PSMtags improve peptide sequencing and throughput in sensitive proteomics
preprint · bioRxiv · 2025
| Date | 2025-05-22 |
| Type | preprint |
| Venue | bioRxiv |
| Publisher | Cold Spring Harbor Laboratory |
| Contribution | adjacent |
| DOI | 10.1101/2025.05.22.655509 |
| Citations (OpenAlex) | 4 |
Abstract
Mass spectrometry-based proteomics enables comprehensive characterization of protein abundance, function, and interactions. Label-free approaches are simple to implement but challenging to scale to thousands of samples per day. Multiplexed techniques, such as plexDIA, can address these limitations but remain restricted by the lack of mass tags optimized for data-independent acquisition (DIA) workflows. Here, we present a systematic approach screening a library of 576 compounds that identifies several small molecules that, when conjugated to peptides, improve their detection and sequence identification by mass spectrometry. The lead molecule, PSMtag, substantially increases the detection of fragment b-ions, which increases the confidence of sequence identification and enhances de novo sequencing. PSMtags allow 9-plexDIA, using only stable isotopes of carbon, oxygen and nitrogen. As a result, it allows simultaneously increasing proteome coverage and sample throughput for plexDIA workflows without compromising quantitative accuracy. We demonstrate 240 samples-per-day with 9-plexDIA, while acquiring 28,359 protein data points in the same time label-free methods acquire 4,340. Our approach constitutes an expandable framework for designing mass tags to overcome existing limitations in multiplexed proteomics and provides plexDIA reagents capable of analyzing over 1,000 samples per day when using 10 minute runs. By facilitating higher throughput and improved identification, this innovation holds significant potential for accelerating proteomic studies across diverse biological and clinical applications.
Methods and tools
- PSMtags: Small-molecule peptide conjugates found by systematic screening that sharply increase b-ion fragment coverage, raising sequence-identification confidence and improving de novo sequencing. Also supports 9-plex stable-isotope multiplexing at ~240 samples/day, boosting protein data points roughly 6.5x over the unlabelled baseline in sensitive (low-input) proteomics.
Data deposited
- PSMtags improve peptide sequencing and throughput in sensitive proteomics (as deposited) · MSV000097968
Data used
- PXD064191 (as deposited) · PXD064191
Cites (4)
- Deep Learning Methods for De Novo Peptide Sequencing (2024) crossref
- Computationally instrument-resolution-independent de novo peptide sequencing for high-resolution devices (2021) crossref
- Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning (2019) crossref
- Novor: Real-Time Peptide de Novo Sequencing Software (2015) crossref