When increasing population density can promote the evolution of metabolic cooperation

The effect of cooperator recognition on competition among clones in spatially structured microbial communities

In spatially structured microbial communities, clonal growth of stationary cells passively generates clusters of related individuals. This can lead to stable cooperation without the need for recognition mechanisms. However, recent research suggests that some biofilm-forming microbes may have mechanisms of kin recognition. To explore this unexpected observation, we studied the effects of different types of cooperation in a microbial colony using spatially explicit, agent-based simulations of two interacting strains. We found scenarios that favor a form of kin recognition in spatially structured microbial communities. In the presence of a "cheater" strain, a strain with greenbeard cooperation was able to increase in frequency more than a strain with obligate cooperation. This effect was most noticeable in high density colonies and when the cooperators were not as abundant as the cheaters. We also studied whether a polychromatic greenbeard, in which cells only cooperate with their own type, could provide a numerical benefit beyond a simple, binary greenbeard. We found the greatest benefit to a polychromatic greenbeard when cooperation is highly effective. These results suggest that in some ecological scenarios, recognition mechanisms may be beneficial even in spatially structured communities.

Interspecific interactions facilitate keystone species in a multispecies biofilm that promotes plant growth

Microorganisms colonizing plant roots co-exist in complex, spatially structured multispecies biofilm communities. However, little is known about microbial interactions and the underlying spatial organization within biofilm communities established on plant roots. Here, a well-established four-species biofilm model (Stenotrophomonas rhizophila, Paenibacillus amylolyticus, Microbacterium oxydans, and Xanthomonas retroflexus, termed as SPMX) was applied to Arabidopsis roots to study the impact of multispecies biofilm on plant growth and the community spatial dynamics on the roots. SPMX co-culture notably promoted root development and plant biomass. Co-cultured SPMX increased root colonization and formed multispecies biofilms, structurally different from those formed by monocultures. By combining 16S rRNA gene amplicon sequencing and fluorescence in situ hybridization with confocal laser scanning microscopy, we found that the composition and spatial organization of the four-species biofilm significantly changed over time. Monoculture P. amylolyticus colonized plant roots poorly, but its population and root colonization were highly enhanced when residing in the four-species biofilm. Exclusion of P. amylolyticus from the community reduced overall biofilm production and root colonization of the three species, resulting in the loss of the plant growth-promoting effects. Combined with spatial analysis, this led to identification of P. amylolyticus as a keystone species. Our findings highlight that weak root colonizers may benefit from mutualistic interactions in complex communities and hereby become important keystone species impacting community spatial organization and function. This work expands the knowledge on spatial organization uncovering interspecific interactions in multispecies biofilm communities on plant roots, beneficial for harnessing microbial mutualism promoting plant growth.

Metabolic efficiency reshapes the seminal relationship between pathogen growth rate and virulence

A cornerstone of classical virulence evolution theories is the assumption that pathogen growth rate is positively correlated with virulence, the amount of damage pathogens inflict on their hosts. Such theories are key for incorporating evolutionary principles into sustainable disease management strategies. Yet, empirical evidence raises doubts over this central assumption underpinning classical theories, thus undermining their generality and predictive power. In this paper, we identify a key component missing from current theories which redefines the growth-virulence relationship in a way that is consistent with data. By modifying the activity of a single metabolic gene, we engineered strains of Magnaporthe oryzae with different nutrient acquisition and growth rates. We conducted in planta infection studies and uncovered an unexpected non-monotonic relationship between growth rate and virulence that is jointly shaped by how growth rate and metabolic efficiency interact. This novel mechanistic framework paves the way for a much-needed new suite of virulence evolution theories.

Spatial self-organization of metabolism in microbial systems: A matter of enzymes and chemicals

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.

