A census of human soluble protein complexes.

Cellular processes often depend on stable physical associations between proteins. Despite recent progress, knowledge of the composition of human protein complexes remains limited. To close this gap, we applied an integrative global proteomic profiling approach, based on chromatographic separation of cultured human cell extracts into more than one thousand biochemical fractions that were subsequently analyzed by quantitative tandem mass spectrometry, to systematically identify a network of 13,993 high-confidence physical interactions among 3,006 stably associated soluble human proteins. Most of the 622 putative protein complexes we report are linked to core biological processes and encompass both candidate disease genes and unannotated proteins to inform on mechanism. Strikingly, whereas larger multiprotein assemblies tend to be more extensively annotated and evolutionarily conserved, human protein complexes with five or fewer subunits are far more likely to be functionally unannotated or restricted to vertebrates, suggesting more recent functional innovations.

Panorama of ancient metazoan macromolecular complexes.

Macromolecular complexes are essential to conserved biological processes, but their prevalence across animals is unclear. By combining extensive biochemical fractionation with quantitative mass spectrometry, here we directly examined the composition of soluble multiprotein complexes among diverse metazoan models. Using an integrative approach, we generated a draft conservation map consisting of more than one million putative high-confidence co-complex interactions for species with fully sequenced genomes that encompasses functional modules present broadly across all extant animals. Clustering reveals a spectrum of conservation, ranging from ancient eukaryotic assemblies that have probably served cellular housekeeping roles for at least one billion years, ancestral complexes that have accrued contemporary components, and rarer metazoan innovations linked to multicellularity. We validated these projections by independent co-fractionation experiments in evolutionarily distant species, affinity purification and functional analyses. The comprehensiveness, centrality and modularity of these reconstructed interactomes reflect their fundamental mechanistic importance and adaptive value to animal cell systems.

An informatic framework for decoding protein complexes by top-down mass spectrometry.

Efforts to map the human protein interactome have resulted in information about thousands of multi-protein assemblies housed in public repositories, but the molecular characterization and stoichiometry of their protein subunits remains largely unknown. Here, we report a computational search strategy that supports hierarchical top-down analysis for precise identification and scoring of multi-proteoform complexes by native mass spectrometry.

Protein complexes, big data, machine learning and integrative proteomics: lessons learned over a decade of systematic analysis of protein interaction networks.

OVERVIEW: Elucidation of the networks of physical (functional) interactions present in cells and tissues is fundamental for understanding the molecular organization of biological systems, the mechanistic basis of essential and disease-related processes, and for functional annotation of previously uncharacterized proteins (via guilt-by-association or -correlation). After a decade in the field, we felt it timely to document our own experiences in the systematic analysis of protein interaction networks. Areas covered: Researchers worldwide have contributed innovative experimental and computational approaches that have driven the rapidly evolving field of 'functional proteomics'. These include mass spectrometry-based methods to characterize macromolecular complexes on a global-scale and sophisticated data analysis tools - most notably machine learning - that allow for the generation of high-quality protein association maps. Expert commentary: Here, we recount some key lessons learned, with an emphasis on successful workflows, and challenges, arising from our own and other groups' ongoing efforts to generate, interpret and report proteome-scale interaction networks in increasingly diverse biological contexts.

Native GELFrEE: a new separation technique for biomolecular assemblies.

The cadre of protein complexes in cells performs an array of functions necessary for life. Their varied structures are foundational to their ability to perform biological functions, lending great import to the elucidation of complex composition and dynamics. Native separation techniques that are operative on low sample amounts and provide high resolution are necessary to gain valuable data on endogenous complexes. Here, we detail and optimize the use of tube gel separations to produce samples proven compatible with native, multistage mass spectrometry (nMS/MS). We find that a continuous system (i.e., no stacking gel) with a gradient in its extent of cross-linking and use of the clear native buffer system performs well for both fractionation and native mass spectrometry of heart extracts and a fungal secretome. This integrated advance in separations and nMS/MS offers the prospect of untargeted proteomics at the next hierarchical level of protein organization in biology.

Scalable multiplex co-fractionation/mass spectrometry platform for accelerated protein interactome discovery.

