1
|
D'Souza N, Porter AM, Rose JB, Dreelin E, Peters SE, Nowlin PJ, Carbonell S, Cissell K, Wang Y, Flood MT, Rachmadi AT, Xi C, Song P, Briggs S. Public health use and lessons learned from a statewide SARS-CoV-2 wastewater monitoring program (MiNET). Heliyon 2024; 10:e35790. [PMID: 39220928 PMCID: PMC11363850 DOI: 10.1016/j.heliyon.2024.e35790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 05/27/2024] [Accepted: 08/02/2024] [Indexed: 09/04/2024] Open
Abstract
The global SARS-CoV-2 monitoring effort has been extensive, resulting in many states and countries establishing wastewater-based epidemiology programs to address the spread of the virus during the pandemic. Challenges for programs include concurrently optimizing methods, training new laboratories, and implementing successful surveillance programs that can rapidly translate results for public health, and policy making. Surveillance in Michigan early in the pandemic in 2020 highlights the importance of quality-controlled data and explores correlations with wastewater and clinical case data aggregated at the state level. The lessons learned and potential measures to improve public utilization of results are discussed. The Michigan Network for Environmental Health and Technology (MiNET) established a network of laboratories that partnered with local health departments, universities, wastewater treatment plants (WWTPs) and other stakeholders to monitor SARS-CoV-2 in wastewater at 214 sites in Michigan. MiNET consisted of nineteen laboratories, twenty-nine local health departments, 6 Native American tribes, and 60 WWTPs monitoring sites representing 45 % of Michigan's population from April 6 and December 29, 2020. Three result datasets were created based on quality control criteria. Wastewater results that met all quality assurance criteria (Dataset Mp) produced strongest correlations with reported clinical cases at 16 days lag (rho = 0.866, p < 0.05). The project demonstrated the ability to successfully track SARS-CoV-2 on a large, state-wide scale, particularly data that met the outlined quality criteria and provided an early warning of increasing COVID-19 cases. MiNET is currently poised to leverage its competency to complement public health surveillance networks through environmental monitoring for new and emerging pathogens of concern and provides a valuable resource to state and federal agencies to support future responses.
Collapse
Affiliation(s)
- Nishita D'Souza
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Alexis M. Porter
- Annis Water Resources Insititute, Grand Valley State University, Muskegon, MI, USA
| | - Joan B. Rose
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Erin Dreelin
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | - Susan E. Peters
- Michigan Department of Health and Human Services, Lansing, MI, USA
| | | | - Samantha Carbonell
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | | | - Yili Wang
- University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew T. Flood
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
| | | | - Chuanwu Xi
- University of Michigan, Ann Arbor, Michigan, USA
| | - Peter Song
- University of Michigan, Ann Arbor, Michigan, USA
| | - Shannon Briggs
- Michigan Department of Environment, Great Lakes, and Energy, Lansing, MI, USA
| | - the Michigan Network for Environmental Health and Technology (MiNET) consortium
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
- Annis Water Resources Insititute, Grand Valley State University, Muskegon, MI, USA
- Michigan Department of Health and Human Services, Lansing, MI, USA
- Northern Michigan Regional Laboratory, Gaylord, MI, USA
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
- Saginaw Valley State University, Michigan, USA
- University of Michigan, Ann Arbor, Michigan, USA
- Institute of Environmental Science and Research (ESR), New Zealand
- Michigan Department of Environment, Great Lakes, and Energy, Lansing, MI, USA
| |
Collapse
|
2
|
Heijnen L, de Vries HJ, van Pelt G, Stroobach E, Atsma A, Vranken J, De Maeyer K, Vissers L, Medema G. Qualitative detection of E. coli in distributed drinking water using real-time reverse transcription PCR targeting 16S rRNA: Validation and practical experiences. WATER RESEARCH 2024; 259:121843. [PMID: 38824794 DOI: 10.1016/j.watres.2024.121843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 05/17/2024] [Accepted: 05/27/2024] [Indexed: 06/04/2024]
Abstract
Escherichia coli (E. coli) plays a central role as an indicator for fecal contamination to predict the possible presence of microbial pathogens in drinking water. Current detection methods for E. coli are based on time-consuming culture-based techniques. There is a strong need for methods to detect fecal contamination rapidly in distributed drinking water to prevent outbreaks of waterborne disease and support water utilities to efficiently manage their operations like actions to repair or maintain distribution pipes, to minimize impact on consumers. This study describes the validation and application of a qualitative real time reverse transcription PCR (RT-PCR) method targeting 16S ribosomal RNA (rRNA) for rapid detection of E. coli in distributed drinking water. The RT-PCR assay targets 16S rRNA, a highly abundant RNA in viable cells, enabling robust detection at the required sensitivity of 1 CFU/100 ml. The validation was performed by comparing the RT-PCR method with the culture-based chromogenic reference method (CCA) using the protocol and criteria described in ISO 16,140-2:2016. The validation demonstrated that this RT-PCR method can be used to specifically detect E. coli in a broad range of drinking water samples with at least the same limit of detection as the culture method (Relative Limit Of Detection = 0.75, range 0.43-1.43). The inclusivity study showed that the RT-PCR method was able to detect a broad range of E. coli strains derived from different sources and geographic areas, including pathogenic serotype O157 strains that are not detected with the culture method. The exclusivity study determined that other bacterial genera are not detected with this RT-PCR. However, Escherichia fergusonii was detected and, based on "in silico" analysis, it is expected that also E. albertii and E. marmotae and Shigella species will be detectable using this RT-PCR. An interlaboratory study confirmed that the RT-PCR and culture method have comparable sensitivities when tested by different participants at different laboratories. The application of RT-PCR to confirm the hygienic quality of distributed drinking water after actions to repair or maintain distribution pipes was compared with the culture method on 8076 routine samples, analyzed by the drinking water laboratories in the Netherlands. This comparison study showed a 96.4 % agreement between RT-PCR and culture. In 3.3 % of the samples E. coli was detected with RT-PCR and not with the culture method and in 0.1 % of the samples E. coli was only detected by culture confirming either a higher sensitivity for RT-PCR or the detection of RNA from uncultivable cells. Finally, the application of RT-PCR was highlighted during a contamination event in Belgium where we demonstrate the potency of RT-PCR as a tool to rapidly monitor the spread of microbial contamination and to monitor the effect of measures to remove the contamination This is the first fully validated rapid nucleic based method for detection of E. coli in distributed drinking water. These results demonstrate that this RT-PCR method can be used as a rapid alternative to the culture method to monitor E. coli in distributed drinking water. However, it should be emphasized that nucleic acid based detection methods rely on highly different detection principles (detection of captured nucleic acids present in a sample) than culture base methods (presence of cells cultivable on a selective medium) resulting in occasional different analysis results. Varying treatment and disinfection steps (UV, chlorine, monochloramine, Ozone) or environmental factors (decay) can influence the results and cause differences between RT-PCR and culture methods.
Collapse
Affiliation(s)
- Leo Heijnen
- KWR Water Research Institute, Nieuwegein, the Netherlands.
| | | | | | | | - Adrie Atsma
- Vitens Water Expertise Center, Leeuwarden, the Netherlands
| | | | | | - Liesbeth Vissers
- AQZ (Aqualab Zuid), Werkendam, the Netherlands; Brabant Water, 's-Hertogenbosch, the Netherlands
| | - Gertjan Medema
- KWR Water Research Institute, Nieuwegein, the Netherlands; Delft University of Technology, Delft, the Netherlands
| |
Collapse
|
3
|
Manzanas C, Morrison E, Kim YS, Alipanah M, Adedokun G, Jin S, Osborne TZ, Fan ZH. Molecular testing devices for on-site detection of E. coli in water samples. Sci Rep 2023; 13:4245. [PMID: 36918634 PMCID: PMC10013241 DOI: 10.1038/s41598-023-31208-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/08/2023] [Indexed: 03/16/2023] Open
Abstract
Escherichia coli (E. coli) cells are present in fecal materials that can be the main source for disease-causing agents in water. As a result, E. coli is recommended as a water quality indicator. We have developed an innovative platform to detect E. coli for monitoring water quality on-site by integrating paper-based sample preparation with nucleic acid isothermal amplification. The platform carries out bacterial lysis and DNA enrichment onto a paper pad through ball-based valves for fluid control, with no need of laboratory equipment, followed by loop-mediated isothermal amplification (LAMP) in a battery-operated coffee mug, and colorimetric detection. We have used the platform to detect E. coli in environmental water samples in about 1 h, with a limit of quantitation of 0.2 CFU/mL, and 3 copies per reaction. The platform was confirmed for detecting multiple E. coli strains, and for water samples of different salt concentrations. We validated the functions of the platform by analyzing recreational water samples collected near the Atlantic Ocean that contain different concentrations of salt and bacteria.
Collapse
Affiliation(s)
- Carlos Manzanas
- Interdisciplinary Microsystems Group, Department of Mechanical and Aerospace Engineering, University of Florida, P.O. Box 116250, Gainesville, FL, 32611, USA
| | - Elise Morrison
- Department of Environmental Engineering Sciences, University of Florida, P.O. Box 116580, Gainesville, FL, 32611, USA.
| | - Young S Kim
- Department of Molecular Genetics and Microbiology, University of Florida, PO Box 100266, Gainesville, FL, 32610, USA
| | - Morteza Alipanah
- Interdisciplinary Microsystems Group, Department of Mechanical and Aerospace Engineering, University of Florida, P.O. Box 116250, Gainesville, FL, 32611, USA
| | - George Adedokun
- Interdisciplinary Microsystems Group, Department of Mechanical and Aerospace Engineering, University of Florida, P.O. Box 116250, Gainesville, FL, 32611, USA
| | - Shouguang Jin
- Department of Molecular Genetics and Microbiology, University of Florida, PO Box 100266, Gainesville, FL, 32610, USA
| | - Todd Z Osborne
- Whitney Laboratory of Marine Bioscience, University of Florida, P.O. Box 116580, St. Augustine, FL, 32080, USA.
- Soil, Water, and Ecosystem Sciences Department, University of Florida, P.O. Box 110290, Gainesville, FL, 32611, USA.
| | - Z Hugh Fan
- Interdisciplinary Microsystems Group, Department of Mechanical and Aerospace Engineering, University of Florida, P.O. Box 116250, Gainesville, FL, 32611, USA.
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, P.O. Box 116131, Gainesville, FL, 32611, USA.
| |
Collapse
|
4
|
Keely SP, Brinkman NE, Wheaton EA, Jahne MA, Siefring SD, Varma M, Hill RA, Leibowitz SG, Martin RW, Garland JL, Haugland RA. Geospatial Patterns of Antimicrobial Resistance Genes in the US EPA National Rivers and Streams Assessment Survey. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:14960-14971. [PMID: 35737903 PMCID: PMC9632466 DOI: 10.1021/acs.est.2c00813] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Antimicrobial resistance (AR) is a serious global problem due to the overuse of antimicrobials in human, animal, and agriculture sectors. There is intense research to control the dissemination of AR, but little is known regarding the environmental drivers influencing its spread. Although AR genes (ARGs) are detected in many different environments, the risk associated with the spread of these genes to microbial pathogens is unknown. Recreational microbial exposure risks are likely to be greater in water bodies receiving discharge from human and animal waste in comparison to less disturbed aquatic environments. Given this scenario, research practitioners are encouraged to consider an ecological context to assess the effect of environmental ARGs on public health. Here, we use a stratified, probabilistic survey of nearly 2000 sites to determine national patterns of the anthropogenic indicator class I integron Integrase gene (intI1) and several ARGs in 1.2 million kilometers of United States (US) rivers and streams. Gene concentrations were greater in eastern than in western regions and in rivers and streams in poor condition. These first of their kind findings on the national distribution of intI1 and ARGs provide new information to aid risk assessment and implement mitigation strategies to protect public health.
Collapse
Affiliation(s)
- Scott P. Keely
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| | - Nichole E. Brinkman
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| | - Emily A. Wheaton
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| | - Michael A. Jahne
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| | - Shawn D. Siefring
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| | - Manju Varma
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| | - Ryan A. Hill
- Center
for Public Health and Environmental Assessment, US Environmental Protection Agency, Corvallis, Oregon 97333, United States
| | - Scott G. Leibowitz
- Center
for Public Health and Environmental Assessment, US Environmental Protection Agency, Corvallis, Oregon 97333, United States
| | - Roy W. Martin
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| | - Jay L. Garland
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| | - Richard A. Haugland
- Center
for Environmental Measurement and Modeling and Center for Environmental Solutions
and Emergency Response, US Environmental
Protection Agency, Cincinnati, Ohio 45268, United States
| |
Collapse
|
5
|
McNair JN, Lane MJ, Hart JJ, Porter AM, Briggs S, Southwell B, Sivy T, Szlag DC, Scull BT, Pike S, Dreelin E, Vernier C, Carter B, Sharp J, Nowlin P, Rediske RR. Validity assessment of Michigan's proposed qPCR threshold value for rapid water-quality monitoring of E. coli contamination. WATER RESEARCH 2022; 226:119235. [PMID: 36257159 DOI: 10.1016/j.watres.2022.119235] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/01/2022] [Accepted: 10/09/2022] [Indexed: 06/16/2023]
Abstract
Michigan's water-quality standards specify that E. coli concentrations at bathing beaches must not exceed 300 E. coli per 100 mL, as determined by the geometric mean of culture-based concentrations in three or more representative samples from a given beach on a given day. Culture-based analysis requires 18-24 h to complete, so results are not available on the day of sampling. This one-day delay is problematic because results cannot be used to prevent recreation at beaches that are unsafe on the sampling day, nor do they reliably indicate whether recreation should be prevented the next day, due to high between-day variability in E. coli concentrations demonstrated by previous studies. By contrast, qPCR-based E. coli concentrations can be obtained in 3-4 h, making same-day beach notification decisions possible. Michigan has proposed a qPCR threshold value (qTV) for E. coli of 1.863 log10 gene copies per reaction as a potential equivalent value to the state standard, based on statistical analysis of a set of state-wide training data from 2016 to 2018. The main purpose of the present study is to assess the validity of the proposed qTV by determining whether the implied qPCR-based beach notification decisions agree well with culture-based decisions on two sets of test data from 2016-2018 (6,564 samples) and 2019-2020 (3,205 samples), and whether performance of the proposed qTV is similar on the test and training data. The results show that performance of Michigan's proposed qTV on both sets of test data was consistently good (e.g., 95% agreement with culture-based beach notification decisions during 2019-2020) and was as good as or better than its performance on the training data set. The false-negative rate for the proposed qTV was 25-29%, meaning that beach notification decisions based on the qTV would be expected to permit recreation on the day of sampling in 25-29% of cases where the beach exceeds the state standard for FIB contamination. This false-negative rate is higher than one would hope to see but is well below the corresponding error rate for culture-based decisions, which permit recreation at beaches that exceed the state standard on the day of sampling in 100% of cases because of the one-day delay in obtaining results. The key advantage of qPCR-based analysis is that it permits a large percentage (71-75%) of unsafe beaches to be identified in time to prevent recreation on the day of sampling.
Collapse
Affiliation(s)
- James N McNair
- Robert B. Annis Water Resources Institute, 740 West Shoreline Dr., Muskegon, MI 49441, USA.
| | - Molly J Lane
- Robert B. Annis Water Resources Institute, 740 West Shoreline Dr., Muskegon, MI 49441, USA
| | - John J Hart
- Robert B. Annis Water Resources Institute, 740 West Shoreline Dr., Muskegon, MI 49441, USA
| | - Alexis M Porter
- Robert B. Annis Water Resources Institute, 740 West Shoreline Dr., Muskegon, MI 49441, USA
| | - Shannon Briggs
- Michigan Department of Environment, Great Lakes, and Energy, 525W. Allegan St., Lansing, MI 48909, USA
| | - Benjamin Southwell
- Lake Superior State University, 650W Easterday Ave., Sault Ste Marie, MI 49783, USA
| | - Tami Sivy
- Saginaw Valley State University, Department of Chemistry, 7400 Bay Road, University Center, MI 48710, USA
| | - David C Szlag
- Oakland University, Department of Chemistry, 146 Library Dr., Rochester, MI 48309, USA
| | - Brian T Scull
- Robert B. Annis Water Resources Institute, 740 West Shoreline Dr., Muskegon, MI 49441, USA
| | - Schuyler Pike
- Ferris State University, Shimadzu Core Laboratory, 820 Campus Dr., Big Rapids, MI 49307, USA
| | - Erin Dreelin
- Michigan State University, Department of Fisheries and Wildlife, 420 Wilson Rd, East Lansing, MI 48824, USA
| | - Chris Vernier
- Assurance Water Laboratory, Central Michigan District Health Department, 103N Bowery Ave, Gladwin, MI 48624, USA
| | - Bonnie Carter
- Oakland County Health Division Laboratory, 1200N. Telegraph, Pontiac, MI, 48341, USA
| | - Josh Sharp
- Biology Department, Northern Michigan University, 1401 Presque Isle Avenue, Marquette, MI 49855, USA
| | - Penny Nowlin
- Northern Michigan Regional Lab, Health Department of Northwest Michigan, 95 Livingston Blvd, Gaylord, MI 49735, USA
| | - Richard R Rediske
- Robert B. Annis Water Resources Institute, 740 West Shoreline Dr., Muskegon, MI 49441, USA
| |
Collapse
|
6
|
Sivaganesan M, Willis JR, Karim M, Babatola A, Catoe D, Boehm AB, Wilder M, Green H, Lobos A, Harwood VJ, Hertel S, Klepikow R, Howard MF, Laksanalamai P, Roundtree A, Mattioli M, Eytcheson S, Molina M, Lane M, Rediske R, Ronan A, D'Souza N, Rose JB, Shrestha A, Hoar C, Silverman AI, Faulkner W, Wickman K, Kralj JG, Servetas SL, Hunter ME, Jackson SA, Shanks OC. Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917. WATER RESEARCH 2022; 225:119162. [PMID: 36191524 PMCID: PMC9932931 DOI: 10.1016/j.watres.2022.119162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 06/16/2023]
Abstract
Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.
Collapse
Affiliation(s)
- Mano Sivaganesan
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA
| | - Jessica R Willis
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA
| | - Mohammad Karim
- Environmental Services Laboratory, City of Santa Cruz, Santa Cruz, CA, USA
| | - Akin Babatola
- Environmental Services Laboratory, City of Santa Cruz, Santa Cruz, CA, USA
| | - David Catoe
- Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA
| | - Alexandria B Boehm
- Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA
| | - Maxwell Wilder
- Department of Environmental Biology, SUNY-ESF, Syracuse, NY, USA
| | - Hyatt Green
- Department of Environmental Biology, SUNY-ESF, Syracuse, NY, USA
| | - Aldo Lobos
- Department of Integrative Biology, University of South Florida, Tampa, FL, USA
| | - Valerie J Harwood
- Department of Integrative Biology, University of South Florida, Tampa, FL, USA
| | - Stephanie Hertel
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA
| | - Regina Klepikow
- U.S. Environmental Protection Agency, Region 7 Laboratory, Kansas City, KS, USA
| | | | | | - Alexis Roundtree
- Waterborne Disease Prevention Branch, Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Mia Mattioli
- Waterborne Disease Prevention Branch, Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Stephanie Eytcheson
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA
| | - Marirosa Molina
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA
| | - Molly Lane
- Annis Water Resources Institute, Grand Valley State University, Muskegon, MI, USA
| | - Richard Rediske
- Annis Water Resources Institute, Grand Valley State University, Muskegon, MI, USA
| | - Amanda Ronan
- U.S. Environmental Protection Agency, Region 2 Laboratory, Edison, NJ, USA
| | - Nishita D'Souza
- Department of Fisheries and Wildlife, Michigan State University, E. Lansing, MI, USA
| | - Joan B Rose
- Department of Fisheries and Wildlife, Michigan State University, E. Lansing, MI, USA
| | - Abhilasha Shrestha
- Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois at Chicago, Chicago, IL, USA
| | - Catherine Hoar
- Department of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA
| | - Andrea I Silverman
- Department of Civil and Urban Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA
| | | | | | - Jason G Kralj
- National Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA
| | - Stephanie L Servetas
- National Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA
| | - Monique E Hunter
- National Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA
| | - Scott A Jackson
- National Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA
| | - Orin C Shanks
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA.
| |
Collapse
|
7
|
Cyterski M, Shanks OC, Wanjugi P, McMinn B, Korajkic A, Oshima K, Haugland R. Bacterial and viral fecal indicator predictive modeling at three Great Lakes recreational beach sites. WATER RESEARCH 2022; 223:118970. [PMID: 35985141 PMCID: PMC9724166 DOI: 10.1016/j.watres.2022.118970] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 06/15/2023]
Abstract
Coliphage are viruses that infect Escherichia coli (E. coli) and may indicate the presence of enteric viral pathogens in recreational waters. There is an increasing interest in using these viruses for water quality monitoring and forecasting; however, the ability to use statistical models to predict the concentrations of coliphage, as often done for cultured fecal indicator bacteria (FIB) such as enterococci and E. coli, has not been widely assessed. The same can be said for FIB genetic markers measured using quantitative polymerase chain reaction (qPCR) methods. Here we institute least-angle regression (LARS) modeling of previously published concentrations of cultured FIB (E. coli, enterococci) and coliphage (F+, somatic), along with newly reported genetic concentrations measured via qPCR for E. coli, enterococci, and general Bacteroidales. We develop site-specific models from measures taken at three beach sites on the Great Lakes (Grant Park, South Milwaukee, WI; Edgewater Beach, Cleveland, OH; Washington Park, Michigan City, IN) to investigate the efficacy of a statistical predictive modeling approach. Microbial indicator concentrations were measured in composite water samples collected five days per week over a beach season (∼15 weeks). Model predictive performance (cross-validated standardized root mean squared error of prediction [SRMSEP] and R2PRED) were examined for seven microbial indicators (using log10 concentrations) and water/beach parameters collected concurrently with water samples. Highest predictive performance was seen for qPCR-based enterococci and Bacteroidales models, with F+ coliphage consistently yielding poor performing models. Influential covariates varied by microbial indicator and site. Antecedent rainfall, bird abundance, wave height, and wind speed/direction were most influential across all models. Findings suggest that some fecal indicators may be more suitable for water quality forecasting than others at Great Lakes beaches.
Collapse
Affiliation(s)
- Mike Cyterski
- U.S. Environmental Protection Agency, Office of Research and Development, Athens, GA, 30605, United States.
| | - Orin C Shanks
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH 45268, United States
| | - Pauline Wanjugi
- New York State Department of Health, Center for Environmental Health, Bureau of Water Supply Protection, New York City Watershed Section, Albany, NY 12201, United States
| | - Brian McMinn
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH 45268, United States
| | - Asja Korajkic
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH 45268, United States
| | - Kevin Oshima
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH 45268, United States
| | - Rich Haugland
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH 45268, United States
| |
Collapse
|
8
|
Tang MLY, Lau SCK. Strategy to Evaluate Changes in Bacterial Community Profiles and Bacterial Pathogen Load Reduction After Sewage Disinfection. Front Microbiol 2022; 13:919207. [PMID: 35898906 PMCID: PMC9309643 DOI: 10.3389/fmicb.2022.919207] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Accepted: 06/16/2022] [Indexed: 11/19/2022] Open
Abstract
Sewage effluent discharge is a major source of pathogenic contamination to the environment. The disinfection process is critical for the elimination of pathogens in sewage. In this study, we examined the impact of chlorine disinfection on the total, viable, and culturable populations of indicator bacteria, pathogens, and bacterial communities in two contrasting types of effluents (primarily treated saline and secondarily treated freshwater). Effluents collected bimonthly over 1 year were examined using cultivation, quantitative PCR (qPCR), and 16S rRNA gene amplicon sequencing coupled with or without propidium monoazide (PMA) treatment. The results showed that each type of effluent was characterized by a specific set of representative genera before disinfection. Salinity appeared to be the major abiotic factor associated with the differences in bacterial community compositions. The pathogen analysis pipeline revealed over 20 viable clinically important pathogenic species in the effluents. Although the bacterial communities differed markedly between the two types of effluents before disinfection, the species of pathogens persisting after disinfection were similar, many of them were members of Enterobacter and Vibrio. The relative abundances of all pathogens identified in the amplicon sequences were multiplied by the 16S rRNA gene copy numbers of total bacteria detected by PMA-qPCR to estimate their concentrations. Pathogens remained viable after disinfection reached 8 log10 16S rRNA copies ml−1 effluent. Meanwhile, around 80 % of the populations of three indicator bacteria including Escherichia coli, Enterococcus, and Bacteroidales were viable after disinfection, but over 99 % of the viable E. coli and Enterococcus were in the non-culturable state. We estimated the total pathogen load by adding the concentrations of all viable pathogens and examined their correlations with indicator bacteria of different types, physiological states, and effluents. The results showed that the PMA-qPCR measurement of E. coli is a reliable proxy of bacterial pathogen loads in both types of effluents. The utility of viable indicator bacteria as a biological index to assess the overall bacteriological hazards in effluents is discussed.
Collapse
|
9
|
Owen C, Wright-Foulkes D, Alvarez P, Delgado H, Durance EC, Wells GF, Poretsky R, Shrestha A. Reduction and discharge of SARS-CoV-2 RNA in Chicago-area water reclamation plants. FEMS MICROBES 2022; 3:xtac015. [PMID: 37332512 PMCID: PMC10117756 DOI: 10.1093/femsmc/xtac015] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/14/2022] [Accepted: 05/05/2022] [Indexed: 08/24/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA is commonly excreted in the feces and urine of infected individuals and is, therefore, detected in wastewaters where infection is present in the surrounding population. Water reclamation plants (WRPs) that treat these wastewaters commonly discharge treated effluents into the surrounding environment, yet little is known about the removal or persistence of SARS-CoV-2 RNA through wastewater treatment systems and potential for eventual release into the environment. We collected 361 24-hour composite influent and effluent samples from seven WRPs in the Greater Chicago Area in Illinois. Samples were collected over a period of 21 weeks for three large WRPs (with design max flows of 1.89-2.32 billion gallons per day and serving a combined population of 4.62 million people) and 11 weeks for four smaller WRPs (with design max flows of 96.3-186 million gallons per day and serving a combined population of >0.5 million people). A total of two of the larger WRPs implemented seasonal disinfection (using UV light or chlorination/dechlorination) for 8 weeks of this sampling period. SARS-CoV-2 RNA was quantified in the influent and effluent samples by reverse-transcription quantitative PCR (RT-qPCR) of the N1 and N2 targets of the nucleocapsid (N) gene. Although SARS-CoV-2 RNA was regularly detected in influent and effluent from all WRPs, viral RNA concentrations in the effluent samples were considerably lower, with mean effluent: influent gene copy concentration ratios ranging from 1:160 to 1:2.95 between WRPs. Samples collected while disinfection was active vs. inactive did not show any significant difference in the portion of RNA persisting through the treatment process (P > .05).
Collapse
Affiliation(s)
- Christopher Owen
- Department of Biological Sciences, University of Illinois Chicago, Chicago, IL 60607, United States
| | - Dorothy Wright-Foulkes
- Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois Chicago, Chicago, IL 60610, United States
| | - Prisila Alvarez
- Department of Biological Sciences, University of Illinois Chicago, Chicago, IL 60607, United States
| | - Haidy Delgado
- Department of Biological Sciences, University of Illinois Chicago, Chicago, IL 60607, United States
| | - Eva C Durance
- Department of Biological Sciences, University of Illinois Chicago, Chicago, IL 60607, United States
| | - George F Wells
- Department of Civil and Environmental Engineering, Northwestern University, Evanston, IL 60208, United States
| | - Rachel Poretsky
- Department of Biological Sciences, University of Illinois Chicago, Chicago, IL 60607, United States
| | - Abhilasha Shrestha
- Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois Chicago, Chicago, IL 60610, United States
| |
Collapse
|
10
|
Willis JR, Sivaganesan M, Haugland RA, Kralj J, Servetas S, Hunter ME, Jackson SA, Shanks OC. Performance of NIST SRM® 2917 with 13 recreational water quality monitoring qPCR assays. WATER RESEARCH 2022; 212:118114. [PMID: 35091220 PMCID: PMC10786215 DOI: 10.1016/j.watres.2022.118114] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/17/2022] [Accepted: 01/20/2022] [Indexed: 06/14/2023]
Abstract
Fecal pollution remains a significant challenge for recreational water quality management worldwide. In response, there is a growing interest in the use of real-time quantitative PCR (qPCR) methods to achieve same-day notification of recreational water quality and associated public health risk as well as to characterize fecal pollution sources for targeted mitigation. However, successful widespread implementation of these technologies requires the development of and access to a high-quality standard control material. Here, we report a single laboratory qPCR performance assessment of the National Institute of Standards and Technology Standard Reference Material 2917 (NIST SRM® 2917), a linearized plasmid DNA construct that functions with 13 recreational water quality qPCR assays. Performance experiments indicate the generation of standard curves with amplification efficiencies ranging from 0.95 ± 0.006 to 0.99 ± 0.008 and coefficient of determination values (R2) ≥ 0.980. Regardless of qPCR assay, variability in repeated measurements at each dilution level were very low (quantification threshold standard deviations ≤ 0.657) and exhibited a heteroscedastic trend characteristic of qPCR standard curves. The influence of a yeast carrier tRNA added to the standard control material buffer was also investigated. Findings demonstrated that NIST SRM® 2917 functions with all qPCR methods and suggests that the future use of this control material by scientists and water quality managers should help reduce variability in concentration estimates and make results more consistent between laboratories.
Collapse
Affiliation(s)
- Jessica R Willis
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA
| | - Mano Sivaganesan
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA
| | - Richard A Haugland
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA
| | - Jason Kralj
- National Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA
| | - Stephanie Servetas
- National Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA
| | - Monique E Hunter
- National Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA
| | - Scott A Jackson
- National Institute of Standards and Technology, Biosystems and Biomaterials Division, Complex Microbial Systems Group, Gaithersburg, MD, USA
| | - Orin C Shanks
- U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH, USA.
| |
Collapse
|
11
|
Large-scale comparison of E. coli levels determined by culture and a qPCR method (EPA Draft Method C) in Michigan towards the implementation of rapid, multi-site beach testing. J Microbiol Methods 2021; 184:106186. [PMID: 33766609 DOI: 10.1016/j.mimet.2021.106186] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 02/28/2021] [Accepted: 03/01/2021] [Indexed: 11/20/2022]
Abstract
Fecal pollution remains a challenge for water quality managers at Great Lakes and inland recreational beaches. The fecal indicator of choice at these beaches is typically Escherichia coli (E. coli), determined by culture-based methods that require over 18 h to obtain results. Researchers at the United States Environmental Protection Agency (EPA) have developed a rapid E. coli qPCR methodology (EPA Draft Method C) that can provide same-day results for improving public health protection with demonstrated sensitivity, specificity, and data acceptance criteria. However, limited information is currently available to compare the occurrence of E. coli determined by cultivation and by EPA Draft Method C (Method C). This study provides a large-scale data collection effort to compare the occurrence of E. coli determined by these alternative methods at more than 100 Michigan recreational beach and other sites using the complete set of quantitative data pairings and selected subsets of the data and sites meeting various eligibility requirements. Simple linear regression analyses of composite (pooled) data indicated a correlation between results of the E. coli monitoring approaches for each of the multi-site datasets as evidenced by Pearson R-squared values ranging from 0.452 to 0.641. Theoretical Method C threshold values, expressed as mean log10 target gene copies per reaction, that corresponded to an established E. coli culture method water quality standard of 300 MPN or CFU /100 mL varied only from 1.817 to 1.908 for the different datasets using this model. Different modeling and derivation approaches that incorporated within and between-site variability in the estimates also gave Method C threshold values in this range but only when relatively well-correlated datasets were used to minimize the error. A hypothetical exercise to evaluate the frequency of water impairments based on theoretical qPCR thresholds corresponding to the E. coli water quality standard for culture methods suggested that the methods may provide the same beach notification outcomes over 90% of the time with Method C results differing from culture method results that indicated acceptable and unacceptable water quality at overall rates of 1.9% and 6.6%, respectively. Results from this study provide useful information about the relationships between E. coli determined by culture and qPCR methods across many diverse freshwater sites and should facilitate efforts to implement qPCR-based E. coli detection for rapid recreational water quality monitoring on a large scale in the State of Michigan.
Collapse
|
12
|
Dufour A. A short history of methods used to measure bathing beach water quality. J Microbiol Methods 2021; 181:106134. [PMID: 33421445 PMCID: PMC7870561 DOI: 10.1016/j.mimet.2021.106134] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 12/30/2020] [Accepted: 01/03/2021] [Indexed: 10/22/2022]
Abstract
The enumeration of fecal indicators of bathing beach water to determine quality have been used since the mid-20th century. In the 1930s and as late the 1970s, the Most Probable Number procedure for estimating microbial densities in water was in general use. The most probable number procedure was replaced as a method of choice by the membrane filter procedure. The membrane filter had been developed in the early 1950s but did not find widespread use until the 1970s. Another development during the 1970s was the quanti -tray method, a proprietary multi-well tray, which was introduced as an innovative form of the Most Probable Number procedure. In 2005 molecular methods were introduced as a rapid 3-hourh procedure for measuring bathing beach water quality. Several variations of this approach are currently in use or in development.
Collapse
Affiliation(s)
- Al Dufour
- U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurements and Modeling, Cincinnati, OH, United States of America.
| |
Collapse
|
13
|
Lane MJ, Rediske RR, McNair JN, Briggs S, Rhodes G, Dreelin E, Sivy T, Flood M, Scull B, Szlag D, Southwell B, Isaacs NM, Pike S. A comparison of E. coli concentration estimates quantified by the EPA and a Michigan laboratory network using EPA Draft Method C. J Microbiol Methods 2020; 179:106086. [PMID: 33058947 DOI: 10.1016/j.mimet.2020.106086] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 10/09/2020] [Accepted: 10/09/2020] [Indexed: 01/15/2023]
Abstract
We evaluated data from 10 laboratories that analyzed water samples from 82 recreational water sites across the state of Michigan between 2016 and 2018. Water sample replicates were analyzed by experienced U.S. Environmental Protection Agency (EPA) analysts and Michigan laboratories personnel, many of whom were newly trained, using EPA Draft Method C-a rapid quantitative polymerase chain reaction (qPCR) technique that provides same day Escherichia coli (E. coli) concentration results. Beach management decisions (i.e. remain open or issue an advisory or closure) based on E. coli concentration estimates obtained by Michigan labs and by the EPA were compared; the beach management decision agreed in 94% of the samples analyzed. We used the Wilcoxon one-sample signed rank test and nonparametric quantile regression to assess (1) the degree of agreement between E. coli concentrations quantified by Michigan labs versus the EPA and (2) Michigan lab E. coli measurement precision, relative to EPA results, in different years and water body types. The median quantile regression curve for Michigan labs versus EPA approximated the 1:1 line of perfect agreement more closely as years progressed. Similarly, Michigan lab E. coli estimates precision also demonstrated yearly improvements. No meaningful difference was observed in the degree of association between Michigan lab and EPA E. coli concentration estimates for inland lake and Great Lakes samples (median regression curve average slopes 0.93 and 0.95, respectively). Overall, our study shows that properly trained laboratory personnel can perform Draft Method C to a degree comparable with experienced EPA analysts. This allows health departments that oversee recreational water quality monitoring to be confident in qPCR results generated by the local laboratories responsible for analyzing the water samples.
Collapse
Affiliation(s)
- Molly J Lane
- Annis Water Resources Institute, Grand Valley State University, 1 Campus Dr., Allendale, MI 49401, USA.
| | - Richard R Rediske
- Annis Water Resources Institute, Grand Valley State University, 1 Campus Dr., Allendale, MI 49401, USA.
| | - James N McNair
- Annis Water Resources Institute, Grand Valley State University, 1 Campus Dr., Allendale, MI 49401, USA.
| | - Shannon Briggs
- Michigan Department of Environment, Great Lakes and Energy (EGLE), 525 W. Allegan St., Lansing, MI 48909, USA.
| | - Geoff Rhodes
- Michigan Department of Environment, Great Lakes and Energy (EGLE), 525 W. Allegan St., Lansing, MI 48909, USA.
| | - Erin Dreelin
- Michigan State University, Department of Fisheries and Wildlife, Natural Resource Building, 420 Wilson Rd, Room 13, East Lansing, MI 48824, USA.
| | - Tami Sivy
- Saginaw Valley State University, Department of Chemistry, 7400 Bay Road, University Center, MI 48710, USA.
| | - Matthew Flood
- Michigan State University, Department of Fisheries and Wildlife, Natural Resource Building, 420 Wilson Rd, Room 13, East Lansing, MI 48824, USA.
| | - Brian Scull
- Annis Water Resources Institute, Grand Valley State University, 1 Campus Dr., Allendale, MI 49401, USA.
| | - David Szlag
- Oakland University, Department of Chemistry, 146 Library Dr., Rochester, MI 48309, USA.
| | - Benjamin Southwell
- Lake Superior State University, 650 W Easterday Ave., Sault Ste Marie, MI 49783, USA.
| | - Natasha M Isaacs
- U.S. Geological Survey (USGS), Upper Midwest Water Science Center, 5840 Enterprise Dr., Lansing, MI 48911, USA.
| | - Schuyler Pike
- Ferris State University, Shimadzu Core Laboratory for Academic and Research Excellence, 820 Campus Dr., Big Rapids, MI 49307, USA.
| |
Collapse
|
14
|
Niestępski S, Harnisz M, Korzeniewska E, Osińska A. Markers Specific to Bacteroides fragilis Group Bacteria as Indicators of Anthropogenic Pollution of Surface Waters. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17197137. [PMID: 33003501 PMCID: PMC7579016 DOI: 10.3390/ijerph17197137] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Revised: 09/24/2020] [Accepted: 09/27/2020] [Indexed: 12/29/2022]
Abstract
The aim of this study was to evaluate the applicability of markers specific to Bacteroides fragilis group (BFG) bacteria as indicators of anthropogenic pollution of surface waters. In addition, the impact of wastewater treatment plants (WWTPs) on the spread of genes specific to fecal indicator bacteria and genes encoding antimicrobial resistance in water bodies was also determined. Samples of hospital wastewater (HWW), untreated wastewater (UWW), and treated wastewater (TWW) evacuated from a WWTP were collected, and samples of river water were taken upstream (URW) and downstream (DRW) from the wastewater discharge point to determine, by qPCR, the presence of genes specific to BFG, Escherichia coli and Enterococcus faecalis, and the abundance of 11 antibiotic resistance genes (ARGs) and two integrase genes. The total number of bacterial cells (TCN) in the examined samples was determined by fluorescence in situ hybridization (FISH). Genes specific to BFG predominated among the analyzed indicator microorganisms in HWW, and their copy numbers were similar to those of genes specific to E. coli and E. faecalis in the remaining samples. The abundance of genes specific to BFG was highly correlated with the abundance of genes characteristic of E. coli and E. faecalis, all analyzed ARGs and intI genes. The results of this study indicate that genes specific to BFG can be used in analyses of human fecal pollution, and as indicators of environmental contamination with ARGs. A significant increase in the copy numbers of genes specific to BFG, E. coli, and seven out of the 11 analyzed ARGs was noted in samples of river water collected downstream from the wastewater discharge point, which suggests that WWTPs are an important source of these genes in riparian environments.
