Locusts are generalist herbivores meaning that they are able to consume a variety of plants. Because of their broad diet, and ability to respond rapidly to a favorable environment with giant swarms of voracious insects, they are dangerous pests. Their potential impacts on humans increase dramatically when individuals switch from their solitarious phase to their gregarious phase where they congregate and begin marching and eventually swarming together. These swarms, often billions strong, can consume the vegetation of enormous swaths of land and can travel hundreds of kilometers in a single day producing a complex threat to food security. To better understand the biology of these important pests we explored the gut microbiome of the South American locust (Schistocerca cancellata). We hypothesized generally that the gut microbiome in this species would be critically important as has been shown in many other species. We extracted and homogenized entire guts from male S. cancellata, and then extracted gut microbiome genomic DNA. Genomic DNA was then confirmed on a gel. The initial extractions were of poor quality for sequencing, but subsequent extractions performed by collaborators during troubleshooting at Southern Illinois University Edwardsville proved more useful and were used for PCR. This resulted in the detections of the following bacterial genera in the gut of S. cancellata: Enterobacter, Enterococcus, Serratia, Pseudomonas, Actinobacter, and Weisella. With this data, we are able to speculate about the physiological roles that they hold within the locust gut generating hypotheses for further testing. Understanding the microbial composition of this species’ gut may help us better understand the locust in general in an effort to more sustainably manage them.

Over 40% of adults in the United States are considered obese. Obesity is known to cause abnormal metabolic effects and lead to other negative health consequences. Interestingly, differences in metabolism and contractile performance between obese and healthy weight individuals are associated with differences in skeletal muscle fiber type composition between these groups. Each fiber type is characterized by unique metabolic and contractile properties, which are largely determined by the myosin heavy chain isoform (MHC) or isoform combination that the fiber expresses. In previous studies, SDS-PAGE single fiber analysis has been utilized as a method to determine MHC isoform distribution and single fiber type distribution in skeletal muscle. Herein, a methodological approach to analyze MHC isoform and fiber type distribution in skeletal muscle was fine-tuned for use in human and rodent studies. In the future, this revised methodology will be implemented to evaluate the effects of obesity and exercise on the phenotypic fiber type composition of skeletal muscle.

In this project I explored the relationship between Qigong and Tai Chi Easy meditative practices and cardiometabolic risk factors, specifically looking at obesity and stress. The meditative focus of Qigong and Tai Chi Easy was expected to improve cardiac vagal tone which should lead to decreases in the inflammatory effects of stress. Additionally, due to the decreases in the harmful effects of stress, we expect to see a decrease in obesity through decreases in BMI and in waist circumference.

Glioblastoma (GB) is one of the deadliest cancers and the most common form of adult primary brain tumors. SGEF (ARHGEF26) has been previously shown to be overexpressed in GB tumors, play a role in cell invasion/migration, and increase temozolomide (TMZ) resistance.[3] It was hypothesized parental LN229 cell lines with SGEF knockdown (LN229-SGEFi) will show decreased metabolism in the MTS assay and decreased colony formation in a colony formation assay compared to parental LN229 cells after challenging the two cell lines with TMZ. For WB and co-immunoprecipitation (co-IP), parental LN229 cells with endogenous SGEF and BRCA were expected to interact and stain in the BRCA1:IP WB. LN229-SGEFi cells were expected to show very little SGEF precipitated due to shRNA targeted knockdown of SGEF. In conditions with mutations in the BRCA1 binding site (LN229-SGEFi + AdBRCAm/AdDM), SGEF expression was expected to decrease compared to parental LN229 or LN229-SGEFi cells reconstituted with WT SGEF (LN229-SGEFi + AdWT). LN229 infected with AdSGEF with a mutated nuclear localization signal (LN229-SGEFi + AdNLS12m) were expected to show BRCA and SGEF interaction since whole cell lysates were used for the co-IP. MTS data showed no significant differences in metabolism between the two cell lines at all three time points (3, 5, and 7 days). Western blot analysis was successful at imaging both SGEF and BRCA1 protein bands from whole cell lysate. The CFA showed no significant difference between cell lines after being challenged with 500uM TMZ. The co-IP immunoblot showed staining for BRCA1 and SGEF for all lysate samples, including unexpected lysates such as LN229-SGEFi, LN229-SGEFi + AdBRCAm, and LN229-SGEFi + AdDM. These results suggested either an indirect protein interaction between BRCA1 and SGEF, an additional BRCA binding site not included in the consensus, or possible detection of the translocated SGEF in knockdown cells lines since shRNA cannot enter the nucleus. Further optimization of CO-IP protocol, MTS assay, and CFA will be needed to characterize the SGEF/BRCA1 interaction and its role in cell survival.

Cancer rates vary between people, between cultures, and between tissue types, driven by clinically relevant distinctions in the risk factors that lead to different cancer types. Despite the importance of cancer location in human health, little is known about tissue-specific cancers in non-human animals. We can gain significant insight into how evolutionary history has shaped mechanisms of cancer suppression by examining how life history traits impact cancer susceptibility across species. Here, we perform multi-level analysis to test how species-level life history strategies are associated with differences in neoplasia prevalence, and apply this to mammary neoplasia within mammals. We propose that the same patterns of cancer prevalence that have been reported across species will be maintained at the tissue-specific level. We used a combination of factor analysis and phylogenetic regression on 13 life history traits across 90 mammalian species to determine the correlation between a life history trait and how it relates to mammary neoplasia prevalence. The factor analysis presented ways to calculate quantifiable underlying factors that contribute to covariance of entangled life history variables. A greater risk of mammary neoplasia was found to be correlated most significantly with shorter gestation length. With this analysis, a framework is provided for how different life history modalities can influence cancer vulnerability. Additionally, statistical methods developed for this project present a framework for future comparative oncology studies and have the potential for many diverse applications.