2022 Meetings on Microbial Population Biology
We look forward to bringing the Microbial Population Biology community back together in the Summer of 2022 at the Max Planck Institute for Evolutionary Biology Plön.
Organizers: Alita Burmeister (Yale University), Andrew Farr (MPI for Evolutionary Biology), Fatima Aysha Hussain (MIT), Tanush Jagdish (Harvard), Clara Moreno-Fenoll (ESPCI-PSL), Loukas Theodosiou (MPI for Evolutionary Biology)
Workshop I - Communities and Coevolution, May 16 - 20, 2022
Schedule and Abstracts Below
Workshop II - Evolutionary Dynamics and Processes, May 30 - June 3
Schedule and Abstracts Coming Soon
Practical Information: https://workshops.evolbio.mpg.de/event/43/page/6-practical-information
Once you land in Hamburg, how can you reach Plön?
Once you reach Hamburg airport, press the link https://www.evolbio.mpg.de/15109/directions and follow the instructions to get to the Max Planck Institute for Evolutionary Biology.
Check-In, have a coffee
Mobile genetic elements (MGEs), such as transposons and insertion sequences, propagate within bacterial genomes, but persistence times in individual lineages are short. For long-term survival, MGEs must continuously invade new hosts by horizontal transfer. Theoretically, MGEs that persist for millions of years in single lineages, and are thus subject to vertical inheritance, should not exist. Here I draw attention to an exception — a class of MGE termed REPIN. REPINs are non-autonomous MGEs whose duplication depends on non-jumping RAYT transposases. Comparisons of REPINs and typical MGEs show that replication rates of REPINs are orders of magnitude lower, REPIN population size fluctuations correlate with changes in available genome space, REPIN conservation depends on RAYT function, and REPIN diversity accumulates within host lineages. These data lead to the hypothesis that REPINs form enduring, beneficial associations with eubacterial chromosomes. Given replicative nesting, the hypothesis predicts conflicts arising from the diverging effects of selection acting simultaneously on REPINs and host genomes. Evidence in support comes from patterns of REPIN abundance and diversity in two distantly related bacterial species. Together this bolsters the conclusion that REPINs are the genetic counterpart of mutualistic endosymbiotic bacteria.
Microbial communities harbor almost unimaginable complexity at all levels of organization. Vast genomic diversity is present even within a single taxon. Diverse genomes across taxa encode complex regulatory programs that modulate physiological traits from chemotaxis to metabolic processes. From these traits emerge interactions between taxa that depend on abiotic factors. Together, these processes drive eco-evolutionary dynamics across multiple timescales. Which of these many aspects of a community must we understand and why? Are some properties of a community more important than others? Important in what sense? I propose that one path forward is to focus on community function, specifically, the emergent metabolite flows responsible for generating energy and biomass in the collective. From this perspective, I suggest that the important physiological, ecological, or evolutionary processes are those that impact and sustain community function. The problem then becomes decoding how genomic, physiological and ecological complexity gives rise to key metabolite flows in the community. With inspiration from physics, we approach this question by measuring function across diverse ensembles of communities, describing metabolite flows phenomenologically, and learning the salient features of the community and control these flows statistically (iScience, 2022). I present two recent studies employing this philosophy. First, using denitrification as a model process, we show that the dynamic flux of nitrate and nitrite through a community can be predicted simply from knowledge of the genes each strain possesses (Cell, 2022). Second, using communities of algae and bacteria that cycle carbon, we show that the carbon cycling rate depends crucially on the metabolic capabilities of the taxa present (PNAS, 2021). These studies show that simple mappings exist from genes to traits and traits to community function. I propose extending this approach to studying communities in the wild, rationally designing functional consortia, and connecting evolutionary dynamics to community metabolism.
