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Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications

Author

Listed:
  • Claudia Ctortecka

    (Broad Institute of MIT and Harvard)

  • Natalie M. Clark

    (Broad Institute of MIT and Harvard)

  • Brian W. Boyle

    (Broad Institute of MIT and Harvard)

  • Anjali Seth

    (Cellenion SASU)

  • D. R. Mani

    (Broad Institute of MIT and Harvard)

  • Namrata D. Udeshi

    (Broad Institute of MIT and Harvard)

  • Steven A. Carr

    (Broad Institute of MIT and Harvard)

Abstract

The recent technological and computational advances in mass spectrometry-based single-cell proteomics have pushed the boundaries of sensitivity and throughput. However, reproducible quantification of thousands of proteins within a single cell remains challenging. To address some of those limitations, we present a dedicated sample preparation chip, the proteoCHIP EVO 96 that directly interfaces with the Evosep One. This, in combination with the Bruker timsTOF demonstrates double the identifications without manual sample handling and the newest generation timsTOF Ultra identifies up to 4000 with an average of 3500 protein groups per single HEK-293T without a carrier or match-between runs. Our workflow spans 4 orders of magnitude, identifies over 50 E3 ubiquitin-protein ligases, and profiles key regulatory proteins upon small molecule stimulation. This study demonstrates that the proteoCHIP EVO 96-based sample preparation with the timsTOF Ultra provides sufficient proteome depth to study complex biology beyond cell-type classifications.

Suggested Citation

  • Claudia Ctortecka & Natalie M. Clark & Brian W. Boyle & Anjali Seth & D. R. Mani & Namrata D. Udeshi & Steven A. Carr, 2024. "Automated single-cell proteomics providing sufficient proteome depth to study complex biology beyond cell type classifications," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49651-w
    DOI: 10.1038/s41467-024-49651-w
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    1. Zilu Ye & Pierre Sabatier & Javier Martin-Gonzalez & Akihiro Eguchi & Maico Lechner & Ole Østergaard & Jingsheng Xie & Yuan Guo & Lesley Schultz & Rafaela Truffer & Dorte B. Bekker-Jensen & Nicolai Ba, 2024. "One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Erwin M. Schoof & Benjamin Furtwängler & Nil Üresin & Nicolas Rapin & Simonas Savickas & Coline Gentil & Eric Lechman & Ulrich auf dem Keller & John E. Dick & Bo T. Porse, 2021. "Quantitative single-cell proteomics as a tool to characterize cellular hierarchies," Nature Communications, Nature, vol. 12(1), pages 1-15, December.
    3. Sarah Djebali & Carrie A. Davis & Angelika Merkel & Alex Dobin & Timo Lassmann & Ali Mortazavi & Andrea Tanzer & Julien Lagarde & Wei Lin & Felix Schlesinger & Chenghai Xue & Georgi K. Marinov & Jaina, 2012. "Landscape of transcription in human cells," Nature, Nature, vol. 489(7414), pages 101-108, September.
    4. Orit Rozenblatt-Rosen & Michael J. T. Stubbington & Aviv Regev & Sarah A. Teichmann, 2017. "The Human Cell Atlas: from vision to reality," Nature, Nature, vol. 550(7677), pages 451-453, October.
    5. Ruedi Aebersold & Matthias Mann, 2016. "Mass-spectrometric exploration of proteome structure and function," Nature, Nature, vol. 537(7620), pages 347-355, September.
    6. Valdemaras Petrosius & Pedro Aragon-Fernandez & Nil Üresin & Gergo Kovacs & Teeradon Phlairaharn & Benjamin Furtwängler & Jeff Op De Beeck & Sarah L. Skovbakke & Steffen Goletz & Simon Francis Thomsen, 2023. "Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
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