Simultaneous maximization of sensitivity, data completeness and throughput in mass-spectrometry proteomics often necessitates trade-offs. To mitigate these trade-offs, we introduce a prioritization algorithm that achieves high sensitivity and data completeness while maximizing throughput. With prioritized single-cell proteomics (pSCoPE), we consistently and accurately quantify proteins and their post-translational modifications in single macrophages and link them to endocytic activity.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Rent or buy this article
Get just this article for as long as you need it
$39.95
Prices may be subject to local taxes which are calculated during checkout
References
Specht, H. & Slavov, N. Transformative opportunities for single cell proteomics. J. Proteome Res. 17, 2565–2571 (2018). An article that outlines major opportunities for single-cell proteomics and emphasizes the benefits of high-throughput targeted (directed) protein analysis.
Leduc, A. et al. Exploring functional protein covariation across single cells using nPOP. Genome Biol. 23, 261 (2022). A research article that introduced nPOP, a method that enables efficient, flexible, and scalable sample preparation for single-cell proteomics.
Slavov, N. Driving single cell proteomics forward with innovation. J. Proteome Res. 20, 4915–4918 (2021). A perspective article that explains the need and opportunities for optimizing MS data acquisition using real-time instrument control.
Wichmann, C. et al. MaxQuant.Live enables global targeting of more than 25,000 peptides. Mol. Cell. Proteom. 18, 982–994 (2019). A research article reporting the software for data acquisition with real-time retention-time alignment that we upgraded to enable prioritization.
Slavov, N. Learning from natural variation across the proteomes of single cells. PLoS Biol. 20, e3001512 (2022). A perspective discussing how joint distributions of proteins can enable inference of biological mechanisms with minimal assumptions.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This is a summary of: Huffman, R. G. et al. Prioritized mass spectrometry increases the depth, sensitivity and data completeness of single-cell proteomics. Nat. Methods https://doi.org/10.1038/s41592-023-01830-1 (2023).
Rights and permissions
About this article
Cite this article
Extending the sensitivity, consistency and depth of single-cell proteomics. Nat Methods 20, 649–650 (2023). https://doi.org/10.1038/s41592-023-01786-2
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41592-023-01786-2
