Selfishness driving reductive evolution shapes interdependent patterns in spatially structured microbial communities

Microbes release a wide variety of metabolites to the environment that benefit the whole population, called public goods. Public goods sharing drives adaptive function loss, and allows the rise of metabolic cross-feeding. However, how public goods sharing governs the succession of communities over evolutionary time scales remains unclear. To resolve this issue, we constructed an individual-based model, where an autonomous population that possessed functions to produce three essential public goods, was allowed to randomly lose functions. Simulations revealed that function loss genotypes could evolve from the autonomous ancestor, driven by the selfish public production trade-off at the individual level. These genotypes could then automatically develop to three possible types of interdependent patterns: complete functional division, one-way dependency, and asymmetric functional complementation, which were influenced by function cost and function redundancy. In addition, we found random evolutionary events, i.e., the priority and the relative spatial positioning of genotype emergence, are also important in governing community assembly. Moreover, communities occupied by interdependent patterns exhibited better resistance to environmental perturbation, suggesting such patterns are selectively favored. Our work integrates ecological interactions with evolution dynamics, providing a new perspective to explain how reductive evolution shapes microbial interdependencies and governs the succession of communities.Subject terms: Microbial ecology, Microbial ecology     

COMMIT: Consideration of metabolite leakage and community composition improves microbial community reconstructions

Composition and functions of microbial communities affect important traits in diverse hosts, from crops to humans. Yet, mechanistic understanding of how metabolism of individual microbes is affected by the community composition and metabolite leakage is lacking. Here, we first show that the consensus of automatically generated metabolic reconstructions improves the quality of the draft reconstructions, measured by comparison to reference models. We then devise an approach for gap filling, termed COMMIT, that considers metabolites for secretion based on their permeability and the composition of the community. By applying COMMIT with two soil communities from the Arabidopsis thaliana culture collection, we could significantly reduce the gap-filling solution in comparison to filling gaps in individual reconstructions without affecting the genomic support. Inspection of the metabolic interactions in the soil communities allows us to identify microbes with community roles of helpers and beneficiaries. Therefore, COMMIT offers a versatile fully automated solution for large-scale modelling of microbial communities for diverse biotechnological applications.     

Modeling microbial community structure and functional diversity across time and space

Microbial communities exhibit exquisitely complex structure. Many aspects of this complexity, from the number of species to the total number of interactions, are currently very difficult to examine directly. However, extraordinary efforts are being made to make these systems accessible to scientific investigation. While recent advances in high-throughput sequencing technologies have improved accessibility to the taxonomic and functional diversity of complex communities, monitoring the dynamics of these systems over time and space - using appropriate experimental design - is still expensive. Fortunately, modeling can be used as a lens to focus low-resolution observations of community dynamics to enable mathematical abstractions of functional and taxonomic dynamics across space and time. Here, we review the approaches for modeling bacterial diversity at both the very large and the very small scales at which microbial systems interact with their environments. We show that modeling can help to connect biogeochemical processes to specific microbial metabolic pathways.     

Adaptive Evolution of Synthetic Cooperating Communities Improves Growth Performance

Symbiotic interactions between organisms are important for human health and biotechnological applications. Microbial mutualism is a widespread phenomenon and is important in maintaining natural microbial communities. Although cooperative interactions are prevalent in nature, little is known about the processes that allow their initial establishment, govern population dynamics and affect evolutionary processes. To investigate cooperative interactions between bacteria, we constructed, characterized, and adaptively evolved a synthetic community comprised of leucine and lysine Escherichia coli auxotrophs. The co-culture can grow in glucose minimal medium only if the two auxotrophs exchange essential metabolites — lysine and leucine (or its precursors). Our experiments showed that a viable co-culture using these two auxotrophs could be established and adaptively evolved to increase growth rates (by ∼3 fold) and optical densities. While independently evolved co-cultures achieved similar improvements in growth, they took different evolutionary trajectories leading to different community compositions. Experiments with individual isolates from these evolved co-cultures showed that changes in both the leucine and lysine auxotrophs improved growth of the co-culture. Interestingly, while evolved isolates increased growth of co-cultures, they exhibited decreased growth in mono-culture (in the presence of leucine or lysine). A genome-scale metabolic model of the co-culture was also constructed and used to investigate the effects of amino acid (leucine or lysine) release and uptake rates on growth and composition of the co-culture. When the metabolic model was constrained by the estimated leucine and lysine release rates, the model predictions agreed well with experimental growth rates and composition measurements. While this study and others have focused on cooperative interactions amongst community members, the adaptive evolution of communities with other types of interactions (e.g., commensalism, ammensalism or parasitism) would also be of interest.     

