Rudolf Aebersold

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Aebersold

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Rudolf

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0000-0002-9576-3267

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Publications 1 - 10 of 120

The Tumor Profiler Study: integrated, multi-omic, functional tumor profiling for clinical decision support
Irmisch, Anja; Bonilla, Ximena; Lehmann, Kjong-Van; et al. (2021)
Cancer Cell
The application and integration of molecular profiling technologies create novel opportunities for personalized medicine. Here, we introduce the Tumor Profiler Study, an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease.
Feasibility of multiomics tumor profiling for guiding treatment of melanoma
Miglino, Nicola; Toussaint, Nora Christina; Ring, Alexander; et al. (2025)
Nature Medicine
There is limited evidence supporting the feasibility of using omics and functional technologies to inform treatment decisions. Here we present results from a cohort of 116 melanoma patients in the prospective, multicentric observational Tumor Profiler (TuPro) precision oncology project. Nine independent technologies, mostly at single-cell level, were used to analyze 126 patient samples, generating up to 500 Gb of data per sample (40,000 potential markers) within 4 weeks. Among established and experimental markers, the molecular tumor board selected 54 to inform its treatment recommendations. In 75% of cases, TuPro-based data were judged to be useful in informing recommendations. Patients received either standard of care (SOC) treatments or highly individualized, polybiomarker-driven treatments (beyond SOC). The objective response rate in difficult-to-treat palliative, beyond SOC patients (n = 37) was 38%, with a disease control rate of 54%. Progression-free survival of patients with TuPro-informed therapy decisions was 6.04 months, (95% confidence interval, 3.75-12.06) and 5.35 months (95% confidence interval, 2.89-12.06) in $\geq$ third therapy lines. The proof-of-concept TuPro project demonstrated the feasibility and relevance of omics-based tumor profiling to support data-guided clinical decision-making.
Longevity interventions modulate mechanotransduction and extracellular matrix homeostasis in C. elegans
Teuscher, Alina C.; Statzer, Cyril; Goyala, Anita; et al. (2024)
Nature Communications
Dysfunctional extracellular matrices (ECM) contribute to aging and disease. Repairing dysfunctional ECM could potentially prevent age-related pathologies. Interventions promoting longevity also impact ECM gene expression. However, the role of ECM composition changes in healthy aging remains unclear. Here we perform proteomics and in-vivo monitoring to systematically investigate ECM composition (matreotype) during aging in C. elegans revealing three distinct collagen dynamics. Longevity interventions slow age-related collagen stiffening and prolong the expression of collagens that are turned over. These prolonged collagen dynamics are mediated by a mechanical feedback loop of hemidesmosome-containing structures that span from the exoskeletal ECM through the hypodermis, basement membrane ECM, to the muscles, coupling mechanical forces to adjust ECM gene expression and longevity via the transcriptional co-activator YAP-1 across tissues. Our results provide in-vivo evidence that coordinated ECM remodeling through mechanotransduction is required and sufficient to promote longevity, offering potential avenues for interventions targeting ECM dynamics.
Single-cell landscape of innate and acquired drug resistance in acute myeloid leukemia
Wegmann, Rebekka; Bonilla Bustillo, Ximena; Casanova, Ruben; et al. (2024)
Nature Communications
Deep single-cell multi-omic profiling offers a promising approach to understand and overcome drug resistance in relapsed or refractory (rr) acute myeloid leukemia (AML). Here, we combine single-cell ex vivo drug profiling (pharmacoscopy) with single-cell and bulk DNA, RNA, and protein analyses, alongside clinical data from 21 rrAML patients. Unsupervised data integration reveals reduced ex vivo response to the Bcl-2 inhibitor venetoclax (VEN) in patients treated with both a hypomethylating agent (HMA) and VEN, compared to those pre-exposed to chemotherapy or HMA alone. Integrative analysis identifies both known and unreported mechanisms of innate and treatment-related VEN resistance and suggests alternative treatments, like targeting increased proliferation with the PLK inhibitor volasertib. Additionally, high CD36 expression in VEN-resistant blasts associates with sensitivity to CD36-targeted antibody treatment ex vivo. This study demonstrates how single-cell multi-omic profiling can uncover drug resistance mechanisms and treatment vulnerabilities, providing a valuable resource for future AML research.
Nucleotide-amino acid π-stacking interactions initiate photo cross-linking in RNA-protein complexes
Knörlein, Anna; Sarnowski, Chris P.; de Vries, Tebbe; et al. (2022)
Nature Communications
Photo-induced cross-linking is a mainstay technique to characterize RNA-protein interactions. However, UV-induced cross-linking between RNA and proteins at “zero-distance” is poorly understood. Here, we investigate cross-linking of the RBFOX alternative splicing factor with its hepta-ribonucleotide binding element as a model system. We examine the influence of nucleobase, nucleotide position and amino acid composition using CLIR-MS technology (crosslinking-of-isotope-labelled-RNA-and-tandem-mass-spectrometry), that locates cross-links on RNA and protein with site-specific resolution. Surprisingly, cross-linking occurs only at nucleotides that are π-stacked to phenylalanines. Notably, this π-stacking interaction is also necessary for the amino-acids flanking phenylalanines to partake in UV-cross-linking. We confirmed these observations in several published datasets where cross-linking sites could be mapped to a high resolution structure. We hypothesize that π-stacking to aromatic amino acids activates cross-linking in RNA-protein complexes, whereafter nucleotide and peptide radicals recombine. These findings will facilitate interpretation of cross-linking data from structural studies and from genome-wide datasets generated using CLIP (cross-linking-and -immunoprecipitation) methods.
