Biology subjects

Wilhelm, M.

Publications and source records attributed to Wilhelm, M..

45 records · Page 3Linked to original sources

bioRxiv2022

p73 controls cell junction dynamics during sprouting angiogenesis and acts via Angiomotin

Preservation of blood vessels integrity, which is critical for normal physiology and organ function, is controlled at multiple levels, including endothelial junctions. However, the mechanism that controls the adequate assembly of endothelial cell junctions is not fully defined. Here we uncover TAp73 transcription factor as a vascular architect that orchestrates transcriptional programs involved in cell junction establishment and developmental blood vessel morphogenesis and identify Angiomotin (AMOT) as a TAp73 direct transcriptional target. Knockdown of p73 in endothelial cells not only results in decreased Angiomotin expression and localization at intercellular junctions, but also affects its downstream function regarding Yes-Associated Protein (YAP) cytoplasmic sequestration upon cell-cell contact. Analysis of adherens junctional morphology after p73-knockdown in human endothelial cells revealed striking alterations, particularly a sharp increase in serrated junctions and actin bundles appearing as stress fibers, both features associated with enhanced barrier permeability. In turn, stabilization of Angiomotin levels rescued those junctional defects, confirming that TAp73 controls endothelial junction dynamics, at least in part, through the regulation of Angiomotin. The observed defects in monolayer integrity were linked to hyperpermeability and reduced transendothelial electric resistance. Moreover, p73-knockout retinas showed a defective sprout morphology coupled to hemorrhages, highlighting the physiological relevance of p73 regulation in the maintenance of vessel integrity in vivo. We propose a new model in which TAp73 acts as a vascular architect integrating transcriptional programs that will impinge with Angiomotin/YAP signaling to maintain junctional dynamics and integrity, whilst balancing endothelial cell rearrangements in angiogenic vessels.

cell biology↗

bioRxiv2021

Novel allosteric mechanism of dual p53/MDM2 and p53/MDM4 inhibition by a small molecule

Restoration of the p53 tumor suppressor for personalised cancer therapy is a promising strategy. However, high-affinity MDM2 inhibitors have shown substantial side effects in clinical trials. Thus, elucidation of the molecular mechanisms of action of p53 reactivating molecules with alternative functional principle is of the utmost importance. Here, we report a discovery of a novel allosteric mechanism of p53 reactivation through targeting the p53 N-terminus which blocks both p53/MDM2 and p53/MDM4 interactions. Using biochemical assays and molecular docking, we identified the binding site of two p53 reactivating molecules, RITA and protoporphyrin IX (PpIX). Ion-mobility mass spectrometry revealed that the binding of RITA to serine 33 and serine 37 is responsible for inducing the allosteric shift in p53, which shields the MDM2 binding residues of p53 and prevents its interactions with MDM2 and MDM4. Our results point to an alternative mechanism of blocking p53 interaction with MDM2 and MDM4 and may pave the way for the development of novel allosteric inhibitors of p53/MDM2 and p53/MDM4 interactions. Contribution to the fieldGiven the immense importance of the p53 tumor suppressor for cancer, efforts have been made to identify p53 activators, which sterically inhibit MDM2. Because high-affinity MDM2 inhibitors are facing problems with considerable side effects, other approaches are needed to reactivate p53 for improved cancer therapy. The allosteric mechanism of action of p53 activator RITA, which we discovered, and its dependence on the oncogenic switch, is an unexpected turn in the p53 story. Our findings provide a basis for the development of p53 activators with a similar mode of functioning, either through the classical drug discovery route or through the drug repurposing approach. Allosteric modulators might have great potential as single agents, or in combination with the standard of care. Further, p53 modulators could serve as invaluable tools to better understand its biology.

biochemistry↗

bioRxiv2021

A proteomics sample metadata representation for multiomics integration, and big data analysis.

