Fractionation profiling: a fast and versatile approach for mapping vesicle proteomes and protein-protein interactions

Cargo selective vesicle tethering: The structural basis for binding of specific cargo proteins by the Golgi tether component TBC1D23

The Golgi-localized golgins golgin-97 and golgin-245 capture transport vesicles arriving from endosomes via the protein TBC1D23. The amino-terminal domain of TBC1D23 binds to the golgins, and the carboxyl-terminal domain of TBC1D23 captures the vesicles, but how it recognizes specific vesicles was unclear. A search for binding partners of the carboxyl-terminal domain unexpectedly revealed direct binding to carboxypeptidase D and syntaxin-16, known cargo proteins of the captured vesicles. Binding is via a threonine-leucine-tyrosine (TLY) sequence present in both proteins next to an acidic cluster. A crystal structure reveals how this acidic TLY motif binds to TBC1D23. An acidic TLY motif is also present in the tails of other endosome-to-Golgi cargo, and these also bind TBC1D23. Structure-guided mutations in the carboxyl-terminal domain that disrupt motif binding in vitro also block vesicle capture in vivo. Thus, TBC1D23 attached to golgin-97 and golgin-245 captures vesicles by a previously undescribed mechanism: the recognition of a motif shared by cargo proteins carried by the vesicle.

Application of Machine Learning in Spatial Proteomics

Spatial proteomics is an interdisciplinary field that investigates the localization and dynamics of proteins, and it has gained extensive attention in recent years, especially the subcellular proteomics. Numerous evidence indicate that the subcellular localization of proteins is associated with various cellular processes and disease progression. Mass spectrometry (MS)-based and imaging-based experimental approaches have been developed to acquire large-scale spatial proteomic data. To allow the reliable analysis of increasingly complex spatial proteomics data, machine learning (ML) methods have been widely used in both MS-based and imaging-based spatial proteomic data analysis pipelines. Here, we comprehensively survey the applications of ML in spatial proteomics from following aspects: (1) data resources for spatial proteome are comprehensively introduced; (2) the roles of different ML algorithms in data analysis pipelines are elaborated; (3) successful applications of spatial proteomics and several analytical tools integrating ML methods are presented; (4) challenges existing in modern ML-based spatial proteomics studies are discussed. This review provides guidelines for researchers seeking to apply ML methods to analyze spatial proteomic data and can facilitate insightful understanding of cell biology as well as the future research in medical and drug discovery communities.

Comparative Analysis of T-Cell Spatial Proteomics and the Influence of HIV Expression

As systems biology approaches to virology have become more tractable, highly studied viruses such as HIV can now be analyzed in new unbiased ways, including spatial proteomics. We employed here a differential centrifugation protocol to fractionate Jurkat T cells for proteomic analysis by mass spectrometry; these cells contain inducible HIV-1 genomes, enabling us to look for changes in the spatial proteome induced by viral gene expression. Using these proteomics data, we evaluated the merits of several reported machine learning pipelines for classification of the spatial proteome and identification of protein translocations. From these analyses, we found that classifier performance in this system was organelle dependent, with Bayesian t-augmented Gaussian mixture modeling outperforming support vector machine learning for mitochondrial and endoplasmic reticulum proteins but underperforming on cytosolic, nuclear, and plasma membrane proteins by QSep analysis. We also observed a generally higher performance for protein translocation identification using a Bayesian model, Bayesian analysis of differential localization experiments, on row-normalized data. Comparative Bayesian analysis of differential localization experiment analysis of cells induced to express the WT viral genome versus cells induced to express a genome unable to express the accessory protein Nef identified known Nef-dependent interactors such as T-cell receptor signaling components and coatomer complex. Finally, we found that support vector machine classification showed higher consistency and was less sensitive to HIV-dependent noise. These findings illustrate important considerations for studies of the spatial proteome following viral infection or viral gene expression and provide a reference for future studies of HIV-gene-dropout viruses.

PSL-LCCL: a resource for subcellular protein localization in liver cancer cell line SK_HEP1

The characterization of subcellular protein localization provides a basis for further understanding cellular behaviors. A delineation of subcellular localization of proteins on cytosolic membrane-bound organelles in human liver cancer cell lines (hLCCLs) has yet to be performed. To obtain its proteome-wide view, we isolated and enriched six cytosolic membrane-bound organelles in one of the hLCCLs (SK_HEP1) and quantified their proteins using mass spectrometry. The vigorous selection of marker proteins and a machine-learning-based algorithm were implemented to localize proteins at cluster and neighborhood levels. We validated the performance of the proposed method by comparing the predicted subcellular protein localization with publicly available resources. The profiles enabled investigating the correlation of protein domains with their subcellular localization and colocalization of protein complex members. A subcellular proteome database for SK_HEP1, including (i) the subcellular protein localization and (ii) the subcellular locations of protein complex members and their interactions, was constructed. Our research provides resources for further research on hLCCLs proteomics.

