Pavel Sinitcyn

Morgridge Institute for Research

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Jürgen Cox

Max Planck Institute of Biochemistry

Joshua J. Coon

University of Wisconsin–Madison

Georg H. H. Borner

Max Planck Institute of Biochemistry

Matthias Mann

Novo Nordisk Foundation

Alexandra K. Davies

Max Planck Institute of Biochemistry

Julia P. Schessner

Max Planck Institute of Biochemistry

Evgenia Shishkova

University of Wisconsin–Madison

Noah M. Lancaster

University of Wisconsin–Madison

Vincent Albrecht

KTH Royal Institute of Technology

Lia R. Serrano

University of Wisconsin–Madison

Cooperative Institutions

Max Planck Institute of Biochemistry

University of Wisconsin–Madison

Technical University of Munich

Klinikum rechts der Isar

Heidelberg University

University of California, San Francisco

German Cancer Research Center

Quantitative BioSciences

Max Planck Society

Lomonosov Moscow State University

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The Perseus computational platform for comprehensive analysis of (prote)omics data

Nature Methods (2016)

Stefka Tyanova Tikira Temu Pavel Sinitcyn Arthur Carlson Marco Y. Hein

Plug-in

Python

10.1038/nmeth.3901

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Citations (7,053)

The One Hour Human Proteome

Molecular & Cellular Proteomics (2024)

Lia R. Serrano Trenton M. Peters-Clarke Tabiwang N. Arrey Eugen Damoc Margaret Lea Robinson

We describe deep analysis of the human proteome in less than one hour. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high MS/MS acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data independent- or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis (DIA) methods. Over a 30-minute active chromatographic method consuming a total analysis time of 56 minutes, the Q-Orbitrap-Astral hybrid MS collects an average of 4,319 MS1 scans and 438,062 MS/MS scans per run, producing 235,916 peptide sequences (1% false discovery rate (FDR)). On average, each 30-minute analysis achieved detection of 10,411 protein groups (1% FDR). We conclude, with these results and alongside other recent reports, that the one-hour human proteome is within reach.

Proteome

Human proteome project

10.1016/j.mcpro.2024.100760

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Citations (16)

Author response: The ER membrane protein complex interacts cotranslationally to enable biogenesis of multipass membrane proteins

Matthew J. Shurtleff Daniel N. Itzhak Jeffrey A. Hussmann Nicole T Schirle Oakdale Elizabeth A. Costa

10.7554/elife.37018.023

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Citations (1)

Deep and fast label-free Dynamic Organellar Mapping - Imaging data

Zenodo (CERN European Organization for Nuclear Research) (2023)

Julia P. Schessner Vincent Albrecht Alexandra K. Davies Pavel Sinitcyn Georg H. H. Borner

Imaging data from the article "Deep and fast label-free Dynamic Organellar Mapping", published in Nature Communications by Schessner et al., from Fig. 6, 7 and Supp. Fig. 6c. Widefield images were captured on a Leica DMi8 inverted microscope equipped with an iTK LMT200 motorised stage, a 63x/1.47 oil objective (HC PL APO 63x/1.47 OIL) and a Leica DFC9000 GTC Camera, and controlled with LAS X (Leica Application Software X). Fig6_GLG1_TGOLN2_GALNT2_SuppFig6c_LC3B: Widefield imaging of wild-type HeLa cells cultured for 1h in either: 1) full growth medium (Control); 2) EBSS to starve the cells (Starve); 3) full growth medium plus 100 nM BafA (Control + BafA); or 4) EBSS plus 100 nM BafA (Starve + BafA). Cells were labelled with anti-GALNT2 (Alexa Fluor 488), in combination with either anti-GLG1 (Alexa Fluor 568) or anti-TGOLN2 (Alexa Fluor 680), as shown in Fig. 6, or were labelled with anti-LC3B (Alexa Fluor 488), as shown in Supp. Fig. 6c. In all images, cells were stained with DAPI to label nuclei. Fig7_GALNT2_GLG1_TM9SF2_TGOLN2_GOLIM4_SDF4: Widefield imaging of HeLa cells left untreated in full growth medium (0h) or cultured in the presence of 100 nM BafA for 0.5, 1, 2, 4, 6 or 8 hours, before fixation. Cells were labelled with anti-GALNT2 (Alexa Fluor 647) in combination with either anti-GLG1, anti-TM9SF2, anti-TGOLN2, anti-GOLIM4 or anti-SDF4 (Alexa Fluor 555). In all images, cells were stained with DAPI and phalloidin-488 to label nuclei and cytoplasm, respectively.

