Role of clathrin in dense core vesicle biogenesis

The dense-core vesicles (DCVs) of neuroendocrine cells are a rich source of bioactive molecules such as peptides, hormones, and neurotransmitters, but relatively little is known about how they are formed. Using fractionation profiling, a method that combines subcellular fractionation with mass spectrometry, we identified ∼1200 proteins in PC12 cell vesicle-enriched fractions, with DCV-associated proteins showing distinct profiles from proteins associated with other types of vesicles. To investigate the role of clathrin in DCV biogenesis, we stably transduced PC12 cells with an inducible shRNA targeting clathrin heavy chain, resulting in ∼85% protein loss. DCVs could still be observed in the cells by electron microscopy, but mature profiles were ∼4-fold less abundant than in mock-treated cells. By quantitative mass spectrometry, DCV-associated proteins were found to be reduced ∼2-fold in clathrin-depleted cells as a whole and ∼5-fold in vesicle-enriched fractions. Our combined datasets enabled us to identify new candidate DCV components. Secretion assays revealed that clathrin depletion causes a near-complete block in secretagogue-induced exocytosis. Taken together, our data indicate that clathrin has a function in DCV biogenesis beyond its established role in removing unwanted proteins from the immature vesicle.This work was funded by grants from the Wellcome Trust: 086598 (to M.S.R.), 100140 (Wellcome Trust Strategic Award), and 093026 (for the FEI Tecnai G2 Spirit BioTWIN transmission EM); and by a National Institutes of Health/National Institute of Diabetes and Digestive and Kidney Diseases grant (R01DK102496) to A.B

Nano Random Forests to mine protein complexes and their relationships in quantitative proteomics data

Ever-increasing numbers of quantitative proteomics data sets constitute an underexploited resource for investigating protein function. Multiprotein complexes often follow consistent trends in these experiments, which could provide insights about their biology. Yet, as more experiments are considered, a complex’s signature may become conditional and less identifiable. Previously we successfully distinguished the general proteomic signature of genuine chromosomal proteins from hitchhikers using the Random Forests (RF) machine learning algorithm. Here we test whether small protein complexes can define distinguishable signatures of their own, despite the assumption that machine learning needs large training sets. We show, with simulated and real proteomics data, that RF can detect small protein complexes and relationships between them. We identify several complexes in quantitative proteomics results of wild-type and knockout mitotic chromosomes. Other proteins covary strongly with these complexes, suggesting novel functional links for later study. Integrating the RF analysis for several complexes reveals known interdependences among kinetochore subunits and a novel dependence between the inner kinetochore and condensin. Ribosomal proteins, although identified, remained independent of kinetochore subcomplexes. Together these results show that this complex-oriented RF (NanoRF) approach can integrate proteomics data to uncover subtle protein relationships. Our NanoRF pipeline is available online

Uncoupling the functions of CALM in VAMP sorting and clathrin-coated pit formation.

CALM (clathrin assembly lymphoid myeloid leukemia protein) is a cargo-selective adaptor for the post-Golgi R-SNAREs VAMPs 2, 3, and 8, and it also regulates the size of clathrin-coated pits and vesicles at the plasma membrane. The present study has two objectives: to determine whether CALM can sort additional VAMPs, and to investigate whether VAMP sorting contributes to CALM-dependent vesicle size regulation. Using a flow cytometry-based endocytosis efficiency assay, we demonstrate that CALM is also able to sort VAMPs 4 and 7, even though they have sorting signals for other clathrin adaptors. CALM homologues are present in nearly every eukaryote, suggesting that the CALM family may have evolved as adaptors for retrieving all post-Golgi VAMPs from the plasma membrane. Using a knockdown/rescue system, we show that wild-type CALM restores normal VAMP sorting in CALM-depleted cells, but that two non-VAMP-binding mutants do not. However, when we assayed the effect of CALM depletion on coated pit morphology, using a fluorescence microscopy-based assay, we found that the two mutants were as effective as wild-type CALM. Thus, we can uncouple the sorting function of CALM from its structural role

Co-regulation map of the human proteome enables identification of protein functions

