scholarly journals Methods To Increase Fidelity of Repetitive Extragenic Palindromic PCR Fingerprint-Based Bacterial Source Tracking Efforts

2005 ◽  
Vol 71 (1) ◽  
pp. 512-518 ◽  
Author(s):  
Wail M. Hassan ◽  
Shiao Y. Wang ◽  
Rudolph D. Ellender
Keyword(s):  
Quality Factor ◽  
Source Tracking ◽  
Blind Test ◽  
E Coli ◽  
Bacterial Source Tracking ◽  
Correct Assignment ◽  
Average Similarity ◽  
Maximum Similarity ◽  
Repetitive Extragenic Palindromic Pcr ◽  
Repetitive Extragenic Palindromic

ABSTRACT The goal of the study was to determine which similarity coefficient and statistical method to use to produce the highest rate of correct assignment (RCA) in repetitive extragenic palindromic PCR-based bacterial source tracking. In addition, the use of standards for deciding whether to accept or reject source assignments was investigated. The use of curve-based coefficients Cosine Coefficient and Pearson's Product Moment Correlation yielded higher RCAs than the use of band-based coefficients Jaccard, Dice, Jeffrey's x, and Ochiai. When enterococcal and Escherichia coli isolates from known sources were used in a blind test, the use of maximum similarity produced consistently higher RCAs than the use of average similarity. We also found that the use of a similarity value threshold and/or a quality factor threshold (the ratio of the average fingerprint similarity within a source to the average similarity of this source's isolates to an unknown) to decide whether to accept source assignments of unknowns increases the reliability of source assignments. Applying a similarity value threshold improved the overall RCA (ORCA) by 15 to 27% when enterococcal fingerprints were used and 8 to 29% when E. coli fingerprints were used. Applying the quality factor threshold resulted in a 22 to 32% improvement in the ORCA, depending on the fingerprinting technique used. This increase in reliability was, however, achieved at the expense of decreased numbers of isolates that were assigned a source.

scholarly journals Identifying Host Sources of Fecal Pollution: Diversity of Escherichia coli in Confined Dairy and Swine Production Systems

2005 ◽  
Vol 71 (10) ◽  
pp. 5992-5998 ◽  
Author(s):  
Zexun Lu ◽  
David Lapen ◽  
Andrew Scott ◽  
Angela Dang ◽  
Edward Topp
Keyword(s):  
Escherichia Coli ◽  
Dairy Farm ◽  
Sampling Strategy ◽  
Farming Systems ◽  
Microbial Source Tracking ◽  
Fecal Pollution ◽  
Source Tracking ◽  
E Coli ◽  
Repetitive Extragenic Palindromic Pcr ◽  
Repetitive Extragenic Palindromic

ABSTRACT Repetitive extragenic palindromic PCR fingerprinting of Escherichia coli is one microbial source tracking approach for identifying the host source origin of fecal pollution in aquatic systems. The construction of robust known-source libraries is expensive and requires an informed sampling strategy. In many types of farming systems, waste is stored for several months before being released into the environment. In this study we analyzed, by means of repetitive extragenic palindromic PCR using the enterobacterial repetitive intergenic consensus primers and comparative analysis using the Bionumerics software, collections of E. coli obtained from a dairy farm and from a swine farm, both of which stored their waste as a slurry in holding tanks. In all fecal samples, obtained from either barns or holding tanks, the diversity of the E. coli populations was underrepresented by collections of 500 isolates. In both the dairy and the swine farms, the diversity of the E. coli community was greater in the manure holding tank than in the barn, when they were sampled on the same date. In both farms, a comparison of stored manure samples collected several months apart suggested that the community composition changed substantially in terms of the detected number, absolute identity, and relative abundance of genotypes. Comparison of E. coli populations obtained from 10 different locations in either holding tank suggested that spatial variability in the E. coli community should be accounted for when sampling. Overall, the diversity in E. coli populations in manure slurry storage facilities is significant and likely is problematic with respect to library construction for microbial source tracking applications.