Using stable isotope tagging and mass spectrometry to characterize protein complexes and to detect changes in their composition
Ranish, Jeffrey A.; Brand, Marjorie; Aebersold, Rudolf (2007)
Methods in Molecular Biology ~ Quantitative Proteomics by Mass Spectrometry
One of the primary goals of proteomics is the description of the composition, dynamics, and connections of the multiprotein modules that catalyze a wide range of biological functions in cells. Mass spectrometry (MS) has proven to be an extremely powerful tool for characterizing the composition of purified complexes. However, because MS is not a quantitative technique, the usefulness of the data is limited. For example, without quantitative measurements, it is difficult to detect dynamic changes in complex composition, and it can be difficult to distinguish bona fide complex components from nonspecifically copurifying proteins. In this chapter, we describe a strategy for characterizing the composition of protein complexes and their dynamic changes in composition by combining affinity purification approaches with stable isotope tagging and MS. The use of software tools for statistical analysis of the data is also described.
Targeted Data Extraction of the MS/MS Spectra Generated by Data-independent Acquisition: A New Concept for Consistent and Accurate Proteome Analysis
Gillet, Ludovic C.; Navarro, Pedro; Tate, Stephen; et al. (2012)
Molecular & Cellular Proteomics
Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.
Integrated multi-omics reveals anaplerotic insufficiency in methylmalonyl-CoA mutase deficiency
Forny, Patrick; Bonilla Bustillo, Ximena; Lamparter, David; et al. (2022)
medRxiv
Multi-layered omics approaches can help define relationships between genetic factors, biochemical processes and phenotypes thus extending research of inherited diseases beyond identifying their monogenic cause 1. We implemented a multi-layered omics approach for the inherited metabolic disorder methylmalonic aciduria (MMA). We performed whole genome sequencing, transcriptomic sequencing, and mass spectrometry-based proteotyping from matched primary fibroblast samples of 230 individuals (210 affected, 20 controls) and related the molecular data to 105 phenotypic features. Integrative analysis identified a molecular diagnosis for 84% (177/210) of affected individuals, the majority (148) of whom had pathogenic variants in methylmalonyl-CoA mutase (MMUT). Untargeted analysis of all three omics layers revealed dysregulation of the TCA cycle and surrounding metabolic pathways, a finding that was further corroborated by multi-organ metabolomics of a hemizygous Mmut mouse model. Integration of phenotypic disease severity indicated downregulation of oxoglutarate dehydrogenase and upregulation of glutamate dehydrogenase, two proteins involved in glutamine anaplerosis of the TCA cycle. The relevance of disturbances in this pathway was supported by metabolomics and isotope tracing studies which showed decreased glutamine-derived anaplerosis in MMA. We further identified MMUT to physically interact with both, oxoglutarate dehydrogenase complex components and glutamate dehydrogenase providing evidence for a multi-protein metabolon that orchestrates TCA cycle anaplerosis. This study emphasizes the utility of a multi-modal omics approach to investigate metabolic diseases and highlights glutamine anaplerosis as a potential therapeutic intervention point in MMA.Take home message Combination of integrative multi-omics technologies with clinical and biochemical features leads to an increased diagnostic rate compared to genome sequencing alone and identifies anaplerotic rewiring as a targetable feature of the rare inborn error of metabolism methylmalonic aciduria.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis project was funded by the ETH domain strategic focus area Personalized Health and Related Technology (PHRT; https://www.sfa-phrt.ch).Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The Ethics Committee of the Canton of Zurich, Switzerland gave ethical approval for this work.I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data produced in the present study are available upon reasonable request to the authors.
A highly sensitive protein-RNA cross-linking mass spectrometry workflow with enhanced structural modeling potential
Sarnowski, Chris P.; Knörlein, Anna; de Vries, Tebbe; et al. (2025)
Nucleic Acids Research
Protein-RNA interactions underpin many critical biological processes, demanding the development of technologies to precisely characterize their nature and functions. Many such technologies depend upon cross-linking under mild irradiation conditions to stabilize contacts between amino acids and nucleobases; for example, the cross-linking of stable isotope labelled RNA coupled to mass spectrometry (CLIR-MS) method. A deeper understanding of the CLIR-MS workflow is required to maximize its impact for structural biology, particularly addressing the low abundance of cross-linking products and the information content of spatial/geometric restraints reflected by a cross-link. Here, we present a vastly improved CLIR-MS pipeline that features enhanced sample preparation, data acquisition and interpretation. These advances significantly increase the number of detected cross-link products per sample. We demonstrate that the procedure is robust against variation of key experimental parameters, including irradiation energy and temperature. Using this improved protocol on four protein-RNA complexes representing canonical and non-canonical RNA-binding domains, we propose for the first time the distances encoded by protein-RNA cross-links, enabling their use as structural restraints. We also compared the cross-linking of canonical RNA with 4-thiouracil-labeled counterparts, showing slight, but noticeable differences. The improved understanding of protein-RNA cross-links refines their structural interpretation and facilitates the adoption of the method in integrative/hybrid structural biology.
Correction: An oncogene addiction phosphorylation signature and its derived scores inform tumor responsiveness to targeted therapies (vol 80, 6, 2022)
Orlando, Eleonora; Medo, Matúš; Bensimon, Ariel; et al. (2023)
Cellular and Molecular Life Sciences

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