Polarization of microbial communities between competitive and cooperative metabolism

2020 ◽  
Author(s):  
Daniel Machado ◽  
Oleksandr M. Maistrenko ◽  
Sergej Andrejev ◽  
Yongkyu Kim ◽  
Peer Bork ◽  
...  
Keyword(s):  
Resource Competition ◽  
Red Queen Hypothesis ◽  
Species Invasion ◽  
Metabolic Cooperation ◽  
Independent Dataset ◽  
Competition And Cooperation ◽  
Community Types ◽  
Genome Scale ◽  
Microbial Community Assembly ◽  
Natural Communities

AbstractResource competition and metabolic cross-feeding are among the main drivers of microbial community assembly. Yet, the degree to which these two conflicting forces are reflected in the composition of natural communities has not been systematically investigated. Here, we use genome-scale metabolic modeling to assess resource competition and metabolic cooperation potential in large co-occurring groups, with up to 40 member species, across thousands of habitats. Our analysis revealed two distinct community types, clustering at opposite ends in a trade-off landscape between competition and cooperation. On one end lie highly cooperative communities, characterized by smaller genomes and multiple auxotrophies, reminiscent of the black queen hypothesis. At the other end lie highly competitive communities, conforming to the red queen hypothesis, featuring larger genomes and overlapping nutritional requirements. While the latter are mainly present in soils, the former are found both in free-living and host-associated habitats. Community-scale flux simulations showed that, while the competitive communities can better resist species invasion but not nutrient shift, the cooperative communities are susceptible to species invasion but resilient to nutrient change. In accord, we show, through analyzing an additional independent dataset, the colonization of the human gut by probiotic species is positively associated with the presence of cooperative species in the recipient microbiome. Together, our analysis highlights the bifurcation between competition and cooperation in the assembly of natural communities and its implications for community modulation.

scholarly journals Metabolic dependencies drive species co-occurrence in diverse microbial communities

2015 ◽  
Vol 112 (20) ◽  
pp. 6449-6454 ◽  
Author(s):  
Aleksej Zelezniak ◽  
Sergej Andrejev ◽  
Olga Ponomarova ◽  
Daniel R. Mende ◽  
Peer Bork ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Resource Competition ◽  
Critical Role ◽  
Metabolic Modeling ◽  
Cooperative Groups ◽  
Cooperative Interactions ◽  
A Genome ◽  
Group Survival ◽  
Metabolic Interactions ◽  
Genome Scale

Microbial communities populate most environments on earth and play a critical role in ecology and human health. Their composition is thought to be largely shaped by interspecies competition for the available resources, but cooperative interactions, such as metabolite exchanges, have also been implicated in community assembly. The prevalence of metabolic interactions in microbial communities, however, has remained largely unknown. Here, we systematically survey, by using a genome-scale metabolic modeling approach, the extent of resource competition and metabolic exchanges in over 800 communities. We find that, despite marked resource competition at the level of whole assemblies, microbial communities harbor metabolically interdependent groups that recur across diverse habitats. By enumerating flux-balanced metabolic exchanges in these co-occurring subcommunities we also predict the likely exchanged metabolites, such as amino acids and sugars, that can promote group survival under nutritionally challenging conditions. Our results highlight metabolic dependencies as a major driver of species co-occurrence and hint at cooperative groups as recurring modules of microbial community architecture.

scholarly journals Spatial and temporal escape from fungal parasitism in natural communities of anciently asexual bdelloid rotifers

2013 ◽  
Vol 280 (1765) ◽  
pp. 20131255 ◽  
Author(s):  
Christopher G. Wilson ◽  
Paul W. Sherman
Keyword(s):  
Field Experiments ◽  
Life Stage ◽  
Red Queen Hypothesis ◽  
Bdelloid Rotifers ◽  
Antagonistic Coevolution ◽  
Freshwater Habitats ◽  
Spatio Temporal ◽  
The Red Queen ◽  
Natural Communities