Microbial growth relies on the presence of several nutrients, including elemental nutrients such as carbon and nitrogen, as well as complex nutrients like vitamins and amino acids. Evidence from biogeochemistry, especially in aquatic environments, suggests that multiple nutrients may be simultaneously rare in nature and therefore limit growth. However, we poorly understand how this co-limitation affects microbial growth, physiology, and evolution. This is especially important in the context of multi-species communities, where pervasive cross-feeding of many nutrients leads to the coevolution of nutrient limitation between species. We introduce a theoretical framework for understanding and quantifying nutrient limitation, which we apply to an evolutionary model to show how limitation for multiple nutrients evolves. We find that evolution can spontaneously drive nutrient uptake to match environmental availability, leading to co-limitation of multiple nutrients. We show how this result depends on the interaction between nutrients and supply of adaptive mutations. In particular, we demonstrate how nutrient limitation coevolves across species in cross-feeding communities. This prediction is consistent with observed correspondences between the elemental composition of microbes and their environments. It suggests that co-limitation may be a generic property of microbial communities due to evolutionary forces.
Communities of interacting microbes perform fundamental processes on Earth. These processes arise from a dense network of interactions between individual cells. Most microbial communities are spatially structured systems, where cells move little, thus interactions occur mostly between cells close in space. Therefore, the spatial arrangement of different species can affect the processes that the whole community performs. Our goal is to uncover how the local interactions between cells determine community-level processes. To do so, we look at synthetic bacterial communities under the microscope at a resolution that allows me to observe both the individual cells and the community as a whole. We measure properties of the single cells, like their growth and their phenotype, and we use mathematical modeling to uncover how these individual-level properties determine community-level properties.
Just as microbes in our guts digest the complex fibers we eat, marine bacteria break down and digest the complex forms of organic matter that phyto- and zoo-plankton produce in the surface ocean. This biological process is key for life on the planet, as it returns carbon back to the atmosphere and balances the elemental cycles that sustain life. Complex organic matter is made up of long polymer chains packed in matrices, which cannot be directly absorbed by cells. Instead, bacteria need to first excrete enzymes that digest polymers into smaller, soluble molecules, a process that triggers a surprising cascade of microbial interactions that determine the mode and tempo of carbon consumption. In this talk I will focus on three key type of interactions that define this process: the transfer of carbon between different species of bacteria occupying well-defined metabolic guilds, the awakening of dormant viruses in the genomes of polymer degraders, and the emergence of cooperative, multicellular cell structures within which polymer-degrading organisms divide metabolic labor. Throughout my talk, I will highlight how studying these natural, polymer-degrading ecosystems can inform emerging efforts in microbiome engineering.
Bacteria derived from polymicrobial urinary tract infections (UTIs) together with commensal urinary residents can be viewed as small ecosystems. By measuring pair-wise interactions we obtained a unique insight in the ecological interactions of these microbiome members. We find that many of these bacterial interactions affect the immediate tolerance to antibiotics, as well as their ability to evolve antibiotic resistance. This shows that environmental circumstances have an effect on both the ecology and the evolution of infection-related bacterial consortia.
Jeroen Meijer, Paulien Hogeweg, Paul Rainey, Bas Dutilh.
Bacteriophages are important players in shaping microbial communities, yet their abundance and dynamics in highly diverse, natural environments remain poorly understood. In particular, many different genotypes of a single phage can be present, but their relevance for viral dynamics and ecological interactions is not currently known. Here, we explore this question by analyzing shotgun metagenomes from 10 compost-derived microbial communities that were tracked in parallel over a period of 1 year, where size-filtered viral fractions were periodically collected, pooled and redistributed between different mesocosms to allow viral migration between communities. By comparing viromes and full community metagenomes we recovered thousands of viral sequences, which revealed both parallel and divergent viral dynamics between the 10 communities. In a subset of communities and time points a single, previously undescribed Schitoviridae bacteriophage accounted for up to 74% of the total community metagenome (i.e. combined cellular and viral sequences), indicating massive viral outbreaks of a single bacteriophage. Tracking polymorphisms of the bacteriophage and taxonomic profiling of the full microbial communities showed that different mesocosms were initially dominated by a single bacteriophage strain which transferred and settled in other communities through the experimental protocol, and that massive outbreaks only occurred in a specific community type. In summary, we here describe viral outbreaks of (to the best of our knowledge) unparalleled magnitude of a single bacteriophage strain, further uncovering the relevant scales of bacteriophage dynamics in complex communities.
