Multiplexed Data-Independent Acquisition-Based Proteomics Enabled by TMTpro Complementary Ions
Data-independent acquisition (DIA) has emerged as a powerful approach in quantitative proteomics, offering more comprehensive and reproducible proteome coverage than the conventional data-dependent acquisition (DDA) method. However, applying multiplexed isobaric labeling to DIA has been challenging due to ratio distortion caused by coisolation and cofragmentation interference. Here, we present a 3-plex TMTpro complementary ion (TMTproC)-based DIA strategy that leverages complementary ions in isobaric labeling to achieve accurate quantification without increasing spectral complexity. By implementing a 4-Da spacing between complementary ions, we significantly reduce isotopic envelope overlap and simplify deconvolution. We systematically optimized higher-energy collisional dissociation (HCD) settings for complementary ion generation and validated this approach using tryptic bovine serum albumin (BSA) peptides labeled at 1:1:1, 10:5:1, and 1:5:10 ratios, achieving median peptide-level ratios within 10% of expected values and median coefficients of variation (CVs) below 4% across triplicates. We further demonstrated this method by applying TMTproC labeling across a 10-fold dynamic range to the yeast proteome in a strong human proteome background. The results exhibited high quantification precision and minimal ratio distortion. Overall, TMTproC-DIA provides a robust, versatile, and scalable solution for high-throughput DIA-based proteomics.
Authors
- Zicong Wang (ORCID: https://orcid.org/0009-0007-1965-6447)
- Peng-Kai Liu (ORCID: https://orcid.org/0009-0005-8580-3498)
- Haiyan Lu (ORCID: https://orcid.org/0000-0001-5655-0237)
- Lingjun Li (ORCID: https://orcid.org/0000-0003-0056-3869)
Institutions
- University of Wisconsin–Madison (US)
- NanoBio (United States) (US)
Publication Details
- Journal
- Analytical Chemistry
- Published
- 2025-11-26
- DOI
- https://doi.org/10.1021/acs.analchem.5c03563
- Citations
- 1
- Primary Topic
- Advanced Proteomics Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.76