Michele Tinti

Visualization and Biochemical Analyses of the Emerging Mammalian 14-3-3-Phosphoproteome

Hundreds of candidate 14-3-3-binding (phospho)proteins have been reported in publications that describe one interaction at a time, as well as high-throughput 14-3-3-affinity and mass spectrometry-based studies. Here, we transcribed these data into a common format, deposited the collated data from low-throughput studies in MINT (http://mint.bio.uniroma2.it/mint), and compared the low- and high-throughput data in VisANT graphs that are easy to analyze and extend. Exploring the graphs prompted questions about technical and biological specificity, which were addressed experimentally, resulting in identification of phosphorylated 14-3-3-binding sites in the mitochondrial import sequence of the iron-sulfur cluster assembly enzyme (ISCU), cytoplasmic domains of the mitochondrial fission factor (MFF), and endoplasmic reticulum-tethered receptor expression-enhancing protein 4 (REEP4), RNA regulator SMAUG2, and cytoskeletal regulatory proteins, namely debrin-like protein (DBNL) and kinesin light chain (KLC) isoforms. Therefore, 14-3-3s undergo physiological interactions with proteins that are destined for diverse subcellular locations. Graphing and validating interactions underpins efforts to use 14-3-3-phosphoproteomics to identify mechanisms and biomarkers for signaling pathways in health and disease.

The capture of phosphoproteins by 14-3-3 proteins mediates actions of insulin

How does signalling via PI3K-PKB (AKT)-mTORC1-p70S6K and ERK-p90RSK mediate wide-ranging physiological responses to insulin? Quantitative proteomics and biochemical experiments are revealing that these signalling pathways induce the phosphorylation of large and overlapping sets of proteins, which are then captured by phosphoprotein-binding proteins named 14-3-3s. The 14-3-3s are dimers that dock onto dual-phosphorylated sites in a configuration with special signalling and mechanical properties. They interact with the Rab GTPase-activating proteins AS160 and TBC1D1 to regulate glucose uptake into target tissues in response to insulin and energy stress. Dynamic patterns in the 14-3-3-binding phosphoproteome are providing new insights into how insulin triggers coherent shifts in metabolism that are integrated with other cellular response systems.

Evolution of signal multiplexing by 14-3-3-binding 2R-ohnologue protein families in the vertebrates

14-3-3 proteins regulate cellular responses to stimuli by docking onto pairs of phosphorylated residues on target proteins. The present study shows that the human 14-3-3-binding phosphoproteome is highly enriched in 2R-ohnologues, which are proteins in families of two to four members that were generated by two rounds of whole genome duplication at the origin of the vertebrates. We identify 2R-ohnologue families whose members share a ‘lynchpin’, defined as a 14-3-3-binding phosphosite that is conserved across members of a given family, and aligns with a Ser/Thr residue in pro-orthologues from the invertebrate chordates. For example, the human receptor expression enhancing protein (REEP) 1–4 family has the commonest type of lynchpin motif in current datasets, with a phosphorylatable serine in the –2 position relative to the 14-3-3-binding phosphosite. In contrast, the second 14-3-3-binding sites of REEPs 1–4 differ and are phosphorylated by different kinases, and hence the REEPs display different affinities for 14-3-3 dimers. We suggest a conceptual model for intracellular regulation involving protein families whose evolution into signal multiplexing systems was facilitated by 14-3-3 dimer binding to lynchpins, which gave freedom for other regulatory sites to evolve. While increased signalling complexity was needed for vertebrate life, these systems also generate vulnerability to genetic disorders.

14-3-3-Pred: improved methods to predict 14-3-3-binding phosphopeptides

Motivation: The 14-3-3 family of phosphoprotein-binding proteins regulates many cellular processes by docking onto pairs of phosphorylated Ser and Thr residues in a constellation of intracellular targets. Therefore, there is a pressing need to develop new prediction methods that use an updated set of 14-3-3-binding motifs for the identification of new 14-3-3 targets and to prioritize the downstream analysis of >2000 potential interactors identified in high-throughput experiments. Results: Here, a comprehensive set of 14-3-3-binding targets from the literature was used to develop 14-3-3-binding phosphosite predictors. Position-specific scoring matrix, support vector machines (SVM) and artificial neural network (ANN) classification methods were trained to discriminate experimentally determined 14-3-3-binding motifs from non-binding phosphopeptides. ANN, position-specific scoring matrix and SVM methods showed best performance for a motif window spanning from −6 to +4 around the binding phosphosite, achieving Matthews correlation coefficient of up to 0.60. Blind prediction showed that all three methods outperform two popular 14-3-3-binding site predictors, Scansite and ELM. The new methods were used for prediction of 14-3-3-binding phosphosites in the human proteome. Experimental analysis of high-scoring predictions in the FAM122A and FAM122B proteins confirms the predictions and suggests the new 14-3-3-predictors will be generally useful. Availability and implementation: A standalone prediction web server is available at http://www.compbio.dundee.ac.uk/1433pred. Human candidate 14-3-3-binding phosphosites were integrated in ANIA: ANnotation and Integrated Analysis of the 14-3-3 interactome database. Contact: cmackintosh@dundee.ac.uk or gjbarton@dundee.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

ANIA: ANnotation and Integrated Analysis of the 14-3-3 interactome.