In this talk I'll provide a survey of studies from my research program all aimed to thinking about higher-order interactions in microbial and social systems. In doing so, I propose the question of whether the science of interactions is truly headed towards being a generalizable physics, that would apply to microbial communities and other sets of actors and parcels of information.
Microbial communities provide an excellent study system to explore the integration of ecology and evolution. At one end of the spectrum, the composition of microbial communities (assessed at broad taxonomic levels) dramatically shifts in response to environmental changes. At the other end, laboratory studies demonstrate the potential for rapid evolution in response to the similar environmental changes. In between these two extremes, very closely related bacterial and fungal strains coexist in natural communities, and this standing variation results in allele frequency shifts within microbial taxa. New advances in microbial population genomics allow us to investigate these blurry eco-evo boundaries. I will present our recent approaches to investigate ecological and evolutionary processes simultaneously in soil microbial communities and solicit feedback about new directions.
A longstanding question in Ecology is which drivers are responsible for the difference in abundance of species within a community. While some species are relatively abundant, many others are rare. Theoretical models have been useful to investigate the drivers of community dynamics. In particular, models that consider the death, birth, and immigration of individuals have been used extensively. For example, models, where the rates are assumed neutral have shown that stochasticity alone can have a strong influence. Understanding the effect of differential adaptation (via growth and death rate differences) has been more challenging. Recently, we have overcome some of these difficulties to study the effect of differential adaptation to the environment in large and diverse communities. For this, we have relied on simulations and analytic tools to compute the distribution of abundances. Then, for each microbial type, we have estimated quantities such as the occurrence frequency and the mean and variance of the abundance. We have looked into the occurrence-abundance pattern often reported in host-associated microbiomes and, more generally, microbial communities. Interestingly, we observe that large immigration and biodiversity -- common in microbial communities -- lead to such patterns, regardless of whether the microbes are neutrally or differentially adapted. This theoretical result has important implications for interpreting and testing empirical data at the community and population levels.
In many natural environments, microorganisms self-assemble around heterogeneously distributed resource patches. The growth and collapse of populations on resource patches can unfold within spatial ranges of a few hundred micrometers or less, making such microscale ecosystems hotspots of biological interactions and nutrient fluxes. Despite the potential importance of patch-level dynamics for the large-scale evolution and function of microbial communities, we have not yet been able to delineate the ecological processes that control natural populations at the microscale. Here, we addressed this challenge in the context of microbially-mediated degradation of particulate organic matter by characterizing the natural marine communities that assembled on over one thousand individual microscale chitin particles. Through shotgun metagenomics, we found significant variation in microscale community composition despite the similarity in initial species pools across replicates. Strikingly, a subset of particles was highly populated by rare chitin-degrading strains; we hypothesized that their conditional success reflected the impact of stochastic colonization and growth on community assembly. In contrast to the conserved functional structures that emerge in ecosystems at larger scales, this taxonomic variability translated to a wide range of predicted chitinolytic abilities and growth returns at the level of individual particles. We found that predation by temperate bacteriophages -- especially of degrader strains that initiate community assembly on chitin particles -- was a significant contributor to the variability in the bacterial compositions and yields observed across communities. Our study suggests that initial stochasticity in assembly states at the microscale, amplified through spatially structured biotic interactions, may have significant consequences for the coexistence, evolution, and function of diverse bacterial and viral populations at larger scales.