Co-fractionation/mass spectrometry (CF/MS) enables the mapping of endogenous macromolecular networks on a proteome scale, but current methods are experimentally laborious, resource intensive and afford lesser quantitative accuracy. Here, we present a technically efficient, cost-effective and reproducible multiplex CF/MS (mCF/MS) platform for measuring and comparing, simultaneously, multi-protein assemblies across different experimental samples at a rate that is up to an order of magnitude faster than previous approaches. We apply mCF/MS to map the protein interaction landscape of non-transformed mammary epithelia versus breast cancer cells in parallel, revealing large-scale differences in protein-protein interactions and the relative abundance of associated macromolecules connected with cancer-related pathways and altered cellular processes. The integration of multiplexing capability within an optimized workflow renders mCF/MS as a powerful tool for systematically exploring physical interaction networks in a comparative manner.

The protein organization of a red blood cell.

Red blood cells (RBCs) (erythrocytes) are the simplest primary human cells, lacking nuclei and major organelles and instead employing about a thousand proteins to dynamically control cellular function and morphology in response to physiological cues. In this study, we define a canonical RBC proteome and interactome using quantitative mass spectrometry and machine learning. Our data reveal an RBC interactome dominated by protein homeostasis, redox biology, cytoskeletal dynamics, and carbon metabolism. We validate protein complexes through electron microscopy and chemical crosslinking and, with these data, build 3D structural models of the ankyrin/Band 3/Band 4.2 complex that bridges the spectrin cytoskeleton to the RBC membrane. The model suggests spring-like compression of ankyrin may contribute to the characteristic RBC cell shape and flexibility. Taken together, our study provides an in-depth view of the global protein organization of human RBCs and serves as a comprehensive resource for future research.

BraInMap Elucidates the Macromolecular Connectivity Landscape of Mammalian Brain.

Connectivity webs mediate the unique biology of the mammalian brain. Yet, while cell circuit maps are increasingly available, knowledge of their underlying molecular networks remains limited. Here, we applied multi-dimensional biochemical fractionation with mass spectrometry and machine learning to survey endogenous macromolecules across the adult mouse brain. We defined a global "interactome" comprising over one thousand multi-protein complexes. These include hundreds of brain-selective assemblies that have distinct physical and functional attributes, show regional and cell-type specificity, and have links to core neurological processes and disorders. Using reciprocal pull-downs and a transgenic model, we validated a putative 28-member RNA-binding protein complex associated with amyotrophic lateral sclerosis, suggesting a coordinated function in alternative splicing in disease progression. This brain interaction map (BraInMap) resource facilitates mechanistic exploration of the unique molecular machinery driving core cellular processes of the central nervous system. It is publicly available and can be explored here https://www.bu.edu/dbin/cnsb/mousebrain/.

Improved proteomic discovery by sample pre-fractionation using dual-column ion-exchange high performance liquid chromatography.

Clinically relevant biomarkers are urgently needed for improving patient diagnosis, risk stratification, prognosis and therapeutic treatments. There is a particularly compelling motivation for identifying protein-based indicators of early-stage disease for more effective interventions. Despite recent progress, the proteomic discovery process remains a daunting challenge due to the sheer heterogeneity and skewed protein abundances in biofluids. Even the most advanced mass spectrometry systems exhibit limiting overall dynamic ranges and sensitivities relative to the needs of modern biomedical applications. To this end, we report the development of a robust, rapid, and reproducible high performance ion-exchange liquid chromatography pre-fractionation method that allows for improved proteomic detection coverage of complex biological specimens using basic tandem mass spectrometry screening procedures. This form of sample simplification prior to global proteomic profiling, which we refer to collectively as 'fractionomics', increases the number and diversity of proteins that can be confidently identified in tissue and cell lysates as compared to the straight analysis of unfractionated crude extracts.

Extracellular histones identified in crocodile blood inhibit in-vitro HIV-1 infection.