Database URL: http://www.igenetics.org.cn/project/PSL-LCCL/

Subcellular proteomics

The eukaryotic cell is compartmentalized into subcellular niches, including membrane-bound and membrane-less organelles. Proteins localize to these niches to fulfil their function, enabling discreet biological processes to occur in synchrony. Dynamic movement of proteins between niches is essential for cellular processes such as signalling, growth, proliferation, motility and programmed cell death, and mutations causing aberrant protein localization are associated with a wide range of diseases. Determining the location of proteins in different cell states and cell types and how proteins relocalize following perturbation is important for understanding their functions, related cellular processes and pathologies associated with their mislocalization. In this Primer, we cover the major spatial proteomics methods for determining the location, distribution and abundance of proteins within subcellular structures. These technologies include fluorescent imaging, protein proximity labelling, organelle purification and cell-wide biochemical fractionation. We describe their workflows, data outputs and applications in exploring different cell biological scenarios, and discuss their main limitations. Finally, we describe emerging technologies and identify areas that require technological innovation to allow better characterization of the spatial proteome.

Unbiased proteomic profiling of host cell extracellular vesicle composition and dynamics upon HIV-1 infection

Cells release diverse types of extracellular vesicles (EVs), which transfer complex signals to surrounding cells. Specific markers to distinguish different EVs (e.g. exosomes, ectosomes, enveloped viruses like HIV) are still lacking. We have developed a proteomic profiling approach for characterizing EV subtype composition and applied it to human Jurkat T cells. We generated an interactive database to define groups of proteins with similar profiles, suggesting release in similar EVs. Biochemical validation confirmed the presence of preferred partners of commonly used exosome markers in EVs: CD81/ADAM10/ITGB1, and CD63/syntenin. We then compared EVs from control and HIV-1-infected cells. HIV infection altered EV profiles of several cellular proteins, including MOV10 and SPN, which became incorporated into HIV virions, and SERINC3, which was re-routed to non-viral EVs in a Nef-dependent manner. Furthermore, we found that SERINC3 controls the surface composition of EVs. Our workflow provides an unbiased approach for identifying candidate markers and potential regulators of EV subtypes. It can be widely applied to in vitro experimental systems for investigating physiological or pathological modifications of EV release.

Spatial proteomics defines the content of trafficking vesicles captured by golgin tethers

Intracellular traffic between compartments of the secretory and endocytic pathways is mediated by vesicle-based carriers. The proteomes of carriers destined for many organelles are ill-defined because the vesicular intermediates are transient, low-abundance and difficult to purify. Here, we combine vesicle relocalisation with organelle proteomics and Bayesian analysis to define the content of different endosome-derived vesicles destined for the trans-Golgi network (TGN). The golgin coiled-coil proteins golgin-97 and GCC88, shown previously to capture endosome-derived vesicles at the TGN, were individually relocalised to mitochondria and the content of the subsequently re-routed vesicles was determined by organelle proteomics. Our findings reveal 45 integral and 51 peripheral membrane proteins re-routed by golgin-97, evidence for a distinct class of vesicles shared by golgin-97 and GCC88, and various cargoes specific to individual golgins. These results illustrate a general strategy for analysing intracellular sub-proteomes by combining acute cellular re-wiring with high-resolution spatial proteomics.

Organellar Maps Through Proteomic Profiling - A Conceptual Guide

Protein subcellular localization is an essential and highly regulated determinant of protein function. Major advances in mass spectrometry and imaging have allowed the development of powerful spatial proteomics approaches for determining protein localization at the whole cell scale. Here, a brief overview of current methods is presented, followed by a detailed discussion of organellar mapping through proteomic profiling. This relatively simple yet flexible approach is rapidly gaining popularity, because of its ability to capture the localizations of thousands of proteins in a single experiment. It can be used to generate high-resolution cell maps, and as a tool for monitoring protein localization dynamics. This review highlights the strengths and limitations of the approach and provides guidance to designing and interpreting profiling experiments.