Microbes affect global nutrient cycles, the development of our immune system, and resource acquisition and stress responses of multicellular organisms. In a rapidly changing world, we would like to predict the ecological and evolutionary trajectories of populations and communities. Recent efforts have shown that microbial community assembly is often fairly predictable at a functional level, and that this predictibility can emerge from simple metabolic contraints. However, even in simple systems, with strong selection and a simplified ecology, evolutionary change can increase ecological complexity leading to distinct outcomes. Here, we present the results of a year-long evolutionary experiment with twelve replicate lines evolving from the same simple community self-assembled in minimal media with glucose as the only carbon source. We find that community assembly is robust to evolutionary change, despite changes in phenotypes of comprising species. In this system, selection for faster growth rate and increased metabolic efficiency affects the emergent metabolic structure of our communities in a reproducible and therefore predictable manner.
Community assembly can reach different outcomes depending on the history of species arrival, a phenomenon known as a priority effect. The study of priority effects has traditionally focused on the ecological consequences of arrival history, often assuming that evolution occurs too slowly to influence community assembly. However, recent models suggest that accounting for local adaptation would alter predictions of community assembly outcomes. We used a series of fully factorial experiments to ask whether previous experiment in an environment (the tomato plant phyllosphere) improved the abilities of bacterial species to invade established communities and/or to resist invasion. We found that prior adaptation to the environment could change the directionality and magnitude of priority effects, but these changes were not always advantageous for the locally adapted species. Further examination revealed that this result was mediated by the evolution of a slower life history, which improved colonization in isolation, but increased vulnerability to timing in competitive conditions. Our study supports a role for eco-evolutionary processes in priority effects, showing that selection can generate traits that feed back to influence community ecology and vice versa.
Bacteria have the potential for rapid evolution thanks to short generation times, large population sizes, and mechanisms for generating genetic variation. But in the wild they live in open communities made up of hundreds of species and exposed to a constant rain of potential new colonists. This talk discusses the potential consequences of natural diversity for bacterial evolution and outlines experimental approaches for tracking evolution in the wild.
Microbial communities in aquatic habitats, ranging from small fresh water streams to the vast oceans, are confronted with a relatively new (from an evolutionary point of view), man-made and omnipresent carbon source: plastics. Research has shown that plastic particles in marine ecosystems are rapidly colonized by microorganisms, and that microbial community in the so-called plastisphere has a different composition than the surrounding seawater. We exposed a natural marine microbial community to different types of plastics in laboratory conditions, to enrich for microorganisms with the metabolic capability to degrade those plastics. The presence of plastic induced a shift in the composition of the microbial community, showing the adaptation when supplied with different types of plastics. Moreover, the microbial community evolved differently, depending on the type of plastics and the amount of nutrients supplied. We furthermore hypothesised that the enriched microbial community that colonizes the plastic, also degrades the plastic. By using a trickling filter, microbial biofilm formation on plastic particles was stimulated. Furthermore, this design allowed us to separate the bacteria preferring a sedentary lifestyle in the biofilm from the planktonic bacteria in the effluent. The microbial community in effluent and biofilm evolved differently over time, as one the one hand, attached bacteria are in close proximity of the polymer, and on the other hand, the released mono- and oligomer compounds attract hydrocarbonoclastic genera. After four weeks, the microbial community in the effluent of the trickling filters already had a remarkable high abundance of Alcanivorax (up to 80%), a genus well-known for oil degradation. This genus was also present in the biofilm, but in lower abundance (up to 20%). Additionally, differences in presence of other genera was seen in the effluent versus the biofilm. Further research should elucidate whether this different microbial community composition can be linked to the different steps in the biodegradation process of polymers.
Understanding how microbial traits affect the evolution and functioning of microbial communities is fundamental for improving the management of harmful microorganisms, while promoting those that are beneficial. Decades of evolutionary ecology research has focused on examining microbial cooperation, diversity, productivity and virulence but with one crucial limitation. The traits under consideration, such as public-good production and resistance to antibiotics or predation, are often assumed to act in isolation. Yet, in reality multiple traits frequently interact, which can lead to unexpected and undesired outcomes for the health of macroorganisms and ecosystem functioning. This is because many predictions generated in a single-trait context aimed at promoting diversity, reducing virulence or controlling antibiotic resistance can fail for systems where multiple traits interact. In this talk I will provide examples of this phenomenon and argue that synthetic microbial communities and multi-trait mathematical models are powerful tools for managing the beneficial and detrimental impact of microbial communities.
