Biology subjects

Hoopmann, M. R.

Publications and source records attributed to Hoopmann, M. R..

12 recordsLinked to original sources

bioRxiv2026

Extending structural surfaceomics to identify aberrant conformations of tumor surface proteins as potential immunotherapy targets

The complement of tumor cell surface proteins, or "surfaceome", is a rich source of potential immunotherapy targets. To move beyond expression-based target discovery, we previously described "structural surfaceomics," combining crosslinking mass spectrometry (XL-MS) with surface protein biotinylation to identify conformation-selective targets. In our prior work, we applied this method to a single model of acute myeloid leukemia (AML), identifying active integrin beta-2 as a promising target. Here, we expand structural surfaceomics to identify additional immunotherapy targets and surface protein biology across additional models of AML, multiple myeloma, and prostate cancer, as well as donor peripheral blood mononuclear cells. Utilizing these models and different chemical crosslinkers, we compile an extensive database of 5,209 crosslinks. We characterize both shared and unique crosslink-based features, identifying 1,612 disease model-specific crosslinks, including 212 potentially defining tumor-specific conformations based on distance constraint violations relative to AlphaFold predictions. We further implement a suite of emerging modeling tools to predict tumor-specific protein structures. We probe crosslinking patterns suggesting multiple myeloma-specific CD48 and AML-specific integrin 1/{beta}4 heterodimer conformations. This work establishes a resource for cancer structural biology by implementation of structural surfaceomics. Our findings also point toward more realistic protein design models, potentially enabling systematic detection of targetable cancer-specific epitopes for next-generation immunotherapies.

cancer biology↗

bioRxiv2025

Nova: A library for rapid development of mass spectrometry software applications

Nova is a software library for the reading, writing, and management of mass spectrometry data natively in the C# language. It complements similar software libraries ubiquitously used in application development for C++, Python, and Java. Few software libraries and resources for mass spectrometry data analysis have been developed for C# relative to other languages. C#, however, remains the dominant language of choice for development of real time mass spectrometry (RTMS) analysis and instrument control applications, illustrating the need for native C# libraries when developing RTMS software. Nova provides fast, easy-to-use structures and classes built upon interfaces that support open community standards, and are easily extensible for current or future mass spectrometry software development needs.

biochemistry↗

bioRxiv2025

Assessment of Reported Error Rates in Crosslinking Mass Spectrometry

We benchmarked eight software tools in crosslinking mass spectrometry (MS) to evaluate their accuracy in detecting protein-protein interactions. Whereas about half performed reliably, others reported up to 31-fold more false interactions than indicated by their reported false discovery rates. During this community-driven effort, we helped correct one of the poorer-performing tools. Our findings demonstrate that, with robust algorithms, crosslinking MS can deliver highly dependable insights into biological systems.

bioinformatics↗

bioRxiv2024

Limelight - An open, web-based tool for visualizing, sharing, and analyzing mass spectrometry data from DDA pipelines

Liquid chromatography-tandem mass spectrometry employing data-dependent acquisition (DDA) is a mature, widely used proteomics technique routinely applied to proteome profiling, protein-protein interaction studies, biomarker discovery, and protein modification analysis. Numerous tools exist for searching DDA data and myriad file formats are output as results. While some search and post processing tools include data visualization features to aid biological interpretation, they are often limited or tied to specific software pipelines. This restricts the accessibility, sharing and interpretation of data, and hinders comparison of results between different software pipelines. We developed Limelight, an easy-to-use, open-source, freely available tool that provides data sharing, analysis and visualization and is not tied to any specific software pipeline. Limelight is a data visualization tool specifically designed to provide access to the whole "data stack", from raw and annotated scan data to peptide-spectrum matches, quality control, peptides, proteins, and modifications. Limelight is designed from the ground up for sharing and collaboration and to support data from any DDA workflow. We provide tools to import data from many widely used open-mass and closed-mass search software workflows. Limelight helps maximize the utility of data by providing an easy-to-use interface for finding and interpreting data, all using the native scores from respective workflows.

bioinformatics↗

bioRxiv2022

Structural surfaceomics reveals an AML-specific conformation of Integrin-β2 as a CAR-T therapy target

