bims-mascan 2025-08-17 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2025–08–17
sixteen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz

Reverse Spectral Search Reimagined: A Simple but Overlooked Solution for Chimeric Spectral Annotation.
Localisation of Organelle Proteins using Data-Independent Acquisition (DIA-LOP).
Computationally unmasking each fatty acyl C=C position in complex lipids by routine LC-MS/MS lipidomics.
Library-free data-independent acquisition mass spectrometry enables comprehensive coverage of the cyanobacterial proteome.
A novel hybrid high speed mass spectrometer allows rapid translation from biomarker candidates to targeted clinical tests using 15N labeled proteins.
Enhancing Lipidomics With High-Resolution Ion Mobility-Mass Spectrometry.
Identification of Merkel cell polyomavirus oncoproteins by mass spectrometry-based proteomics.
Protein Turnover Dynamics Analysis With Subcellular Spatial Resolution.
Simple and sensitive LC-MS analysis of short chain fatty acids in cecum content and feces in mice: A derivatization-free approach.
Evaluating Novel Direct Injection Liquid Chromatography-Mass Spectrometry Method and Extraction-Based Workflows for Untargeted Lipidomics of Extracellular Vesicles.
Boosting Quantification of N-Glycans by an Enhanced Isobaric Multiplex Reagents for Carbonyl-Containing Compound (SUGAR) Tagging Strategy.
Single-cell Raman and mass spectrometry analysis to probe cellular heterogeneity in tamoxifen uptake and metabolism.
Metabolomics and Lipidomics Explore Phenotype-Specific Molecular Signatures for Phenylketonuria.
Online Coupling of Acoustic Droplet Levitation with Capillary Electrophoresis Mass Spectrometry Enables Midair Enrichment for Improved Proteomic Sensitivity.
Fast and Memory-Efficient Searching of Large-Scale Mass Spectrometry Data Using Tide.
Synergistic Arg-C Ultra and Lys-C Digestion for Quantitative Proteomics.

Anal Chem. 2025 Aug 15.

Reverse Spectral Search Reimagined: A Simple but Overlooked Solution for Chimeric Spectral Annotation.

Shipei Xing, Vincent Charron-Lamoureux, Haoqi Nina Zhao, Yasin El Abiead, Mingxun Wang, Pieter C Dorrestein.

The exponential growth of untargeted metabolomics data, now reaching billions of mass spectra in public repositories, benefits from reannotation strategies for data reuse. While tandem mass spectrometry (MS/MS) library matching remains the gold standard, annotation workflows face a critical bottleneck: chimeric spectra. These composite spectra, arising from simultaneous fragmentation of multiple precursor ions, compromise the ability to annotate MS/MS spectra against nonchimeric reference spectra. Here, we demonstrate that an enhanced version of reverse spectral search, a principle first introduced in 1975 but largely overlooked, provides a simple, computationally efficient solution, rescuing up to 62% more metabolite annotations in benchmark data sets while maintaining stringent quality control. The enhanced reverse spectral search is now added to the GNPS ecosystem. Source codes can be accessed at https://github.com/Philipbear/reverse_search.

DOI: https://doi.org/10.1021/acs.analchem.5c02047
Mol Cell Proteomics. 2025 Aug 07. pii: S1535-9476(25)00146-X. [Epub ahead of print] 101047

Localisation of Organelle Proteins using Data-Independent Acquisition (DIA-LOP).

K J A McCaskie, C Hutchings, R Feret, Y Kim, L M Breckels, M J Deery, K S Lilley.

