Exposure to 17a ethinyl-estradiol (EE2), an endocrine-disrupting compound found commonly in birth control and the environment, impacts both development and reproduction in fish. Although it has been established to also cause aneuploidy in those exposed, the effect of EE2 on disease resistance is not well understood. This study uses the zebrafish model to address the effect of EE2 on fish health. Embryos will have been exposed to three concentrations of EE2 (1, 10, 50 ng/L) and a vehicle control from 10-72 hrs post fertilization. At 72 hrs, embryos will have been infected with Edwardsiella ictaluri (gram negative pathogen of fish) and monitored for differential mortality. In addition, the host immune response (via induction of immune genes) is assessed on day two and three post infection using quantitative RT-PCR. Quantitative RT-PCR is a method where RNA is transcribed to cDNA using reverse transcriptase and then is then used as a template for the PCR reaction. Specifically, we will have assessed the regulation of serum amyloid A1 (SAA1-acute phase response) and the proinflammatory gene interleukin 1 b (IL1B). From previous experiments and test runs, these two genes are expected to be upregulated after the exposure to EE2 and the subsequent infection. Overall, this study addresses the hypothesis that exposure to endocrine disrupting compounds can lead to increased disease susceptibility in fish at the individual and population level.

With 9.5 million new cases of active disease annually and 30% of the world latently infected, tuberculosis (TB) disease is a public health crisis on a massive scale. Despite decades of research, treatment options are still suboptimal, with standard drug regimens ranging from 6-12 months for drug-susceptible cases and up to 24 months in instances of drug resistance. Detection of drug resistance is essential to getting patients the appropriate treatment regimen, but the diagnosis of resistance can take 4-6 weeks using standard culturing approaches. Current TB research is often done with “batch culture” techniques, which are tests done on millions to billions of bacteria and the average response is used to make inferences about individual bacteria. While useful, batch culturing contributes to the lengthy diagnosis of drug resistance and is at odds with the clinical course of TB infections, where such numbers of bacteria are seen in only the most extreme cases of disease. To address this limitation we developed a platform to watch and track single cells responding to a variety of environments. Our platform features a semi-solid growth substrate, brightfield and fluorescent microscopy, and the ability to faithfully track  single cells for more than 5 days. Using our platform we tested TB susceptibility to isoniazid, a common first line TB drug. Benchmarking against batch culture, we found the killing dose of isoniazid to be comparable with our platform; however, unexpectedly, we found that sublethal doses of drug have the opposite effect: they increase bacterial growth rates. In addition to impacting knowledge about the basic biology of TB, our platform has the potential to evolve into a diagnostic test for drug resistance, with the ability to identify drug resistant strains of TB in <4 days.