Bacterial response to spatial gradients of algal-derived nutrients in a porous microplate

Photosynthetic microalgae are responsible for 50% of the global atmospheric CO₂ fixation into organic matter and hold potential as a renewable bioenergy source. Their metabolic interactions with the surrounding microbial community (the algal microbiome) play critical roles in carbon cycling, but due to methodological limitations, it has been challenging to examine how community development is influenced by spatial proximity to their algal host. Here we introduce a copolymer-based porous microplate to co-culture algae and bacteria, where metabolites are constantly exchanged between the microorganisms while maintaining physical separation. In the microplate, we found that the diatom Phaeodactylum tricornutum accumulated to cell abundances ~20 fold higher than under normal batch conditions due to constant replenishment of nutrients through the porous structure. We also demonstrate that algal-associated bacteria, both single isolates and complex communities, responded to inorganic nutrients away from their host as well as organic nutrients originating from the algae in a spatially predictable manner. These experimental findings coupled with a mathematical model suggest that host proximity and algal culture growth phase impact bacterial community development in a taxon-specific manner through organic and inorganic nutrient availability. Our novel system presents a useful tool to investigate universal metabolic interactions between microbes in aquatic ecosystems.Subject terms: Microbial ecology, Microbial ecology, Microbial ecology     

A road map for the development of community systems (CoSy) biology

Microbial interactions are essential for all global geochemical cycles and have an important role in human health and disease. Although we possess general knowledge about the major processes within a microbial community, we are presently unable to decipher what role individual microorganisms have and how their individual actions influence others in the community. We also have limited knowledge with which to predict the effects of microbial interactions and community composition on the environment and vice versa. In this Opinion article, we describe how community systems (CoSy) biology will enable us to decode these complex relationships and will therefore improve our understanding of individual members of the community and the modes of interactions in which they engage.     

Spatio-temporal modeling of the crowding conditions and metabolic variability in microbial communities

The metabolic capabilities of the species and the local environment shape the microbial interactions in a community either through the exchange of metabolic products or the competition for the resources. Cells are often arranged in close proximity to each other, creating a crowded environment that unevenly reduce the diffusion of nutrients. Herein, we investigated how the crowding conditions and metabolic variability among cells shape the dynamics of microbial communities. For this, we developed CROMICS, a spatio-temporal framework that combines techniques such as individual-based modeling, scaled particle theory, and thermodynamic flux analysis to explicitly incorporate the cell metabolism and the impact of the presence of macromolecular components on the nutrients diffusion. This framework was used to study two archetypical microbial communities (i) Escherichia coli and Salmonella enterica that cooperate with each other by exchanging metabolites, and (ii) two E. coli with different production level of extracellular polymeric substances (EPS) that compete for the same nutrients. In the mutualistic community, our results demonstrate that crowding enhanced the fitness of cooperative mutants by reducing the leakage of metabolites from the region where they are produced, avoiding the resource competition with non-cooperative cells. Moreover, we also show that E. coli EPS-secreting mutants won the competition against the non-secreting cells by creating less dense structures (i.e. increasing the spacing among the cells) that allow mutants to expand and reach regions closer to the nutrient supply point. A modest enhancement of the relative fitness of EPS-secreting cells over the non-secreting ones were found when the crowding effect was taken into account in the simulations. The emergence of cell-cell interactions and the intracellular conflicts arising from the trade-off between growth and the secretion of metabolites or EPS could provide a local competitive advantage to one species, either by supplying more cross-feeding metabolites or by creating a less dense neighborhood.     