Sexual reproduction is costly, but it is nearly ubiquitous among plants and animals, whereas obligately asexual taxa are rare and almost always short-lived. The Red Queen hypothesis proposes that sex overcomes its costs by enabling organisms to keep pace with coevolving parasites and pathogens. If so, the few cases of stable long-term asexuality ought to be found in groups whose coevolutionary interactions with parasites are unusually weak. In theory, antagonistic coevolution will be attenuated if hosts disperse among patches within a metapopulation separately from parasites and more rapidly. We examined whether these conditions are met in natural communities of bdelloid rotifers, one of the longest-lived asexual lineages. At any life stage, these microscopic invertebrates can tolerate the complete desiccation of their ephemeral freshwater habitats, surviving as dormant propagules that are readily carried by the wind. In our field experiments, desiccation and wind transport enabled bdelloids to disperse independently of multiple fungal parasites, in both time and space. Surveys of bdelloid communities in unmanipulated moss patches confirmed that fungal parasitism was negatively correlated with extended drought and increasing height (exposure to wind). Bdelloid ecology therefore matches a key condition of models in which asexuals persist through spatio-temporal decoupling from coevolving enemies.

scholarly journals Pathway-based and phylogenetically adjusted quantification of metabolic interaction between microbial species

2020 ◽  
Author(s):  
Tony J. Lam ◽  
Moses Stamboulian ◽  
Wontack Han ◽  
Yuzhen Ye
Keyword(s):  
Microbial Communities ◽  
Bacterial Species ◽  
Microbial Interactions ◽  
Phylogenetic Distance ◽  
Phylogenetic Relatedness ◽  
Bacterial Interactions ◽  
Competition And Cooperation ◽  
Microbial Species ◽  
Metabolic Interactions ◽  
Genome Scale

AbstractMicrobial community members exhibit various forms of interactions. Taking advantage of the increasing availability of microbiome data, many computational approaches have been developed to infer bacterial interactions from the co-occurrence of microbes across diverse microbial communities. Additionally, the introduction of genome-scale metabolic models have also enabled the inference of metabolic interactions, such as competition and cooperation, between bacterial species. By nature, phylogenetically similar microbial species are likely to share common functional profiles or biological pathways due to their genomics similarity. Without properly factoring out the phylogenetic relationship, any estimation of the competition and cooperation based on functional/pathway profiles may bias downstream applications.To address these challenges, we developed a novel approach for estimating the competition and complementarity indices for a pair of microbial species, adjusted by their phylogenetic distance. An automated pipeline, PhyloMint, was implemented to construct competition and complementarity indices from genome scale metabolic models derived from microbial genomes. Application of our pipeline to 2,815 human-gut bacteria showed high correlation between phylogenetic distance and metabolic competition/cooperation indices among bacteria. Using a discretization approach, we were able to detect pairs of bacterial species with cooperation scores significantly higher than the average pairs of bacterial species with similar phylogenetic distances. A network community analysis of high metabolic cooperation but low competition reveals distinct modules of bacterial interactions. Our results suggest that niche differentiation plays a dominant role in microbial interactions, while habitat filtering also plays a role among certain clades of bacterial species.Author summaryMicrobial communities, also known as microbiomes, are formed through the interactions of various microbial species. Utilizing genomic sequencing, it is possible to infer the compositional make-up of communities as well as predict their metabolic interactions. However, because some species are more similarly related to each other, while others are more distantly related, one cannot directly compare metabolic relationships without first accounting for their phylogenetic relatedness. Here we developed a computational pipeline which predicts complimentary and competitive metabolic relationships between bacterial species, while normalizing for their phylogenetic relatedness. Our results show that phylogenetic distances are correlated with metabolic interactions, and factoring out such relationships can help better understand microbial interactions which drive community formation.

scholarly journals Model-based and phylogenetically adjusted quantification of metabolic interaction between microbial species

2020 ◽  
Vol 16 (10) ◽  
pp. e1007951
Author(s):  
Tony J. Lam ◽  
Moses Stamboulian ◽  
Wontack Han ◽  
Yuzhen Ye
Keyword(s):  
Dominant Role ◽  
Bacterial Species ◽  
Community Analysis ◽  
Microbial Interactions ◽  
Phylogenetic Distance ◽  
Metabolic Cooperation ◽  
Bacterial Interactions ◽  
Microbial Species ◽  
Metabolic Models ◽  
Genome Scale

