In natural habitats, nutrient availability limits bacterial growth. We discovered that bacteria can overcome this limitation by acquiring nutrients by lysing neighboring cells through contact-dependent antagonism. Using single-cell live imaging and isotopic markers, we found that during starvation, the type VI secretion system (T6SS) lysed neighboring cells and thus provided nutrients from lysing cells for growth. Genomic adaptations in antagonists, characterized by a reduced metabolic gene repertoire, and the previously unexplored distribution of the T6SS across bacterial taxa in natural environments suggest that bacterial antagonism may contribute to nutrient transfer within microbial communities in many ecosystems.

Microbiome metabolism underlies numerous vital ecosystem functions. Individual microbiome members often perform partial catabolism of substrates or do not express all of the metabolic functions required for growth. Microbiome members can complement each other by exchanging metabolic intermediates and cellular building blocks to achieve a collective metabolism. We currently lack a mechanistic framework to explain why microbiome members adopt partial metabolism and how metabolic functions are distributed among them. Here we argue that natural selection for proteome efficiency—that is, performing essential metabolic fluxes at a minimal protein investment—explains partial metabolism of microbiome members, which underpins the collective metabolism of microbiomes. Using the carbon cycle as an example, we discuss motifs of collective metabolism, the conditions under which these motifs increase the proteome efficiency of individuals and the metabolic interactions they result in. In summary, we propose a mechanistic framework for how collective metabolic functions emerge from selection on individuals.

UV light emitting diodes (LEDs) are considered the new frontier of UV water disinfection. As UV technologies continue to evolve, so does the need to understand disinfection mechanisms to ensure that UV treatment continues to adequately protect public health. In this research, two Escherichia coli (E. coli) strains (the wild type K12 MG1655 and K12 SP11 (ThiI E342K)) were irradiated with UV-C at 268 nm both independently and after exposure to UV-A (365 nm). A synergistic effect was found on the viability of the wild type E. coli K12 strain when UV-A irradiation was applied prior to UV-C. Sublethal UV-A doses, which had a negligible effect on cell viability alone, enhanced UV-C inactivation by several orders of magnitude. This indicated a specific cellular response mechanism to UV-A irradiation, which was traced to direct photolysis of the transfer RNA (tRNA), which are critical links in the translation of messenger RNA to proteins. The wild type K12 strain MG1655, containing tRNAs with a thiolated uridine, directly absorbs the UV-A light, which leads to a reduction in protein synthesis, making them more susceptible to UV-C induced damage. However, the K12 strain SP11 (ThiI E342K), with a point mutation in the thiI gene that prevents a post-transcriptional modification of tRNA, experienced less inactivation upon subsequent irradiation by UV-C. The growth rate of cells, which was inhibited by sublethal UV-A doses, was not inhibited in this mutant strain with the modified tRNA. Time-lapse microscopy with microfluidics showed that sub-lethal UV-A caused a transient, reversible, growth arrest in E. coli. However, once the growth resumed, the cell division time resembled that of unirradiated cells. Damage induced by UV-A impaired the recovery of damage induced by UV-C. Depending on the UV-A dose applied, the synergistic effect remained even when there was a time delay of several hours between UV-A and UV-C exposures. The effect of sublethal UV-A was reversible over time; therefore, the synergistic effect was strongest when UV-C was applied immediately after UV-A. Combining UV-A and UV-C irradiation may serve as a practical tool to increase UV disinfection efficacy, which could potentially reduce costs while still adequately protecting public health.

Most of Earth's biomass is composed of polysaccharides. During biomass decomposition, polysaccharides are degraded by heterotrophic bacteria as a nutrient and energy source and are thereby partly remineralized into CO₂. As polysaccharides are heterogeneously distributed in nature, following the colonization and degradation of a polysaccharide hotspot the cells need to reach new polysaccharide hotspots. Even though many studies indicate that these degradation-dispersal cycles contribute to the carbon flow in marine systems, we know little about how cells alternate between polysaccharide degradation and motility, and which environmental factors trigger this behavioral switch. Here, we studied the growth of the marine bacterium Vibrio cyclitrophicus ZF270 on the abundant marine polysaccharide alginate, both in its soluble polymeric form as well as on its breakdown products. We used microfluidics coupled to time-lapse microscopy to analyze motility and growth of individual cells, and RNA sequencing to study associated changes in gene expression. We found that single cells grow at reduced rate on alginate until they form large groups that cooperatively break down the polymer. Exposing cell groups to digested alginate accelerates cell growth and changes the expression of genes involved in alginate degradation and catabolism, central metabolism, ribosomal biosynthesis, and transport. However, exposure to digested alginate also triggers cells to become motile and disperse from cell groups, proportionally increasing with the group size before the nutrient switch, and this is accompanied by high expression of genes involved in flagellar assembly, chemotaxis, and quorum sensing. The motile cells chemotax toward polymeric but not digested alginate, likely enabling them to find new polysaccharide hotspots. Overall, our findings reveal cellular mechanisms that might also underlie bacterial degradation-dispersal cycles, which influence the remineralization of biomass in marine environments.

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.

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.

Most bacteria live in dense, spatially structured communities such as biofilms. The high density allows cells to alter the local microenvironment, whereas the limited mobility can cause species to become spatially organized. Together, these factors can spatially organize metabolic processes within microbial communities so that cells in different locations perform different metabolic reactions. The overall metabolic activity of a community depends both on how metabolic reactions are arranged in space and on how they are coupled, i.e., how cells in different regions exchange metabolites. Here, we review mechanisms that lead to the spatial organization of metabolic processes in microbial systems. We discuss factors that determine the length scales over which metabolic activities are arranged in space and highlight how the spatial organization of metabolic processes affects the ecology and evolution of microbial communities. Finally, we define key open questions that we believe should be the main focus of future research.

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.

Polysaccharide breakdown by bacteria requires the activity of enzymes that degrade polymers either intra- or extra-cellularly. The latter mechanism generates a localized pool of breakdown products that are accessible to the enzyme producers themselves as well as to other organisms. Marine bacterial taxa often show marked differences in the production and secretion of degradative enzymes that break down polysaccharides. These differences can have profound effects on the pool of diffusible breakdown products and hence on the ecological dynamics. However, the consequences of differences in enzymatic secretions on cellular growth dynamics and interactions are unclear. Here we study growth dynamics of single cells within populations of marine Vibrionaceae strains that grow on the abundant marine polymer alginate, using microfluidics coupled to quantitative single-cell analysis and mathematical modelling. We find that strains that have low extracellular secretions of alginate lyases aggregate more strongly than strains that secrete high levels of enzymes. One plausible reason for this observation is that low secretors require a higher cellular density to achieve maximal growth rates in comparison with high secretors. Our findings indicate that increased aggregation increases intercellular synergy amongst cells of low-secreting strains. By mathematically modelling the impact of the level of degradative enzyme secretion on the rate of diffusive oligomer loss, we find that enzymatic secretion capability modulates the propensity of cells within clonal populations to cooperate or compete with each other. Our experiments and models demonstrate that enzymatic secretion capabilities can be linked with the propensity of cell aggregation in marine bacteria that extracellularly catabolize polysaccharides.

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 antibioticor 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.

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.

The ocean's nitrogen is largely fixed by cyanobacteria, including Trichodesmium, which forms aggregates comprising hundreds of filaments arranged in organized architectures. Aggregates often form upon exposure to stress and have ecological and biophysical characteristics that differ from those of single filaments. Here, we report that Trichodesmium aggregates can rapidly modulate their shape, responding within minutes to changes in environmental conditions. Combining video microscopy and mathematical modeling, we discovered that this reorganization is mediated by "smart reversals" wherein gliding filaments reverse when their overlap with other filaments diminishes. By regulating smart reversals, filaments control aggregate architecture without central coordination. We propose that the modulation of gliding motility at the single-filament level is a determinant of Trichodesmium's aggregation behavior and ultimately of its biogeochemical role in the ocean.

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.

Differences between species promote stable coexistence in a resource-limited environment. These differences can result from interspecies competition leading to character shifts, a process referred to as character displacement. While character displacement is often interpreted as a consequence of genetically fixed trait differences between species, it can also be mediated by phenotypic plasticity in response to the presence of another species. Here, we test whether phenotypic plasticity leads to a shift in proteome allocation during co-occurrence of two bacterial species from the abundant, leaf-colonizing families Sphingomonadaceae and Rhizobiaceae in their natural habitat. Upon mono-colonizing of the phyllosphere, both species exhibit specific and shared protein functions indicating a niche overlap. During co-colonization, quantitative differences in the protein repertoire of both bacterial populations occur as a result of bacterial coexistence in planta. Specifically, the Sphingomonas strain produces enzymes for the metabolization of xylan, while the Rhizobium strain reprograms its metabolism to beta-oxidation of fatty acids fueled via the glyoxylate cycle and adapts its biotin acquisition. We demonstrate the conditional relevance of cross-species facilitation by mutagenesis leading to loss of fitness in competition in planta. Our results show that dynamic character displacement and niche facilitation mediated by phenotypic plasticity can contribute to species coexistence.

Miniature ecosystems provide insights into general ecological principles

Bacteria are essential drivers of global biogeochemical cycles, including the carbon cycle. They play an important role in the degradation of organic matter that involves the breakdown of carbon polymers. These carbon polymers are too large to be taken up by bacterial cells. Therefore, bacteria often secrete extracellular enzymes to cleave the polymers into smaller oligomers and monomers that can be imported into the cell and metabolized. However, secreted enzymes and the released breakdown products can be lost through diffusion or flow. Mathematical models and experimental evidence suggest that aggregation of cells can reduce diffusional loss of secreted compounds and released nutrients. According to these findings, bacteria might benefit from forming aggregates when growing on carbon polymers due to the increased cell density and synergistic interactions between them. In this thesis, I used a wellstudied model system - the aquatic bacterium Caulobacter crescentus - to study the dynamics of bacterial behavior in response to growth on polymeric carbon sources. I used a microfluidics setup combined with automated time-lapse microscopy and quantitative image analysis to track growth dynamics and spatial organization of this bacterium at the single-cell level. [...]

Bakterien sind wesentliche Triebkräfte der globalen biogeochemischen Kreisläufe, einschließlich des Kohlenstoffkreislaufs. Sie spielen eine wichtige Rolle beim Abbau von organischem Material, der die Zersetzung von Kohlenstoffpolymeren beinhaltet. Diese Kohlenstoffpolymere sind zu groß, um von den Bakterienzellen aufgenommen zu werden. Daher scheiden Bakterien häufig extrazelluläre Enzyme aus, um die Polymere in kleinere Oligomere und Monomere zu spalten, die in die Zelle importiert und verstoffwechselt werden können. Allerdings können die sezernierten Enzyme und die freigesetzten Abbauprodukte durch Diffusion oder Strömung verloren gehen. Mathematische Modelle und experimentelle Beweise deuten darauf hin, dass die Aggregation von Zellen den Diffusionsverlust von sekretierten Verbindungen und freigesetzten Nährstoffen verringern kann. Diesen Erkenntnissen zufolge könnten Bakterien von der Bildung von Aggregaten profitieren, wenn sie auf Kohlenstoffpolymeren wachsen, da die Zelldichte erhöht wird und synergistische Wechselwirkungen zwischen den Zellen stattfinden. In dieser Arbeit habe ich ein gut untersuchtes Modellsystem - das aquatische Bakterium Caulobacter crescentus - verwendet, um die Dynamik des bakteriellen Verhaltens als Reaktion auf das Wachstum auf polymeren Kohlenstoffquellen zu untersuchen. Ich verwendete einen mikrofluidischen Aufbau in Kombination mit automatisierter Zeitraffermikroskopie und quantitativer Bildanalyse, um die Wachstumsdynamik und die räumliche Organisation dieses Bakteriums auf der Ebene einzelner Zellen zu verfolgen. [...]

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 communitylevel 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.

Microbial communities execute metabolic pathways to drive global nutrient cycles. Within a community, functionally specialized strains can perform different yet complementary steps within a linear pathway, a phenomenon termed metabolic division of labor (MDOL). However, little is known about how such metabolic behaviors shape microbial communities. Here, we derive a theoretical framework to define the assembly of a community that degrades an organic compound through MDOL. The framework indicates that to ensure community stability, the strains performing the initial steps should hold a growth advantage (m) over the “private benefit” (n) of the strain performing the last step. The steady-state frequency of the last strain is then determined by the quotient of n and m. Our experiments show that the framework accurately predicts the assembly of our synthetic consortia that degrade naphthalene through MDOL. Our results provide insights for designing and managing stable microbial systems for metabolic pathway optimization.

Horizontal gene transfer, mediated by conjugative plasmids, is a major driver of the global rise of antibiotic resistance. However, the relative contributions of factors that underlie the spread of plasmids and their roles in conjugation in vivo are unclear. To address this, we investigated the spread of clinical Extended Spectrum Beta-Lactamase (ESBL)-producing plasmids in the absence of antibiotics in vitro and in the mouse intestine. We hypothesised that plasmid properties would be the primary determinants of plasmid spread and that bacterial strain identity would also contribute. We found clinical Escherichia coli strains natively associated with ESBL-plasmids conjugated to three distinct E. coli strains and one Salmonella enterica serovar Typhimurium strain. Final transconjugant frequencies varied across plasmid, donor, and recipient combinations, with qualitative consistency when comparing transfer in vitro and in vivo in mice. In both environments, transconjugant frequencies for these natural strains and plasmids covaried with the presence/absence of transfer genes on ESBL-plasmids and were affected by plasmid incompatibility. By moving ESBL-plasmids out of their native hosts, we showed that donor and recipient strains also modulated transconjugant frequencies. This suggests that plasmid spread in the complex gut environment of animals and humans can be predicted based on in vitro testing and genetic data.

