Water pollution is a serious problem that not only threatens wildlife, but also the health and safety of human populations around the world. While the commonly held perception is that water pollution only affects vulnerable groups in developing countries, the 2014 water crisis in Flint, Michigan is a stark reminder that even developed nations are not impervious. Given the scope and weight of this problem, there has yet to be an accurate and affordable way to reliably test for heavy metals and other water-soluble contaminants. Current solutions such as handheld digital instruments can be expensive and require calibration and electricity, making them less practical in low-resource settings. Test strips, while deployable, are often inaccurate. Hence, our aim is to create an inexpensive, deployable yeast-based diagnostic tool that can detect various water pollutants with high sensitivity and report results with a fluorescent or color output. At the beginning stages of our project, we are using Next-Generation RNA Sequencing and experimenting with various analysis techniques to screen for genes in Saccharomyces cerevisiae that exhibit a unique and differential expression profile after exposure to a particular contaminant. For now, we are limiting the scope of our research to zinc, copper sulfate and caffeine because there are existing gene sets in literature for us to reference, but as more data are acquired, we hope to apply this pipeline to a wider range of chemical pollutants, including pesticides, toxins and hormones.