Mapping the ecological networks of microbial communities

Xiao, Yandong; Angulo, Marco Tulio; Friedman, Jonathan; Waldor, Matthew K.; Weiss, Scott T.; Liu, Yang‐Yu

doi:10.1038/s41467-017-02090-2

Cited by 157 publications

(103 citation statements)

References 60 publications

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“…Fort ) and heterogeneous (e.g. Xiao et al ) competitive interactions. In such communities, strong feedbacks are hidden at equilibrium, and only revealed during the dynamics, a situation termed the ‘ghost of competition present’ (Miller et al ).…”

Section: Discussionmentioning

confidence: 99%

Superorganisms or loose collections of species? A unifying theory of community patterns along environmental gradients

et al. 2019

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The question whether communities should be viewed as superorganisms or loose collections of individual species has been the subject of a long-standing debate in ecology. Each view implies different spatiotemporal community patterns. Along spatial environmental gradients, the organismic view predicts that species turnover is discontinuous, with sharp boundaries between communities, while the individualistic view predicts gradual changes in species composition. Using a spatially explicit multispecies competition model, we show that organismic and individualistic forms of community organisation are two limiting cases along a continuum of outcomes. A high variance of competition strength leads to the emergence of organism-like communities due to the presence of alternative stable states, while weak and uniform interactions induce gradual changes in species composition. Dispersal can play a confounding role in these patterns. Our work highlights the critical importance of considering species interactions to understand and predict the responses of species and communities to environmental changes.

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Section: Discussionmentioning

confidence: 99%

Superorganisms or loose collections of species? A unifying theory of community patterns along environmental gradients

et al. 2019

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“…Such modelling approaches include ordinary differential equations 90 and agent-based models 91 and can simulate dynamic changes of regulatory networks (signalling pathways and metabolic pathways) and microbial communities. Mathematical modelling of microbial community dynamics has been reviewed previously 89 .…”

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confidence: 99%

The social network of microorganisms — how auxotrophies shape complex communities

2018

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Microorganisms engage in complex interactions with other organisms and their environment. Recent studies have shown that these interactions are not limited to the exchange of electron donors. Most microorganisms are auxotrophs, thus relying on external nutrients for growth, including the exchange of amino acids and vitamins. Currently, we lack a deeper understanding of auxotrophies in microorganisms and how nutrient requirements differ between different strains and different environments. In this Opinion article, we describe how the study of auxotrophies and nutrient requirements among members of complex communities will enable new insights into community composition and assembly. Understanding this complex network over space and time is crucial for developing strategies to interrogate and shape microbial communities.

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“…We believe systems pharmacology approaches are necessary to identify small molecule drugs for modulating the microbiome ecosystem instead of targeting a single pathogen. With the awareness of the complexity and integrity of microbiota, the reconstruction of microbiota networks is a critical step to study the microbial community and to realize systems pharmacology, and it draws increasing interests [55]. Besides occurrence abundance correlation-based methods, exploring microbes growth sources and chemical products is crucial to elucidate the mechanism of interplay between microbes.…”

Section: Discussionmentioning

confidence: 99%

Small Molecule Modulation of Microbiome Ecosystem: A Systems Pharmacology Perspective

Qiao

Lee

Xie

2020

Preprint

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21 An increasing body of evidence suggests that microbes are not only strongly associated with many 22 human diseases but also responsible for the efficacy, resistance, and toxicity of drugs. Small-23 molecule drugs which can precisely fine-tune the microbial ecosystem on the basis of individual 24 patients may revolutionize biomedicine. However, emerging endeavors in small-molecule 25 microbiome drug discovery continue to follow a conventional "one-drug-one-target-one-disease" 26 process. It is often insufficient and less successful in tackling complex systematic diseases. A 27 systematic pharmacology approach that intervenes multiple interacting pathogenic species in the 28 microbiome, could offer an attractive alternative solution. Advances in the Human Microbiome 29 Project have provided numerous genomics data to study microbial interactions in the complex 30 microbiome community. Integrating microbiome data with chemical genomics and other 31 biological information enables us to delineate the landscape for the small molecule modulation of 32 the human microbiome network. In this paper, we construct a disease-centric signed microbe-33 microbe interaction network using metabolite information of microbes and curated microbe effects 34 on human health from published work. We develop a Signed Random Walk with Restart algorithm 35 for the accurate prediction of pathogenic and commensal species. With a survey on the druggable 36 and evolutionary space of microbe proteins, we find that 8-10% of them can be targeted by existing 37 drugs or drug-like chemicals and that 25% of them have homologs to human proteins. We also 38 demonstrate that drugs for diabetes are enriched in the potential inhibitors that target pathogenic 39 microbe without affecting the commensal microbe, thus can be repurposed to modulate the 40 microbiome ecosystem. We further show that periplasmic and cellular outer membrane proteins 41 are overrepresented in the potential drug targets set in pathogenic microbe, but not in the 3 42 commensal microbe. The systematic studies of polypharmacological landscape of the microbiome 43 network may open a new avenue for the small-molecule drug discovery of microbiome.

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Mapping the ecological networks of microbial communities

Cited by 157 publications

References 60 publications

Superorganisms or loose collections of species? A unifying theory of community patterns along environmental gradients

Superorganisms or loose collections of species? A unifying theory of community patterns along environmental gradients

The social network of microorganisms — how auxotrophies shape complex communities

Small Molecule Modulation of Microbiome Ecosystem: A Systems Pharmacology Perspective

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