Microbial community members exhibit various forms of interactions. Taking advantage of the increasing availability of microbiome data, many computational approaches have been developed to infer bacterial interactions from the co-occurrence of microbes across diverse microbial communities. Additionally, the introduction of genome-scale metabolic models have also enabled the inference of cooperative and competitive metabolic interactions between bacterial species. By nature, phylogenetically similar microbial species are more likely to share common functional profiles or biological pathways due to their genomic similarity. Without properly factoring out the phylogenetic relationship, any estimation of the competition and cooperation between species based on functional/pathway profiles may bias downstream applications. To address these challenges, we developed a novel approach for estimating the competition and complementarity indices for a pair of microbial species, adjusted by their phylogenetic distance. An automated pipeline, PhyloMint, was implemented to construct competition and complementarity indices from genome scale metabolic models derived from microbial genomes. Application of our pipeline to 2,815 human-gut associated bacteria showed high correlation between phylogenetic distance and metabolic competition/cooperation indices among bacteria. Using a discretization approach, we were able to detect pairs of bacterial species with cooperation scores significantly higher than the average pairs of bacterial species with similar phylogenetic distances. A network community analysis of high metabolic cooperation but low competition reveals distinct modules of bacterial interactions. Our results suggest that niche differentiation plays a dominant role in microbial interactions, while habitat filtering also plays a role among certain clades of bacterial species.

scholarly journals Metabolic rules of microbial community assembly

2020 ◽  
Author(s):  
Sylvie Estrela ◽  
Jean C. C. Vila ◽  
Nanxi Lu ◽  
Djordje Bajic ◽  
Maria Rebolleda-Gomez ◽  
...  
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Community Assembly ◽  
Self Assembly ◽  
Taxonomic Composition ◽  
Species Level ◽  
Growth Responses ◽  
Structure Of Communities ◽  
Genome Scale ◽  
Microbial Community Assembly

AbstractTo develop a quantitative theory that can predict how microbiomes assemble, and how they respond to perturbations, we must identify which descriptive features of microbial communities are reproducible and predictable, which are unpredictable, and why. The emergent metagenomic structure of communities is often quantitatively convergent in similar habitats, with highly similar fractions of the metagenome being devoted to the same metabolic pathways. By contrast, the species-level taxonomic composition is often highly variable even in replicate environments. The mechanisms behind these patterns are not yet understood. By studying the self-assembly of hundreds of communities in replicate, synthetic habitats, we show that the reproducibility of microbial community assembly reflects an emergent metabolic structure, which is quantitatively predictable from first-principles, genome-scale metabolic models. Taxonomic variability within functional groups arises through multistability in population dynamics, and the species-level community composition is predictably governed by the mutual competitive exclusion of two sub-dominant strains. Our findings provide a mechanistic bridge between microbial community structure at different levels of organization, and show that the evolutionary conservation of metabolic traits, both in terms of growth responses and niches constructed, can be leveraged to quantitatively predict the taxonomic and metabolic structure of microbial communities.

scholarly journals Metage2Metabo: metabolic complementarity applied to genomes of large-scale microbiotas for the identification of keystone species

2019 ◽  
Author(s):  
Arnaud Belcour ◽  
Clémence Frioux ◽  
Méziane Aite ◽  
Anthony Bretaudeau ◽  
Anne Siegel
Keyword(s):  
Large Scale ◽  
Metabolic Networks ◽  
Keystone Species ◽  
Large Family ◽  
Functional Screening ◽  
Metabolic Cooperation ◽  
Metabolic Functions ◽  
Genome Scale ◽  
Equivalent Properties ◽  
Processing Solution

AbstractCapturing the functional diversity of microbiotas entails identifying metabolic functions and species of interest within hundreds or thousands. Starting from genomes, a way to functionally analyse genetic information is to build metabolic networks. Yet, no method enables a functional screening of such a large number of metabolic networks nor the identification of critical species with respect to metabolic cooperation.Metage2Metabo (M2M) addresses scalability issues raised by metagenomics datasets to identify keystone, essential and alternative symbionts in large microbiotas communities with respect to individual metabolism and collective metabolic complementarity. Genome-scale metabolic networks for the community can be either provided by the user or very efficiently reconstructed from a large family of genomes thanks to a multi-processing solution to run the Pathway Tools software. The pipeline was applied to 1,520 genomes from the gut microbiota and 913 metagenome-assembled genomes of the rumen microbiota. Reconstruction of metabolic networks and subsequent metabolic analyses were performed in a reasonable time.M2M identifies keystone, essential and alternative organisms by reducing the complexity of a large-scale microbiota into minimal communities with equivalent properties, suitable for further analyses.

scholarly journals Metage2Metabo, microbiota-scale metabolic complementarity for the identication of key species