Subcellular localisation within the proteome fundamentally influences cellular processes, however the development of high-throughput techniques to allow proteome-wide mapping of the cell has proven difficult. Here we present DIA-LOP, an approach capable of high-throughput spatial proteome mapping with in-depth subcellular resolution. This unified framework integrates differential-ultracentrifugation (DC) with ion-mobility-based data-independent acquisition mass spectrometry, alongside data processing using DIA-NN and spatial analysis within the pRoloc bioinformatics pipeline. We obtain the largest DIA-based subcellular proteomics map, with 8242 protein identifications across 13 organellar compartments in U-2 OS cells. Within the same experimental pipeline, we compare DC fractionation with an alternate detergent-based protocol using either DIA or data-dependent acquisition (DDA) mass spectrometry approaches, highlighting the increased subcellular resolution of the DC approach and the increased proteome coverage when DIA is applied. We demonstrate the ability of DIA-LOP to inform clinical studies by identifying and mapping disease related proteins within our osteosarcoma cell model. With impressive coverage and resolution, DIA-LOP provides a straightforward, high-throughput tool for biochemical discovery. This study thus informs potential users of subcellular proteomics strategies that employ biochemical fractionation of the optimal workflows to achieve high proteome coverage and subcellular resolution.

DOI: https://doi.org/10.1016/j.mcpro.2025.101047
Nat Commun. 2025 Aug 11. 16(1): 7277

Computationally unmasking each fatty acyl C=C position in complex lipids by routine LC-MS/MS lipidomics.

Leonida M Lamp, Gosia M Murawska, Joseph P Argus, Aaron M Armando, Radu A Talmazan, Marlene Pühringer, Evelyn Rampler, Oswald Quehenberger, Edward A Dennis, Jürgen Hartler.

Identifying carbon-carbon double bond (C=C) positions in complex lipids is essential for elucidating physiological and pathological processes. Currently, this is impossible in high-throughput analyses of native lipids without specialized instrumentation that compromises ion yields. Here, we demonstrate automated, chain-specific identification of C=C positions in complex lipids based on the retention time derived from routine reverse-phase chromatography tandem mass spectrometry (RPLC-MS/MS). We introduce LC=CL, a computational solution that utilizes a comprehensive database capturing the elution profile of more than 2400 complex lipid species identified in RAW264.7 macrophages, including 1145 newly reported compounds. Using machine learning, LC=CL provides precise and automated C=C position assignments, adaptable to any suitable chromatographic condition. To illustrate the power of LC=CL, we re-evaluated previously published data and discovered new C=C position-dependent specificity of cytosolic phospholipase A2 (cPLA2). Accordingly, C=C position information is now readily accessible for large-scale high-throughput studies with any MS/MS instrumentation and ion activation method.

DOI: https://doi.org/10.1038/s41467-025-61911-x
Plant Physiol. 2025 Aug 12. pii: kiaf334. [Epub ahead of print]

Library-free data-independent acquisition mass spectrometry enables comprehensive coverage of the cyanobacterial proteome.

David A Russo, Felix R Schneidmadel, Julie A Z Zedler.

Cyanobacteria have played a leading role in elucidating the fundamental mechanisms behind oxygenic photosynthesis, carbon fixation, the circadian clock, and phototaxis. Such molecular processes rely on proteins at their core. Thus, proteomics has become an indispensable tool in building our understanding of these processes. Amongst the proteomic approaches used, "shotgun proteomics", where complex protein mixtures are enzymatically digested into peptides and analyzed by liquid chromatography-mass spectrometry, has become the go-to technique for whole-proteome analysis. In this study, we introduce shotgun workflows that excel in speed, throughput, and sensitivity, and allow an in-depth description of the cyanobacterial proteome. The main features of these workflows are the improvement of sample cleanup and digestion through single-pot solid phase-enhanced sample preparation (SP3), the adoption of a previously validated trifluoroacetic acid lysis strategy, and the application of library-free data-independent acquisition. Using the established model organism Synechococcus elongatus PCC 7942, we show that these workflows exhibit high quantitative reproducibility and enable the detection of 83% to 85% of all open reading frames, the greatest single-shot coverage achieved so far for a cyanobacterium. These workflows require only a couple of hours of hands-on time and should be applicable to most, if not all, cyanobacterial species. Together with the rapid advancements in mass spectrometry technologies, this work has the potential to accelerate cyanobacterial proteomics.