Background: In December 2020, the United Kingdom (UK) reported a SARS-CoV-2 Variant of Concern (VoC) which is now named B.1.1.7. Based on initial data from the UK and later data from other countries, this variant was estimated to have a transmission fitness advantage of around 40–80 % (Volz et al., 2021; Leung et al., 2021; Davies et al., 2021).
Aim: This study aims to estimate the transmission fitness advantage and the effective reproductive number of B.1.1.7 through time based on data from Switzerland.
Methods: We generated whole genome sequences from 11.8 % of all confirmed SARS-CoV-2 cases in Switzerland between 14 December 2020 and 11 March 2021. Based on these data, we determine the daily frequency of the B.1.1.7 variant and quantify the variant's transmission fitness advantage on a national and a regional scale.
Results: We estimate B.1.1.7 had a transmission fitness advantage of 43–52 % compared to the other variants circulating in Switzerland during the study period. Further, we estimate B.1.1.7 had a reproductive number above 1 from 01 January 2021 until the end of the study period, compared to below 1 for the other variants. Specifically, we estimate the reproductive number for B.1.1.7 was 1.24 [1.07–1.41] from 01 January until 17 January 2021 and 1.18 [1.06–1.30] from 18 January until 01 March 2021 based on the whole genome sequencing data. From 10 March to 16 March 2021, once B.1.1.7 was dominant, we estimate the reproductive number was 1.14 [1.00–1.26] based on all confirmed cases. For reference, Switzerland applied more non-pharmaceutical interventions to combat SARS-CoV-2 on 18 January 2021 and lifted some measures again on 01 March 2021.
Conclusion: The observed increase in B.1.1.7 frequency in Switzerland during the study period is as expected based on observations in the UK. In absolute numbers, B.1.1.7 increased exponentially with an estimated doubling time of around 2–3.5 weeks. To monitor the ongoing spread of B.1.1.7, our plots are available online.

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

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.

Nutrient limitation is one of the most common triggers of antibiotic tolerance and persistence. Here, we present two microfluidic setups to study how spatial and temporal variation in nutrient availability lead to increased survival of bacteria to antibiotics. The first setup is designed to mimic the growth dynamics of bacteria in spatially structured populations (e.g., biofilms) and can be used to study how spatial gradients in nutrient availability, created by the collective metabolic activity of a population, increase antibiotic tolerance. The second setup captures the dynamics of feast-and-famine cycles that bacteria recurrently encounter in nature, and can be used to study how phenotypic heterogeneity in growth resumption after starvation increases survival of clonal bacterial populations. In both setups, the growth rates and metabolic activity of bacteria can be measured at the single-cell level. This is useful to build a mechanistic understanding of how spatiotemporal variation in nutrient availability triggers bacteria to enter phenotypic states that increase their tolerance to antibiotics.

It has long been known that bacteria coordinate their physiology with their nutrient environment, yet our current understanding offers little intuition for how bacteria respond to the second-to-minute scale fluctuations in nutrient concentration characteristic of many microbial habitats. To investigate the effects of rapid nutrient fluctuations on bacterial growth, we couple custom microfluidics with single-cell microscopy to quantify the growth rate of E. coli experiencing 30 s to 60 min nutrient fluctuations. Compared to steady environments of equal average concentration, fluctuating environments reduce growth rate by up to 50%. However, measured reductions in growth rate are only 38% of the growth loss predicted from single nutrient shifts. This enhancement derives from the distinct growth response of cells grown in environments that fluctuate rather than shift once. We report an unexpected physiology adapted for growth in nutrient fluctuations and implicate nutrient timescale as a critical environmental parameter beyond nutrient identity and concentration.

Positive species interactions underlie the functioning of ecosystems. Given their importance, it is crucial to understand the stability of positive interactions over evolutionary timescales, in both constant and fluctuating environments; e.g., environments interrupted with periods of competition. We addressed this question using a two-species microbial system in which we modulated interactions according to the nutrient provided. We evolved in parallel four experimental replicates of species growing in isolation or together in consortia for 200 generations in both a constant and fluctuating environment with daily changes between commensalism and competition. We sequenced full genomes of single clones isolated at different time points during the experiment. We found that the two species coexisted over 200 generations in the constant commensal environment. In contrast, in the fluctuating environment, coexistence broke down when one of the species went extinct in two out of four cases. We showed that extinction was highly deterministic: when we replayed the evolution experiment from an intermediate time point we repeatably reproduced species extinction. We further show that these dynamics were driven by adaptive mutations in a small set of genes. In conclusion, in a fluctuating environment, rapid evolution destabilizes the long-term stability of positive pairwise interactions.

In bacterial communities, cells often communicate by the release and detection of small diffusible molecules, a process termed quorum-sensing. Signal molecules are thought to broadly diffuse in space; however, they often regulate traits such as conjugative transfer that strictly depend on the local community composition. This raises the question how nearby cells within the community can be detected. Here, we compare the range of communication of different quorum-sensing systems. While some systems support long-range communication, we show that others support a form of highly localized communication. In these systems, signal molecules propagate no more than a few microns away from signaling cells, due to the irreversible uptake of the signal molecules from the environment. This enables cells to accurately detect micron scale changes in the community composition. Several mobile genetic elements, including conjugative elements and phages, employ short-range communication to assess the fraction of susceptible host cells in their vicinity and adaptively trigger horizontal gene transfer in response. Our results underscore the complex spatial biology of bacteria, which can communicate and interact at widely different spatial scales.

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.

Communities of interacting microorganisms play important roles across all habitats on Earth. These communities typically consist of a large number of species that perform different metabolic processes. The functions of microbial communities ultimately emerge from interactions between these different microorganisms. To understand the dynamics and functions of microbial communities, we thus need to know the nature and strength of these interactions. Here, we quantified the interaction strength between individual cells in microbial communities. We worked with synthetic communities of Escherichia coli bacteria that exchange metabolites to grow. We combined single-cell growth rate measurements with mathematical modelling to quantify metabolic interactions between individual cells and to map the spatial interaction network in these communities. We found that cells only interact with other cells in their immediate neighbourhood. This short interaction range limits the coupling between different species and reduces their ability to perform metabolic processes collectively. Our experiments and models demonstrate that the spatial scale of biotic interaction plays a fundamental role in shaping the ecological dynamics of communities and the functioning of ecosystems.

Microbial communities are complex multi-species assemblages that are characterized by a multitude of interspecies interactions, which can range from mutualism to competition. The overall sign and strength of interspecies interactions have important consequences for emergent community-level properties such as productivity and stability. It is not well understood how interspecies interactions change over evolutionary timescales. Here, we review the empirical evidence that evolution is an important driver of microbial community properties and dynamics on timescales that have traditionally been regarded as purely ecological. Next, we briefly discuss different modelling approaches to study evolution of communities, emphasizing the similarities and differences between evolutionary and ecological perspectives. We then propose a simple conceptual model for the evolution of interspecies interactions in communities. Specifically, we propose that to understand the evolution of interspecies interactions, it is important to distinguish between direct and indirect fitness effects of a mutation. We predict that in well-mixed environments, traits will be selected exclusively for their direct fitness effects, while in spatially structured environments, traits may also be selected for their indirect fitness effects. Selection of indirectly beneficial traits should result in an increase in interaction strength over time, while selection of directly beneficial traits should not have such a systematic effect. We tested our intuitions using a simple quantitative model and found support for our hypotheses. The next step will be to test these hypotheses experimentally and provide input for a more refined version of the model in turn, thus closing the scientific cycle of models and experiments.
This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

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.

Microorganisms perform multiple metabolic functions that shape the global cycling of elements, health and disease of their host organisms, and biotechnological processes. The rates, at which different metabolic activities are performed by individual cells, can vary between genetically identical cells within clonal populations. While the molecular mechanisms that result in such metabolic heterogeneity have attracted considerable interest, the environmental conditions that shape heterogeneity and its consequences have received attention only in recent years. Here, we review the environmental drivers that lead to metabolic heterogeneity with a focus on nutrient limitation, temporal fluctuations and spatial structure, and the functional consequences of such heterogeneity. We highlight studies using single-cell methods that allow direct investigation of metabolic heterogeneity and discuss the relevance of metabolic heterogeneity in complex microbial communities.

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.

Increasing concerns about the rising rates of antibiotic therapy failure and advances in single-cell analyses have inspired a surge of research into antibiotic persistence. Bacterial persister cells represent a subpopulation of cells that can survive intensive antibiotic treatment without being resistant. Several approaches have emerged to define and measure persistence, and it is now time to agree on the basic definition of persistence and its relation to the other mechanisms by which bacteria survive exposure to bactericidal antibiotic treatments, such as antibiotic resistance, heteroresistance or tolerance. In this Consensus Statement, we provide definitions of persistence phenomena, distinguish between triggered and spontaneous persistence and provide a guide to measuring persistence. Antibiotic persistence is not only an interesting example of non-genetic single-cell heterogeneity, it may also have a role in the failure of antibiotic treatments. Therefore, it is our hope that the guidelines outlined in this article will pave the way for better characterization of antibiotic persistence and for understanding its relevance to clinical outcomes.

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.

Bacteria often live in spatially structured groups such as biofilms. In these groups, cells can collectively generate gradients through the uptake and release of compounds. In turn, individual cells adapt their activities to the environment shaped by the whole group. Here, we studied how these processes can generate phenotypic variation in clonal populations and how this variation contributes to the resilience of the population to antibiotics. We grew two-dimensional populations of Escherichia coli in microfluidic chambers where limiting amounts of glucose were supplied from one side. We found that the collective metabolic activity of cells created microscale gradients where nutrient concentration varied over a few cell lengths. As a result, growth rates and gene expression levels varied strongly between neighbouring cells. Furthermore, we found evidence for a metabolic cross-feeding interaction between glucose-fermenting and acetate-respiring subpopulations. Finally, we found that subpopulations of cells were able to survive an antibiotic pulse that was lethal in well-mixed conditions, likely due to the presence of a slow-growing subpopulation. Our work shows that emergent metabolic gradients can have important consequences for the functionality of bacterial populations as they create opportunities for metabolic interactions and increase the populations' tolerance to environmental stressors.
This article is part of a discussion meeting issue 'Single cell ecology'.

Microbes live in ever-changing environments where they need to adapt their metabolism to different nutrient conditions. Many studies have characterized the response of genetically identical cells to nutrient switches in homogeneous cultures; however, in nature, microbes often live in spatially structured groups such as biofilms where cells can create metabolic gradients by consuming and releasing nutrients. Consequently, cells experience different local microenvironments and vary in their phenotype. How does this phenotypic variation affect the ability of cells to cope with nutrient switches? Here, we address this question by growing dense populations of Escherichia coli in microfluidic chambers and studying a switch from glucose to acetate at the single-cell level. Before the switch, cells vary in their metabolic activity: some grow on glucose, while others cross-feed on acetate. After the switch, only few cells can resume growth after a period of lag. The probability to resume growth depends on a cells' phenotype prior to the switch: it is highest for cells cross-feeding on acetate, while it depends in a non-monotonic way on the growth rate for cells growing on glucose. Our results suggest that the strong phenotypic variation in spatially structured populations might enhance their ability to cope with fluctuating environments.

Many microorganisms secrete molecules that interact with resources outside of the cell. This includes, for example, enzymes that degrade polymers like chitin, and chelators that bind trace metals like iron. In contrast to direct uptake via the cell surface, such release strategies entail the risk of losing the secreted molecules to environmental sinks, including ‘cheating’ genotypes. Nevertheless, such secretion strategies are widespread, even in the well-mixed marine environment. Here, we investigate the benefits of a release strategy whose efficiency has frequently been questioned: iron uptake in the ocean by secretion of iron chelators called siderophores. We asked the question whether the release itself is essential for the function of siderophores, which could explain why this risky release strategy is widespread. We developed a reaction–diffusion model to determine the impact of siderophore release on iron uptake from the predominant iron sources in marine environments, colloidal or particulate iron, formed due to poor iron solubility. We found that release of siderophores is essential to accelerate iron uptake, as secreted siderophores transform slowly diffusing large iron particles to small, quickly diffusing iron–siderophore complexes. In addition, we found that cells can synergistically share their siderophores, depending on their distance and the size of the iron sources. Our study helps understand why release of siderophores is so widespread: even though a large fraction of siderophores is lost, the solubilization of iron through secreted siderophores can efficiently increase iron uptake, especially if siderophores are produced cooperatively by several cells. Overall, resource uptake mediated via release of molecules transforming their substrate could be essential to overcome diffusion limitation specifically in the cases of large, aggregated resources. In addition, we find that including the reaction of the released molecule with the substrate can impact the result of cooperative and competitive interactions, making our model also relevant for release-based uptake of other substrates.

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.

