| Autor: |
Nshimyimana JP; School of Civil and Environmental Engineering, Nanyang Technological University (NTU) , 50 Nanyang Avenue, Singapore 639798, Singapore.; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT) , 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.; Centre for Environmental Sensing and Modeling (CENSAM), Singapore-MIT Alliance for Research and Technology (SMART) , 1 Create Way, Singapore 138602, Singapore.; Singapore Center on Environmental Life Sciences Engineering (SCELSE), NTU , 60 Nanyang Drive, Singapore 637551, Singapore., Freedman AJE; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT) , 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.; Centre for Environmental Sensing and Modeling (CENSAM), Singapore-MIT Alliance for Research and Technology (SMART) , 1 Create Way, Singapore 138602, Singapore., Shanahan P; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT) , 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.; Centre for Environmental Sensing and Modeling (CENSAM), Singapore-MIT Alliance for Research and Technology (SMART) , 1 Create Way, Singapore 138602, Singapore., Chua LCH; School of Engineering, Deakin University , Waurn Ponds, Geelong, Victoria 3216, Australia., Thompson JR; Department of Civil and Environmental Engineering, Massachusetts Institute of Technology (MIT) , 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.; Centre for Environmental Sensing and Modeling (CENSAM), Singapore-MIT Alliance for Research and Technology (SMART) , 1 Create Way, Singapore 138602, Singapore. |
| Abstrakt: |
A major challenge for assessment of water quality in tropical environments is the natural occurrence and potential growth of Fecal Indicator Bacteria (FIB). To gain a better understanding of the relationship between measured levels of FIB and the distribution of sewage-associated bacteria, including potential pathogens, in the tropics this study compared the abundance of FIB (Total coliforms and E. coli) and the Bacteroidales (HF183 marker) with bacterial community structure determined by next-generation amplicon sequencing. Water was sampled twice over 6 months from 18 sites within a tropical urban catchment and reservoir, followed by extraction of DNA from microorganisms, and sequencing targeting the V3-V4 region of the 16S rRNA gene. Multivariate statistical analyses indicated that bacterial community composition (BCC) varied between reservoir and catchment, within catchment land-uses, and with E. coli concentration. Beta-regression indicated that the proportion of sequences from sewage-associated taxa (SAT) or pathogen-like sequences (PLS) were predicted most significantly by measured levels of E. coli(log MPN/100 mL) (χ 2 > 8.7; p < 0.003). In addition, SAT were significantly predicted by log HF183 levels (χ 2 =13.1; p = 0.0003) while PLS were not. Our study suggests that measurements of E. coli concentration could be useful in predicting samples enriched in sewage-associated and pathogen-like bacteria in tropical environments despite the potential for nonconservative behavior. |