Cheating Promotes Coexistence in a Two-Species One-Substrate Culture Model

Cheating in microbial communities is often regarded as a precursor to a “tragedy of the commons,” ultimately leading to over-exploitation by a few species and destabilization of the community. While current evidence suggests that cheaters are evolutionarily and ecologically abundant, they can also play important roles in communities, such as promoting cooperative behaviors of other species. We developed a closed culture model with two microbial species and a single, complex nutrient substrate (the metaphorical “common”). One of the organisms, an enzyme producer, degrades the substrate, releasing an essential and limiting resource that it can use both to grow and produce more enzymes, but at a cost. The second organism, a cheater, does not produce the enzyme but can access the diffused resource produced by the other species, allowing it to benefit from the public good without contributing to it. We investigated evolutionarily stable states of coexistence between the two organisms and described how enzyme production rates and resource diffusion influence organism abundances. Our model shows that, in the long-term evolutionary scale, monocultures of the producer species drive themselves extinct because selection always favors mutant invaders that invest less in enzyme production, ultimately driving down the release of resources. However, the presence of a cheater buffers this process by reducing the fitness advantage of lower enzyme production, thereby preventing runaway selection in the producer, and promoting coexistence. Resource diffusion rate controls cheater growth, preventing it from outcompeting the producer. These results show that competition from cheaters can force producers to maintain adequate enzyme production to sustain both itself and the cheater. This is similar to what is known in evolutionary game theory as a “snowdrift game” – a metaphor describing a snow shoveler and a cheater following in their clean tracks. We move further to show that cheating can stabilize communities and possibly be a precursor to cooperation, rather than extinction.

On the Ecological Significance of Phenotypic Heterogeneity in Microbial Populations Undergoing Starvation

To persist in variable environments, populations of microorganisms have to survive periods of starvation and be able to restart cell division in nutrient-rich conditions. Typically, starvation signals initiate a transition to a quiescent state in a fraction of individual cells, while the rest of the cells remain nonquiescent. It is widely believed that, while quiescent (Q) cells help the population to survive long starvation, the nonquiescent (NQ) cells are a side effect of imperfect transition. We analyzed the regrowth of starved monocultures of Q and NQ cells compared to that of mixed, heterogeneous cultures from simple and complex starvation environments. Our experiments, as well as mathematical modeling, demonstrate that Q monocultures benefit from better survival during long starvation and from a shorter lag phase after resupply of rich medium. However, when the starvation period is very short, the NQ monocultures outperform Q and mixed cultures due to their short lag phase. In addition, only NQ monocultures benefit from complex starvation environments, where nutrient recycling is possible. Our study suggests that phenotypic heterogeneity in starved populations could be a form of bet hedging that is adaptive when environmental determinants, such as the length of the starvation period, the length of the regrowth phase, and the complexity of the starvation environment, vary over time.

IMPORTANCE Nongenetic cell heterogeneity is present in glucose-starved yeast populations in the form of quiescent (Q) and nonquiescent (NQ) phenotypes. There is evidence that Q cells help the population survive long starvation. However, the role of the NQ cell type is not known, and it has been speculated that the NQ phenotype is just a side effect of the imperfect transition to the Q phenotype. Here, we show that, in contrast, there are ecological scenarios in which NQ cells perform better than monocultures of Q cells or naturally occurring mixed populations containing both Q and NQ cells. NQ cells benefit when the starvation period is very short and environmental conditions allow nutrient recycling during starvation. Our experimental and mathematical modeling results suggest a novel hypothesis: the presence of both Q and NQ phenotypes within starved yeast populations may reflect a form of bet hedging where different phenotypes provide fitness advantages depending on the environmental conditions.

Would that it were so simple: Interactions between multiple traits undermine classical single-trait-based predictions of microbial community function and evolution

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. Here, we provide a much needed discussion and synthesis of the most recent research to reveal the widespread and diverse nature of multi-trait interactions and their consequences for predicting and controlling microbial community dynamics. Importantly, we argue that synthetic microbial communities and multi-trait mathematical models are powerful tools for managing the beneficial and detrimental impacts of microbial communities, such that past mistakes, like those made regarding the stewardship of antimicrobials, are not repeated.