How unicellular organisms optimize the production of compounds is a fundamental biological question. While it is typically thought that production is optimized at the individual-cell level, secreted compounds could also allow for optimization at the group level, leading to a division of labor where a subset of cells produces and shares the compound with everyone. Using mathematical modeling, we show that the evolution of such division of labor depends on the cost function of compound production. Specifically, for any trait with saturating benefits, linear costs promote the evolution of uniform production levels across cells. Conversely, production costs that diminish with higher output levels favor the evolution of specialization–especially when compound shareability is high. When experimentally testing these predictions with pyoverdine, a secreted iron-scavenging compound produced by Pseudomonas aeruginosa, we found linear costs and, consistent with our model, detected uniform pyoverdine production levels across cells. We conclude that for shared compounds with saturating benefits, the evolution of division of labor is facilitated by a diminishing cost function. More generally, we note that shifts in the level of selection from individuals to groups do not solely require cooperation, but critically depend on mechanistic factors, including the distribution of compound synthesis costs.

Freshwater lakes and impoundments are an important source of methane into the atmosphere. Methane is the second most important greenhouse gas after carbon dioxide and accounts for about 75% of the climate impact of lakes. The only process that reduces methane emissions from lakes is the oxidation by methanotrophic bacteria. This diverse group of bacteria has the unique ability to use methane and oxygen to gain energy and produce biomass.
Aim of this dissertation was to improve our understanding of the ecology of these bacteria and their importance to prevent methane emissions from freshwater lakes. From the outset, the interdisciplinary project was designed to complement field studies with modelling. The focus was in particular on the methane dynamics during the autumnal overturn of stratified lakes. During this critical phase, large amounts of methane that accumulate in the anoxic hypolimnion during stratification are transported to the surface. [...]

Microbes are exposed to changing environments, to which they can respond by adopting various lifestyles such as swimming, colony formation or dormancy. These lifestyles are often studied in isolation, thereby giving a fragmented view of the life cycle as a whole. Here, we study lifestyles in the context of this whole. We first use machine learning to reconstruct the expression changes underlying life cycle progression in the bacterium Bacillus subtilis, based on hundreds of previously acquired expression profiles. This yields a timeline that reveals the modular organization of the life cycle. By analysing over 380 Bacillales genomes, we then show that life cycle modularity gives rise to mosaic evolution in which life stages such as motility and sporulation are conserved and lost as discrete units. We postulate that this mosaic conservation pattern results from habitat changes that make these life stages obsolete or detrimental. Indeed, when evolving eight distinct Bacillales strains and species under laboratory conditions that favour colony growth, we observe rapid and parallel losses of the sporulation life stage across species, induced by mutations that affect the same global regulator. We conclude that a life cycle perspective is pivotal to understanding the causes and consequences of modularity in both regulation and evolution.

The emergence of subpopulations that perform distinct metabolic roles has been observed in populations of genetically identical bacteria.

Aerobic methane-oxidizing bacteria (MOB) have the ability to thrive on methane, a potent greenhouse gas with critical climatic implications. They use methane as their sole source of carbon and energy. They phylogenetically mainly group as Alpha- and Gammaproteobacteria, as well as Verrucomicrobia. The metalloenzyme methane-monooxygenase (MMO) catalyses the initial oxidation step, the conversion of methane to methanol. The membrane-bound, particulate MMO (pMMO) is widespread among MOB, however, its atomic structure and active site composition remains a matter of debate. Nevertheless, it is generally agreed that pMMO is a copper-dependent enzyme.
Freshwater lakes are significant contributors to global natural methane emissions. However, MOB inhabiting their water column substantially reduce methane fluxes from the sediments to the atmosphere. MOB are commonly highly enriched at oxic-anoxic transition zones, but increasing evidence suggests that methane oxidation by MOB is also occurring at depths depleted in oxygen. [...]

Methan ist ein starkes Treibhausgas mit kritischen klimatischen Auswirkungen. Aerobe Methan oxidierende Bakterien (MOB) haben die Fähigkeit, Methan als einzige Kohlenstoff- und Energiequelle zu nutzen. Phylogenetisch werden sie hauptsächlich in Alpha- und Gammaproteobakterien sowie Verrucomicrobia eingeteilt. Das Enzym Methan-Monooxygenase (MMO) katalysiert den ersten Oxidationsschritt, die Umsetzung von Methan zu Methanol. Die membrangebundene, partikuläre MMO (pMMO) ist unter MOB weit verbreitet, jedoch sind seine chemische Struktur und die Zusammensetzung seines aktiven Zentrums weiterhin umstritten. Nichtsdestotrotz besteht ein allgemeiner Konsens, dass pMMO ein kupferabhängiges Enzym ist.
Süsswasserseen tragen wesentlich zu den globalen natürlichen Methanemissionen bei. Die in ihrer Wassersäule lebenden MOB konsumieren eine erhebliche Menge an Methan, welches aus den Sedimenten austritt, und andernfalls in die Atmosphäre gelangen würde. MOB findet man normalerweise stark angereichert in oxisch-anoxischen Übergangszonen, es gibt jedoch zunehmend Hinweise, dass Methanoxidation durch MOB auch in sauerstoffarmen Tiefen stattfindet. [...]

Microbial communities often exhibit incredible taxonomic diversity, raising questions regarding the mechanisms enabling species coexistence and the role of this diversity in community functioning. On the one hand, many coexisting but taxonomically distinct microorganisms can encode the same energy-yielding metabolic functions, and this functional redundancy contrasts with the expectation that species should occupy distinct metabolic niches. On the other hand, the identity of taxa encoding each function can vary substantially across space or time with little effect on the function, and this taxonomic variability is frequently thought to result from ecological drift between equivalent organisms. Here, we synthesize the powerful paradigm emerging from these two patterns, connecting the roles of function, functional redundancy and taxonomy in microbial systems. We conclude that both patterns are unlikely to be the result of ecological drift, but are inevitable emergent properties of open microbial systems resulting mainly from biotic interactions and environmental and spatial processes.

While antibiotics are a mainstay of contemporary medicine, many basic questions about how they inactivate and kill bacteria are still unresolved. The main goal of this thesis was to address some of these questions. Specifically, we aimed at expanding our understanding of two central themes that are difficult to explore in traditional microbiological approaches. The first theme is about how antibiotics affect the basic components of bacterial growth: cell division and death. We exposed bacterial populations to various concentrations of antibiotics and analyzed how the population growth patterns that we observed emerged from the interplay between cell division and cell death. The second theme is nongenetic factors that contribute to differences in the response and survival to antibiotics, either between individual cells or between environments with plenty or limited resources. We used Escherichia coli and ribosome-binding antibiotics as our model systems and employed microfluidics and time-lapse microscopy to investigate the effects of antibiotics at the level of individual cells. [...]

Antibiotika spielen eine zentrale Rolle in der zeitgenössischen Medizin. Nichtsdestotrotz verstehen wir aber nicht im Detail, wie Bakterien durch Antibiotika inaktiviert und abgetötet werden. Das zentrale Ziel dieser Dissertation war es, an diesen Wissenslücken zu arbeiten. Konkret haben wir uns auf zwei Aspekte fokussiert, die mit traditionellen Methoden aus der Mikrobiologie schwierig anzugehen sind. Der erste Aspekt ist, wie Antibiotika die grundlegenden Komponenten des bakteriellen Wachstums – Zellteilung und Zelltod – beeinflussen. Wir haben Bakterien verschiedenen Konzentrationen von Antibiotika ausgesetzt und haben untersucht, wie das beobachtete Populationswachstum zu Stande kommt durch ein Wechselspiel von Zellteilung und – tod. Der zweite Aspekt ist, dass nichtgenetische Faktoren einen erheblichen Effekt haben können darauf, wie Bakterien Antibiotika-Exposition überleben, und Unterschiede im Überleben zwischen individuellen Zellen innerhalb von klonalen Population oder zwischen verschiedenen Wachstumsbedingungen verursachen können. Wir haben das Bakterium Escherichia coli als Modellsystem verwendet, und mit Antibiotika gearbeitet, die an das bakterielle Ribosom binden. Um die Effekte von Antibiotika auf Einzelzell-Ebene zu untersuchen, haben wir Experimente in Mikrofluidik-Kammer und mit Zeitraffer-Mikroskopen durchgeführt. [...]

Here we used flow cytometry (FCM) and filtration paired with amplicon sequencing to determine the abundance and composition of small low nucleic acid (LNA)-content bacteria in a variety of freshwater ecosystems. We found that FCM clusters associated with LNA-content bacteria were ubiquitous across several ecosystems, varying from 50 to 90% of aquatic bacteria. Using filter-size separation, we separated small LNA-content bacteria (passing 0.4 µm filter) from large bacteria (captured on 0.4 µm filter) and characterized communities with 16S amplicon sequencing. Small and large bacteria each represented different sub-communities within the ecosystems’ community. Moreover, we were able to identify individual operational taxonomical units (OTUs) that appeared exclusively with small bacteria (434 OTUs) or exclusively with large bacteria (441 OTUs). Surprisingly, these exclusive OTUs clustered at the phylum level, with many OTUs appearing exclusively with small bacteria identified as candidate phyla (i.e. lacking cultured representatives) and symbionts. We propose that LNA-content bacteria observed with FCM encompass several previously characterized categories of bacteria (ultramicrobacteria, ultra-small bacteria, candidate phyla radiation) that share many traits including small size and metabolic dependencies on other microorganisms.

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.

Persisters are a subpopulation of bacteria that are not killed by antibiotics even though they lack genetic resistance. Here we provide evidence that persisters can manifest as small colony variants (SCVs) in clinical infections. We analyze growth kinetics of Staphylococcus aureus sampled from in vivo conditions and in vitro stress conditions that mimic growth in host compartments. We report that SCVs arise as a result of a long lag time, and that this phenotype emerges de novo during the growth phase in various stress conditions including abscesses and acidic media. We further observe that long lag time correlates with antibiotic usage. These observations suggest that treatment strategies should be carefully tailored to address bacterial persisters in clinics.

Populations of genetically identical cells can display marked variation in phenotypic traits; such variation is termed phenotypic heterogeneity. Here, we investigate the effect of substrate and electron donor limitation on phenotypic heterogeneity in N₂ and CO₂ fixation in the green sulphur bacterium Chlorobium phaeobacteroides. We grew populations in chemostats and batch cultures and used stable isotope labelling combined with nanometer-scale secondary ion mass spectrometry (NanoSIMS) to quantify phenotypic heterogeneity. Experiments in H₂S (i.e. electron donor) limited chemostats show that varying levels of NH₄⁺ limitation induce heterogeneity in N₂ fixation. Comparison of phenotypic heterogeneity between chemostats and batch (unlimited for H₂S) populations indicates that electron donor limitation drives heterogeneity in N₂ and CO₂ fixation. Our results demonstrate that phenotypic heterogeneity in a certain metabolic activity can be driven by different modes of limitation and that heterogeneity can emerge in different metabolic processes upon the same mode of limitation. In conclusion, our data suggest that limitation is a general driver of phenotypic heterogeneity in microbial populations.

Gene expression levels in clonal bacterial groups have been found to be spatially correlated. These correlations can partly be explained by the shared lineage history of nearby cells, although they could also arise from local cell-cell interactions. Here, we present a quantitative framework that allows us to disentangle the contributions of lineage history, long-range spatial gradients, and local cell-cell interactions to spatial correlations in gene expression. We study pathways involved in toxin production, SOS stress response, and metabolism in Escherichia coli microcolonies and find for all pathways that shared lineage history is the main cause of spatial correlations in gene expression levels. However, long-range spatial gradients and local cell-cell interactions also contributed to spatial correlations in SOS response, amino acid biosynthesis, and overall metabolic activity. Together, our data show that the phenotype of a cell is influenced by its lineage history and population context, raising the question of whether bacteria can arrange their activities in space to perform functions they cannot achieve alone.

Even in the absence of genetic or environmental differences, cells differ from each other in their molecular make-up. The consequences of these phenotypic differences are often not well understood. New work by Waite et al (2016) directly links variation in the molecular composition of individual bacterial cells to their population-level performance.

Recent theory predicts that the fitness of pioneer populations can decline when species expand their range, due to high rates of genetic drift on wave fronts making selection less efficient at purging deleterious variants. To test these predictions, we studied the fate of mutator bacteria expanding their range for 1650 generations on agar plates. In agreement with theory, we find that growth abilities of strains with a high mutation rate (HMR lines) decreased significantly over time, unlike strains with a lower mutation rate (LMR lines) that present three to four times fewer mutations. Estimation of the distribution of fitness effect under a spatially explicit model reveals a mean negative effect for new mutations (–0.38%), but it suggests that both advantageous and deleterious mutations have accumulated during the experiment. Furthermore, the fitness of HMR lines measured in different environments has decreased relative to the ancestor strain, whereas that of LMR lines remained unchanged. Contrastingly, strains with a HMR evolving in a well-mixed environment accumulated less mutations than agar-evolved strains and showed an increased fitness relative to the ancestor. Our results suggest that spatially expanding species are affected by deleterious mutations, leading to a drastic impairment of their evolutionary potential.

