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Accounting for bacterial overlap between raw water communities and contaminating sources improves the accuracy of signature-based microbial source tracking
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2018 (English)In: Frontiers in Microbiology, ISSN 1664-302X, E-ISSN 1664-302X, Vol. 9, article id 2364Article in journal (Refereed) Published
Abstract [en]

Microbial source tracking (MST) analysis is essential to identifying and mitigating the fecal pollution of water resources. The signature-based MST method uses a library of sequences to identify contaminants based on operational taxonomic units (OTUs) that are unique to a certain source. However, no clear guidelines for how to incorporate OTU overlap or natural variation in the raw water bacterial community into MST analyses exist. We investigated how the inclusion of bacterial overlap between sources in the library affects source prediction accuracy. To achieve this, large-scale sampling-including feces from seven species, raw sewage, and raw water samples from water treatment plants - was followed by 16S rRNA amplicon sequencing. The MST library was defined using three settings: (i) no raw water communities represented; (ii) raw water communities selected through clustering analysis; and (iii) local water communities collected across consecutive years. The results suggest that incorporating either the local background or representative bacterial composition improves MST analyses, as the results were positively correlated to measured levels of fecal indicator bacteria and the accuracy at which OTUs were assigned to the correct contamination source increased fourfold. Using the proportion of OTUs with high source origin probability, underpinning a contaminating signal, is a solid foundation in a framework for further deciphering and comparing contaminating signals derived in signature-based MST approaches. In conclusion, incorporating background bacterial composition of water in MST can improve mitigation efforts for minimizing the spread of pathogenic and antibiotic resistant bacteria into essential freshwater resources.

Place, publisher, year, edition, pages
Frontiers Media S.A., 2018. Vol. 9, article id 2364
Keywords [en]
microbial source tracking, fecal contamination, bacterial community analysis, microbial community profiling, 16S rRNA amplicon
National Category
Microbiology
Identifiers
URN: urn:nbn:se:umu:diva-152872DOI: 10.3389/fmicb.2018.02364ISI: 000446079800001OAI: oai:DiVA.org:umu-152872DiVA, id: diva2:1259984
Funder
Swedish Civil Contingencies Agency, SOFA-2013-02Swedish Civil Contingencies Agency, SOFA-2013-03Available from: 2018-10-31 Created: 2018-10-31 Last updated: 2018-10-31Bibliographically approved

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Borgmästars, EmmyStenberg, PerSjödin, Andreas

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SurgeryDepartment of Ecology and Environmental SciencesDepartment of Chemistry
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