Engineering measurement tools to advance quantitative single-cell biology and pathogen inactivation
Skip to main content
eScholarship
Open Access Publications from the University of California

UC Berkeley

UC Berkeley Electronic Theses and Dissertations bannerUC Berkeley

Engineering measurement tools to advance quantitative single-cell biology and pathogen inactivation

Abstract

Quantitative measurement techniques are critical to new biological discoveries and reproducibility in science and medicine. Research advances are often driven by novel measurement capabilities or improvements in the sensitivity, specificity, or multiplexing of existing approaches. Improvements in throughput and precision can enable more accessible and accurate validation techniques to support reproducibility. Here, we introduce and optimize measurement approaches to advance two fields of quantitative biology: (1) single- and few-cell molecular profiling, and (2) germicidal ultraviolet-C (UV-C) pathogen inactivation. The measurement techniques developed here support research to understand the cellular heterogeneity driving development and disease, as well as safe and effective UV-C decontamination in clinical settings. First, we focus on advancing proteomic characterization of single cells with high specificity. Different proteoforms – different molecular forms of a protein arising from the same gene – often have unique roles in disease progression and other important biological processes. However, many assays cannot distinguish between proteoforms due to a lack of proteoform-specific antibodies. Electrophoretic cytometry increases proteoform specificity by using electrophoretic separations to spatially resolve proteoforms by mass or charge prior to antibody-based detection. To facilitate quantitative comparison of the ~100s of single-cell protein measurements which can be made on a single electrophoretic cytometry device, is it important to characterize and minimize measurement error. Here, we first investigate approaches to minimize and control for technical variation in both protein abundance and molecular mass measurements made by electrophoretic cytometry. We identify physicochemical mechanisms which contribute to intra-assay technical variation in protein immobilization and antibody binding within the electrophoretic sieving matrix, and use this fundamental understanding to develop strategies to improve the precision of single-cell protein abundance measurements. To improve the precision of molecular mass measurements, we develop protein-loaded microparticles which can be co-loaded with single-cells to act as a molecular mass ladder and control for technical variation in protein electromigration. Overall, these strategies allow finer biological differences in protein abundance and proteoform molecular mass to be distinguished. Next, we extend electrophoretic cytometry approaches to a range of biological sample types and incorporate multimodal detection capabilities. First, to support study of the roles of different proteoforms in mammalian development, we develop and apply an electrophoretic cytometry approach to characterize proteins expressed in single mouse embryos and blastomeres. To understand the relationship between protein expression and upstream nucleic acids (DNA, mRNA), we also develop an approach to fractionate a single cell or embryo and measure both cytoplasmic proteins and nuclear DNA or mRNA from the same single cell or embryo. While these platforms advance molecular profiling of detached cells in suspension, measurements of adherent cells are also valuable to understand spatial variation in protein expression and to understand cell-microenvironment interactions. To characterize proteoforms from adherent cells while preserving information about the starting cell locations, we investigate the use of projection electrophoresis to separate proteoforms in the Z-dimension while maintaining spatial context information in the X-Y plane. Because adherent cell projection electrophoresis has a different assay geometry and boundary conditions than traditional electrophoretic cytometry platforms in which detached cells are isolated and lysed within microwells, we compare the sensitivity and lateral spatial resolution of adherent cell and microwell-based projection electrophoresis platforms using simulation and fluorescent protein imaging. Informed by this characterization, we demonstrate a proof-of-concept projection electrophoretic separation of subconfluent adherent breast cancer cells. Overall, this work extends electrophoretic cytometry to new sample types and offers a new approach to couple nucleic acid and proteoform measurements from the same single or few cells. In addition to advancing techniques to measure biological samples directly, we also advance research and implementation of germicidal UV-C pathogen inactivation through the development of quantitative, high-throughput, and accessible UV-C dosimetry techniques. To address shortages induced by the COVID-19 pandemic, UV-C decontamination has been identified as a promising approach to decontaminate N95 respirators for emergency reuse. Both pathogen inactivation and N95 degradation depend on UV-C dose. However, it is challenging to measure UV-C dose on N95 surfaces, as radiometers and other standard UV-C dose measurement techniques have insufficiently small form factor, and often have nonideal angular response. Here, we develop a high-throughput quantitative UV-C dosimetry approach using colorimetric indicators, characterize the impact of optical attenuators on dosimeter dynamic range and angular response, and apply the dosimetry approach to make first-in-kind paired measurements of on-N95 UV-C dose and SARS-CoV-2 viral inactivation. Improved UV-C dose measurement techniques facilitate research of UV-C pathogen inactivation and validation of UV-C decontamination protocols. Taken together, the work covered in this dissertation advances the range and precision of measurements important to studying single-cell biology and pathogen inactivation, supporting a variety of research and clinical applications.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View