Biology subjects

Mehnert, M.

Publications and source records attributed to Mehnert, M..

4 recordsLinked to original sources

bioRxiv2022

Systematic dissection of phosphorylation-dependent YAP1 complex formation elucidates a key role for PTPN14 in Hippo signal integration

Cellular signaling relies on the temporal and spatial control of the formation of transient protein complexes by post-translational modifications, most notably by phosphorylation. While several computational methods have been developed to predict the functional relevance of phosphorylation sites, assessing experimentally the interdependency between protein phosphorylation and protein-protein interactions (PPIs) remains a major challenge. Here, we describe an experimental strategy to establish interdependencies between specific phosphorylation events and complex formation. This strategy is based on three main steps: (i) systematically charting the phosphorylation landscape of a target protein; (ii) assigning distinct proteoforms of the target protein to different protein complexes by electrophoretic separation of native complexes (BNPAGE) and protein/phopho correlation profiling; and (iii) genetically deleting known regulators of the target protein to identify which ones are required for given proteoforms and complexes. We applied this strategy to study phosphorylation- dependent modulation of complexes containing the transcriptional co-regulator YAP1. YAP1 is highly phosphorylated and among the most extensively connected proteins in the human interactome. It functions as the main signal integrator and effector protein of the Hippo pathway which controls organ size and tissue homeostasis. Using our workflow, we could identify several distinct YAP1 proteoforms specifically associated with physically distinct complexes and infer how their formation is affected by known Hippo pathway members. Importantly, our findings suggest that the tyrosine phosphatase PTPN14 controls the co-transcriptional activity of YAP1 by regulating its interaction with the LATS1/2 kinases. In summary, we present a powerful strategy to establish interdependencies between specific phosphorylation events and complex formation, thus contributing to the "functionalization" of phosphorylation events and by this means provide new insights into Hippo signaling.

systems biology↗

bioRxiv2021

Novel biochemical, structural and systems insights into inflammatory signaling revealed by contextual interaction proteomics

Protein-protein interactions (PPI) represent the main mode of the proteome organization in the cell. In the last decade, several large-scale representations of PPI networks have captured generic aspects of the functional organization of network components, but mostly lack the context of cellular states. However, the generation of contextual representations of PPI networks is essential for structural and systems-level modeling of biological processes and remains an unsolved challenge. In this study we describe an integrated experimental/computational strategy to achieve a contextualized modeling of PPI. This strategy defines the composition, stoichiometry, spatio-temporal organization and cellular requirements for the formation of target assemblies. We used this approach to generate an integrated model of the formation principles and architecture of a large signalosome, the TNF-receptor signaling complex (TNF-RSC). Overall, we show that the integration of systems- and structure-level information provides a generic, largely unexplored link between the modular proteome and cellular function. Significance StatementIn this work, we propose a critical shift in the way we analyze, and think the study of, protein-protein interactions (PPI), and present an experimental and computational framework to model them in the cellular context. We applied this framework to the signalosome tumor necrosis factor receptor signaling complex (TNF-RSC), and generated an integrated model of its formation and architecture that provides new insights and resolved controversies regarding its organization and regulation. To achieve a contextual modelling of PPIs, we first optimized and developed, and then combined, approaches to map the composition of a target complex, its absolute stoichiometry, its spatial organization and assembly/disassembly dynamics, its temporal dependence on signaling, and its reliance on cellular resources.

systems biology↗

bioRxiv2018

Rapid Proteomic Screen of CRISPR Experiment Outcome by Data Independent Acquisition Mass Spectrometry: A Case Study for HMGN1

CRISPR-Cas gene editing holds substantial promise in many biomedical disciplines and basic research. Due to the important functional implications of non-histone chromosomal protein HMG-14 (HMGN1) in regulating chromatin structure and tumor immunity, we performed gene knockout of HMGN1 by CRISPR in cancer cells and studied the following proteomic regulation events. In particular, we utilized DIA mass spectrometry (DIA-MS) and reproducibly measured more than 6200 proteins (protein-FDR 1%) and more than 82,000 peptide precursors in the single MS shots of two hours. HMGN1 protein deletion was confidently verified by DIA-MS in all of the clone- and dish- replicates following CRISPR. Statistical analysis revealed 147 proteins changed their expressions significantly after HMGN1 knockout. Functional annotation and enrichment analysis indicate the deletion of HMGN1 induces the histone inactivation, various stress pathways, remodeling of extracellular proteomes, cell proliferation, as well as immune regulation processes such as complement and coagulation cascade and interferon alpha/ gamma response in cancer cells. These results shed new lights on the cellular functions of HMGN1. We suggest that DIA-MS can be reliably used as a rapid, robust, and cost-effective proteomic screening tool to assess the outcome of the CRISPR experiments.

systems biology↗

bioRxiv2018

Genomic, Proteomic and Phenotypic Heterogeneity in HeLa Cells across Laboratories: Implications for Reproducibility of Research Results

The independent reproduction of research results is a cornerstone of experimental research, yet it is beset by numerous challenges, including the quality and veracity of reagents and materials. Much of life science research depends on life materials, including human tissue culture cells. In this study we aimed at determining the degree of variability in the molecular makeup and the ensuing phenotypic consequences in commonly used human tissue culture cells. We collected 14 stock HeLa aliquots from 13 different laboratories across the globe, cultured them in uniform conditions and profiled the genome-wide copy numbers, mRNAs, proteins and protein turnover rates via genomic techniques and SWATH mass spectrometry, respectively. We also phenotyped each cell line with respect to the ability of transfected Let7 mimics to modulate Salmonella infection.\n\nWe discovered significant heterogeneity between HeLa variants, especially between lines of the CCL2 and Kyoto variety. We also observed progressive divergence within a specific cell line over 50 successive passages. From the aggregate multi-omic datasets we quantified the response of the cells to genomic variability across the transcriptome and proteome. We discovered organelle-specific proteome remodeling and buffering of protein abundance by protein complex stoichiometry, mediated by the adaptation of protein turnover rates. By associating quantitative proteotype and phenotype measurements we identified protein patterns that explained the varying response of the different cell lines to Salmonella infection.\n\nAltogether the results indicate a striking degree of genomic variability, the rapid evolution of genomic variability in culture and its complex translation into distinctive expressed molecular and phenotypic patterns. The results have broad implications for the interpretation and reproducibility of research results obtained from HeLa cells and provide important basis for a general discussion of the value and requirements for communicating research results obtained from human tissue culture cells.

systems biology↗