DOI: https://doi.org/10.1093/plphys/kiaf334
Mol Cell Proteomics. 2025 Aug 13. pii: S1535-9476(25)00149-5. [Epub ahead of print] 101050

A novel hybrid high speed mass spectrometer allows rapid translation from biomarker candidates to targeted clinical tests using 15N labeled proteins.

Maria Wahle, Philip M Remes, Vincent Albrecht, Michael Baggio Lorenz, Johannes Mueller-Reif, Sophia Steigerwald, Tim Heymann, Lili Niu, Philip Lössl, Stevan Horning, Cristina C Jacob, Matthias Mann.

Recent developments in affinity binder or mass spectrometry (MS)-based plasma proteomics are now producing panels of potential biomarker candidates for diagnosis or prognosis. However, clinical validation and implementation of these biomarkers remain limited by the reliance on dated triple quadrupole MS technology. Here, we evaluate a novel hybrid high-speed mass spectrometer, Stellar MS, which integrates the robustness of triple quadrupoles with the enhanced capabilities of an advanced linear ion trap analyzer. This instrument allows for extremely rapid and sensitive parallel reaction monitoring (PRM) and MS3 targeting. The Stellar MS allowed targeting thousands of peptides originally measured on Orbitrap Astral MS, achieving high reproducibility and low coefficients of variation (CV) as well as sensitivity and specificity sufficient for many of the top 1000 plasma proteins. Furthermore, we developed targeted assays for alcohol-related liver disease (ALD) biomarkers, showcasing the potential of Stellar MS in clinical applications. Absolute quantification is typically a requirement for clinical assays and we explore the use of 15N labeled protein standards in a rapid, streamlined and generic manner. Our results indicate that the Stellar MS can bridge the gap between proteomics discovery and routine clinical testing, enhancing the diagnostic and prognostic utility of protein biomarkers.

DOI: https://doi.org/10.1016/j.mcpro.2025.101050
Proteomics. 2025 Aug 13. e70026

Enhancing Lipidomics With High-Resolution Ion Mobility-Mass Spectrometry.

Gaoyuan Lu, Shuling Xu, Penghsuan Huang, Lingjun Li.

Lipids, indispensable yet structurally intricate biomolecules, serve as critical regulators of cellular function and disease progression. Conventional lipidomics, constrained by limited resolution for isomeric and low-abundance species, has been transformed by ion mobility-mass spectrometry (IM-MS). This technology augments analytical power through enhanced orthogonal separation, collision cross-section (CCS)-based identification, and improved sensitivity. This review examines the transformative advances in IM-MS-driven lipidomics, focusing on three major pillars: (1) a critical evaluation of leading ion mobility spectrometry (IMS) platforms, emphasizing innovative instrument geometries and breakthroughs in resolving lipid isomers; (2) an exploration of lipid CCS databases and predictive frameworks, spotlighting computational modeling and machine learning strategies that synergize experimental data with molecular representations for high-confidence lipid annotation; (3) emerging multi-dimensional lipidomics workflows integrating CCS with liquid chromatography-MS/MS to boost identification and depth, alongside mass spectrometry imaging for spatially resolved lipidomics. By unifying cutting-edge instrumentation, computational advances, and biological insights, this review outlines a roadmap for leveraging IM-MS to unravel lipidome complexity, catalyzing biomarker discovery and precision medicine innovation.

DOI: https://doi.org/10.1002/pmic.70026
J Invest Dermatol. 2025 Aug 13. pii: S0022-202X(25)02339-5. [Epub ahead of print]

Identification of Merkel cell polyomavirus oncoproteins by mass spectrometry-based proteomics.

Ann Mari Rosager, Sonja Kabatnik, Ying Zhang, Sofie Agerbæk, Michael Bzorek, Marianne Bengtson Løvendorf, Beatrice Dyring-Andersen.