OBJECTIVE: It has been reported that crocodile blood contains potent antibacterial and antiviral properties. However, its effects on HIV-1 infection remain unknown. DESIGN: We obtained blood from saltwater crocodiles to examine whether serum or plasma could inhibit HIV-1 infection. We purified plasma fractions then used liquid chromatography-mass spectrometry to identify the inhibitory protein factor(s). We then analyzed the ability of recombinant proteins to recapitulate HIV-1 inhibition and determine their mechanism of action. METHODS: Crocodylus porosus plasma was tested for inhibition of Jurkat T-cell HIV-1 infection. Inhibitor(s) were purified by reverse-phase chromatography then identified by protein liquid chromatography-mass spectrometry. Anti-HIV-1 activity of purified plasma or recombinant proteins were measured by p24 enzyme-linked immunosorbent assay and luciferase readouts, and mechanism of action was determined by measuring HIV-1 RNA, cDNA and transcription (using 1G5 cells). RESULTS: Crocodile plasma contains potent inhibitors of HIV-1IIIB infection, which were identified as histones. Recombinant human histones H1 and H2A significantly reduced HIV-1JR-FL infection (IC50 of 0.79 and 0.45 µmol/l, respectively), whereas H4 enhanced JR-FL luciferase activity. The inhibitory effects of crocodile plasma, recombinant H1 or recombinant H2A on HIV-1 infection were during or post-viral transcription. CONCLUSION: Circulating histones in crocodile blood, possibly released by neutrophil extracellular traps, are significant inhibitors of HIV-1 infection in-vitro. Extracellular recombinant histones have different effects on HIV-1 transcription and protein expression and are downregulated in HIV-1 patients. Circulating histones may be a novel resistance factor during HIV-1 infection, and peptide versions should be explored as future HIV-1 therapeutics that modulate viral transcription.

CN-GELFrEE - Clear Native Gel-eluted Liquid Fraction Entrapment Electrophoresis.

Protein complexes perform an array of crucial cellular functions. Elucidating their non-covalent interactions and dynamics is paramount for understanding the role of complexes in biological systems. While the direct characterization of biomolecular assemblies has become increasingly important in recent years, native fractionation techniques that are compatible with downstream analysis techniques, including mass spectrometry, are necessary to further expand these studies. Nevertheless, the field lacks a high-throughput, wide-range, high-recovery separation method for native protein assemblies. Here, we present clear native gel-eluted liquid fraction entrapment electrophoresis (CN-GELFrEE), which is a novel separation modality for non-covalent protein assemblies. CN-GELFrEE separation performance was demonstrated by fractionating complexes extracted from mouse heart. Fractions were collected over 2 hr and displayed discrete bands ranging from ~30 to 500 kDa. A consistent pattern of increasing molecular weight bandwidths was observed, each ranging ~100 kDa. Further, subsequent reanalysis of native fractions via SDS-PAGE showed molecular-weight shifts consistent with the denaturation of protein complexes. Therefore, CN-GELFrEE was proved to offer the ability to perform high-resolution and high-recovery native separations on protein complexes from a large molecular weight range, providing fractions that are compatible with downstream protein analyses.

Proteome-wide dataset supporting the study of ancient metazoan macromolecular complexes.

Our analysis examines the conservation of multiprotein complexes among metazoa through use of high resolution biochemical fractionation and precision mass spectrometry applied to soluble cell extracts from 5 representative model organisms Caenorhabditis elegans, Drosophila melanogaster, Mus musculus, Strongylocentrotus purpuratus, and Homo sapiens. The interaction network obtained from the data was validated globally in 4 distant species (Xenopus laevis, Nematostella vectensis, Dictyostelium discoideum, Saccharomyces cerevisiae) and locally by targeted affinity-purification experiments. Here we provide details of our massive set of supporting biochemical fractionation data available via ProteomeXchange (PXD002319-PXD002328), PPIs via BioGRID (185267); and interaction network projections via (http://metazoa.med.utoronto.ca) made fully accessible to allow further exploration. The datasets here are related to the research article on metazoan macromolecular complexes in Nature [1].

ComplexQuant: high-throughput computational pipeline for the global quantitative analysis of endogenous soluble protein complexes using high resolution protein HPLC and precision label-free LC/MS/MS.

The experimental isolation and characterization of stable multi-protein complexes are essential to understanding the molecular systems biology of a cell. To this end, we have developed a high-throughput proteomic platform for the systematic identification of native protein complexes based on extensive fractionation of soluble protein extracts by multi-bed ion exchange high performance liquid chromatography (IEX-HPLC) combined with exhaustive label-free LC/MS/MS shotgun profiling. To support these studies, we have built a companion data analysis software pipeline, termed ComplexQuant. Proteins present in the hundreds of fractions typically collected per experiment are first identified by exhaustively interrogating MS/MS spectra using multiple database search engines within an integrative probabilistic framework, while accounting for possible post-translation modifications. Protein abundance is then measured across the fractions based on normalized total spectral counts and precursor ion intensities using a dedicated tool, PepQuant. This analysis allows co-complex membership to be inferred based on the similarity of extracted protein co-elution profiles. Each computational step has been optimized for processing large-scale biochemical fractionation datasets, and the reliability of the integrated pipeline has been benchmarked extensively. This article is part of a Special Issue entitled: From protein structures to clinical applications.