Impact of direct physical association and motility on fitness of a synthetic interkingdom microbial community

Mutualistic exchange of metabolites can play an important role in microbial communities. Under natural environmental conditions, such exchange may be compromised by the dispersal of metabolites and by the presence of non-cooperating microorganisms. Spatial proximity between members during sessile growth on solid surfaces has been shown to promote stabilization of cross-feeding communities against these challenges. Nonetheless, many natural cross-feeding communities are not sessile but rather pelagic and exist in turbulent aquatic environments, where partner proximity is often achieved via direct cell-cell adhesion, and cooperation occurs between physically associated cells. Partner association in aquatic environments could be further enhanced by motility of individual planktonic microorganisms. In this work, we establish a model bipartite cross-feeding community between bacteria and yeast auxotrophs to investigate the impact of direct adhesion between prokaryotic and eukaryotic partners and of bacterial motility in a stirred mutualistic co-culture. We demonstrate that adhesion can provide fitness benefit to the bacterial partner, likely by enabling local metabolite exchange within co-aggregates, and that it counteracts invasion of the community by a non-cooperating cheater strain. In a turbulent environment and at low cell densities, fitness of the bacterial partner and its competitiveness against a non-cooperating strain are further increased by motility that likely facilitates partner encounters and adhesion. These results suggest that, despite their potential fitness costs, direct adhesion between partners and its enhancement by motility may play key roles as stabilization factors for metabolic communities in turbulent aquatic environments.Subject terms: Microbial ecology, Environmental microbiology     

Metabolic and Demographic Feedbacks Shape the Emergent Spatial Structure and Function of Microbial Communities

Microbes are predominantly found in surface-attached and spatially structured polymicrobial communities. Within these communities, microbial cells excrete a wide range of metabolites, setting the stage for interspecific metabolic interactions. The links, however, between metabolic and ecological interactions (functional relationships), and species spatial organization (structural relationships) are still poorly understood. Here, we use an individual-based modelling framework to simulate the growth of a two-species surface-attached community where food (resource) is traded for detoxification (service) and investigate how metabolic constraints of individual species shape the emergent structural and functional relationships of the community. We show that strong metabolic interdependence drives the emergence of mutualism, robust interspecific mixing, and increased community productivity. Specifically, we observed a striking and highly stable emergent lineage branching pattern, generating a persistent lineage mixing that was absent when the metabolic exchange was removed. These emergent community properties are driven by demographic feedbacks, such that aid from neighbouring cells directly enhances focal cell growth, which in turn feeds back to neighbour fecundity. In contrast, weak metabolic interdependence drives conflict (exploitation or competition), and in turn greater interspecific segregation. Together, these results support the idea that species structural and functional relationships represent the net balance of metabolic interdependencies.     

Metaproteogenomic analysis of a community of sponge symbionts

Sponges harbour complex communities of diverse microorganisms, which have been postulated to form intimate symbiotic relationships with their host. Here we unravel some of these interactions by characterising the functional features of the microbial community of the sponge Cymbastela concentrica through a combined metagenomic and metaproteomic approach. We discover the expression of specific transport functions for typical sponge metabolites (for example, halogenated aromatics, dipeptides), which indicates metabolic interactions between the community and the host. We also uncover the simultaneous performance of aerobic nitrification and anaerobic denitrification, which would aid to remove ammonium secreted by the sponge. Our analysis also highlights the requirement for the microbial community to respond to variable environmental conditions and hence express an array of stress protection proteins. Molecular interactions between symbionts and their host might also be mediated by a set of expressed eukaryotic-like proteins and cell–cell mediators. Finally, some sponge-associated bacteria (for example, a Phyllobacteriaceae phylotype) appear to undergo an evolutionary adaptation process to the sponge environment as evidenced by active mobile genetic elements. Our data clearly show that a combined metaproteogenomic approach can provide novel information on the activities, physiology and interactions of sponge-associated microbial communities.     

Morphological complexity affects the diversity of marine microbiomes

Large eukaryotes support diverse communities of microbes on their surface—epibiota—that profoundly influence their biology. Alternate factors known to structure complex patterns of microbial diversity—host evolutionary history and ecology, environmental conditions and stochasticity—do not act independently and it is challenging to disentangle their relative effects. Here, we surveyed the epibiota from 38 sympatric seaweed species that span diverse clades and have convergent morphology, which strongly influences seaweed ecology. Host identity explains most of the variation in epibiont communities and deeper host phylogenetic relationships (e.g., genus level) explain a small but significant portion of epibiont community variation. Strikingly, epibiota community composition is significantly influenced by host morphology and epibiota richness increases with morphological complexity of the seaweed host. This effect is robust after controlling for phylogenetic non-independence and is strongest for crustose seaweeds. We experimentally validated the effect of host morphology by quantifying bacterial community assembly on latex sheets cut to resemble three seaweed morphologies. The patterns match those observed in our field survey. Thus, biodiversity increases with habitat complexity in host-associated microbial communities, mirroring patterns observed in animal communities. We suggest that host morphology and structural complexity are underexplored mechanisms structuring microbial communities.Subject terms: Microbial ecology, Biodiversity     