Keywords:  Merkel cell carcinoma; cancer; mass spectrometry-based proteomics; oncoproteins; polyomavirus

DOI:  https://doi.org/10.1016/j.jid.2025.07.026
Bio Protoc. 2025 Aug 05. 15(15): e5409

Protein Turnover Dynamics Analysis With Subcellular Spatial Resolution.

Lorena Alamillo, Alexander Black, Maggie P Y Lam, Edward Lau.

  Protein synthesis and degradation (i.e., turnover) forms an important part of protein homeostasis and has been implicated in many age-associated diseases. Different cellular locations, such as organelles and membraneless compartments, often contain individual protein quality control and degradation machineries. Conventional methods to assess protein turnover across subcellular compartments require targeted genetic manipulation or isolation of specific organelles. Here we describe a protocol for simultaneous proteome localization and turnover (SPLAT) analysis, which combines protein turnover measurements with unbiased subcellular spatial proteomics to measure compartment-specific protein turnover rates on a proteome-wide scale. This protocol utilizes dynamic stable isotope labeling of amino acids in cell culture (dynamic SILAC) to resolve the temporal information of protein turnover and multi-step differential ultracentrifugation to assign proteins to multiple subcellular localizations. We further incorporate 2D liquid chromatography fractionation to greatly increase analytical depth while multiplexing with tandem mass tags (TMT) to reduce acquisition time 10-fold. This protocol resolves the spatial and temporal distributions of proteins and can also reveal temporally distinct spatial localizations within a protein pool. Key features • Captures protein turnover rates and subcellular localization of proteins. • Hyperplexing of dynamic SILAC and TMT LOPIT-DC in MS1 and MS2 level data. • Sample collection and processing can be completed within 1 week. • Allows comparison of organellar proteome turnover rates.

Keywords:  Mass spectrometry; Proteomics; Spatial proteomics; Subcellular localization; Temporal proteomics; Turnover

DOI:  https://doi.org/10.21769/BioProtoc.5409
J Chromatogr A. 2025 Aug 09. pii: S0021-9673(25)00608-9. [Epub ahead of print]1760 466263

Simple and sensitive LC-MS analysis of short chain fatty acids in cecum content and feces in mice: A derivatization-free approach.

Soo Takasu, Yumi Nagasaki, Juri Koizumi, Tetsuo Koshizuka, Yukihiro Esaka.

  Short-chain fatty acids (SCFAs), such as acetic, propionic, and butyric acid, are important biomarkers that reflect gut microbiota composition, disease progression, and overall health. Conventional SCFA analysis typically involves derivatization prior to liquid or gas chromatography. However, derivatization is challenging due to the volatility of SCFAs and interference from similar carboxylic acids in biological samples and often requires complex purification steps. Consequently, the development of derivatization-free liquid chromatography-mass spectrometry (LC-MS) methods is desirable, although direct LC-MS analysis of intact SCFAs often suffers from limited sensitivity and accuracy. In this study, we have developed a derivatization-free LC-MS method for the analysis of major SCFAs (C2-C4) in the cecum content and feces of mice. Separation was performed using a mixed-mode column combining hydrophilic interaction chromatography and anion-exchange chromatography. We found that ammonium formate, required for separation, significantly suppressed SCFA signal intensity, whereas its replacement by ammonium fluoride prevented this suppression. Furthermore, we have demonstrated that the background noise in biological sample analysis can be reduced by selective reaction monitoring (SRM) mode, in which the same m/z value was set for both the precursor and product ions, as compared with selective ion monitoring (SIM) mode. The method developed in this study showed good validation values and sensitivity in the quantification of targeted SCFAs in mouse biological samples, demonstrating the excellent practicability of this method and making it a useful tool for research on the gut microbiome.

Keywords:  Ammonium fluoride; Gut microbiota; Hydrophilic interaction chromatography (HILIC); LC-MS analysis; Short-chain fatty acids (SCFAs)

DOI:  https://doi.org/10.1016/j.chroma.2025.466263
J Proteome Res. 2025 Aug 11.

