High-altitude environments present unique physiological challenges, paramount of which is chronic hypoxia. Populations who have resided at high elevation for millennia, including Tibetans and Andeans, show unique genetic adaptations to this environmental pressure. Most of our understandings of human high-altitude adaptation stem from studies of autosomal DNA. However, mitochondria with their independent mitochondrial genome, switch from aerobic respiration to glycolysis in hypoxia. Therefore, evolutionary adaptation to hypoxia also may have proceeded by evolutionary change to the mitochondrial genome. This study investigates differences in mitochondrial DNA (mtDNA) single nucleotide polymorphisms (SNPs) between high-altitude and low-altitude populations to identify potential signatures of positive selection. Using population genetic analyses, including fixation index (FST) and Population Branch Statistic (PBS), we compared allele frequency distributions across multiple populations. The results revealed SNPs with significant differentiation at several mtDNA loci, particularly within genes involved in oxidative phosphorylation, such as MT-ND, MT-CO, and MT-ATP complexes. These findings suggest that selection has shaped mtDNA variation to optimize cellular energy production in hypoxic environments. Overall, this study provides insight into the role of mitochondrial genetic variation in human adaptation to extreme environments and contributes to a broader understanding of evolutionary responses to environmental stressors.

Aging is a major risk factor for many of the leading causes of death, and this process also involves changes to the epigenome. Transient induction of transcription factors Oct4, Sox2, Klf4, and c-Myc(OSKM), so-called partial reprogramming, has been shown in vivo in mice to rejuvenate age-related biological function and reverse epigenetic markers. However, it remains unclear to what extent the changes in DNA methylation(DNAm) induced by OSKM overlap with the changes during aging, and how OSKM induced these changes. Here, we investigate how OSKM-induced partial reprogramming alters age-associated DNAm changes. Specifically, we aim to understand which age-related DNAm changes are reversed and which remain unchanged by measuring and comparing the DNAm changes between young mice, old mice, and OSKM old mice using Enzymatic Methyl-Seq. This work aims to clarify the scope of global DNAm remodeling during partial reprogramming.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the fastest-growing cause of liver cancer in the United States, affecting nearly 25% of the global population, yet effective therapies remain scarce. A key contributor to liver injury in MAFLD is the relationship between excessive hepatic progenitor cell (HPC) proliferation and increased fibrosis. One candidate for HPC growth mediation is ascorbate supplementation, given its role as a reducing agent in tumor suppression. Additionally, previous research identified dietary impacted ascorbate levels impacting HPC growth. This project investigated how ascorbate impacts HPCs and what implications this could have for managing MAFLD. HPC organoids derived from mouse livers were cultured in ascorbate and qPCR, and bulk RNA sequencing assays were performed. Results demonstrated robust downregulation of stemness marker Lgr5, signifying a role of ascorbate in affecting Wnt signaling within these organoids. Additionally, sequencing revealed differentially expressed genes between ascorbate and control conditions. Although preliminary data, these findings highlight mechanistic changes induced by ascorbate on HPCs and suggest a possibility for its therapeutic use. We will further examine these mechanisms by the extent of cell death versus growth arrest through Caspase 9 screening, as well as looking into connections in vivo. Understanding how ascorbate mitigates HPC growth in MAFLD could lead to accessible interventions for the millions of people struggling with MAFLD today.

T cell therapies are vital to anti-tumor efficacy and are successful in hematologic malignancies. However, largely due to hypoxic and metabolically restrictive tumor microenvironments, solid tumors inhibit T cell therapies through impairing metabolism, infiltration, and persistence, necessitating strategies to enhance metabolic resilience without compromising effector activity. Here, we present an integrated computational and synthetic biology framework to identify and engineer pathways that promote hypoxia resistance in Jurkat T cell models. Using a published genome-wide CRISPR/Cas9 deletion screen defining gene essentiality under hypoxia, we calculated gene-level fitness under hypoxic conditions and performed Gene Ontology enrichment to derive pathway-level features. We applied Elastic Net, ridge regression, and random forest models with bootstrap resampling to identify pathways consistently associated with improved cellular fitness. Across models, Receptor Tyrosine Kinase signaling, Metabolism of RNA, and Cytokine Signaling in the Immune System emerged as robust predictors of hypoxia resilience. Based on these results, we are working to overexpress PPARGC1A and upregulate heparanase, hoping to improve mitochondrial biogenesis and extracellular matrix degradation via TP53 loss-of-function. This machine learning–guided pathway elucidates genetic targets that could enhance T cell persistence in hypoxic environments through coupling bioinformatics-driven target identification with functional cellular reprogramming.

This abstract has been withheld from publication.