Publication | Open Access
An Optimized Shotgun Strategy for the Rapid Generation of Comprehensive Human Proteomes
541
Citations
62
References
2017
Year
The study investigates how to comprehensively catalog the complete human proteome from a single cell type using mass spectrometry‑based shotgun proteomics. The authors modified a classical two‑dimensional high‑resolution reversed‑phase peptide fractionation scheme and optimized the protocol to provide sufficient peak capacity to saturate the sequencing speed of modern mass spectrometers. The optimized strategy achieved the deepest proteome of a human single‑cell type to date, sequencing ~584,000 unique peptides and ~14,200 protein isoforms (~12,200 protein‑coding genes), matching next‑generation RNA sequencing depth, enabling identification of ~7,000 N‑acetylation and ~10,000 phosphorylation sites without enrichment, and demonstrating general applicability and clinical potential by quantifying global proteomes in various cancer cell lines and patient tissues.
This study investigates the challenge of comprehensively cataloging the complete human proteome from a single-cell type using mass spectrometry (MS)-based shotgun proteomics. We modify a classical two-dimensional high-resolution reversed-phase peptide fractionation scheme and optimize a protocol that provides sufficient peak capacity to saturate the sequencing speed of modern MS instruments. This strategy enables the deepest proteome of a human single-cell type to date, with the HeLa proteome sequenced to a depth of ∼584,000 unique peptide sequences and ∼14,200 protein isoforms (∼12,200 protein-coding genes). This depth is comparable with next-generation RNA sequencing and enables the identification of post-translational modifications, including ∼7,000 N-acetylation sites and ∼10,000 phosphorylation sites, without the need for enrichment. We further demonstrate the general applicability and clinical potential of this proteomics strategy by comprehensively quantifying global proteome expression in several different human cancer cell lines and patient tissue samples.
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