Optogenetic Tools for Control of Public Goods in Saccharomyces cerevisiae

Microorganisms live in dense and diverse communities, with interactions between cells guiding community development and phenotype. The ability to perturb specific intercellular interactions in space and time provides a powerful route to determining the critical interactions and design rules for microbial communities. Approaches using optogenetic tools to modulate these interactions offer promise, as light can be exquisitely controlled in space and time. We report new plasmids for rapid integration of an optogenetic system into Saccharomyces cerevisiae to engineer light control of expression of a gene of interest. In a proof-of-principle study, we demonstrate the ability to control a model cooperative interaction, namely, the expression of the enzyme invertase (SUC2) which allows S. cerevisiae to hydrolyze sucrose and utilize it as a carbon source. We demonstrate that the strength of this cooperative interaction can be tuned in space and time by modulating light intensity and through spatial control of illumination. Spatial control of light allows cooperators and cheaters to be spatially segregated, and we show that the interplay between cooperative and inhibitory interactions in space can lead to pattern formation. Our strategy can be applied to achieve spatiotemporal control of expression of a gene of interest in S. cerevisiae to perturb both intercellular and interspecies interactions.

IMPORTANCE Recent advances in microbial ecology have highlighted the importance of intercellular interactions in controlling the development, composition, and resilience of microbial communities. In order to better understand the role of these interactions in governing community development, it is critical to be able to alter them in a controlled manner. Optogenetically controlled interactions offer advantages over static perturbations or chemically controlled interactions, as light can be manipulated in space and time and does not require the addition of nutrients or antibiotics. Here, we report a system for rapidly achieving light control of a gene of interest in the important model organism Saccharomyces cerevisiae and demonstrate that by controlling expression of the enzyme invertase, we can control cooperative interactions. This approach will be useful for understanding intercellular and interspecies interactions in natural and synthetic microbial consortia containing S. cerevisiae and serves as a proof of principle for implementing this approach in other consortia.

Density-dependent private benefit leads to bacterial mutualism

Microorganisms produce and secrete materials that are beneficial for themselves and their neighbors. We modeled the situation when cells can produce different costly secretions which increase the carrying capacity of the population. Strains that lose the function of producing one or more secretions avoid the cost of production and can exhaust the producers. However, secreting substances provides a private benefit for the producers in a density-dependent way. We developed a model to examine the outcome of the selection among different types of producer strains from the nonproducer strain to the partial producers, to the full producer strain. We were interested in circumstances under which selection maintains partners that produce complementary secreted materials thus forming an interdependent mutualistic interaction. We show that interdependent mutualism is selected under a broad range of conditions if private benefit decreases with density. Selection frequently causes the coexistence of more and less generalist cooperative strains, thus cooperation and exploitation co-occur. Interdependent mutualism is evolved under more specific circumstances if private benefit increases with density and these general observations are valid in a well-mixed and a structured deme model. We show that the applied population structure allows the invasion of rare cooperators and supports cooperation in general.

Predicting microbial growth dynamics in response to nutrient availability

Developing mathematical models to accurately predict microbial growth dynamics remains a key challenge in ecology, evolution, biotechnology, and public health. To reproduce and grow, microbes need to take up essential nutrients from the environment, and mathematical models classically assume that the nutrient uptake rate is a saturating function of the nutrient concentration. In nature, microbes experience different levels of nutrient availability at all environmental scales, yet parameters shaping the nutrient uptake function are commonly estimated for a single initial nutrient concentration. This hampers the models from accurately capturing microbial dynamics when the environmental conditions change. To address this problem, we conduct growth experiments for a range of micro-organisms, including human fungal pathogens, baker's yeast, and common coliform bacteria, and uncover the following patterns. We observed that the maximal nutrient uptake rate and biomass yield were both decreasing functions of initial nutrient concentration. While a functional form for the relationship between biomass yield and initial nutrient concentration has been previously derived from first metabolic principles, here we also derive the form of the relationship between maximal nutrient uptake rate and initial nutrient concentration. Incorporating these two functions into a model of microbial growth allows for variable growth parameters and enables us to substantially improve predictions for microbial dynamics in a range of initial nutrient concentrations, compared to keeping growth parameters fixed.