Evaluating Novel Direct Injection Liquid Chromatography-Mass Spectrometry Method and Extraction-Based Workflows for Untargeted Lipidomics of Extracellular Vesicles.

Michał Młynarczyk, Felicja Gajdowska, Jorge Matinha-Cardoso, Paulo Oliveira, Paula Tamagnini, Mariusz Belka, Jagoda Mantej, Danuta Gutowska-Owsiak, Weronika Hewelt-Belka.

  Lipids of extracellular vesicles (EVs) are attracting attention due to their crucial biological functions and potential roles in processes such as carcinogenesis. This study compares three commonly used lipid extraction techniques, i.e., liquid-liquid extraction, single-phase extraction, and solid-phase extraction, with a novel direct injection liquid chromatography-mass spectrometry (DI-LC-MS) workflow tailored to EV lipidomics. In the DI-LC-MS approach, EVs are disrupted and released directly in the chromatographic system, enabling the analysis of lipids without a prior extraction step. The applicability of the DI-LC-MS workflow was demonstrated by profiling lipids in mammalian and bacterial EVs. The lipidome coverage and high precision of the DI-LC-MS method (coefficient of variation of peak area lower than 20% for all the identified lipids) enabled identification of differences in lipid profiles of EV samples. The column used in the DI-LC-MS method exhibited a sufficient lifespan and stability for comparative lipidomic studies. Lipidome coverage, lipid species distribution, and precision varied across the studied workflows; our findings highlight the strengths and limitations of these methods. The DI-LC-MS emerges as a sustainable alternative for EV lipidomic studies by eliminating the need for sample preparation and reducing analysis time, solvent use, and chemical noise while requiring less than 1 μL of sample.

Keywords:  LC-MS; extracellular vesicles; lipid extraction; lipidomics; liquid–liquid extraction; solid-phase extraction

DOI:  https://doi.org/10.1021/acs.jproteome.5c00156
J Am Soc Mass Spectrom. 2025 Aug 11.

Boosting Quantification of N-Glycans by an Enhanced Isobaric Multiplex Reagents for Carbonyl-Containing Compound (SUGAR) Tagging Strategy.

Jingwei Zhang, Zicong Wang, Yuan Liu, Henrik Zetterberg, Lingjun Li.

Glycans are complex molecules composed of various monosaccharides and exhibit diverse, branched polymer structures. Extensive research has been conducted on mass spectrometry (MS)-based qualitative and quantitative glycan analysis due to their critical biological functions. However, traditional data-dependent acquisition (DDA) in MS analysis primarily selects a limited subset of abundant ions during MS1 scans for fragmentation in subsequent MS2 stages. In this study, we introduce an advanced isobaric labeling strategy that incorporates a large amount of content-relevant sample labeled with one isobaric tag channel as an additional boosting channel. This innovation enhances the efficiency of isobaric multiplex reagents for carbonyl-containing compound (SUGAR) tagging in quantitative glycomics. Notably, this approach significantly improves the characterization of low-abundance N-glycans and enables the detection of subtle quantitative differences in N-glycan profiling.

DOI: https://doi.org/10.1021/jasms.5c00153
Anal Bioanal Chem. 2025 Aug 14.

Single-cell Raman and mass spectrometry analysis to probe cellular heterogeneity in tamoxifen uptake and metabolism.

Congrou Zhang, Yasmine Abouleila, Sylvia Le Dévédec, Thomas Hankemeier, Arno Germond, Ahmed Ali.

