The social network of a cell: recent advances in interactome mapping

Effect of Mechanical Damage in Green-Making Process on Aroma of Rougui Tea

Rougui Tea (RGT) is a typical Wuyi Rock Tea (WRT) that is favored by consumers for its rich taste and varied aroma. The aroma of RGT is greatly affected by the process of green-making, but its mechanism is not clear. Therefore, in this study, fresh leaves of RGT in spring were picked, and green-making (including shaking and spreading) and spreading (unshaken) were, respectively, applied after sun withering. Then, they were analyzed by GC-TOF-MS, which showed that the abundance of volatile compounds with flowery and fruity aromas, such as nerolidol, jasmine lactone, jasmone, indole, hexyl hexanoate, (E)-3-hexenyl butyrate and 1-hexyl acetate, in green-making leaves, was significantly higher than that in spreading leaves. Transcriptomic and proteomic studies showed that long-term mechanical injury and dehydration could activate the upregulated expression of genes related to the formation pathways of the aroma, but the regulation of protein expression was not completely consistent. Mechanical injury in the process of green-making was more conducive to the positive regulation of the allene oxide synthase (AOS) branch of the α-linolenic acid metabolism pathway, followed by the mevalonate (MVA) pathway of terpenoid backbone biosynthesis, thus promoting the synthesis of jasmonic acid derivatives and sesquiterpene products. Protein interaction analysis revealed that the key proteins of the synthesis pathway of jasmonic acid derivatives were acyl-CoA oxidase (ACX), enoyl-CoA hydratase (MFP2), OPC-8:0 CoA ligase 1 (OPCL1) and so on. This study provides a theoretical basis for the further explanation of the formation mechanism of the aroma substances in WRT during the manufacturing process.

Electroporated recombinant proteins as tools for in vivo functional complementation, imaging and chemical biology

Delivery of native or chemically modified recombinant proteins into mammalian cells shows promise for functional investigations and various technological applications, but concerns that sub-cellular localization and functional integrity of delivered proteins may be affected remain high. Here, we surveyed batch electroporation as a delivery tool for single polypeptides and multi-subunit protein assemblies of the kinetochore, a spatially confined and well-studied subcellular structure. After electroporation into human cells, recombinant fluorescent Ndc80 and Mis12 multi-subunit complexes exhibited native localization, physically interacted with endogenous binding partners, and functionally complemented depleted endogenous counterparts to promote mitotic checkpoint signaling and chromosome segregation. Farnesylation is required for kinetochore localization of the Dynein adaptor Spindly. In cells with chronically inhibited farnesyl transferase activity, in vitro farnesylation and electroporation of recombinant Spindly faithfully resulted in robust kinetochore localization. Our data show that electroporation is well-suited to deliver synthetic and chemically modified versions of functional proteins, and, therefore, constitutes a promising tool for applications in chemical and synthetic biology.

Exploring the protein-protein interaction landscape in plants

Protein-protein interactions (PPIs) represent an essential aspect of plant systems biology. Identification of key protein players and their interaction networks provide crucial insights into the regulation of plant developmental processes and into interactions of plants with their environment. Despite the great advance in the methods for the discovery and validation of PPIs, still several challenges remain. First, the PPI networks are usually highly dynamic, and the in vivo interactions are often transient and difficult to detect. Therefore, the properties of the PPIs under study need to be considered to select the most suitable technique, because each has its own advantages and limitations. Second, besides knowledge on the interacting partners of a protein of interest, characteristics of the interaction, such as the spatial or temporal dynamics, are highly important. Hence, multiple approaches have to be combined to obtain a comprehensive view on the PPI network present in a cell. Here, we present the progress in commonly used methods to detect and validate PPIs in plants with a special emphasis on the PPI features assessed in each approach and how they were or can be used for the study of plant interactions with their environment.

Halfway between 2D and Animal Models: Are 3D Cultures the Ideal Tool to Study Cancer-Microenvironment Interactions?

An area that has come to be of tremendous interest in tumor research in the last decade is the role of the microenvironment in the biology of neoplastic diseases. The tumor microenvironment (TME) comprises various cells that are collectively important for normal tissue homeostasis as well as tumor progression or regression. Seminal studies have demonstrated the role of the dialogue between cancer cells (at many sites) and the cellular component of the microenvironment in tumor progression, metastasis, and resistance to treatment. Using an appropriate system of microenvironment and tumor culture is the first step towards a better understanding of the complex interaction between cancer cells and their surroundings. Three-dimensional (3D) models have been widely described recently. However, while it is claimed that they can bridge the gap between in vitro and in vivo, it is sometimes hard to decipher their advantage or limitation compared to classical two-dimensional (2D) cultures, especially given the broad number of techniques used. We present here a comprehensive review of the different 3D methods developed recently, and, secondly, we discuss the pros and cons of 3D culture compared to 2D when studying interactions between cancer cells and their microenvironment.

A Perspective on Extracellular Vesicles Proteomics

Increasing attention has been given to secreted extracellular vesicles (EVs) in the past decades, especially in the portrayal of their molecular cargo and role as messengers in both homeostasis and pathophysiological conditions. This review presents the state-of-the-art proteomic technologies to identify and quantify EVs proteins along with their PTMs, interacting partners and structural details. The rapid growth of mass spectrometry-based analytical strategies for protein sequencing, PTMs and structural characterization has improved the level of molecular details that can be achieved from limited amount of EVs isolated from different biological sources. Here we will provide a perspective view on the achievements and challenges on EVs proteome characterization using mass spectrometry. A detailed bioinformatics approach will help us to picture the molecular fingerprint of EVs and understand better their pathophysiological function.

