Geology topics

Erin A. Stelzer

Publications and source records attributed to Erin A. Stelzer.

33 records · Page 2Linked to original sources

USGS2016

Estimating microcystin levels at recreational sites in western Lake Erie and Ohio

Cyanobacterial harmful algal blooms (cyanoHABs) and associated toxins, such as microcystin, are a major global water-quality issue. Water-resource managers need tools to quickly predict when and where toxin-producing cyanoHABs will occur. This could be done by using site-specific models that estimate the potential for elevated toxin concentrations that cause public health concerns. With this study, samples were collected at three Ohio lakes to identify environmental and water-quality factors to develop linear-regression models to estimate microcystin levels. Measures of the algal community (phycocyanin, cyanobacterial biovolume, and cyanobacterial gene concentrations) and pH were most strongly correlated with microcystin concentrations. Cyanobacterial genes were quantified for general cyanobacteria, general Microcystis and Dolichospermum , and for microcystin synthetase ( mcyE ) for Microcystis , Dolichospermum , and Planktothrix. For phycocyanin, the relations were different between sites and were different between hand-held measurements on-site and nearby continuous monitor measurements for the same site. Continuous measurements of parameters such as phycocyanin, pH, and temperature over multiple days showed the highest correlations to microcystin concentrations. The development of models with high R 2 values (0.81–0.90), sensitivities (92%), and specificities (100%) for estimating microcystin concentrations above or below the Ohio Recreational Public Health Advisory level of 6 μg L −1 was demonstrated for one site; these statistics may change as more data are collected in subsequent years. This study showed that models could be developed for estimates of exceeding a microcystin threshold concentration at a recreational freshwater lake site, with potential to expand their use to provide relevant public health information to water resource managers and the public for both recreational and drinking waters.

Ohio↗

USGS2016

Multi-laboratory survey of qPCR enterococci analysis method performance in U.S. coastal and inland surface waters

Quantitative polymerase chain reaction (qPCR) has become a frequently used technique for quantifying enterococci in recreational surface waters, but there are several methodological options. Here we evaluated how three method permutations, type of mastermix, sample extract dilution and use of controls in results calculation, affect method reliability among multiple laboratories with respect to sample interference. Multiple samples from each of 22 sites representing an array of habitat types were analyzed using EPA Method 1611 and 1609 reagents with full strength and five-fold diluted extracts. The presence of interference was assessed three ways: using sample processing and PCR amplifications controls; consistency of results across extract dilutions; and relative recovery of target genes from spiked enterococci in water sample compared to control matrices with acceptable recovery defined as 50 to 200%. Method 1609, which is based on an environmental mastermix, was found to be superior to Method 1611, which is based on a universal mastermix. Method 1611 had over a 40% control assay failure rate with undiluted extracts and a 6% failure rate with diluted extracts. Method 1609 failed in only 11% and 3% of undiluted and diluted extracts analyses. Use of sample processing control assay results in the delta–delta Ct method for calculating relative target gene recoveries increased the number of acceptable recovery results. Delta–delta tended to bias recoveries from apparent partially inhibitory samples on the high side which could help in avoiding potential underestimates of enterococci — an important consideration in a public health context. Control assay and delta–delta recovery results were largely consistent across the range of habitats sampled, and among laboratories. The methodological option that best balanced acceptable estimated target gene recoveries with method sensitivity and avoidance of underestimated enterococci densities was Method 1609 without extract dilution and using the delta–delta calculation method. The applicability of this method can be extended by the analysis of diluted extracts to sites where interference is indicated but, particularly in these instances, should be confirmed by augmenting the control assays with analyses for target gene recoveries from spiked target organisms.

