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High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip

Author

Listed:
  • Jongmin Woo

    (Pacific Northwest National Laboratory)

  • Sarah M. Williams

    (Pacific Northwest National Laboratory)

  • Lye Meng Markillie

    (Pacific Northwest National Laboratory)

  • Song Feng

    (Pacific Northwest National Laboratory)

  • Chia-Feng Tsai

    (Pacific Northwest National Laboratory)

  • Victor Aguilera-Vazquez

    (Pacific Northwest National Laboratory)

  • Ryan L. Sontag

    (Pacific Northwest National Laboratory)

  • Ronald J. Moore

    (Pacific Northwest National Laboratory)

  • Dehong Hu

    (Pacific Northwest National Laboratory)

  • Hardeep S. Mehta

    (Pacific Northwest National Laboratory)

  • Joshua Cantlon-Bruce

    (Scienion AG
    Cellenion SASU)

  • Tao Liu

    (Pacific Northwest National Laboratory)

  • Joshua N. Adkins

    (Pacific Northwest National Laboratory)

  • Richard D. Smith

    (Pacific Northwest National Laboratory)

  • Geremy C. Clair

    (Pacific Northwest National Laboratory)

  • Ljiljana Pasa-Tolic

    (Pacific Northwest National Laboratory)

  • Ying Zhu

    (Pacific Northwest National Laboratory)

Abstract

Global quantification of protein abundances in single cells could provide direct information on cellular phenotypes and complement transcriptomics measurements. However, single-cell proteomics is still immature and confronts many technical challenges. Herein we describe a nested nanoPOTS (N2) chip to improve protein recovery, operation robustness, and processing throughput for isobaric-labeling-based scProteomics workflow. The N2 chip reduces reaction volume to 240 single cells on a single microchip. The tandem mass tag (TMT) pooling step is simplified by adding a microliter droplet on the nested nanowells to combine labeled single-cell samples. In the analysis of ~100 individual cells from three different cell lines, we demonstrate that the N2 chip-based scProteomics platform can robustly quantify ~1500 proteins and reveal membrane protein markers. Our analyses also reveal low protein abundance variations, suggesting the single-cell proteome profiles are highly stable for the cells cultured under identical conditions.

Suggested Citation

  • Jongmin Woo & Sarah M. Williams & Lye Meng Markillie & Song Feng & Chia-Feng Tsai & Victor Aguilera-Vazquez & Ryan L. Sontag & Ronald J. Moore & Dehong Hu & Hardeep S. Mehta & Joshua Cantlon-Bruce & T, 2021. "High-throughput and high-efficiency sample preparation for single-cell proteomics using a nested nanowell chip," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26514-2
    DOI: 10.1038/s41467-021-26514-2
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    References listed on IDEAS

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    1. 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.
    2. Ruedi Aebersold & Matthias Mann, 2016. "Mass-spectrometric exploration of proteome structure and function," Nature, Nature, vol. 537(7620), pages 347-355, September.
    3. Wenting Yang & Yuandong Tao & Yan Wu & Xinyuan Zhao & Weijie Ye & Dianyuan Zhao & Ling Fu & Caiping Tian & Jing Yang & Fuchu He & Li Tang, 2019. "Neutrophils promote the development of reparative macrophages mediated by ROS to orchestrate liver repair," Nature Communications, Nature, vol. 10(1), pages 1-14, December.
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    Cited by:

    1. Yu Wang & Zhi-Ying Guan & Shao-Wen Shi & Yi-Rong Jiang & Jie Zhang & Yi Yang & Qiong Wu & Jie Wu & Jian-Bo Chen & Wei-Xin Ying & Qin-Qin Xu & Qian-Xi Fan & Hui-Feng Wang & Li Zhou & Ling Wang & Jin Fa, 2024. "Pick-up single-cell proteomic analysis for quantifying up to 3000 proteins in a Mammalian cell," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. 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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