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Protein phosphorylation is one of the most widespread post-translational modifications in biology 1 , 2 . With advances in mass-spectrometry-based phosphoproteomics, 90,000 sites of serine and threonine phosphorylation have so far been identified, and several thousand have been associated with human diseases and biological processes 3 , 4 . For the vast majority of phosphorylation events, it is not yet known which of the more than 300 protein serine/threonine (Ser/Thr) kinases encoded in the human genome are responsible 3 . Here we used synthetic peptide libraries to profile the substrate sequence specificity of 303 Ser/Thr kinases, comprising more than 84% of those predicted to be active in humans. Viewed in its entirety, the substrate specificity of the kinome was substantially more diverse than expected and was driven extensively by negative selectivity. We used our kinome-wide dataset to computationally annotate and identify the kinases capable of phosphorylating every reported phosphorylation site in the human Ser/Thr phosphoproteome. For the small minority of phosphosites for which the putative protein kinases involved have been previously reported, our predictions were in excellent agreement. When this approach was applied to examine the signalling response of tissues and cell lines to hormones, growth factors, targeted inhibitors and environmental or genetic perturbations, it revealed unexpected insights into pathway complexity and compensation. Overall, these studies reveal the intrinsic substrate specificity of the human Ser/Thr kinome, illuminate cellular signalling responses and provide a resource to link phosphorylation events to biological pathways. Analysis of the kinase activity of 300 protein Ser/Thr kinases reveals that the substrate specificity of the kinome is substantially more diverse than expected and is driven extensively by negative selectivity

Mass spectrometry is the method of choice for deep and reliable exploration of the (human) proteome. Targeted mass spectrometry reliably detects and quantifies pre-determined sets of proteins in a complex biological matrix and is used in studies that rely on the quantitatively accurate and reproducible measurement of proteins across multiple samples. It requires the one-time, a priori generation of a specific measurement assay for each targeted protein. SWATH-MS is a mass spectrometric method that combines data-independent acquisition (DIA) and targeted data analysis and vastly extends the throughput of proteins that can be targeted in a sample compared to selected reaction monitoring (SRM). Here we present a compendium of highly specific assays covering more than 10,000 human proteins and enabling their targeted analysis in SWATH-MS datasets acquired from research or clinical specimens. This resource supports the confident detection and quantification of 50.9% of all human proteins annotated by UniProtKB/Swiss-Prot and is therefore expected to find wide application in basic and clinical research. Data are available via ProteomeXchange (PXD000953-954) and SWATHAtlas (SAL00016-35). Design Type(s) reference design • replicate design • protein expression profiling • quality control testing design Measurement Type(s) protein expression profiling Technology Type(s) mass spectrometry assay Factor Type(s) purification • Proteolysis Sample Characteristic(s) Homo sapiens • Monocyte • Neutrophil • Kidney • Muscle • Lung • Blood platelet • Gut • Blood plasma • 293 cell • THP-1 cell • U2 OS cell • HeLa cell • U2OS & HeLa • NCI60 • LNCAP cell • CAL-51 cell Machine-accessible metadata file describing the reported data (ISA-Tab format)

Characterization of the chloroplast proteome is needed to understand the essential contribution of the chloroplast to plant growth and development. Here we present a large scale analysis by nanoLC-Q-TOF and nanoLC-LTQ-Orbitrap mass spectrometry (MS) of ten independent chloroplast preparations from Arabidopsis thaliana which unambiguously identified 1325 proteins. Novel proteins include various kinases and putative nucleotide binding proteins. Based on repeated and independent MS based protein identifications requiring multiple matched peptide sequences, as well as literature, 916 nuclear-encoded proteins were assigned with high confidence to the plastid, of which 86% had a predicted chloroplast transit peptide (cTP). The protein abundance of soluble stromal proteins was calculated from normalized spectral counts from LTQ-Obitrap analysis and was found to cover four orders of magnitude. Comparison to gel-based quantification demonstrates that 'spectral counting' can provide large scale protein quantification for Arabidopsis. This quantitative information was used to determine possible biases for protein targeting prediction by TargetP and also to understand the significance of protein contaminants. The abundance data for 550 stromal proteins was used to understand abundance of metabolic pathways and chloroplast processes. We highlight the abundance of 48 stromal proteins involved in post-translational proteome homeostasis (including aminopeptidases, proteases, deformylases, chaperones, protein sorting components) and discuss the biological implications. N-terminal modifications were identified for a subset of nuclear- and chloroplast-encoded proteins and a novel N-terminal acetylation motif was discovered. Analysis of cTPs and their cleavage sites of Arabidopsis chloroplast proteins, as well as their predicted rice homologues, identified new species-dependent features, which will facilitate improved subcellular localization prediction. No evidence was found for suggested targeting via the secretory system. This study provides the most comprehensive chloroplast proteome analysis to date and an expanded Plant Proteome Database (PPDB) in which all MS data are projected on identified gene models.

