MassIVE MSV000094795

Complete Public PXD052357

Benchmarking and automating the biotinylation proteomics workflow

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Description

While protein biotinylation has been widely used in biochemistry and biotechnology with various enrichment methods, different biotin enrichment strategies have not been systematically compared. Traditional biotinylation proteomics workflows suffer from complex sample preparation steps, non-specific bindings, limited throughput, and experimental variability. To address these critical challenges, we designed a two-proteome model, where yeast proteins were biotinylated in vitro and spiked in unlabeled human proteins, allowing us to distinguish true enrichment (yeast) from non-specific bindings (human) for comprehensively benchmarking of biotinylation proteomics methods. We also significantly optimized the entire workflow and reduced the sample preparation time from the traditional 3 days to just 9 hours, enabling a fully automated 96-well format sample processing for excellent reproducibility and throughput with minimized non-specific bindings. We then applied this optimized and automated workflow to proximity labeling proteomics and investigated the intricate interplay between mitochondria and lysosomes in living cells under both healthy state and mitochondrial damage. We demonstrated that mitochondrial damage led to an increased mitochondria-lysosome membrane contact and induced broad alternations in mitophagy-related proteins. We identified and quantified biotinylated proteins and precise amino acid residues at mitochondria-lysosome contact sites and within the mitophagy pathway, revealing an elevated level of interaction between mitochondria and lysosomes and proteome-wide remodeling in response to mitochondrial damage. [doi:10.25345/C5PN8XS37] [dataset license: CC0 1.0 Universal (CC0 1.0)]

Keywords: biotinylation ; proximity labeling ; HeLa cell

Contact

Principal Investigators:
(in alphabetical order) 		Ling Hao, The George Washington University, United States
Submitting User: haolab
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Distinct protein accessions are counted across all files submitted in the "Statistical Analysis of Quantified Analytes" category having a "Protein" column in this dataset.

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