From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota

Bauer, Eugen; Thiele, Ines

doi:10.1128/msystems.00209-17

Cited by 81 publications

(73 citation statements)

References 94 publications

(120 reference statements)

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“…For example, associations between microbes may be non‐random in that phylogenetically or functionally similar species may co‐occur more frequently (e.g. Bauer & Thiele, ). However, non‐random associations detected in the human gut have been found to be often negative and between phylogenetically or functionally similar bacterial species, indicating that competition is likely an important driver of structure in this community (Faust et al, ).…”

Section: Introductionmentioning

confidence: 99%

Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition

Fountain-Jones

Clark

Kinsley

et al. 2020

Journal of Animal Ecology

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Microbial communities are increasingly recognized as crucial for animal health. However, our understanding of how microbial communities are structured across wildlife populations is poor. Mechanisms such as interspecific associations are important in structuring free‐living communities, but we still lack an understanding of how important interspecific associations are in structuring gut microbial communities in comparison with other factors such as host characteristics or spatial proximity of hosts. Here, we ask how gut microbial communities are structured in a population of North American moose Alces alces. We identify key microbial interspecific associations within the moose gut and quantify how important they are relative to key host characteristics, such as body condition, for predicting microbial community composition. We sampled gut microbial communities from 55 moose in a population experiencing decline due to a myriad of factors, including pathogens and malnutrition. We examined microbial community dynamics in this population utilizing novel graphical network models that can explicitly incorporate spatial information. We found that interspecific associations were the most important mechanism structuring gut microbial communities in moose and detected both positive and negative associations. Models only accounting for associations between microbes had higher predictive value compared to models including moose sex, evidence of previous pathogen exposure or body condition. Adding spatial information on moose location further strengthened our model and allowed us to predict microbe occurrences with ~90% accuracy. Collectively, our results suggest that microbial interspecific associations coupled with host spatial proximity are vital in shaping gut microbial communities in a large herbivore. In this case, previous pathogen exposure and moose body condition were not as important in predicting gut microbial community composition. The approach applied here can be used to quantify interspecific associations and gain a more nuanced understanding of the spatial and host factors shaping microbial communities in non‐model hosts.

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Section: Introductionmentioning

confidence: 99%

Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition

Fountain-Jones

Clark

Kinsley

et al. 2020

Journal of Animal Ecology

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“…C) Compartment‐, population‐, and individual‐based models of microbial communities. B and C) Adapted under the Creative Commons Attribution 4.0 International License (CC BY 4.0) . Copyright 2018, American Society for Microbiology.…”

Section: Metabolic Modelingmentioning

confidence: 99%

“…The core of FBA is the selected GEM, followed by the use of a linear programming solver to generate metabolic flux distributions. It does this by searching for optimized solutions to identify the metabolic pathways that are predicted to be functional in the GEM's living counterpart with the given environmental parameters . FBA can be used for metabolic modeling of steady‐state metabolic fluxes in a single species or multiple species.…”

Section: Metabolic Modelingmentioning

confidence: 99%

“…Second, the use of metabolic modeling serves as an efficient way to elucidate the systemic interconnected activity of all the enzymes found within and beyond the same microbial species, giving rise to a complex set of metabolic pathways . To achieve this, the constraint‐based reconstruction and analysis (COBRA) approach on genome‐scale metabolic reconstructions has been developed and applied to study the systems metabolic interactions in the human microbiota and predict the effect of their perturbations on human health caused by dysbiosis or therapeutic interventions …”

Section: Introductionmentioning

confidence: 99%

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Meta‐Omics‐ and Metabolic Modeling‐Assisted Deciphering of Human Microbiota Metabolism

Sieow

Nurminen

Ling

2019

Biotechnology Journal

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The human microbiota is a complex community of commensal, symbiotic, and pathogenic microbes that play a crucial role in maintaining the homeostasis of human health. Such a homeostasis is maintained through the collective functioning of enzymatic genes responsible for the production of metabolites, enabling the interaction and signaling within microbiota as well as between microbes and the human host. Understanding microbial genes, their associated chemistries and functions would be valuable for engineering systemic metabolic pathways within the microbiota to manage human health and diseases. Given that there are many unknown gene metabolic functions and interactions, increasing efforts have been made to gain insights into the underlying functions of microbiota metabolism. This can be achieved through culture‐independent metagenomic approaches and metabolic modeling to simulate the microenvironment of human microbiota. In this article, the recent advances in metagenome mining and functional profiling for the discovery of the genetic and biochemical links in human microbiota metabolism as well as metabolic modeling for simulation and prediction of metabolic fluxes in the human microbiota are reviewed. This review provides useful insights into the understanding, reconstruction, and modulation of the human microbiota guided by the knowledge acquired from the basic understanding of the human microbiota metabolism.

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“…Current computational methods employing high-resolution predictions complement wet lab experiments and expand our current knowledge, which can be used to generate hypotheses for follow-up experiments [48]. Such systems biology approaches include modeling of ecological characteristics or the metabolism of cell communities [49]. In particular, functional pathways and modules of the microbiome can nowadays be annotated using sequence data from metagenomes or from the genomes of single microbial species [50].…”

Section: Computational Modeling Approachesmentioning

confidence: 99%

Functions of the Microbiota for the Physiology of Animal Metaorganisms

et al. 2018

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Animals are usually regarded as independent entities within their respective environments. However, within an organism, eukaryotes and prokaryotes interact dynamically to form the so-called metaorganism or holobiont, where each partner fulfils its versatile and crucial role. This review focuses on the interplay between microorganisms and multicellular eukaryotes in the context of host physiology, in particular aging and mucus-associated crosstalk. In addition to the interactions between bacteria and the host, we highlight the importance of viruses and nonmodel organisms. Moreover, we discuss current culturing and computational methodologies that allow a deeper understanding of underlying mechanisms controlling the physiology of metaorganisms.

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From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota

Abstract: An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities.

Cited by 81 publications

References 94 publications

Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition

Microbial associations and spatial proximity predict North American moose (Alces alces) gastrointestinal community composition

Meta‐Omics‐ and Metabolic Modeling‐Assisted Deciphering of Human Microbiota Metabolism

Functions of the Microbiota for the Physiology of Animal Metaorganisms

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