Plants are essential for life and are extremely diverse organisms with unique molecular capabilities 1 . Here we present a quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana . Our analysis provides initial answers to how many genes exist as proteins (more than 18,000), where they are expressed, in which approximate quantities (a dynamic range of more than six orders of magnitude) and to what extent they are phosphorylated (over 43,000 sites). We present examples of how the data may be used, such as to discover proteins that are translated from short open-reading frames, to uncover sequence motifs that are involved in the regulation of protein production, and to identify tissue-specific protein complexes or phosphorylation-mediated signalling events. Interactive access to this resource for the plant community is provided by the ProteomicsDB and ATHENA databases, which include powerful bioinformatics tools to explore and characterize Arabidopsis proteins, their modifications and interactions. A quantitative atlas of the transcriptomes, proteomes and phosphoproteomes of 30 tissues of the model plant Arabidopsis thaliana provides a valuable resource for plant research.

Compartmentalization is a defining characteristic of eukaryotic cells, and partitions distinct biochemical processes into discrete subcellular locations. Microscopy 1 and biochemical fractionation coupled with mass spectrometry 2 – 4 have defined the proteomes of a variety of different organelles, but many intracellular compartments have remained refractory to such approaches. Proximity-dependent biotinylation techniques such as BioID provide an alternative approach to define the composition of cellular compartments in living cells 5 – 7 . Here we present a BioID-based map of a human cell on the basis of 192 subcellular markers, and define the intracellular locations of 4,145 unique proteins in HEK293 cells. Our localization predictions exceed the specificity of previous approaches, and enabled the discovery of proteins at the interface between the mitochondrial outer membrane and the endoplasmic reticulum that are crucial for mitochondrial homeostasis. On the basis of this dataset, we created humancellmap.org as a community resource that provides online tools for localization analysis of user BioID data, and demonstrate how this resource can be used to understand BioID results better. A proximity-dependent biotinylation technique defines the location of more than 4,000 proteins in a human cell, and almost 36,000 proximal interactions between proteins, including those at the interface of the mitochondria and ER.

Affinity purification–mass spectrometry elucidates protein interaction networks and co-complexes to build, to our knowledge, the largest experimentally derived human protein interaction network so far, termed BioPlex 2.0. Mapping protein interactions The thousands of proteins within a cell function as modules and networks to coordinate their biological activities. Large-scale efforts are underway to build protein interaction maps that reveal cellular proteome architecture. Here, Wade Harper and colleagues use affinity purification mass spectrometry to elucidate protein interaction networks and co-complexes and build the largest experimentally derived human proteome interaction network to date, termed BioPlex 2.0. Containing over 29,000 novel co-associations and 1,300 protein communities representing diverse cellular activities, BioPlex 2.0 is more than double the size of their earlier interaction network BioPlex 1.0 and will be a valuable resource for exploring uncharacterized proteins and candidate disease-linked genes. The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein–protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease 1 , 2 , 3 . Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification–mass spectrometry methodology 4 to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering 5 of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness 6 , 7 are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.

