Marc van Oostrum

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van Oostrum

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Marc

ORCID

0000-0001-8747-9787

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Publications 1 - 10 of 10

Proteogenetic drug response profiling elucidates targetable vulnerabilities of myelofibrosis
Wildschut, Mattheus Henricus Ernst; Mena, Julien; Dördelmann, Cyril; et al. (2023)
Nature Communications
Myelofibrosis is a hematopoietic stem cell disorder belonging to the myeloproliferative neoplasms. Myelofibrosis patients frequently carry driver mutations in either JAK2 or Calreticulin (CALR) and have limited therapeutic options. Here, we integrate ex vivo drug response and proteotype analyses across myelofibrosis patient cohorts to discover targetable vulnerabilities and associated therapeutic strategies. Drug sensitivities of mutated and progenitor cells were measured in patient blood using high-content imaging and single-cell deep learning-based analyses. Integration with matched molecular profiling revealed three targetable vulnerabilities. First, CALR mutations drive BET and HDAC inhibitor sensitivity, particularly in the absence of high Ras pathway protein levels. Second, an MCM complex-high proliferative signature corresponds to advanced disease and sensitivity to drugs targeting pro-survival signaling and DNA replication. Third, homozygous CALR mutations result in high endoplasmic reticulum (ER) stress, responding to ER stressors and unfolded protein response inhibition. Overall, our integrated analyses provide a molecularly motivated roadmap for individualized myelofibrosis patient treatment.
A tissue-specific atlas of protein-protein associations enables prioritization of candidate disease genes
Trip, Diederik S. Laman; van Oostrum, Marc; Memon, Danish; et al. (2025)
Nature Biotechnology
Despite progress in mapping protein-protein interactions, their tissue specificity is understudied. Here, given that protein coabundance is predictive of functional association, we compiled and analyzed protein abundance data of 7,811 proteomic samples from 11 human tissues to produce an atlas of tissue-specific protein associations. We find that this method recapitulates known protein complexes and the larger structural organization of the cell. Interactions of stable protein complexes are well preserved across tissues, while cell-type-specific cellular structures, such as synaptic components, are found to represent a substantial driver of differences between tissues. Over 25% of associations are tissue specific, of which <7% are because of differences in gene expression. We validate protein associations for the brain through cofractionation experiments in synaptosomes, curation of brain-derived pulldown data and AlphaFold2 modeling. We also construct a network of brain interactions for schizophrenia-related genes, indicating that our approach can functionally prioritize candidate disease genes in loci linked to brain disorders.
The in silico human surfaceome
Bausch-Fluck, Damaris; Goldmann, Ulrich; Müller, Sebastian; et al. (2018)
Proceedings of the National Academy of Sciences of the United States of America
Cell-surface proteins are of great biomedical importance, as demonstrated by the fact that 66% of approved human drugs listed in the DrugBank database target a cell-surface protein. Despite this biomedical relevance, there has been no comprehensive assessment of the human surfaceome, and only a fraction of the predicted 5,000 human transmembrane proteins have been shown to be located at the plasma membrane. To enable analysis of the human surfaceome, we developed the surfaceome predictor SURFY, based on machine learning. As a training set, we used experimentally verified high-confidence cell-surface proteins from the Cell Surface Protein Atlas (CSPA) and trained a random forest classifier on 131 features per protein and, specifically, per topological domain. SURFY was used to predict a human surfaceome of 2,886 proteins with an accuracy of 93.5%, which shows excellent overlap with known cell-surface protein classes (i.e., receptors). In deposited mRNA data, we found that between 543 and 1,100 surfaceome genes were expressed in cancer cell lines and maximally 1,700 surfaceome genes were expressed in embryonic stem cells and derivative lines. Thus, the surfaceome diversity depends on cell type and appears to be more dynamic than the nonsurface proteome. To make the predicted surfaceome readily accessible to the research community, we provide visualization tools for intuitive interrogation (wlab.ethz.ch/surfaceome). The in silico surfaceome enables the filtering of data generated by multiomics screens and supports the elucidation of the surfaceome nanoscale organization.
In vitro quantification of botulinum neurotoxin type A1 using immobilized nerve cell-mimicking nanoreactors in a microfluidic platform
Weingart, Oliver G.; Eyer, Klaus; Lüchtenborg, Christian; et al. (2019)
The Analyst
Enzymatic dissociation induces transcriptional and proteotype bias in brain cell populations
Mattei, Daniele; Ivanov, Andranik; van Oostrum, Marc; et al. (2020)
International Journal of Molecular Sciences
