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Tools to minimize interlaboratory variability in vitellogenin gene expression monitoring programs
Citation:
Jastrow, A., D. Gordon, K. Auger, E. Punska, K. Arcaro, K. Keteles, D. Winkleman, D. Lattier, A. Biales, AND Jim Lazorchak. Tools to minimize interlaboratory variability in vitellogenin gene expression monitoring programs. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, 36(11):3102-3107, (2017). https://doi.org/10.1002/etc.3885
Impact/Purpose:
This manuscript is an interlab study on QPCR methods for detection of estrogen exposures using fathead minnows and gene expression. It demonstrates that the gene expression method for Vtg is very robust and can be reliable when the same samples are measured by various laboratories using different equipment and kits.
Description:
The egg yolk precursor protein vitellogenin is widely used as a biomarker of estrogen exposure in male fish. However, standardized methodology is lacking and little is known regarding the reproducibility of results among laboratories using different equipment, reagents, protocols, and employing different analysts. To address this data gap we developed a standard operating procedure (SOP) to evaluate vitellogenin gene (vtg) expression across multiple laboratories. We applied the SOP to samples from three concurrent studies of male fathead minnows (Pimephales promelas) exposed to 17α-ethinylestradiol (EE2) and minnows exposed to processed wastewater effluent and evaluated variability in gene expression among four laboratories. Our results indicate remarkable consistency among laboratories with three of four detecting vtg in fish exposed to 5 ng/L EE2 (n = 5). All laboratories significantly detected vtg in male fish exposed to wastewater effluent (n = 15). Finally, the source of high inter-laboratory variability was the expression analysis software unique to each real-time quantitative polymerase chain reaction (qPCR) machine. We eliminated this variability by analyzing the raw fluorescence data exported from each machine with independent freeware. This yielded cycle thresholds and PCR efficiencies that were not biased by proprietary software. Our results suggest that laboratories wishing to engage in collaborative monitoring programs can maintain current PCR protocols and simply analyze their gene expression data following the guidelines established herein.
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DOI: Tools to minimize interlaboratory variability in vitellogenin gene expression monitoring programs
PubMed Central Version: PMC5894818