Project description:Today, many contaminants of emerging concern can be measured in waters across the United States, including the tributaries of the Great Lakes. However, just because the chemicals can be measured does not mean that they necessarily result in harm to fish and other aquatic species. Complicating risk assessment in these waters is the fact that aquatic species are encountering the chemicals as mixtures, which may have additive or synergistic risks that cannot be calculated using single chemical hazard and concentration-response information. We developed an in vitro effects-based screening approach to help us predict potential liver toxicity and cancer in aquatic organisms using water from specific Great Lakes tributaries: St. Louis River (MN), Bad River (WI), Fox River (WI), Manitowoc River (WI), Milwaukee River (WI), Indiana Harbor Canal (IN), St. Joseph River (MI), Grand River (MI), Clinton River (MI), River Rouge (MI), Maumee River (OH), Vermilion River (OH), Cuyahoga River (OH), Genesee River (NY), and Oswego River (NY). We exposed HepG2 cells for 48hrs to medium spiked with either field collected water (final concentration of environmental samples in the exposure medium were 75% of the field-collected water samples) or purified water. Using a deep neural network we clustered our collection sites from each tributary based on water chemistry. We also performed high throughput transcriptomics on the RNA obtained from the HepG2 cells. We used the transcriptomics data with our Bayesian Inferene for Sustance and Chemical Toxicity (BISCT) Bayesian Network for Steatosis to predict the probability of the field samples yielding a gene expression pattern consistent with predicting steatosis as an outcome. Surprisingly, we found that the probability of steatosis did not correspond to the surface water chemistry clustering. Our analysis suggests that chemical signatures are not informative in predicting biological effects. Furthermore, recent reports published after we obtained our samples, suggest that chemical levels in the sediment may be more relevant for predicting potential biological effects in the fish species developing tumors in the Great Lakes basin.

Project description:We used gene expression accompanied by physical characteristics and gill Na+/K+-ATPase activity to analyze physiological differences associated with two life history variations of juvenile fall Chinook Salmon in the Snake River basin. Subyearlings originating in the Snake River typically migrate seaward as subyearlings, whereas many subyearlings from the Clearwater River delay seaward migration during summer and complete seaward migration the following spring as yearlings. We examined gill Na+/K+-ATPase activity and gene expression of subyearlings at different times during rearing and seaward emigration. Natural-origin Snake River subyearlings rearing under an increasing photoperiod and seasonally increasing temperatures showed a typical increasing pattern of parr to smolt gill Na+/K+-ATPase activity development, which then declined into autumn. In contrast, Clearwater River subyearlings that had experienced cooler temperatures showed no pattern of increasing gill Na+/K+-ATPase activities and were not different from parr. Liver transcription of genes involved in DNA repair and binding, the cell cycle, metabolism (steroid, fatty acid and other metabolic pathways) iron homeostasis, heme and oxygen binding, the immune response, and male sexual development were enriched amongst genes differentially expressed between Snake River parr versus smolts. Gene expression results confirmed that Clearwater River subyearlings were parr-like in their physiological status. By autumn, subyearlings had low gill Na+/K+-ATPase activities despite their large size and external smolt characteristics. We suggest that environmental factors like temperature and photoperiod influence subyearling physiological status in each river that ultimately dictates juvenile life history pathways. Non-migrating and migrating natural subyearling fall Chinook salmon were collected from the Snake River. Non-migrating natural subyearling fall Chinook salmon were collected from the Clearwater River. Twelve fish were collected at each of four different time points for a total of 48 fish. Total RNA was extracted from the liver of each fish. Equal amounts of RNA from three fish were pooled to create four pools of RNA per time point. Each RNA pool was hybridized to an array for a total of 16 arrays with four arrays per time point.

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