Identification of Podocyte Cargo Proteins by Proteomic Analysis of Clathrin-Coated Vesicles

Background

Clathrin-mediated endocytosis (CME) plays a fundamental role in podocyte health. Genetic ablation of genes implicated in CME has been shown to cause severe proteinuria and foot process effacement in mice. However, little is known about the cargo of clathrin-coated vesicles (CCVs) in podocytes. The goal of this study was to isolate CCVs from podocytes and identify their cargo by proteomic analysis.

Methods

Glomeruli isolated from Podocin-Cre Rosa-DTRflox mouse kidneys were seeded and treated with diphtheria toxin to obtain pure primary podocyte cultures. CCVs were isolated by differential gradient ultracentrifugation, and enrichment of CCVs was assessed by immunoblotting and electron microscopy (EM). Liquid chromatography-mass spectrometry (LC-MS) was performed for proteomic analysis. Proteins with higher abundance than transferrin receptor protein 1 were evaluated for CCV cargo potential against previously published literature. Immunofluorescence staining of identified cargo proteins and CCVs was performed in podocytes for further verification.

Results

Immunoblotting for multiple protein markers of CME revealed enrichment in the CCV fraction. Enrichment of CCVs among other small vesicles was observed via EM. Proteomics yielded a total of >1200 significant proteins. Multiple-step data analysis revealed 36 CCV-associated proteins, of which 10 represent novel, highly abundant cargo proteins in podocytes. Colocalization of cargo proteins and CCVs on immunostaining was observed.

Conclusions

Our identification of podocyte CCV cargo proteins helps to elucidate the importance of endocytic trafficking for podocyte health and maintenance of the glomerular environment.

Structure of TBC1D23 N-terminus reveals a novel role for rhodanese domain

Members of the Tre2-Bub2-Cdc16 (TBC) family often function to regulate membrane trafficking and to control signaling transductions pathways. As a member of the TBC family, TBC1D23 is critical for endosome-to-Golgi cargo trafficking by serving as a bridge between Golgi-bound golgin-97/245 and the WASH/FAM21 complex on endosomal vesicles. However, the exact mechanisms by which TBC1D23 regulates cargo transport are poorly understood. Here, we present the crystal structure of the N-terminus of TBC1D23 (D23N), which consists of both the TBC and rhodanese domains. We show that the rhodanese domain is unlikely to be an active sulfurtransferase or phosphatase, despite containing a putative catalytic site. Instead, it packs against the TBC domain and forms part of the platform to interact with golgin-97/245. Using the zebrafish model, we show that impacting golgin-97/245-binding, but not the putative catalytic site, impairs neuronal growth and brain development. Altogether, our studies provide structural and functional insights into an essential protein that is required for organelle-specific trafficking and brain development.

Endosome-to-TGN Trafficking: Organelle-Vesicle and Organelle-Organelle Interactions

Retrograde transport from endosomes to the trans-Golgi network (TGN) diverts proteins and lipids away from lysosomal degradation. It is essential for maintaining cellular homeostasis and signaling. In recent years, significant advancements have been made in understanding this classical pathway, revealing new insights into multiple steps of vesicular trafficking as well as critical roles of ER-endosome contacts for endosomal trafficking. In this review, we summarize up-to-date knowledge about this trafficking pathway, in particular, mechanisms of cargo recognition at endosomes and vesicle tethering at the TGN, and contributions of ER-endosome contacts.

Spatial proteomics: a powerful discovery tool for cell biology

Protein subcellular localization is tightly controlled and intimately linked to protein function in health and disease. Capturing the spatial proteome - that is, the localizations of proteins and their dynamics at the subcellular level - is therefore essential for a complete understanding of cell biology. Owing to substantial advances in microscopy, mass spectrometry and machine learning applications for data analysis, the field is now mature for proteome-wide investigations of spatial cellular regulation. Studies of the human proteome have begun to reveal a complex architecture, including single-cell variations, dynamic protein translocations, changing interaction networks and proteins localizing to multiple compartments. Furthermore, several studies have successfully harnessed the power of comparative spatial proteomics as a discovery tool to unravel disease mechanisms. We are at the beginning of an era in which spatial proteomics finally integrates with cell biology and medical research, thereby paving the way for unbiased systems-level insights into cellular processes. Here, we discuss current methods for spatial proteomics using imaging or mass spectrometry and specifically highlight global comparative applications. The aim of this Review is to survey the state of the field and also to encourage more cell biologists to apply spatial proteomics approaches.