Safely expanding indications for cellular therapies has been challenging given a lack of highly cancer-specific surface markers. Here, we explore the hypothesis that tumor cells express cancer-specific surface protein conformations, invisible to standard target discovery pipelines evaluating gene or protein expression, that can be identified and immunotherapeutically targeted. We term this strategy, integrating cross-linking mass spectrometry (XL-MS) with glycoprotein surface capture, "structural surfaceomics". As a proof of principle, we apply this technology to acute myeloid leukemia, a hematologic malignancy with dismal outcomes and no known optimal immunotherapy target. We identify the activated conformation of integrin-{beta}2 as a structurally-defined, widely-expressed, AML-specific target. We develop and characterize recombinant antibodies to this protein conformation, and show that chimeric antigen receptor (CAR) T-cells eliminate AML cells and patient-derived xenografts without notable toxicity versus normal hematopoietic cells. Our findings validate an AML conformation-specific target antigen while demonstrating a toolkit for applying these strategies more broadly.

cancer biology↗

bioRxiv2022

The Crux toolkit for analysis of bottom-up tandem mass spectrometry proteomics data

The Crux tandem mass spectrometry data analysis toolkit provides a collection of algorithms for analyzing bottom-up proteomics tandem mass spectrometry data. Many publications have described various individual components of Crux, but a comprehensive summary has not been published since 2014. The goal of this work is to summarize the functionality of Crux, focusing on developments since 2014. We begin with empirical results demonstrating our recently implemented speedups to the Tide search engine. Other new features include a new score function in Tide, two new confidence estimation procedures, as well as three new tools: Param-medic for estimating search parameters directly from mass spectrometry data, Kojak for searching cross-linked mass spectra, and DIAmeter for searching data independent acquisition data against a sequence database.

bioinformatics↗

bioRxiv2021

Discovery and visualization of uncharacterized drug-protein adducts using mass spectrometry.

Drugs are often metabolized to reactive intermediates that form protein adducts. Adducts can inhibit protein activity, elicit immune responses, and cause life threatening adverse drug reactions. The masses of reactive metabolites are frequently unknown, rendering traditional mass spectrometry-based proteomics incapable of adduct identification. Here, we present Magnum, an open-mass search algorithm optimized for adduct identification, and Limelight, a web-based data processing package for analysis and visualization of data from all existing algorithms. Limelight incorporates tools for sample comparisons and xenobiotic-adduct discovery. We validate our tools with two drug/protein combinations and apply our workflow to identify novel xenobiotic-protein adducts in CYP3A4. Our new methods and software enable accurate identification of xenobiotic-protein adducts with no prior knowledge of adduct masses or protein targets. Magnum outperforms existing tools in xenobiotic-protein adduct discovery, while Limelight fulfills a major need in the rapidly developing field of open-mass searching, which until now lacked comprehensive data visualization tools.

pharmacology and toxicology↗

bioRxiv2021

Plasmodium falciparum Calcium Dependent Protein Kinase 4 is critical for male gametogenesis and transmission to the mosquito vector

Gametocytes of the malaria parasite Plasmodium are taken up by the mosquito vector with an infectious blood meal, representing a critical stage for parasite transmission. Calcium dependent protein kinases (CDPKs) play key roles in calcium-mediated signaling across the complex life cycle of the parasite. We sought to understand their role in human parasite transmission from the host to the mosquito vector and thus investigated the role of the human-infective parasite Plasmodium falciparum CDPK4 in the parasite life cycle. P. falciparum cdpk4- parasites created by targeted gene deletion showed no effect in blood stage development or gametocyte development. However, cdpk4- parasites showed a severe defect in male gametogenesis and the emergence of flagellated male gametes. To understand the molecular underpinnings of this defect, we performed mass spectrometry-based phosphoproteomic analyses of wild type and Plasmodium falciparum cdpk4- late gametocyte stages, to identify key CDPK4-mediated phosphorylation events that may be important for the regulation of male gametogenesis. We further employed in vitro assays to identify these putative substrates of Plasmodium falciparum CDPK4. This indicated that CDPK4 regulates male gametogenesis by directly or indirectly controlling key essential events such as DNA replication, mRNA translation and cell motility. Taken together, our work demonstrates that PfCDPK4 is a central kinase that regulates exflagellation, and thereby is critical for parasite transmission to the mosquito vector. IMPORTANCETransmission of the malaria parasite to the mosquito vector is critical for the completion of the sexual stage of the parasite life cycle and is dependent on the release of male gametes from the gametocyte body inside the mosquito midgut. In the present study, we demonstrate that PfCDPK4 is critical for male gametogenesis and is involved in phosphorylation of proteins essential for male gamete emergence. Targeting PfCDPK4 and its substrates may provide insights into achieving effective malaria transmission-blocking strategies.