Linking watershed modeling and bacterial source tracking to better assess E. coli sources

2019 ◽  
Vol 648 ◽  
pp. 164-175 ◽  
Author(s):  
Jaehak Jeong ◽  
Kevin Wagner ◽  
Jaime J. Flores ◽  
Tim Cawthon ◽  
Younggu Her ◽  
...  
Keyword(s):  
Watershed Modeling ◽  
Source Tracking ◽  
E Coli ◽  
Bacterial Source Tracking

scholarly journals A statistical appraisal of disproportional versus proportional microbial source tracking libraries

2007 ◽  
Vol 5 (4) ◽  
pp. 503-509 ◽  
Author(s):  
Brian J. Robinson ◽  
Kerry J. Ritter ◽  
R. D. Ellender
Keyword(s):  
Nearest Neighbor ◽  
Unknown Origin ◽  
Microbial Source Tracking ◽  
Source Tracking ◽  
Correct Prediction ◽  
Statistical Algorithm ◽  
Average Similarity ◽  
Source Category ◽  
Matching Criteria ◽  
Maximum Similarity

Library-based microbial source tracking (MST) can assist in reducing or eliminating fecal pollution in waters by predicting sources of fecal-associated bacteria. Library-based MST relies on an assembly of genetic or phenotypic “fingerprints” from pollution-indicative bacteria cultivated from known sources to compare with and identify fingerprints of unknown origin. The success of the library-based approach depends on how well each source candidate is represented in the library and which statistical algorithm or matching criterion is used to match unknowns. Because known source libraries are often built based on convenience or cost, some library sources may contain more representation than others. Depending on the statistical algorithm or matching criteria, predictions may become severely biased toward classifying unknowns into the library's dominant source category. We examined prediction bias for four of the most commonly used statistical matching algorithms in library-based MST when applied to disproportionately-represented known source libraries; maximum similarity (MS), average similarity (AS), discriminant analyses (DA), and k-means nearest neighbor (k-NN). MS was particularly sensitive to disproportionate source representation. AS and DA were more robust. k-NN provided a compromise between correct prediction and sensitivity to disproportional libraries including increased matching success and stability that should be considered when matching to disproportionally-represented libraries.

scholarly journals Identification of the sources of Escherichia coli in a watershed using carbon-utilization patterns and composite data sets

2008 ◽  
Vol 6 (2) ◽  
pp. 197-207 ◽  
Author(s):  
Samir H. Moussa ◽  
Rene D. Massengale
Keyword(s):  
Antibiotic Resistance ◽  
Predictive Value ◽  
Predictive Accuracy ◽  
Source Tracking ◽  
Carbon Utilization ◽  
E Coli ◽  
Bacterial Source Tracking ◽  
Resistance Analysis ◽  
Utilization Patterns ◽  
Antibiotic Resistance Analysis

The field of bacterial source tracking (BST) has been rapidly evolving to meet the demands of water pollution analysis, specifically the contamination of waterways and drinking water reservoirs by point source and nonpoint source pollution. The goal of the current study was to create a BST library based on carbon-utilization patterns (CUP) for predicting sources of E. coli in a watershed, to compare this library to an antibiotic-resistance analysis (ARA) library previously published for the same isolates, and to determine the efficacy of using a composite dataset which combines data from both datasets into a single library for predicting the source of unknown isolates. This was accomplished by generating a CUP dataset and a composite ARA-CUP dataset for the E. coli isolates from known fecal sources within a watershed. These libraries were then used to predict the sources of E. coli isolates collected from 13 water sites in the same watershed and compared in regard to predictive accuracy. The dominant sources of E. coli in the South Bosque watershed were cattle as identified by all three methods. The 6-source composite library had higher average rates of correct classification (96.7%), specificity (99.2%), positive-predictive value (99.1%), and negative-predictive value (96.8%) than either the ARA or CUP 6 source libraries (ARCC 80.1% and 86.7% respectively). The current study is the first field study to compare two phenotypic methods, Antibiotic Resistance Analysis (ARA) and Carbon Utilization Profiling (CUP). This study is also the first to combine both of these methods to create a composite “toolbox” type approach.

scholarly journals Numbers of fecal streptococci and Escherichia coli in fresh and dry cattle, horse, and sheep manure

2005 ◽  
Vol 51 (10) ◽  
pp. 847-851 ◽  
Author(s):  
R W Weaver ◽  
J A Entry ◽  
Alexandria Graves
Keyword(s):  
Escherichia Coli ◽  
Fecal Coliform ◽  
Bos Taurus ◽  
Source Tracking ◽  
Stream Pollution ◽  
E Coli ◽  
Bacterial Source Tracking ◽  
Fresh Manure ◽  
Sheep Manure ◽  
Fecal Streptococci

Livestock are known contributors to stream pollution. Numbers of fecal streptococci and Escherichia coli in manure naturally deposited by livestock in the field are needed for activities related to bacterial source tracking and determining maximum daily bacterial loading of streams. We measured populations of fecal streptococci and E. coli in fresh and dry manure from cattle (Bos taurus L.), horses (Equus caballus L.), and sheep (Ovis aires L.) on farms in southern Idaho. Populations of indicator bacteria in dry manure were often as high as that in fresh manure from horse and sheep. There was a 2 log10 drop in the population of fecal coliform numbers in dry cattle manure from cattle in pastures but not from cattle in pens. Bacterial isolates used in source tracking should include isolates from both fresh and dry manure to better represent the bacterial source loading of streams.Key words: enterococci, E. coli, fecal streptococci, bacterial indicators, bacterial source tracking, pollution.