Journal of Microbiological Methods↗

USGS2015

Water Quality, Cyanobacteria, and Environmental Factors and Their Relations to Microcystin Concentrations for Use in Predictive Models at Ohio Lake Erie and Inland Lake Recreational Sites, 2013-14

Harmful cyanobacterial “algal” blooms (cyanoHABs) and associated toxins, such as microcystin, are a major water-quality issue for Lake Erie and inland lakes in Ohio. Predicting when and where a bloom may occur is important to protect the public that uses and consumes a water resource; however, predictions are complicated and likely site specific because of the many factors affecting toxin production. Monitoring for a variety of environmental and water-quality factors, for concentrations of cyanobacteria by molecular methods, and for algal pigments such as chlorophyll and phycocyanin by using optical sensors may provide data that can be used to predict the occurrence of cyanoHABs. To test these monitoring approaches, water-quality samples were collected at Ohio recreational sites during May–November in 2013 and 2014. In 2013, samples were collected monthly at eight sites at eight lakes to facilitate an initial assessment and select sites for more intensive sampling during 2014. In 2014, samples were collected approximately weekly at five sites at three lakes. Physical water-quality parameters were measured at the time of sampling. Composite samples were preserved and analyzed for dissolved and total nutrients, toxins, phytoplankton abundance and biovolume, and cyanobacterial genes by molecular methods. Molecular assays were done to enumerate (1) general cyanobacteria, (2) general Microcystis and Dolichospermum ( Anabaena ), (3) mcyE genes for Microcystis , Dolichospermum ( Anabaena ), and Planktothrix targeting deoxyribonucleic acid (DNA), and (4) mcyE transcripts for Microcystis , Dolichospermum ( Anabaena ), and Planktothrix targeting ribonucleic acid (RNA).The DNA assays for the mcyE gene provide data on cyanobacteria that have the potential to produce microcystin, whereas the RNA assays provide data on cyanobacteria that are actively transcribing the toxin gene. Environmental data were obtained from available online sources. Quality-control (QC) samples were collected and analyzed for all constituents to characterize bias and variability; however, QC data for molecular assays were examined in more detail than for the other constituents. The QC data for molecular assays suggested that sampling variability and qPCR variability were small in comparison with the combined variability associated with sample filtering, extraction and purification, and the matrix itself. A total of 46 water-quality samples were collected during 2013 at 8 beach sites—Buck Creek, Buckeye Crystal, Deer Creek, Harsha Main, Maumee Bay State Park (MBSP) Inland (negative control site), MBSP Lake Erie, Port Clinton, and Sandusky Bay. Microcystin was detected in 67–100 percent of samples at all sites except for MBSP Inland, where microcystin was detected in only 20 percent of samples. Microcystin concentrations ranged from <0.10 to 48 micrograms per liter (µ/L), with the widest range found at MBSP Lake Erie and the highest concentrations found at Buckeye Crystal. Saxitoxin was detected in five samples, and cylindrospermopsin was not detected in any samples. A total of 65 water-quality samples were collected during 2014 at 5 sites on 3 lakes—Buckeye Fairfield and Onion Island, Harsha Main and Campers, and MBSP Lake Erie beach. Four of the sites were bathing beaches and one site, Onion Island, was an offshore boater swim area. Concentrations of microcystin ranged from <0.10 to 240 µ/L and, as in 2013, the widest range was found at MBSP Lake Erie. At Buckeye Lake, microcystin concentrations were consistently high (greater than 20 µ/L), ranging from 23 to 81 µ/L. At Harsha Main and Campers, microcystin concentrations ranged from <0.10 to 15 µ/L. Saxitoxin was detected in four samples collected at MBSP Lake Erie. Throughout the 2014 season, the cyanobacterial community, as determined by molecular and microscopy methods, and the dominance associated with the highest microcystin concentrations were unique to individual lakes. At Buckeye Lake, Planktothrix dominated the cyanobacterial community throughout the season and Planktothrix DNA and RNA were found in 100 percent of samples; Microcystis mcyE DNA was found in low concentrations. At Harsha Lake, Dolichospermum and Microcystis were a substantial percentage of the community from late May through August, and the highest microcystin concentrations occurred in June and July. At MBSP Lake Erie, Microcystis generally dominated from mid-July through early November, and the highest microcystin concentrations occurred in August. Spearman’s correlation coefficient (rho) was computed to determine the relations between environmental and water-quality factors and microcystin concentrations at four sites—Buckeye Fairfield, Buckeye Onion Island, Harsha Main, and MBSP Lake Erie. Factors were evaluated for use as potential independent variables in two types of predictive models—daily and long-term models. Easily or continuously measured water-quality factors and available environmental data are used for daily predictions that do not require a site visit. Data from factors used in daily predictions and results from samples collected and analyzed in a laboratory are used for long-term predictions (a few days to several weeks). A few statistically significant correlations (p ≤ 0.05) between microcystin concentrations and factors for both daily and long-term predictions were found at Buckeye Onion Island, and many were found at Harsha Main and MBSP Lake Erie. There were only a few statistically significant factors for daily predictions at Buckeye Fairfield, likely because of the lack of variability in microcystin concentrations. Among factors for daily predictions, phycocyanin had the highest Spearman’s correlation to microcystin concentrations (rho = 0.79 to 0.93) at all sites except for Buckeye Fairfield. Turbidity, pH, algae category, and Secchi depth were significantly correlated to microcystin concentrations at Harsha Main and MBSP Lake Erie. Algae categories were observational categories from 0 (none) to 4 (extreme). Several discharge variables (Maumee River at Waterville, river mouth is approximately 3.5 miles from the beach) at MBSP Lake Erie were promising environmental factors for daily predictions. In addition to discrete water-quality measurements recorded at Harsha Main at the time of sampling, many manipulated measurements (factors derived from mathematical manipulation of time-series data) available from a nearby continuous monitor were strongly correlated to microcystin concentrations; the highest correlation was found for the relation between microcystin concentrations and the antecedent 7-day average phycocyanin (rho = 0.98). For long-term predictions, the most highly correlated molecular assays were Planktothrix mcyE DNA at Buckeye Onion Island and Microcystis mcyE DNA at Harsha Main and MBSP Lake Erie. Concentrations of several nutrient constituents were significantly correlated to microcystin concentrations including total nitrogen at Buckeye Onion Island, ammonia and nitrate plus nitrite (both negatively correlated) at Harsha Main and MBSP Lake Erie, and total phosphorus at MBSP Lake Erie. The results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.