Biogenesis of lysosome-related organelles complex-1 (BORC) regulates late endosomal/lysosomal size through PIKfyve-dependent phosphatidylinositol-3,5-bisphosphate

Mechanisms that control lysosomal function are essential for cellular homeostasis. Lysosomes adapt in size and number to cellular needs but little is known about the underlying molecular mechanism. We demonstrate that the late endosomal/lysosomal multimeric BLOC-1-related complex (BORC) regulates the size of these organelles via PIKfyve-dependent phosphatidylinositol-3,5-bisphosphate [PI(3,5)P2 ] production. Deletion of the core BORC component Diaskedin led to increased levels of PI(3,5)P2 , suggesting activation of PIKfyve, and resulted in enhanced lysosomal reformation and subsequent reduction in lysosomal size. This process required AMP-activated protein kinase (AMPK), a known PIKfyve activator, and was additionally dependent on the late endosomal/lysosomal adaptor, mitogen-activated protein kinases and mechanistic target of rapamycin activator (LAMTOR/Ragulator) complex. Consistently, in response to glucose limitation, AMPK activated PIKfyve, which induced lysosomal reformation with increased baseline autophagy and was coupled to a decrease in lysosomal size. These adaptations of the late endosomal/lysosomal system reversed under glucose replete growth conditions. In summary, our results demonstrate that BORC regulates lysosomal reformation and size in response to glucose availability.

The expanding spectrum of neurological disorders of phosphoinositide metabolism

Phosphoinositides (PIPs) are a ubiquitous group of seven low-abundance phospholipids that play a crucial role in defining localized membrane properties and that regulate myriad cellular processes, including cytoskeletal remodeling, cell signaling cascades, ion channel activity and membrane traffic. PIP homeostasis is tightly regulated by numerous inositol kinases and phosphatases, which phosphorylate and dephosphorylate distinct PIP species. The importance of these phospholipids, and of the enzymes that regulate them, is increasingly being recognized, with the identification of human neurological disorders that are caused by mutations in PIP-modulating enzymes. Genetic disorders of PIP metabolism include forms of epilepsy, neurodegenerative disease, brain malformation syndromes, peripheral neuropathy and congenital myopathy. In this Review, we provide an overview of PIP function and regulation, delineate the disorders associated with mutations in genes that modulate or utilize PIPs, and discuss what is understood about gene function and disease pathogenesis as established through animal models of these diseases.

Summary: This Review highlights the intersection between phosphoinositides and the enzymes that regulate their metabolism, which together are crucial regulators of myriad cellular processes and neurological disorders.

Rab regulation by GEFs and GAPs during membrane traffic

Rab GTPases and their regulatory proteins play a crucial role in vesicle-mediated membrane trafficking. During vesicle membrane tethering Rab GTPases are activated by GEFs (guanine nucleotide exchange factors) and then inactivated by GAPs (GTPase activating proteins). Recent evidence shows that in addition to activating and inactivating Rab GTPases, both Rab GEFs and GAPs directly contribute to membrane tethering events during vesicle traffic. Other studies have extended the range of processes, in which Rabs function, and revealed roles for Rabs and their GAPs in the regulation of autophagy. Here, we will discuss these advances and the emerging relationship between the domain architectures of Rab GEFs and vesicle coat protein complexes linked with GTPases of the Sar, ARF and Arl families in animal cells.

Dynamic Organellar Maps for Spatial Proteomics

Eukaryotic cells are highly compartmentalized and protein subcellular localization critically influences protein function. Identification of the subcellular localizations of proteins and their translocation events upon perturbation has mostly been confined to targeted studies or laborious microscopy-based methods. Here we describe a systematic mass spectrometry-based method for spatial proteomics. The approach uses simple fractionation profiling and has two applications: Firstly it can be used to infer subcellular protein localization on a proteome-wide scale, resulting in a protein map of the cell. Secondly, the method permits identification of changes in protein localization, by comparing maps made under different conditions, as a tool for unbiased systems cell biology. © 2018 by John Wiley & Sons, Inc.

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.

The WDR11 complex facilitates the tethering of AP-1-derived vesicles

Vesicluar transport of proteins from endosomes to the trans-Golgi network (TGN) is an essential cellular pathway, but much of its machinery is still unknown. A screen for genes involved in endosome-to-TGN trafficking produced two hits, the adaptor protein-1 (AP-1 complex), which facilitates vesicle budding, and WDR11. Here we demonstrate that WDR11 forms a stable complex with two other proteins, which localises to the TGN region and does not appear to be associated with AP-1, suggesting it may act downstream from budding. In a vesicle tethering assay, capture of vesicles by golgin-245 was substantially reduced in WDR11-knockout cells. Moreover, structured illumination microscopy and relocation assays indicate that the WDR11 complex is initially recruited onto vesicles rather than the TGN, where it may in turn recruit the golgin binding partner TBC1D23. We propose that the complex acts together with TBC1D23 to facilitate the golgin-mediated capture of vesicles that were generated using AP-1.

