Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/23695
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dc.contributor.authorMolina Ortiz, JP-
dc.contributor.authorMcClure, DD-
dc.contributor.authorShanahan, ER-
dc.contributor.authorDehghani, F-
dc.contributor.authorHolmes, AJ-
dc.contributor.authorRead, MN-
dc.date.accessioned2021-12-07T15:12:19Z-
dc.date.available2021-12-07T15:12:19Z-
dc.date.issued2021-08-30-
dc.identifier1965698-
dc.identifier.citationMolina Ortiz, J.P., McClure, D.D., Shanahan, E.R., Dehghani, F., Holmes, A.J. and Read, M.N. (2021) 'Enabling rational gut microbiome manipulations by understanding gut ecology through experimentally-evidenced in silico models', Gut Microbes, 13 (1), pp. 1 - 19. doi: 10.1080/19490976.2021.1965698.en_US
dc.identifier.issn1949-0984-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/23695-
dc.description.abstract© 2021 The Author(s). The gut microbiome has emerged as a contributing factor in non-communicable disease, rendering it a target of health-promoting interventions. Yet current understanding of the host-microbiome dynamic is insufficient to predict the variation in intervention outcomes across individuals. We explore the mechanisms that underpin the gut bacterial ecosystem and highlight how a more complete understanding of this ecology will enable improved intervention outcomes. This ecology varies within the gut over space and time. Interventions disrupt these processes, with cascading consequences throughout the ecosystem. In vivo studies cannot isolate and probe these processes at the required spatiotemporal resolutions, and in vitro studies lack the representative complexity required. However, we highlight that, together, both approaches can inform in silico models that integrate cellular-level dynamics, can extrapolate to explain bacterial community outcomes, permit experimentation and observation over ecological processes at high spatiotemporal resolution, and can serve as predictive platforms on which to prototype interventions. Thus, it is a concerted integration of these techniques that will enable rational targeted manipulations of the gut ecosystem.en_US
dc.description.sponsorshipUniversity of Sydney’s Centre for Advanced Food and Engineering; JPMO acknowledges a PhD scholarship from the Faculty of Engineering at the University of Sydney. ERS acknowledges the financial support from the à Beckett Cancer Research Trust (University of Sydney Fellowship).en_US
dc.format.extent1 - 19-
dc.format.mediumPrint-Electronic-
dc.languageen-
dc.language.isoen_USen_US
dc.rights© 2021 The Author(s). Published with license by Taylor & Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectprecision medicineen_US
dc.subjectdietary interventionen_US
dc.subjectgut microbial ecologyen_US
dc.subjecthost–microbiome interactionsen_US
dc.subjectagent-based modelingen_US
dc.subjectmicrobial culturingen_US
dc.subjectcomputational microbiologyen_US
dc.subjectsystems biologyen_US
dc.titleEnabling rational gut microbiome manipulations by understanding gut ecology through experimentally-evidenced in silico modelsen_US
dc.typeArticleen_US
dc.identifier.doihttps://doi.org/10.1080/19490976.2021.1965698-
dc.relation.isPartOfGut Microbes-
pubs.issue1-
pubs.publication-statusPublished-
pubs.volume13-
dc.identifier.eissn1949-0984-
Appears in Collections:Chemistry

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