Revealing metabolic mechanisms of interaction in the anaerobic digestion microbiome by flux balance analysis

Anaerobic digestion is a key biological process for renewable energy, yet the mechanistic knowledge on its hidden microbial dynamics is still limited. The present work charted the interaction network in the anaerobic digestion microbiome via the full characterization of pairwise interactions and the associated metabolite exchanges. To this goal, a novel collection of 836 genome-scale metabolic models was built to represent the functional capabilities of bacteria and archaea species derived from genome-centric metagenomics. Dominant microbes were shown to prefer mutualistic, parasitic and commensalistic interactions over neutralism, amensalism and competition, and are more likely to behave as metabolite importers and profiteers of the coexistence. Additionally, external hydrogen injection positively influences microbiome dynamics by promoting commensalism over amensalism. Finally, exchanges of glucogenic amino acids were shown to overcome auxotrophies caused by an incomplete tricarboxylic acid cycle. Our novel strategy predicted the most favourable growth conditions for the microbes, overall suggesting strategies to increasing the biogas production efficiency. In principle, this approach could also be applied to microbial populations of biomedical importance, such as the gut microbiome, to allow a broad inspection of the microbial interplays.     

Environments that induce synthetic microbial ecosystems

Interactions between microbial species are sometimes mediated by the exchange of small molecules, secreted by one species and metabolized by another. Both one-way (commensal) and two-way (mutualistic) interactions may contribute to complex networks of interdependencies. Understanding these interactions constitutes an open challenge in microbial ecology, with applications ranging from the human microbiome to environmental sustainability. In parallel to natural communities, it is possible to explore interactions in artificial microbial ecosystems, e.g. pairs of genetically engineered mutualistic strains. Here we computationally generate artificial microbial ecosystems without re-engineering the microbes themselves, but rather by predicting their growth on appropriately designed media. We use genome-scale stoichiometric models of metabolism to identify media that can sustain growth for a pair of species, but fail to do so for one or both individual species, thereby inducing putative symbiotic interactions. We first tested our approach on two previously studied mutualistic pairs, and on a pair of highly curated model organisms, showing that our algorithms successfully recapitulate known interactions, robustly predict new ones, and provide novel insight on exchanged molecules. We then applied our method to all possible pairs of seven microbial species, and found that it is always possible to identify putative media that induce commensalism or mutualism. Our analysis also suggests that symbiotic interactions may arise more readily through environmental fluctuations than genetic modifications. We envision that our approach will help generate microbe-microbe interaction maps useful for understanding microbial consortia dynamics and evolution, and for exploring the full potential of natural metabolic pathways for metabolic engineering applications.     

Strategy Diversity Stabilizes Mutualism through Investment Cycles,Phase Polymorphism,and Spatial Bubbles

There is continuing interest in understanding factors that facilitate the evolution and stability of cooperation within and between species. Such interactions will often involve plasticity in investment behavior, in response to the interacting partner''s investments. Our aim here is to investigate the evolution and stability of reciprocal investment behavior in interspecific interactions, a key phenomenon strongly supported by experimental observations. In particular, we present a comprehensive analysis of a continuous reciprocal investment game between mutualists, both in well-mixed and spatially structured populations, and we demonstrate a series of novel mechanisms for maintaining interspecific mutualism. We demonstrate that mutualistic partners invariably follow investment cycles, during which mutualism first increases, before both partners eventually reduce their investments to zero, so that these cycles always conclude with full defection. We show that the key mechanism for stabilizing mutualism is phase polymorphism along the investment cycle. Although mutualistic partners perpetually change their strategies, the community-level distribution of investment levels becomes stationary. In spatially structured populations, the maintenance of polymorphism is further facilitated by dynamic mosaic structures, in which mutualistic partners form expanding and collapsing spatial bubbles or clusters. Additionally, we reveal strategy-diversity thresholds, both for well-mixed and spatially structured mutualistic communities, and discuss factors for meeting these thresholds, and thus maintaining mutualism. Our results demonstrate that interspecific mutualism, when considered as plastic investment behavior, can be unstable, and, in agreement with empirical observations, may involve a polymorphism of investment levels, varying both in space and in time. Identifying the mechanisms maintaining such polymorphism, and hence mutualism in natural communities, provides a significant step towards understanding the coevolution and population dynamics of mutualistic interactions.     

