Spatial and Temporal Dynamics of Microbial Community Composition of Recreational Water

Session: 01. - Disease, Parasites, and Pathogens of the Great Lakes and Freshwater Ecosystems

Abdolrazagh Hashemi Shahraki, Great Lakes Institute for Environmental Research (GLIER), University of Windsor, [email protected]
Subba Rao Chaganti, University of Windsor, [email protected]
Daniel Heath, Great Leaks Environmental Research Institute, University of Windsor, Windsor, Ontario, Canada, [email protected]

Abstract

Based on current knowledge, we have an incomplete view of aquatic microbial community composition, dynamics and their co-occurrence in stressed aquatic environments such as the Great Lakes and their associated recreational waters. Four public beaches located in Lake Erie and Lake St Clair were sampled weekly from June 2016 to September 2017 (15 months. Water samples were filtered, and then environmental DNA was extracted.  We metabarcoded the microbial community using the V5-V6 regions of the 16S rRNA gene and the ION Torrent PGM Next Generation sequencing platform. At phyla level, Actinobacteria, Bacteroidetes, and Proteobacteria were the phyla at all beaches; however, we observed substantial spatial variation of the microbial community composition across the public beaches at genus level. We also characterized temporal variation in community composition at weekly, monthly and seasonal levels and again detected significant temporal variation at each of the four public beaches. Within Proteobacteria, genera that include pathogenic species were common, for example, Acinetobacter followed by Pseudomonas were dominant at the Lake St. Clair beaches while at the Lake Erie beaches Staphylococcus, Acinetobacter, Legionella and Mycobacteria were the dominant genera with pathogen taxa. Our study shows strong spatial and temporal variation in microbial community composition in Great

1. Keyword
microbiological studies

2. Keyword
water quality

4. Additional Keyword
Microbial Community

5. Additional Keyword
Temporal Variation

6. Additional Keyword
Spatial Variation