Ohio↗

USGS2014

Chemical and biological quality of water in Grand Lake St. Marys, Ohio, 2011-12, with emphasis on cyanobacteria

Grand Lake St. Marys (GLSM) is a shallow lake in northwest Ohio, which is about 9 miles long and 3 miles wide with depths averaging less than 8 feet. Cyanobacteria blooms are common in GLSM, and high concentrations of microcystins—toxins produced by cyanobacteria—have been documented therein. During 2011–12, the U.S. Geological Survey collected 11 sets of water samples at 6 locations in the lake. The water samples were analyzed for concentrations of nutrients, chlorophyll, and microcystin and to determine plankton community structure and abundance. Analysis by quantitative polymerase chain reaction (qPCR) and quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was used to identify the relations between microcystin concentrations and Planktothrix and Microcystis genotypes (toxic versus non-toxic). The qPCR analysis targets deoxyribonucleic acid (DNA) genes and quantifies the potential for toxin production, whereas the qRT-PCR analysis targets ribonucleic acid (RNA) transcripts and quantifies the expression of the toxin gene. Water samples were collected six times at one site for analyses of major ions and trace elements. In addition, field measurements were made to determine transparency, temperature, dissolved oxygen, pH, and specific conductance of the water. GLSM is shallow with a long fetch, which contributes to the warm and turbid water conditions. Secchi-disk measurements generally ranged from 0.2 to 0.3 meters, and summer water temperatures in GLSM frequently exceed 25 degrees Celsius (°C), with peak temperatures greater than 30 °C. Dissolved oxygen readings below 0.5 milligrams per liter (mg/L) occurred at the lake bottom, which can lead to the internal recycling of phosphorus in the lake. Phytoplankton analyses indicated that GLSM is dominated by cyanobacteria with Planktothrix , the dominant genera during 2011–12. Nitrate ranged from 0.19 to 3.23 mg/L, although concentrations in most samples were less than 1 mg/L. Total nitrogen concentrations ranged from 1.86 to 5.42 mg/L. Orthophosphate (as P) concentrations ranged from less than 0.004 to 0.067 mg/L, although concentrations of most samples were less than 0.004 mg/L. Total phosphorus (as P) concentrations ranged from 0.12 to 0.43 mg/L. Microcystin concentrations ranged from 7.3 to 83 micrograms per liter. Microcystin concentrations were correlated to cyanobacteria biovolumes, and to concentrations of one ion (sodium) and three trace elements (molybdenum, antimony, and lithium). Concentrations of toxin genes ( mcyE ) determined by qPCR were consistently low for Microcystis and consistently high for Planktothrix throughout both sampling years. Concentrations of cyanobacteria found by qPCR were correlated to microcystin concentrations, cyanobacteria biovolumes, selected nutrient concentrations, and other parameters. Results from qRT-PCR assays showed that toxin gene expression was predominantly from the genus Planktothrix , and concentrations of the RNA transcript varied throughout the two sampling years. A number of conditions that may play a role in the dominance of Planktothrix and the production of microcystin were identified including water temperature; low-light transmission; low concentrations of silica and manganese; and relatively high concentrations of sodium, sulfate, and the trace elements of strontium, vanadium, and boron.