The systematic analysis of protein-lipid interactions comes of age

Lipids tailor membrane identities and function as molecular hubs in all cellular processes. However, the ways in which lipids modulate protein function and structure are poorly understood and still require systematic investigation. In this Innovation article, we summarize pioneering technologies, including lipid-overlay assays, lipid pull-down assays, affinity-purification lipidomics and the liposome microarray-based assay (LiMA), that will enable protein-lipid interactions to be deciphered on a systems level. We discuss how these technologies can be applied to the charting of system-wide networks and to the development of new pharmaceutical strategies.

PathwayMatrix: visualizing binary relationships between proteins in biological pathways

Background

Molecular activation pathways are inherently complex, and understanding relations across many biochemical reactions and reaction types is difficult. Visualizing and analyzing a pathway is a challenge due to the network size and the diversity of relations between proteins and molecules.

Results

In this paper, we introduce PathwayMatrix, a visualization tool that presents the binary relations between proteins in the pathway via the use of an interactive adjacency matrix. We provide filtering, lensing, clustering, and brushing and linking capabilities in order to present relevant details about proteins within a pathway.

Conclusions

We evaluated PathwayMatrix by conducting a series of in-depth interviews with domain experts who provided positive feedback, leading us to believe that our visualization technique could be helpful for the larger community of researchers utilizing pathway visualizations. PathwayMatrix is freely available at https://github.com/CreativeCodingLab/PathwayMatrix.

Quantitative affinity purification mass spectrometry: a versatile technology to study protein-protein interactions

While the genomic revolution has dramatically accelerated the discovery of disease-associated genes, the functional characterization of the corresponding proteins lags behind. Most proteins fulfill their tasks in complexes with other proteins, and analysis of protein–protein interactions (PPIs) can therefore provide insights into protein function. Several methods can be used to generate large-scale protein interaction networks. However, most of these approaches are not quantitative and therefore cannot reveal how perturbations affect the network. Here, we illustrate how a clever combination of quantitative mass spectrometry with different biochemical methods provides a rich toolkit to study different aspects of PPIs including topology, subunit stoichiometry, and dynamic behavior.

Quantitative Circadian Phosphoproteomic Analysis of Arabidopsis Reveals Extensive Clock Control of Key Components in Physiological, Metabolic, and Signaling Pathways

The circadian clock provides adaptive advantages to an organism, resulting in increased fitness and survival. The phosphorylation events that regulate circadian-dependent signaling and the processes which post-translationally respond to clock-gated signals are largely unknown. To better elucidate post-translational events tied to the circadian system we carried out a survey of circadian-regulated protein phosphorylation events in Arabidopsis seedlings. A large-scale mass spectrometry-based quantitative phosphoproteomics approach employing TiO2-based phosphopeptide enrichment techniques identified and quantified 1586 phosphopeptides on 1080 protein groups. A total of 102 phosphopeptides displayed significant changes in abundance, enabling the identification of specific patterns of response to circadian rhythms. Our approach was sensitive enough to quantitate oscillations in the phosphorylation of low abundance clock proteins (early flowering4; ELF4 and pseudoresponse regulator3; PRR3) as well as other transcription factors and kinases. During constant light, extensive cyclic changes in phosphorylation status occurred in critical regulators, implicating direct or indirect regulation by the circadian system. These included proteins influencing transcriptional regulation, translation, metabolism, stress and phytohormones-mediated responses. We validated our analysis using the elf4-211 allele, in which an S45L transition removes the phosphorylation herein identified. We show that removal of this phosphorylatable site diminishes interaction with early flowering3 (ELF3), a key partner in a tripartite evening complex required for circadian cycling. elf4-211 lengthens period, which increases with increasing temperature, relative to the wild type, resulting in a more stable temperature compensation of circadian period over a wider temperature range.

Rapid, optimized interactomic screening

We must reliably map the interactomes of cellular macromolecular complexes in order to fully explore and understand biological systems. However, there are no methods to accurately predict how to capture a given macromolecular complex with its physiological binding partners. Here, we present a screen that comprehensively explores the parameters affecting the stability of interactions in affinity-captured complexes, enabling the discovery of physiological binding partners and the elucidation of their functional interactions in unparalleled detail. We have implemented this screen on several macromolecular complexes from a variety of organisms, revealing novel profiles even for well-studied proteins. Our approach is robust, economical and automatable, providing an inroad to the rigorous, systematic dissection of cellular interactomes.

Bridging topological and functional information in protein interaction networks by short loops profiling

Protein-protein interaction networks (PPINs) have been employed to identify potential novel interconnections between proteins as well as crucial cellular functions. In this study we identify fundamental principles of PPIN topologies by analysing network motifs of short loops, which are small cyclic interactions of between 3 and 6 proteins. We compared 30 PPINs with corresponding randomised null models and examined the occurrence of common biological functions in loops extracted from a cross-validated high-confidence dataset of 622 human protein complexes. We demonstrate that loops are an intrinsic feature of PPINs and that specific cell functions are predominantly performed by loops of different lengths. Topologically, we find that loops are strongly related to the accuracy of PPINs and define a core of interactions with high resilience. The identification of this core and the analysis of loop composition are promising tools to assess PPIN quality and to uncover possible biases from experimental detection methods. More than 96% of loops share at least one biological function, with enrichment of cellular functions related to mRNA metabolic processing and the cell cycle. Our analyses suggest that these motifs can be used in the design of targeted experiments for functional phenotype detection.

