Your browser doesn't support javascript.
loading
Metagenomics as a Public Health Risk Assessment Tool in a Study of Natural Creek Sediments Influenced by Agricultural and Livestock Runoff: Potential and Limitations.
Suttner, Brittany; Johnston, Eric R; Orellana, Luis H; Rodriguez-R, Luis M; Hatt, Janet K; Carychao, Diana; Carter, Michelle Q; Cooley, Michael B; Konstantinidis, Konstantinos T.
Afiliación
  • Suttner B; School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Johnston ER; School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Orellana LH; Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA.
  • Rodriguez-R LM; School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Hatt JK; School of Biological Sciences, Center for Bioinformatics and Computational Genomics, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Carychao D; School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.
  • Carter MQ; Produce Safety and Microbiology, USDA-ARS Western Regional Research Center, Albany, California, USA.
  • Cooley MB; Produce Safety and Microbiology, USDA-ARS Western Regional Research Center, Albany, California, USA.
  • Konstantinidis KT; Produce Safety and Microbiology, USDA-ARS Western Regional Research Center, Albany, California, USA.
Appl Environ Microbiol ; 86(6)2020 03 02.
Article en En | MEDLINE | ID: mdl-31924621
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 quantified. 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 (∼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 significant differences in the abundance of human- or cow-specific 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 significantly 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.IMPORTANCE 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 quantification, 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.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Salud Pública / Medición de Riesgo / Sedimentos Geológicos / Escherichia coli Shiga-Toxigénica / Metagenómica Tipo de estudio: Etiology_studies / Risk_factors_studies Límite: Animals País/Región como asunto: America do norte Idioma: En Revista: Appl Environ Microbiol Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Salud Pública / Medición de Riesgo / Sedimentos Geológicos / Escherichia coli Shiga-Toxigénica / Metagenómica Tipo de estudio: Etiology_studies / Risk_factors_studies Límite: Animals País/Región como asunto: America do norte Idioma: En Revista: Appl Environ Microbiol Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos