Progress 09/15/06 to 09/14/08
Outputs
OUTPUTS: Testing was extended to an adjacent state,Ohio,and a distant state, Iowa, applying proficiency testing to determine how this EC-BST method performed in various HOME,FOREIGN,and all combinations of West Virginia, Ohio, and Iowa databases.The major purpose of extending our testing to other states was to determine if FOREIGN databases could be used in lieu of HOME databases as this would extend this technology to communities without databases at a considerable cost-savings.Our goal was exceeded by collecting 1364 samples from Ohio and Iowa and generating 4580 E. coli DNA fingerprints for database inclusion.Based on random proficiency testing, both HOME and FOREIGN databases were shown to have >80% matching efficiency and >80% accuracy rates for a 2-way analysis,human versus nonhuman classification demonstrating that FOREIGN West Virginia databases can be used in remote regions for source-tracking at these rates.In a 3-way analysis,human versus wildlife versus domestic animal classification,the matching efficiency and accurate rates of Ohio and Iowa proficiency samples were improved when HOME isolates were included in the test database.One major obstacle we overcame this year was to develop a computer program to manage and perform the vast number of computations associated with the increased number of databases required to evaluate and the significant increase in database isolates.One such development is a real-time, PCR procedure that is allowing us direct quantification of E. coli from source waters thus avoiding traditional culture-based testing that is currently in use.Our master database now contains a total of 12,791 E. coli DNA fingerprints all of which are cataloged by host source. Two databases and proficiency sets were generated from remote regions, Ross County(Ohio)and the Backbone watershed(Iowa).The goal was to collect at least 60 database and 5 proficiency samples from seven different species for a projected total of 455 samples and 2275 isolates per database.Each regional database included human, cow, pig, deer, goose, and raccoon.The seventh species was chicken and sheep for Ohio and Iowa,respectively. Collection goals were met in each category; however, not all samples yielded E. coli requiring additional collections, particularly for human.A total of 714 and 650 samples were collected from Ohio and Iowa.Rate for samples yielding E. coli ranged from 42%(human)-97%(cow)with an average of 70% yield. The term home(H)database was used to denote the region of origin of the proficiency samples and isolates. Upon completion of the N and M databases,independently collected blind proficiency samples, and their respective isolates, were utilized to challenge the database(s) with respect to average rate of correct classification(ARCC),average rate of matching efficiency (ARME),and indeterminant classification for 2-way, 3-way(human vs wildlife vs domesticated animal),and 7-way species specific analysis.Proficiency samples from all database regions were utilized to determine if home-region-derived (home) proficiency isolates performed best in home versus out-of-region-derived(foreign)databases and all combinations of databases. PARTICIPANTS: Marshall University School of Medicine, Forensic Science: Pamela Staton, Terry Fenger, Conan Goolsby, Amanda Mittermeier, Tara O'Brien, Jeremy Tanner,David Bailey, Alexis Them, Kenneth Jones, Jennifer Ross Marshall University School of Medicine, Biomedical Sciences: Hongwei Yu Backbone Watershed, Iowa Department of Natural Resources, Water Monitoring Section: Eric O'Brien, Michelle Kilgore Ross County Health District, Chillicothe, OH: Tim Angel, Lana Cherrington West Virginia Department of Agriculture: Kriston Strickler, Joshua Hardy, Wildlife Removal Services, Inc. Kenna, WV: Noel Braley TARGET AUDIENCES: Escherichia coli is a bacterial species known to reside normally in the intestinal tract of warm-blooded animals, including humans. Upon defecation, the bacterium is eliminated as a component of fecal matter. This waste product may find its way into the environment in a variety of ways primarily through overflow from public sewage facilities and leaky commercial septic systems designed to contain human waste, in addition to land surface run-off from domestic animals and wildlife. As EPA standards for fecal pollution are exceeded, E. coli serves as an indicator that disease-causing pathogens may also be present in sufficient quantity to be a public health concern. Feces-contaminated waters are a particular concern when serving as a source of drinking water. As the source of fecal pollution is not always obvious, bacterial source tracking methods are needed to identify the probable source of fecal pollution to guide timely and efficient remediation efforts. Our studies demonstrate that E. coli NotI pulsed field gel electrophoresis generated databases can efficiently match and accurately identify isolates from randomly collected samples in 2-way analysis. Interestingly, select foreign databases performed at the same or higher rate than home databases alone. Therefore, it may be possible for regions to utilize preexisting databases to forego costly and time-consuming creation of databases prior to water testing. In every instance, combination databases outperformed home databases in 2-way and 3-way analysis. An ideal database-dependent Bacterial Source Tracking method is one that demonstrates both matching efficiency and accuracy in host classification. As an isolate should not be classified unless a suitable match is found in the database, matching efficiency is an essential prelude to source identification. While a high degree of accuracy in source assignment is highly desirable for such methods, so also is matching efficiency for a database-dependent method. A database-dependent method that cannot match a high percentage of random isolates would be an ineffective, and potentially biased, method for water testing. As a gold standard reference method is currently not available, it becomes necessary to enter into carefully designed studies that assess the robustness of the system under analysis. In this study, we used proficiency test sets to assess both the average rate of matching efficiency and average rate of correct classification based on randomly collected E coli isolates simulating what might be found in environmental water samples. In this way, we applied proficiency sets to answer important and practical questions including which databases matched and accurately classified the most randomly selected isolates, which foreign databases could serve beyond the region of their origin, and whether home isolates are required in every case. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
The home database performed more robustly than WV foreign, single databases.A rating score of 8.7 is interpreted as approximately 9 of 10 isolates from a water sample could be predicted to be correct for a 2-way analysis.All combinations of foreign-composite databases ranked from 7.2-8.3, 7.2-8.2,and 7.5-8.2 in 2X, 3X, and 4X combinations, respectively.Results from all combinations of home-foreign composites ranged from 8.3-8.7,8.2-8.5, and 8.0-8.3 in 2X,3X,and 4X combinations, respectively.Two additional databases, the New River and the Mid-Ohio watershed in West Virginiawere added to a composite database.The composite BST PFGE database now includes representative samples and isolates from 5 WV databases,Potomac River,Berkeley County,New River,Lower-Ohio and Mid-Ohio watersheds of West Virginia.Development of two out-of-state databases is under construction,one in an adjacent state,Ross County,Ohio,and another in a remote state,Backbone watershed,Iowa.All databases are being maintained as a regional,or home,database with its associated proficiency samples as well as being added to all combinations of databases.In this way, we are able to evaluate the matching efficiency and accurate classification of blind proficiency samples in their home as well as in combinatorial, or composite, databases.Depending on the region analyzed,results indicate that combinatorial databases rival home databases in the average rate of correct classification of proficiency isolates. These are promising findings as the requirement for development of regional databases in all regions seeking to perform this procedure would be cost prohibitive for most. With this in mind, it is essential to determine if foreign composite databases are reliable for use in regions where no home database exists. Progress continues to be made toward standardization and validation of the NotI pulsed-field gel electrophoresis bacterial source tracking method for animal/human source determination of freshwater fecal pollution. The New River (N) contributes significantly to the West Virginia tourism industry as a well-known destination for white-water rafting in addition to its other recreational and scenic offerings.Our previous work prompted the evaluation of this BST method in two additional regions, the New River(N)and the Mid-Ohio(M)watershed in West Virginia. A total of 265 scat samples were analyzed in the NR region from 7 species (human, poultry, bovine, swine, Canadian goose, deer, and raccoon.Each scat sample was cultured for Escherichia coli and PFGE performed following NotI restriction. For the M database, 382 samples were collected, cultured, and PFGE performed.The N and M databases now contain 1091 and 1764 species-specific E. coli NotI PFGE profiles, respectively. Our findings demonstrate the advantage of including foreign isolates to home databases to improve the performance of this BST method and demonstrate combined database utility for use in regions where no database exists.This is an important finding toward limiting the costs to the user.
Publications
- Goolsby, C.L., A.L. Mittermeier, T. O'Brien, J.R. Tanner, P.J. Staton. (2006) Q-248 NotI PFGE Bacterial Source Tracking: Three Region Proficiency Testing in West Virginia. American Society for Microbiology
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Progress 09/15/06 to 09/14/07
Outputs
OUTPUTS: During this period, progress was made on addition of human isolates to the overall database. The purpose for this was to bring the number of human isolates into line with the number of wildlife and domesticated animal isolates overall. To accomplish this, 177 human fecal samples were collected in our region, cultured and confirmed as E. coli yielding 885 E. coli isolates. Of these, 86% (n=759) produced high-quality NotI pulsed-field gel electrophoresis genetic profiles which were added to the known-source database. Another source of human isolates was provided by Michigan State University consisting of 990 Shiga-toxin E. coli isolates from human sources which were tested in a similar manner and added as known (human) - source isolates. To date, 744 isolates from this pathogenic subset of isolates have been processed up through PFGE with 487 genetic profiles resulting for addition to the database. Collectively, 1246 human-source E. coli isolates were added to the database for
this period. The overall database contains 14,363 known-source E. coli isolates that are currently being used to test blind proficiency and water isolates for source determination. Through a collaborative effort with the Lincoln County (WV) West Virginia University EPA Extension Agency, known-source domesticated and wildlife fecal samples and E. coli isolates from cow, goose, chicken, pig, raccoon, and goose were also added to the database. Water samples (n=15) collected by the Lincoln County working group were received on spent testing filters submitted to our laboratory. From these spent filters, E. coli was isolated and identified. DNA from each isolate was genetically "fingerprinted" using the standard NotI PFGE procedure of our laboratory. These resulting fingerprints (n=150) were compared to an existing know-source isolate database. Both 3-way (human vs wildlife vs domesticated animal) and 2-way (human vs nonhuman) analysis was performed on each isolate with the results provided
to the requesting party. The purpose of this analysis was to determine if a human signal could be identified in water samples tested to lend guidance to this water restoration project. A second E. coli RT-PCR TaqMan probe was designed for comparison to a fret probe to determine which has the greatest specificity and sensitivity with raw water samples.
PARTICIPANTS: Ric MacDowell Lincoln County Commission, West Virginia Left Fork of the Mud River Decentralized Wastewater Demonstration Project Assistance ID # X-83212101-1 We substituted Left Fork of the Mud River for the Coal River which was originally stated in the grant.
TARGET AUDIENCES: Private citizens Insurance agencies Cities States Industry reliant on clean water Businesses Realtors
PROJECT MODIFICATIONS: We filed for a 12 month extension.
Impacts
Escherichia coli (E.coli) is a normal intestinal inhabitant and a well-recognized microbial indicator of fecal contamination in water. Feces finds its way into waterways through a variety of means primarily through waste water overflow, release from municipal sewage systems or leaky septic tanks, as well as through land surface run-off from domestic animals and wildlife. When feces is released into the environment, disease-causing pathogens may also be present. This is of particular concern when such waters are used for drinking, swimming, as well as habitats for aquaculture or irrigation for crops ultimately destined for human consumption. While elevated E. coli counts may be useful in cautioning users that fecal pathogens may be present, such counts do not provide sufficient information regarding the source of such contamination so that effective remediate actions may be taken. Bacterial Source Tracking (BST) is a scientific approach under development that seeks to
identify the host-source of fecal pollution and contamination. NotI pulsed-field gel electrophoresis (PFGE) is a database-dependent, BST method whereby E. coli DNA fingerprinting is used to develop known-host-source databases for tracking unknown-host-source E. coli. To evaluate and validate this BST method, we use proficiency testing to determine which of our 127 single and combinatorial in-house databases perform best for any particular region. To best contain costs for future users, we also seek to determine the extent to which this method, and its associated databases, may be used in regions that currently have no regional NotI PFGE database. This past year studies conducted in West Virginia, Ohio, and Iowa were reported. RESULTS: Our results suggest that 1) in some cases, out-of-region or "foreign" databases may be a cost- and time-effective alternative to building large (more than 2000 isolates) home databases, 2) access to regionally diverse databases may be useful in
customizing a database for a region, 3) combining databases to include isolates from other regions improves matching efficiency and accuracy of classification beyond those results obtained when using the home database alone. As each of our single and combination databases is uniquely different in size and composition, only through use of proficiency testing is it possible to predict which database(s) would best serve a particular region.
Publications
- No publications reported this period
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