Data-Independent Acquisition Shortens the Analytical Window of Single-Cell Proteomics to Fifteen Minutes in Capillary Electrophoresis Mass Spectrometry
Separation in single-cell mass spectrometry (MS) improves molecular coverage and quantification; however, it also elongates measurements, thus limiting analytical throughput to study large populations of cells. Here, we advance the speed of bottom-up proteomics by capillary electrophoresis (CE) high-resolution mass spectrometry (MS) for single-cell proteomics. We adjust the applied electrophoresis potential to readily control the duration of electrophoresis. On the HeLa proteome standard, shorter separation times curbed proteome detection using data-dependent acquisition (DDA) but not data-independent acquisition (DIA) on an Orbitrap analyzer. This DIA method identified 1161 proteins vs 401 proteins by the reference DDA within a 15 min effective separation from single HeLa-cell-equivalent (∼200 pg) proteome digests. Label-free quantification found these exclusively DIA-identified proteins in the lower domain of the concentration range, revealing sensitivity improvement. The approach also significantly advanced the reproducibility of quantification, where ∼76% of the DIA-quantified proteins had <20% coefficient of variation vs ∼43% by DDA. As a proof of principle, the method allowed us to quantify 1242 proteins in subcellular niches in a single, neural-tissue fated cell in the live <i>Xenopus laevis</i> (frog) embryo, including many canonical components of organelles. DIA integration enhanced throughput by ∼2-4 fold and sensitivity by a factor of ∼3 in single-cell (subcellular) CE-MS proteomics.
Authors
- Péter Nemes (ORCID: https://orcid.org/0000-0002-4704-4997)
- Bo‐Wen Shen (ORCID: https://orcid.org/0000-0003-0750-0625)
- Leena R. Pade (ORCID: https://orcid.org/0000-0003-4081-3535)
Institutions
- University of Maryland, College Park (US)
Publication Details
- Journal
- Journal of Proteome Research
- Published
- 2024-09-26
- DOI
- https://doi.org/10.1021/acs.jproteome.4c00491
- Citations
- 11
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 2.65
Funders
- Arnold and Mabel Beckman Foundation
- University of Maryland
- National Institute of General Medical Sciences