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Enhancing single-cell proteomics through tailored Data-Independent Acquisition and micropillar array-based chromatography

View ORCID ProfileValdemaras Petrosius, Pedro Aragon-Fernandez, View ORCID ProfileNil Üresin, View ORCID ProfileTeeradon Phlairaharn, View ORCID ProfileBenjamin Furtwängler, View ORCID ProfileJeff op de Beeck, View ORCID ProfileSimon Francis Thomsen, View ORCID ProfileUlrich auf dem Keller, View ORCID ProfileBo T. Porse, View ORCID ProfileErwin M. Schoof
doi: https://doi.org/10.1101/2022.11.29.518366
Valdemaras Petrosius
1Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs. Lyngby, Denmark
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Pedro Aragon-Fernandez
1Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs. Lyngby, Denmark
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Nil Üresin
1Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs. Lyngby, Denmark
2The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
3Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
4Novo Nordisk Foundation Center for Stem Cell Biology, DanStem, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
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Teeradon Phlairaharn
1Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs. Lyngby, Denmark
5The Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, Copenhagen 2200, Denmark; Department of Proteomics and Signal Transduction
6MaxPlanck Institute of Biochemistry, Martinsried 82152, Germany
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Benjamin Furtwängler
1Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs. Lyngby, Denmark
2The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
3Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
4Novo Nordisk Foundation Center for Stem Cell Biology, DanStem, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
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Jeff op de Beeck
7Thermo Fisher Scientific, Technologiepark-Zwijnaarde 82, B-9052 Gent, Belgium
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Simon Francis Thomsen
8Department of Dermatology, Bispebjerg Hospital and Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
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Ulrich auf dem Keller
1Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs. Lyngby, Denmark
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Bo T. Porse
2The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
3Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark
4Novo Nordisk Foundation Center for Stem Cell Biology, DanStem, Faculty of Health Sciences, University of Copenhagen, Copenhagen, Denmark
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Erwin M. Schoof
1Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 224 2800 Kgs. Lyngby, Denmark
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  • For correspondence: erws@dtu.dk
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Abstract

Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, mass spectrometry-based single-cell proteomics (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carried out comprehensive analysis of orbitrap-based data independent acquisition (DIA) for limited material proteomics. Notably, we found a fundamental difference between optimal DIA methods for high- and low-load samples. We further improved our low-input DIA method by relying on high-resolution MS1 quantification, thus more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we were able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we establish a complete experimental scp-MS workflow, combining DIA with accessible single-cell sample preparation and the latest chromatographic and computational advances and showcase our developments by profiling real single cells.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted November 30, 2022.
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Enhancing single-cell proteomics through tailored Data-Independent Acquisition and micropillar array-based chromatography
Valdemaras Petrosius, Pedro Aragon-Fernandez, Nil Üresin, Teeradon Phlairaharn, Benjamin Furtwängler, Jeff op de Beeck, Simon Francis Thomsen, Ulrich auf dem Keller, Bo T. Porse, Erwin M. Schoof
bioRxiv 2022.11.29.518366; doi: https://doi.org/10.1101/2022.11.29.518366
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Enhancing single-cell proteomics through tailored Data-Independent Acquisition and micropillar array-based chromatography
Valdemaras Petrosius, Pedro Aragon-Fernandez, Nil Üresin, Teeradon Phlairaharn, Benjamin Furtwängler, Jeff op de Beeck, Simon Francis Thomsen, Ulrich auf dem Keller, Bo T. Porse, Erwin M. Schoof
bioRxiv 2022.11.29.518366; doi: https://doi.org/10.1101/2022.11.29.518366

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