Bacteriophage transfer (lysogenic conversion) promotes bacterial virulence evolution. There is limited understanding of the factors that determine lysogenic conversion dynamics within infected hosts. A murine Salmonella Typhimurium (S.Tm) diarrhea model was used to study the transfer of SopEΦ, a prophage from S.Tm SL1344, to S.Tm ATCC14028S. Gut inflammation and enteric disease triggered >55% lysogenic conversion of ATCC14028S within 3 days. Without inflammation, SopEΦ transfer was reduced by up to 10⁵-fold. This was because inflammation (e.g., reactive oxygen species, reactive nitrogen species, hypochlorite) triggers the bacterial SOS response, boosts expression of the phage antirepressor Tum, and thereby promotes free phage production and subsequent transfer. Mucosal vaccination prevented a dense intestinal S.Tm population from inducing inflammation and consequently abolished SopEΦ transfer. Vaccination may be a general strategy for blocking pathogen evolution that requires disease-driven transfer of temperate bacteriophages.

Background: While mutualistic interactions between different genotypes are pervasive in nature, their evolutionary origin is not clear. The dilemma is that, for mutualistic interactions to emerge and persist, an investment into the partner genotype must pay off: individuals of a first genotype that invest resources to promote the growth of a second genotype must receive a benefit that is not equally accessible to individuals that do not invest. One way for exclusive benefits to emerge is through spatial structure (i.e., physical barriers to the movement of individuals and resources).
Results: Here we propose that organisms can evolve their own spatial structure based on physical attachment between individuals, and we hypothesize that attachment evolves when spatial proximity to members of another species is advantageous. We tested this hypothesis using experimental evolution with combinations of E. coli strains that depend on each other to grow. We found that attachment between cells repeatedly evolved within 8 weeks of evolution and observed that many different types of mutations potentially contributed to increased attachment.
Conclusions: We postulate a general principle by which passive beneficial interactions between organisms select for attachment, and attachment then provides spatial structure that could be conducive for the evolution of active mutualistic interactions.

Background. The ability to form a cellular memory and use it for cellular decision-making could help bacteria to cope with recurrent stress conditions. We analyzed whether bacteria would form a cellular memory specifically if past events are predictive of future conditions. We worked with the asymmetrically dividing bacterium Caulobacter crescentus where past events are expected to only be informative for one of the two cells emerging from division, the sessile cell that remains in the same microenvironment and does not migrate.
Results. Time-resolved analysis of individual cells revealed that past exposure to low levels of antibiotics increases tolerance to future exposure for the sessile but not for the motile cell. Using computer simulations, we found that such an asymmetry in cellular memory could be an evolutionary response to situations where the two cells emerging from division will experience different future conditions.
Conclusions. Our results raise the question whether bacteria can evolve the ability to form and use cellular memory conditionally in situations where it is beneficial.

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.

Since different wavelengths of light impact different cellular targets, microorganisms exposed to natural sunlight experience a combination of multiple stressors. In order to better understand the effects of sunlight on microorganisms we, therefore, need to understand how different wavelength act alone and in combination. Here, we describe a synergistic effect between UVA and UVB irradiation on viability of Escherichia coli bacteria. To investigate the basis of this synergistic effect we analysed mutant strains that were obtained through selection for increased resistance to combined UVA and UVB. By identifying and reconstructing genetic changes in the resistant strains we provide evidence that UVA-absorbing thiouridine residues in tRNAs are the key to the synergistic effect. Our study provides insights into how naturally occurring combinations of stressors can interact, and points to new ways for controlling microbial populations.

Drinking water, even when distributed safely, deteriorates in quality after entering the home. The microbiological quality of this building plumbing water is of particular interest because opportunistic pathogens (e.g. Legionella pneumophila) are known to proliferate there. Beyond the potential threat to health, microbial growth results in customer complaints about taste, odor, color, turbidity, slime formation, and filter clogging in building plumbing.
While water distributors strive to deliver a product that remains stable in the home, they have minimal influence on the design, maintenance, and operation of building plumbing systems. At the property line, legal responsibility for the water shifts away from the water distributor to the building owner. On top of this, monitoring water stability in the home requires invasive sampling and has potential privacy implications. All of these factors contribute to a poor understanding of the microbiology of water in building plumbing.
Many factors give building plumbing a unique growth environment. Pipe materials are varied and sometimes unregulated. In the building multiple materials are found within inches of each other. With high surface area to volume ratios, and more frequent replacement (e.g. with bathroom remodels), these materials have a considerably higher impact in buildings than in the distribution network. Temperature is high (e.g. hot and mixed water distribution) compared to the distribution network, creating favorable growth conditions. Building distalends are also only flowing intermittently (i.e. long stagnation times), allowing for biofilm and water phase interactions. While all of these factors are known to contribute to growth, their impact on bacterial concentration and composition is not completely understood. Moreover, each building is different with respect to design, operation, and location, complicating synthesis of various building plumbing studies.
The research presented here primarily addresses three factors in building plumbing, namely material quality, stagnation, and temperature. These three factors come together at shower hoses, which have (1) flexible polymeric materials that leach large amounts of biodegradable carbon, (2) long stagnation intervals (i.e. once daily showers), and (3) temperatures ranging only from warm to room temperature (i.e. neither hot nor cold). Shower hoses were thus often used as a model system throughout this thesis, for studies of both biofilm development and stagnation dependent water dynamics. As this research was supported by highly quantitative culture-independent methods (i.e., flow cytometry and qPCR), some critical aspects of these methods were also further investigated.
Throughout this work, building plumbing is approached as an ecological system governed by simple ecological principles, primarily that of dispersal (i.e., movement of bacteria) and selection (i.e., favorable growth conditions). This approach allowed for a cohesive understanding of building plumbing behavior in both large data sets from around the world and a series of highly controlled systems. For example, the quality of polymeric material was selective, but the effect could be surpassed by dispersal from the distribution network, and the selective factors ‘upstream’, like chlorination or temperature. During stagnation, spatial dispersal along the continuum of water delivery was insignificant compared to local dispersal from the biofilm to the water phase, which affected both concentration and microbiome composition. Ultimately, controlling bacterial growth in buildings will take advantage of these principles, and will furthermore embrace the inevitable growth in building plumbing pipes and water. Altogether, this research presents valuable steps towards a better understanding and better management of the microbiology within building plumbing.

A central question in microbial ecology is whether microbial interactions are predominantly cooperative or competitive. The secretion of siderophores, microbial iron chelators, is a model system for cooperative interactions. However, siderophores have also been shown to mediate competition by sequestering available iron and making it unavailable to competitors. The details of how siderophores mediate competition are not well understood, especially considering the complex distribution of iron phases in the environment. One pertinent question is whether sequestering iron through siderophores can indeed be effective in natural conditions; many natural environments are characterized by large pools of precipitated iron, and it is conceivable that any soluble iron that is sequestered by siderophores is replenished by the dissolution of these precipitated iron sources. Our goal here was to address this issue, and investigate the magnitude and mechanism of siderophore-mediated competition in the presence of precipitated iron. We combined experimental work with thermodynamic modeling, using Pseudomonas aeruginosa as a model system and ferrihydrite precipitates as the iron source with low solubility. Our experiments show that competitive growth inhibition by the siderophore pyochelin is indeed efficient, and that inhibition of a competitor can even have a stronger growth-promoting effect than solubilization of precipitated iron. Based on the results of our thermodynamic models we conclude that the observed inhibition of a competitor is effective because sequestered iron is only very slowly replenished by the dissolution of precipitated iron. Our research highlights the importance of competitive benefits mediated by siderophores, and underlines that the dynamics of siderophore production and uptake in environmental communities could be a signature of competitive, not just cooperative, dynamics.

To survive antibiotics, bacteria use two different strategies: counteracting antibiotic effects by expression of resistance genes or evading their effects e.g. by persisting inside host cells. Since bacterial adhesins provide access to the shielded, intracellular niche and the adhesin type 1 fimbriae increases bacterial survival chances inside macrophages, we asked if fimbriae also influenced survival by antibiotic evasion. Combined gentamicin survival assays, flow cytometry, single cell microscopy and kinetic modeling of dose response curves showed that type 1 fimbriae increased the adhesion and internalization by macrophages. This was caused by strongly decreased off-rates and affected the number of intracellular bacteria but not the macrophage viability and morphology. Fimbriae thus promote antibiotic evasion which is particularly relevant in the context of chronic infections.

Bacteria are an integral part of natural and engineered aquatic ecosystems. They contribute to many ecosystem processes (e.g., food webs, nutrient cycling) but are also used to remove nutrients in drinking water treatment (e.g., in biological filtration). However, bacteria can also have negative impacts on drinking water quality and infrastructure (e.g., biologically induced corrosion, aesthetic problems) and even pose a health risk.
All aquatic ecosystems experience perturbations at relatively short time scales from seconds to days and thus dynamics in bacterial concentrations are to be expected on similar time scales. Knowledge on such short-term microbial dynamics is important for a better understanding of natural and engineered ecosystem functioning. In drinking water production, knowledge on fluctuations in raw water quality as well as during treatment, storage, and distribution is crucial for appropriate design and operation of these systems. Furthermore, many basic laboratory experiments would strongly benefit from highly resolved, direct detection of bacterial concentrations. [...]

Bakterien sind ein fester Bestandteil von natürlichen und technischen Ökosystemen. Sie wirken bei vielen Prozessen in Ökosystemen mit (z.B. Nahrungsnetze, Nährstoffkreisläufe), werden aber auch für die Reduktion von Nährstoffen in der Trinkwasseraufbereitung eingesetzt (z.B. biologische Filtration). Allerdings können Bakterien auch negative Auswirkungen auf die Trinkwasserqualität und -infrastruktur haben (z.B. biologisch induzierte Korrosion, ästhetische Probleme) und sogar eine Gesundheitsgefährdung darstellen.
Alle aquatischen Ökosysteme erfahren Perturbationen auf relativ kurzen Zeitskalen von Sekunden bis Tagen und folglich ist zu erwarten, dass auch Dynamiken in der Bakterienkonzentration auf diesen Zeitskalen auftreten. Kenntnisse über solche kurzzeitige mikrobiologische Dynamiken sind wichtig für ein besseres Verständnis des Funktionierens von natürlichen und technischen Ökosystemen. In der Trinkwasserproduktion ist Wissen über Fluktuationen im Rohwasser aber auch in der Aufbereitung, Speicherung und Verteilung essentiell für die angemessene Planung und den Betrieb solcher Systeme. Des Weiteren würden auch viele grundlegende Laborexperimente stark von hochaufgelösten, direkten Messungen von Bakterienkonzentrationen profitieren. [...]

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.

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.

Following the success of the inaugural games, the Microbial Olympics return with a new series of events and microbial competitors. The games may have moved to a new hosting venue, but the dedication to training, fitness, competition (and yes, education and humour) lives on.

Freshwater lakes represent a major natural source of methane to the atmosphere, a potent greenhouse gas with critical climatic implications. Particularly in stratified lakes methane can potentially build up to high concentrations in the anoxic hypolimnion and be emitted by a variety of flux mechanisms. Microbial methane oxidation, which is principally mediated by anaerobic archaea and aerobic proteobacteria, is the only process impeding methane emissions from lacustrine waters. The majority of occurring methane oxidation in lakes has been ascribed to aerobic methanotrophs, which are preferably located at oxic/anoxic interfaces in both sediments and water columns. However, there is increasing evidence that methane is also oxidized in anoxic hypolimnia of lakes, where oxygen is not available as an oxidizing agent. It is speculated that electron acceptors such as nitrate, nitrite and iron- or manganese oxides could be of relevance there. Though the microorganisms mediating these processes remain elusive, recent laboratory studies revealed novel methanotrophs and pathways for methane oxidation, which could also be essential in lakes. [...]

Methan ist ein starkes Treibhausgas und hoch relevant für Klimafragen. Wichtige Quellen des natürlichen Ausstosses von Methan in die Atmosphäre sind Süsswasserseen. Besonders in geschichteten Seen können hohe Konzentrationen von Methan im anoxischen Hypolimnion akkumuliert und auf verschiedenste Weise emittiert werden. Einzig durch mikrobielle Methanoxidation, welche prinzipiell durch anaerobe Archeaen und aerobe Proteobakterien durchgeführt wird, kann der Ausstoss von Methan aus Seen unterbunden werden. Der Hauptteil der mikrobiellen Methanoxidation wird aeroben methanotrophen Bakterien zugeschrieben, welche sich vorzugsweise in oxisch/anoxischen Grenzschichten von Sedimenten oder Wassersäulen aufhalten. Zunehmend gibt es jedoch Hinweise, dass Methan auch im anoxischen Hypolimnion oxidiert wird, also ohne Verfügbarkeit von Sauerstoff als Oxidationsmittel. Stattdessen könnten unter diesen Bedingungen alternative Elektronenakzeptoren, wie Nitrat, Nitrit und Eisen- oder Manganoxide eine Rolle spielen. Bislang konnte nicht geklärt werden, welche Mikroorganismen diese Prozesse steuern, jedoch wurden kürzlich in Laborstudien neue methanotrophe Mikroorganismen entdeckt, welche ebenfalls eine wichtige Rolle in Seen spielen könnten. [...]