Successional and seasonal variations in soil and litter microbial community structure and function during tropical postagricultural forest regeneration: a multiyear study

Soil microorganisms regulate fundamental biochemical processes in plant litter decomposition and soil organic matter (SOM) transformations. Understanding how microbial communities respond to changes in vegetation is critical for improving predictions of how land‐cover change affects belowground carbon storage and nutrient availability. We measured intra‐ and interannual variability in soil and forest litter microbial community composition and activity via phospholipid fatty acid analysis (PLFA) and extracellular enzyme activity across a well‐replicated, long‐term chronosequence of secondary forests growing on abandoned pastures in the wet subtropical forest life zone of Puerto Rico. Microbial community PLFA structure differed between young secondary forests and older secondary and primary forests, following successional shifts in tree species composition. These successional patterns held across seasons, but the microbial groups driving these patterns differed over time. Microbial community composition from the forest litter differed greatly from those in the soil, but did not show the same successional trends. Extracellular enzyme activity did not differ with forest succession, but varied by season with greater rates of potential activity in the dry seasons. We found few robust significant relationships among microbial community parameters and soil pH, moisture, carbon, and nitrogen concentrations. Observed inter‐ and intrannual variability in microbial community structure and activity reveal the importance of a multiple, temporal sampling strategy when investigating microbial community dynamics with land‐use change. Successional control over microbial composition with forest recovery suggests strong links between above and belowground communities.     

Microbial competition reduces metabolic interaction distances to the low µm-range

Metabolic interactions between cells affect microbial community compositions and hence their function in ecosystems. It is well-known that under competition for the exchanged metabolite, concentration gradients constrain the distances over which interactions can occur. However, interaction distances are typically quantified in two-dimensional systems or without accounting for competition or other metabolite-removal, conditions which may not very often match natural ecosystems. We here analyze the impact of cell-to-cell distance on unidirectional cross-feeding in a three-dimensional aqueous system with competition for the exchanged metabolite. Effective interaction distances were computed with a reaction-diffusion model and experimentally verified by growing a synthetic consortium of 1 µm-sized metabolite producer, receiver, and competitor cells in different spatial structures. We show that receivers cannot interact with producers located on average 15 µm away from them, as product concentration gradients flatten close to producer cells. We developed an aggregation protocol and varied the receiver cells’ product affinity, to show that within producer–receiver aggregates even low-affinity receiver cells could interact with producers. These results show that competition or other metabolite-removal of a public good in a three-dimensional system reduces metabolic interaction distances to the low µm-range, highlighting the importance of concentration gradients as physical constraint for cellular interactions.Subject terms: Microbial ecology, Microbial communities     

Protozoa populations are ecosystem engineers that shape prokaryotic community structure and function of the rumen microbial ecosystem

Unicellular eukaryotes are an integral part of many microbial ecosystems where they interact with their surrounding prokaryotic community—either as predators or as mutualists. Within the rumen, one of the most complex host-associated microbial habitats, ciliate protozoa represent the main micro-eukaryotes, accounting for up to 50% of the microbial biomass. Nonetheless, the extent of the ecological effect of protozoa on the microbial community and on the rumen metabolic output remains largely understudied. To assess the role of protozoa on the rumen ecosystem, we established an in-vitro system in which distinct protozoa sub-communities were introduced to the native rumen prokaryotic community. We show that the different protozoa communities exert a strong and differential impact on the composition of the prokaryotic community, as well as its function including methane production. Furthermore, the presence of protozoa increases prokaryotic diversity with a differential effect on specific bacterial populations such as Gammaproteobacteria, Prevotella and Treponema. Our results suggest that protozoa contribute to the maintenance of prokaryotic diversity in the rumen possibly by mitigating the effect of competitive exclusion between bacterial taxa. Our findings put forward the rumen protozoa populations as potentially important ecosystem engineers for future microbiome modulation strategies.Subject terms: Microbial ecology, Food webs     

