TY - JOUR AU - NENENG, Liswara AU - NUGROHO, Rudy Agung AU - KOMAI, Yukio AU - TAKAYAMA, Naru AU - KAWAMURA, Koji PY - 2019/07/22 Y2 - 2024/03/29 TI - Water Quality Measurements with a Simple Molecular Analysis (PCR-RFLP) of the Microbiome in a Metropolitan River System in Japan JF - Walailak Journal of Science and Technology (WJST) JA - Walailak J Sci & Tech VL - 17 IS - 3 SE - Research Article DO - 10.48048/wjst.2020.5869 UR - https://wjst.wu.ac.th/index.php/wjst/article/view/5869 SP - 257-268 AB - <p>Urbanization has affected natural freshwater environments by contamination with sewage, toxic chemicals, and excess nutrients, which cause algal bloom, pollution, and ecosystem degradation. To ensure sustainable use of natural waters, appropriate monitoring methods are required. This study aims to investigate the diversity of the microbial community in a metropolitan river system in Japan using a low-cost DNA-based approach, PCR (Polymerase Chain Reaction)-RFLP (Restriction Fragment Length Polymorphism), as a potential bioindicator of environmental change. Surface waters were sampled in seven sites in a river system. Water chemical parameters and concentrations of heavy metals were determined. Microbial DNA was extracted from the samples, ribosomal RNA was amplified with universal primers, and RFLP was scored by agarose gels. Water chemical analyses showed that surface water at the inflow point of a sewage treatment plant had signs of eutrophication. Heavy metal concentrations in surface water were low (&lt; 0.01 ppm) in all sites. The PCR-RFLP analysis showed polymorphisms both in 16S and 18S rRNAs, indicating that the method can detect at least a part of the microbiome changes in a river system. Sequencing of some fragments found the sequence close to a ciliate isolated in wastewater treatment plants, implying contamination from sewage. Principal component analysis (PCA) identified the RFLPs associated with chemical water parameters, which could be bioindicators of environmental pollution. We also found the RFLPs independent of water quality parameters, suggesting that this simple DNA-based analysis can also detect biological changes in water ecosystems that are not quantified by chemical measurements of water quality.</p> ER -