Dataset Information

Co-existence of Network Architectures Supporting the Human Gut Microbiome.

ABSTRACT: Microbial organisms of the human gut microbiome do not exist in isolation but form complex and diverse interactions to maintain health and reduce risk of disease development. The organization of the gut microbiome is assumed to be a singular assortative network, where interactions between operational taxonomic units (OTUs) can readily be clustered into segregated and distinct communities. Here, we leverage recent methodological advances in network modeling to assess whether communities in the human microbiome exhibit a single network structure or whether co-existing mesoscale network architectures are present. We found evidence for core-periphery structures in the microbiome, supported by strong, assortative community interactions. This complex architecture, coupled with previously reported functional roles of OTUs, provides a nuanced understanding of how the microbiome simultaneously promotes high microbial diversity and maintains functional redundancy.

SUBMITTER: Hall CV

PROVIDER: S-EPMC6911941 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Co-existence of Network Architectures Supporting the Human Gut Microbiome.

Hall Caitlin V CV Lord Anton A Betzel Richard R Zakrzewski Martha M Simms Lisa A LA Zalesky Andrew A Radford-Smith Graham G Cocchi Luca L

iScience 20191121

Microbial organisms of the human gut microbiome do not exist in isolation but form complex and diverse interactions to maintain health and reduce risk of disease development. The organization of the gut microbiome is assumed to be a singular assortative network, where interactions between operational taxonomic units (OTUs) can readily be clustered into segregated and distinct communities. Here, we leverage recent methodological advances in network modeling to assess whether communities in the hu ...[more]

PMID: 31812808

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Project description:Human learners acquire complex interconnected networks of relational knowledge. The capacity for such learning naturally depends on two factors: the architecture (or informational structure) of the knowledge network itself and the architecture of the computational unit-the brain-that encodes and processes the information. That is, learning is reliant on integrated network architectures at two levels: the epistemic and the computational, or the conceptual and the neural. Motivated by a wish to understand conventional human knowledge, here, we discuss emerging work assessing network constraints on the learnability of relational knowledge, and theories from statistical physics that instantiate the principles of thermodynamics and information theory to offer an explanatory model for such constraints. We then highlight similarities between those constraints on the learnability of relational networks, at one level, and the physical constraints on the development of interconnected patterns in neural systems, at another level, both leading to hierarchically modular networks. To support our discussion of these similarities, we employ an operational distinction between the modeller (e.g. the human brain), the model (e.g. a single human's knowledge) and the modelled (e.g. the information present in our experiences). We then turn to a philosophical discussion of whether and how we can extend our observations to a claim regarding explanation and mechanism for knowledge acquisition. What relation between hierarchical networks, at the conceptual and neural levels, best facilitate learning? Are the architectures of optimally learnable networks a topological reflection of the architectures of comparably developed neural networks? Finally, we contribute to a unified approach to hierarchies and levels in biological networks by proposing several epistemological norms for analysing the computational brain and social epistemes, and for developing pedagogical principles conducive to curious thought. This article is part of the theme issue 'Unifying the essential concepts of biological networks: biological insights and philosophical foundations'.

Project description:BackgroundBacteriophages (phages) and bacteria within the gut microbiome persist in long-term stable coexistence. These interactions are driven by eco-evolutionary dynamics, where bacteria employ a variety of mechanisms to evade phage infection, while phages rely on counterstrategies to overcome these defences. Among the most abundant phages in the gut are the crAss-like phages that infect members of the Bacteroidales, in particular Bacteroides. In this study, we explored some of the mechanisms enabling the co-existence of four phage-Bacteroidales host pairs in vitro using a multi-omics approach (transcriptomics, proteomics and metabolomics). These included three Bacteroides species paired with three crAss-like phages (Bacteroides intestinalis and ϕcrAss001, Bacteroides xylanisolvens and ϕcrAss002, and an acapsular mutant of Bacteroides thetaiotaomicron with DAC15), and Parabacteroides distasonis paired with the siphovirus ϕPDS1.ResultsWe show that phase variation of individual capsular polysaccharides (CPSs) is the primary mechanism promoting phage co-existence in Bacteroidales, but this is not the only strategy. Alternative resistance mechanisms, while potentially less efficient than CPS phase variation, can be activated to support bacterial survival by regulating gene expression and resulting in metabolic adaptations, particularly in amino acid degradation pathways. These mechanisms, also likely regulated by phase variation, enable bacterial populations to persist in the presence of phages, and vice versa. An acapsular variant of B. thetaiotaomicron demonstrated broader transcriptomic, proteomic, and metabolomic changes, supporting the involvement of additional resistance mechanisms beyond CPS variation.ConclusionsThis study advances our understanding of long-term phage-host interaction, offering insights into the long-term persistence of crAss-like phages and extending these observations to other phages, such as ϕPDS1. Knowledge of the complexities of phage-bacteria interactions is essential for designing effective phage therapies and improving human health through targeted microbiome interventions.

Dataset Information

Co-existence of Network Architectures Supporting the Human Gut Microbiome.

Publications

Co-existence of Network Architectures Supporting the Human Gut Microbiome.

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