The dimeric 14-3-3 proteins dock onto pairs of phosphorylated Ser and Thr residues on hundreds of proteins, and thereby regulate many events in mammalian cells. To facilitate global analyses of these interactions, we developed a web resource named ANIA: ANnotation and Integrated Analysis of the 14-3-3 interactome, which integrates multiple data sets on 14-3-3-binding phosphoproteins. ANIA also pinpoints candidate 14-3-3-binding phosphosites using predictor algorithms, assisted by our recent discovery that the human 14-3-3-interactome is highly enriched in 2R-ohnologues. 2R-ohnologues are proteins in families of two to four, generated by two rounds of whole genome duplication at the origin of the vertebrate animals. ANIA identifies candidate ‘lynchpins’, which are 14-3-3-binding phosphosites that are conserved across members of a given 2R-ohnologue protein family. Other features of ANIA include a link to the catalogue of somatic mutations in cancer database to find cancer polymorphisms that map to 14-3-3-binding phosphosites, which would be expected to interfere with 14-3-3 interactions. We used ANIA to map known and candidate 14-3-3-binding enzymes within the 2R-ohnologue complement of the human kinome. Our projections indicate that 14-3-3s dock onto many more human kinases than has been realized. Guided by ANIA, PAK4, 6 and 7 (p21-activated kinases 4, 6 and 7) were experimentally validated as a 2R-ohnologue family of 14-3-3-binding phosphoproteins. PAK4 binding to 14-3-3 is stimulated by phorbol ester, and involves the ‘lynchpin’ site phosphoSer99 and a major contribution from Ser181. In contrast, PAK6 and PAK7 display strong phorbol ester-independent binding to 14-3-3, with Ser113 critical for the interaction with PAK6. These data point to differential 14-3-3 regulation of PAKs in control of cell morphology. Database URL: https://ania-1433.lifesci.dundee.ac.uk/prediction/webserver/index.py

Global Membrane Protein Interactome Analysis using In vivo Crosslinking and Mass Spectrometry-based Protein Correlation Profiling

We present a methodology using in vivo crosslinking combined with HPLC-MS for the global analysis of endogenous protein complexes by protein correlation profiling. Formaldehyde crosslinked protein complexes were extracted with high yield using denaturing buffers that maintained complex solubility during chromatographic separation. We show this efficiently detects both integral membrane and membrane-associated protein complexes,in addition to soluble complexes, allowing identification and analysis of complexes not accessible in native extracts. We compare the protein complexes detected by HPLC-MS protein correlation profiling in both native and formaldehyde crosslinked U2OS cell extracts. These proteome-wide data sets of both in vivo crosslinked and native protein complexes from U2OS cells are freely available via a searchable online database (www.peptracker.com/epd). Raw data are also available via ProteomeXchange (identifier PXD003754).

Identification of Caveolar Resident Proteins in Ventricular Myocytes Using a Quantitative Proteomic Approach: Dynamic Changes in Caveolar Composition Following Adrenoceptor Activation

The lipid raft concept proposes that membrane environments enriched in cholesterol and sphingolipids cluster certain proteins and form platforms to integrate cell signaling. In cardiac muscle, caveolae concentrate signaling molecules and ion transporters, and play a vital role in adrenergic regulation of excitation–contraction coupling, and consequently cardiac contractility. Proteomic analysis of cardiac caveolae is hampered by the presence of contaminants that have sometimes, erroneously, been proposed to be resident in these domains. Here we present the first unbiased analysis of the proteome of cardiac caveolae, and investigate dynamic changes in their protein constituents following adrenoreceptor (AR) stimulation. Rat ventricular myocytes were treated with methyl-β-cyclodextrin (MβCD) to deplete cholesterol and disrupt caveolae. Buoyant caveolin-enriched microdomains (BCEMs) were prepared from MβCD-treated and control cell lysates using a standard discontinuous sucrose gradient. BCEMs were harvested, pelleted, and resolubilized, then alkylated, digested, and labeled with iTRAQ reagents, and proteins identified by LC-MS/MS on a LTQ Orbitrap Velos Pro. Proteins were defined as BCEM resident if they were consistently depleted from the BCEM fraction following MβCD treatment. Selective activation of α-, β1-, and β2-AR prior to preparation of BCEMs was achieved by application of agonist/antagonist pairs for 10 min in populations of field-stimulated myocytes. We typically identified 600–850 proteins per experiment, of which, 249 were defined as high-confidence BCEM residents. Functional annotation clustering indicates cardiac BCEMs are enriched in integrin signaling, guanine nucleotide binding, ion transport, and insulin signaling clusters. Proteins possessing a caveolin binding motif were poorly enriched in BCEMs, suggesting this is not the only mechanism that targets proteins to caveolae. With the notable exception of the cavin family, very few proteins show altered abundance in BCEMs following AR activation, suggesting signaling complexes are preformed in BCEMs to ensure a rapid and high fidelity response to adrenergic stimulation in cardiac muscle.

