Several microbes and chemicals have been considered as potential tracers to identify fecal sources in the environment. However, to date, no one approach has been shown to accurately identify the origins of fecal pollution in aquatic environments. In this multilaboratory study, different microbial and chemical indicators were analyzed in order to distinguish human fecal sources from nonhuman fecal sources using wastewaters and slurries from diverse geographical areas within Europe. Twenty-six parameters, which were later combined to form derived variables for statistical analyses, were obtained by performing methods that were achievable in all the participant laboratories: enumeration of fecal coliform bacteria, enterococci, clostridia, somatic coliphages, F-specific RNA phages, bacteriophages infecting Bacteroides fragilis RYC2056 and Bacteroides thetaiotaomicron GA17, and total and sorbitol-fermenting bifidobacteria; genotyping of F-specific RNA phages; biochemical phenotyping of fecal coliform bacteria and enterococci using miniaturized tests; specific detection of Bifidobacterium adolescentis and Bifidobacterium dentium; and measurement of four fecal sterols. A number of potentially useful source indicators were detected (bacteriophages infecting B. thetaiotaomicron, certain genotypes of F-specific bacteriophages, sorbitol-fermenting bifidobacteria, 24-ethylcoprostanol, and epycoprostanol), although no one source identifier alone provided 100% correct classification of the fecal source. Subsequently, 38 variables (both single and derived) were defined from the measured microbial and chemical parameters in order to find the best subset of variables to develop predictive models using the lowest possible number of measured parameters. To this end, several statistical or machine learning methods were evaluated and provided two successful predictive models based on just two variables, giving 100% correct classification: the ratio of the densities of somatic coliphages and phages infecting Bacteroides thetaiotaomicron to the density of somatic coliphages and the ratio of the densities of fecal coliform bacteria and phages infecting Bacteroides thetaiotaomicron to the density of fecal coliform bacteria. Other models with high rates of correct classification were developed, but in these cases, higher numbers of variables were required.Determining the source of fecal contamination in aquatic environments is essential for estimating the health risks associated with pollution, facilitating measures to remediate polluted waterways, and resolving legal responsibility for remediation. Source tracking methods should enable investigators to uncover the sources of fecal pollution in a particular water body (40). Candidate microbes and chemicals have been investigated and reviewed (15,54,55) as potential tools for the identification of human fecal sources. More recently, new approaches using eukaryotic mitochondrial DNA to differentiate fecal sources in feces-contaminated surface waters have been explored (43). However, field ...
Microbial adhesion to hydrocarbons and microelectrophoresis were investigated in order to characterize the surface properties of Cryptosporidium parvum. Oocysts exhibited low removal rates by octane (only 20% on average), suggesting that the Cryptosporidium sp. does not demonstrate marked hydrophobic properties. A zeta potential close to ؊25 mV at pH 6 to 6.5 in deionized water was observed for the parasite. Measurements of hydrophobicity and zeta potential were performed as a function of pH and ionic strength or conductivity. Hydrophobicity maxima were observed at extreme pH values, with 40% of adhesion of oocysts to octane. It also appeared that ionic strength (estimated by conductivity) could influence the hydrophobic properties of oocysts. Cryptosporidium oocysts showed a pH-dependent surface charge, with zeta potentials becoming less negative as pH was reduced, starting at ؊35 mV for alkaline pH and reaching 0 at isoelectric points for pH 2.5. On the other hand, variation of surface charge with respect to conductivity of the suspension tested in this work was quite small. The knowledge of hydrophobic properties and surface charge of the parasite provides information useful in, for example, the choice of various flocculation treatments, membrane filters, and cleaning agents in connection with oocyst recovery.
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