Ohio↗

USGS2013

Geographic setting influences Great Lakes beach microbiological water quality

Understanding of factors that influence Escherichia coli (EC) and enterococci (ENT) concentrations, pathogen occurrence, and microbial sources at Great Lakes beaches comes largely from individual beach studies. Using 12 representative beaches, we tested enrichment cultures from 273 beach water and 22 tributary samples for EC, ENT, and genes indicating the bacterial pathogens Shiga-toxin producing E. coli (STEC), Shigella spp., Salmonella spp, Campylobacter jejuni/coli, and methicillin-resistant Staphylococcus aureus, and 108–145 samples for Bacteroides human, ruminant, and gull source-marker genes. EC/ENT temporal patterns, general Bacteroides concentration, and pathogen types and occurrence were regionally consistent (up to 40 km), but beach catchment variables (drains/creeks, impervious surface, urban land cover) influenced exceedances of EC/ENT standards and detections of Salmonella and STEC. Pathogen detections were more numerous when the EC/ENT Beach Action Value (but not when the Geometric Mean and Statistical Threshold Value) was exceeded. EC, ENT, and pathogens were not necessarily influenced by the same variables. Multiple Bacteroides sources, varying by date, occurred at every beach. Study of multiple beaches in different geographic settings provided new insights on the contrasting influences of regional and local variables, and a broader-scale perspective, on significance of EC/ENT exceedances, bacterial sources, and pathogen occurrence.

Great Lakes↗

USGS2013

Predictive models for Escherichia coli concentrations at inland lake beaches and relationship of model variables to pathogen detection

Predictive models, based on environmental and water quality variables, have been used to improve the timeliness and accuracy of recreational water quality assessments, but their effectiveness has not been studied in inland waters. Sampling at eight inland recreational lakes in Ohio was done in order to investigate using predictive models for Escherichia coli and to understand the links between E. coli concentrations, predictive variables, and pathogens. Based upon results from 21 beach sites, models were developed for 13 sites, and the most predictive variables were rainfall, wind direction and speed, turbidity, and water temperature. Models were not developed at sites where the E. coli standard was seldom exceeded. Models were validated at nine sites during an independent year. At three sites, the model resulted in increased correct responses, sensitivities, and specificities compared to use of the previous day's E. coli concentration (the current method). Drought conditions during the validation year precluded being able to adequately assess model performance at most of the other sites. Cryptosporidium , adenovirus, eaeA ( E. coli ), ipaH ( Shigella ), and spvC ( Salmonella ) were found in at least 20% of samples collected for pathogens at five sites. The presence or absence of the three bacterial genes was related to some of the model variables but was not consistently related to E. coli concentrations. Predictive models were not effective at all inland lake sites; however, their use at two lakes with high swimmer densities will provide better estimates of public health risk than current methods and will be a valuable resource for beach managers and the public.

Ohio↗

USGS2013

Comparison of filters for concentrating microbial indicators and pathogens in lake-water samples