Trafficking from endosomes to the trans-Golgi network requires recognition of vesicle tethers during membrane docking. Here, the authors identify a complex localised to AP-1 generated vesicles containing WDR11, C17orf75 and FAM91A, which together with TBC1D23 facilitates vesicle capture on Golgi membranes

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.

The interactome of intact mitochondria by cross-linking mass spectrometry provides evidence for coexisting respiratory supercomplexes

Mitochondria exert an immense amount of cytophysiological functions, but the structural basis of most of these processes is still poorly understood. Here we use cross-linking mass spectrometry to probe the organization of proteins in native mouse heart mitochondria. Our approach provides the largest survey of mitochondrial protein interactions reported so far. In total, we identify 3,322 unique residue-to-residue contacts involving half of the mitochondrial proteome detected by bottom-up proteomics. The obtained mitochondrial protein interactome gives insights in the architecture and submitochondrial localization of defined protein assemblies, and reveals the mitochondrial localization of four proteins not yet included in the MitoCarta database. As one of the highlights, we show that the oxidative phosphorylation complexes I-V exist in close spatial proximity, providing direct evidence for supercomplex assembly in intact mitochondria. The specificity of these contacts is demonstrated by comparative analysis of mitochondria after high salt treatment, which disrupts the native supercomplexes and substantially changes the mitochondrial interactome.

The two TRAPP complexes of metazoans have distinct roles and act on different Rab GTPases

In yeast, the TRAPP complexes activate Rab1 with TRAPPII also activating Rab11, but less is known about the two TRAPPs in metazoans. Riedel et al. show that in Drosophila melanogaster, TRAPPIII is an essential Rab1 activator, and TRAPPII activates Rab1 and Rab11 and becomes essential when an unrelated Rab11 activator is deleted.

Originally identified in yeast, transport protein particle (TRAPP) complexes are Rab GTPase exchange factors that share a core set of subunits. TRAPPs were initially found to act on Ypt1, the yeast orthologue of Rab1, but recent studies have found that yeast TRAPPII can also activate the Rab11 orthologues Ypt31/32. Mammals have two TRAPP complexes, but their role is less clear, and they contain subunits that are not found in the yeast complexes but are essential for cell growth. To investigate TRAPP function in metazoans, we show that Drosophila melanogaster have two TRAPP complexes similar to those in mammals and that both activate Rab1, whereas one, TRAPPII, also activates Rab11. TRAPPII is not essential but becomes so in the absence of the gene parcas that encodes the Drosophila orthologue of the SH3BP5 family of Rab11 guanine nucleotide exchange factors (GEFs). Thus, in metazoans, Rab1 activation requires TRAPP subunits not found in yeast, and Rab11 activation is shared by TRAPPII and an unrelated GEF that is metazoan specific.

TBC1D23 is a bridging factor for endosomal vesicle capture by golgins at the trans-Golgi

The specificity of membrane traffic involves tethers at destination organelles that selectively capture incoming transport vesicles to allow SNAREs on opposing membranes to then assemble and drive fusion1,2. Tethers include both protein complexes and long coiled-coil proteins, although how they contribute to specificity remains unclear3,4. The golgin coiled-coil proteins at the Golgi apparatus capture vesicles from different origins, but the vesicle-specific molecular cues that they recognise are unknown5–8. Vesicle tethering is typically a transient process and so challenging to interrogate in vivo. We have thus used a system where an ectopic golgin causes vesicles to accumulate in a tethered state. By applying proximity biotinylation to the golgin-captured vesicles we identify TBC1D23, an apparently catalytically inactive member of a family of Rab GTPase activating proteins (GAPs), as a vesicle-golgin adaptor that is required for endosome-to-Golgi traffic. The Rab-GAP domain of TBC1D23 binds to a conserved motif at the tip of golgin-245 and golgin-97 at the trans-Golgi, while the C-terminus binds to the WASH complex on endosome-derived vesicles. Thus TBC1D23 is a specificity determinant that links vesicle to target membrane during endosome-to-Golgi trafficking.