[The use of immobilized ubiquitin for biosensor analysis of the mitochondrial subinteractome]

Protein ubiquitination is considered as an important mechanism that is responsible not only for specific labeling of proteins for their subsequent degradation but also for localization of proteins in the cell and regulation of protein-protein interactions. In the context of protein-protein interactions binding of (mono/poly)ubiquitinated molecules to proteins containing specific ubiquitin binding domains appear to play the decisive role. Although formation of the ubiquitin interactome has been demonstrated for cytosol, involvement of mitochondria and associated extramitochondrial proteins into such interactions still requires detailed investigation. In this study using an optical biosensor we have demonstrated binding of proteins of mouse brain mitochondrial lysates to immobilized monomeric ubiquitin. Model purified proteins, which are known to be associated with the outer mitochondrial compartment (glyceraldehyde-3-phosphate dehydorgenase, creatine phosphokinase), interacted with immobilized ubiquitin as well as with each other. This suggests that (poly)ubiquitinated chains may be involved in protein-protein interactions between ubiquitinated and non-ubiquitinated proteins and thus may contribute to formation of (mitochondrial) ubiquitin subinteractome.

Real-time monitoring of protein conformational changes using a nano-mechanical sensor

Proteins can switch between different conformations in response to stimuli, such as pH or temperature variations, or to the binding of ligands. Such plasticity and its kinetics can have a crucial functional role, and their characterization has taken center stage in protein research. As an example, Topoisomerases are particularly interesting enzymes capable of managing tangled and supercoiled double-stranded DNA, thus facilitating many physiological processes. In this work, we describe the use of a cantilever-based nanomotion sensor to characterize the dynamics of human topoisomerase II (Topo II) enzymes and their response to different kinds of ligands, such as ATP, which enhance the conformational dynamics. The sensitivity and time resolution of this sensor allow determining quantitatively the correlation between the ATP concentration and the rate of Topo II conformational changes. Furthermore, we show how to rationalize the experimental results in a comprehensive model that takes into account both the physics of the cantilever and the dynamics of the ATPase cycle of the enzyme, shedding light on the kinetics of the process. Finally, we study the effect of aclarubicin, an anticancer drug, demonstrating that it affects directly the Topo II molecule inhibiting its conformational changes. These results pave the way to a new way of studying the intrinsic dynamics of proteins and of protein complexes allowing new applications ranging from fundamental proteomics to drug discovery and development and possibly to clinical practice.

Plant systems biology: insights, advances and challenges

Plants dwelling at the base of biological food chain are of fundamental significance in providing solutions to some of the most daunting ecological and environmental problems faced by our planet. The reductionist views of molecular biology provide only a partial understanding to the phenotypic knowledge of plants. Systems biology offers a comprehensive view of plant systems, by employing a holistic approach integrating the molecular data at various hierarchical levels. In this review, we discuss the basics of systems biology including the various 'omics' approaches and their integration, the modeling aspects and the tools needed for the plant systems research. A particular emphasis is given to the recent analytical advances, updated published examples of plant systems biology studies and the future trends.

NMR approaches for structural analysis of multidomain proteins and complexes in solution

NMR spectroscopy is a key method for studying the structure and dynamics of (large) multidomain proteins and complexes in solution. It plays a unique role in integrated structural biology approaches as especially information about conformational dynamics can be readily obtained at residue resolution. Here, we review NMR techniques for such studies focusing on state-of-the-art tools and practical aspects. An efficient approach for determining the quaternary structure of multidomain complexes starts from the structures of individual domains or subunits. The arrangement of the domains/subunits within the complex is then defined based on NMR measurements that provide information about the domain interfaces combined with (long-range) distance and orientational restraints. Aspects discussed include sample preparation, specific isotope labeling and spin labeling; determination of binding interfaces and domain/subunit arrangements from chemical shift perturbations (CSP), nuclear Overhauser effects (NOEs), isotope editing/filtering, cross-saturation, and differential line broadening; and based on paramagnetic relaxation enhancements (PRE) using covalent and soluble spin labels. Finally, the utility of complementary methods such as small-angle X-ray or neutron scattering (SAXS, SANS), electron paramagnetic resonance (EPR) or fluorescence spectroscopy techniques is discussed. The applications of NMR techniques are illustrated with studies of challenging (high molecular weight) protein complexes.

Defining dynamic protein interactions using SILAC-based quantitative mass spectrometry

Protein-protein interactions are essential to various physiological processes in living cells. A full characterization of protein interactions is critical to our understanding of their roles in the regulation of protein functions. Affinity purification coupled with mass spectrometry (AP-MS) has become one of the most effective approaches to systematically study protein-protein interactions. In combination with quantitative mass spectrometry, specific interacting proteins can be efficiently distinguished from nonspecific background proteins. Based on interaction affinity and kinetics, protein interactions can be classified into different categories such as stable and dynamic interactions. Standard biochemical methods are effective in capturing and identifying stable protein interactions but are not sufficient enough to identify dynamic interactors. In this chapter, we describe integrated strategies to allow the identification of dynamic interactors of protein complexes by incorporating new sample preparation methods with SILAC-based quantitation.

