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dc.contributor.authorScotti, Riccardo
dc.contributor.authorSouthern, Stuart
dc.contributor.authorBoinett, Christine
dc.contributor.authorJenkins, Timothy P.
dc.contributor.authorCortés, Alba
dc.contributor.authorCantacessi, Cinzia
dc.date.accessioned2021-02-02T17:15:00Z
dc.date.available2021-02-02T17:15:00Z
dc.date.issued2020-02-03
dc.date.submitted2019-10-13
dc.identifier.others40168-019-0782-7
dc.identifier.other782
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/317032
dc.description.abstractAbstract: Background: The complex network of interactions occurring between gastrointestinal (GI) and extra-intestinal (EI) parasitic helminths of humans and animals and the resident gut microbial flora is attracting increasing attention from biomedical researchers, because of the likely implications for the pathophysiology of helminth infection and disease. Nevertheless, the vast heterogeneity of study designs and microbial community profiling strategies, and of bioinformatic and biostatistical approaches for analyses of metagenomic sequence datasets hinder the identification of bacterial targets for follow-up experimental investigations of helminth-microbiota cross-talk. Furthermore, comparative analyses of published datasets are made difficult by the unavailability of a unique repository for metagenomic sequence data and associated metadata linked to studies aimed to explore potential changes in the composition of the vertebrate gut microbiota in response to GI and/or EI helminth infections. Results: Here, we undertake a meta-analysis of available metagenomic sequence data linked to published studies on helminth-microbiota cross-talk in humans and veterinary species using a single bioinformatic pipeline, and introduce the 'MICrobiome HELminth INteractions database' (MICHELINdb), an online resource for mining of published sequence datasets, and corresponding metadata, generated in these investigations. Conclusions: By increasing data accessibility, we aim to provide the scientific community with a platform to identify gut microbial populations with potential roles in the pathophysiology of helminth disease and parasite-mediated suppression of host inflammatory responses, and facilitate the design of experiments aimed to disentangle the cause(s) and effect(s) of helminth-microbiota relationships. 3-P6fXwiUKUizQ4bBEnJ8wVideo abstract.
dc.languageen
dc.publisherBioMed Central
dc.rightsAttribution 4.0 International (CC BY 4.0)en
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en
dc.subjectResearch
dc.titleMICHELINdb: a web-based tool for mining of helminth-microbiota interaction datasets, and a meta-analysis of current research
dc.typeArticle
dc.date.updated2021-02-02T17:14:59Z
prism.issueIdentifier1
prism.publicationNameMicrobiome
prism.volume8
dc.identifier.doi10.17863/CAM.64143
dcterms.dateAccepted2019-12-27
rioxxterms.versionofrecord10.1186/s40168-019-0782-7
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidCantacessi, Cinzia [0000-0001-6863-2950]
dc.identifier.eissn2049-2618
pubs.funder-project-idIsaac Newton Trust (GB) (N/A)
pubs.funder-project-idBiotechnology and Biological Sciences Research Council (N/A)
pubs.funder-project-idUniversity of Cambridge (N/A)
pubs.funder-project-idFundación Alfonso Martín Escudero (N/A)


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Attribution 4.0 International (CC BY 4.0)
Except where otherwise noted, this item's licence is described as Attribution 4.0 International (CC BY 4.0)