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Biology subjects

Zenkner, M.

Publications and source records attributed to Zenkner, M..

5 recordsLinked to original sources

HAP40 functions as a proteostasis regulator by controlling huntingtin interactions and its release into the extracellular space

Huntingtin-associated protein 40 (HAP40) forms a stable protein complex with huntingtin (HTT). Its cellular function and how HAP40 loss influences mutant HTT (mHTT) abundance and pathobiology are currently unclear. Here, using diverse cellular models and OMICs methods, we demonstrate that HAP40 is an obligate interaction partner of full-length HTT and through its binding controls the abundance of HTT-associated proteins, indicating that it functions as HTT interaction regulatory unit. Also, loss of HAP40 in mHTT-expressing striatal cells impairs autophagosome-lysosome flux, triggers massive transcriptional dysregulation, including the activation of the CLEAR network, demonstrating that it functions as proteostasis regulator that acts on quality control pathways. Finally, mHTT-expressing cells lacking HAP40 showed increased secretion of mHTT through the ER-to-Golgi route, indicating that striatal cells reduce intracellular mHTT-induced proteotoxicity through activation of secretory pathways. Together, these results establish HAP40 as a critical proteostasis regulator that through controlling HTT interactions maintains cellular homeostasis.

cell biology↗

Molecular architecture of synaptic vesicles.

Synaptic vesicles (SVs) store and transport neurotransmitters to the presynaptic active zone for release by exocytosis. After release, SV proteins and excess membrane are recycled via endocytosis, and new SVs are formed in a clathrin-dependent manner. This process maintains the morphology and complex molecular composition of SVs through multiple recycling rounds. Previous studies explored the molecular composition of SVs through proteomic analysis and fluorescent microscopy, proposing a model for an average SV1,2. However, the structural heterogeneity and molecular architecture of individual SVs are not well described. Here we used cryo-electron tomography to visualize morphological and molecular details of SVs isolated from mouse brains and inside cultured neurons. We describe several classes of small proteins on the SV surface and long proteinaceous densities inside SVs. We identified V-ATPases, determined a structure using subtomogram average, and showed them forming a complex with the membrane-embedded protein synaptophysin. Our bioluminescence assay revealed pairwise interactions between VAMP2 and synaptophysin and V-ATPase Voe1 domains. Interestingly, V-ATPases were randomly distributed on the surface of SVs irrespective of vesicle sizes. A subpopulation of isolated vesicles and vesicles inside neurons contained a partially assembled clathrin coat with a soccer-ball symmetry. We observed a V-ATPase under clathrin cage in several isolated clathrin-coated vesicles. Additionally, from isolated SV preparations and within hippocampal neurons we identified clathrin baskets without vesicles. We determined their preferential location in proximity to the cell membrane. Our analysis advances the understanding of individual SVs diversity and their molecular architecture.

biophysics↗

AI-guided pipeline for protein-protein interaction drug discovery identifies a SARS-CoV-2 inhibitor

Protein-protein interactions (PPIs) offer great opportunities to expand the druggable proteome and therapeutically tackle various diseases, but remain challenging targets for drug discovery. Here, we provide a comprehensive pipeline that combines experimental and computational tools to identify and validate PPI targets and perform early-stage drug discovery. We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold-Multimer predictions. Using the quantitative assay LuTHy together with our machine learning algorithm, we identified high-confidence interactions among SARS-CoV-2 proteins for which we predicted three-dimensional structures using AlphaFold Multimer. We employed VirtualFlow to target the contact interface of the NSP10-NSP16 SARS-CoV-2 methyltransferase complex by ultra-large virtual drug screening. Thereby, we identified a compound that binds to NSP10 and inhibits its interaction with NSP16, while also disrupting the methyltransferase activity of the complex, and SARS-CoV-2 replication. Overall, this pipeline will help to prioritize PPI targets to accelerate the discovery of early-stage drug candidates targeting protein complexes and pathways.