Multispecies bacterial communities often perform functions arising from the interactions among their members. These community functions can, in principle, be improved via directed evolution. Yet, current selection methods for improved community function have shown limited success. One reason for this limited success might be that methods of community selection rely on the assumption that bacterial communities are individuals in selection. However, competition among species members within these communities is pervasive and, as a consequence, selection at the level of member species can override selection at the community level. Here, we have begun designing an artificial selection strategy based on evolutionary individuality first, improved function second. Specifically, our aim is to simulate a community selection method driving the transition in individuality by decreasing competition within communities and increasing competition between them. Once within-community competition is diminished, we will select the transitioned communities for improved community function using classic breeding methods. Even though selection for improved function might reverse the transition in individuality, we hypothesise that communities whose transition is irreversible will outcompete those in which within-community competition reemerges. It remains to be seen whether our hypothesis holds. We hope to have enough data for its verdict on time for the workshop.
Mutualisms, or interactions between species where both provide a net fitness benefit to each other, are numerous and ecologically relevant. Presumably, these interactions affect the evolution of both species, possibly resulting in coevolution where evolutionary changes in one causes selection for changes in the other species. However, rigorous studies of coevolution in mutualisms have been uncommon, have often focused on only one of the species involved, have focused on highly-evolved mutualisms, and rarely on microorganisms. In this presentation, I will describe our attempts to test whether or not coevolution is a common feature of evolution in the first 5000 generations of adaptation to a new mutualism. The mutualism we studied is composed of the sulfate-reducing bacteria Desulfovibrio vulgaris, and the archaeon Methanococcus maripaludis. These species were put in an environment where there was no sulfate, and the only means for survival for both species is to cooperatively ferment lactate, passing electrons via hydrogen to provide energy to M. maripaludis and maintain favorable growth conditions for D. vulgaris. Similar species and interactions play a fundamental role in carbon degradation and methane production in environments such as rice paddies, cow rumens, and anaerobic digestors. In addition, efficient transfer of hydrogen between the species is in the best interest of both parties, suggesting few, if any opportunities for cheating. We tested whether these species have coevolved using timeshift experiments, where the fitness of a population with partners from its past and future is compared. In addition, we have sequenced the metagenomes of many of these communities over time, and the prevalence of evolutionary dynamics resembling expected coevolution will be discussed.
Predation drives the microbial world, but trophic interactions among microbes are poorly understood. One charismatic predator, the social soil bacterium Myxococcus xanthus, is a model system for studying cooperation and aggregative multicellularity. It has been studied in bi-trophic but never tri-trophic systems, despite the proposed importance for interactions with predators in the evolution of aggregative traits. Given the complexity of natural soil communities, it seems unlikely that a bacterium functions as an apex predator, yet it has rarely been studied relative to its own potential predators and its actual role in its native communities is poorly understood. Our previous work indicates that M. xanthus is considered an unpalatable food source by the nematode Caenorhabditis elegans, suggesting that the bacterium possesses some kind of anti-predator defenses. To investigate this further, we used a novel model food web comprising the bacterivorous nematode Pristionchus pacificus as an apex predator, M. xanthus as a mesopredator, and Escherichia coli as a basal prey to examine how M. xanthus’s social traits adapted to interactions with these two organisms and whether the mesopredator experienced evolutionary tradeoffs in adapting to each. Over the course of an evolution experiment, M. xanthus populations increased in fitness in environments containing E. coli, P. pacificus, or both. Most striking was the clear environment-specific modulation of phenotypes associated with M. xanthus’s well-studied ability to, upon starvation, aggregate into fruiting bodies and sporulate. This suggests that aggregation and fruiting body formation are not simply responses of this bacterium to nutrient levels but may also play a role in defense against predators. Further exploration may yield insights into the evolutionary origin of these traits, as well as provide a bridge to studies of predation avoidance traits in larger organisms.