Most microorganisms live in environments where nutrients are limited and fluctuate over time. Cells respond to nutrient fluctuations by sensing and adapting their physiological state. Recent studies suggest phenotypic heterogeneity¹ in isogenic populations as an alternative strategy in fluctuating environments, where a subpopulation of cells express a function that allows growth under conditions that might arise in the future^2-9. It is unknown how environmental factors such as nutrient limitation shape phenotypic heterogeneity in metabolism and whether this allows cells to respond to nutrient fluctuations. Here, we show that substrate limitation increases phenotypic heterogeneity in metabolism, and this heterogeneity allows cells to cope with substrate fluctuations. We subjected the N₂-fixing bacterium Klebsiella oxytoca to different levels of substrate limitation and substrate shifts, and obtained time-resolved single-cell measurements of metabolic activities using nanometre-scale secondary ion mass spectrometry (NanoSIMS). We found that the level of NH₄⁺ limitation shapes phenotypic heterogeneity in N₂ fixation. In turn, the N₂ fixation rate of single cells during NH₄⁺ limitation correlates positively with their growth rate after a shift to NH₄⁺ depletion, experimentally demonstrating the benefit of heterogeneity. The results indicate that phenotypic heterogeneity is a general solution to two important ecological challenges—nutrient limitation and fluctuations—that many microorganisms face.

Human-induced environmental changes are causing major shifts in ecosystems around the globe. To support environmental management, scientific research has to infer both general trends and context dependency in these shifts at global and local scales. Combining replicated real-world experiments, which take advantage of implemented mitigation measures or other forms of human impact, with research-led experimental manipulations can provide powerful scientific tools for inferring causal drivers of ecological change and the generality of their effects. Additionally, combining these two approaches can facilitate communication with stakeholders involved in implementing management strategies. We demonstrate such an integrative approach using the case study EcoImpact, which aims at empirically unravelling the impacts of wastewater-born micropollutants on aquatic ecosystems.

Most microbial communities consist of a genetically diverse assembly of different organisms, and the level of genetic diversity plays an important part in community properties and functions. However, biological diversity also arises at a lower level of biological organization, between genetically identical cells that reside in the same microenvironment. In this Review, I outline the molecular mechanisms responsible for phenotypic heterogeneity and discuss how phenotypic heterogeneity allows genotypes to persist in fluctuating environments. I also describe how it promotes interactions between phenotypic subpopulations in clonal groups, providing microbial groups with new functionality.

Antibiotic resistance can impair bacterial growth or competitive ability in the absence of antibiotics, frequently referred to as a 'cost' of resistance. Theory and experiments emphasize the importance of such effects for the distribution of resistance in pathogenic populations. However, recent work shows that costs of resistance are highly variable depending on environmental factors such as nutrient supply and population structure, as well as genetic factors including the mechanism of resistance and genetic background. Here, we suggest that such variation can be better understood by distinguishing between the effects of resistance mechanisms on individual traits such as growth rate or yield ('trait effects') and effects on genotype frequencies over time ('selective effects'). We first give a brief overview of the biological basis of costs of resistance and how trait effects may translate to selective effects in different environmental conditions. We then review empirical evidence of genetic and environmental variation of both types of effects and how such variation may be understood by combining molecular microbiological information with concepts from evolution and ecology. Ultimately, disentangling different types of costs may permit the identification of interventions that maximize the cost of resistance and therefore accelerate its decline.

Biodiversities can differ substantially among different wastewater treatment plant (WWTP) communities. Whether differences in biodiversity translate into differences in the provision of particular ecosystem services, however, is under active debate. Theoretical considerations predict that WWTP communities with more biodiversity are more likely to contain strains that have positive effects on the rates of particular ecosystem functions, thus resulting in positive associations between those two variables. However, if WWTP communities were sufficiently biodiverse to nearly saturate the set of possible positive effects, then positive associations would not occur between biodiversity and the rates of particular ecosystem functions. To test these expectations, we measured the taxonomic biodiversity, functional biodiversity, and rates of 10 different micropollutant biotransformations for 10 full-scale WWTP communities. We have demonstrated that biodiversity is positively associated with the rates of specific, but not all, micropollutant biotransformations. Thus, one cannot assume whether or how biodiversity will associate with the rate of any particular micropollutant biotransformation. We have further demonstrated that the strongest positive association is between biodiversity and the collective rate of multiple micropollutant biotransformations. Thus, more biodiversity is likely required to maximize the collective rates of multiple micropollutant biotransformations than is required to maximize the rate of any individual micropollutant biotransformation. We finally provide evidence that the positive associations are stronger for rare micropollutant biotransformations than for common micropollutant biotransformations. Together, our results are consistent with the hypothesis that differences in biodiversity can indeed translate into differences in the provision of particular ecosystem services by full-scale WWTP communities.

In order to protect aquatic ecosystems from the adverse effects of chemical pollutants it is important to understand the factors that can influence their impact on organisms in the environment. Aquatic organisms, such as microalgae, are not only exposed to chemical pollutants, but also to additional environmental stressors, such as ultraviolet radiation (UVR). In combination, chemical and environmental stressors cause so-called multiple stressor effects. Effects resulting from combined exposure to multiple stressors might be predicted from the known effects of each individual stressor. However, multiple stressor effects might also be higher (synergism) or lower (antagonism) than expected, depending on the stressor combination. Stressor effect interactions are believed to be one reason for the limited predictability of multiple stressor effects. Moreover, organisms can acclimate to stressful environmental conditions which may increase or decrease (cotolerance) their sensitivity toward chemical pollutants and thus change multiple stressor effects. [...]

Um die aquatische Umwelt vor den negativen Effekten von Schadstoffen schützen zu können, muss man diejenigen Faktoren verstehen, die deren schädlichen Auswirkungen auf die Umwelt beeinflussen. Wasserlebewesen, wie z.B. Mikroalgen, sind nicht nur chemischen Schadstoffen allein ausgesetzt, sondern zusätzlich auch weiteren Umweltstressoren, wie Ultraviolettstrahlung (UVR). In Kombination können chemische Stressoren und Umweltstressoren sogenannte Multiple-Stressor-Effekte verursachen. Die Effekte die aus einer kombinierten Exposition gegenüber mehreren Stressoren resultieren, können gegebenenfalls anhand der Effekte der einzelnen Stressoren erklärt werden, können aber je nach Stressor auch höher (synergistisch) oder niedriger (antagonistisch) sein. Interaktionen von Stressor-Effekten werden als ein Grund für die begrenzte Vorhersagbarkeit von Multiple-Stressor-Effekten angesehen. Darüber hinaus können sich Organismen auch an widrige Umweltbedingungen akklimatisieren was unter Umständen ihre Sensitivität gegenüber chemischen Schadstoffen erhöhen oder vermindern (Ko-Toleranz) kann. [...]

Resource competition traits can be useful to predict the outcome of competition between different species. Focusing on the resources light and nitrogen, I conducted two resource limitation experiments to predict the outcome of competition between C. reinhardtii and 7 other freshwater algae species. The analysis of the data was based on the Monod model which is part of David Tilman’s resource ratio theory. Most species did not differ in their minimum requirement for light indicating that they also did not differ in their competition ability for light. Five different clones and a genetically diverse population of C. reinhardtii were included in the experiments to incorporate clonal diversity. The clones and the diverse population differed in their maximum growth rates when light was the limiting resource as well as in their growth dynamics in the high light treatments. Because of several issues, which will be discussed in this paper, the data of the nitrogen limitation experiment could not be used to fit the Monod model.

Populations of genetically identical microorganisms residing in the same environment can display marked variability in their phenotypic traits; this phenomenon is termed phenotypic heterogeneity. The relevance of such heterogeneity in natural habitats is unknown, because phenotypic characterization of a sufficient number of single cells of the same species in complex microbial communities is technically difficult. We report a procedure that allows to measure phenotypic heterogeneity in bacterial populations from natural environments, and use it to analyze N₂ and CO₂ fixation of single cells of the green sulfur bacterium Chlorobium phaeobacteroides from the meromictic lake Lago di Cadagno. We incubated lake water with ¹⁵N₂ and ¹³CO₂ under in situ conditions with and without NH₄⁺. Subsequently, we used flow cell sorting with auto-fluorescence gating based on a pure culture isolate to concentrate C. phaeobacteroides from its natural abundance of 0.2% to now 26.5% of total bacteria. C. phaeobacteroides cells were identified using catalyzed-reporter deposition fluorescence in situ hybridization (CARD-FISH) targeting the 16S rRNA in the sorted population with a species-specific probe. In a last step, we used nanometer-scale secondary ion mass spectrometry to measure the incorporation ¹⁵N and ¹³C stable isotopes in more than 252 cells. We found that C. phaeobacteroides fixes N₂ in the absence of NH₄⁺, but not in the presence of NH₄⁺ as has previously been suggested. N₂ and CO₂ fixation were heterogeneous among cells and positively correlated indicating that N₂ and CO₂ fixation activity interact and positively facilitate each other in individual cells. However, because CARD-FISH identification cannot detect genetic variability among cells of the same species, we cannot exclude genetic variability as a source for phenotypic heterogeneity in this natural population. Our study demonstrates the technical feasibility of measuring phenotypic heterogeneity in a rare bacterial species in its natural habitat, thus opening the door to study the occurrence and relevance of phenotypic heterogeneity in nature.

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

Phenotypic heterogeneity can confer clonal groups of organisms with new functionality. A paradigmatic example is the bistable expression of virulence genes in Salmonella typhimurium, which leads to phenotypically virulent and phenotypically avirulent subpopulations. The two subpopulations have been shown to divide labor during S. typhimurium infections. Here, we show that heterogeneous virulence gene expression in this organism also promotes survival against exposure to antibiotics through a bet-hedging mechanism. Using microfluidic devices in combination with fluorescence time-lapse microscopy and quantitative image analysis, we analyzed the expression of virulence genes at the single cell level and related it to survival when exposed to antibiotics. We found that, across different types of antibiotics and under concentrations that are clinically relevant, the subpopulation of bacterial cells that express virulence genes shows increased survival after exposure to antibiotics. Intriguingly, there is an interplay between the two consequences of phenotypic heterogeneity. The bet-hedging effect that arises through heterogeneity in virulence gene expression can protect clonal populations against avirulent mutants that exploit and subvert the division of labor within these populations. We conclude that bet-hedging and the division of labor can arise through variation in a single trait and interact with each other. This reveals a new degree of functional complexity of phenotypic heterogeneity. In addition, our results suggest a general principle of how pathogens can evade antibiotics: Expression of virulence factors often entails metabolic costs and the resulting growth retardation could generally increase tolerance against antibiotics and thus compromise treatment.

Determining the molecular changes that give rise to functional innovations is a major unresolved problem in biology. The paucity of examples has served as a significant hindrance in furthering our understanding of this process. Here we used experimental evolution with the bacterium Escherichia coli to quantify the molecular changes underlying functional innovation in 68 independent instances ranging over 22 different metabolic functions. Using whole-genome sequencing, we show that the relative contribution of regulatory and structural mutations depends on the cellular context of the metabolic function. In addition, we find that regulatory mutations affect genes that act in pathways relevant to the novel function, whereas structural mutations affect genes that act in unrelated pathways. Finally, we use population genetic modeling to show that the relative contributions of regulatory and structural mutations during functional innovation may be affected by population size. These results provide a predictive framework for the molecular basis of evolutionary innovation, which is essential for anticipating future evolutionary trajectories in the face of rapid environmental change.

The identity of plant host genetic factors controlling the composition of the plant microbiota and the extent to which plant genes affect associated microbial populations is currently unknown. Here, we use a candidate gene approach to investigate host effects on the phyllosphere community composition and abundance. To reduce the environmental factors that might mask genetic factors, the model plant Arabidopsis thaliana was used in a gnotobiotic system and inoculated with a reduced complexity synthetic bacterial community composed of seven strains representing the most abundant phyla in the phyllosphere. From a panel of 55 plant mutants with alterations in the surface structure, cell wall, defense signaling, secondary metabolism, and pathogen recognition, a small number of single host mutations displayed an altered microbiota composition and/or abundance. Host alleles that resulted in the strongest perturbation of the microbiota relative to the wild-type were lacs2 and pec1. These mutants affect cuticle formation and led to changes in community composition and an increased bacterial abundance relative to the wild-type plants, suggesting that different bacteria can benefit from a modified cuticle to different extents. Moreover, we identified ein2, which is involved in ethylene signaling, as a host factor modulating the community's composition. Finally, we found that different Arabidopsis accessions exhibited different communities, indicating that plant host genetic factors shape the associated microbiota, thus harboring significant potential for the identification of novel plant factors affecting the microbiota of the communities.

Antibiotics are powerful therapeutics but are not equally effective against all cells in bacterial populations. Bacteria that express an antibiotic-tolerant phenotype ("persisters") can evade treatment [1]. Persisters can cause relapses of the infection after the end of the therapy [2]. It is still poorly understood whether persistence affects the evolution of bacterial virulence. During infections, persisters have been found preferentially at particular sites within the host [3 and 4]. If bacterial virulence factors are required to reach such sites, treatment with antibiotics could impose selection on the expression of virulence genes, in addition to their well-established effects on bacterial resistance. Here, we report that treatment with antibiotics selects for virulence and fosters transmissibility of Salmonella Typhimurium. In a mouse model for Salmonella diarrhea, treatment with the broad-spectrum antibiotic ciprofloxacin reverses the outcome of competition between wild-type bacteria and avirulent mutants that can spontaneously arise during within-host evolution [ 5]. While avirulent mutants take over the gut lumen and abolish disease transmission in untreated mice, ciprofloxacin tilts the balance in favor of virulent, wild-type bacteria. This is explained by the need for virulence factors to invade gut tissues and form a persistent reservoir. Avirulent mutants remain in the gut lumen and are eradicated. Upon cessation of antibiotic treatment, tissue-lodged wild-type pathogens reseed the gut lumen and thereby facilitate disease transmissibility to new hosts. Our results suggest a general principle by which antibiotic treatment can promote cooperative virulence during within-host evolution, increase duration of transmissibility, and thereby enhance the spread of an infectious disease.