The amount of public proteomics data is increasing at an extraordinary rate. Hundreds of datasets are submitted each month to ProteomeXchange repositories, representing many types of proteomics studies, focusing on different aspects such as quantitative experiments, post-translational modifications, protein-protein interactions, or subcellular localization, among many others. For every proteomics dataset, two levels of data are captured: the dataset description, and the data files (encoded in different file formats). Whereas the dataset description and data file formats are supported by all ProteomeXchange partner repositories, there is no standardized format to properly describe the sample metadata and their relationship with the dataset files in a way that fully allows their understanding or re-analysis. It is left to the users choice whether to provide or not an ad hoc document containing this information. Therefore, in many cases, understanding the study design and data requires going back to the associated publication. This can be tedious and may be restricted in the case of non-open access publications. In many cases, this problem limits the generalization and reuse of public proteomics data. Here we present a standard representation for sample metadata tailored to proteomics datasets produced by the HUPO Proteomics Standards Initiative and supported by ProteomeXchange resources. We repurposed the existing data format MAGE-TAB used routinely in the transcriptomics field to represent and annotate proteomics datasets. MAGETAB-Proteomics defines a set of annotation rules that the datasets submitted to ProteomeXchange should follow, ranging from sample properties to data analysis protocols. We also introduce a crowdsourcing project that enabled the manual curation of over 200 public datasets using MAGE-TAB-Proteomics. In addition, we describe an ecosystem of tools and libraries that were developed to validate and submit sample metadata-related information to ProteomeXchange. We expect that these tools will improve the reproducibility of published results and facilitate the reanalysis and integration of public proteomics datasets.

bioinformatics↗

bioRxiv2020

An integrated multi-omic analysis of iPSC-derived motor neurons from C9ORF72 ALS patients

Neurodegenerative diseases present a challenge for systems biology, due to the lack of reliable animal models and the difficulties in obtaining samples from patients at early stages of disease, when interventions might be most effective. Studying induced pluripotent stem cell (iPSC)-derived neurons could overcome these challenges and dramatically accelerate and broaden therapeutic strategies. Here we undertook a network-based multi-omic characterization of iPSC-derived motor neurons from ALS patients carrying genetically dominant hexanucleotide expansions in C9orf72 to gain a deeper understanding of the relationship between DNA, RNA, epigenetics and protein in the same pool of tissue. ALS motor neurons showed the expected C9orf72-related alterations to specific nucleoporins and production of dipeptide repeats. RNA-seq, ATAC-seq and data-independent acquisition mass-spectrometry (DIA-MS) proteomics were then performed on the same motor neuron cultures. Using integrative computational methods that combined all of the omics, we discovered a number of novel dysregulated pathways including biological adhesion and extracellular matrix organization and disruption in other expected pathways such as RNA splicing and nuclear transport. We tested the relevance of these pathways in vivo in a C9orf72 Drosophila model, analyzing the data to determine which pathways were causing disease phenotypes and which were compensatory. We also confirmed that some pathways are altered in late-stage neurodegeneration by analyzing human postmortem C9 cervical spine data. To validate that these key pathways were integral to the C9 signature, we prepared a separate set of C9orf72 and control motor neuron cultures using a different differentiation protocol and applied the same methods. As expected, there were major overall differences between the differentiation protocols, especially at the level of in individual omics data. However, a number of the core dysregulated pathways remained significant using the integrated multiomic analysis. This new method of analyzing patient specific neural cultures allows the generation of disease-related hypotheses with a small number of patient lines which can be tested in larger cohorts of patients.

neuroscience↗

bioRxiv2020

Universal Spectrum Explorer: A standalone (web-)application for cross-resource spectrum comparison

Here we present the Universal Spectrum Explorer (USE), a web-based tool based on IPSA for cross-resource (peptide) spectrum visualization and comparison (https://www.proteomicsdb.org/use/). Mass spectra under investigation can either be provided manually by the user (table format), or automatically retrieved from online repositories supporting access to spectral data via the universal spectrum identifier (USI), or requested from other resources and services implementing a newly designed REST interface. As a proof of principle, we implemented such an interface in ProteomicsDB thereby allowing the retrieval of spectra acquired within the ProteomeTools project or real-time prediction of tandem mass spectra from the deep learning framework Prosit. Annotated mirror spectrum plots can be exported from the USE as editable scalable high quality vector graphics. The USE was designed and implemented with minimal external dependencies allowing local usage and integration into other websites (https://github.com/kusterlab/universal_spectrum_explorer).

bioinformatics↗

bioRxiv2020

PPM1D is a neuroblastoma oncogene and therapeutic target in childhood neural tumors.

