(2du) Bridging Biological Sequence and Molecular Function for Precision Diagnostics and Therapeutics

Research Interests
Chronic diseases impact an individual’s quality of life and burden the United States healthcare system, costing over $1 trillion annually. Despite the clinical understanding that these conditions often implicate the interconnected functioning of multiple organs, the underlying molecular and genetic changes that are occurring between these organs and driving pathology remain largely unknown, thereby stymying our ability to understand and treat these conditions.

My research program will develop technology to treat, diagnose, and manage high-burden chronic diseases.

The unifying objective of my research vision is to study the human body’s response to specific chronic diseases by integrating molecular measurements and a systems-level view. My laboratory’s research will couple measurements from high-throughput omics and various techniques from molecular biology with methodologies from machine learning and data science. With this approach, my research group will both define a comprehensive landscape of interconnected organ functioning at the molecular and genetic level and develop technology addressing unmet clinical needs.

Research Experience
My graduate research with Professor Stephen Quake intersected the fields of liquid biopsy and single cell transcriptomics. A liquid biopsy offers a comprehensive window into the health and functioning of organs throughout the body; however, current state-of-the-art assays merely indicate sick/healthy phenotypes. Separately, hundreds of single cell datasets are produced each year, facilitating unprecedented insights into the transcriptional heterogeneity driving complex biological systems. Despite the rich information captured by these datasets, their application for clinical insights remains limited. My doctoral research bridged this gap: I demonstrated that liquid biopsies measuring cell-free RNA (cfRNA) are decomposable at cell-type resolution using single cell transcriptomics and that specific cell types implicated in numerous diseases are noninvasively measurable [1]. These methods were then applied to a liquid biopsy for early prediction of preeclampsia, a serious pregnancy complication that can damage multiple organs throughout the body, to noninvasively resolve organ-specific cell types and their changes over gestation [2]. Following my work demonstrating that cell type of origin resolution in health and disease is achievable in a cfRNA assay, I built a novel liquid biopsy and demonstrate that this assay facilitates the direct measurement of the health and functioning of tissues at cell type resolution with poor representation in a traditional cell-free RNA liquid biopsy [3].

Teaching Interests
My teaching objectives are to equip students with a strong foundation of the underlying physical principles governing a given system and to train them to independently identify and solve important problems. At Stanford, I was a teaching assistant for two courses offered for the first time: the first term of a newly developed, two-part undergraduate thermodynamics series and a first-time course covering foundational biology for engineers. From writing problem sets, giving a lecture, or holding recitations, I worked to teach course material effectively while instilling problem solving methodology in my students. In the laboratory, I have mentored two undergraduate students, both of whom have contributed as co-authors on manuscripts. I served as a mentor for undergraduate and graduate students, including for first-year Chemical Engineering graduate students, the Stanford Society for Women Engineers, the Stanford Undergraduate Research Association, and first years in Stanford ChEM-H CBI. Beyond the classroom and laboratory, I am passionate about applying my scientific background and teaching skills for accessible education of the public on scientific problems impacting society at-large. I have been involved in antimicrobial drug policy advocacy, and I wrote an op-ed published in STAT News, a national news source for health and biotech.

As a classically trained chemical engineer, I am prepared to teach any core Chemical Engineering course at the undergraduate or graduate level. I am particularly interested in teaching courses interfacing chemical engineering with machine learning or data science, either in augmenting existing coursework or developing a new course, Data mining for scientific problem choice and decision making.

Selected Awards
MIT Chemical Engineering Rising Stars, 2022
Centennial TA Award, Stanford University 2021
Outstanding Teaching Assistant Award, Stanford Department of Chemical Engineering 2021
Stanford ChEM-H Predoctoral Training Program at the Chemistry/Biology Interface, 2018
National Science Foundation Graduate Research Fellowship, 2018
Stanford Graduate Fellowship, 2018
Alfred L. Goldberg Fellowship, Cold Spring Harbor Laboratory 2016

Selected Publications
[1] Vorperian, S. K., Moufarrej, M. N., & Quake, S. R. (2022). Cell types of origin of the cell-free transcriptome. Nature Biotechnology, 1-7.

[2] Moufarrej, M. N., Vorperian, S. K., Wong, R. J., Campos, A. A., Quaintance, C. C., Sit, R. V., Tan, M., Detweiler, A.M., Mekonen, H., Neff, N.F., Baruch-Gravett C., Litch, J.A., Druzin, M.L., Winn, V.D., Shaw, G.M., Stevenson, D.K., Quake, S. R. (2022). Early prediction of preeclampsia in pregnancy with cell-free RNA. Nature, 1-6.

[3] Vorperian, S.K., Buonomo, J.A., Gray, I., Chinchinian, H.J., Yu, B., Yan, R., La, V., Lee, T., Mach, K., DeFelice, B., Loeb, G., Lafayette, R., Meyer, T., Leong, J., Bertozzi, C.R., Quake, S.R. (2023). In preparation.