Bacterial indicators are used to indicate increased health risk from pathogens and to make beach closure and advisory decisions; however, beaches are seldom monitored for the pathogens themselves. Studies of sources and types of pathogens at beaches are needed to improve estimates of swimming-associated health risks. It would be advantageous and cost-effective, especially for studies conducted on a regional scale, to use a method that can simultaneously filter and concentrate all classes of pathogens from the large volumes of water needed to detect pathogens. In seven recovery experiments, stock cultures of viruses and protozoa were seeded into 10-liter lake water samples, and concentrations of naturally occurring bacterial indicators were used to determine recoveries. For the five filtration methods tested, the highest median recoveries were as follows: glass wool for adenovirus (4.7%); NanoCeram for enterovirus (14.5%) and MS2 coliphage (84%); continuous-flow centrifugation (CFC) plus Virocap (CFC+ViroCap) for Escherichia coli (68.3%) and Cryptosporidium (54%); automatic ultrafiltration (UF) for norovirus GII (2.4%); and dead-end UF for Enterococcus faecalis (80.5%), avian influenza virus (0.02%), and Giardia (57%). In evaluating filter performance in terms of both recovery and variability, the automatic UF resulted in the highest recovery while maintaining low variability for all nine microorganisms. The automatic UF was used to demonstrate that filtration can be scaled up to field deployment and the collection of 200-liter lake water samples.

Michigan, New York, Ohio, Wisconsin↗

USGS2013

Relations between DNA- and RNA-based molecular methods for cyanobacteria and microcystin concentration at Maumee Bay State Park Lakeside Beach, Oregon, Ohio, 2012

Water samples were collected from Maumee Bay State Park Lakeside Beach, Oregon, Ohio, during the 2012 recreational season and analyzed for selected cyanobacteria gene sequences by DNA-based quantitative polymerase chain reaction (qPCR) and RNA-based quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Results from the four DNA assays (for quantifying total cyanobacteria, total Microcystis , and Microcystis and Planktothrix strains that possess the microcystin synthetase E ( mcyE ) gene) and two RNA assays (for quantifying Microcystis and Planktothrix genera that are expressing the microcystin synthetase E ( mcyE ) gene) were compared to microcystin concentration results determined by an enzyme-linked immunosorbent assay (ELISA). Concentrations of the target in replicate analyses were log10 transformed. The average value of differences in log10 concentrations for the replicates that had at least one detection were found to range from 0.05 to >0.37 copy per 100 milliliters (copy/100 mL) for DNA-based methods and from >0.04 to >0.17 copy/100 mL for RNA-based methods. RNA has a shorter half-life than DNA; consequently, a 24-hour holding-time study was done to determine the effects of holding time on RNA concentrations. Holding-time comparisons for the RNA-based Microcystis toxin mcyE assay showed reductions in the number of copies per 100 milliliters over 24 hours. The log difference between time 2 hours and time 24 hours was >0.37 copy/100 mL, which was higher than the analytical variability (log difference of >0.17 copy/100 mL). Spearman’s correlation analysis indicated that microcystin toxin concentrations were moderately to highly related to DNA-based assay results for total cyanobacteria (rho=0.69), total Microcystis (rho=0.74), and Microcystis strains that possess the mcyE gene (rho=0.81). Microcystin toxin concentrations were strongly related with RNA-based assay results for Microcystis mcyE gene expression (rho=0.95). Correlation analysis could not be done for Planktothrix mcyE gene expression because of too few detections.

Ohio↗

USGS2012

Microbial source tracking markers at three inland recreational lakes in Ohio, 2011

During the 2011 recreational season, samples were collected for E. coli and microbial source tracking (MST) marker concentrations to begin to understand potential sources of fecal contamination at three inland recreational lakes in Ohio - Buckeye, Atwood, and Tappan Lakes. The results from 32 regular samples, 4 field blanks, and 7 field replicates collected at 5 sites are presented in this report. At the three lakes, the ruminant-associated marker was found most often (57-73 percent of samples) but at estimated quantities, followed by the dog-associated marker (30-43 percent of samples). The human-associated marker was found in 14 and 50 percent of samples from Atwood and Tappan Lakes, respectively, but was not found in any samples from the two Buckeye Lake sites. The gull-associated marker was detected in only two samples, both from Tappan Lake.

