Differential network analysis of oral microbiome metatranscriptomes identifies community scale metabolic restructuring in dental caries

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dc.contributor.authorEspinoza, J.
dc.contributor.authorTorralba, M.
dc.contributor.authorLeong, P.
dc.contributor.authorSaffery, R.
dc.contributor.authorBockmann, M.
dc.contributor.authorKuelbs, C.
dc.contributor.authorSingh, S.
dc.contributor.authorHughes, T.
dc.contributor.authorCraig, J.
dc.contributor.authorNelson, K.
dc.contributor.authorDupont, C.
dc.contributor.editorBrenner, D.
dc.date.issued2022
dc.descriptionAdvance access publication date: 18 October 2022
dc.description.abstractDental caries is a microbial disease and the most common chronic health condition, affecting nearly 3.5 billion people worldwide. In this study, we used a multiomics approach to characterize the supragingival plaque microbiome of 91 Australian children, generating 658 bacterial and 189 viral metagenome-assembled genomes with transcriptional profiling and gene-expression network analysis. We developed a reproducible pipeline for clustering sample-specific genomes to integrate metagenomics and metatranscriptomics analyses regardless of biosample overlap. We introduce novel feature engineering and compositionally-aware ensemble network frameworks while demonstrating their utility for investigating regime shifts associated with caries dysbiosis. These methods can be applied when differential abundance modeling does not capture statistical enrichments or the results from such analysis are not adequate for providing deeper insight into disease. We identified which organisms and metabolic pathways were central in a coexpression network as well as how these networks were rewired between caries and caries-free phenotypes. Our findings provide evidence of a core bacterial microbiome that was transcriptionally active in the supragingival plaque of all participants regardless of phenotype, but also show highly diagnostic changes in the ways that organisms interact. Specifically, many organisms exhibit high connectedness with central carbon metabolism to Cardiobacterium and this shift serves a bridge between phenotypes. Our evidence supports the hypothesis that caries is a multifactorial ecological disease.
dc.description.statementofresponsibilityJosh L. Espinoza, Manolito Torralba, Pamela Leong, Richard Saffery, Michelle Bockmann, Claire Kuelbs, Suren Singh, Toby Hughes, Jeffrey M. Craig, Karen E. Nelson and Chris L. Dupont
dc.identifier.citationPNAS Nexus, 2022; 1(5):pgac239-1-pgac239-16
dc.identifier.doi10.1093/pnasnexus/pgac239
dc.identifier.issn2752-6542
dc.identifier.issn2752-6542
dc.identifier.orcidBockmann, M. [0000-0001-8050-0993]
dc.identifier.orcidHughes, T. [0000-0001-8668-7744]
dc.identifier.urihttps://hdl.handle.net/2440/139755
dc.language.isoen
dc.publisherOxford University Press (OUP)
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/437015
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/607358
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/349448
dc.relation.granthttp://purl.org/au-research/grants/nhmrc/1006294
dc.rights© The Author(s) 2022. Published by Oxford University Press on behalf of the National Academy of Sciences. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
dc.source.urihttps://doi.org/10.1093/pnasnexus/pgac239
dc.subjectdental caries; feature engineering; machine-learning; oral microbiome
dc.titleDifferential network analysis of oral microbiome metatranscriptomes identifies community scale metabolic restructuring in dental caries
dc.typeJournal article
pubs.publication-statusPublished

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