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Data Independent Acquisition Approaches for Single Cell Proteomics
  • Gautam Ghosh,
  • Ariana Shannon,
  • Brian Searle
Gautam Ghosh
The Ohio State University
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Ariana Shannon
The Ohio State University Medical Center
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Brian Searle
The Ohio State University Medical Center

Corresponding Author:[email protected]

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Abstract

Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis might overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells and this review highlights the role of data-independent acquisition MS (DIA-MS) in SCP. One major hurdle in SCP is the limited material in single-cell samples, but DIA-based techniques offer multiple potential solutions for their analysis. Utilizing wide precursor isolation windows to fragment multiple peptides simultaneously, DIA-based methods improve sensitivity, quantitative accuracy, and reproducibility at a cost in data analysis complexity. DIA methods can also be combined with sample multiplexing methods to increase the sample throughput, currently a key limitation in SCP. Challenges remain for interpreting sample multiplexed data from DIA-based SCP experiments, particularly with regards to isobaric tagging methods. Even still, we believe that DIA-based SCP approaches will play a major role in our understanding of systems biology.
18 May 2024Submitted to PROTEOMICS
17 Jun 2024Review(s) Completed, Editorial Evaluation Pending
17 Jun 2024Editorial Decision: Revise Minor
09 Jul 2024Review(s) Completed, Editorial Evaluation Pending
09 Jul 20241st Revision Received
10 Jul 2024Editorial Decision: Accept