Ohio↗

USGS2012

Interlaboratory comparison of three microbial source tracking quantitative polymerase chain reaction (qPCR) assays from fecal-source and environmental samples

During summer and early fall 2010, 15 river samples and 6 fecal-source samples were collected in West Virginia. These samples were analyzed by three laboratories for three microbial source tracking (MST) markers: AllBac, a general fecal indicator; BacHum, a human-associated fecal indicator; and BoBac, a ruminant-associated fecal indicator. MST markers were analyzed by means of the quantitative polymerase chain reaction (qPCR) method. The aim was to assess interlaboratory precision when the three laboratories used the same MST marker and shared deoxyribonucleic acid (DNA) extracts of the samples, but different equipment, reagents, and analyst experience levels. The term assay refers to both the markers and the procedure differences listed above. Interlaboratory precision was best for all three MST assays when using the geometric mean absolute relative percent difference (ARPD) and Friedman's statistical test as a measure of interlaboratory precision. Adjustment factors (one for each MST assay) were calculated using results from fecal-source samples analyzed by all three laboratories and applied retrospectively to sample concentrations to account for differences in qPCR results among labs using different standards and procedures. Following the application of adjustment factors to qPCR results, ARPDs were lower; however, statistically significant differences between labs were still observed for the BacHum and BoBac assays. This was a small study and two of the MST assays had 52 percent of samples with concentrations at or below the limit of accurate quantification; hence, more testing could be done to determine if the adjustment factors would work better if the majority of sample concentrations were above the quantification limit.

West Virginia↗

USGS2011

Interlaboratory comparison of real-time pcr protocols for quantification of general fecal indicator bacteria

The application of quantitative real-time PCR (qPCR) technologies for the rapid identification of fecal bacteria in environmental waters is being considered for use as a national water quality metric in the United States. The transition from research tool to a standardized protocol requires information on the reproducibility and sources of variation associated with qPCR methodology across laboratories. This study examines interlaboratory variability in the measurement of enterococci and Bacteroidales concentrations from standardized, spiked, and environmental sources of DNA using the Entero1a and GenBac3 qPCR methods, respectively. Comparisons are based on data generated from eight different research facilities. Special attention was placed on the influence of the DNA isolation step and effect of simplex and multiplex amplification approaches on interlaboratory variability. Results suggest that a crude lysate is sufficient for DNA isolation unless environmental samples contain substances that can inhibit qPCR amplification. No appreciable difference was observed between simplex and multiplex amplification approaches. Overall, interlaboratory variability levels remained low (<10% coefficient of variation) regardless of qPCR protocol.

Environmental Science & Technology↗

USGS2011

Semi-quantitative evaluation of fecal contamination potential by human and ruminant sources using multiple lines of evidence

Protocols for microbial source tracking of fecal contamination generally are able to identify when a source of contamination is present, but thus far have been unable to evaluate what portion of fecal-indicator bacteria (FIB) came from various sources. A mathematical approach to estimate relative amounts of FIB, such as Escherichia coli , from various sources based on the concentration and distribution of microbial source tracking markers in feces was developed. The approach was tested using dilute fecal suspensions, then applied as part of an analytical suite to a contaminated headwater stream in the Rocky Mountains (Upper Fountain Creek, Colorado). In one single-source fecal suspension, a source that was not present could not be excluded because of incomplete marker specificity; however, human and ruminant sources were detected whenever they were present. In the mixed-feces suspension (pet and human), the minority contributor (human) was detected at a concentration low enough to preclude human contamination as the dominant source of E. coli to the sample. Without the semi-quantitative approach described, simple detects of human-associated marker in stream samples would have provided inaccurate evidence that human contamination was a major source of E. coli to the stream. In samples from Upper Fountain Creek the pattern of E. coli , general and host-associated microbial source tracking markers, nutrients, and wastewater-associated chemical detections—augmented with local observations and land-use patterns—indicated that, contrary to expectations, birds rather than humans or ruminants were the predominant source of fecal contamination to Upper Fountain Creek. This new approach to E. coli allocation, validated by a controlled study and tested by application in a relatively simple setting, represents a widely applicable step forward in the field of microbial source tracking of fecal contamination.

