Author
Listed:
- Monika A. Roy
(Department of Environmental Health Sciences, School of Public Health & Health Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA
Biotechnology Training Program, University of Massachusetts Amherst, Amherst, MA 01003, USA)
- Jean M. Arnaud
(Department of Environmental Health Sciences, School of Public Health & Health Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA)
- Paul M. Jasmin
(Equipes mobiles d’intervention rapide (EMIRA) du Ministère de la Santé Publique et de la Population (MSPP), Hinche HT 5111, Haiti)
- Steve Hamner
(Department of Environmental Health Sciences, School of Public Health & Health Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA)
- Nur A. Hasan
(CosmosID Inc., 1600 East Gude Drive, Rockville, MD 20850, USA
Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA)
- Rita R. Colwell
(CosmosID Inc., 1600 East Gude Drive, Rockville, MD 20850, USA
Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA)
- Timothy E. Ford
(Department of Environmental Health Sciences, School of Public Health & Health Sciences, University of Massachusetts Amherst, Amherst, MA 01003, USA)
Abstract
The cholera epidemic that occurred in Haiti post-earthquake in 2010 has resulted in over 9000 deaths during the past eight years. Currently, morbidity and mortality rates for cholera have declined, but cholera cases still occur on a daily basis. One continuing issue is an inability to accurately predict and identify when cholera outbreaks might occur. To explore this surveillance gap, a metagenomic approach employing environmental samples was taken. In this study, surface water samples were collected at two time points from several sites near the original epicenter of the cholera outbreak in the Central Plateau of Haiti. These samples underwent whole genome sequencing and subsequent metagenomic analysis to characterize the microbial community of bacteria, fungi, protists, and viruses, and to identify antibiotic resistance and virulence associated genes. Replicates from sites were analyzed by principle components analysis, and distinct genomic profiles were obtained for each site. Cholera toxin converting phage was detected at one site, and Shiga toxin converting phages at several sites. Members of the Acinetobacter family were frequently detected in samples, including members implicated in waterborne diseases. These results indicate a metagenomic approach to evaluating water samples can be useful for source tracking and the surveillance of pathogens such as Vibrio cholerae over time, as well as for monitoring virulence factors such as cholera toxin.
Suggested Citation
Monika A. Roy & Jean M. Arnaud & Paul M. Jasmin & Steve Hamner & Nur A. Hasan & Rita R. Colwell & Timothy E. Ford, 2018.
"A Metagenomic Approach to Evaluating Surface Water Quality in Haiti,"
IJERPH, MDPI, vol. 15(10), pages 1-16, October.
Handle:
RePEc:gam:jijerp:v:15:y:2018:i:10:p:2211-:d:174672
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