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dc.contributor.authorBhanvadia, Amit
dc.contributor.authorZhu, Roger
dc.contributor.authorAmarnani, Abhimanyu
dc.contributor.authorGibbons, Sean M.
dc.contributor.authorMartello, Laura A.
dc.contributor.authorPakpour, Sepideh
dc.contributor.authorGibbons, Sean Michael
dc.contributor.authorGurry, Thomas Jerome
dc.contributor.authorAlm, Eric J
dc.date.accessioned2018-02-12T19:40:23Z
dc.date.available2018-02-12T19:40:23Z
dc.date.issued2017-11
dc.date.submitted2017-08
dc.identifier.issn2049-2618
dc.identifier.urihttp://hdl.handle.net/1721.1/113594
dc.description.abstractBackground: Colonization by the pathogen Clostridium difficile often occurs in the background of a disrupted microbial community. Identifying specific organisms conferring resistance to invasion by C. difficile is desirable because diagnostic and therapeutic strategies based on the human microbiota have the potential to provide more precision to the management and treatment of Clostridium difficile infection (CDI) and its recurrence. Methods: We conducted a longitudinal study of adult patients diagnosed with their first CDI. We investigated the dynamics of the gut microbiota during antibiotic treatment, and we used microbial or demographic features at the time of diagnosis, or after treatment, to predict CDI recurrence. To check the validity of the predictions, a meta-analysis using a previously published dataset was performed. Results: We observed that patients’ microbiota “before” antibiotic treatment was predictive of disease relapse, but surprisingly, post-antibiotic microbial community is indistinguishable between patients that recur or not. At the individual OTU level, we identified Veillonella dispar as a candidate organism for preventing CDI recurrence; however, we did not detect a corresponding signal in the conducted meta-analysis. Conclusion: Although in our patient population, a candidate organism was identified for negatively predicting CDI recurrence, results suggest the need for larger cohort studies that include patients with diverse demographic characteristics to generalize species that robustly confer colonization resistance against C. difficile and accurately predict disease relapse.en_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofhttp://dx.doi.org/10.1186/s40168-017-0368-1en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceBioMed Centralen_US
dc.titleIdentifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatmenten_US
dc.typeArticleen_US
dc.identifier.citationPakpour, Sepideh, et al. “Identifying Predictive Features of Clostridium Difficile Infection Recurrence before, during, and after Primary Antibiotic Treatment.” Microbiome, vol. 5, no. 1, Dec. 2017.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Center for Microbiome Informatics and Therapeuticsen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineeringen_US
dc.contributor.mitauthorPakpour, Sepideh
dc.contributor.mitauthorGibbons, Sean Michael
dc.contributor.mitauthorGurry, Thomas Jerome
dc.contributor.mitauthorAlm, Eric J
dc.relation.journalMicrobiomeen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2017-11-19T05:27:12Z
dc.language.rfc3066en
dc.rights.holderThe Author(s).
dspace.orderedauthorsPakpour, Sepideh; Bhanvadia, Amit; Zhu, Roger; Amarnani, Abhimanyu; Gibbons, Sean M.; Gurry, Thomas; Alm, Eric J.; Martello, Laura A.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-8639-1860
dc.identifier.orcidhttps://orcid.org/0000-0001-8294-9364
mit.licensePUBLISHER_CCen_US


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