MSACL 2025 Abstract

Simple, Large-Scale Absolute Quantitative Proteomics Through Stable Isotope-Labeled Mouse Internal Standard

Timon Geib (1), Yassene Mohammed (1,2,3), Vincent R. Richard (1), Pradyumn Maheshwar (4), Claudia Gaither (4,5), Robert Popp (4), René P. Zahedi (6,7,8,9), and Christoph H. Borchers (1,2,10,11)
(1) Segal Cancer Proteomics Centre, Jewish General Hospital, Montreal, QC, Canada, (2) Gerald Bronfman Department of Oncology, Jewish General Hospital, Montreal, QC, Canada, (3) Center for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, The Netherlands, (4) MRM Proteomics, Inc, Montreal, QC, Canada, (5) Faculty of Veterinary Medicine, Department of Clinical Sciences, University of Montreal, Saint- Hyacinthe, QC, Canada, (6) Manitoba Centre for Proteomics and Systems Biology, Winnipeg, MB, Canada, (7) Department of Internal Medicine, University of Manitoba, Winnipeg, MB, Canada, (8) Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, MB, Canada, (9) Paul Albrechtsen Research Institute, CancerCare Manitoba, Winnipeg, MB, Canada, (10) Division of Experimental Medicine, McGill University, Montreal, QC, Canada, (11) Department of Pathology, McGill University, Montreal, QC, Canada

Timon Geib, PhD (Presenter) Lady Davis Institute

Presenter Bio: Dr. Geib is a Research Associate and Project Manager with extensive experience in bioanalytical chemistry and mass spectrometry. He has experience in leading scientific projects involving complex sample matrices, and targeted and untargeted LC-MS. With a Ph.D. in Chemistry from Université du Québec à Montréal (UQAM) and over a dozen publications, Timon specializes in proteomics, and has presented his work at numerous international conferences. He is trilingual (German, English, French) and holds several academic awards, including the MMSDG Michel Bertrand Award and the FRQNT Doctoral Scholarship.

Relevant Financial Disclosures (within past 24 months, reported on Apr 21, 2026) No relevant financial relationship(s) to disclose. Conflict mitigation NOT REQUIRED.

INTRODUCTION:
Large-scale proteomics faces persistent challenges, including batch effects, often extensive offline fractionation, and long LC run times, that repeatably undermine the statistical significance of data and as a result the detection of subtle yet critical changes in complex biological samples. These barriers are magnified when inter-laboratory reproducibility is required. Stable isotope-labeled (SIL) standards offer a solution, but their high cost and lack of off-the-shelf availability frequently limit widespread adoption. We have introduced “SysQuan”, leveraging SIL mouse as a versatile, system-wide internal standard, enabling the absolute quantitation of the human proteome. SysQuan simplifies proteomics workflows, reduces costs, and enhances scalability, while offering absolute proteome quantitation within a single sample.

METHODS:
C57BL/6 mice were fed 13C-lysine chow over six generations. Human and SIL mouse fresh-frozen livers were cryo-homogenized and then ultrasonicated. Homogenized livers, as well as human and SIL mouse plasma were heated in sodium dodecyl sulfate (SDS) buffer. A one-to-one mix of human and mouse liver, and one-to-one mix of human and mouse plasma were reduced with tris (2-carboxyethyl) phosphine (TCEP), alkylated with iodoacetamide and then digested overnight using trypsin and S-Trap cartridges. Up to 1 µg of digests were injected on column and analyzed by dynamic multiple reaction monitoring (MRM), performed on an Evosep One LC system, equipped with an IonOpticks Aurora Elite 15 cm x 75 μm C18 UHPLC column, coupled to an Agilent 6495 triple quadrupole. In addition, digests were offline fractionated by high-pH reversed-phase LC. Untargeted top 10 data-dependent acquisition (DDA)–parallel accumulation-serial fragmentation (PASEF) was run on an Evosep One coupled to a Bruker timsTOF HT.

RESULTS:
Through in-depth untargeted analysis of extensively fractionated liver digests (48 fractions), we identified over 48,000 SIL/light peptide pairs representing more than 6,900 unique human proteins in liver samples. In parallel, we identified over 5,700 peptides in plasma with quantifiable SIL and light features, representing more than 1,400 unique human plasma proteins. Building on this, we shifted focus to liver metabolism, targeting up to 800 proteins using targeted MRM analysis of unfractionated liver digests. From an initial set of 5,324 peptides—comprising 2,662 SIL mouse/human pairs with at least three pairs per protein—we refined the data using ion ratio matching. This resulted in the successful detection and quantitation of 541 peptides representing as many as 296 liver proteins. This was accomplished without optimizing MRM transitions, collision energies, or MRM retention time windows. Instead, a 60-min nano-flow gradient and scheduled MRM scanning were employed. Over 500 peptides were detected with dwell times as short as <1 msec.

We are actively working to further enhance detection and quantitation rate by reducing transitions to three fragments per precursor and optimizing retention times and collision energies to maximize the performance of each feature. For this, we are synthesizing and optimizing light peptide standards for the remaining ~500 hepatic protein targets. Similarly, we are implementing the same approach to the 1,400 plasma proteins.

Additionally, light peptide standards are being utilized to reverse-quantify mouse SIL liver and plasma proteins. This will allow for the direct, off-the-shelf quantitation of hundreds of proteins in a single MRM run, even with complex, unfractionated liver and plasma samples.

CONCLUSION:
SysQuan transforms absolute quantitation of the human liver and plasma proteome with a novel, single-injection workflow, making scalability and cross-laboratory comparisons accessible.