  Current drug discovery is limited by the lack of single-cell data on drug uptake, metabolism, and effects, as population-level methods obscure cellular heterogeneity. While single-cell RNA sequencing has revealed drug resistance mechanisms, it cannot simultaneously measure drug concentrations and cellular responses. Raman spectroscopy probes single-cell drug effects but lacks sensitivity for drug or its metabolite quantification, whereas single-cell mass spectrometry (MS) offers high sensitivity but consumes samples, preventing repeated measurements. Integrating Raman spectroscopy with MS enables simultaneous assessment of cellular states and drug metabolism. However, existing studies are limited by small sample sizes and single drug concentrations. We employ a combined single-cell Raman and mass spectrometry (Raman-MS) approach to investigate variability in drug uptake, metabolism, and effects in HepG2 liver cancer cells. The cells were exposed to three concentrations of tamoxifen, after which we quantified the heterogeneity in tamoxifen and its hepatotoxic metabolites. This validates the potential of single-cell analysis for advancing drug discovery and cancer research. Our results indicated that tamoxifen induces concentration-dependent metabolic changes in single liver cancer cells, as revealed by Raman spectroscopy and mass spectrometry. The findings highlight a potential threshold concentration beyond which cellular integrity is compromised, underscoring the importance of single-cell approaches for understanding drug uptake, metabolism, and therapeutic heterogeneity.

Keywords:  Cellular heterogeneity; Raman spectroscopy; Single-cell mass spectrometry; Tamoxifen

DOI:  https://doi.org/10.1007/s00216-025-06058-w
Int J Mol Sci. 2025 Jul 25. pii: 7171. [Epub ahead of print]26(15):

Metabolomics and Lipidomics Explore Phenotype-Specific Molecular Signatures for Phenylketonuria.

Buket Yurteri Şahiner, Ali Dursun, Basri Gülbakan.

  Phenylketonuria (PKU) is a monogenic disorder caused by pathogenic variants in the gene encoding phenylalanine hydroxylase (PAH), an enzyme essential for phenylalanine (Phe) metabolism. It is characterized by elevated Phe levels, leading to a wide spectrum of clinical phenotypes. These phenotypes are characterized by varying Phe accumulation, dietary tolerance, and heterogeneous cognitive and neurological outcomes, but current monitoring methods, focused primarily on blood Phe levels, are limited in capturing this variability. In this study, we applied mass spectrometry-based advanced quantitative amino acid analyses, untargeted metabolomics, and lipidomics analyses. We examined the plasma metabolite and lipid profiles in a total of 73 individuals with various PKU phenotypes against healthy controls to see how the metabolome and lipidome of the patients change in different phenotypes. We investigated whether novel markers could be associated with metabolic control status. By elucidating the metabolic and lipid fingerprints of PKU's phenotypic variability, our findings may provide novel insights that could inform the refinement of dietary and pharmacological interventions, thereby supporting the development of more personalized treatment strategies.

Keywords:  biomarker discovery; phenylketonuria; untargeted lipidomics; untargeted metabolomics

DOI:  https://doi.org/10.3390/ijms26157171
Anal Chem. 2025 Aug 11.

Online Coupling of Acoustic Droplet Levitation with Capillary Electrophoresis Mass Spectrometry Enables Midair Enrichment for Improved Proteomic Sensitivity.

Dashuang Jia, Peter Nemes.

Contact between analytes and surfaces during sample handling remains a major barrier to sensitivity in trace-level proteomics, including single-cell mass spectrometry (MS). Here, we introduce the first online integration of acoustic droplet levitation with capillary electrophoresis-electrospray ionization mass spectrometry (CE-ESI-MS), enabling containerless, midair sample enrichment and analysis. In this Levitational CE-MS platform, droplets containing proteome digests were stably levitated and allowed to evaporate midair, without active acceleration, using an asymmetric acoustic levitator to concentrate analytes prior to CE-MS analysis. Optical imaging confirmed a ∼4.4-fold volume reduction after 60 min of passive evaporation, corresponding to ∼3.4-fold concentration enrichment based on label-free quantification of the resulting proteome. This enhancement increased sample utilization by ∼100% compared to conventional CE-ESI-MS, doubling protein identifications from ∼3 ng HeLa digest (∼10 cells) to 2169 proteins after enrichment (∼14 ng). Quantitation showed consistent proteome composition without concentration or hydrophobicity bias. These results establish Levitational CE-ESI-MS as a sensitive, reproducible, and contact-free strategy for trace-level proteomics, opening new possibilities for low-input including single-cell analyses.