Collapse
|
15
|
Holcomb DA, Stewart JR. Microbial Indicators of Fecal Pollution: Recent Progress and Challenges in Assessing Water Quality. Curr Environ Health Rep 2020; 7:311-324. [PMID: 32542574 PMCID: PMC7458903 DOI: 10.1007/s40572-020-00278-1] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE OF REVIEW Fecal contamination of water is a major public health concern. This review summarizes recent developments and advancements in water quality indicators of fecal contamination. RECENT FINDINGS This review highlights a number of trends. First, fecal indicators continue to be a valuable tool to assess water quality and have expanded to include indicators able to detect sources of fecal contamination in water. Second, molecular methods, particularly PCR-based methods, have advanced considerably in their selected targets and rigor, but have added complexity that may prohibit adoption for routine monitoring activities at this time. Third, risk modeling is beginning to better connect indicators and human health risks, with the accuracy of assessments currently tied to the timing and conditions where risk is measured. Research has advanced although challenges remain for the effective use of both traditional and alternative fecal indicators for risk characterization, source attribution and apportionment, and impact evaluation.
Collapse
Affiliation(s)
- David A Holcomb
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr., Chapel Hill, NC, 27599-7435, USA
| | - Jill R Stewart
- Department of Environmental Sciences and Engineering, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, 135 Dauer Dr., Chapel Hill, NC, 27599-7431, USA.
| |
Collapse
|
16
|
Lane MJ, McNair JN, Rediske RR, Briggs S, Sivaganesan M, Haugland R. Simplified Analysis of Measurement Data from A Rapid E. coli qPCR Method (EPA Draft Method C) Using A Standardized Excel Workbook. WATER 2020; 12:1-775. [PMID: 32461809 PMCID: PMC7252523 DOI: 10.3390/w12030775] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Draft method C is a standardized method for quantifying E. coli densities in recreational waters using quantitative polymerase chain reaction (qPCR). The method includes a Microsoft Excel workbook that automatically screens for poor-quality data using a set of previously proposed acceptance criteria, generates weighted linear regression (WLR) composite standard curves, and calculates E. coli target gene copies in test samples. We compared standard curve parameter values and test sample results calculated with the WLR model to those from a Bayesian master standard curve (MSC) model using data from a previous multi-lab study. The two models' mean intercept and slope estimates from twenty labs' standard curves were within each other's 95% credible or confidence intervals for all labs. E. coli gene copy estimates of six water samples analyzed by eight labs were highly overlapping among labs when quantified with the WLR and MSC models. Finally, we compared multiple labs' 2016-2018 composite curves, comprised of data from individual curves where acceptance criteria were not used, to their corresponding composite curves with passing acceptance criteria. Composite curves developed from passing individual curves had intercept and slope 95% confidence intervals that were often narrower than without screening and an analysis of covariance test was passed more often. The Excel workbook WLR calculation and acceptance criteria will help laboratories implement draft method C for recreational water analysis in an efficient, cost-effective, and reliable manner.
Collapse
Affiliation(s)
- Molly J. Lane
- Annis Water Resources Institute, Grand Valley State University, Muskegon, MI 49401, USA
| | - James N. McNair
- Annis Water Resources Institute, Grand Valley State University, Muskegon, MI 49401, USA
| | - Richard R. Rediske
- Annis Water Resources Institute, Grand Valley State University, Muskegon, MI 49401, USA
- Correspondence:
| | - Shannon Briggs
- Michigan Department of Environment, Great Lakes, and Energy (EGLE), 525 W. Allegan St., Lansing, MI 48909, USA
| | - Mano Sivaganesan
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. EPA, Cincinnati, OH 45268, USA
| | - Richard Haugland
- Center for Environmental Measurement and Modeling, Office of Research and Development, U.S. EPA, Cincinnati, OH 45268, USA
| |
Collapse
|
17
|
Li X, Chase JA, Bond RF, Lor P, Fernandez K, Nguyen TH, Partyka ML, Thiptara A, Atwill ER. Microbiological safety of popular recreation swimming sites in Central California. ENVIRONMENTAL MONITORING AND ASSESSMENT 2019; 191:456. [PMID: 31230187 DOI: 10.1007/s10661-019-7601-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Accepted: 06/12/2019] [Indexed: 06/09/2023]
Abstract
The objective of the study was to assess the microbiological safety of popular recreational swimming sites in Central California. Water samples were collected from eleven monitoring sites across the lower reaches of two watersheds for two consecutive swimming seasons (2012-2013), and levels of indicator and pathogenic microorganisms were determined. Data on ambient weather and water chemistry were collected for analyzing their associations with microorganisms in water. All water samples were positive for indicator E. coli with mean concentrations per site ranging from 3.07 to 216.11 MPN/100 ml in 2012 and 13.4 to 226.97 MPN/100 ml in 2013. Mean E. coli concentrations in 27% and 36% samplings sites exceeded the EPA 2012 Recreational Water Quality Criteria recommended mean concentration of ≤ 126 CFU/100 ml of E. coli, in 2012 and 2013, respectively. Cryptosporidium spp. oocysts were detected in all water samples from all sampling sites, with an overall prevalence of 50% and mean concentrations of 0.08 oocysts/l in 2012 and 0.19 oocysts/l in 2013. Giardia spp. cysts were detected at eight sites, with an overall prevalence of 28.8% and mean concentration of 0.2 cysts/l in both years. The majority of the detected Cryptosporidium spp. oocysts and Giardia spp. cysts appeared damaged under microscopy. E. coli O157:H7 was detected in 9% of water samples, with positive samples limited to three sites. Salmonella spp. were detected in all but one site across the two years, with mean concentrations of 0.94 MPN/l in 2012 and 1.85 MPN/l in 2013. Cryptosporidium spp. oocyst concentrations were negatively associated with 30-day mean wind speed and cumulative precipitation and dissolved oxygen in water. Giardia spp. cyst concentrations were positively associated with turbidity and pH of water and negatively associated with E. coli concentrations and 24-h mean air temperature. Salmonella spp. concentrations were positively associated with 30-day mean air temperature. The occurrence of E. coli O157:H7 was positively associated with previous 30-day cumulative precipitation.