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Arnaud Belcour ◽  
Clémence Frioux ◽  
Méziane Aite ◽  
Anthony Bretaudeau ◽  
Falk Hildebrand ◽  
...  
Keyword(s):  
Functional Diversity ◽  
Large Scale ◽  
Metabolic Networks ◽  
De Novo ◽  
Functional Screening ◽  
Metabolic Cooperation ◽  
Metabolic Functions ◽  
Key Species ◽  
Genome Scale ◽  
Equivalent Properties

To capture the functional diversity of microbiota, one must identify metabolic functions and species of interest within hundreds or thousands of microorganisms. We present Metage2Metabo (M2M) a resource that meets the need for de-novo functional screening of genome-scale metabolic networks (GSMNs) at the scale of a metagenome, and the identification of critical species with respect to metabolic cooperation. M2M comprises a flexible pipeline for the characterisation of individual metabolisms and collective metabolic complementarity. In addition, M2M identifies key species, that are meaningful members of the community for functions of interest. We demonstrate that M2M is applicable to collections of genomes as well as metagenome-assembled genomes, permits an efficient GSMN reconstruction with Pathway Tools, and assesses the cooperation potential between species. M2M identifies key organisms by reducing the complexity of a large-scale microbiota into minimal communities with equivalent properties, suitable for further analyses.

scholarly journals Metabolic overlap in environmentally diverse microbial communities

2019 ◽  
Author(s):  
Eric R. Hester ◽  
Mike S.M. Jetten ◽  
Cornelia U. Welte ◽  
Sebastian Lücker
Keyword(s):  
Microbial Communities ◽  
Future Research ◽  
Aquatic Environments ◽  
Competition And Cooperation ◽  
Microbial Species ◽  
Common Resource ◽  
Animal Hosts ◽  
Genome Scale ◽  
Genome Information ◽  
Detailed Picture

AbstractThe majority of microbial communities consist of hundreds to thousands of species, creating a massive network of organisms competing for available resources within an ecosystem. In natural microbial communities it appears that many microbial species have highly redundant metabolisms and seemingly are capable of utilizing the same substrates. This is paradoxical, as theory indicates that species requiring a common resource should outcompete one another. To better understand why microbial species can co-exist, we developed Metabolic Overlap (MO) as a new metric to survey the functional redundancy of microbial communities at the genome scale across a wide variety of ecosystems. Using metagenome-assembled genomes, we surveyed over 1200 studies across ten ecosystem types. We found the highest MO in extreme (i.e., low pH/high temperature) and aquatic environments, while the lowest MO was observed in communities associated with animal hosts, or the built/engineered environment. In addition, different metabolism subcategories were explored for their degree of metabolic overlap. For instance, overlap in nitrogen metabolism was among the lowest in Animal and Engineered ecosystems, while the most was in species from the Built environment. Together, we present a metric that utilizes whole genome information to explore overlapping niches of microbes. This provides a detailed picture of potential metabolic competition and cooperation between species present in an ecosystem, indicates the main substrate types sustaining the community and serves as a valuable tool to generate hypotheses for future research.

Quantitative EM of gap junction distribution in mutant drosophila wing discs

1983 ◽  
Vol 41 ◽  
pp. 720-721
Author(s):  
J.S. Ryerse
Keyword(s):  
Gap Junctions ◽  
Growth Control ◽  
Intercellular Junctions ◽  
Wing Disc ◽  
En Bloc ◽  
Metabolic Cooperation ◽  
Drosophila Wing ◽  
Adult Wing ◽  
Wing Discs ◽  
Wing Pouch

Gap junctions are intercellular junctions found in both vertebrates and invertebrates through which ions and small molecules can pass. Their distribution in tissues could be of critical importance for ionic coupling or metabolic cooperation between cells or for regulating the intracellular movement of growth control and pattern formation factors. Studies of the distribution of gap junctions in mutants which develop abnormally may shed light upon their role in normal development. I report here the distribution of gap junctions in the wing pouch of 3 Drosophila wing disc mutants, vg (vestigial) a cell death mutant, 1(2)gd (lethal giant disc) a pattern abnormality mutant and 1(2)gl (lethal giant larva) a neoplastic mutant and compare these with wildtype wing discs.The wing pouch (the anlagen of the adult wing blade) of a wild-type wing disc is shown in Fig. 1 and consists of columnar cells (Fig. 5) joined by gap junctions (Fig. 6). 14000x EMs of conventionally processed, UA en bloc stained, longitudinally sectioned wing pouches were enlarged to 45000x with a projector and tracings were made on which the lateral plasma membrane (LPM) and gap junctions were marked.

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