10.5281/zenodo.8197844

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MaxQuant goes Linux

Nature Methods (2018)

Pavel Sinitcyn Shivani Tiwary Jan Daniel Rudolph Petra Gutenbrunner Christoph Wichmann

10.1038/s41592-018-0018-y

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Citations (46)

Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry

Nature Communications (2016)

Michal Bassani‐Sternberg Eva Bräunlein Richard Klar Thomas Engleitner Pavel Sinitcyn

Abstract Although mutations may represent attractive targets for immunotherapy, direct identification of mutated peptide ligands isolated from human leucocyte antigens (HLA) on the surface of native tumour tissue has so far not been successful. Using advanced mass spectrometry (MS) analysis, we survey the melanoma-associated immunopeptidome to a depth of 95,500 patient-presented peptides. We thereby discover a large spectrum of attractive target antigen candidates including cancer testis antigens and phosphopeptides. Most importantly, we identify peptide ligands presented on native tumour tissue samples harbouring somatic mutations. Four of eleven mutated ligands prove to be immunogenic by neoantigen-specific T-cell responses. Moreover, tumour-reactive T cells with specificity for selected neoantigens identified by MS are detected in the patient’s tumour and peripheral blood. We conclude that direct identification of mutated peptide ligands from primary tumour material by MS is possible and yields true neoepitopes with high relevance for immunotherapeutic strategies in cancer.

Cancer Immunotherapy

10.1038/ncomms13404

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Citations (643)

Systematic benchmarking of mass spectrometry-based antibody sequencing reveals methodological biases

bioRxiv (Cold Spring Harbor Laboratory) (2024)

Maria Chernigovskaya Khang Lê Quý Maria Stensland Sachin Singh Rowan Nelson

Abstract The circulating antibody repertoire is crucial for immune protection, holding significant immunological and biotechnological value. While bottom-up mass spectrometry (MS) is the most widely used proteomics technique for profiling the sequence diversity of circulating antibodies (Ab-seq), it has not been thoroughly benchmarked. We quantified the replicability and robustness of Ab-seq using six monoclonal antibodies with known protein sequences in 70 different combinations of concentration and oligoclonality, both with and without polyclonal serum IgG background. Each combination underwent four protease treatments and was analyzed across four experimental and three technical replicates, totaling 3,360 LC-MS/MS runs. We quantified the dependence of MS-based Ab-seq identification on antibody sequence, concentration, protease, background signal diversity, and bioinformatics setups. Integrating the data from experimental replicates, proteases, and bioinformatics tools enhanced antibody identification. De novo peptide sequencing showed similar performance to database-dependent methods for higher antibody concentrations, but de novo antibody reconstruction remains challenging. Our work provides a foundational resource for the field of MS-based antibody profiling.

Benchmarking

10.1101/2024.11.11.622451

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Multi-targeted therapy resistance via drug-induced secretome fucosylation

eLife (2023)

Mark Borris D. Aldonza Junghwa Cha Insung Yong Jayoung Ku Pavel Sinitcyn

Cancer secretome is a reservoir for aberrant glycosylation. How therapies alter this post- translational cancer hallmark and the consequences thereof remain elusive. Here, we show that an elevated secretome fucosylation is a pan-cancer signature of both response and resistance to multiple targeted therapies. Large-scale pharmacogenomics revealed that fucosylation genes display widespread association with resistance to these therapies. In cancer cell cultures, xenograft mouse models, and patients, targeted kinase inhibitors distinctively induced core fucosylation of secreted proteins less than 60 kDa. Label-free proteomics of N-glycoproteomes identified fucosylation of the antioxidant PON1 as a critical component of the therapy-induced secretome (TIS). N-glycosylation of TIS and target core fucosylation of PON1 are mediated by the fucose salvage-FUT8-SLC35C1 axis with PON3 directly modulating GDP-Fuc transfer on PON1 scaffolds. Core fucosylation in the Golgi impacts PON1 stability and folding prior to secretion, promoting a more degradation-resistant PON1. Global and PON1-specific secretome de-N-glycosylation both limited the expansion of resistant clones in a tumor regression model. We defined the resistance-associated transcription factors (TFs) and genes modulated by the N-glycosylated TIS via a focused and transcriptome-wide analyses. These genes characterize the oxidative stress, inflammatory niche, and unfolded protein response as important factors for this modulation. Our findings demonstrate that core fucosylation is a common modification indirectly induced by targeted therapies that paradoxically promotes resistance.

Fucosylation

10.7554/elife.75191

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Citations (6)

Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer

Nature Communications (2024)

Noah M. Lancaster Pavel Sinitcyn Patrick Forny Trenton M. Peters-Clarke Caroline Fecher

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method, we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology is benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We apply this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detect 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of phosphorylation events relevant to mitochondrial and brain biology.

Orbitrap

10.1038/s41467-024-51274-0

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Citations (8)

Deep and fast label-free Dynamic Organellar Mapping - Imaging data

Zenodo (CERN European Organization for Nuclear Research) (2023)

Julia P. Schessner Vincent Albrecht Alexandra K. Davies Pavel Sinitcyn Georg H. H. Borner

10.5281/zenodo.8197843

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Citations (0)