The ability of living systems to adapt to changing conditions originates from their capacity to change their molecular constitution. This is achieved by multiple mechanisms that modulate the quantitative composition and the diversity of the molecular inventory. Molecular diversification is particularly pronounced on the proteome level, at which multiple proteoforms derived from the same gene can in turn combinatorially form different protein complexes, thus expanding the repertoire of functional modules in the cell. The study of molecular and modular diversity and their involvement in responses to changing conditions has only recently become possible through the development of new ‘omics’-based screening technologies. This Review explores our current knowledge of the mechanisms regulating functional diversification along the axis of gene expression, with a focus on the proteome and interactome. We explore the interdependence between different molecular levels and how this contributes to functional diversity. Finally, we highlight several recent techniques for studying molecular diversity, with specific focus on mass spectrometry-based analysis of the proteome and its organization into functional modules, and examine future directions for this rapidly growing field.Cells maximize the repertoire of functions produced from their genome through introducing diversity at each stage of the gene expression process, including at the post-translational level. New advances in proteomics and interactomics have begun to shed light on the extent to which diversity is introduced on the proteome level and by the organization of proteins into modular interaction networks.

Numerous biological processes are concurrently and coordinately active in every living cell. Each of them encompasses synthetic, catalytic and regulatory functions that are, almost always, carried out by proteins organized further into higher-order structures and networks. For decades, the structures and functions of selected proteins have been studied using biochemical and biophysical methods. However, the properties and behaviour of the proteome as an integrated system have largely remained elusive. Powerful mass-spectrometry-based technologies now provide unprecedented insights into the composition, structure, function and control of the proteome, shedding light on complex biological processes and phenotypes.

Nanoscale or single-cell technologies are critical for biomedical applications. However, current mass spectrometry (MS)-based proteomic approaches require samples comprising a minimum of thousands of cells to provide in-depth profiling. Here, we report the development of a nanoPOTS (nanodroplet processing in one pot for trace samples) platform for small cell population proteomics analysis. NanoPOTS enhances the efficiency and recovery of sample processing by downscaling processing volumes to <200 nL to minimize surface losses. When combined with ultrasensitive liquid chromatography-MS, nanoPOTS allows identification of ~1500 to ~3000 proteins from ~10 to ~140 cells, respectively. By incorporating the Match Between Runs algorithm of MaxQuant, >3000 proteins are consistently identified from as few as 10 cells. Furthermore, we demonstrate quantification of ~2400 proteins from single human pancreatic islet thin sections from type 1 diabetic and control donors, illustrating the application of nanoPOTS for spatially resolved proteome measurements from clinical tissues. There is a great need of developing highly sensitive mass spectrometry-based proteomics analysis for small cell populations. Here, the authors establish a robotically controlled chip-based nanodroplet processing platform and demonstrate its ability to profile the proteome from 10–100 mammalian cells.

The modest protection afforded by the RV144 vaccine offers an opportunity to evaluate its mechanisms of protection. Differences between HIV-1 breakthrough viruses from vaccine and placebo recipients can be attributed to the RV144 vaccine as this was a randomized and double-blinded trial. CD8 and CD4 T cell epitope repertoires were predicted in HIV-1 proteomes from 110 RV144 participants. Predicted Gag epitope repertoires were smaller in vaccine than in placebo recipients (p = 0.019). After comparing participant-derived epitopes to corresponding epitopes in the RV144 vaccine, the proportion of epitopes that could be matched differed depending on the protein conservation (only 36% of epitopes in Env vs 84-91% in Gag/Pol/Nef for CD8 predicted epitopes) or on vaccine insert subtype (55% against CRF01_AE vs 7% against subtype B). To compare predicted epitopes to the vaccine, we analyzed predicted binding affinity and evolutionary distance measurements. Comparisons between the vaccine and placebo arm did not reveal robust evidence for a T cell driven sieve effect, although some differences were noted in Env-V2 (0.022≤p-value≤0.231). The paucity of CD8 T cell responses identified following RV144 vaccination, with no evidence for V2 specificity, considered together both with the association of decreased infection risk in RV 144 participants with V-specific antibody responses and a V2 sieve effect, lead us to hypothesize that this sieve effect was not T cell specific. Overall, our results did not reveal a strong differential impact of vaccine-induced T cell responses among breakthrough infections in RV144 participants.