Privatization of public goods can cause population decline

Microbes commonly deploy a risky strategy to acquire nutrients from their environment, involving the production of costly public goods that can be exploited by neighbouring individuals. Why engage in such a strategy when an exploitation-free alternative is readily available whereby public goods are kept private? We address this by examining metabolism of Saccharomyces cerevisiae in its native form and by creating a new three-strain synthetic community deploying different strategies of sucrose metabolism. Public-metabolizers digest resources externally, private-metabolizers internalize resources before digestion, and cheats avoid the metabolic costs of digestion but exploit external products generated by competitors. A combination of mathematical modelling and ecological experiments reveal that private-metabolizers invade and take over an otherwise stable community of public-metabolizers and cheats. However, owing to the reduced growth rate of private-metabolizers and population bottlenecks that are frequently associated with microbial communities, privatizing public goods can become unsustainable, leading to population decline.

Intercellular cooperation in a fungal plant pathogen facilitates host colonization

Cooperation is associated with major transitions in evolution such as the emergence of multicellularity. It is central to the evolution of many complex traits in nature, including growth and virulence in pathogenic bacteria. Whether cells of multicellular parasites function cooperatively during infection remains, however, largely unknown. Here, we show that hyphal cells of the fungal pathogen Sclerotinia sclerotiorum reprogram toward division of labor to facilitate the colonization of host plants. Using global transcriptome sequencing, we reveal that gene expression patterns diverge markedly in cells at the center and apex of hyphae during Arabidopsis thaliana colonization compared with in vitro growth. We reconstructed a genome-scale metabolic model for S. sclerotiorum and used flux balance analysis to demonstrate metabolic heterogeneity supporting division of labor between hyphal cells. Accordingly, continuity between the central and apical compartments of invasive hyphae was required for optimal growth in planta Using a multicell model of fungal hyphae, we show that this cooperative functioning enhances fungal growth predominantly during host colonization. Our work identifies cooperation in fungal hyphae as a mechanism emerging at the multicellular level to support host colonization and virulence.

Selfish, sharing and scavenging bacteria in the Atlantic Ocean: a biogeographical study of bacterial substrate utilisation

Identifying the roles played by individual heterotrophic bacteria in the degradation of high molecular weight (HMW) substrates is critical to understanding the constraints on carbon cycling in the ocean. At five sites in the Atlantic Ocean, we investigated the processing of organic matter by tracking changes in microbial community composition as HMW polysaccharides were enzymatically hydrolysed over time. During this investigation, we discovered that a considerable fraction of heterotrophic bacteria uses a newly-identified ‘selfish’ mode of substrate processing. We therefore additionally examined the balance of individual substrate utilisation mechanisms at different locations by linking individual microorganisms to distinct substrate utilisation mechanisms. Through FISH and uptake of fluorescently-labelled polysaccharides, ‘selfish’ organisms were identified as belonging to the Bacteroidetes, Planctomycetes and Gammaproteobacteria. ‘Sharing’ (extracellular enzyme producing) and ‘scavenging’ (non-enzyme producing) organisms predominantly belonged to the Alteromonadaceae and SAR11 clades, respectively. The extent to which individual mechanisms prevail depended on the initial population structure of the bacterial community at a given location and time, as well as the growth rate of specific bacteria. Furthermore, the same substrate was processed in different ways by different members of a pelagic microbial community, pointing to significant follow-on effects for carbon cycling.