Modelling spatial patterns in host-associated microbial communities

dc.contributor.authorRuuskanen Matti O
dc.contributor.authorSommeria-Klein Guilhem
dc.contributor.authorHavulinna Aki S
dc.contributor.authorNiiranen Teemu J
dc.contributor.authorLahti Leo
dc.contributor.organizationfi=data-analytiikka|en=Data-analytiikka|
dc.contributor.organizationfi=sisätautioppi|en=Internal Medicine|
dc.contributor.organizationfi=tyks, vsshp|en=tyks, varha|
dc.contributor.organization-code1.2.246.10.2458963.20.40502528769
dc.contributor.organization-code1.2.246.10.2458963.20.68940835793
dc.converis.publication-id54398705
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/54398705
dc.date.accessioned2022-10-27T12:11:03Z
dc.date.available2022-10-27T12:11:03Z
dc.description.abstractMicrobial communities exhibit spatial structure at different scales, due to constant interactions with their environment and dispersal limitation. While this spatial structure is often considered in studies focusing on free-living environmental communities, it has received less attention in the context of host-associated microbial communities or microbiota. The wider adoption of methods accounting for spatial variation in these communities will help to address open questions in basic microbial ecology as well as realize the full potential of microbiome-aided medicine. Here, we first overview known factors affecting the composition of microbiota across diverse host types and at different scales, with a focus on the human gut as one of the most actively studied microbiota. We outline a number of topical open questions in the field related to spatial variation and patterns. We then review the existing methodology for the spatial modelling of microbiota. We suggest that methodology from related fields, such as systems biology and macro-organismal ecology, could be adapted to obtain more accurate models of spatial structure. We further posit that methodological developments in the spatial modelling and analysis of microbiota could in turn broadly benefit theoretical and applied ecology and contribute to the development of novel industrial and clinical applications.
dc.identifier.eissn1462-2920
dc.identifier.jour-issn1462-2912
dc.identifier.olddbid173744
dc.identifier.oldhandle10024/156838
dc.identifier.urihttps://www.utupub.fi/handle/11111/33009
dc.identifier.urlhttps://doi.org/10.1111/1462-2920.15462
dc.identifier.urnURN:NBN:fi-fe2021050328503
dc.language.isoen
dc.okm.affiliatedauthorRuuskanen, Matti
dc.okm.affiliatedauthorSommeria-Klein, Guilhem
dc.okm.affiliatedauthorNiiranen, Teemu
dc.okm.affiliatedauthorLahti, Leo
dc.okm.affiliatedauthorDataimport, tyks, vsshp
dc.okm.discipline3111 Biomedicineen_GB
dc.okm.discipline3121 Internal medicineen_GB
dc.okm.discipline3141 Health care scienceen_GB
dc.okm.discipline3111 Biolääketieteetfi_FI
dc.okm.discipline3121 Sisätauditfi_FI
dc.okm.discipline3141 Terveystiedefi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA2 Scientific Article
dc.publisherWILEY
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.doi10.1111/1462-2920.15462
dc.relation.ispartofjournalEnvironmental Microbiology
dc.source.identifierhttps://www.utupub.fi/handle/10024/156838
dc.titleModelling spatial patterns in host-associated microbial communities
dc.year.issued2021

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