Fecal indicator bacteria (FIB), commonly used to regulate sanitary water quality, cannot discriminate among sources of contamination. The use of alternative quantitative PCR (qPCR) methods for monitoring fecal contamination or microbial source tracking requires an understanding of relationships with cultivated FIB, as contamination ages under various conditions in the environment. In this study, the decay rates of three Bacteroidales 16S rRNA gene markers (AllBac for general contamination and qHF183 and BacHum for human-associated contamination) were compared with the decay rate of cultivated Escherichia coli in river water microcosms spiked with human wastewater. The following five sets of microcosms were monitored over 11 days: control, artificial sunlight, sediment exposure, reduced temperature, and no autochthonous predation. Decay was characterized by estimation of the time needed to produce a 2-log reduction ( t ₉₉ ). No treatment-associated differences in the decay of the 4 targets were evident except with reduced predation, where E. coli , qHF183, and BacHum markers had lower levels of decay by day 3. However, there were substantial target-associated differences. Decay curves for the AllBac marker indicated a larger persistent population than those of the other targets. Exposure to sunlight, sediment, and reduced predation resulted in more rapid decay of the human-associated markers relative to cultivable E. coli , but there were no differences in t ₉₉ values among the 4 targets under control conditions or at reduced temperatures. Further evaluation of epidemiological relationships will be needed in order to relate the markers directly to health risk. These findings suggest that the tested human-associated markers can complement E. coli as indicators of the human impact on sanitary water quality under the constrained conditions described in this paper.

Cyanotoxins occur in rivers worldwide but are understudied in lotic ecosystems relative to lakes and reservoirs. We sampled 11 large river sites located throughout the United States during June–September 2017 to determine the occurrence of cyanobacteria with known cyanotoxin-producing strains, cyanotoxin synthetase genes, and cyanotoxins. Chlorophyll a concentrations ranged from oligotrophic to eutrophic (0.5–64.4 µg L⁻¹). Cyanobacteria were present in the algal communities of all rivers (82% of samples, n = 50) but rarely dominated the phytoplankton (0–52% of total abundance; mean = 8.8%). Pseudanabaena and Planktothrix occurred most often, and many (64%) of the cyanobacterial genera identified (n = 25) have known cyanotoxin-producing strains. Cyanotoxin synthetase genes occurred in all but one river. The mcyE and sxtA genes were most common, present in 73% of rivers and 44% and 40% of samples, respectively. The cyrA gene was less common (22% of samples) but occurred in 64% of rivers. The anaC gene was detected in one river (4% of samples). Anatoxin-a and microcystins were detected at low levels (0.10–0.38 µg L⁻¹) in 2 midcontinent rivers. Cylindrospermopsins and saxitoxins were not detected. Cyanobacteria, cyanotoxin synthetase genes, and cyanotoxins were present at low concentrations throughout this subset of US rivers. Eutrophic rivers located in the midcontinent region of the United States had the highest algal biomass, abundance of cyanotoxin synthetase genes, and cyanotoxin occurrence.

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.

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.