There is increasing evidence that rapid phenotypic evolution can strongly influence population dynamics, but how are such eco-evolutionary dynamics influenced by the source of trait variation (i.e., genetic variation or phenotypic plasticity)? To investigate this, we used rotifer–algae microcosm experiments to test how the phenotypic and genetic composition of prey populations affect predator–prey population dynamics. We chose four genetically distinct strains of the green alga Chlamydomonas reinhardtii that varied in their growth rate, standing levels of defense, and inducible defense. To additionally test for strain specificity of plasticity responses, we quantified protein expression of each strain in the presence and absence of rotifer predators (Brachionus calyciflorus). We then tested how different strain combinations influenced the outcome of pairwise competition trials with and without rotifer predation. We tracked individual strain frequencies using quantitative polymerase chain reaction (qPCR), and compared the observed dynamics to a suite of eco-evolutionary models of varying complexity. We found that variation in trade-offs between growth and defense between algal strains strongly influenced the outcome of competition and the overall predator–prey dynamics. Our purely ecological model of the observed dynamics, which allowed for the presence of phenotypic plasticity but no trait variation between strains, never outperformed any of our eco-evolutionary models in which strains could have different trait values. Our best fitting eco-evolutionary model allowed strains to differ in an inducible defense trait. Overall, our results provide some of the first experimental evidence that variation in phenotypically plastic responses among prey genotypes can be an important component of eco-evolutionary dynamics in a predator–prey system.

In vivo, antibiotics are often much less efficient than ex vivo and relapses can occur. The reasons for poor in vivo activity are still not completely understood. We have studied the fluoroquinolone antibiotic ciprofloxacin in an animal model for complicated Salmonellosis. High-dose ciprofloxacin treatment efficiently reduced pathogen loads in feces and most organs. However, the cecum draining lymph node (cLN), the gut tissue, and the spleen retained surviving bacteria. In cLN, approximately 10%-20% of the bacteria remained viable. These phenotypically tolerant bacteria lodged mostly within CD103⁺CX₃CR1^-CD11c⁺ dendritic cells, remained genetically susceptible to ciprofloxacin, were sufficient to reinitiate infection after the end of the therapy, and displayed an extremely slow growth rate, as shown by mathematical analysis of infections with mixed inocula and segregative plasmid experiments. The slow growth was sufficient to explain recalcitrance to antibiotics treatment. Therefore, slow-growing antibiotic-tolerant bacteria lodged within dendritic cells can explain poor in vivo antibiotic activity and relapse. Administration of LPS or CpG, known elicitors of innate immune defense, reduced the loads of tolerant bacteria. Thus, manipulating innate immunity may augment the in vivo activity of antibiotics. Author Summary Antibiotics that are known to kill bacteria in vitro can be less efficacious in vivo. The reasons for this have remained poorly understood. Using a mouse model for Salmonella diarrhea, we found that bacterial persistence occurs in the presence of the antibiotic ciprofloxacin because Salmonella can exist in two different states: as a fast-growing population that spreads in the host's tissues and as a slow-growing persister subpopulation. The slow-growing bacteria infect and hide out inside dendritic cells of the host's immune system and cannot be attacked by the antibioticthey are thereby rendered tolerant, despite their genetic susceptibility to the drug. These tolerant bacteria form a reservoir of viable cells that are able to reinitiate the infection on cessation of antibiotic therapy. Fortunately, however, these tolerant Salmonella cells are not invincible, and can be killed by adding agents that directly stimulate the host's immune defense. Combining innate immune stimulants with antibiotic treatment may offer new opportunities to improve antibacterial therapies.

Bacteria typically rely on secreted metabolites, potentially shareable at the community level, to scavenge resources from the environment. The evolution of diffusible, shareable metabolites is, however, difficult to explain because molecules can get lost, or be exploited by cheating mutants. A key question is whether natural selection can act on molecule structure to control loss and shareability. We tested this possibility by collating information on diffusivity properties of 189 secreted iron-scavenging siderophores and the natural habitats occupied by the siderophore-producing species. In line with evolutionary theory, we found that highly diffusible siderophores have preferentially evolved in species living in structured habitats, such as soil and hosts, because structuring can keep producers and their shareable goods together. Poorly diffusible siderophores, meanwhile, have preferentially evolved in species living in unstructured habitats, such as seawater, indicating that these metabolites are less shareable and more likely provide direct benefits to the producers.

Combination therapy is rarely used to counter the evolution of resistance in bacterial infections. Expansion of the use of combination therapy requires knowledge of how drugs interact at inhibitory concentrations. More than 50 years ago, it was noted that, if bactericidal drugs are most potent with actively dividing cells, then the inhibition of growth induced by a bacteriostatic drug should result in an overall reduction of efficacy when the drug is used in combination with a bactericidal drug. Our goal here was to investigate this hypothesis systematically. We first constructed time-kill curves using five different antibiotics at clinically relevant concentrations, and we observed antagonism between bactericidal and bacteriostatic drugs. We extended our investigation by performing a screen of pairwise combinations of 21 different antibiotics at subinhibitory concentrations, and we found that strong antagonistic interactions were enriched significantly among combinations of bacteriostatic and bactericidal drugs. Finally, since our hypothesis relies on phenotypic effects produced by different drug classes, we recreated these experiments in a microfluidic device and performed time-lapse microscopy to directly observe and quantify the growth and division of individual cells with controlled antibiotic concentrations. While our single-cell observations supported the antagonism between bacteriostatic and bactericidal drugs, they revealed an unexpected variety of cellular responses to antagonistic drug combinations, suggesting that multiple mechanisms underlie the interactions.

Traditionally, differences between individuals belonging to the same species are explained by differences in their genes and the environments they live in. In microbiological research, working with populations of genetically identical bacteria growing in homogeneous environments is standard procedure. A great amount of knowledge, on bacteria but also on general biological principles, has been gained by treating such populations as homogeneous samples and measuring traits on the population level. However, drawing conclusions from
such measurements is only valid under the implicit assumption that the measured trait is unimodally distributed in the population, and for a number of traits this assumption is wrong. Considering bacterial individuality generated by means other than genes and the environment – phenotypic heterogeneity – can lead to new insights in how bacterial communities work. This thesis is about the origins and functions of phenotypic heterogeneity. [...]

Traditionell werden Unterschiede zwischen Individuen, die zur selben Art gehören, durch Unterschiede in ihren Genen und in der Umwelt in der sie leben erklärt. In der mikrobiologischen Forschung ist die Arbeit mit genetisch identischen bakteriellen Populationen, die in derselben Umwelt wachsen, der Standard. Eine grosse Menge an Wissen, über Bakterien aber auch über allgemeine biologische Prinzipien, ist gewonnen worden, indem man solche Populationen als homogene Proben behandelt und deren Eigenschaften auf Populationsebene gemessen hat. Allerdings ist es nur zulässig, Schlüsse aus solchen Messungen zu ziehen, wenn man implizit annimmt, dass die gemessene Eigenschaft in der untersuchten Population unimodal verteilt ist. Bei einigen Eigenschaften ist diese Annahme falsch. Wenn man bakterielle Individualität, die von anderen Mechanismen als den Genen und der Umwelt generiert wurde – phänotypische Heterogenität – in Betracht zieht, kann das zum Gewinn neuer Erkenntnisse darüber führen, wie bakterielle Gemeinschaften funktionieren. Diese Arbeit behandelt die Ursprünge und Funktionen von phänotypischer Heterogenität. [...]

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 understood¹. 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^2,3. 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^4,5. 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.

Bacteria produce a wide arsenal of toxic compounds in order to kill competing species. Bacteriocins, protein-based toxins produced by nearly all bacteria, have generally been considered a ubiquitous anti-competitor strategy, used to kill competing bacterial strains. Some of these bacteriocins are encoded on plasmids, which also code for closely linked immunity compounds (thereby rendering toxin producing cells immune to their own toxin). However, the production of bacteriocins can also be interpreted as a means to promote plasmid stability by preferentially selecting for cells carrying the plasmid. If, for example, a cell were to lose the plasmid, it would no longer produce the immunity compound and would be killed by its bacteriocin-producing clone mates. In this respect, bacteriocins can be regarded as similar to previously described toxin–antitoxin systems that are able promote the stable transmission of plasmids to daughter cells. In order to test this prediction, we carried out an experimental evolution study using the bacterium Escherichia coli, finding that bacteriocins can indeed select for the stable maintenance of plasmids. This suggests that bacteriocins can act primarily as selfish genetic elements promoting their own transmission in the population, which may help explain their unique ecology and evolution.

Unicellular, diazotrophic cyanobacteria temporally separate dinitrogen (N₂) fixation and photosynthesis to prevent inactivation of the nitrogenase by oxygen. This temporal segregation is regulated by a circadian clock with oscillating activities of N₂ fixation in the dark and photosynthesis in the light. On the population level, this separation is not always complete, since the two processes can overlap during transitions from dark to light. How do single cells avoid inactivation of nitrogenase during these periods? One possibility is that phenotypic heterogeneity in populations leads to segregation of the two processes. Here, we measured N₂ fixation and photosynthesis of individual cells using nanometer-scale secondary ion mass spectrometry (nanoSIMS) to assess both processes in a culture of the unicellular, diazotrophic cyanobacterium Crocosphaera watsonii during a dark-light and a continuous light phase. We compared single-cell rates with bulk rates and gene expression profiles. During the regular dark and light phases, C. watsonii exhibited the temporal segregation of N₂ fixation and photosynthesis commonly observed. However, N₂ fixation and photosynthesis were concurrently measurable at the population level during the subjective dark phase in which cells were kept in the light rather than returned to the expected dark phase. At the single-cell level, though, cells discriminated against either one of the two processes. Cells that showed high levels of photosynthesis had low nitrogen fixing activities, and vice versa. These results suggest that, under ambiguous environmental signals, single cells discriminate against either photosynthesis or nitrogen fixation, and thereby might reduce costs associated with running incompatible processes in the same cell.

Background: In this study, we aimed at investigating heterogeneity in the expression of metabolic genes in clonal populations of Escherichia coli growing on glucose as the sole carbon source. Different metabolic phenotypes can arise in these clonal populations through variation in the expression of glucose transporters and metabolic enzymes. First, we focused on the glucose transporters PtsG and MglBAC to analyze the diversity of glucose uptake strategies. Second, we analyzed phenotypic variation in the expression of genes involved in gluconeogenesis and acetate scavenging (as acetate is formed and excreted during bacterial growth on glucose), which can reveal, for instance, phenotypic subpopulations that cross-feed through the exchange of acetate. In these experiments, E. coli MG1655 strains containing different transcriptional GFP reporters were grown in chemostats and reporter expression was measured with flow cytometry.
Results: Our results suggest heterogeneous expression of metabolic genes in bacterial clonal populations grown in glucose environments. The two glucose transport systems exhibited different level of heterogeneity. The majority of the bacterial cells expressed the reporters for both glucose transporters MglBAC and PtsG and a small fraction of cells only expressed the reporter for Mgl. At a low dilution rate, signals from transcriptional reporters for acetyl-CoA synthetase Acs and phosphoenolpyruvate carboxykinase Pck indicated that almost all cells expressed the genes that are part of acetate utilization and the gluconeogenesis pathway, respectively. Possible co-existence of two phenotypic subpopulations differing in acs expression occurred at the threshold of the switch to overflow metabolism. The overflow metabolism results in the production of acetate and has been previously reported to occur at intermediate dilution rates in chemostats with high concentration of glucose in the feed.
Conclusions: Analysis of the heterogeneous expression of reporters for genes involved in glucose and acetate metabolism raises new question whether different metabolic phenotypes are expressed in clonal populations growing in continuous cultures fed on glucose as the initially sole carbon source.

The most common microbiological technique to cultivate bacteria is to grow them in flasks and to measure average bacterial characteristics. In only 1 milliliter of those bacterial cultures there can be millions and millions of individual cells – and, yet, by this approach one would get one data point for a single measurement. In comparison, we are more than 7 billion people in the world. Now imagine that one scientific question would be, what is the average people’s height. One number would describe height of billions of individuals. This information is relevant in a way that we get intuition or perspective for future scientific questions. However, one average measurement does not need to reflect the characteristics of an individual and population structure, neither in humans, nor in bacteria. This thesis focuses on describing physiology and biological properties of individual bacterial cells. I used single-cell techniques, usually fluorescence microscopy and flow cytometry, to investigate variation or heterogeneity within genetically identical bacterial cells. [...]