PHYTOPHAGOUS INSECT–MICROBE MUTUALISMS AND ADAPTIVE EVOLUTIONARY DIVERSIFICATION

Adaptive diversification is a process intrinsically tied to species interactions. Yet, the influence of most types of interspecific interactions on adaptive evolutionary diversification remains poorly understood. In particular, the role of mutualistic interactions in shaping adaptive radiations has been largely unexplored, despite the ubiquity of mutualisms and increasing evidence of their ecological and evolutionary importance. Our aim here is to encourage empirical inquiry into the relationship between mutualism and evolutionary diversification, using herbivorous insects and their microbial mutualists as exemplars. Phytophagous insects have long been used to test theories of evolutionary diversification; moreover, the diversification of a number of phytophagous insect lineages has been linked to mutualisms with microbes. In this perspective, we examine microbial mutualist mediation of ecological opportunity and ecologically based divergent natural selection for their insect hosts. We also explore the conditions and mechanisms by which microbial mutualists may either facilitate or impede adaptive evolutionary diversification. These include effects on the availability of novel host plants or adaptive zones, modifying host-associated fitness trade-offs during host shifts, creating or reducing enemy-free space, and, overall, shaping the evolution of ecological (host plant) specialization. Although the conceptual framework presented here is built on phytophagous insect–microbe mutualisms, many of the processes and predictions are broadly applicable to other mutualisms in which host ecology is altered by mutualistic interactions.     

Habitat loss and the structure of plant-animal mutualistic networks

Recent papers have described the structure of plant–animal mutualistic networks. However, no study has yet explored the dynamical implications of network structure for the persistence of such mutualistic communities. Here, we develop a patch-model of a whole plant–animal community and explore its persistence. To assess the role of network structure, we build three versions of the model. In the first version, we use the exact network of interactions of two real mutualistic communities. In the other versions, we randomize the observed network of interactions using two different null models. We show that the community response to habitat loss is affected by network structure. Real communities start to decay sooner than random communities, but persist for higher destruction levels. There is a destruction threshold at which the community collapses. Our model is the first attempt to describe the dynamics of whole mutualistic metacommunities interacting in realistic ways.     

Phytophagous insect-microbe mutualisms and adaptive evolutionary diversification.

Adaptive diversification is a process intrinsically tied to species interactions. Yet, the influence of most types of interspecific interactions on adaptive evolutionary diversification remains poorly understood. In particular, the role of mutualistic interactions in shaping adaptive radiations has been largely unexplored, despite the ubiquity of mutualisms and increasing evidence of their ecological and evolutionary importance. Our aim here is to encourage empirical inquiry into the relationship between mutualism and evolutionary diversification, using herbivorous insects and their microbial mutualists as exemplars. Phytophagous insects have long been used to test theories of evolutionary diversification; moreover, the diversification of a number of phytophagous insect lineages has been linked to mutualisms with microbes. In this perspective, we examine microbial mutualist mediation of ecological opportunity and ecologically based divergent natural selection for their insect hosts. We also explore the conditions and mechanisms by which microbial mutualists may either facilitate or impede adaptive evolutionary diversification. These include effects on the availability of novel host plants or adaptive zones, modifying host-associated fitness trade-offs during host shifts, creating or reducing enemy-free space, and, overall, shaping the evolution of ecological (host plant) specialization. Although the conceptual framework presented here is built on phytophagous insect-microbe mutualisms, many of the processes and predictions are broadly applicable to other mutualisms in which host ecology is altered by mutualistic interactions.     

