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ARS Home » Pacific West Area » Albany, California » Western Regional Research Center » Produce Safety and Microbiology Research » Research » Publications at this Location » Publication #366639

Research Project: Ecology and Detection of Human Pathogens in the Produce Production Continuum

Location: Produce Safety and Microbiology Research

Title: Metagenomics as a public health risk assessment tool in a study of natural creek sediments influenced by agricultural and livestock runoff: potential and limitations

Author
item SUTTNER, BRITTANY - Georgia Institute Of Technology
item JOHNSTON, ERIC - Georgia Institute Of Technology
item ORELLANA, LUIS - Georgia Institute Of Technology
item RODRIGUEZ, LUIS - Georgia Institute Of Technology
item HATT, JANET - Georgia Institute Of Technology
item Carychao, Diana
item Carter, Michelle
item Cooley, Michael - Mike
item KONSTANTINIDIS, KONSTANTINOS - Georgia Institute Of Technology

Submitted to: Applied and Environmental Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/2/2020
Publication Date: 3/2/2020
Citation: Suttner, B.J., Johnston, E.R., Orellana, L.H., Rodriguez, L.M., Hatt, J.K., Carychao, D.K., Carter, M.Q., Cooley, M.B., Konstantinidis, K.T. 2020. Metagenomics as a public health risk assessment tool in a study of natural creek sediments influenced by agricultural and livestock runoff: potential and limitations. Applied and Environmental Microbiology. 86(6):e02525-19. https://doi.org/10.1128/AEM.02525-19.
DOI: https://doi.org/10.1128/AEM.02525-19

Interpretive Summary: Current agricultural and livestock practices contribute to fecal contamination in the environment and the spread of food- and waterborne disease and antibiotic resistance genes (ARGs). Traditionally, the level of pollution and risk to public health are assessed by culture-based tests for the intestinal bacterium Escherichia coli. However, the accuracy of these traditional methods (e.g., low accuracy in quanti'cation, and false-positive signal when PCR based) and their suitability for sediments remain unclear. We collected sediments for a time series metagenomics study from one of the most highly productive agricultural regions in the United States in order to assess how agricultural runoff affects the native microbial communities and if the presence of Shiga toxin-producing Escherichia coli (STEC) in sediment samples can be detected directly by sequencing. Our study provided important information on the potential for using metagenomics as a tool for assessment of public health risk in natural environments.

Technical Abstract: Little is known about the public health risks associated with natural creek sediments that are affected by runoff and fecal pollution from agricultural and livestock practices. For instance, the persistence of foodborne pathogens such as Shiga toxin-producing Escherichia coli (STEC) originating from these practices remains poorly quanti'ed. Towards closing these knowledge gaps, the water-sediment interface of two creeks in the Salinas River Valley of California was sampled over a 9-month period using metagenomics and traditional culture-based tests for STEC. Our results revealed that these sediment communities are extremely diverse and have functional and taxonomic diversity comparable to that observed in soils. With our sequencing effort (about 4 Gbp per library), we were unable to detect any pathogenic E. coli in the metagenomes of 11 samples that had tested positive using culture-based methods, apparently due to relatively low abundance. Furthermore, there were no signi'cant differences in the abundance of human- or cow-speci'c gut microbiome sequences in the downstream impacted sites compared to that in upstream more pristine (control) sites, indicating natural dilution of anthropogenic inputs. Notably, the high number of metagenomic reads carrying antibiotic resistance genes (ARGs) found in all samples was signi'cantly higher than ARG reads in other available freshwater and soil metagenomes, suggesting that these communities may be natural reservoirs of ARGs. The work presented here should serve as a guide for sampling volumes, amount of sequencing to apply, and what bioinformatics analyses to perform when using metagenomics for public health risk studies of environmental samples such as sediments.