We analyze properties of experimental microbial time series, from plankton and the human microbiome, and investigate whether stochastic generalized Lotka-Volterra (gLV) models could reproduce those properties. We show that this is the case when the noise term is large and a linear function of the species abundance, while the strength of the self-interactions varies over multiple orders of magnitude. We stress the fact that all the observed stochastic properties can be obtained from a logistic model, that is, without interactions, even the niche character of the experimental time series. Linear noise is associated with growth rate stochasticity, which is related to changes in the environment. This suggests that fluctuations in the sparsely sampled experimental time series may be caused by extrinsic sources. Additionally we show that adding a global maximal capacity to gLV models lead to heavy-tailed abundance distributions.
Stressful water-limited soils are typically covered by scattered plant patches that generate a mosaic of low-productive habitats, which are almost devoid of plants and comparatively driven by abiotic filters, interspersed with high-productive habitats comparatively driven by biotic interactions. Such ecosystems provide an ideal setting to disentangle which processes dominate the community assembly of soil microbiota and beyond, how community composition and diversity impact microbial-driven ecosystem functions. The talk will review, by combining metagenomics and phylogenetics, the abiotic and biotic processes that structure soil microbial communities in drylands, and how they leave specific phenotypic and phylogenetic signatures. The talk will also show how tracking microbial evolutionary legacies and exploring communities in terms of anciently- and recently-divergent lineages may enhance the predictions of key ecosystem functions, such as decomposition and nutrient cycling.
Poor predictability of stable microbial colonization undermines our ability to harness probiotics and phage therapy in human health applications. Person-specific diversity contributes to this unpredictability; it is unclear how microbes colonize and evolve on individuals to create microbiomes with unique compositions, in which most genetic variation occurs within species boundaries. Bacteria-phage dynamics are implicated in promoting microbiome diversity by generating species- and strain-level population fluctuations. Yet, much remains unknown about the assembly and structure of phage populations in human ecosystems, and consequently their role in stable microbial colonization. Sebaceous skin offers a tractable model to unravel phage population dynamics due to its low complexity, ease of temporospatial sampling, and selective conduciveness to colonization at different developmental stages, as biological changes in the human host cause periods of ecological disturbance. Here, we use amplicon sequencing to examine the coevolutionary dynamics of the highly abundant and ubiquitous skin commensal Cutibacterium acnes and its phage. We collect facial swabs from 35 healthy subjects aged 5 – 60 on short (daily, weekly, or monthly) and long (every 6 months) timescales. We detect C. acnes phage at multiple developmental stages on the majority of subjects. Across individuals we observe a range of population structures; some dominated by a single variant while others are more even. Typically, we find multiple variants on an individual, often with nearly identical or distantly related variants coexisting, suggesting acquisition of pre-existing variants from the environment and on-person evolution. Most variants are person-specific, but some are shared. Independent of age, we find multiple cases of variants persisting on short and long timescales. This finding highlights the need for phylogenetic reconstruction at the genome-level to confidently distinguish between variant sharing and putative transmission events.
Microbial communities are incredibly diverse. Molecular techniques such as ‘omics’ have uncovered a vast number of microbial ‘species’ in communities from natural environments. Yet, the ecological and evolutionary processes originating this diversity remain understudied. This study investigated the ecological and evolutionary forces by which new bacterial ‘species’ emerge and coexist in communities. We focused on a commensal interaction between two bacterial species in which Acinetobacter cross-feeds resources to Pseudomonas. We evolved in parallel four experimental replicates of species growing in isolation or together in consortia for 200 generations. After only 60 generations, Pseudomonas diversified into two morphotypes that coexisted until the end of the experiment. Morphotypes differed from the ancestor and each other in one point mutation. Interestingly, the coexistence of mutants was only observed in the presence of Acinetobacter and not in isolation. To further confirm that the commensal interaction with Acinetobacter promoted the diversification of Pseudomonas, we performed invasion experiments, both in the presence and absence of Acinetobacter. In sum, by studying diversification through ecological coexistence theory, we showed that species interactions play an essential role in forming new bacterial ‘species’ in microbial communities.