Majority of cancers harbor alterations of the tumor suppressor TP53. However, childhood cancers, including unfavorable neuroblastoma, often lack TP53 mutations despite frequent loss of p53 function, suggesting alternative p53 inactivating mechanisms. Here we show that p53-regulating PPM1D at chromosome 17q22.3 is linked to aggressive tumors and poor prognosis in neuroblastoma. We identified that WIP1-phosphatase encoded by PPM1D, is activated by frequent segmental 17q-gain further accumulated during clonal evolution, gene-amplifications, gene-fusions or gain-of-function somatic and germline mutations. Pharmacological and genetic manipulation established WIP1 as a druggable target in neuroblastoma. Genome-scale CRISPR-Cas9 screening demonstrated PPM1D genetic dependency in TP53 wild-type neuroblastoma cell lines, and shRNA PPM1D knockdown significantly delayed in vivo tumor formation. Establishing a transgenic mouse model overexpressing PPM1D showed that these mice develop cancers phenotypically and genetically similar to tumors arising in mice with dysfunctional p53 when subjected to low-dose irradiation. Tumors include T-cell lymphomas harboring Notch1-mutations, Pten-deletions and p53-accumulation, adenocarcinomas and PHOX2B-expressing neuroblastomas establishing PPM1D as a bona fide oncogene in wtTP53 cancer and childhood neuroblastoma. Pharmacological inhibition of WIP1 suppressed the growth of neural tumors in nude mice proposing WIP1 as a therapeutic target in neural childhood tumors.

cancer biology↗

bioRxiv2019

Generating high-quality libraries for DIA-MS with empirically-corrected peptide predictions

Data-independent acquisition approaches typically rely on sample-specific spectrum libraries requiring offline fractionation and tens to hundreds of injections. We demonstrate a new library generation workflow that leverages fragmentation and retention time prediction to build libraries containing every peptide in a proteome, and then refines those libraries with empirical data. Our method specifically enables rapid library generation for non-model organisms, which we demonstrate using the malaria parasite Plasmodium falciparum, and non-canonical databases, which we show by detecting missense variants in HeLa.

systems biology↗

bioRxiv2018

Novel allosteric mechanism of p53 activation by small molecules for targeted anticancer therapy

Given the immense significance of p53 restoration for anti-cancer therapy, elucidation of the mechanisms of action of p53-activating molecules is of the utmost importance. Here we report a discovery of novel allosteric modulation of p53 by small molecules, which is an unexpected turn in the p53 story. We identified a structural element involved in p53 regulation, whose targeting by RITA, PpIX and licofelone block the binding of p53 inhibitors, MDM2 and MDMX. Deletion and mutation analysis followed by molecular modeling, identified the key p53 residues S33 and S37 targeted by RITA and PpIX. We propose that the binding of small molecules to the identified site induces a conformational trap preventing p53 from the interaction with MDM2 and MDMX. These results point to a high potential of allosteric activators. Our study provides the basis for the development of therapeutics with a novel mechanism of action, thus extending the p53 pharmacological potential.

cancer biology↗

bioRxiv2018

A deep proteome and transcriptome abundance atlas of 29 healthy human tissues

Genome-, transcriptome- and proteome-wide measurements provide valuable insights into how biological systems are regulated. However, even fundamental aspects relating to which human proteins exist, where they are expressed and in which quantities are not fully understood. Therefore, we have generated a systematic, quantitative and deep proteome and transcriptome abundance atlas from 29 paired healthy human tissues from the Human Protein Atlas Project and representing human genes by 17,615 transcripts and 13,664 proteins. The analysis revealed that few proteins show truly tissue-specific expression, that vast differences between mRNA and protein quantities within and across tissues exist and that the expression levels of proteins are often more stable across tissues than those of transcripts. In addition, only ~2% of all exome and ~7% of all mRNA variants could be confidently detected at the protein level showing that proteogenomics remains challenging, requires rigorous validation using synthetic peptides and needs more sophisticated computational methods. Many uses of this resource can be envisaged ranging from the study of gene/protein expression regulation to protein biomarker specificity evaluation to name a few.

systems biology↗