microbiology↗

bioRxiv2020

A druggable oxidative folding pathway in the endoplasmic reticulum of human malaria parasites

Malaria remains a major global health problem, and there exists a constant need to identify druggable weaknesses in P. falciparum biology. The endoplasmic reticulum (ER) has many essential roles in the asexual lifecycle and may offer new drug targets, but it remains critically understudied. We generated conditional mutants of the putative redox-active, ER chaperone PfJ2, and show that it is essential for parasite survival. Using a redox-active cysteine crosslinker, we identify its substrates to be other mediators of oxidative folding, PfPDI8 and PfPDI11, suggesting a redox-regulatory role for PfJ2. Knockdown of these protein disulfide isomerases in PfJ2 conditional mutants show that PfPDI11 is not essential, while PfPDI8 is essential for asexual growth and may work in a complex with PfJ2 and other ER chaperones. Finally, we show that these redox interactions in the parasite ER are sensitive to small molecule inhibition. Together these data build a model for how oxidative folding occurs in the P. falciparum ER and demonstrate its suitability for antimalarial drug development.

microbiology↗

bioRxiv2019

PTMProphet: Fast and Accurate Mass Modification Localization for the Trans-Proteomic Pipeline

Spectral matching sequence database search engines commonly used on mass spectrometry-based proteomics experiments excel at identifying peptide sequence ions, and in addition, possible sequence ions carrying post-translational modifications (PTMs), but most do not provide confidence metrics for the exact localization of those PTMs when several possible sites are available. Localization is absolutely required for downstream molecular cell biology analysis of PTM function in vitro and in vivo. Therefore, we developed PTMProphet, a free and open-source software tool integrated into the Trans-Proteomic Pipeline, which reanalyzes identified spectra from any search engine for which pepXML output is available to provide localization confidence to enable appropriate further characterization of biologic events. Localization of any type of mass modification (e.g., phosphorylation) is supported. PTMProphet applies Bayesian mixture models to compute probabilities for each site/peptide spectrum match where a PTM has been identified. These probabilities can be combined to compute a global false localization rate at any threshold to guide downstream analysis. We describe the PTMProphet tool, its underlying algorithms and demonstrate its performance on ground-truth synthetic peptide reference datasets, one previously published small dataset, one new larger dataset, and also on a previously published phospho-enriched dataset where the correct sites of modification are unknown. Data have been deposited to ProteomeXchange with identifier PXD013210.\n\nO_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

bioinformatics↗

bioRxiv2018

Cross-linking/Mass Spectrometry: A Community-Wide, Comparative Study Towards Establishing Best Practice Guidelines

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has largely increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats that are generally accepted in the field and that have shown to lead to high-quality results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. From the results obtained, common protocols will be established. Our study serves as basis for establishing best practice guidelines in the field for conducting cross-linking experiments, performing data analysis, and reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.

biochemistry↗

bioRxiv2017

A protein standard that emulates homology for the characterization of protein inference algorithms

A natural way to benchmark the performance of an analytical experimental setup is to use samples of known content, and see to what degree one can correctly infer the content of such a sample from the data. For shotgun proteomics, one of the inherent problems of interpreting data is that the measured analytes are peptides and not the actual proteins themselves. As some proteins share proteolytic peptides, there might be more than one possible causative set of proteins resulting in a given set of peptides and there is a need for mechanisms that infer proteins from lists of detected peptides. A weakness of commercially available samples of known content is that they consist of proteins that are deliberately selected for producing tryptic peptides that are unique to a single protein. Unfortunately, such samples do not expose any complications in protein inference. For a realistic benchmark of protein inference procedures, there is, therefore, a need for samples of known content where the present proteins share peptides with known absent proteins. Here, we present such a standard, that is based on E. coli expressed human protein fragments. To illustrate the usage of this standard, we benchmark a set of different protein inference procedures on the data. We observe that inference procedures excluding shared peptides provide more accurate estimates of errors compared to methods that include information from shared peptides, while still giving a reasonable performance in terms of the number of identified proteins. We also demonstrate that using a sample of known protein content without proteins with shared tryptic peptides can give a false sense of accuracy for many protein inference methods.

bioinformatics↗