Collapse
Affiliation(s)
- Xunde Li
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, 4207 Vet Med 3B, Davis, CA, 95616, USA
- Western Institute for Food Safety and Security, University of California, Davis, Davis, CA, 95616, USA
| | - Jennifer A Chase
- Western Institute for Food Safety and Security, University of California, Davis, Davis, CA, 95616, USA
| | - Ronald F Bond
- Western Institute for Food Safety and Security, University of California, Davis, Davis, CA, 95616, USA
| | - Panachon Lor
- Western Institute for Food Safety and Security, University of California, Davis, Davis, CA, 95616, USA
| | - Kristine Fernandez
- Western Institute for Food Safety and Security, University of California, Davis, Davis, CA, 95616, USA
| | - Trân H Nguyen
- Western Institute for Food Safety and Security, University of California, Davis, Davis, CA, 95616, USA
| | - Melissa L Partyka
- School of Fisheries, Aquaculture and Aquatic Sciences, Auburn University, Auburn, AL, 36849, USA
| | - Anyarat Thiptara
- Western Institute for Food Safety and Security, University of California, Davis, Davis, CA, 95616, USA
| | - Edward R Atwill
- Department of Population Health and Reproduction, School of Veterinary Medicine, University of California-Davis, 4207 Vet Med 3B, Davis, CA, 95616, USA.
- Western Institute for Food Safety and Security, University of California, Davis, Davis, CA, 95616, USA.
| |
Collapse
|
18
|
Aw TG, Sivaganesan M, Briggs S, Dreelin E, Aslan A, Dorevitch S, Shrestha A, Isaacs N, Kinzelman J, Kleinheinz G, Noble R, Rediske R, Scull B, Rosenberg S, Weberman B, Sivy T, Southwell B, Siefring S, Oshima K, Haugland R. Evaluation of multiple laboratory performance and variability in analysis of recreational freshwaters by a rapid Escherichia coli qPCR method (Draft Method C). WATER RESEARCH 2019; 156:465-474. [PMID: 30953844 PMCID: PMC9994418 DOI: 10.1016/j.watres.2019.03.014] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2018] [Revised: 03/05/2019] [Accepted: 03/12/2019] [Indexed: 06/01/2023]
Abstract
There is interest in the application of rapid quantitative polymerase chain reaction (qPCR) methods for recreational freshwater quality monitoring of the fecal indicator bacteria Escherichia coli (E. coli). In this study we determined the performance of 21 laboratories in meeting proposed, standardized data quality acceptance (QA) criteria and the variability of target gene copy estimates from these laboratories in analyses of 18 shared surface water samples by a draft qPCR method developed by the U.S. Environmental Protection Agency (EPA) for E. coli. The participating laboratories ranged from academic and government laboratories with more extensive qPCR experience to "new" water quality and public health laboratories with relatively little previous experience in most cases. Failures to meet QA criteria for the method were observed in 24% of the total 376 test sample analyses. Of these failures, 39% came from two of the "new" laboratories. Likely factors contributing to QA failures included deviations in recommended procedures for the storage and preparation of reference and control materials. A master standard curve calibration model was also found to give lower overall variability in log10 target gene copy estimates than the delta-delta Ct (ΔΔCt) calibration model used in previous EPA qPCR methods. However, differences between the mean estimates from the two models were not significant and variability between laboratories was the greatest contributor to overall method variability in either case. Study findings demonstrate the technical feasibility of multiple laboratories implementing this or other qPCR water quality monitoring methods with similar data quality acceptance criteria but suggest that additional practice and/or assistance may be valuable, even for some more generally experienced qPCR laboratories. Special attention should be placed on providing and following explicit guidance on the preparation, storage and handling of reference and control materials.
Collapse
Affiliation(s)
- Tiong Gim Aw
- Department of Global Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 2100, New Orleans, LA, 70112, USA
| | - Mano Sivaganesan
- U.S. Environmental Protection Agency, National Risk Management Research Laboratory, 26 W. M.L. King Dr, Cincinnati, OH, 45268, USA
| | - Shannon Briggs
- Water Resources Division, Michigan Department of Environmental Quality, P. O. Box 30458, 525 West Allegan Street, Lansing, MI, 48909, USA
| | - Erin Dreelin
- Center for Water Sciences, Michigan State University, 1405 South Harrison Road, East Lansing, MI, 48823, USA
| | - Asli Aslan
- Georgia Southern University, Department of Environmental Health Sciences, 501 Forest Drive, Statesboro, GA, 30458, USA
| | - Samuel Dorevitch
- University of Illinois at Chicago, School of Public Health, 2121 W. Taylor Street, Chicago, IL, 60612, USA
| | - Abhilasha Shrestha
- University of Illinois at Chicago, School of Public Health, 2121 W. Taylor Street, Chicago, IL, 60612, USA
| | - Natasha Isaacs
- U.S. Geological Survey, Upper Midwest Water Science Center, 6520 Mercantile Way, Ste 5, Lansing, MI, 48911, USA
| | - Julie Kinzelman
- City of Racine Public Health Department, 730 Washington Ave, Racine, WI, 53403, USA
| | - Greg Kleinheinz
- University of Wisconsin-Oshkosh, Environmental Research Laboratory, 800 Algoma Boulevard, Oshkosh, WI, 54901, USA
| | - Rachel Noble
- Institute of Marine Sciences, University of North Carolina at Chapel Hill, 3431 Arendell Street, Morehead City, NC, 28557, USA
| | - Rick Rediske
- Annis Water Resources Institute, Lake Michigan Center, 740 W. Shoreline Dr, Muskegon, MI, 49441, USA
| | - Brian Scull
- Annis Water Resources Institute, Lake Michigan Center, 740 W. Shoreline Dr, Muskegon, MI, 49441, USA
| | - Susan Rosenberg
- Oakland County Health Division Laboratory, 1200 N. Telegraph, Pontiac, MI, 48341, USA
| | - Barbara Weberman
- Oakland County Health Division Laboratory, 1200 N. Telegraph, Pontiac, MI, 48341, USA
| | - Tami Sivy
- Saginaw Valley State University, Department of Chemistry, 7400 Bay Road, University Center, MI, 48710, USA
| | - Ben Southwell
- Lake Superior State University, Environmental Analysis Laboratory, 650 W. Easterday Ave, Sault Ste Marie, MI, 49783, USA
| | - Shawn Siefring
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 26 W. M.L. King Dr, Cincinnati, OH, 45268, USA
| | - Kevin Oshima
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 26 W. M.L. King Dr, Cincinnati, OH, 45268, USA
| | - Richard Haugland
- U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, 26 W. M.L. King Dr, Cincinnati, OH, 45268, USA.
| |
Collapse
|