Link clustering reveals structural characteristics and biological contexts in signed molecular networks

Many biological networks are signed molecular networks which consist of positive and negative links. To reveal the distinct features between links with different signs, we proposed signed link-clustering coefficients that assess the similarity of inter-action profiles between linked molecules. We found that positive links tended to cluster together, while negative links usually behaved like bridges between positive clusters. Positive links with higher adhesiveness tended to share protein domains, be associated with protein-protein interactions and make intra-connections within protein complexes. Negative links that were more bridge-like tended to make interconnections between protein complexes. Utilizing the proposed measures to group positive links, we observed hierarchical modules that could be well characterized by functional annotations or known protein complexes. Our results imply that the proposed sign-specific measures can help reveal the network structural characteristics and the embedded biological contexts of signed links, as well as the functional organization of signed molecular networks.

Latest developments in experimental and computational approaches to characterize protein-lipid interactions

Understanding the functional roles of all the molecules in cells is an ultimate goal of modern biology. An important facet is to understand the functional contributions from intermolecular interactions, both within a class of molecules (e.g. protein-protein) or between classes (e.g. protein-DNA). While the technologies for analyzing protein-protein and protein-DNA interactions are well established, the field of protein-lipid interactions is still relatively nascent. Here, we review the current status of the experimental and computational approaches for detecting and analyzing protein-lipid interactions. Experimental technologies fall into two principal categories, namely solution-based and array-based methods. Computational methods include large-scale data-driven analyses and predictions/dynamic simulations based on prior knowledge of experimentally identified interactions. Advances in the experimental technologies have led to improved computational analyses and vice versa, thereby furthering our understanding of protein-lipid interactions and their importance in biological systems.

Detection and characterization of protein interactions in vivo by a simple live-cell imaging method

Over the last decades there has been an explosion of new methodologies to study protein complexes. However, most of the approaches currently used are based on in vitro assays (e.g. nuclear magnetic resonance, X-ray, electron microscopy, isothermal titration calorimetry etc). The accurate measurement of parameters that define protein complexes in a physiological context has been largely limited due to technical constrains. Here, we present PICT (Protein interactions from Imaging of Complexes after Translocation), a new method that provides a simple fluorescence microscopy readout for the study of protein complexes in living cells. We take advantage of the inducible dimerization of FK506-binding protein (FKBP) and FKBP-rapamycin binding (FRB) domain to translocate protein assemblies to membrane associated anchoring platforms in yeast. In this assay, GFP-tagged prey proteins interacting with the FRB-tagged bait will co-translocate to the FKBP-tagged anchor sites upon addition of rapamycin. The interactions are thus encoded into localization changes and can be detected by fluorescence live-cell imaging under different physiological conditions or upon perturbations. PICT can be automated for high-throughput studies and can be used to quantify dissociation rates of protein complexes in vivo. In this work we have used PICT to analyze protein-protein interactions from three biological pathways in the yeast Saccharomyces cerevisiae: Mitogen-activated protein kinase cascade (Ste5-Ste11-Ste50), exocytosis (exocyst complex) and endocytosis (Ede1-Syp1).

PodNet, a protein-protein interaction network of the podocyte

Interactions between proteins crucially determine cellular structure and function. Differential analysis of the interactome may help elucidate molecular mechanisms during disease development; however, this analysis necessitates mapping of expression data on protein-protein interaction networks. These networks do not exist for the podocyte; therefore, we built PodNet, a literature-based mouse podocyte network in Cytoscape format. Using database protein-protein interactions, we expanded PodNet to XPodNet with enhanced connectivity. In order to test the performance of XPodNet in differential interactome analysis, we examined podocyte developmental differentiation and the effect of cell culture. Transcriptomes of podocytes in 10 different states were mapped on XPodNet and analyzed with the Cytoscape plugin ExprEssence, based on the law of mass action. Interactions between slit diaphragm proteins are most significantly upregulated during podocyte development and most significantly downregulated in culture. On the other hand, our analysis revealed that interactions lost during podocyte differentiation are not regained in culture, suggesting a loss rather than a reversal of differentiation for podocytes in culture. Thus, we have developed PodNet as a valuable tool for differential interactome analysis in podocytes, and we have identified established and unexplored regulated interactions in developing and cultured podocytes.

Photocrosslinking approaches to interactome mapping

Photocrosslinking approaches can be used to map interactome networks within the context of living cells. Photocrosslinking methods rely on use of metabolic engineering or genetic code expansion to incorporate photocrosslinking analogs of amino acids or sugars into cellular biomolecules. Immunological and mass spectrometry techniques are used to analyze crosslinked complexes, thereby defining specific interactomes. Because photocrosslinking can be conducted in native, cellular settings, it can be used to define context-dependent interactions. Photocrosslinking methods are also ideally suited for determining interactome dynamics, mapping interaction interfaces, and identifying transient interactions in which intrinsically disordered proteins and glycoproteins engage. Here we discuss the application of cell-based photocrosslinking to the study of specific problems in immune cell signaling, transcription, membrane protein dynamics, nucleocytoplasmic transport, and chaperone-assisted protein folding.