Duhita G. Sant 1, Aysha L. Sezmis 1, Laura C. Woods 1 and Mike J. McDonald1* 1 School of Biological Sciences, Monash University, Monash, Australia * Correspondence should be addressed to: mike.mcdonald@monash.edu
Microbial communities comprised of many interacting species sustain all ecosystems and are essential for life. A major goal is to be able to intervene when microbiomes become dysfunctional. Phages have been recognized as potential tool for the deliberate modification of microbial communities. While the co-evolutionary dynamics of phage and their bacterial hosts are well studied, the impact of introducing a phage into a microbial community remains an open question. Here we propagated experimental populations of the T7-like bacteriophage øJB01 and its host Escherichia coli EPEC E2348/69 for 20 days in conditions where the phage and host co-evolved, or where only the phage was permitted to evolve, and then tested the capacity for the evolved phage to eradicate the ancestral host. We found that these two evolution treatments have trade-offs, with static-host phage evolving high infectivity and low host range while the evolving-host phage evolved relatively low infectivity with an expanded host range. Phage populations from both of these evolution treatments were equally better at repressing growth of focal host EPEC, however evolution of phage resistance was observed within 8 to 10 hours. Next, we tested the capacity of evolved phage populations to suppress the growth of the target host when present in a model microbial community of 8 strains of E. coli. We found that the phages can cause alterations in the community ecology and by tracking the frequency of the target host using amplicon sequencing and qPCR, we saw that the growth of the target host was strongly suppressed when phage was added in a healthy microbiota. Moreover, evolved phages could also perturb the frequency of a broad range of E. coli strains present in the community. We are speculating that the presence of other bacterial strains suppressed the evolution of phage resistance. Our results show that the context of the microbial community should be taken into account when using phage to modify microbiota.
Microbial communities in soil or the mammalian gut are constantly changing, as they first assemble and as species adapt to each other and to their environment. Being able to predict how these dynamics play out is crucial, as these communities greatly affect us and our environment. But since studying co-evolutionary dynamics in natural systems is extremely challenging, in my lab we study small bacterial communities as model systems. First, I will show how the interactions between four bacterial species depend on their environment: the harsher the environment, the more positively species interact. These positive interactions meant that community function - degradation of a pollutant - was greater when the species were together. We then allowed the community to evolve over almost a year and found that as our community stabilised, interactions between its members tended to become weaker, as did their degradation ability, but the community became more resistant to invasion by additional species. The final part of my talk will explore whether one can build new communities from scratch using artificial selection that have a greater and more evolutionarily stable function. We show that selection for increased community function is indeed possible, although complicated in practice. These results provide an intuition on how microbial species adapt to one another over ecological and evolutionary time-scales when left to co-evolve naturally, or if we strive to drive their selection toward a desired target.
Evolutionary dynamics can occur over similar time scales as ecological selection, meaning that there can be feedback between ecology and evolution. However, evidence of concordant eco-evolutionary selection often comes from in vitro studies, where there necessarily will be strong selection. Moreover, these studies have typically focussed on different focal traits meaning ecological and evolutionary dynamics are not directly comparable. Here, we quantify ecological and evolutionary responses to selection of the same trait measured both within and between species. We focus on siderophore production – these costly secretions are not only used to scavenge poorly soluble iron but also to detoxify environments polluted with other metals. In the context of detoxification, siderophores can benefit both the producer and nearby cells by preventing toxic metal uptake into the bacterial cell. We found that responses to copper-imposed selection within and between species were ultimately the same – intermediate levels were favoured – and occurred over similar time scales. Despite being a social trait, this represents the optimal strategy regardless of the social context. Our study unequivocally demonstrates that evolutionary selection can drive changes as rapidly as ecological selection.
