# A universal multiplexing approach to unlock the hidden proteome

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2021 · $329,976

## Abstract

SUMMARY
Mass spectrometry (MS) based proteomics has made remarkable advances over the past several years, now
enabling the detection of 8,000 proteins in a single analysis, or with extensive fractionation, protein detection
levels approaching that of transcriptomics can now be achieved. Despite such advances, a significant bias
exists in the proteome routinely detected by MS due to the near exclusive use of trypsin for proteolytic
cleavage during sample preparation. Trypsin is a well­suited protease for proteomics, as it produces peptides
with favorable chemical composition for MS analysis, however, it also locks a considerable fraction of the
proteome in peptides either too small or too large for MS detection ­ thus rendering these segments of the
proteome effectively invisible in >99% of the proteomics experiments performed to date. Only a handful of
global proteomics experiments have reported the use of alternative proteases, primarily due to the generally
superior performance of trypsin, and the increased instrument time required to analyze additional samples ­ a
limiting factor for most labs. Recently developed MS approaches, specifically data­independent acquisition
(DIA), operate under new experimental and computational paradigms which rely on deconvolution of highly
complex MS spectra and matching to peptide or spectral databases for detection. This new paradigm presents
the opportunity to multiplex proteomic samples generated from a variety of different proteases in a single MS
analysis. However, to date DIA analysis has been exclusively developed for tryptic peptides. Here we propose
an innovative DIA acquisition and computational analysis approach to multiplex multiple proteases and unlock
the hidden proteome. To achieve the goals of this proposal we will first optimize DIA for non­trypsin proteases,
and then apply these optimized conditions in a DIA multiplexed setting with a mixture of different proteases.
Lastly, we will further develop and apply this framework to the analysis of post­translational modifications (e.g.
phosphorylation) where increased proteome coverage is essential for modification detection and localization.
Successful completion of this work will provide a robust framework to dramatically increase the proteome
routinely detected and quantified in MS analysis. Importantly, all details of this workflow, from sample handling
to software for data analysis, will be well documented in step­by­step online protocols and freely distributed to
the community to enable rapid integration of this approach into modern proteomics workflows.

## Key facts

- **NIH application ID:** 10240468
- **Project number:** 5R01GM133981-03
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Danielle L Swaney
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $329,976
- **Award type:** 5
- **Project period:** 2019-09-15 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10240468

## Citation

> US National Institutes of Health, RePORTER application 10240468, A universal multiplexing approach to unlock the hidden proteome (5R01GM133981-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10240468. Licensed CC0.

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