Detection of a rare BCR-ABL tyrosine kinase fusion protein in H929 multiple myeloma cells using immunoprecipitation (IP)-tandem mass spectrometry (MS/MS)

Hypothesis directed proteomics offers higher throughput over global analyses. We show that immunoprecipitation (IP)-tandem mass spectrometry (LC-MS/MS) in H929 multiple myeloma (MM) cancer cells led to the discovery of a rare and unexpected BCR-ABL fusion, informing a therapeutic intervention using imatinib (Gleevec). BCR-ABL is the driving mutation in chronic myeloid leukemia (CML) and is uncommon to other cancers. Three different IP-MS experiments central to cell signaling pathways were sufficient to discover a BCR-ABL fusion in H929 cells: phosphotyrosine (pY) peptide IP, p85 regulatory subunit of phosphoinositide-3-kinase (PI3K) IP, and the GRB2 adaptor IP. The pY peptides inform tyrosine kinase activity, p85 IP informs the activating adaptors and receptor tyrosine kinases (RTKs) involved in AKT activation and GRB2 IP identifies RTKs and adaptors leading to ERK activation. Integration of the bait-prey data from the three separate experiments identified the BCR-ABL protein complex, which was confirmed by biochemistry, cytogenetic methods, and DNA sequencing revealed the e14a2 fusion transcript. The tyrosine phosphatase SHP2 and the GAB2 adaptor protein, important for MAPK signaling, were common to all three IP-MS experiments. The comparative treatment of tyrosine kinase inhibitor (TKI) drugs revealed only imatinib, the standard of care in CML, was inhibitory to BCR-ABL leading to down-regulation of pERK and pS6K and inhibiting cell proliferation. These data suggest a model for directed proteomics from patient tumor samples for selecting the appropriate TKI drug(s) based on IP and LC-MS/MS. The data also suggest that MM patients, in addition to CML patients, may benefit from BCR-ABL diagnostic screening.

Personalized medicine: the impact on chemistry

An effective strategy for personalized medicine requires a major conceptual change in the development and application of therapeutics. In this article, we argue that further advances in this field should be made with reference to another conceptual shift, that of network pharmacology. We examine the intersection of personalized medicine and network pharmacology to identify strategies for the development of personalized therapies that are fully informed by network pharmacology concepts. This provides a framework for discussion of the impact personalized medicine will have on chemistry in terms of drug discovery, formulation and delivery, the adaptations and changes in ideology required and the contribution chemistry is already making. New ways of conceptualizing chemistry's relationship with medicine will lead to new approaches to drug discovery and hold promise of delivering safer and more effective therapies.

Time-controlled transcardiac perfusion crosslinking for in vivo interactome studies

The time-controlled transcardiac perfusion crosslinking (tcTPC) method differs from conventional perfusion fixation in that the crosslinking reagent is administered throughout the circulatory system for only a relatively short period of time, thereby allowing limited crosslinking to occur. Bait protein complexes are isolated by affinity capture (AC) under stringent conditions and are recovered from the AC matrix by acidic elution. Affinity-purified proteins are reduced, alkylated, and digested with a specific endoproteinase, such as trypsin. Subsequently, peptides are isotopically labeled, separated by reversed-phase chromatography and analyzed by quantitative tandem mass spectrometry (MS/MS). The proteins crosslinked to the bait protein during tcTPC are identified by database searches with conventional protein identification software. The tcTPC strategy offers unique advantages over alternative approaches for studying a subset of protein complexes which require a particular environment for their structural integrity, such as membrane protein complexes that are notorious for their tendency to dissociate upon detergent solubilization. The sensitivity and utility of this method are influenced by the spatial distribution of chemical groups within the bait protein complexes that can engage in productive crosslinks.

Structural analysis of the UBA domain of X-linked inhibitor of apoptosis protein reveals different surfaces for ubiquitin-binding and self-association

Background

Inhibitor of apoptosis proteins (IAPs) belong to a pivotal antiapoptotic protein family that plays a crucial role in tumorigenesis, cancer progression, chemoresistance and poor patient-survival. X-linked inhibitor of apoptosis protein (XIAP) is a prominent member of IAPs attracting intense research because it has been demonstrated to be a physiological inhibitor of caspases and apoptosis. Recently, an evolutionarily conserved ubiquitin-associated (UBA) domain was identified in XIAP and a number of RING domain-bearing IAPs. This has placed the IAPs in the group of ubiquitin binding proteins. Here, we explore the three-dimensional structure of the XIAP UBA domain (XIAP-UBA) and how it interacts with mono-ubiquitin and diubiquitin conjugates.

Principal Findings

The solution structure of the XIAP-UBA domain was determined by NMR spectroscopy. XIAP-UBA adopts a typical UBA domain fold of three tightly packed α-helices but with an additional N-terminal 3₁₀ helix. The XIAP-UBA binds mono-ubiquitin as well as Lys48-linked and linear-linked diubiquitins at low-micromolar affinities. NMR analysis of the XIAP-UBA–ubiquitin interaction reveals that it involves the classical hydrophobic patches surrounding Ile44 of ubiquitin and the conserved MGF/LV motif surfaces on XIAP-UBA. Furthermore, dimerization of XIAP-UBA was observed. Mapping of the self-association surface of XIAP-UBA reveals that the dimerization interface is formed by residues in the N-terminal 3₁₀ helix, helix α1 and helix α2, separate from the ubiquitin-binding surface.

Conclusion

Our results provide the first structural information of XIAP-UBA and map its interaction with mono-ubiquitin, Lys48-linked and linear-linked diubiquitins. The notion that XIAP-UBA uses different surfaces for ubiquitin-binding and self-association provides a plausible model to explain the reported selectivity of XIAP in binding polyubiquitin chains with different linkages.