scholarly journals Assessment of statistical methods used in library-based approaches to microbial source tracking

2003 ◽  
Vol 1 (4) ◽  
pp. 209-223 ◽  
Author(s):  
Kerry J. Ritter ◽  
Ethan Carruthers ◽  
C. Andrew Carson ◽  
R. D. Ellender ◽  
Valerie J. Harwood ◽  
...  
Keyword(s):  
Statistical Methods ◽  
Large Scale ◽  
Final Analysis ◽  
Microbial Source Tracking ◽  
Source Tracking ◽  
Effective Sample Size ◽  
Correct Classification ◽  
Average Similarity ◽  
Maximum Similarity ◽  
Threshold Criteria

Several commonly used statistical methods for fingerprint identification in microbial source tracking (MST) were examined to assess the effectiveness of pattern-matching algorithms to correctly identify sources. Although numerous statistical methods have been employed for source identification, no widespread consensus exists as to which is most appropriate. A large-scale comparison of several MST methods, using identical fecal sources, presented a unique opportunity to assess the utility of several popular statistical methods. These included discriminant analysis, nearest neighbour analysis, maximum similarity and average similarity, along with several measures of distance or similarity. Threshold criteria for excluding uncertain or poorly matched isolates from final analysis were also examined for their ability to reduce false positives and increase prediction success. Six independent libraries used in the study were constructed from indicator bacteria isolated from fecal materials of humans, seagulls, cows and dogs. Three of these libraries were constructed using the rep-PCR technique and three relied on antibiotic resistance analysis (ARA). Five of the libraries were constructed using Escherichia coli and one using Enterococcus spp. (ARA). Overall, the outcome of this study suggests a high degree of variability across statistical methods. Despite large differences in correct classification rates among the statistical methods, no single statistical approach emerged as superior. Thresholds failed to consistently increase rates of correct classification and improvement was often associated with substantial effective sample size reduction. Recommendations are provided to aid in selecting appropriate analyses for these types of data.

scholarly journals Geographic sharing of ribotype patterns in Enterococcus faecalis for bacterial source tracking

2007 ◽  
Vol 5 (4) ◽  
pp. 539-551 ◽  
Author(s):  
Peter G. Hartel ◽  
Robin L. Kuntz ◽  
Karen Rodgers ◽  
Samuel P. Myoda ◽  
Kerry J. Ritter ◽  
...  
Keyword(s):  
New York ◽  
Enterococcus Faecalis ◽  
Wastewater Treatment Plants ◽  
Geographic Distance ◽  
Similarity Index ◽  
Clonal Diversity ◽  
Mantel Test ◽  
Source Tracking ◽  
Tolerance Level ◽  
Bacterial Source Tracking

The limited host range of Enterococcus faecalis may reduce its clonal diversity and thereby increase its geographic sharing of ribotype patterns. Such sharing would be advantageous for bacterial source tracking (BST). We determined the geographic sharing of ribotype patterns in 752 Ent. faecalis isolates obtained primarily from wastewater treatment plants in Delaware (15 locations; 490 isolates), Georgia (2 locations; 48 isolates), Idaho (1 location; 118 isolates), New York (2 locations; 48 isolates), and Puerto Rico (2 locations; 48 isolates). Isolates were ribotyped with a RiboPrinter. When pooled across all locations and analyzed at a similarity index of 100% and a tolerance level of 1.00%, the 752 Ent. faecalis isolates yielded 652 different ribotypes, of which 429 (66%) were unshared. Even when the matching criterion was relaxed by decreasing the tolerance level from 1% to 10% or lowering the similarity cutoff from 100% to 90%, half or almost half of the ribotypes were unshared. A Mantel test of zero correlation showed no statistically significant correlation between ribotype patterns and geographic distance among the 32 samples (one location at one time) at either the 1.00% (P = 0.91) or 10.00% (P = 0.83) tolerance levels. Therefore, the percentage of ribotype patterns shared between two locations did not increase as the distance between locations decreased. In the case of BST, a permanent host origin database sufficiently large to encompass these ribotype patterns would be time-consuming and expensive to construct.

