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

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Thielert,  Marvin
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;
IMPRS-ML: Martinsried, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons292619

Itang,  Ericka C. M.
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;
IMPRS-ML: Martinsried, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons273054

Ammar,  Constantin
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons292643

Rosenberger,  Florian A.
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons247346

Bludau,  Isabell
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons247786

Schweizer,  Lisa
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;
IMPRS-ML: Martinsried, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons291638

Nordmann,  Thierry M.
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons281940

Skowronek,  Patricia
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;
IMPRS-ML: Martinsried, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons284696

Wahle,  Maria
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;
IMPRS-ML: Martinsried, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons265701

Zeng,  Wen-Feng
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons284698

Zhou,  Xie-Xuan
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Brunner,  Andreas-David
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

/persons/resource/persons195396

Steger,  Martin
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

Mann,  Matthias
Mann, Matthias / Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Max Planck Society;

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Zitation

Thielert, M., Itang, E. C. M., Ammar, C., Rosenberger, F. A., Bludau, I., Schweizer, L., et al. (2023). Robust dimethyl-based multiplex-DIA doubles single-cell proteome depth via a reference channel. Molecular Systems Biology, 19(9): e1150. doi:10.15252/msb.202211503.


Zitierlink: https://hdl.handle.net/21.11116/0000-000D-C121-3
Zusammenfassung
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. 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.