Project description:The copper redhorse (Moxostoma hubbsi) is an endangered fish endemic to Quebec, Canada that is only known to spawn in two locations within the Richelieu River, a waterway draining a significant area of agricultural land. Accordingly, concerns have been raised over the impacts that agricultural pesticide contamination of spawning grounds and nursery habitats within the Richelieu River may have on early life stage copper redhorse. We assessed the effects of contaminants on early life stages of copper redhorse and river redhorse (Moxostoma carinatum), a closely related fish that shares the copper redhorse’s habitat and spawning grounds but is distributed more widely and is not yet listed as endangered. Copper and river redhorse embryos (1000 each) were exposed to either Richelieu River water in an in-situ flow-through system or to laboratory water used as a control. We assessed embryos hatching time, incidence of deformities and survival in copper and river redhorses. We then performed RNA sequencing on copper redhorse larvae to better understand changes due to river water exposure. We identified 341 compounds in the river water that were absent from lab water. Pesticide concentrations in the river peaked following rainfall during the spawning season. Embryos exposed to river water hatched prematurely at 63.0 and 59.2 cumulative degree days (CDD) compared to 65.4 and 69.9 CDD in laboratory water for river and copper redhorse, respectively. Copper redhorse exposed to river water also had a significantly lower survival rate than laboratory water (73% vs. 93%). RNA sequencing of copper redhorse revealed 18 differentially expressed genes (DEGs) following river water exposure. Eight of the upregulated DEGs (cd44, il1b, lamb3, lamc2, tgm5, orm1, saa, acod1) are linked to immune function and injury response and 7 of the downregulated DEGs (cpa2, ctrb, cela2a, ctrl, cpa1, prss1, cel) are involved with digestion and nutrient absorption. This study provided valuable data on the effects of anthropogenic contaminants present in the Richelieu River and increased our knowledge on the individual and mixture effects they have on an endangered fish.

Project description:The delta smelt (Hypomesus transpacificus) is a pelagic fish species endemic to the Sacramento-San Joaquin Estuary in Northern California, listed as endangered under both the USA Federal and Californian State Endangered Species Acts and acts as an indicator of ecosystem health in its habitat range. Interrogative tools are required to successfully monitor effects of contaminants upon the delta smelt, and to research potential causes of population decline in this species. We used microarray technology to investigate genome-wide effects in 47-day old larvae after a 7-day exposure to ambient water samples from the Sacramento River at a monitoring field station (Hood) situated 8 miles downstream of the Sacramento regional Wastewater Treatment Plant. Genomic assessments were carried out on surviving organisms and contrasted to laboratory controls. Microarray assessments were conducted on larvae exposed for 7-days to Sacramento River water collected at Hood and pooled laboratory controls. Assessments were carried out in quadruplicate, using 3 fish per treatment. RNA was extracted from frozen whole, individual organisms, using Trizol Reagent (Invitrogen) as per manufacturer's guidelines. Total RNA from 5 fish was pooled per treatment and cDNA was synthesized from a total of 2ug total RNA, amplified using a SuperScripttm Indirect RNA Amplification System (Invitrogen). Resulting aRNA was labeled with Alexa fluor dyes (Invitrogen) as per manufacturerM-bM-^@M-^Ys instructions. Two color microarray assessments were carried out on quadruplicate treatments, using 5M-BM-5g of aRNA for pooled controls vs exposed sample, (total 4 samples). Microarray hybridizations were performed manually, and incubated in a waterbath at 42C for 16 hours. Slides were scanned using a GenePix 4000B scanner (Axon Instruments). Data was analyzed using LIMMA GUI (Linear model for microarray analysis graphical user interface) (Smyth, 2005), written in the R-programming language available through Bioconductor http://www.Bioconductor.org. Data was normalized within using print-tip Lowess and between arrays applying average intensity quantile (Aquantile) normalization methods with background correction (Smyth, 2005). A linear model fit was computed using the duplicates on the arrays and the least-squares method, with Benjamin Hochberg false discovery rate adjustment.

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Lake water metagenome

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