Proteomics

Dataset Information

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A Universal 384-Well Proteomic Sample Preparation Platform for High-Throughput Screening and Biomarker Discovery


ABSTRACT: Major advances have been made to improve the sensitivity of mass analyzers, spectral quality, and the speed of data processing enabling more comprehensive proteome discovery and quantitation. While focus has recently begun shifting toward robust proteomic sample preparation efforts, a high throughput proteomics sample preparation is still lacking. We report the development of a highly-automated universal 384-well plate sample preparation platform with high reproducibility and adaptability for extraction of proteins from cells within a culture plate. Digestion efficiency was excellent in comparison to a commercial digest peptide standard with minimal sample loss while improving sample preparation throughput by 20- to 40-fold (<1 min/sample for entire process from cells to clean peptides). Analysis of six human cell types, which included two primary cell samples, identified and quantified approximately 4,000 proteins for each sample in a single HPLC-MS/MS injection with only 100 -10,000 cells, thus demonstrating universality of the platform.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture

SUBMITTER: Dingyin Tao  

LAB HEAD: Dingyin Tao

PROVIDER: PXD023374 | Pride | 2021-06-14

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
100_3D_1NeoKerat.raw Raw
100_3E_AC16.raw Raw
100_3F_1NeoKerat.raw Raw
100_3G_AC16.raw Raw
100_3H_1NeoKerat.raw Raw
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Major advances have been made to improve the sensitivity of mass analyzers, spectral quality, and speed of data processing enabling more comprehensive proteome discovery and quantitation. While focus has recently begun shifting toward robust proteomics sample preparation efforts, a high-throughput proteomics sample preparation is still lacking. We report the development of a highly automated universal 384-well plate sample preparation platform with high reproducibility and adaptability for extra  ...[more]

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