Differentially co-expressed interacting protein pairs discriminate samples under distinct stages of HIV type 1 infection

Background

Microarray analyses based on differentially expressed genes (DEGs) have been widely used to distinguish samples across different cellular conditions. However, studies based on DEGs have not been able to clearly determine significant differences between samples of pathophysiologically similar HIV-1 stages, e.g., between acute and chronic progressive (or AIDS) or between uninfected and clinically latent stages. We here suggest a novel approach to allow such discrimination based on stage-specific genetic features of HIV-1 infection. Our approach is based on co-expression changes of genes known to interact. The method can identify a genetic signature for a single sample as contrasted with existing protein-protein-based analyses with correlational designs.

Methods

Our approach distinguishes each sample using differentially co-expressed interacting protein pairs (DEPs) based on co-expression scores of individual interacting pairs within a sample. The co-expression score has positive value if two genes in a sample are simultaneously up-regulated or down-regulated. And the score has higher absolute value if expression-changing ratios are similar between the two genes. We compared characteristics of DEPs with that of DEGs by evaluating their usefulness in separation of HIV-1 stage. And we identified DEP-based network-modules and their gene-ontology enrichment to find out the HIV-1 stage-specific gene signature.

Results

Based on the DEP approach, we observed clear separation among samples from distinct HIV-1 stages using clustering and principal component analyses. Moreover, the discrimination power of DEPs on the samples (70–100% accuracy) was much higher than that of DEGs (35–45%) using several well-known classifiers. DEP-based network analysis also revealed the HIV-1 stage-specific network modules; the main biological processes were related to “translation,” “RNA splicing,” “mRNA, RNA, and nucleic acid transport,” and “DNA metabolism.” Through the HIV-1 stage-related modules, changing stage-specific patterns of protein interactions could be observed.

Conclusions

DEP-based method discriminated the HIV-1 infection stages clearly, and revealed a HIV-1 stage-specific gene signature. The proposed DEP-based method might complement existing DEG-based approaches in various microarray expression analyses.

Monitoring protein-protein interactions in mammalian cells by trans-SUMOylation

Protein-protein interactions are essential for almost all cellular processes, hence understanding these processes mainly depends on the identification and characterization of the relevant protein-protein interactions. In the present paper, we introduce the concept of TRS (trans-SUMOylation), a new method developed to identify and verify protein-protein interactions in mammalian cells in vivo. TRS utilizes Ubc9-fusion proteins that trans-SUMOylate co-expressed interacting proteins. Using TRS, we analysed interactions of 65 protein pairs co-expressed in HEK (human embryonic kidney)-293 cells. We identified seven new and confirmed 16 known protein interactions, which were determined via endogenous SUMOylation sites of the binding partners or by using SUMOylation-site tags respectively. Four of the new protein interactions were confirmed by GST (glutathione transferase) pull-down and the p38α-Edr2 interaction was verified by co-localization analysis. Functionally, this p38α-Edr2 interaction could possibly be involved in the recruitment of p38α to the polycomb chromatin-remodelling complex to phosphorylate Bmi1. We also used TRS to characterize protein-interaction domains of the protein kinase pairs p38α-MK2 [MK is MAPK (mitogen-activated protein kinase)-activated protein kinase] and ERK3 (extracellular-signal-regulated kinase 3)-MK5 and of the p38α-p53 complex. The ability of TRS to monitor protein interactions in mammalian cells in vivo at levels similar to endogenous expression makes it an excellent new tool that can help in defining the protein interactome of mammalian cells.

Triple SILAC to determine stimulus specific interactions in the Wnt pathway

Many important regulatory functions are performed by dynamic multiprotein complexes that adapt their composition and activity in response to different stimuli. Here we employ quantitative affinity purification coupled with mass spectrometry to efficiently separate background from specific interactors but add an additional quantitative dimension to explicitly characterize stimulus-dependent interactions. This is accomplished by SILAC in a triple-labeling format, in which pull-downs with bait, with bait and stimulus, and without bait are quantified against each other. As baits, we use full-length proteins fused to the green fluorescent protein and expressed under endogenous control. We applied this technology to Wnt signaling, which is important in development, tissue homeostasis, and cancer, and investigated interactions of the key components APC, Axin-1, DVL2, and CtBP2 with differential pathway activation. Our screens identify many known Wnt signaling complex components and link novel candidates to Wnt signaling, including FAM83B and Girdin, which we found as interactors to multiple Wnt pathway players. Girdin binds to DVL2 independent of stimulation with the ligand Wnt3a but to Axin-1 and APC in a stimulus-dependent manner. The core destruction complex itself, which regulates beta-catenin stability as the key step in canonical Wnt signaling, remained essentially unchanged.

SCOWLP update: 3D classification of protein-protein, -peptide, -saccharide and -nucleic acid interactions, and structure-based binding inferences across folds

Background

Protein interactions are essential for coordinating cellular functions. Proteomic studies have already elucidated a huge amount of protein-protein interactions that require detailed functional analysis. Understanding the structural basis of each individual interaction through their structural determination is necessary, yet an unfeasible task. Therefore, computational tools able to predict protein binding regions and recognition modes are required to rationalize putative molecular functions for proteins. With this aim, we previously created SCOWLP, a structural classification of protein binding regions at protein family level, based on the information obtained from high-resolution 3D protein-protein and protein-peptide complexes.