Water Research↗

USGS2011

Using host-associated genetic markers to investigate sources of fecal contamination in two Vermont streams

The use of host-associated Bacteroidales-based 16S ribosomal ribonucleic acid genetic markers was investigated as a tool for providing information to managers on sources of bacterial impairment in Vermont streams. The study was conducted during 2009 in two watersheds on the U.S. Environmental Protection Agency's 303(d) List of Impaired Waters, the Huntington and the Mettawee Rivers. Streamwater samples collected during high-flow and base-flow conditions were analyzed for concentrations of Escherichia coli (E. coli) and Bacteroidales genetic markers (General AllBac, Human qHF183 and BacHum, Ruminant BoBac, and Canid BacCan) to identify humans, ruminants, and canids as likely or unlikely major sources of fecal contamination. Fecal reference samples from each of the potential source groups, as well as from common species of wildlife, were collected during the same season and from the same watersheds as water samples. The results were combined with data from other states to assess marker cross reaction and to relate marker results to E. coli, the regulated water-quality parameter, with a higher degree of statistical significance. Results from samples from the Huntington River collected under different flow conditions on three dates indicated that humans were unlikely to be a major source of fecal contamination, except for a single positive result at one station that indicated the potential for human sources. Ruminants (deer, moose, cow, or sheep) were potential sources of fecal contamination at all six stations on the Huntington River during one high-flow event and at all but two stations during the other high-flow event. Canids were potential sources of fecal contamination at some stations during two high-flow events, with genetic-marker concentrations in samples from two of the six stations showing consistent positive results for canids for both storm dates. A base-flow sample showed no evidence of major fecal contamination in the Huntington River from humans, ruminants, or canids. Results from samples from the Mettawee River watershed collected during high-flow conditions (12 storm samples on 2 dates at 6 stations) indicated that there was no evidence of fecal contamination from humans in seven samples and possible evidence in five samples. Results for humans were positive for only one station during both storm events. For two of the five samples with evidence for human fecal contamination, results for two different human genetic markers agreed, but results from three samples were inconsistent. In samples from five of the six Mettawee stations, ruminants were a potential source of fecal contamination on at least one of the three sampled dates, including three positive results for the base-flow sample. Yet samples from all of the stations that showed positive results for ruminants did so for only one or two of the three sampled dates. Samples from only one of the six stations gave consistent results, which were negative for ruminants for all three dates. In the Mettawee River base-flow sample, humans were an unlikely source of major fecal contamination. Factors that may influence results and conclusions include the timing of sample collection relative to the storm event; variability of E. coli and Bacteroidales concentrations in fecal reference samples and in water; sampling and analytical errors; the potential cross reactivity of host-associated genetic markers; and different persistence and survival rates of E. coli bacteria and Bacteroidales genetic markers on land, in water, and by season. These factors interfere with the ability to directly relate Bacteroidales concentrations to E. coli concentrations in river samples. It must be recognized that while use of Bacteroidales genetic markers as a source tracking tool coupled with the interpretive approach described in this report cannot be used quantitatively to pinpoint sources, it can be used to exclude potential sources as major contributors to fecal contamination.

Vermont↗

USGS2011

Quantifying viruses and bacteria in wastewater—Results, interpretation methods, and quality control