DOI: https://doi.org/10.1021/acs.analchem.5c03550
J Proteome Res. 2025 Aug 12.

Fast and Memory-Efficient Searching of Large-Scale Mass Spectrometry Data Using Tide.

Attila Kertesz-Farkas, Frank Lawrence Nii Adoquaye Acquaye, Vladislav Ostapenko, Rufino Haroldo Locon, Yang Lu, Charles E Grant, William Stafford Noble.

  Over the past 30 years, software for searching tandem mass spectrometry data against a protein database has improved dramatically in speed and statistical power. However, existing tools can still struggle to analyze truly massive data sets when either the number of spectra or the number of proteins being analyzed grows too large. Here, we describe enhancements to the Tide search engine that allow it to handle data sets containing >10 million spectra and databases containing >7 billion peptides on commodity hardware. We demonstrate that the new Tide architecture is around 2-7 times faster than the previous version and is now comparable to MSFragger and Sage in speed while requiring much less memory. Tide is open source and is publicly available as precompiled binaries for Windows, Linux, and Mac.

Keywords:  Tandem mass spectrometry; database search; peptide detection

DOI:  https://doi.org/10.1021/acs.jproteome.5c00297
bioRxiv. 2025 Jul 18. pii: 2025.07.15.664461. [Epub ahead of print]

Synergistic Arg-C Ultra and Lys-C Digestion for Quantitative Proteomics.

Vyas Pujari, Joseph Crapse, Connor Nisbet, Gloria Bao, Wessley Ferguson, Christopher M Hosfield, Michael Rosenblatt, Felix Keber, Martin Wühr.

Shotgun proteomics hinges on complete enzymatic digestion of proteins into peptides. Incomplete digestion narrows proteome coverage and inflates variability in quantitative workflows, whether label-free DIA or multiplexing with isobaric tags. Sequential Lys-C/Trypsin digestions mitigate missed cleavages at lysine residues, but arginine sites remain a persistent challenge. Arg-C Ultra, a recently released cysteine protease, efficiently targets arginine residues but requires reducing conditions that inactivate Lys-C activity and compromise NHS- ester labeling in multiplexed workflows. Here, we systematically characterized Arg-C Ultra and Lys-C with chromogenic substrates that mimic arginine- and lysine-containing peptides, as well as shotgun proteomics. Arg-C Ultra operates optimally at room temperature, pH 7.5-8.5, under reducing conditions, whereas Lys-C is most active at 37 °C, pH 7.5-8.5, yet rapidly loses activity when exposed to common reductants. Among tested reducing agents, 1 mM TCEP uniquely preserved TMTpro integrity while sustaining Arg-C Ultra activity. Guided by these insights, we established a sequential digestion workflow that is fully compatible with both label- free DIA and TMTpro multiplexing. Proteins are first digested overnight with Lys-C at 37 °C (pH 8.5), then treated with 1 mM TCEP and Arg-C Ultra at room temperature (pH 8.5). The resulting peptides can be analyzed directly by label-free DIA or subjected to TMTpro labeling for multiplexed quantification. Applied to HeLa cell lysates, this protocol achieved >99% arginine and 95% lysine cleavage efficiencies, boosting the number of quantified proteins by 6% in label- free DIA and 11% in TMTproC experiments. Replicate measurements displayed reproducibility that approached the limits set by ion statistics. Thus, the introduced synergistic Lys-C/Arg-C Ultra digestion strategy enhances proteome coverage with excellent quantitative reproducibility across both label-free and multiplexed platforms.

DOI: https://doi.org/10.1101/2025.07.15.664461