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Environ Sci Technol. 2018 Dec 4;52(23):13914-13924. doi: 10.1021/acs.est.8b04895. Epub 2018 Nov 19.

Abundance of Chlorinated Solvent and 1,4-Dioxane Degrading Microorganisms at Five Chlorinated Solvent Contaminated Sites Determined via Shotgun Sequencing.

Author information

1
Department of Civil and Environmental Engineering , Michigan State University , East Lansing , Michigan 48824 , United States.
2
APTIM , 17 Princess Road , Lawrenceville , New Jersey 08648 , United States.
3
Center for Microbial Ecology , Michigan State University , East Lansing , Michigan 48824 , United States.

Abstract

Shotgun sequencing was used for the quantification of taxonomic and functional biomarkers associated with chlorinated solvent bioremediation in 20 groundwater samples (five sites), following bioaugmentation with SDC-9. The analysis determined the abundance of (1) genera associated with chlorinated solvent degradation, (2) reductive dehalogenase (RDases) genes, (3) genes associated with 1,4-dioxane removal, (4) genes associated with aerobic chlorinated solvent degradation, and (5) D. mccartyi genes associated with hydrogen and corrinoid metabolism. The taxonomic analysis revealed numerous genera previously linked to chlorinated solvent degradation, including Dehalococcoides, Desulfitobacterium, and Dehalogenimonas. The functional gene analysis indicated vcrA and tceA from D. mccartyi were the RDases with the highest relative abundance. Reads aligning with both aerobic and anaerobic biomarkers were observed across all sites. Aerobic solvent degradation genes, etnC or etnE, were detected in at least one sample from each site, as were pmoA and mmoX. The most abundant 1,4-dioxane biomarker detected was Methylosinus trichosporium OB3b mmoX. Reads aligning to thmA or Pseudonocardia were not found. The work illustrates the importance of shotgun sequencing to provide a more complete picture of the functional abilities of microbial communities. The approach is advantageous over current methods because an unlimited number of functional genes can be quantified.

PMID:
30427665
DOI:
10.1021/acs.est.8b04895
[Indexed for MEDLINE]

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