Gaining Wings to FLY: Using Drosophila Oogenesis as an Entry Point for Citizen Scientists in Laboratory Research.

Citizen science is a productive approach to include non-scientists in research efforts that impact particular issues or communities. In most cases, scientists at advanced career stages design high-quality, exciting projects that enable citizen contribution, a crowdsourcing process that drives discovery forward and engages communities. The challenges of having citizens design their own research with no or limited training and providing access to laboratory tools, reagents, and supplies have limited citizen science efforts. This leaves the incredible life experiences and immersion of citizens in communities that experience health disparities out of the research equation, thus hampering efforts to address community health needs with a full picture of the challenges that must be addressed. Here, we present a robust and reproducible approach that engages participants from Grade 5 through adult in research focused on defining how diet impacts disease signaling. We leverage the powerful genetics, cell biology, and biochemistry of Drosophila oogenesis to define how nutrients impact phenotypes associated with genetic mutants that are implicated in cancer and diabetes. Participants lead the project design and execution, flipping the top-down hierarchy of the prevailing scientific culture to co-create research projects and infuse the research with cultural and community relevance.

Functional analysis of rare variants in mismatch repair proteins augments results from computation-based predictive methods.

The cancer-predisposing Lynch Syndrome (LS) arises from germline mutations in DNA mismatch repair (MMR) genes, predominantly MLH1, MSH2, MSH6, and PMS2. A major challenge for clinical diagnosis of LS is the frequent identification of variants of uncertain significance (VUS) in these genes, as it is often difficult to determine variant pathogenicity, particularly for missense variants. Generic programs such as SIFT and PolyPhen-2, and MMR gene-specific programs such as PON-MMR and MAPP-MMR, are often used to predict deleterious or neutral effects of VUS in MMR genes. We evaluated the performance of multiple predictive programs in the context of functional biologic data for 15 VUS in MLH1, MSH2, and PMS2. Using cell line models, we characterized VUS predicted to range from neutral to pathogenic on mRNA and protein expression, basal cellular viability, viability following treatment with a panel of DNA-damaging agents, and functionality in DNA damage response (DDR) signaling, benchmarking to wild-type MMR proteins. Our results suggest that the MMR gene-specific classifiers do not always align with the experimental phenotypes related to DDR. Our study highlights the importance of complementary experimental and computational assessment to develop future predictors for the assessment of VUS.