Correlation profiling of brain sub-cellular proteomes reveals co-assembly of synaptic proteins and subcellular distribution

Protein correlation profiling might assist in defining co-assembled proteins and subcellular distribution. Here, we quantified the proteomes of five biochemically isolated mouse brain cellular sub-fractions, with emphasis on synaptic compartments, from three brain regions, hippocampus, cortex and cerebellum. We demonstrated the expected co-fractionation of canonical synaptic proteins belonging to the same functional groups. The enrichment profiles also suggested the presence of many novel pre- and post-synaptic proteins. Using super-resolution microscopy on primary neuronal culture we confirmed the postsynaptic localization of PLEKHA5 and ADGRA1. We further detected profound brain region specific differences in the extent of enrichment for some functionally associated proteins. This is exemplified by different AMPA receptor subunits and substantial differences in sub-fraction distribution of their potential interactors, which implicated the differences of AMPA receptor complex compositions. This resource aids the identification of proteins partners and subcellular distribution of synaptic proteins.

Contribution of the clathrin adaptor AP-1 subunit µ1 to acidic cluster protein sorting

Acidic clusters act as sorting signals for packaging cargo into clathrin-coated vesicles (CCVs), and also facilitate down-regulation of MHC-I by HIV-1 Nef. To find acidic cluster sorting machinery, we performed a gene-trap screen and identified the medium subunit (µ1) of the clathrin adaptor AP-1 as a top hit. In µ1 knockout cells, intracellular CCVs still form, but acidic cluster proteins are depleted, although several other CCV components were either unaffected or increased, indicating that cells can compensate for long-term loss of AP-1. In vitro experiments showed that the basic patch on µ1 that interacts with the Nef acidic cluster also contributes to the binding of endogenous acidic cluster proteins. Surprisingly, µ1 mutant proteins lacking the basic patch and/or the tyrosine-based motif binding pocket could rescue the µ1 knockout phenotype completely. In contrast, these mutants failed to rescue Nef-induced down-regulation of MHC class I, suggesting a possible mechanism for attacking the virus while sparing the host cell.

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 short hairpin RNA targeting clathrin heavy chain, resulting in ∼85% protein loss. DCVs could still be observed in the cells by electron microscopy, but mature profiles were approximately fourfold less abundant than in mock-treated cells. By quantitative mass spectrometry, DCV-associated proteins were found to be reduced approximately twofold in clathrin-depleted cells as a whole and approximately fivefold in vesicle-enriched fractions. Our combined data sets 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.

Lineage-specific proteins essential for endocytosis in trypanosomes

Clathrin-mediated endocytosis (CME) is the most evolutionarily ancient endocytic mechanism known, and in many lineages the sole mechanism for internalisation. Significantly, in mammalian cells CME is responsible for the vast bulk of endocytic flux and has likely undergone multiple adaptations to accommodate specific requirements by individual species. In African trypanosomes, we previously demonstrated that CME is independent of the AP-2 adaptor protein complex, that orthologues to many of the animal and fungal CME protein cohort are absent, and that a novel, trypanosome-restricted protein cohort interacts with clathrin and drives CME. Here, we used a novel cryomilling affinity isolation strategy to preserve transient low-affinity interactions, giving the most comprehensive trypanosome clathrin interactome to date. We identified the trypanosome AP-1 complex, Trypanosoma brucei (Tb)EpsinR, several endosomal SNAREs plus orthologues of SMAP and the AP-2 associated kinase AAK1 as interacting with clathrin. Novel lineage-specific proteins were identified, which we designate TbCAP80 and TbCAP141. Their depletion produced extensive defects in endocytosis and endomembrane system organisation, revealing a novel molecular pathway subtending an early-branching and highly divergent form of CME, which is conserved and likely functionally important across the kinetoplastid parasites.

Summary: Endocytosis is a vital process in most cells, and here we identify important proteins required for this process in trypanosomes. Significantly, these are unique and not present in animals, fungi or plants.

Interactome disassembly during apoptosis occurs independent of caspase cleavage

Protein-protein interaction networks (interactomes) define the functionality of all biological systems. In apoptosis, proteolysis by caspases is thought to initiate disassembly of protein complexes and cell death. Here we used a quantitative proteomics approach, protein correlation profiling (PCP), to explore changes in cytoplasmic and mitochondrial interactomes in response to apoptosis initiation as a function of caspase activity. We measured the response to initiation of Fas-mediated apoptosis in 17,991 interactions among 2,779 proteins, comprising the largest dynamic interactome to date. The majority of interactions were unaffected early in apoptosis, but multiple complexes containing known caspase targets were disassembled. Nonetheless, proteome-wide analysis of proteolytic processing by terminal amine isotopic labeling of substrates (TAILS) revealed little correlation between proteolytic and interactome changes. Our findings show that, in apoptosis, significant interactome alterations occur before and independently of caspase activity. Thus, apoptosis initiation includes a tight program of interactome rearrangement, leading to disassembly of relatively few, select complexes. These early interactome alterations occur independently of cleavage of these protein by caspases.

