Bacteria can inherit genes through two modes of transmission: vertical inheritance, in which a cell receives genes from its parent cell during division, or horizontal gene transfer, in which genes are passed laterally between two unrelated cells. Extrachromosomal DNA, called plasmids, can be transmitted from a bacterial cell to a neighboring cell of the same or different species through a form of horizontal gene transfer known as conjugation. These conjugative plasmids can encode for antibiotic resistance genes which allows a host cell to produce proteins that degrade antibiotics. In an environment with these drugs, a host cell with this plasmid would be more likely to survive, compared to a plasmid-free cell, due to the benefits of the antibiotic resistance gene. Additionally, these antibiotic resistance genes can often acquire mutations which increases the level of antibiotic resistance for the host cell. However, these acquired mutations may be more beneficial (i.e., higher resistance for the host cell) in one bacterial species than the same mutation in another species. In other words, the effect of mutation on the plasmid-encoded antibiotic resistance gene may be contingent upon the host species. Given that antibiotic resistance genes are often encoded on conjugative plasmids that are shared among species, my project is investigating how protein evolution may be affected due to plasmid genes existing in multiple bacterial hosts. I performed a series of competitions between three bacterial species containing plasmids with versions of an antibiotic resistance gene to determine which versions of the gene outcompete others in an environment containing antibiotics. In doing so, I can determine how this particular gene may evolve when various bacterial hosts exist in a microbial community. The results of this experiment will improve our understanding of plasmid biology and the evolution of antibiotic resistance genes in diverse communities of bacteria.

Methylotuvimicrobium buryatense 5GB1C is a methane-oxidizing bacterium with significant potential for metabolic engineering to divert methane waste and create valuable biomolecules. In order to engineer this organism’s metabolism, however, more must be understood about the grammar of its genetic regulation. M. buryatense encodes two methanol dehydrogenase enzymes. MxaF uses calcium as a cofactor while the other, XoxF, can use a number of lanthanide metals as its cofactor. In order for this species to regulate its metabolism, mxaF and other associated genes are downregulated in the presence of lanthanide metals. We hypothesize that regulatory proteins must exist that bind to promoter region sequences of such genes and respond to the presence of lanthanide metals. With the program MEME, we identified possible binding site consensus sequences within the promoter regions of up to five genes that are downregulated in the presence of lanthanum. After identifying candidate sequences, we created plasmids linking the promoter regions of three lanthanum-repressed genes to xylE, a reporter gene. We then mutated these genetic constructs, separately creating multiple point mutations in each proposed regulatory site in order to disrupt their consensus motifs. These genetic constructs were mated into M. buryatense 5GB1C for insertion into its chromosome. Reporter gene assays were performed to compare the relative expressions of xylE linked to wild type and mutant promoter sequences in the presence or absence of lanthanum. We anticipate these mutant promoters will lead to altered gene expression in either the presence or absence of lanthanum, indicating that these sites are required for gene activation or repression. The results will inform metabolic engineering strategies to modify how a gene is expressed in this interesting and promising organism. Future steps will involve pairing these mutants with mutated regulatory proteins to further elucidate transcriptional mechanisms.

Memory has been widely studied for its crucial role in learning and its diverse range of expression. Although the means of acquisition differ, it is generally accepted that memory goes through three encoding stages: sensory, short-term and long-term memory. The retention of memory is important as it enables us to act with the wisdom of past experience. However, although one could not survive without memory, remembering everything is also devastating. In fact, forgetting is an important cognitive feature that allows us to adapt to the constantly changing environments. Despite its importance for cognition, little is known about the molecular nature of forgetting. Here, we investigated the genes behind forgetting by studying an olfactory memory in the nematode C. elegans. Like human, worms can modify their behavior upon acquiring unpleasant experience – their movement towards preferred odor is significantly reduced after prolonged exposure to the odor during starvation. Upon returning to food (e. coli OP50), the odor attraction slowly returns to the worms within 3-4 hours, indicating a diminishing impact of the starvation experience. By contrast, the forgetting process was significantly accelerated by 1-2 hours, when worms were cultivated on pathogenic bacteria, pseudomonas aeruginosa PA14. Our genetic studies showed that a null mutation to the daf-16 gene restored recovery time to 3-4 hours, despite of the exposure to PA14. These data indicate that daf-16 plays a positive role in accelerated memory loss upon pathogen ingestion. Because DAF-16 is involved in innate immunity and stress response, our results provide a potential connection that couples the memory to environmental stressors.