Nested species interactions promote feasibility over stability during the assembly of a pollinator community

The foundational concepts behind the persistence of ecological communities have been based on two ecological properties: dynamical stability and feasibility. The former is typically regarded as the capacity of a community to return to an original equilibrium state after a perturbation in species abundances and is usually linked to the strength of interspecific interactions. The latter is the capacity to sustain positive abundances on all its constituent species and is linked to both interspecific interactions and species demographic characteristics. Over the last 40 years, theoretical research in ecology has emphasized the search for conditions leading to the dynamical stability of ecological communities, while the conditions leading to feasibility have been overlooked. However, thus far, we have no evidence of whether species interactions are more conditioned by the community''s need to be stable or feasible. Here, we introduce novel quantitative methods and use empirical data to investigate the consequences of species interactions on the dynamical stability and feasibility of mutualistic communities. First, we demonstrate that the more nested the species interactions in a community are, the lower the mutualistic strength that the community can tolerate without losing dynamical stability. Second, we show that high feasibility in a community can be reached either with high mutualistic strength or with highly nested species interactions. Third, we find that during the assembly process of a seasonal pollinator community located at The Zackenberg Research Station (northeastern Greenland), a high feasibility is reached through the nested species interactions established between newcomer and resident species. Our findings imply that nested mutualistic communities promote feasibility over stability, which may suggest that the former can be key for community persistence.     

Metabolic capacity estimation of Escherichia coli as a platform for redox biocatalysis: constraint-based modeling and experimental verification

Whole-cell redox biocatalysis relies on redox cofactor regeneration by the microbial host. Here, we applied flux balance analysis based on the Escherichia coli metabolic network to estimate maximal NADH regeneration rates. With this optimization criterion, simulations showed exclusive use of the pentose phosphate pathway at high rates of glucose catabolism, a flux distribution usually not found in wild-type cells. In silico, genetic perturbations indicated a strong dependency of NADH yield and formation rate on the underlying metabolic network structure. The linear dependency of measured epoxidation activities of recombinant central carbon metabolism mutants on glucose uptake rates and the linear correlation between measured activities and simulated NADH regeneration rates imply intracellular NADH shortage. Quantitative comparison of computationally predicted NADH regeneration and experimental epoxidation rates indicated that the achievable biocatalytic activity is determined by metabolic and enzymatic limitations including non-optimal flux distributions, high maintenance energy demands, energy spilling, byproduct formation, and uncoupling. The results are discussed in the context of cellular optimization of biotransformation processes and may guide a priori design of microbial cells as redox biocatalysts.     

On the evolution of non-specific mutualism

It has been argued that mutualisms are non-specific when mutualistic interactions are weak and transient, and become more specific as interactions increase in strength. However, this runs counter to the observation that there exist tightly linked mutualisms of great antiquity that are highly nonspecific. Here we argue that mutualism generates positive, interspecific, frequency-dependent selection, which acts as a cohesive evolutionary force, discouraging evolution of specificity. A simple mathematical model is constructed to analyse the evolution of a community consisting of two guilds of species with mutualistic between-guild interactions, two competing species in each guild and two genetically distinct phenotypes within each species. With some simplifying assumptions, the trajectories in the neighbourhood of the only interior equilibrium point are determined analytically in terms of interactions between individuals. These show that the equilibrium is locally stable (no evolution) when there is little differentiation between phenotypes in mutualistic and interspecific, competitive interactions. On the other hand, when there is strong differentiation between phenotypes in their mutualistic interactions, the equilibrium is unstable and the community starts to evolve towards non-specificity. There are, however, two forces counteracting this tendency which, if sufficiently potent, cause evolution towards specificity. The first is generated by strong differentiation between phenotypes in interspecific competition; the second is caused by specificity which already exists between species in their mutualistic interactions. Thus, the tendency for non-specificity or specificity to evolve depends on the interplay between antagonistic and mutualistic interactions in the community. We illustrate these results with some numerical examples and, finally, survey some data on specificity of mutualisms in the light of the analysis.     