Flood and rainfall mobilisation of E. coli and faecal source tracking markers from decomposing cowpats 

2021 ◽  
Author(s):  
Megan Devane ◽  
Brent Gilpin ◽  
Jennifer Webster-Brown ◽  
Louise Weaver ◽  
Pierre Dupont ◽  
...  
Keyword(s):  
Water Quality ◽  
Overland Flow ◽  
Quantitative Polymerase Chain Reaction ◽  
Linear Regression Analysis ◽  
Water Quality Monitoring ◽  
Quality Monitoring ◽  
Source Tracking ◽  
Faecal Contamination ◽  
E Coli ◽  
Faecal Indicators

<p>The intensification of dairy farming on the agricultural landscape in New Zealand has raised concerns about pollution sources from dairy faecal runoff into waterways. The transport of faecal pollution from farms into waterways is facilitated by overland flow, which can result from rain and flood events, poorly designed irrigation practices and the washing down of milking sheds.</p><p>An important step for mitigation of pollution is the identification of the source(s) of faecal contamination. When elevated levels of faecal indicator bacteria (FIB) such as <em>Escherichia coli </em>are identified in a waterway, faecal source tracking (FST) tools such as microbial source tracking (MST) using quantitative polymerase chain reaction (qPCR), and faecal steroids (for example, cholesterol) provide information about the sources of faecal contamination. The understanding of the fate (degradation/persistence) and transport of these FST markers in the environment is recognised as an important requirement for the interpretation of water quality monitoring in aquatic environments.</p><p>This study investigated the effects of faecal decomposition on bovine faecal indicators (<em>E. coli </em>and FST markers: bovine-associated qPCR markers and ten faecal steroids) by monitoring the effect of flood and rainfall events on simulated cowpats over a five and a half month period under field conditions. Two separate spring/summer trials were conducted to evaluate: Trial 1) the mobilisation under simulated flood conditions of the faecal indicators from irrigated versus non-irrigated cowpats, Trial 2) the mobilisation of faecal indicators from non-irrigated cowpat flood runoff versus runoff after simulated rainfall onto non-irrigated cowpats.</p><p>The microbial community changes within the decomposing cowpat (as illustrated by amplicon-based metagenomic analysis) were expected to impact on the survival/persistence of the bacterial targets of the MST markers, and also alter the ratio between faecal sterols and their biodegradation products, the stanols. It was hypothesised, therefore, that there would be:</p><ul><li>Changes over time in the concentration of<em> E. coli </em>and the bovine-associated MST markers mobilised into the cowpat runoff</li> <li>Alterations in the FST ratio signature of the ten measured faecal steroids, resulting in a change from a bovine faecal steroid signature in fresh cowpat runoff to other animal faecal signatures in the runoff from decomposing cowpats</li> <li>A difference in the mobilisation decline rates of all FST and microbial markers within a treatment regime and between treatments.</li> </ul><p>Linear regression analysis was undertaken to establish mobilisation decline rates for each of the analytes in the mobilisable phase from the cowpat runoff treatments, with calculation of the time taken in days for reduction in 90% of the concentration (T<sub>90</sub>), and statistical comparison of the regression coefficients (slopes) of all analytes. The results will include a discussion of the impacts of the study’s observations on the interpretation of faecal indicator assessments for water quality monitoring in waterways influenced by sources of faecal contamination.</p>

The use of antibiotic resistance profiling as a means of tracing sources of fecal contamination in source waters

2010 ◽  
Vol 10 (2) ◽  
pp. 209-215
Author(s):  
M. S. Mthembu ◽  
P. T. Biyela ◽  
T. G. Djarova ◽  
A. K. Basson
Keyword(s):  
Antibiotic Resistance ◽  
Municipal Wastewater ◽  
Fecal Contamination ◽  
Source Tracking ◽  
Human Consumption ◽  
Biochemical Tests ◽  
Isolation And Identification ◽  
E Coli ◽  
Intestinal Pathogens ◽  
Source Waters

Fecal contamination of source waters and its associated intestinal pathogens continues to pose risks to public health although the extent and effect of microbial contamination of source waters gets very little attention in designing treatment plants in most developing countries. Coliform counts give an indication of the overall bacterial contamination of water and thus its safety for human consumption. However, their presence fails to provide information about the source of fecal contamination which is vital to managing fecal contamination problems in surface waters. This study explored the use of multiple antibiotic resistance (MAR) indexing as means of differentiating E. coli isolates from different sources. A total of 322 E. coli isolates were obtained from municipal wastewater and from fecal samples from domestic and wild animals. Conventional culture methods and standard chemical and biochemical tests were used for isolation and identification of E. coli. Isolates were assayed against 10 antibiotics using the micro-dilution technique. The results obtained generated antibiotic resistance profiles which were used to statistically group the isolates into different subsets. Correct source classification was obtained for 60% of human-derived and 95% non-human-derived E. coli respectively. These results indicate the validity of the usefulness of MAR indexing as a method of bacterial source tracking.

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