Calcific Aortic Valve Disease (CAVD) is progressive osteogenic changes including calcium deposition and thickening of the aortic valve causing stiffness which impairs normal function ultimately leading to ventricular hypertrophy and death. Runx2, a transcription factor involved in osteogenic changes, has been observed to be upregulated in the diseased valves. RNA sequencing data from the lab had previously revealed several genes regulated in a Runx2 knock out mouse model of CAVD. This study aims to determine if NKX2.5, one of the genes identified in the RNA sequencing data, is an upstream regulator of Runx2. Baboon valve interstitial cells (BVICs), which can be induced to calcify and share characteristics similar to human valve cells, were used in CRISPR knockout experiments to determine molecular and biochemical changes following NKX2.5 deletion. CRISPR-Cas9 is an effective method of gene deletion that uses programmable guide RNA to induce a gene mutation, inactivating its protein product. Initial experiments were aimed at optimizing the conditions for electroporation and gRNA delivery to ensure BVIC survival and efficient gene deletion in the cell line. Gene deletion success was determined by sequencing a ~1kb region around the deletion site. After generating BVIC lacking NKX2.5, cells were cultured in media known to induce calcification. A biochemical assay indicated changes in activation. Cells were assessed for calcification changes using biochemical assay, changes in activation, and Runx2 expression determined via RT-qPCR. We expect to confirm that NKX2.5 negatively regulates Runx2 and in turn calcification.

Previous research has shown the ability of Apo2 Ligand/TNF-Related Apoptosis Inducing Ligand (Apo2L/TRAIL) of inducing apoptosis in cancer cells without causing adverse effects on normal cells. However, clinical trials have shown that TRAIL resistance poses as a significant obstacle to anticancer drugs. Further optimizing the TRAIL apoptotic pathway through investigating the oligomerization and activation of TRAIL receptors may be a strategy towards success in cancer therapy. In this research, de novo designed protein nanocages exhibiting antibodies against the TRAIL receptor DR5 (AMG655) were synthesized by the Institute for Protein Design (IPD). We have shown that the nanocages induced significant activation of caspase 8 and caspase-3 in renal carcinoma TRAIL resistant cells, but not in healthy primary kidney tubular cells. Furthermore, our preliminary data from western blots indicate that the nanocages significantly decreased pro-survival cFLIP and pAkt in RCC4 cells. We are now investigating the mechanistic effects of the nanocages on other pathways, such as NF-kB, MAPK, autophagy and necroptosis. In addition, we are generating DR5 knockouts cancer cells using CRISPR/Cas9 to study the specificity of the nanocages. As a whole, this work will be a valuable contribution towards enhancing TRAIL pro-apoptotic signaling through TRAIL receptor engagement with novel protein designs.

Human pluripotent stem cells (hPSCs) are cells capable of self-renewal while differentiating into any cell type in the body. The differentiation into skeletal muscle progenitor cells (SMPCs), results in mature skeletal muscle cells. As the potential of deriving SMPCs from hPSCs has been further researched for medical application, the problem encountered is how to generate fully functional skeletal muscle cells from hPSCs experimentally. Currently, there are many existing protocols (e.g., HX, JC, MS Protocols) for such differentiation, known as myogenesis, but each has problems that need to overcome (e.g., time-consuming, not fully functional cells, resulted in other cell types). Our goal is to figure out what genes and metabolites are involved in the natural process of differentiation (from prenatal skeletal muscle progenitors to satellite cells) and apply the knowledge experimentally. To address this, we present the use of computational methods for the biological network-based integration of transcriptomic and metabolomic data. By analyzing data for both in vivo process and in vitro protocol results, we can find potential genes and metabolites differences, relating from the transcriptomic level to metabolomic level, revealing the inadequacy in the experimental protocols, presenting probable genes to improve the results. This involves RNA sequencing data analysis (e.g., single-cell, microarray) of human and mouse cells from embryonic to postnatal stages, with Seurat (pseudo-time analysis), Monocle, and AFFY, which processes/analyzes the data revealing potential genes. Then further analysis with UKIN, guided network propagation, to rank and identify the most probable genes, and perturb-Met to analyze metabolites involved. This is a time and cost-efficient way to find most probable genes directing the differentiation, which can then be tested and verified experimentally. If successful, it can be further developed into potential treatments much more effective and efficient than available medications and technologies for presently incurable musculoskeletal diseases.