The changing nature of plant–microbe interactions during a biological invasion

Invasive plant species can alter belowground microbial communities. Simultaneously, the composition of soil microbial communities and the abundance of key microbes can influence invasive plant success. Such reciprocal effects may cause plant–microbe interactions to change rapidly during the course of biological invasions in ways that either inhibit or promote invasive species growth. Here we use a space-for-time substitution to illustrate how effects of soil microbial communities on the exotic legume Vicia villosa vary across uninvaded sites, recently invaded sites, and sites invaded by V. villosa for over a decade. We find that soil microorganisms from invaded areas increase V. villosa growth compared to sterilized soil or live soils collected from uninvaded sites, likely because mutualistic nitrogen-fixing rhizobia are not abundant in uninvaded areas. Notably, the benefits resulting from inoculation with live soils were higher for soils from recently invaded sites compared to older invasions, potentially indicating that over longer time scales, soil microbial communities change in ways that may reduce the success of exotic species. These findings suggest that short-term changes to soil microbial communities following invasion may facilitate exotic legume growth likely because of increases in the abundance of mutualistic rhizobia, but also indicate that longer term changes to soil microbial communities may reduce the growth benefits belowground microbial communities provide to exotic species. Our results highlight the changing nature of plant–microbe interactions during biological invasions and illustrate how altered biotic interactions could contribute to both the initial success and subsequent naturalization of invasive legume species.     

地下水脱卤过程中的微生物种间代谢互作：提高原位氯代烯烃厌氧脱氯效能的有效途径

有机卤呼吸细菌(organohalide-respiring bacteria, OHRB)在氯代烯烃污染地下水的原位生物修复中扮演着关键性的角色,提高其丰度及活性对氯代烯烃的完全去除具有重要意义。在实际环境中,有机卤呼吸细菌往往与多种微生物共存,微生物种间代谢互作现象十分普遍,有机污染物的完全无害化往往需要通过微生物菌群的协同代谢作用来实现。因此,本文围绕微生物种间代谢互作进行综述,对目前获得的脱氯微生物菌种资源及脱氯机理进行了回顾,重点阐述了专性OHRB、非专性OHRB和非OHRB的种间代谢互作行为及机制,并提出以种间代谢互作为指导进行合成微生物群落的构建来有效提高氯代烯烃厌氧生物降解效率,为实现环境氯代烯烃类有机污染物的快速、彻底无害化提供理论指导。     

Interspecific interactions affect species and community responses to climate shifts

The response of individual species to climate change may alter the composition and dynamics of communities. Here, we show that the impacts of environmental change on communities can depend on the nature of the interspecific interactions: mutualistic communities typically respond differently than commensalistic or parasitic communities. We model and analyse the geographic range shifting of metapopulations of two interacting species – a host and an obligate species. Different types of interspecific interactions are implemented by modifying local extinction rates according to the presence/absence of the other species. We distinguish and compare three fundamentally different community types: mutualism, commensalism and parasitism. We find that community dynamics during geographic range shifting critically depends on the type of interspecific interactions. Parasitic interactions exacerbate the negative effect of environmental change whereas mutualistic interactions only partly compensate it. Commensalistic interactions exhibit an intermediate response. Based on these model outcomes, we predict that parasitic species interactions may be more vulnerable to geographic range shifting than commensalistic or mutualistic ones. However, we observe that when climate stabilises following a period of change, the rate of community recovery is largely independent of the type of interspecific interactions. These results emphasize that communities respond delicately to environmental change, and that local interspecific interactions can affect range shifting communities at large spatial scales.     

