Recent development of high throughput single cell methods has expanded our understanding of tissue heterogeneity, cell states, and developmental biology. Current single cell methods aim to understand cell function and phenotype by measuring a variety of cell features, like DNA sequence, mRNA abundance, chromatin accessibility, cell surface proteins, and histone modifications. However, cell phenotypes are regulated by a number of factors that escape the abundance measurements of current single

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... ll methods. To directly measure cell phenotypes, I developed a method to measure enzyme activities in single cells. To this end, I designed DNA repair substrates that can be used to measure strand incision events catalyzed by endogenous DNA repair enzymes and called the method "Haircut". Haircut semi-quantitatively measures base excision repair and ribonucleotide excision repair and has been adapted to work simultaneously in a single cell mRNA sequencing experiment. Using Haircut, I measured mRNA expression and DNA repair activities in primary human immune cells and found differences in several DNA repair enzyme activities between immune cell types. Some of the repair activity measurements were supported by mRNA abundance measurements in those cell types. While other activities, especially those catalyzed by multimeric proteins, did not correlate with gene expression measurements. Additionally, I used Haircut to measure mRNA expression and DNA repair heterogeneity in immune cells from a preliminary cohort of individuals with trisomy 21 and found no differences in DNA repair between individuals with trisomy 21 and individuals with disomy 21. iv In summary, I developed a platform to measure enzymatic activities in single cells. I used Haircut to measure known and previously unknown differences in DNA repair across immune cell types. The platform I developed can be modified to measure other enzymatic activities and mRNA expression in thousands of single cells and can be expanded further to measure many enzymatic activities in millions of cells. Cell phenotypes are regulated by many complex mechanisms and are difficult to predict using DNA sequence or gene expression alone. Single cell analysis of biochemical phenotypes has the potential to bridge the gap between gene expression and cell function and provide direct functional readouts where other single cell methods cannot. The form and content of this abstract are approved. I recommend its publication. Approved: Jay R. Hesselberth v DEDICATION To Eric for the daily love, support, laughs, and adventures and to Josh for making the roadmap for me to follow vi ACKNOWLEDGEMENTS It truly takes a village and I will do my best to thank all those who have helped and guided me during this time. First and foremost, I thank my advisor, Jay Hesselberth. I admire Jay's broad scientific curiosity and innovative approach to science. The possibility of working with Jay was one the reasons I attended to the University of Colorado Anschutz. I am grateful to have had the opportunity to work with and learn from Jay. Jay taught me to approach innovation through an "it's going to work" attitude that was extremely helpful in navigating the doctoral training process. I want to thank my committee members, Heide Ford, Josh Black, James DeGregori, Katerina Kechris, and Aaron Johnson for their continued feedback and thoughtful questions. The Hesselberth lab has been a wonderful place to work and I am grateful for the enthusiasm, humor, wisdom, and hard work that the lab embodies. My forever rotation buddy Laura White has been a constant presence during my graduate career. I admire Laura's pure curiosity-driven approach to science and her thoughtful approach to graduate school. I hope to someday have the work ethic of Rachel Ancar. Rachel single-handedly juggles several projects, clinicals, and committee duties with enthusiasm and determination. I want to express my extreme fondness and gratitude to both Laura and Rachel. I am grateful for their comradery through the highs and lows of graduate school and I could not have asked for a better set of classmates and labmates. Shannon Walsh has been an invaluable teacher in the lab. I am thankful to have benefited from her expertise. Several of the ideas in this thesis have been reduced to practice by her and I would like to explicitly thank her for the precision medicine figure. Shannon has been a wonderful bay-mate and I appreciated her tolerance for my many interrupting questions throughout the day. Patrick Cherry's methodical and detailed approach to science was an inspiration and I hope I absorbed some of his attention to detail. It would be remiss of me to not recognize Monica Ransom. vii Monica Ransom is responsible for all of my training in next-generation sequencing and I am appreciative for all her teachings. Thank you to the "guys downstairs" who have patiently answered any and all my analysis questions. I especially want to thank Kent Riemondy for his contributions to the scrunchy software package and the DNA repair paper.