systems biology↗

A proteomics analysis of 5xFAD mouse brain regions reveals the lysosome-associated protein Arl8b as a candidate biomarker for Alzheimer's disease

BackgroundAlzheimers disease (AD) is characterized by the accumulation of amyloid-{beta} (A{beta}) peptides in intra- and extracellular deposits. How A{beta} aggregates perturb the proteome in brains of patients and AD transgenic mouse models, however, remains largely unclear. State-of-the-art mass spectrometry (MS) methods can comprehensively detect proteomic alterations in neurodegenerative disorders, providing relevant insights unobtainable with transcriptomics investigations. Analyses of the relationship between progressive A{beta} aggregation and protein abundance changes in brains of 5xFAD transgenic mice have not been reported previously. MethodsWe quantified progressive A{beta} aggregation in hippocampus and cortex of 5xFAD mice and controls with immunohistochemistry and biochemical membrane filter assays. Protein changes in different mouse tissues were analysed by MS-based proteomics using label-free quantification (LFQ); resulting MS data were processed using an established pipeline. Results were contrasted with existing proteomic data sets from postmortem AD patient brains. Finally, abundance changes in the candidate marker Arl8b were validated in CSF from AD patients and controls using ELISAs. ResultsExperiments revealed a more rapid accumulation of A{beta}42 peptides in hippocampus than in cortex of 5xFAD mice, accompanied by many more protein abundance changes in hippocampus than in cortex, indicating that A{beta}42 aggregate deposition is associated with brain region-specific proteome perturbations. Generating time-resolved data sets, we defined A{beta} aggregate-correlated and anticorrelated proteome changes, a fraction of which was conserved in postmortem AD patient brain tissue, suggesting that proteome changes in 5xFAD mice mimic disease relevant changes in human AD. We detected a positive correlation between A{beta}42 aggregate deposition in the hippocampus of 5xFAD mice and the abundance of the lysosome-associated small GTPase Arl8b, which accumulated together with axonal lysosomal membranes in close proximity of extracellular A{beta} plaques in 5xFAD brains. Abnormal aggregation of Arl8b was observed in AD brain tissue. Arl8b protein levels were significantly increased in cerebrospinal fluid (CSF) of AD patients, a clinically accessible body fluid. ConclusionsWe report a comprehensive biochemical and proteomic investigation of hippocampal and cortical brain tissue derived from 5xFAD transgenic mice, providing a valuable resource to the neuroscientific community. We identified Arl8b, with significant abundance changes in 5xFAD and AD patient brains. Arl8b might enable the measurement of progressive lysosome accumulation in AD patients and have clinical utility as a candidate biomarker. Data are available via ProteomeXchange with identifier PXD030348.

molecular biology↗

A quantitative mapping approach to identify direct interactions within complexomes

Complementary methods are required to fully characterize all protein complexes, or the complexome, of a cell. Affinity purification coupled to mass-spectrometry (AP-MS) can identify the composition of complexes at proteome-scale. However, information on direct contacts between subunits is often lacking. In contrast, solving the 3D structure of protein complexes can provide this information, but structural biology techniques are not yet scalable for systematic, proteome-wide efforts. Here, we optimally combine two orthogonal high-throughput binary interaction assays, LuTHy and N2H, and demonstrate that their quantitative readouts can be used to differentiate direct interactions from indirect associations within multiprotein complexes. We also show that LuTHy allows accurate distance measurements between proteins in live cells and apply these findings to study the impact of the polyglutamine expansion mutation on the structurally unresolved N-terminal domain of Huntingtin. Thus, we present a new framework based on quantitative interaction assays to complement structural biology and AP-MS techniques, which should help to provide first-approximation contact maps of multiprotein complexes at proteome-scale. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/457734v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1cc7cf1org.highwire.dtl.DTLVardef@1eed9borg.highwire.dtl.DTLVardef@8197b2org.highwire.dtl.DTLVardef@e5cb8_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