at the community level emerges from single-species behaviours and interspecific interactions. Our findings suggest that changes in species interactions can profoundly impact the ecological dynamics and properties of microbial systems.

Stabilization of cooperative virulence by the expression of an avirulent phenotype.

Pathogens often infect hosts through collective actions: they secrete growth-promoting compounds or virulence factors, or evoke host reactions that fuel the colonization of the host. Such behaviours are vulnerable to the rise of mutants that benefit from the collective action without contributing to it; how these behaviours can be evolutionarily stable is not well understood. We address this question using the intestinal pathogen Salmonella enterica serovar Typhimurium (hereafter termed S. typhimurium), which manipulates its host to induce inflammation, and thereby outcompetes the commensal microbiota. Notably, the virulence factors needed for host manipulation are expressed in a bistable fashion, leading to a slow-growing subpopulation that expresses virulence genes, and a fast-growing subpopulation that is phenotypically avirulent. Here we show that the expression of the genetically identical but phenotypically avirulent subpopulation is essential for the evolutionary stability of virulence in this pathogen. Using a combination of mathematical modelling, experimental evolution and competition experiments we found that within-host evolution leads to the emergence of mutants that are genetically avirulent and fast-growing. These mutants are defectors that exploit inflammation without contributing to it. In infection experiments initiated with wild-type S. typhimurium, defectors increase only slowly in frequency. In a genetically modified S. typhimurium strain in which the phenotypically avirulent subpopulation is reduced in size, defectors rise more rapidly, inflammation ceases prematurely, and S. typhimurium is quickly cleared from the gut. Our results establish that host manipulation by S. typhimurium is a cooperative trait that is vulnerable to the rise of avirulent defectors; the expression of a phenotypically avirulent subpopulation that grows as fast as defectors slows down this process, and thereby promotes the evolutionary stability of virulence. This points to a key role of bistable virulence gene expression in stabilizing cooperative virulence and may lead the way to new approaches for controlling pathogens.

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

Most bacteria live in ever-changing environments where periods of stress are common. One fundamental question is whether individual bacterial cells have an increased tolerance to stress if they recently have been exposed to lower levels of the same stressor. To address this question, we worked with the bacterium Caulobacter crescentus and asked whether exposure to a moderate concentration of sodium chloride would affect survival during later exposure to a higher concentration. We found that the effects measured at the population level depended in a surprising and complex way on the time interval between the two exposure events: The effect of the first exposure on survival of the second exposure was positive for some time intervals but negative for others. We hypothesized that the complex pattern of history dependence at the population level was a consequence of the responses of individual cells to sodium chloride that we observed: (i) exposure to moderate concentrations of sodium chloride caused delays in cell division and led to cell-cycle synchronization, and (ii) whether a bacterium would survive subsequent exposure to higher concentrations was dependent on the cell-cycle state. Using computational modeling, we demonstrated that indeed the combination of these two effects could explain the complex patterns of history dependence observed at the population level. Our insight into how the behavior of single cells scales up to processes at the population level provides a perspective on how organisms operate in dynamic environments with fluctuating stress exposure.

Genetic Manipulation of Glycogen Allocation Affects Replicative Lifespan in E. coli.

In bacteria, replicative aging manifests as a difference in growth or survival between the two cells emerging from division. One cell can be regarded as an aging mother with a decreased potential for future survival and division, the other as a rejuvenated daughter. Here, we aimed at investigating some of the processes involved in aging in the bacterium Escherichia coli, where the two types of cells can be distinguished by the age of their cell poles. We found that certain changes in the regulation of the carbohydrate metabolism can affect aging. A mutation in the carbon storage regulator gene, csrA, leads to a dramatically shorter replicative lifespan; csrA mutants stop dividing once their pole exceeds an age of about five divisions. These old-pole cells accumulate glycogen at their old cell poles; after their last division, they do not contain a chromosome, presumably because of spatial exclusion by the glycogen aggregates. The new-pole daughters produced by these aging mothers are born young; they only express the deleterious phenotype once their pole is old. These results demonstrate how manipulations of nutrient allocation can lead to the exclusion of the chromosome and limit replicative lifespan in E. coli, and illustrate how mutations can have phenotypic effects that are specific for cells with old poles. This raises the question how bacteria can avoid the accumulation of such mutations in their genomes over evolutionary times, and how they can achieve the long replicative lifespans that have recently been reported.

Light-Induced Mechanistic Divergence in Gold(I) Catalysis: Revisiting the Reactivity of Diazonium Salts.

In a systematic study of the Au-catalyzed reaction of o-alkynylphenols with aryldiazonium salts, we find that essentially the same reaction conditions lead to a change in mechanism when a light source is applied. If the reaction is carried out at room temperature using a AuI catalyst, the diazonium salt undergoes electrophilic deauration of a vinyl AuI intermediate and provides access to substituted azobenzofurans. If the reaction mixture is irradiated with blue LED light, C-C bond formation due to N2 -extrusion from the diazonium salt is realized selectively, using the same starting materials without the need for an additional photo(redox) catalyst under aerobic conditions. We report a series of experiments demonstrating that the same vinyl AuI intermediate is capable of producing the observed products under photolytic and thermal conditions. The finding that a vinyl AuI complex can directly, without the need for an additional photo(redox) catalyst, result in C-C bond formation under photolytic conditions is contrary to the proposed mechanistic pathways suggested in the literature till date and highlights that the role of oxidation state changes in photoredox catalysis involving Au is thus far only poorly understood and may hold surprises for the future. Computational results indicate that photochemical activation can occur directly from a donor-acceptor complex formed between the vinyl AuI intermediate and the diazonium salt.

Bacterial Ventures into Multicellularity: Collectivism through Individuality.

Multicellular eukaryotes can perform functions that exceed the possibilities of an individual cell. These functions emerge through interactions between differentiated cells that are precisely arranged in space. Bacteria also form multicellular collectives that consist of differentiated but genetically identical cells. How does the functionality of these collectives depend on the spatial arrangement of the differentiated bacteria? In a previous issue of PLOS Biology, van Gestel and colleagues reported an elegant example of how the spatial arrangement of differentiated cells gives rise to collective behavior in Bacillus subtilus colonies, further demonstrating the similarity of bacterial collectives to higher multicellular organisms.