Description

We present here a new version of SCOWLP that has been enhanced by the inclusion of protein-nucleic acid and protein-saccharide interactions. SCOWLP takes interfacial solvent into account for a detailed characterization of protein interactions. In addition, the binding regions obtained per protein family have been enriched by the inclusion of predicted binding regions, which have been inferred from structurally related proteins across all existing folds. These inferences might become very useful to suggest novel recognition regions and compare structurally similar interfaces from different families.

Conclusions

The updated SCOWLP has new functionalities that allow both, detection and comparison of protein regions recognizing different types of ligands, which include other proteins, peptides, nucleic acids and saccharides, within a solvated environment. Currently, SCOWLP allows the analysis of predicted protein binding regions based on structure-based inferences across fold space. These predictions may have a unique potential in assisting protein docking, in providing insights into protein interaction networks, and in guiding rational engineering of protein ligands. The newly designed SCOWLP web application has an improved user-friendly interface that facilitates its usage, and is available at http://www.scowlp.org.

Network-based methods for human disease gene prediction

Despite the considerable progress in disease gene discovery, we are far from uncovering the underlying cellular mechanisms of diseases since complex traits, even many Mendelian diseases, cannot be explained by simple genotype-phenotype relationships. More recently, an increasingly accepted view is that human diseases result from perturbations of cellular systems, especially molecular networks. Genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks. Such observations have built the basis for a large collection of computational approaches to find previously unknown genes associated with certain diseases. The majority of the methods are based on protein interactome networks, with integration of other large-scale genomic data or disease phenotype information, to infer how likely it is that a gene is associated with a disease. Here, we review recent, state of the art, network-based methods used for prioritizing disease genes as well as unraveling the molecular basis of human diseases.

Interactome networks and human disease

Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease.

Investigating a macromolecular complex: the toolkit of methods

Structural biologists studying macromolecular complexes spend considerable effort doing strictly "non-structural" work: investigating the physiological relevance and biochemical properties of a complex, preparing homogeneous samples for structural analysis, and experimentally validating structure-based hypotheses regarding function or mechanism. Familiarity with the diverse perspectives and techniques available for studying complexes helps in the critical assessment of non-structural data, expedites the pre-structural characterization of a complex and facilitates the investigation of function. Here we survey the approaches and techniques used to study macromolecular complexes from various viewpoints, including genetics, cell and molecular biology, biochemistry/biophysics, structural biology, and systems biology/bioinformatics. The aim of this overview is to heighten awareness of the diversity of perspectives and experimental tools available for investigating complexes and of their usefulness for the structural biologist.

Mass Spectrometry for Structural Biology: Determining the Composition and Architecture of Protein Complexes

Knowledge of protein structure and protein–protein interactions is vital for appreciating the elaborate biochemical pathways that underlie cellular function. While many techniques exist to probe the structure and complex interplay between functional proteins, none currently offer a complete picture. Mass spectrometry and associated methods provide complementary information to established structural biology tools, and with rapidly evolving technological advances, can in some cases even exceed other techniques by its diversity in application and information content. This is primarily because of the ability of mass spectrometry to precisely identify protein complex stoichiometry, detect individual species present in a mixture, and concomitantly offer conformational information. This review describes the attributes of mass spectrometry for the structural investigation of multiprotein assemblies in the context of recent developments and highlights in the field.

Genetic approaches to aging in budding and fission yeasts: new connections and new opportunities

Yeasts are powerful model systems to examine the evolutionarily conserved aspects of eukaryotic aging because they maintain many of the same core cellular signaling pathways and essential organelles as human cells. We constructed a strain of the budding yeast Saccharomyces cerevisiae that could monitor the distribution of proteins involved in heterochromatic silencing and aging, and isolated mutants that alter this distribution. The largest class of such mutants cause defects in mitochondrial function, and appear to cause changes in nuclear silencing separate from the well-known Rtg2p-dependent pathway that alters nuclear transcription in response to the loss of the mitochondrial genome. Mutants that inactivate the ATP2 gene, which encodes the ATPase subunit of the mitochondrial F(1)F(0)-ATPase, were isolated twice in our screen and identify a lifespan extending pathway in a gene that is conserved in both prokaryotes and eukaryotes. The budding yeast S. cerevisiae S. cerevisiae has been used with great success to identify other lifespan-extending pathways in screens using surrogate phenotypes such as stress resistance or silencing to identify random mutants, or in high throughput screens that utilize the deletion strain set resource. However, the direct selection of long-lived mutants from a pool of random mutants is more challenging. We have established a new chronological aging assay for the evolutionarily distant fission yeast Schizosaccharomyces pombe that recapitulates aspects of aging conserved in all eukaryotes. We have constructed a novel S. pombe S. pombe DNA insertion mutant bank, and used it to show that we can directly select for a long-lived mutant. The use of both the budding and fission yeast systems should continue to facilitate the identification and validation of lifespan extending pathways that are conserved in humans.

Literature curation of protein interactions: measuring agreement across major public databases

Literature curation of protein interaction data faces a number of challenges. Although curators increasingly adhere to standard data representations, the data that various databases actually record from the same published information may differ significantly. Some of the reasons underlying these differences are well known, but their global impact on the interactions collectively curated by major public databases has not been evaluated. Here we quantify the agreement between curated interactions from 15 471 publications shared across nine major public databases. Results show that on average, two databases fully agree on 42% of the interactions and 62% of the proteins curated from the same publication. Furthermore, a sizable fraction of the measured differences can be attributed to divergent assignments of organism or splice isoforms, different organism focus and alternative representations of multi-protein complexes. Our findings highlight the impact of divergent curation policies across databases, and should be relevant to both curators and data consumers interested in analyzing protein-interaction data generated by the scientific community.

