Metagenomics is the study of the structure and function of microbial communities through the application of the whole-genome shotgun (WGS) sequencing method. Providing high-resolution community profiles at species or even strain levels, metagenomics points to a new direction for microbiome research in understanding microbial gene function, microbial-microbial interactions, and host-microbe interactions. My thesis work includes innovation in metagenomic research through the application of ChatGPT in assisting beginning researchers, adopt pre-existed alpha diversity metric for metagenomic data to improve diversity calculation, and the application of metagenomic data in Alzheimer’s disease research.Since the release of ChatGPT in March 2023, the conversation regarding AI in research has promptly been debated. Through the prompted bioinformatic case study, I demonstrate the application of ChatGPT in conducting metagenomic analysis. I constructed and tested a working pipeline aimed at instructing GPT in completing shotgun metagenomic research. The pipeline includes instructions for various essential analytic steps: quality controls, host filtering, read classification, abundance estimation, diversity calculation, and data visualization. The pipeline demonstrated successful completion and reproducible results. Alpha diversity measurement is critical to understanding microbiomes. The widely used Faith’s phylogenetic diversity (PD) metric is agnostic of feature abundance and, therefore, falls short of analyzing metagenomic data. BWPDθ, an abundance weighted variant of Faith’s PD, was implemented in scikit-bio alpha diversity metrics. My analysis shows that BWPDθ does have better performance compared to Faith’s PD, revealing more biological significance, and maintaining their robustness at a lower sampling depth. The progression of Alzheimer’s disease (AD) is known to be associated with alterations in the patient’s gut microbiome. Utilizing metagenomic data from the AlzBiom study, I explored the differential abundance of bacterial pncA genes among healthy and AD participants by age group. The analysis showed that there was no significant difference in pncA abundance between the healthy and AD patients. However, when stratified by age group, within the age group 64 to 69, AD was shown to have significantly lower pncA abundance than the healthy control group. The Pearson's test showed a moderate positive association between age and pncA abundance.

Understanding why individuals vary in the onset and progression of aging-related diseases is important for developing interventions to extend healthy human lifespans. A possible mechanism underlying variation in aging and disease is increased somatic mutations with age. One result of somatic mutation, clonal hematopoiesis (CH), is the overrepresentation of blood cells originating from a single progenitor stem cell. When these clones become more frequent (≥4% of white blood cells), it is called “clonal hematopoiesis of indeterminate potential” (CHIP), which is associated with aging, pre-cancer, inflammation, and cardiovascular disease. Frequency of these mutations may also be predicted by facets of individuals’ environments, such as experiencing significant adverse life events, which have been linked to acceleration of other aspects of aging. We hypothesize that older individuals, particularly those that have experienced environmental adversity, will be more likely to have CH mutations. We also expect to see expansion of CHIP clones over time within individuals. We are testing these hypotheses in a population of free-ranging rhesus macaques, which have similar immune systems to humans and experience various types of environmental adversity. We have sequenced DNA from this population and are working to identify animals with CHIP. We plan to test whether demographic and environmental factors (i.e., adversity, sex) influence the development of CH driver mutations during aging, along with analyzing clonal dynamics and phenotypic effects in individuals with CHIP. Our findings will provide insight into the factors that influence CHIP development and progression, ultimately contributing to interventions to delay or prevent CHIP.

As the global population of people over 65 increases, so does the risk for developing dementia such as Alzheimer’s Disease. This neurodegenerative disease leads to severe cognitive decline and memory deficits as a result of dysregulation in neurons. While the symptoms of Alzheimer's are well-characterized, the mechanisms contributing to this disease pathology are not fully understood. In this study, I used rhesus macaques as models for age-related cognitive decline based on their similarities in brain structure with humans. The RNA sequencing data in this study came from four different types of glial cells in the entorhinal cortex of the brain: oligodendrocytes, microglia, astrocytes, and oligodendrocyte precursor cells (OPCs). I observed that glial cell classes exhibit sex differences in cell composition, with males generally displaying greater changes in cell composition with age than females. A greater number of differentially expressed genes were upregulated with age than were downregulated. Multiple genes in every glial cell class were directly related to neuronal function and maintenance. Generally, genes upregulated with age in these cells were related to synaptic signaling and neuron development. These findings showcase changes in glial cells that could potentially be linked to cellular pathways involved in Alzheimer’s pathogenesis. With a more robust understanding of how specific genes in these types of cells change with age, it could be possible to improve early disease detection methods.

