Abstract

Single-Cell Proteomics (SCP) can provide unique insights into biological processes by resolving heterogeneity that is obscured by bulk measurements. Gains in the overall sensitivity and proteome coverage through improvements in sample processing and analysis increase the information content obtained from each cell, particularly for less abundant proteins. In addition to achieving in-depth proteome coverage from single cells, higher throughput measurements enable large-scale and statistically significant features within single cell populations. This dissertation focuses on method development to improve the sensitivity and throughput of SCP based on the nanoPOTS (nanodroplet Processing in One pot for Trace Samples) platform. The methods discussed here include miniaturization of bottom-up proteome sample preparation and liquid chromatography (LC) separations, implementation of an ultrasensitive latest-generation mass spectrometer, development of automated sample handling workflow, and combination of isotopic and isobaric labeling for higher order multiplexing. The miniaturization of sample preparation largely reduced protein loss during sample preparation and enabled in-depth single-cell proteomics. The sensitivity was further improved using a 20-μm-i.d. in-house-packed nanoLC column and the latest generation Orbitrap Eclipse Tribrid mass spectrometer. A >70% increase in proteome coverage was observed for single cells relative to previous efforts using a 30-μm-i.d. LC columns coupled to a previous-generation Orbitrap Fusion Lumos mass spectrometer. To make SCP and low-input proteome profiling accessible to more proteomics laboratories, a fully automated platform termed autoPOTS (automated Preparation in One pot for Trace Samples) was developed using only commercially available instrumentation for sample processing and analysis. AutoPOTS can be used to analyze 1–500 cells with a modest reduction in peptide coverage for 150 cells and a 24% reduction in coverage for single cells compared to the nanoliter preparation. To improve the throughput of SCP, a hyperplexing sample preparation and analysis method for Single-Cell Proteomics (hyperSCP) was developed using a combination of isotopic and isobaric labeling. This method can improve the throughput by at least 28 times with the same gradient compared to the label-free proteomics and can double or triple the throughput of standard tandem mass tag multiplexing.

Degree

PhD

College and Department

Physical and Mathematical Sciences; Chemistry and Biochemistry

Rights

https://lib.byu.edu/about/copyright/