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BoxCarmax: A High-Selectivity Data-Independent Acquisition Mass Spectrometry Method for the Analysis of Protein Turnover and Complex Samples
Open accessPublished version of a preprint
Abstract
The data-independent acquisition (DIA) performed in the latest high-resolution, high-speed mass spectrometers offers a powerful analytical tool for biological investigations. The DIA mass spectrometry (DIA-MS) combined with the isotopic labeling approach holds a particular promise for increasing the multiplexity of DIA-MS analysis, which could assist the relative protein quantification and the proteome-wide turnover profiling. However, the wide MS1 isolation windows employed in conventional DIA methods lead to a limited efficiency in identifying and quantifying isotope-labeled peptide pairs through peptide fragment ions. Here, we optimized a high-selectivity DIA-MS named BoxCarmax that supports the analysis of complex samples, such as those generated from Stable isotope labeling by amino acids in cell culture (SILAC) and pulse SILAC (pSILAC) experiments. BoxCarmax enables multiplexed acquisition at both MS1 and MS2 levels, through the integration of BoxCar and MSX features, as well as a gas-phase separation strategy. We found BoxCarmax significantly improved the quantitative accuracy in SILAC and pSILAC samples by mitigating the ratio suppression of isotope-peptide pairs. We further applied BoxCarmax to measure protein degradation regulation during serum starvation stress in cultured cells, revealing valuable biological insights. Our study offered an alternative and accurate approach for the MS analysis of protein turnover and complex samples.
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Metadata
- Authors
- Salovska, B., Li, W., Di, Y., & Liu, Y.
- Affiliations
- Yale Cancer Biology Institute, Yale University, West Haven, Connecticut CT 06520, United States
- Yale University (US)
- Corresponding author
- Liu, Yansheng
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2021-02-03
- Volume
- 93
- Issue
- 6
- Pages
- 3103-3111
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- PMC
- PMC8959401
- OpenAlex
- W3126155190
- Cited by
- 35
- References
- 6
- Citations by year
- 2026: 1 · 2025: 8 · 2024: 5 · 2023: 10 · 2022: 10 · 2021: 1
- FWCI
- 2.37
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Analytical Chemistry (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (R01GM137031)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Keywords
- data-independent acquisition, boxcars, MSX, SILAC, protein turnover, protein degradation, serum deprivation, gas-phase separation, relative protein quantification
- MeSH terms
- Isotope Labeling, Proteins, Mass Spectrometry, Proteome, Proteomics, Proteolysis
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