Though researchers are working to correct it, a disparity exists in the knowledge of and treatment for cardiovascular disease, hypertension, and type II diabetes among the sexes. A disparity likewise arises in our understanding of the impact of sex hormones on disease between the sexes. This review article aims to explain the state of our knowledge on the impact of sex hormones on disease across the lifespan based on research published from 2018-2024.

Viruses are the most abundant biological entities on Earth, infecting all types of cellular organisms. Yet less than 1% of the virosphere on our planet has been characterized to date. Viruses are both an important driver of bacterial evolution and have significant implications for human health, therefore understanding the relative contributions of various evolutionary forces in shaping their genomic landscapes is of critical importance both mechanistically as well as clinically. In my thesis I use computational genomic approaches to gain novel insights into bacteriophage and human cytomegalovirus evolution. In my first two chapters and associated appendices I characterized the complete genomes of the Cluster P bacteriophage Phegasus and Cluster DR bacteriophage BiggityBass, whose isolation hosts were Mycobacterium smegmatis mc²155 and Gordonia terrae CAG3, respectively. I also determined the bacteriophages' phylogenetic placement and computationally inferred their putative host ranges. For my fourth chapter I assessed the performance of several of these computational host range prediction tools using a dataset of bacteriophages whose host ranges have been experimentally validated. Finally, in my fifth chapter I reviewed the key parameters for developing an evolutionary baseline model of another virus, human cytomegalovirus.

CrAssphages are a type of bacteriophage, a virus that infects bacteria and reproduces within them. They are thought to infect one of the most prevalent bacteria in the human gut microbiome, Bacteroides (Dutilh et al., 2014). CrAssphages are suspected to be in 73-77% of humans (Siranosian et al., 2020), however little is known about the effects they might have on the gut microbiome or the host organism’s digestion, metabolism, nutrition, or host immune function and disease states (Shreiner et al., 2015). CrAssphages were recently identified in gelada fecal samples from infants and adults. This study analyzed variables surrounding crAssphage presence in fecal samples collected throughout infant development and from adults and analyzed the presence of six crAssphages that were genetically similar to the proto-crAssphage originally discovered in humans (Dutilh et al., 2014). It was determined that recent rainfall has a significant effect on crAssphage presence. Additionally, recent rainfall and gelada sex have significant effects on the likelihood of infection by multiple crAssphages at once. The six crAssphages analyzed all peaked in presence between 10-20 months of age, while Bacteroides presence decreases at ~10 months (Baniel et al., 2022). It remains unsure if Bacteroides are the true host of crAssphages, or if there are other possible hosts.

It is well characterized that exposure to air pollutants is deleterious to human health. However, there is currently a gap in studying the effects of long term, low levels of exposure to pollution. The central objective of this study was to determine the effect(s) of environmental pollutants on health in the companion dog. This study used the vast Health and Life Experience Survey, Environment survey, Health Conditions survey, and Cancer Conditions survey from the Dog Aging Project as well as publicly available pollution data from the Environmental Protection Agency. These data along with a composite exposure measure, generated to accurately capture average exposure, were used to assess and model how exposure to environmental pollutants can affect reported health and disease. Overall, higher levels of exposure were found to be associated with a higher number of reported diseases. This study also included paired deoxyribonucleic acid (DNA) methylation data for a subset of dogs to investigate possible molecular mechanisms behind these observed associations. It was found that differential DNA methylation is not only associated with exposure to environmental pollutants but also that these changes mimic observed age-related changes. Due to companion dogs sharing their environment with humans, our findings may be applicable to human health. Continuing investigations into how poor air quality causes detrimental effects to health and disease will be especially valuable for more vulnerable populations.