Database URL:http://wodaklab.org/iRefWeb

Interactome mapping suggests new mechanistic details underlying Alzheimer's disease

Recent advances toward the characterization of Alzheimer's disease (AD) have permitted the identification of a dozen of genetic risk factors, although many more remain undiscovered. In parallel, works in the field of network biology have shown a strong link between protein connectivity and disease. In this manuscript, we demonstrate that AD-related genes are indeed highly interconnected and, based on this observation, we set up an interaction discovery strategy to unveil novel AD causative and susceptibility genes. In total, we report 200 high-confidence protein-protein interactions between eight confirmed AD-related genes and 66 candidates. Of these, 31 are located in chromosomal regions containing susceptibility loci related to the etiology of late-onset AD, and 17 show dysregulated expression patterns in AD patients, which makes them very good candidates for further functional studies. Interestingly, we also identified four novel direct interactions among well-characterized AD causative/susceptibility genes (i.e., APP, A2M, APOE, PSEN1, and PSEN2), which support the suggested link between plaque formation and inflammatory processes and provide insights into the intracellular regulation of APP cleavage. Finally, we contextualize the discovered relationships, integrating them with all the interaction data reported in the literature, building the most complete interactome associated to AD. This general view facilitates the analyses of global properties of the network, such as its functional modularity, and triggers many hypotheses on the molecular mechanisms implicated in AD. For instance, our analyses suggest a putative role for PDCD4 as a neuronal death regulator and ECSIT as a molecular link between oxidative stress, inflammation, and mitochondrial dysfunction in AD.

Revealing the molecular relationship between type 2 diabetes and the metabolic changes induced by a very-low-carbohydrate low-fat ketogenic diet

Background

The prevalence of type 2 diabetes is increasing worldwide, accounting for 85-95% of all diagnosed cases of diabetes. Clinical trials provide evidence of benefits of low-carbohydrate ketogenic diets in terms of clinical outcomes on type 2 diabetes patients. However, the molecular events responsible for these improvements still remain unclear in spite of the high amount of knowledge on the primary mechanisms of both the diabetes and the metabolic state of ketosis. Molecular network analysis of conditions, diseases and treatments might provide new insights and help build a better understanding of clinical, metabolic and molecular relationships among physiological conditions. Accordingly, our aim is to reveal such a relationship between a ketogenic diet and type 2 diabetes through systems biology approaches.

Methods

Our systemic approach is based on the creation and analyses of the cell networks representing the metabolic state in a very-low-carbohydrate low-fat ketogenic diet. This global view might help identify unnoticed relationships often overlooked in molecule or process-centered studies.

Results

A strong relationship between the insulin resistance pathway and the ketosis main pathway was identified, providing a possible explanation for the improvement observed in clinical trials. Moreover, the map analyses permit the formulation of some hypothesis on functional relationships between the molecules involved in type 2 diabetes and induced ketosis, suggesting, for instance, a direct implication of glucose transporters or inflammatory processes. The molecular network analysis performed in the ketogenic-diet map, from the diabetes perspective, has provided insights on the potential mechanism of action, but also has opened new possibilities to study the applications of the ketogenic diet in other situations such as CNS or other metabolic dysfunctions.

Recent advances in charting protein-protein interaction: mass spectrometry-based approaches

Cellular functions are the result of the coordinated action of groups of proteins interacting in molecular assemblies or pathways. The systematic and unbiased charting of protein-protein networks in a variety of organisms has become an important challenge in systems biology. These protein-protein interaction networks contribute comprehensive cartographies of key pathways or biological processes relevant to health or disease by providing a molecular frame for the interpretation of genetic links. At a structural level protein-protein networks enabled the identification of the sequences, motifs and structural folds involved in the process of molecular recognition. A rapidly growing choice of technologies is available for the global charting of protein-protein interactions. In this review, we focus on recent developments in a suite of methods that enable the purification of protein complexes under native conditions and, in conjunction with protein mass spectrometry, identification of their constituents.

Testicular postgenomics: targeting the regulation of spermatogenesis

Sperm are, arguably, the most differentiated cells produced within the body of any given species. This is owing to the fact that spermatogenesis is an intricate and highly specialized process evolved to suit the individual particularities of each sexual species. Despite a vast diversity in method, the aim of spermatogenesis is always the same, the idealized transmission of genetic patrimony. Towards this goal certain requirements must always be met, such as a relative twofold reduction in ploidy, repackaging of the chromatin for transport and specialized enhancements for cell motility, recognition and fusion. In the past 20 years, the study of molecular networks coordinating male germ cell development, particularly in mammals, has become more and more facilitated thanks to large-scale analyses of genome expression. Such postgenomic endeavors have generated landscapes of data for both fundamental and clinical reproductive biology. Continuous, large-scale integration analyses of these datasets are undertaken which provide access to very precise information on a myriad of biomolecules. This review presents commonly used transcriptomic and proteomic workflows applied to various testicular germ cell studies. We will also provide a general overview of the technical possibilities available to reproductive genomic biologists, noting the advantages and drawbacks of each technique.