Abstract

Single Cell Proteomics (SCP) is an emerging discipline that contributes to a deeper understanding of individual cells' essential components. In biological systems, individual cells exhibit remarkable diversity, showcasing distinct proteomic profiles and functions. Mass Spectrometry (MS)-based techniques have become essential tools for exploring the proteomes of single cells with remarkable precision. While traditional bulk proteomics methods have been invaluable in revealing the overall protein composition of biological samples, they fall short in capturing the subtle nuances and heterogeneity among individual cells in a population. This limitation emphasizes the need for more targeted and detailed analyses to uncover the protein makeup of single cells. The MS-Based Single-Cell Proteomics technology serves as a valuable solution, providing comprehensive insight at the cellular level by analyzing proteins for identity, abundance, post-translational modifications, and interactions. This dissertation focuses on advancing single-cell proteomics through method development to enhance sensitivity and throughput. It presents a detailed protocol for a label-free single-cell proteomics workflow that integrates the cost-effective HP D100 Single Cell Dispenser and a one-hour, one-step sample preparation method. In contrast to the standard data-dependent acquisition method, the novel wide window acquisition (WWA) intentionally co-isolates and co-fragments adjacent precursors along with the selected precursor, using large isolation windows. Optimized WWA significantly increased the number of MS2-identified proteins by ≈40% compared to standard data-dependent acquisition. In a 40-minute LC gradient at ≈15 nL/min, an average of 3000 proteins per single HeLa cell was identified. Employing this platform, we compared protein expression in individual HeLa cells where the crucial autophagy gene, atg9a, was knocked out, and contrasted it with their isogenic wild-type parental line. To enhance throughput and robustness while preserving superior sensitivity at ultra-low flow rates, we developed an improved multi-column nanoLC system. This system features accelerated offline gradient generation, multiple storage sample loops with selective elution profiles, and allows for analysis as fast as every 20 minutes at 40 nL/min with close to 100% MS utilization time. Moreover, it enables continuous operation for up to 6 months without the need for column replacement. When applied to single-cell Multiple Myeloma treated with lenalidomide, this workflow identified an average of around 1300 unique protein groups.

Degree

PhD

College and Department

Computational, Mathematical, and Physical Sciences; Chemistry and Biochemistry

Rights

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

Date Submitted

2023-12-11

Document Type

Dissertation

Handle

http://hdl.lib.byu.edu/1877/etd13506

Keywords

label-free, bottom-up mass spectrometry, single-cell proteomics, sample preparation, multi-column, ultra-low flow nanoLC

Language

english

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