Data from: Groundwater surveillance of endemic swine pathogens on forty Iowa swine farms via dead-end ultrafiltration

Authors: DOUGHAN, GABRIELLE - Iowa State University; WALTHART, BECCA - Iowa State University; MONCRIEF, MICHELE - Iowa State University; SKOLAND, KIRSTIN - Iowa State University; FIRNSTAHL, AARON - Us Geological Survey; Opelt, Sarah; Cook, Rachel; GAUGER, PHILLIP - Iowa State University; BROWN, JUSTIN - Iowa State University; BONNEMA, J.L. - Iowa State University; BORCHARDT, MARK - US Department Of Agriculture (USDA); Heffron, Joseph; STOKDYK, JOEL - Us Geological Survey; Burch, Tucker

Submitted to: Ag Data Commons
Publication Type: Database / Dataset
Publication Acceptance Date: 5/27/2025
Publication Date: 5/27/2025
Citation: Doughan, G.E., Walthart, B.K., Moncrief, M.I., Skoland, K.J., Firnstahl, A.D., Opelt, S.A., Cook, R.M., Gauger, P.C., Brown, J.T., Bonnema, J., Borchardt, M.A., Heffron, J.A., Stokdyk, J.P., Burch, T.R. 2025. Dataset from: quantitative polymerase chain reaction measurements of endemic swine microbes in groundwater from 40 Iowa swine farms. Ag Data Commons. https://doi.org/10.15482/USDA.ADC/28665137.v1.
DOI: https://doi.org/10.15482/USDA.ADC/28665137.v1

Interpretive Summary: Infectious organisms like porcine reproductive and respiratory syndrome virus (PRRSV) cause expensive diseases for the U.S. swine herd every year. However, it is difficult to understand how many of these organisms gain entry to farms given strict biosecurity practices in the U.S. swine industry. Groundwater used as drinking water for swine is one possible route that has not yet been investigated. ARS researchers in Marshfield, Wisconsin worked with collaborators from Iowa State University and the U.S. Geological Survey to assess groundwater wells on 40 Iowa swine farms for contamination by genetic markers for endemic swine pathogens and bacteria found in swine manure. Ten of 40 samples (25%) were positive for one or more markers. Detections included markers for swine manure bacteria, porcine circovirus type 2, and Cryptosporidium. Results demonstrate that groundwater can be a biosecurity risk for swine farms and indicate a need for further evaluation of waterborne pathogen transmission on swine farms.

Technical Abstract: Groundwater samples were collected in an observational study design by dead-end ultrafiltration from private wells on 40 Iowa swine farms and analyzed by quantitative polymerase chain reaction (qPCR) to assess contamination by endemic swine pathogens and swine manure markers. These data facilitate investigation of groundwater as a biosecurity risk on swine farms. Each farm was sampled one time. Twenty farms were sampled in spring of 2024 (4/15/2024 – 5/29/2024) and twenty farms were sampled in fall of 2024 (9/16/2024 – 10/29/2024). Sample volumes were 639–853 L (mean = 759). Control samples were collected in the field for each field sample, and control samples were tested for all organisms if the corresponding field sample tested positive for any organism. Samples were shipped on ice to the laboratory where they were backflushed, underwent secondary concentration, and archived at -80 degrees Celsius. Secondary concentrates were subsampled for nucleic acid extraction using the QIAGEN QIAcube Connect system, and each nucleic acid extract was analyzed in duplicate by qPCR using a Roche LightCycler 480 II for the following microorganisms: Cryptosporidium spp., enteropathogenic Escherichia coli, porcine circovirus type 2, porcine epidemic diarrhea virus, porcine reproductive and respiratory syndrome virus, rotavirus group C, Salmonella spp., swine Bacteroidales (2 qPCR assays), and swine influenza virus. Negative and positive controls were included at lab steps for concentration, nucleic acid extraction, reverse transcription, and qPCR. PCR inhibition was assessed in each nucleic acid extract and mitigated by dilution if necessary. Data are expressed as genomic copies per liter of groundwater sampled unless otherwise indicated. Dataset consists of 1 spreadsheet file: Dataset 01102025_V4.csv. Variables in this file are described in the included data dictionary.