Membrane bioreactors (MBR), used for wastewater treatment in Ohio and elsewhere in the United States, have pore sizes small enough to theoretically reduce concentrations of protozoa and bacteria, but not viruses. Sampling for viruses in wastewater is seldom done and not required. Instead, the bacterial indicators Escherichia coli (E. coli) and fecal coliforms are the required microbial measures of effluents for wastewater-discharge permits. Information is needed on the effectiveness of MBRs in removing human enteric viruses from wastewaters, particularly as compared to conventional wastewater treatment before and after disinfection. A total of 73 regular and 28 quality-control (QC) samples were collected at three MBR and two conventional wastewater plants in Ohio during 23 regular and 3 QC sampling trips in 2008-10. Samples were collected at various stages in the treatment processes and analyzed for bacterial indicators E. coli, fecal coliforms, and enterococci by membrane filtration; somatic and F-specific coliphage by the single agar layer (SAL) method; adenovirus, enterovirus, norovirus GI and GII, rotavirus, and hepatitis A virus by molecular methods; and viruses by cell culture. While addressing the main objective of the study-comparing removal of viruses and bacterial indicators in MBR and conventional plants-it was realized that work was needed to identify data analysis and quantification methods for interpreting enteric virus and QC data. Therefore, methods for quantifying viruses, qualifying results, and applying QC data to interpretations are described in this report. During each regular sampling trip, samples were collected (1) before conventional or MBR treatment (post-preliminary), (2) after secondary or MBR treatment (post-secondary or post-MBR), (3) after tertiary treatment (one conventional plant only), and (4) after disinfection (post-disinfection). Glass-wool fiber filtration was used to concentrate enteric viruses from large volumes, and small volume grab samples were collected for direct-plating analyses for bacterial indicators and coliphage. After filtration, the viruses were eluted from the filter and further concentrated. The final concentrated sample volume (FCSV) was used for enteric virus analysis by use of two methods-cell culture and a molecular method, polymerase chain reaction (PCR). Quantitative PCR (qPCR) for DNA viruses and quantitative reverse-transcriptase PCR (qRT-PCR) for RNA viruses were used in this study. To support data interpretations, the assay limit of detection (ALOD) was set for each virus assay and used to determine sample reporting limits (SRLs). For qPCR and qRT-PCR the ALOD was an estimated value because it was not established according to established method detection limit procedures. The SRLs were different for each sample because effective sample volumes (the volume of the original sample that was actually used in each analysis) were different for each sample. Effective sample volumes were much less than the original sample volumes because of reductions from processing steps and (or) from when dilutions were made to minimize the effects from PCR-inhibiting substances. Codes were used to further qualify the virus data and indicate the level of uncertainty associated with each measurement. Quality-control samples were used to support data interpretations. Field and laboratory blanks for bacteria, coliphage, and enteric viruses were all below detection, indicating that it was unlikely that samples were contaminated from equipment or processing procedures. The absolute value log differences (AVLDs) between concurrent replicate pairs were calculated to identify the variability associated with each measurement. For bacterial indicators and coliphage, the AVLD results indicated that concentrations <10 colony-forming units or plaque-forming units per 100 mL can differ between replicates by as much as 1 log, whereas higher concentrations can differ by as much as 0.3 log. The AVLD results for viruses indicated that differences between replicates can be as great as 1.2 log genomic copies per liter, regardless of the concentration of virus. Relatively large differences in molecular results for viruses between replicate pairs were likely due to lack of precision for samples with small effective volumes. Concentrations of E. coli, fecal coliforms, enterococci, and somatic and F-specific coliphage in post-secondary and post-tertiary samples in conventional plants were higher than those in post-MBR samples. In post-MBR and post-secondary samples, concentrations of somatic coliphage were higher than F-specific coliphage. In post-disinfection samples from two MBR plants (the third MBR plant had operational issues) and the ultraviolet conventional plant, concentrations for all bacterial indicators and coliphage were near or below detection; from the chlorine conventional plant, concentrations in post-disinfection samples were in the single or double digits. All of the plants met the National Pollutant Discharge Elimination System required effluent limits established for fecal coliforms. Norovirus GII and hepatitis A virus were not detected in any samples, and rotavirus was detected in one sample but could not be quantified. Adenovirus was found in 100 percent, enterovirus in over one-half, and norovirus GI in about one-half of post-preliminary wastewater samples. Adenovirus and enterovirus were detected throughout the treatment processes, and norovirus GI was detected less often than the other two enteric viruses. Culturable viruses were detected in post-preliminary samples and in only two post-treatment samples from the plant with operational issues.

Scientific Investigations Report↗

USGS2009

Results From a Microbial Source-Tracking Study at Villa Angela Beach, Cleveland, Ohio, 2007

During the 2007 recreational season at Villa Angela Beach in Cleveland, Ohio, scientists with the U.S. Geological Survey (USGS) and the Northeast Ohio Regional Sewer District (NEORSD) found high Escherichia coli (E. coli) concentrations that were not easily explained by results obtained to date in ongoing investigations of recreational water quality at the beach. To help understand the sources behind these elevated E. coli concentrations, the USGS and NEORSD sampled beach-area water for Bacteroides DNA markers. Bacteroides are a group of enteric bacteria that are being used in microbial source tracking, in hope that host-associated DNA markers could be used to indicate potential sources of E. coli in the Villa Angela environment. The USGS Ohio Water Microbiology Laboratory analyzed a total of 13 source samples (sewage and waterfowl feces) and 33 beach-area water and sand samples for three Bacteroides DNA markers. This report lists the results of those analyses, along with environmental conditions at Villa Angela on the dates that samples were collected.

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