Interactions between functionally diverse fungal mutualists inconsistently affect plant performance and competition

Plants form mutualistic relationship with a variety of belowground fungal species. Such a mutualistic relationship can enhance plant growth and resistance to pathogens. Yet, we know little about how interactions between functionally diverse groups of fungal mutualists affect plant performance and competition. We experimentally determined the effects of interaction between two functional groups of belowground fungi that form mutualistic relationship with plants, arbuscular mycorrhizal (AM) fungi and Trichoderma, on interspecific competition between pairs of closely related plant species from four different genera. We hypothesized that the combination of two functionally diverse belowground fungal species would allow plants and fungi to partition their symbiotic relationships and relax plant–plant competition. Our results show that: 1) the AM fungal species consistently outcompeted the Trichoderma species independent of plant combinations; 2) the fungal species generally had limited effects on competitive interactions between plants; 3) however, the combination of fungal species relaxed interspecific competition in one of the four instances of plant–plant competition, despite the general competitive superiority of AM fungi over Trichoderma. We highlight that the competitive outcome between functionally diverse fungal species may show high consistency across a broad range of host plants and their combinations. However, despite this consistent competitive hierarchy, the consequences of their interaction for plant performance and competition can strongly vary among plant communities.     

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.     

Thermodynamically based profiling of drug metabolism and drug-drug metabolic interactions: a case study of acetaminophen and ethanol toxic interaction

Drug-drug metabolic interactions can result in unwanted side effects, including reduced drug efficacy and formation of toxic metabolic intermediates. In this work, thermodynamic constraints on non-equilibrium metabolite concentrations are used to reveal the biochemical interactions between the metabolic pathways of ethanol and acetaminophen (N-acetyl-p-aminophenol), two drugs known to interact unfavorably. It is known that many reactions of these pathways are coupled to the central energy metabolic reactions through a number of metabolites and the cellular redox potential. Based on these observations, a metabolic network model has been constructed and a database of thermodynamic properties for all participating metabolites and reactions has been compiled. Constraint-based computational analysis of the feasible metabolite concentrations reveals that the non-toxic pathways for APAP metabolism and the pathway for detoxifying N-acetyl-p-benzoquinoneimine (NAPQI) are inhibited by network interactions with ethanol metabolism. These results point to the potential utility of thermodynamically based profiling of metabolic network interactions in screening of drug candidates and analysis of potential toxicity.     

Seeing through the static: the temporal dimension of plant–animal mutualistic interactions

Most studies of plant–animal mutualistic networks have come from a temporally static perspective. This approach has revealed general patterns in network structure, but limits our ability to understand the ecological and evolutionary processes that shape these networks and to predict the consequences of natural and human‐driven disturbance on species interactions. We review the growing literature on temporal dynamics of plant–animal mutualistic networks including pollination, seed dispersal and ant defence mutualisms. We then discuss potential mechanisms underlying such variation in interactions, ranging from behavioural and physiological processes at the finest temporal scales to ecological and evolutionary processes at the broadest. We find that at the finest temporal scales (days, weeks, months) mutualistic interactions are highly dynamic, with considerable variation in network structure. At intermediate scales (years, decades), networks still exhibit high levels of temporal variation, but such variation appears to influence network properties only weakly. At the broadest temporal scales (many decades, centuries and beyond), continued shifts in interactions appear to reshape network structure, leading to dramatic community changes, including loss of species and function. Our review highlights the importance of considering the temporal dimension for understanding the ecology and evolution of complex webs of mutualistic interactions.     

Inference of Network Dynamics and Metabolic Interactions in the Gut Microbiome

We present a novel methodology to construct a Boolean dynamic model from time series metagenomic information and integrate this modeling with genome-scale metabolic network reconstructions to identify metabolic underpinnings for microbial interactions. We apply this in the context of a critical health issue: clindamycin antibiotic treatment and opportunistic Clostridium difficile infection. Our model recapitulates known dynamics of clindamycin antibiotic treatment and C. difficile infection and predicts therapeutic probiotic interventions to suppress C. difficile infection. Genome-scale metabolic network reconstructions reveal metabolic differences between community members and are used to explore the role of metabolism in the observed microbial interactions. In vitro experimental data validate a key result of our computational model, that B. intestinihominis can in fact slow C. difficile growth.