Different cell isolation techniques exist for transcriptomic and proteotype profiling of brain cells. Here, we provide a systematic investigation of the influence of different cell isolation protocols on transcriptional and proteotype profiles in mouse brain tissue by taking into account single-cell transcriptomics of brain cells, proteotypes of microglia and astrocytes, and flow cytometric analysis of microglia. We show that standard enzymatic digestion of brain tissue at 37 °C induces profound and consistent alterations in the transcriptome and proteotype of neuronal and glial cells, as compared to an optimized mechanical dissociation protocol at 4 °C. These findings emphasize the risk of introducing technical biases and biological artifacts when implementing enzymatic digestion-based isolation methods for brain cell analyses. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Classification of mouse B cell types using surfaceome proteotype maps
van Oostrum, Marc; Müller, Maik; Klein, Fabian; et al. (2019)
Nature Communications
System-wide quantification of the cell surface proteotype and identification of extracellular glycosylation sites is challenging when samples are limited. Here, we miniaturize and automate the previously described Cell Surface Capture (CSC) technology, increasing sensitivity, reproducibility and throughput. We use this technology, which we call autoCSC, to create population-specific surfaceome maps of developing mouse B cells and use targeted flow cytometry to uncover developmental cell subpopulations.
Dynamics and Nanoscale Organization of the Neuronal Surface Proteotype
van Oostrum, Marc (2019)
Light-mediated discovery of surfaceome nanoscale organization and intercellular receptor interaction networks
Müller, Maik; Gräbnitz, Fabienne; Barandun, Niculò; et al. (2021)
Nature Communications
The molecular nanoscale organization of the surfaceome is a fundamental regulator of cellular signaling in health and disease. Technologies for mapping the spatial relationships of cell surface receptors and their extracellular signaling synapses would unlock theranostic opportunities to target protein communities and the possibility to engineer extracellular signaling. Here, we develop an optoproteomic technology termed LUX-MS that enables the targeted elucidation of acute protein interactions on and in between living cells using light-controlled singlet oxygen generators (SOG). By using SOG-coupled antibodies, small molecule drugs, biologics and intact viral particles, we demonstrate the ability of LUX-MS to decode ligand receptor interactions across organisms and to discover surfaceome receptor nanoscale organization with direct implications for drug action. Furthermore, by coupling SOG to antigens we achieved light-controlled molecular mapping of intercellular signaling within functional immune synapses between antigen-presenting cells and CD8+ T cells providing insights into T cell activation with spatiotemporal specificity. LUX-MS based decoding of surfaceome signaling architectures thereby provides a molecular framework for the rational development of theranostic strategies.
Proteomics-Based Monitoring of Pathway Activity Reveals that Blocking Diacylglycerol Biosynthesis Rescues from Alpha-Synuclein Toxicity
Soste, Martin; Charmpi, Konstantina; Lampert, Fabienne; et al. (2019)
Cell Systems
Proteinaceous inclusions containing alpha-synuclein (α-Syn) have been implicated in neuronal toxicity in Parkinson’s disease, but the pathways that modulate toxicity remain enigmatic. Here, we used a targeted proteomic assay to simultaneously measure 269 pathway activation markers and proteins deregulated by α-Syn expression across a panel of 33 Saccharomyces cerevisiae strains that genetically modulate α-Syn toxicity. Applying multidimensional linear regression analysis to these data predicted Pah1, a phosphatase that catalyzes conversion of phosphatidic acid to diacylglycerol at the endoplasmic reticulum membrane, as an effector of rescue. Follow-up studies demonstrated that inhibition of Pah1 activity ameliorates the toxic effects of α-Syn, indicate that the diacylglycerol branch of lipid metabolism could enhance α-Syn neuronal cytotoxicity, and suggest a link between α-Syn toxicity and the biology of lipid droplets.
Surfaceome dynamics reveal proteostasis-independent reorganization of neuronal surface proteins during development and synaptic plasticity
van Oostrum, Marc; Campbell, Benjamin; Seng, Charlotte; et al. (2020)
Nature Communications
Neurons are highly compartmentalized cells with tightly controlled subcellular protein organization. While brain transcriptome, connectome and global proteome maps are being generated, system-wide analysis of temporal protein dynamics at the subcellular level are currently lacking. Here, we perform a temporally-resolved surfaceome analysis of primary neuron cultures and reveal dynamic surface protein clusters that reflect the functional requirements during distinct stages of neuronal development. Direct comparison of surface and total protein pools during development and homeostatic synaptic scaling demonstrates system-wide proteostasis-independent remodeling of the neuronal surface, illustrating widespread regulation on the level of surface trafficking. Finally, quantitative analysis of the neuronal surface during chemical long-term potentiation (cLTP) reveals fast externalization of diverse classes of surface proteins beyond the AMPA receptor, providing avenues to investigate the requirement of exocytosis for LTP. Our resource (neurosurfaceome.ethz.ch) highlights the importance of subcellular resolution for systems-level understanding of cellular processes.

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Marc van Oostrum

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