Üblicherweise werden Bakterien in grossen Mengen in Kulturkolben angezüchtet um deren durchschnittliche Eigenschaften zu analysieren. In nur einem tausendstel Liter dieser Bakterienkulturen können sich Millionen und Abermillionen individuelle Zellen befinden, mit der herkömmlichen Methode der Kultivation ergibt sich daraus jedoch nur ein einzelner Datenpunkt für eine einzige Messung. Um dies zu verdeutlichen: auf der Erde befinden sich über sieben Milliarden Menschen. Stellen sie sich nun vor dass eine mögliche wissenschaftliche Fragestellung beinhalten könnte welches die Körpergrösse eines durchschnittlichen Menschen ist. Somit würde nur eine Zahl die Körpergrösse von Milliarden von Individuen wiedergeben. Diese Information mag relevant für zukünftige wissenschaftliche Fragen sein. Allerdings kann ein durchschnittliches Mass nicht die Eigenschaften eines Individuums wiedergeben, weder bei Menschen noch bei Bakterien. Der Schwerpunkt dieser Arbeit liegt auf der Beschreibung der Physiologie und der biologischen Eigenschaften einzelner individueller Bakterienzellen. [...]
 

The microbial cell is, in contrast to multicellular organisms, directly exposed to environmental stimuli and stresses. This means on one hand that dissolved nutrients can directly and quickly be taken up. On the other hand, this also implies that microbes are directly exposed to unfavourable conditions such as low nutrient concentrations, low or high pH and temperature, or UV light. In order to survive, the cells have to be able to adapt to these conditions. Unfavourable conditions, as well as all environmental changes that require physiological adaptations of the cell, i.e., in gene expression and cellular composition, can be regarded as a stress for the microbial cell. In Escherichia coli a wide range of responses to these stresses is governed by the alternative sigma factor σ^S. [...]

Im Gegensatz zu multizellulären Organismen ist die mikrobielle Zelle Umwelteinflüssen und Stress direkt ausgesetzt. Einerseits heisst dies, dass gelöste Nährstoffe schnell direkt aufgenommen werden können, bedingt andererseits aber auch, dass Mikroorganismen ungünstigen Bedingungen wie niedrigen Nährstoffkonzentrationen, extremen pH-Werten und Temperaturen oder UV-Strahlung unmittelbar ausgesetzt sind. Um derartige Bedingungen zu überleben, müssen die Zellen in der Lage sein sich diesen anzupassen. Dabei müssen nicht nur ungünstige Umweltbedingungen als Stress für Mikroorganismen angesehen werden, sondern generell jede Veränderung der Umgebung, die eine physiologische Anpassung auf Ebene der Genexpression oder Zellzusammensetzung erfordert. In Escherichia coli wird eine Reihe von Antworten auf Umweltstress über den alternativen Sigma-Faktor σ^S gesteuert. [...]

Most organisms live in ever-changing environments, and have to cope with a range of different conditions. Often, the set of biological traits that are needed to grow, reproduce, and survive varies between conditions. As a consequence, organisms have evolved sensory systems to detect environmental signals, and to modify the expression of biological traits in response. However, there are limits to the ability of such plastic responses to cope with changing environments. Sometimes, environmental shifts might occur suddenly, and without preceding signals, so that organisms might not have time to react. Other times, signals might be unreliable, causing organisms to prepare themselves for changes that then do not occur. Here, we focus on such unreliable signals that indicate the onset of adverse conditions. We use analytical and individual-based models to investigate the evolution of simple rules that organisms use to decide whether or not to switch to a protective state. We find evolutionary transitions towards organisms that use a combination of random switching and switching in response to the signal. We also observe that, in spatially heterogeneous environments, selection on the switching strategy depends on the composition of the population, and on population size. These results are in line with recent experiments that showed that many unicellular organisms can attain different phenotypic states in a probabilistic manner, and lead to testable predictions about how this could help organisms cope with unreliable signals.

Essential genes code for fundamental cellular functions required for the viability of an organism. For this reason, essential genes are often highly conserved across organisms. However, this is not always the case: orthologues of genes that are essential in one organism are sometimes not essential in other organisms or are absent from their genomes. This suggests that, in the course of evolution, essential genes can be rendered nonessential. How can a gene become non-essential? Here we used genetic manipulation to deplete the products of 26 different essential genes in Escherichia coli. This depletion results in a lethal phenotype, which could often be rescued by the overexpression of a non-homologous, non-essential gene, most likely through replacement of the essential function. We also show that, in a smaller number of cases, the essential genes can be fully deleted from the genome, suggesting that complete functional replacement is possible. Finally, we show that essential genes whose function can be replaced in the laboratory are more likely to be non-essential or not present in other taxa. These results are consistent with the notion that patterns of evolutionary conservation of essential genes are influenced by their compensability—that is, by how easily they can be functionally replaced, for example through increased expression of other genes.

Microbial (re)growth is of major concern in environmental and especially drinking water
systems. Biological stability describes whether or not such regrowth can take place
in a given system. In drinking water production, biological stability is often characterised
by an absolute threshold (meaning a concentration) for the commonly limiting
resource, i.e. reduced carbon species. This view is extended in this thesis by taking into
account the initial concentration of consumers in addition to initially available resource.
This view is expressed with a novel, relative measure of biological stability: the
initial resource-to-consumer ratio.
The basic relationship of resources and microbial growth was first shown in glucoselimited
batch experiments with Escherichia coli (E. coli). The difference between initial
and repeated addition of limiting resource was also illustrated. In a second experiment
series, a specific pattern of net growth as a function of the initial resource-toconsumer
ratio not described in existing literature was observed. Interestingly, the
pattern was identified in a variety of setups – from pure cultures and high concentrations
of a single substrate to indigenous environmental communities depending on
complex freshwater carbon at low concentrations. The pattern consisted of two large
stable zones of zero and maximum net growth and a small transitional zone with variable
net growth. A new, relative threshold for biological stability was introduced and
was estimated to be 1 x 10^-14 g_AOC cell^-1. The experimental data were checked against
published data on energy consumption in simple model calculations for E. coli. Further
experiments lead to qualitative considerations on the influence of interspecies competition
highlighted the potential of pathogen regrowth at favourable initial resourceto-
consumer ratios. The basic insights from the first three studies were then looked at
in a real-world application, which could be compared to a batch reactor. A preliminary
microbial assessment of drinking water produced by a gravity-driven membrane filtration
(GDMF) prototype was completed. Total cell concentration (TCC) in the produced
water was relatively high (9 x 10⁵ cells ml^-1 to 3 x 106 cells ml^-1). The concept of the
initial resource-to-consumer ratio was used to explain the results with limited success.
Regrowth dynamics proved to be more complex mainly due to biofilm formation in
the filter and piping. Four major factors were analysed that appear to govern the overall
performance of the prototype in terms of microbial water quality.
This thesis advocates an alternative way of looking at microbial growth in non-steady
state situations. Results support the perception that it is crucial to take into account
both resources and initial consumers when assessing growth potential and biological
stability of water. Such a perspective may have wide application in the optimisation of
water management and treatment. Further testing of the concept is necessary especially
with a wider range of resource types and concentrations.

The objective of this work was to improve our understanding of the quantitative predictive capabilities of metatranscriptomics. To meet this objective, we investigated whether we can predict the activity level of a specific biochemical function based on the abundance of the corresponding gene transcript within measured community metatranscriptomes. In addition, we investigated the lower limit of a microorganism's abundance that still allows detection of its transcripts within a metatranscriptome and prediction of the activity levels of the enzyme encoded by the transcript. To do this, we amended an undefined microbial community with varying fractions of an Escherichia coli strain that can catalyze a specific transformation reaction for the herbicide atrazine. We observed a linear and proportional relationship between the activity level of the transformation reaction and the abundance of its associated encoding transcript down to an E. coli cell density of 0.05% of the population.

Understanding the emergence and evolution of multicellularity and cellular differentiation is a core problem in biology. We develop a quantitative model that shows that a multicellular form emerges from genetically identical unicellular ancestors when the compartmentalization of poorly compatible physiologicalv processes into component cells of an aggregate produces a fitness advantage. Thisvdivision of labour between the cells in the aggregate occurs spontaneously at the regulatory level owing to mechanisms present in unicellular ancestors and does not require any genetic predisposition for a particular role in the aggregate or any orchestrated cooperative behaviour of aggregate cells. Mathematically, aggregation implies an increase in the dimensionality of phenotype space that generates a fitness landscape with new fitness maxima, in which the unicellular states of optimized metabolism become fitness saddle points. Evolution of multicellularity is modelled as evolution of a hereditary parameter: the propensity of cells to stick together, which determines the fraction of time a cell spends in the aggregate form. Stickiness can increase evolutionarily owing to the fitness advantage generated by the division of labour between cells in an aggregate.

Metabolic specialization is a general biological principle that shapes the assembly of microbial communities. Individual cell types rarely metabolize a wide range of substrates within their environment. Instead, different cell types often specialize at metabolizing only subsets of the available substrates. What is the advantage of metabolizing subsets of the available substrates rather than all of them? In this perspective piece, we argue that biochemical conflicts between different metabolic processes can promote metabolic specialization and that a better understanding of these conflicts is therefore important for revealing the general principles and rules that govern the assembly of microbial communities. We first discuss three types of biochemical conflicts that could promote metabolic specialization. Next, we demonstrate how knowledge about the consequences of biochemical conflicts can be used to predict whether different metabolic processes are likely to be performed by the same cell type or by different cell types. We then discuss the major challenges in identifying and assessing biochemical conflicts between different metabolic processes and propose several approaches for their measurement. Finally, we argue that a deeper understanding of the biochemical causes of metabolic specialization could serve as a foundation for the field of synthetic ecology, where the objective would be to rationally engineer the assembly of a microbial community to perform a desired biotransformation.

Benzo(a)pyrene (BaP) is a ubiquitous pollutant derived by incomplete combustion of organic matter. BaP is classified by the International Agency of Cancer (IARC) as carcinogenic to humans and is controlled in drinking water in the United States and Europe. BaP needs to be metabolized to become carcinogenic. Its metabolism is induced by the interaction between  BaP and the aryl hydrocarbon receptor (AhR) and subsequent gene regulation. Despite this general knowledge, details about BaP entry into cells, distribution and internal concentrations able to elicit a cellular response are largely unexplored and mechanisms of actions incompletely understood. This PhD thesis therefore aims to investigate in a time and concentration dependent manner the molecular response of a murine hepatoma cell line, Hepa1c1c7, exposed to BaP, combining high throughput techniques, bioinformatics, phenotype characterization and chemical analysis. [...]

Using optimal control theory as the basic theoretical tool, we investigate the efficacy of different antibiotic treatment protocols in the most exacting of circumstances, described as follows. Viewing a continuous culture device as a proxy for a much more complex host organism, we first inoculate the device with a single bacterial species and deem this the 'commensal' bacterium of our host. We then force the commensal to compete for a single carbon source with a rapidly evolving and fitter 'pathogenic bacterium', the latter so-named because we wish to use a bacteriostatic antibiotic to drive the pathogen toward low population densities. Constructing a mathematical model to mimic the biology, we do so in such a way that the commensal would be eventually excluded by the pathogen if no antibiotic treatment were given to the host or if the antibiotic were over-deployed. Indeed, in our model, all fixed-dose antibiotic treatment regimens will lead to the eventual loss of the commensal from the host proxy. Despite the obvious gravity of the situation for the commensal bacterium, we show by example that it is possible to design drug deployment protocols that support the commensal and reduce the pathogen load. This may be achieved by appropriately fluctuating the concentration of drug in the environment; a result that is to be anticipated from the theory optimal control where bang-bang solutions may be interpreted as intermittent periods of either maximal and minimal drug deployment. While such 'antibiotic pulsing' is near-optimal for a wide range of treatment objectives, we also use this model to evaluate the efficacy of different antibiotic usage strategies to show that dynamically changing antimicrobial therapies may be effective in clearing a bacterial infection even when every 'static monotherapy' fails.

Medical and pharmacological communities have long searched for antimicrobial drugs that increase their effect when used in combination, an interaction known as synergism. These drug combinations, however, impose selective pressures in favour of multi-drug resistance and as a result, the benefit of synergy may be lost after only a few bacterial generations. Furthermore, there is experimental evidence that antibiotic treatment can disrupt colonization resistance by shifting the balance between enteropathogenic and commensal bacteria in favour of the pathogens, with the potential to increase the risk of infections. So, we ask, what is the best way of using synergistic drugs? We pose an evolutionary model of commensal and pathogenic bacteria competing in a continuous culture device for a single limiting carbon source under the effect of two bacteriostatic and synergistic antibiotics. This model allows us to evaluate the efficacy of different drug deployment strategies and, using ideas from optimal control theory, to understand whether there are circumstances in which other types of therapy might be favoured over those based on fixed-dose multi-drug combinations. Our main result can be stated thus: the optimal deployment of synergistic antibiotics to remove a pathogen in the presence of commensal bacteria in our model system occurs not in combination, but by deploying them sequentially.

Gene expression is subject to random perturbations that lead to fluctuations in the rate of protein production. As a consequence, for any given protein, genetically identical organisms living in a constant environment will contain different amounts of that particular protein, resulting in different phenotypes. This phenomenon is known as "phenotypic noise." In bacterial systems, previous studies have shown that, for specific genes, both transcriptional and translational processes affect phenotypic noise. Here, we focus on how the promoter regions of genes affect noise and ask whether levels of promoter-mediated noise are correlated with genes' functional attributes, using data for over 60% of all promoters in Escherichia coli. We find that essential genes and genes with a high degree of evolutionary conservation have promoters that confer low levels of noise. We also find that the level of noise cannot be attributed to the evolutionary time that different genes have spent in the genome of E. coli. In contrast to previous results in eukaryotes, we find no association between promoter-mediated noise and gene expression plasticity. These results are consistent with the hypothesis that, in bacteria, natural selection can act to reduce gene expression noise and that some of this noise is controlled through the sequence of the promoter region alone.