Identification of 2R-ohnologue gene families displaying the same mutation-load skew in multiple cancers.

The complexity of signalling pathways was boosted at the origin of the vertebrates, when two rounds of whole genome duplication (2R-WGD) occurred. Those genes and proteins that have survived from the 2R-WGD—termed 2R-ohnologues—belong to families of two to four members, and are enriched in signalling components relevant to cancer. Here, we find that while only approximately 30% of human transcript-coding genes are 2R-ohnologues, they carry 42–60% of the gene mutations in 30 different cancer types. Across a subset of cancer datasets, including melanoma, breast, lung adenocarcinoma, liver and medulloblastoma, we identified 673 2R-ohnologue families in which one gene carries mutations at multiple positions, while sister genes in the same family are relatively mutation free. Strikingly, in 315 of the 322 2R-ohnologue families displaying such a skew in multiple cancers, the same gene carries the heaviest mutation load in each cancer, and usually the second-ranked gene is also the same in each cancer. Our findings inspire the hypothesis that in certain cancers, heterogeneous combinations of genetic changes impair parts of the 2R-WGD signalling networks and force information flow through a limited set of oncogenic pathways in which specific non-mutated 2R-ohnologues serve as effectors. The non-mutated 2R-ohnologues are therefore potential therapeutic targets. These include proteins linked to growth factor signalling, neurotransmission and ion channels.

Prediction of Protein Complexes in Trypanosoma brucei by Protein Correlation Profiling Mass Spectrometry and Machine Learning.

A disproportionate number of predicted proteins from the genome sequence of the protozoan parasite Trypanosoma brucei, an important human and animal pathogen, are hypothetical proteins of unknown function. This paper describes a protein correlation profiling mass spectrometry approach, using two size exclusion and one ion exchange chromatography systems, to derive sets of predicted protein complexes in this organism by hierarchical clustering and machine learning methods. These hypothesis-generating proteomic data are provided in an open access online data visualization environment (http://134.36.66.166:8083/complex_explorer). The data can be searched conveniently via a user friendly, custom graphical interface. We provide examples of both potential new subunits of known protein complexes and of novel trypanosome complexes of suggested function, contributing to improving the functional annotation of the trypanosome proteome. Data are available via ProteomeXchange with identifier PXD005968.

Single-subunit oligosaccharyltransferases of Trypanosoma brucei display different and predictable peptide acceptor specificities

Trypanosoma brucei causes African trypanosomiasis and contains three full-length oligosaccharyltransferase (OST) genes; two of which, TbSTT3A and TbSTT3B, are expressed in the bloodstream form of the parasite. These OSTs have different peptide acceptor and lipid-linked oligosaccharide donor specificities, and trypanosomes do not follow many of the canonical rules developed for other eukaryotic N-glycosylation pathways, raising questions as to the basic architecture and detailed function of trypanosome OSTs. Here, we show by blue-native gel electrophoresis and stable isotope labeling in cell culture proteomics that the TbSTT3A and TbSTT3B proteins associate with each other in large complexes that contain no other detectable protein subunits. We probed the peptide acceptor specificities of the OSTs in vivo using a transgenic glycoprotein reporter system and performed glycoproteomics on endogenous parasite glycoproteins using sequential endoglycosidase H and peptide:N-glycosidase-F digestions. This allowed us to assess the relative occupancies of numerous N-glycosylation sites by endoglycosidase H-resistant N-glycans originating from Man5GlcNAc2-PP-dolichol transferred by TbSTT3A, and endoglycosidase H-sensitive N-glycans originating from Man9GlcNAc2-PP-dolichol transferred by TbSTT3B. Using machine learning, we assessed the features that best define TbSTT3A and TbSTT3B substrates in vivo and built an algorithm to predict the types of N-glycan most likely to predominate at all the putative N-glycosylation sites in the parasite proteome. Finally, molecular modeling was used to suggest why TbSTT3A has a distinct preference for sequons containing and/or flanked by acidic amino acid residues. Together, these studies provide insights into how a highly divergent eukaryote has re-wired protein N-glycosylation to provide protein sequence-specific N-glycan modifications. Data are available via ProteomeXchange with identifiers PXD007236, PXD007267, and PXD007268.