A Multi-omic Study of Biota Responses to Great Lakes Sediment, Effluent and Surface Waters

Session: 15. - Environmental 'omics: New Tools for Aquatic Ecosystem Science and Management

Denina Simmons, University of Ontario Institute of Technology, [email protected]
Bernard Duncker, University of Waterloo, [email protected]
Jim Sherry, Environment Canada, [email protected]
Bharat Chandramouli, SGS AXYS, [email protected]
Heather Butler, SGS AXYS, [email protected]
John Cosgrove, SGS AXYS, [email protected]
Trudy Watson-Leung, Ontario Ministry of the Environment and Climate Change, [email protected]
Sonya Kleywegt, Ontario Ministry of Environment and Climate Change, [email protected]
Caren Helbing, University of Victoria, [email protected]

Abstract

Sediment, effluent and surface water samples were collected from various sites across Hamilton Harbour, Toronto Harbour, Humber Bay and Lake Erie between 2014 and 2015. Hexagenia sp. and Rainbow Trout were exposed to these samples in the laboratory for 48 hours. Liver, plasma and fin tissue was collected from exposed and control Rainbow Trout while exposed and control Hexagenia were collected whole. Levels of 11 transcripts in Rainbow Trout and 7 in Hexagenia were measured. Shotgun proteomics data were generated for Rainbow Trout and Hexagenia. 219 metabolites including amino acids, lipids, bile acids, and fatty acids were quantified. A total of over 500 individual contaminants and water quality indicators were measured in the effluent, surface water and sediment samples. Results showed distinct signatures by exposure type. Metabolomics data in Hexagenia exposed to sediment from Hamilton Harbour sites with high persistent organic pollutant concentrations showed 60 metabolites differing significantly between sites and correlating with contaminant levels. Two transcripts also showed statistically significant differences between these sites. 101 Hexagenia proteins had significantly different levels following exposure to Hamilton Harbour effluent samples. It is expected that the combination of omic results will have higher differentiating power than data from a single endpoint measurement.

1. Keyword
Lake Ontario

2. Keyword
Hamilton Harbour

3. Keyword
pollution sources

4. Additional Keyword
Toronto Harbour

5. Additional Keyword
Multi-Omic

6. Additional Keyword
Multi-species