The mammalian gut harbors a dense microbial community interacting in multiple ways, including horizontal gene transfer (HGT). Pangenome analyses established particularly high levels of genetic flux between Gram-negative Enterobacteriaceae. However, the mechanisms fostering intraenterobacterial HGT are incompletely understood. Using a mouse colitis model, we found that Salmonella-inflicted enteropathy elicits parallel blooms of the pathogen and of resident commensal Escherichia coli. These blooms boosted conjugative HGT of the colicin-plasmid p2 from Salmonella enterica serovar Typhimurium to E. coli. Transconjugation efficiencies of ∼100% in vivo were attributable to high intrinsic p2-transfer rates. Plasmid-encoded fitness benefits contributed little. Under normal conditions, HGT was blocked by the commensal microbiota inhibiting contact-dependent conjugation between Enterobacteriaceae. Our data show that pathogen-driven inflammatory responses in the gut can generate transient enterobacterial blooms in which conjugative transfer occurs at unprecedented rates. These blooms may favor reassortment of plasmid-encoded genes between pathogens and commensals fostering the spread of fitness-, virulence-, and antibiotic-resistance determinants.

A number of recent experiments at the single-cell level have shown that genetically identical bacteria that live in homogeneous environments often show a substantial degree of phenotypic variation between cells. Often, this variation is attributed to stochastic aspects of biology—the fact that many biological processes involve small numbers of molecules and are thus inherently variable. However, not all variation between cells needs to be stochastic in nature; one deterministic process that could be important for cell variability in some bacterial species is the age of the cell poles. Working with the alphaproteobacterium Methylobacterium extorquens, we monitored individuals in clonally growing populations over several divisions and determined the pole age, cell size, and interdivision intervals of individual cells. We observed the high levels of variation in cell size and the timing of cell division that have been reported before. A substantial fraction of this variation could be explained by each cell's pole age and the pole age of its mother: cell size increased with increasing pole age, and the interval between cell divisions decreased. A theoretical model predicted that populations governed by such processes will quickly reach a stable distribution of different age and size classes. These results show that the pole age distribution in bacterial populations can contribute substantially to cellular individuality. In addition, they raise questions about functional differences between cells of different ages and the coupling of cell division to cell size.

Background: The essential Escherichia coli gene ygjD belongs to a universally conserved group of genes whose function has been the focus of a number of recent studies. Here, we put ygjD under control of an inducible promoter, and used time-lapse microscopy and single cell analysis to investigate the phenotypic consequences of the depletion of YgjD protein from growing cells.
Results: We show that loss of YgjD leads to a marked decrease in cell size and termination of cell division. The transition towards smaller size occurs in a controlled manner: cell elongation and cell division remain coupled, but cell size at division decreases. We also find evidence that depletion of YgjD leads to the synthesis of the intracellular signaling molecule (p)ppGpp, inducing a cellular reaction resembling the stringent response. Concomitant deletion of the relA and spoT genes - leading to a strain that is uncapable of synthesizing (p)ppGpp - abrogates the decrease in cell size, but does not prevent termination of cell division upon YgjD depletion.
Conclusions: Depletion of YgjD protein from growing cells leads to a decrease in cell size that is contingent on (p)ppGpp, and to a termination of cell division. The combination of single-cell timelapse microscopy and statistical analysis can give detailed insights into the phenotypic consequences of the loss of essential genes, and can thus serve as a new tool to study the function of essential genes.

In the Ethiopian Rift Valley, there are two main concerns about drinking water: fluoride and fecal contamination. OSHO (an Ethiopian NGO) works on a defluoridation project with household and community filters to remove fluoride from drinking water. The project area includes seven villages, with more than 300 household filters in use and one community filter.
This is the first study on the impact of household defluoridation filters in rural Ethiopian microbial water quality. The visited villages use different water sources, such as surface water, boreholes, windmills or dug wells. Microbial contamination is present at the sources, and in much higher extent in the households.
Compact Dry plates (Nissui Ltd, Japan) were uses to detect E.coli, total coliforms and Enterococci as fecal indicator organisms. The method is valid for detection and enumeration of microbial water contamination even under the challenging conditions of rural Ethiopia. The bacterial growth in dependence of incubation temperature showed similar counts above 30°C, which leads to representative results even if the power supply is interrupted. It was compared to standard methods (Colilert, IDEXX, and Petrifilm, 3M) and did not show significant differences.
The household filters have an overall positive impact on fecal indicator organisms in all studied villages; nevertheless the contamination level is very high. The main contamination was taking place between the source and the inlet, respectively the jerrycan. There were no differences in drinking water quality found in a glass from household filter or community filter. The microbial inactivation of copper was tested in the lab and in the field, but no general improvement of the water quality found.
Microbial contamination levels are alarmingly high in all studied households, and measures have to be taken enhance water quality. Hygiene and sanitation are very poor or absent in the area, and diarrheal diseases widespread. Technical possibilities to improve the situation are chlorination of the filters and source water, replacement of sand filter with candle filter,
installation of sanitation facilities. They will not be sustainable without awareness creation and education of the interrelation between water, sanitation, hygiene and health.

Measuring the efficiency of virus disinfection with quantitative PCR (qPCR) has been criticized as inadequate due to the production of false-positive signals. Such a claim, however, presupposes an understanding of the theoretical qPCR response. Many studies have assumed that the loss in qPCR signal upon disinfection should equal the loss in infectivity, without accounting for the fact that qPCR typically assays only a fraction of the viral genome. This study aimed to develop a theoretical framework to relate viral infectivity with genome damage measured by qPCR. The framework quantified damage to the entire genome based on the qPCR amplification of smaller sections, assuming single-hit inactivation and a Poissonian distribution of damage. The framework was tested and modified using UV₂₅₄ inactivation studies with bacteriophage MS2 (culturing and qPCR of approximately half the genome). Genome regions showed heterogeneous sensitivities to UV₂₅₄ treatment, thus deviating from the assumption of Poissonian damage. We offered two modifications to account for these deviations and confirmed that the qPCR-based framework accurately estimated virus infectivity. This framework offers the potential to monitor the infectivity of viruses that remain nonculturable (norovirus). While developed for UV₂₅₄-inactivated virus, the framework should apply to any disinfection technique that causes inactivation via single genomic lesions.

Virulence factors generally enhance a pathogen's fitness and thereby foster transmission. However, most studies of pathogen fitness have been performed by averaging the phenotypes over large populations. Here, we have analyzed the fitness costs of virulence factor expression by Salmonella enterica subspecies I serovar Typhimurium in simple culture experiments. The type III secretion system ttss-1, a cardinal virulence factor for eliciting Salmonella diarrhea, is expressed by just a fraction of the S. Typhimurium population, yielding a mixture of cells that either express ttss-1 (TTSS-1⁺ phenotype) or not (TTSS-1⁻ phenotype). Here, we studied in vitro the TTSS-1⁺ phenotype at the single cell level using fluorescent protein reporters. The regulator hilA controlled the fraction of TTSS-1+ individuals and their ttss-1 expression level. Strikingly, cells of the TTSS-1⁺ phenotype grew slower than cells of the TTSS-1⁻ phenotype. The growth retardation was at least partially attributable to the expression of TTSS-1 effector and/or translocon proteins. In spite of this growth penalty, the TTSS-1⁺ subpopulation increased from <10% to approx. 60% during the late logarithmic growth phase of an LB batch culture. This was attributable to an increasing initiation rate of ttss-1 expression, in response to environmental cues accumulating during this growth phase, as shown by experimental data and mathematical modeling. Finally, hilA and hilD mutants, which form only fast-growing TTSS-1⁻ cells, outcompeted wild type S. Typhimurium in mixed cultures. Our data demonstrated that virulence factor expression imposes a growth penalty in a non-host environment. This raises important questions about compensating mechanisms during host infection which ensure successful propagation of the genotype.

When E. coli is grown in long-term glucose limited continuous cultures it could be shown that a stable acetate cross-feeding polymorphism evolves repeatedly. However, the processes prior to genetic differentiation are still unknown. In this study we analyzed the gene expression of different genes involved in metabolism. We used E. coli MG1655 clones containing a plasmid with different promoter-GFP fusions. They were grown in continuous cultures and GFP expression was measured after ~5 generations to minimize the probability of mutations. We were interested in whether an isogenic population divides into two different acetate cross-feeding phenotypes. Most analyzed genes (aceB, ackA, mglB, mlc, pck, ptsG) showed variation in gene expression but no clear evidence for different cross-feeding phenotypes. In some experiments, the expression profile of acs (acetyl-CoA synthetase) suggested the occurrence of different phenotypic subpopulations. But also other mechanism than acetate cross-feeding could cause the heterogeneity in gene expression.

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.

When isogenic populations of bacteria are killed by antibiotics, the decrease of living cells usually follows an exponential curve. This implies that while most of the cells die in the very beginning, some can survive for long times. Those differences in survival time are due to a distribution of non-­‐genetic resistances between the individual cells. It could be shown that the rate of killing is proportional to the growth rate of bacterial cultures that were grown under different conditions. However, it was unknown if differences in growth rates between single cells can affect the survival time. Here we show that differences in interdivision times between single Caulobacter crescentus cells before the administration of ampicillin influence the survival time under antibiotic stress. Cells that grow slower survive antibiotic stress longer. This could have implications on the development of new antibiotics, particularly for diseases where single surviving cells are a major problem.

Biofilms are communities of surface-attached, matrix-embedded microbial cells that can resist antimicrobial chemotherapy and contribute to persistent infections. Using an Escherichia coli biofilm model we found that exposure of bacteria to subinhibitory concentrations of ribosome-targeting antibiotics leads to strong biofilm induction. We present evidence that this effect is elicited by the ribosome in response to translational stress. Biofilm induction involves upregulation of the polysaccharide adhesin poly-β-1,6-N-acetyl-glucosamine (poly-GlcNAc) and two components of the poly-GlcNAc biosynthesis machinery, PgaA and PgaD. Poly-GlcNAc control depends on the bacterial signalling molecules guanosine-bis 3', 5'(diphosphate) (ppGpp) and bis-(3'-5')-cyclic di-GMP (c-di-GMP). Treatment with translation inhibitors causes a ppGpp hydrolase (SpoT)-mediated reduction of ppGpp levels, resulting in specific derepression of PgaA. Maximal induction of PgaD and poly-GlcNAc synthesis requires the production of c-di-GMP by the dedicated diguanylate cyclase YdeH. Our results identify a novel regulatory mechanism that relies on ppGpp signalling to relay information about ribosomal performance to the Pga machinery, thereby inducing adhesin production and biofilm formation. Based on the important synergistic roles of ppGpp and c-di-GMP in this process, we suggest that interference with bacterial second messenger signalling might represent an effective means for biofilm control during chronic infections.

Genetically identical populations of unicellular organisms often show marked variation in some phenotypic traits. To investigate the molecular causes and possible biological functions of this phenotypic noise, it would be useful to have a method to identify genes whose expression varies stochastically on a certain time scale. Here, we developed such a method and used it for identifying genes with high levels of phenotypic noise in Salmonella enterica ssp. I serovar Typhimurium (S. Typhimurium). We created a genomic plasmid library fused to a green fluorescent protein (GFP) reporter and subjected replicate populations harboring this library to fluctuating selection for GFP expression using fluorescent-activated cell sorting (FACS). After seven rounds of fluctuating selection, the populations were strongly enriched for promoters that showed a high amount of noise in gene expression. Our results indicate that the activity of some promoters of S. Typhimurium varies on such a short time scale that these promoters can absorb rapid fluctuations in the direction of selection, as imposed during our experiment. The genomic fragments that conferred the highest levels of phenotypic variation were promoters controlling the synthesis of flagella, which are associated with virulence and host–pathogen interactions. This confirms earlier reports that phenotypic noise may play a role in pathogenesis and indicates that these promoters have among the highest levels of noise in the S. Typhimurium genome. This approach can be applied to many other bacterial and eukaryotic systems as a simple method for identifying genes with noisy expression.

The majority of bacterial members in the free-living microbial world is not accessible with conventional microbiological tools, such as plating. Members of this “unseen majority” are typically small in size and not easy or even impossible to cultivate. Knowledge on their growth properties is still largely inexistent, although lots of genetic information has been acquired recently using cultivation-independent methods. In this thesis, a novel cultivation approach, with natural freshwater as substrate and flow cytometry (FCM) as monitor tool, was applied to explore this “unseen majority”. [...]

Der Grossteil der frei lebenden mikrobiellen Flora ist nicht zugänglich mit konventionellen mikrobiellen Methoden wie z.B. Plattierung. Diese „unsichtbare Mehrheit“ besteht typischerweise aus sehr kleinen Zellen, die nicht einfach oder sogar unmöglich zu kultivieren sind. Kenntnisse über ihr Wachstumsverhalten sind grösstenteils noch nicht vorhanden, obwohl durch kultivierungsunabhängige Methoden in den letzten Jahren genetische Information über diese Mikroorganismen gesammelt wurde. Um diese „unsichtbare Mehrheit“ zu erforschen, wurde in dieser Doktorarbeit ein neuer Kultivierungsansatz mit natürlichem Süsswasser als Substrat und Durchflusszytometrie (FCM) als Messinstrument angewandt. [...]