Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition
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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, single-cell proteomics by Mass Spectrometry (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 carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
| Originalsprog | Engelsk |
|---|---|
| Artikelnummer | 5910 |
| Tidsskrift | Nature Communications |
| Vol/bind | 14 |
| Antal sider | 16 |
| ISSN | 2041-1723 |
| DOI | |
| Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:
We would like to thank Robert van Ling at ThermoFisher for early access to the μPAC Neo Low Load column and pre-column, and EvoSep for elaborate collaborations on the EvoSep One instrument. We also thank Biognosys for pre-release access to Spectronaut 17. Some of this work was funded by a grant from the Novo Nordisk Foundation to E.M.S. with reference number NNF21OC0071016. B.F. is the recipient of a fellowship from the Novo Nordisk Foundation as part of the Copenhagen Bioscience PhD. Programme, supported through grant NNF19SA0035442. V.P. is funded by a Leo Foundation grant awarded to S.F.T and E.M.S. (LF-OC-21-000832). P.A.F. is funded by a Danish Cancer Society grant (R324-A17978). Work in the B.T.P. lab is supported by grants from the Svend Andersen Foundation, the Candys foundation, the Danish Cancer Society, Independent Research Fund Denmark and through a center grant from the Novo Nordisk Foundation (Novo Nordisk Foundation Center for Stem Cell Biology, DanStem; Grant Number NNF17CC0027852). U.A.D.K. acknowledges funding by a Novo Nordisk Foundation Young Investigator Award (NNF16OC0020670). The S.G. group is supported by Novo Nordisk Foundation Grants NNF19SA0056783, NNF20SA0066621, and NNF19SA0057794. We also thank all members from the Cell Diversity Lab, headed by E.M.S. for constructive input and fruitful discussions, and the DTU Proteomics Core for technical instrument support.
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© 2023, Springer Nature Limited.
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