Reciprocal interactions such as cooperation, parasitism, altruism, etc are strongly affected by population mixing and modes of transmission. However, the effect of population mixing on the evolutionary dynamics of prey-predator interactions remains largely unexplored. Hence, in a laboratory evolution experiment, we propagated bacterial predator-prey communities in two distinct transfer regimes. In the first regimen we mixed replicate populations periodically (horizontal transfer regime), and in the second treatment populations were not mixed (vertical transfer regime). To do so, we used Myxococcus xanthus as a generalist bacterial predator and Escherichia coli as a prey bacterium. Analysis of the evolved populations revealed that the prey populations from two regimens evolved different degrees of resistance to predation, and on average were more resistant to predation than their ancestors. Our results further demonstrate that prey from the horizontal regimen were under directional selection resulting in lesser phenotypic divergence within each population, and a higher degree of resistance to predation. Whereas in the vertical regimen, prey populations were under fluctuating selection resulting in higher phenotypic divergence in which isolates with both higher and lower degrees of resistance relative to ancestors were maintained. Surprisingly though, in contrary to our expectation, though predatory behaviour of evolved M. xanthus populations from both the regimens was different from each other, it was lower than their respective ancestors. Moreover, our results suggest that the intra-species competition plays an important role -if not more than the predatory pressure- during the evolution of prey bacteria. Together, we demonstrate that the population-mixing results in directional selection on prey bacteria (but not the predator), that selects for the evolution of increased resistance to predation over evolutionary time.
Microbial ecosystems are composed of multiple species in constant metabolic exchange. A pervasive interaction in microbial communities is metabolic cross-feeding. The metabolic burden of producing costly metabolites is distributed between community members, in some cases for the benefit of all interacting partners. In particular, amino acid auxotrophies generate obligate metabolic interdependencies in mixed populations and have been shown to produce a dynamic profile of interaction that depends upon nutrient availability. However, identifying the key components that determine the pair-wise interaction profile remains a challenging problem, partly because metabolic exchange has consequences on multiple levels, from allocating proteomic resources at a cellular level to modulating the structure, function, and stability of microbial communities. In this talk, we couple a resource allocation model into a population dynamics model to evaluate the effect of a range of amino acid concentrations and population structures on the susceptibility profile to different antibiotics. We validate our theoretical predictions using a synthetic model system consisting of Escherichia coli K12 strains with amino acid auxotrophies and metabolic interdependencies. Both our computational and experimental approaches conclude that drug susceptibility is contingent upon the interaction profile exhibited by microbial communities.
Authors: Josie Elliott, Bridget Watson, Edze Westra, Tiffany Taylor
CRISPR-Cas is an adaptive bacterial defence system that offers protection against foreign DNA, including phages. This antiviral system allows bacteria to acquire resistance to new infections, providing a powerful weapon in the evolutionary arms races that exist between bacteria and their phage. Despite these systems being widely distributed across bacteria, they are not universal, and the ecological and evolutionary drivers that determine their prevalence remains unknown. One theory is that CRISPR-Cas systems are maintained at low levels in bacterial populations through horizontal gene transfer (HGT) between hosts. However, the adaptive forces that maintain CRISPR-Cas following acquisition and the consequence for antagonistic coevolutionary dynamics between phage and bacteria is an open question. We modelled an HGT event by transferring a synthetic, modular, minimal version of the CRISPR-Cas system from the opportunistic pathogen Pseudomonas aeruginosa to the common soil bacterium Pseudomonas fluorescens, which lacks CRISPR-Cas. The rapid and reciprocal co-evolutionary dynamics between P. fluorescens and its phage phi-2 have become a well-studied model. We use an experimental evolution approach to explore how these carefully poised interactions between P. fluorescens and phi-2 are affected by the introduction of a newly acquired CRISPR-Cas system. This work will ultimately improve our understanding of how short-term changes, such as acquisition of bacterial defence systems like CRISPR-Cas, modulate classic arms race coevolutionary dynamics between bacteria and phage. Furthermore, this offers a model system to determine the long-term evolutionary dynamics that follow a CRISPR-Cas HGT event to a naïve host.