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

Nano Random Forests is a machine learning-based approach to extract valuable information about multiprotein complexes in collections of proteomics experiments. In mitotic chromosome data, it retrieves known relationships among kinetochore substructures and provides highly specific predictions about uncharacterized protein function.

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.

Global, quantitative and dynamic mapping of protein subcellular localization

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

DOI:http://dx.doi.org/10.7554/eLife.16950.001

The interior of every cell is highly organised, and contains many compartments, called organelles, that are dedicated to specific roles. Proteins are the tools and machines of the cell, and each organelle has its own set of proteins that it requires to work correctly. Each cell contains ten or more organelles, and several thousand different types of proteins. The exact location of proteins in the cell is important; once we know what compartment a protein is in, it is easier to narrow down what it might be doing.

The location of many proteins in a cell is unclear or simply not known. Moreover, since changing the location of a protein can change its activity, it is also important to be able to detect changes in the location of proteins under different circumstances, such as before and after drug treatment.

Itzhak et al. set out to develop a method that reveals the locations of all the proteins in a cell at any given time. The resulting technique maps the location of most of the proteins in a human cancer cell line and, in addition, determines how many copies of each protein there are. Combining these two types of information produces a model of the cell’s architecture. Importantly, Itzhak et al. were able to compare such a model of the cell under normal circumstances to a model made after the cell had been stimulated with a growth factor. This revealed which proteins had changed location, identifying these proteins as important for the cell’s response to the growth factor.

The new mapping method could be used in the future to analyse the anatomy of different cell types, such as nerve cells and cells of the immune system. Itzhak et al. also want to investigate the differences between healthy cells and cells from people with neurological disorders to understand how such diseases arise.

DOI:http://dx.doi.org/10.7554/eLife.16950.002

Forty Years of Clathrin-coated Vesicles

The purification of coated vesicles and the discovery of clathrin by Barbara Pearse in 1975 was a landmark in cell biology. Over the past 40 years, work from many labs has uncovered the molecular details of clathrin and its associated proteins, including how they assemble into a coated vesicle and how they select cargo. Unexpected connections have been found with signalling, development, neuronal transmission, infection, immunity and genetic disorders. But there are still a number of unanswered questions, including how clathrin-mediated trafficking is regulated and how the machinery evolved.

OCRL1 engages with the F-BAR protein pacsin 2 to promote biogenesis of membrane-trafficking intermediates

Mutation of the inositol 5-phosphatase OCRL1 causes Lowe syndrome and Dent-2 disease. Loss of OCRL1 function perturbs several cellular processes, including membrane traffic, but the underlying mechanisms remain poorly defined. Here we show that OCRL1 is part of the membrane-trafficking machinery operating at the trans-Golgi network (TGN)/endosome interface. OCRL1 interacts via IPIP27A with the F-BAR protein pacsin 2. OCRL1 and IPIP27A localize to mannose 6-phosphate receptor (MPR)-containing trafficking intermediates, and loss of either protein leads to defective MPR carrier biogenesis at the TGN and endosomes. OCRL1 5-phosphatase activity, which is membrane curvature sensitive, is stimulated by IPIP27A-mediated engagement of OCRL1 with pacsin 2 and promotes scission of MPR-containing carriers. Our data indicate a role for OCRL1, via IPIP27A, in regulating the formation of pacsin 2-dependent trafficking intermediates and reveal a mechanism for coupling PtdIns(4,5)P2 hydrolysis with carrier biogenesis on endomembranes.

Decoding protein networks during virus entry by quantitative proteomics

Virus entry into host cells relies on interactions between viral and host structures including lipids, carbohydrates and proteins. Particularly, protein–protein interactions between viral surface proteins and host proteins as well as secondary host protein–protein interactions play a pivotal role in coordinating virus binding and uptake. These interactions are dynamic and frequently involve multiprotein complexes. In the past decade mass spectrometry based proteomics methods have reached sensitivities and high throughput compatibilities of genomics methods and now allow the reliable quantitation of proteins in complex samples from limited material. As proteomics provides essential information on the biologically active entity namely the protein, including its posttranslational modifications and its interactions with other proteins, it is an indispensable method in the virologist's toolbox. Here we review protein interactions during virus entry and compare classical biochemical methods to study entry with novel technically advanced quantitative proteomics techniques. We highlight the value of quantitative proteomics in mapping functional virus entry networks, discuss the benefits and limitations and illustrate how the methodology will help resolve unsettled questions in virus entry research in the future.