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: All mass spectrometry raw files generated in-house have been deposited in the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository36 with the dataset identifier PXD008888. The co-regulation map is hosted on our website at www.proteomeHD.net, and pair-wise co-regulation scores are available through STRING (https://string-db.org). A network of the top 0.5% co-regulated protein pairs can be explored interactively on NDEx (https://doi.org/10.18119/N9N30Q).Code availability: Data analysis was performed in R 3.5.1. R scripts and input files required to reproduce the results of this manuscript are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/ProteomeHD. R scripts related specifically to the benchmarking of the treeClust algorithm using synthetic data are available in the following GitHub repository: https://github.com/Rappsilber-Laboratory/treeClust-benchmarking. The R package data.table was used for fast data processing. Figures were prepared using ggplot2, gridExtra, cowplot and viridis.Note that the title of the AAM is different from the published versionThe annotation of protein function is a longstanding challenge of cell biology that suffers from the sheer magnitude of the task. Here we present ProteomeHD, which documents the response of 10,323 human proteins to 294 biological perturbations, measured by isotope-labelling mass spectrometry. We reveal functional associations between human proteins using the treeClust machine learning algorithm, which we show to improve protein co-regulation analysis due to robust selectivity for close linear relationships. Our co-regulation map identifies a functional context for many uncharacterized proteins, including microproteins that are difficult to study with traditional methods. Co-regulation also captures relationships between proteins which do not physically interact or co-localize. For example, co-regulation of the peroxisomal membrane protein PEX11β with mitochondrial respiration factors led us to discover a novel organelle interface between peroxisomes and mitochondria in mammalian cells. The co-regulation map can be explored at www.proteomeHD.net .Biotechnology & Biological Sciences Research Council (BBSRC)European Commissio

Clathrin heavy chain 22 contributes to the control of neuropeptide degradation and secretion during neuronal development.

The repertoire of cell types in the human nervous system arises through a highly orchestrated process, the complexity of which is still being discovered. Here, we present evidence that CHC22 has a non-redundant role in an early stage of neural precursor differentiation, providing a potential explanation of why CHC22 deficient patients are unable to feel touch or pain. We show the CHC22 effect on neural differentiation is independent of the more common clathrin heavy chain CHC17, and that CHC22-dependent differentiation is mediated through an autocrine/paracrine mechanism. Using quantitative proteomics, we define the composition of clathrin-coated vesicles in SH-SY5Y cells, and determine proteome changes induced by CHC22 depletion. In the absence of CHC22 a subset of dense core granule (DCG) neuropeptides accumulated, were processed into biologically active ‘mature’ forms, and secreted in sufficient quantity to trigger neural differentiation. When CHC22 is present, however, these DCG neuropeptides are directed to the lysosome and degraded, thus preventing differentiation. This suggests that the brief reduction seen in CHC22 expression in sensory neural precursors may license a step in neuron precursor neurodevelopment; and that this step is mediated through control of a novel neuropeptide processing pathway

AP-4 vesicles contribute to spatial control of autophagy via RUSC-dependent peripheral delivery of ATG9A.

Adaptor protein 4 (AP-4) is an ancient membrane trafficking complex, whose function has largely remained elusive. In humans, AP-4 deficiency causes a severe neurological disorder of unknown aetiology. We apply unbiased proteomic methods, including ‘Dynamic Organellar Maps’, to find proteins whose subcellular localisation depends on AP-4. We identify three transmembrane cargo proteins, ATG9A, SERINC1 and SERINC3, and two AP-4 accessory proteins, RUSC1 and RUSC2. We demonstrate that AP-4 deficiency causes missorting of ATG9A in diverse cell types, including patient-derived cells, as well as dysregulation of autophagy. RUSC2 facilitates the transport of AP-4-derived, ATG9A-positive vesicles from the trans-Golgi network to the cell periphery. These vesicles cluster in close association with autophagosomes, suggesting they are the “ATG9A reservoir” required for autophagosome biogenesis. Our study uncovers ATG9A trafficking as a ubiquitous function of the AP-4 pathway. Furthermore, it provides a potential molecular pathomechanism of AP-4 deficiency, through dysregulated spatial control of autophagy