Whole-Cell Fatty Acid Composition of Total Coliforms to Predict Sources of Fecal Contamination |
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Authors: | Berat Z. Haznedaro?lu Daniel H. Zitomer George B. Hughes-Strange Metin Duran |
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Affiliation: | 1Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Villanova Univ., Villanova, PA 19085. E-mail: berat.haznedaroglu@villanova.edu 2Associate Professor, Dept. of Civil and Environmental Engineering, Marquette Univ., Milwaukee, WI 53201. E-mail: daniel.zitomer@marquette.edu 3Undergraduate Student, Washington Univ. in St. Louis, Dept. of Chemistry, St. Louis, MO 63130. E-mail: gbhughes@artsci.wustl.edu 4Assistant Professor, Dept. of Civil and Environmental Engineering, Villanova Univ., Villanova, PA 19085. (corresponding author). E-mail: metin.duran@villanova.edu
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Abstract: | The objective of this study was to test the hypothesis that total coliforms isolated from human and nonhuman sources have distinctly different whole-cell fatty acid methyl ester (FAME) profiles. The FAME profiles studied included total coliforms isolated from sewage; feces of livestock, including bovine (dairy cattle), poultry, and swine; and feces of wildlife, including waterfowl and deer. Multiple samples within each category were collected and 303 total coliform isolates were cultured. It was found that the FAMEs 12:0 2OH and 14:0 2OH were exclusively associated with sewage samples, whereas the FAMEs 18:0 and 19:0 ISO were identified only in isolates from the livestock samples. In addition to the presence of signature FAMEs, the average relative masses of 16:1 ω7c, 18:1 ω7c, and 19:0 CYCLO ω8c were significantly different between human and nonhuman sources of total coliforms. A linear discriminant function based on these differences discriminated total coliform isolates of human origin against the other five host categories at a 77% rate of correct classification (RCC). These results strongly support the validity of our hypothesis and suggest that the FAME profiles of total coliforms have the potential to be used as a phenotypic microbial source tracking (MST) tool for predicting the sources of microbial contamination in water environments. |
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Keywords: | Microbes Pathogens Public health Sewage Contamination |
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