Contributions of epsinR and gadkin to clathrin-mediated intracellular trafficking

EpsinR and gadkin are two components of intracellular clathrin-coated vesicles whose precise functions are unclear. Rapid depletion of each protein from the available pool using the knocksideways method strongly inhibited the production of intracellular clathrin-coated vesicles, providing new insights into the functions of both proteins.

The precise functions of most of the proteins that participate in clathrin-mediated intracellular trafficking are unknown. We investigated two such proteins, epsinR and gadkin, using the knocksideways method, which rapidly depletes proteins from the available pool by trapping them onto mitochondria. Although epsinR is known to be an N-ethylmaleimide–sensitive factor attachment protein receptor (SNARE)-specific adaptor, the epsinR knocksideways blocked the production of the entire population of intracellular clathrin-coated vesicles (CCVs), suggesting a more global function. Using the epsinR knocksideways data, we were able to estimate the copy number of all major intracellular CCV proteins. Both sides of the vesicle are densely covered, indicating that CCVs sort their cargo by molecular crowding. Trapping of gadkin onto mitochondria also blocked the production of intracellular CCVs but by a different mechanism: vesicles became cross-linked to mitochondria and pulled out toward the cell periphery. Both phenotypes provide new insights into the regulation of intracellular CCV formation, which could not have been found using more conventional approaches.

Recruitment of VPS33A to HOPS by VPS16 Is Required for Lysosome Fusion with Endosomes and Autophagosomes

The mammalian homotypic fusion and vacuole protein sorting (HOPS) complex is comprised of six subunits: VPS11, VPS16, VPS18, VPS39, VPS41 and the Sec1/Munc18 (SM) family member VPS33A. Human HOPS has been predicted to be a tethering complex required for fusion of intracellular compartments with lysosomes, but it remains unclear whether all HOPS subunits are required. We showed that the whole HOPS complex is required for fusion of endosomes with lysosomes by monitoring the delivery of endocytosed fluorescent dextran to lysosomes in cells depleted of individual HOPS proteins. We used the crystal structure of the VPS16/VPS33A complex to design VPS16 and VPS33A mutants that no longer bind each other and showed that, unlike the wild-type proteins, these mutants no longer rescue lysosome fusion with endosomes or autophagosomes in cells depleted of the endogenous proteins. There was no effect of depleting either VIPAR or VPS33B, paralogs of VPS16 and VPS33A, on fusion of lysosomes with either endosomes or autophagosomes and immunoprecipitation showed that they form a complex distinct from HOPS. Our data demonstrate the necessity of recruiting the SM protein VPS33A to HOPS via its interaction with VPS16 and that HOPS proteins, but not VIPAR or VPS33B, are essential for fusion of endosomes or autophagosomes with lysosomes.

Development of a computational framework for the analysis of protein correlation profiling and spatial proteomics experiments

Standard approaches to studying an interactome do not easily allow conditional experiments but in recent years numerous groups have demonstrated the potential for co-fractionation/co-migration based approaches to assess an interactome at a similar sensitivity and specificity yet significantly lower cost and higher speed than traditional approaches. Unfortunately, there is as yet no implementation of the bioinformatics tools required to robustly analyze co-fractionation data in a way that can also integrate the valuable information contained in biological replicates. Here we have developed a freely available, integrated bioinformatics solution for the analysis of protein correlation profiling SILAC data. This modular solution allows the deconvolution of protein chromatograms into individual Gaussian curves enabling the use of these chromatography features to align replicates and assemble a consensus map of features observed across replicates; the chromatograms and individual curves are then used to quantify changes in protein interactions and construct the interactome. We have applied this workflow to the analysis of HeLa cells infected with a Salmonella enterica serovar Typhimurium infection model where we can identify specific interactions that are affected by the infection. These bioinformatics tools simplify the analysis of co-fractionation/co-migration data to the point where there is no specialized knowledge required to measure an interactome in this way.

BIOLOGICAL SIGNIFICANCE

We describe a set of software tools for the bioinformatics analysis of co-migration/co-fractionation data that integrates the results from multiple replicates to generate an interactome, including the impact on individual interactions of any external perturbation. This article is part of a Special Issue entitled: Protein dynamics in health and disease. Guest Editors: Pierre Thibault and Anne-Claude Gingras.