Ecology and evolution of antimicrobial resistance in bacterial communities

Accumulating evidence suggests that the response of bacteria to antibiotics is significantly affected by the presence of other interacting microbes. These interactions are not typically accounted for when determining pathogen sensitivity to antibiotics. In this perspective, we argue that resistance and evolutionary responses to antibiotic treatments should not be considered only a trait of an individual bacteria species but also an emergent property of the microbial community in which pathogens are embedded. We outline how interspecies interactions can affect the responses of individual species and communities to antibiotic treatment, and how these responses could affect the strength of selection, potentially changing the trajectory of resistance evolution. Finally, we identify key areas of future research which will allow for a more complete understanding of antibiotic resistance in bacterial communities. We emphasise that acknowledging the ecological context, i.e. the interactions that occur between pathogens and within communities, could help the development of more efficient and effective antibiotic treatments.Subject terms: Microbial ecology, Antibiotics, Bacterial evolution     

Environmental stress destabilizes microbial networks

Environmental stress is increasing worldwide, yet we lack a clear picture of how stress disrupts the stability of microbial communities and the ecosystem services they provide. Here, we present the first evidence that naturally-occurring microbiomes display network properties characteristic of unstable communities when under persistent stress. By assessing changes in diversity and structure of soil microbiomes along 40 replicate stress gradients (elevation/water availability gradients) in the Florida scrub ecosystem, we show that: (1) prokaryotic and fungal diversity decline in high stress, and (2) two network properties of stable microbial communities—modularity and negative:positive cohesion—have a clear negative relationship with environmental stress, explaining 51–78% of their variation. Interestingly, pathogenic taxa/functional guilds decreased in relative abundance along the stress gradient, while oligotrophs and mutualists increased, suggesting that the shift in negative:positive cohesion could result from decreasing negative:positive biotic interactions consistent with the predictions of the Stress Gradient Hypothesis. Given the crucial role microbiomes play in ecosystem functions, our results suggest that, by limiting the compartmentalization of microbial associations and creating communities dominated by positive associations, increasing stress in the Anthropocene could destabilize microbiomes and undermine their ecosystem services.Subject terms: Microbial ecology, Microbial ecology     

成像质谱在微生物代谢产物研究中的应用

微生物代谢产物的结构和功能多样,对相邻微生物和环境会产生重要影响。传统的天然产物分离方法不能系统全面地监测单一或混合微生物样品中代谢物的合成和释放模式。成像质谱能够同时可视化观察从单一微生物菌落到复杂微生物群落的多个代谢产物的时空分布,可以用于发现重要的生物活性分子,观察微生物菌落的代谢交流,以及跟踪微生物之间相互竞争过程中代谢物的修饰等方面的研究。本文综述了成像质谱在微生物代谢产物研究中的最新进展,展望了该技术的应用前景。     

Microbial resistance and resilience in response to environmental changes under the higher intensity of human activities than global average level

With the increasing intensity of global human activities, the ecosystem function, which is supported by the microbial community, will be dramatically changed and impaired. To investigate microbial resistance and resilience of microbial communities to human activities, we chose two typical types of human disturbances, urbanization, and reclamation under the higher intensity of human activities than the global average level. We examined microbial traits, including the abundance, diversity, phylogeny, and co‐occurrence interactions in soil microbial communities, together with the nitrification activities observed in the subtropical coastal ecosystem of the Pearl River Estuary and in soil microcosm experiments. Microbial communities were less resistant to the environmental changes caused by urbanization than to those caused by reclamation, which was significantly reflected in the nitrogen and/or carbon‐related patterns. However, most of the microbial traits could be recovered almost to the original level without significant differences in the microcosm after 40 days of incubation. The co‐occurrence interactions between nitrifiers and other microbial communities were dramatically changed and could not be completely recovered, but this change did not affect their nitrification activities for balancing the ammonium in the soil to the original level during the recovery stage, suggesting that the interactions between microbial communities might have fewer effects on their activities than previously thought. This study quantitatively demonstrated that microbial communities as a whole can recover to a status similar to the original state in a short time after the removal of stress at a large ecosystem scale even under the higher intensity of human activities than global average level in coastal ecosystems, which implied a strong recovery capacity of soil microbial community even after intense human disturbance.