Dataset Information

Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel

ABSTRACT: Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited in proteomic depth, throughput, and robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated and complete dimethyl labeling of bulk or single-cell samples, without losing proteomic depth. Lys-N digestion enables fiveplex quantification at MS1 and MS2 level. Because the multiplexed channels are quantitatively isolated from each other, mDIA accommodates a reference channel that does not interfere with the target channels. Our algorithm RefQuant takes advantage of this and confidently quantifies twice as many proteins per single cell compared to our previous work (Brunner et al, PMID 35226415), while our workflow currently allows routine analysis of 80 single cells per day. Finally, we combined mDIA with spatial proteomics to increase the throughput of Deep Visual Proteomics seven-fold for microdissection and four-fold for MS analysis. Applying this to primary cutaneous melanoma, we discovered proteomic signatures of cells within distinct tumor microenvironments, showcasing its potential for precision oncology.

INSTRUMENT(S): timsTOF, Orbitrap Exploris 480, timsTOF SCP

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Prof. Dr. Matthias Mann

PROVIDER: MSV000090956 | MassIVE | Thu Dec 22 06:11:00 GMT 2022

REPOSITORIES: MassIVE

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Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel.

Thielert Marvin M Itang Ericka Cm EC Ammar Constantin C Rosenberger Florian A FA Bludau Isabell I Schweizer Lisa L Nordmann Thierry M TM Skowronek Patricia P Wahle Maria M Zeng Wen-Feng WF Zhou Xie-Xuan XX Brunner Andreas-David AD Richter Sabrina S Levesque Mitchell P MP Theis Fabian J FJ Steger Martin M Mann Matthias M

Molecular systems biology 20230821 9

Single-cell proteomics aims to characterize biological function and heterogeneity at the level of proteins in an unbiased manner. It is currently limited in proteomic depth, throughput, and robustness, which we address here by a streamlined multiplexed workflow using data-independent acquisition (mDIA). We demonstrate automated and complete dimethyl labeling of bulk or single-cell samples, without losing proteomic depth. Lys-N digestion enables five-plex quantification at MS1 and MS2 level. Beca ...[more]

PMID: 37602975

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