,Identifying and developing effective and sensitive detection methods for antimicrobial resistant Salmonella enterica from surface water is a goal of the U.S. National Antimicrobial Resistance Monitoring System (NARMS). No specific microbiological methods used in surveillance efforts for Salmonella enterica or antimicrobial resistant S. enterica in water have been standardized or reported in the U.S. Here we describe a multi-laboratory evaluation of four methods, bulk water enrichment (BW), vertical Modified Moore Swab (VMMS), modified Standard Method 9260.B3 (SM), and dead-end ultrafiltration (DEUF), to recover S. enterica from surface water. In Phase 1, one-liter volumes of surface water (n=60) were collected from the same site in Fall 2021 on five different dates. Water was shipped and analyzed at four different USDA ARS laboratories for recovery of environmental Salmonella and an inoculated fluorescent S. Typhimurium strain (ca. 30 CFU/L). One-liter samples (n=20) were subjected to recovery and enrichment by either BW, VMMS, or SM. Overall, fluorescent S. Typhimurium and environmental Salmonella spp. were recovered from 65% (39/60) and 45% (27/60) of water samples, respectively. SM, VMMS, and BW recovered fluorescent S. Typhimurium from 75%, 60% and 60% of inoculated samples, respectively. Analysis by Chi-squared test determined that laboratory location had a significant (p < 0.05) effect on recovery compared to method or date of water collection. In Phase 2, DEUF was compared to SM at two different laboratory locations to recover fluorescent S. Typhimurium (30 CFU/L) from 1-L samples. SM and DEUF recovered S. Typhimurium from 100% (20/20) and 95% (19/20) of inoculated water samples, respectively; laboratory location nor recovery method (p> 0.05) affected S. Typhimurium recovery. Results indicate that SM method consistently recovered low levels of Salmonella from inoculated water samples and should be prioritized for Salmonella recovery from surface water.,Resources in this dataset:,,

This is a compiled data set for the qPCR analyses, bacterial enumeration analyses, and water quality parameters collected for this study. This dataset is associated with the following publication: Buse, H., B. Morris, and E. Rice. Early detection of viable Francisella tularensis in environmental matrices byculture-based PCR. BMC Microbiology. BioMed Central Ltd, London, UK, 20(66): 15, (2020).

,This repository contains data supporting the publication, "Detection of viral, bacterial, and protozoan pathogens and microbial source tracking markers in paired large- and small-volume water samples." The dataset comprises qPCR concentrations of microbial targets in paired large volume and small volume samples from field studies and laboratory recovery experiments, as described in the main publication.,"Field studies.csv" contains sample data and target concentrations for three field studies, two in groundwater and one in surface water. In the "Groundwater - Private wells (n = 138)" study, large volume samples taken by dead-end ultrafiltration were compared to small volume grab samples. In the remaining two studies, large volume dead-end ultrafiltration and small volume samples were collected synchronously to remove the effect of spatial/temporal heterogeneity during collection. Only the 15 qPCR assays with detections and common to all studies are included. Geographic information is not included to protect the privacy of study participants.,"Recovery data.csv" contains laboratory data for large volume and small volume method recovery of three microbial targets (a bacterium, a virus, and a protozoan) at varying initial concentrations.,"Storage data.csv" contains laboratory data for microbial target decay during storage prior to processing. Liquid small volume samples and large volume ultrafilters were stored at 4 C to simulate normal sample storage and transport conditions. Concentrations of three microbial targets (a bacterium, a virus, and a protozoan) were determined for storage times from 0 to 96 hours.,Descriptive data for all microbial targets is provided in "Target data.csv". An explanation of variables (with units) for all data files can found in "Key to variables.csv".,

These data describe microbiological analyses performed on groundwater samples from domestic drinking water supply collected from 42 groundwater wells in the Central Valley of California. Samples were collected between January 2014 and April 2014 for the Groundwater Ambient Monitoring and Assessment (GAMA) program priority basin assessment of the Madera, Chowchilla, and Kings (MACK) groundwater sub-basins’ shallow aquifers. A total of 75 wells were sampled for the MACK study unit between August 2013 and April 2014. Samples for this dataset were vacuum filtered and plated on MI and mEI agars prior to incubation to promote colony growth. Colonies were tallied by their species into columns for various fecal indicator bacteria (FIBs): total coliforms (TCs), Escherichia coli (E. coli), enterococci. Non-target growths were also counted and tallied. Six additional replicate samples were collected for quality assurance. Of the 579 total FIB colonies detected, 106 were selected for polymerase chain reaction (PCR) analysis with the goal of sequencing their DNA. Selected colonies consisted of both target and non-target growths and were taken from 14 samples collected at 13 different wells. DNA sequencing was successful for 34 of the sampled colonies out of a total of 59 submitted. Results for these analyses were reported in FASTA format with the number of bases and their starting position indicated for each batch.

Surface water samples (n = 33) were collected in fall of 2023 at stream sites in Scott County Iowa, USA and were analyzed for microbial source tracking markers by quantitative polymerase chain reaction at the Laboratory for Infectious Disease and the Environment (LIDE). Microbial source tracking markers identify fecal sources of contamination by detecting microbes that are specific to certain animals. Cooperators include Partners of Scott County Watersheds, Prairie Rivers of Iowa, and U.S. Department of Agriculture-Agricultural Research Service.

Surface water samples (n = 33) were collected in fall of 2023 at stream sites in Scott County Iowa, USA and were analyzed for microbial source tracking markers by quantitative polymerase chain reaction at the Laboratory for Infectious Disease and the Environment (LIDE). Microbial source tracking markers identify fecal sources of contamination by detecting microbes that are specific to certain animals. Cooperators include Partners of Scott County Watersheds, Prairie Rivers of Iowa, and U.S. Department of Agriculture-Agricultural Research Service.

Groundwater and surface-water samples were collected and analyzed for microbial source tracking markers to identify the primary sources of fecal bacteria at a Lake Michigan beach in Northwestern Indiana.

Data were collected in August and September 2015 for analysis of bacteria communities of the Grand Calumet River and associated shorelines. Water samples were collected on three occasions corresponding to one rain-related (wet) events and two non-rain (dry) events. Water samples were collected in the Grand Calumet River, at the mouth of the river, at offshore locations around the peninsular impoundment and at shoreline locations: Jeorse Park (East Chicago, Indiana), Whihala (Whiting, Indiana), and 63rd Street (Chicago, Illinois) beaches. Samples were collected in triplicate, and water was filtered at the USGS Lake Michigan Ecological Research Station. After DNA extraction, samples were analyzed using 16S rRNA sequencing using Illumina sequencing. Taxonomic identification was assigned for communities in each sample, at multiple taxonomic levels (Kingdom, Phylum, Class, Order, Family, Genus). Water was also analyzed for E. coli bacteria and turbidity, at the USGS laboratory. Hydrological conditions corresponding to the days of sample collection were obtained from publicly available USGS information (NWIS-National Water Information System). The coordinate file includes information regarding sampling locations and their corresponding latitude and longitudes. The Data file include E. coli densities, laboratory turbidity measurements, and NWIS hydrological data. The raw metagenomic data can be accessed at the NCBI repository under the biproject accession PRJNA541325: https://www.ncbi.nlm.nih.gov/sra/PRJNA541325