Structural and functional protein network analyses predict novel signaling functions for rhodopsin

On the origin of proteins in human drusen: The meet, greet and stick hypothesis

Retinal drusen formation is not only a clinical hallmark for the development of age-related macular degeneration (AMD) but also for other disorders, such as Alzheimer's disease and renal diseases. The initiation and growth of drusen is poorly understood. Attention has focused on lipids and minerals, but relatively little is known about the origin of drusen-associated proteins and how they are retained in the space between the basal lamina of the retinal pigment epithelium and the inner collagenous layer space (sub-RPE-BL space). While some authors suggested that drusen proteins are mainly derived from cellular debris from processed photoreceptor outer segments and the RPE, others suggest a choroidal cell or blood origin. Here, we reviewed and supplemented the existing literature on the molecular composition of the retina/choroid complex, to gain a more complete understanding of the sources of proteins in drusen. These "drusenomics" studies showed that a considerable proportion of currently identified drusen proteins is uniquely originating from the blood. A smaller, but still large fraction of drusen proteins comes from both blood and/or RPE. Only a small proportion of drusen proteins is uniquely derived from the photoreceptors or choroid. We next evaluated how drusen components may "meet, greet and stick" to each other and/or to structures like hydroxyapatite spherules to form macroscopic deposits in the sub-RPE-BL space. Finally, we discuss implications of our findings with respect to the previously proposed homology between drusenogenesis in AMD and plaque formation in atherosclerosis.

Analyzing of Molecular Networks for Human Diseases and Drug Discovery

Molecular networks represent the interactions and relations of genes/proteins, and also encode molecular mechanisms of biological processes, development and diseases. Among the molecular networks, protein-protein Interaction Networks (PINs) have become effective platforms for uncovering the molecular mechanisms of diseases and drug discovery. PINs have been constructed for various organisms and utilized to solve many biological problems. In human, most proteins present their complex functions by interactions with other proteins, and the sum of these interactions represents the human protein interactome. Especially in the research on human disease and drugs, as an emerging tool, the PIN provides a platform to systematically explore the molecular complexities of specific diseases and the references for drug design. In this review, we summarized the commonly used approaches to aid disease research and drug discovery with PINs, including the network topological analysis, identification of novel pathways, drug targets and sub-network biomarkers for diseases. With the development of bioinformatic techniques and biological networks, PINs will play an increasingly important role in human disease research and drug discovery.

Opportunities and Challenges of Whole-Cell and -Tissue Simulations of the Outer Retina in Health and Disease

Visual processing starts in the outer retina, where photoreceptor cells sense photons that trigger electrical responses. Retinal pigment epithelial cells are located external to the photoreceptor layer and have critical functions in supporting cell and tissue homeostasis and thus sustaining a healthy retina. The high level of specialization makes the retina vulnerable to alterations that promote retinal degeneration. In this review, we discuss opportunities and challenges in proposing whole-cell and -tissue simulations of the human outer retina. An implicit position taken throughout this review is that mapping diverse data sets onto integrative computational models is likely to be a pivotal approach to understanding complex disease and developing novel interventions.

Simple and complex retinal dystrophies are associated with profoundly different disease networks

Retinopathies are a group of monogenetic or complex retinal diseases associated with high unmet medical need. Monogenic disorders are caused by rare genetic variation and usually arise early in life. Other diseases, such as age-related macular degeneration (AMD), develop late in life and are considered to be of complex origin as they develop from a combination of genetic, ageing, environmental and lifestyle risk factors. Here, we contrast the underlying disease networks and pathological mechanisms of monogenic as opposed to complex retinopathies, using AMD as an example of the latter. We show that, surprisingly, genes associated with the different forms of retinopathies in general do not overlap despite their overlapping retinal phenotypes. Further, AMD risk genes participate in multiple networks with interaction partners that link to different ubiquitous pathways affecting general tissue integrity and homeostasis. Thus AMD most likely represents an endophenotype with differing underlying pathogenesis in different subjects. Localising these pathomechanisms and processes within and across different retinal anatomical compartments provides a novel representation of AMD that may be extended to complex disease in general. This approach may generate improved treatment options that target multiple processes with the aim of restoring tissue homeostasis and maintaining vision.

A Comprehensive View of the β-Arrestinome

G protein-coupled receptors (GPCRs) are membrane receptors critically involved in sensing the environment and orchestrating physiological processes. As such, they transduce extracellular signals such as hormone, neurotransmitters, ions, and light into an integrated cell response. The intracellular trafficking, internalization, and signaling ability of ligand-activated GPCRs are controlled by arrestins, adaptor proteins that they interact with upon ligand binding. β-arrestins 1 and 2 in particular are now considered as hub proteins assembling multiprotein complexes to regulate receptor fate and transduce diversified cell responses. While more than 400 β-arrestin interaction partners have been identified so far, much remains to be learnt on how discrimination between so many binding partners is accomplished. Here, we gathered the interacting partners of β-arrestins through database mining and manual curation of the literature to map the β-arrestin interactome (β-arrestinome). We discussed several parameters that determine compatible (AND) or mutually exclusive (XOR) binding of β-arrestin interactors, such as structural constraints, intracellular abundance, or binding affinity.

microRNA regulatory circuits in a mouse model of inherited retinal degeneration

miRNA dysregulation is a hallmark of many neurodegenerative disorders, including those involving the retina. Up-regulation of miR-1/133 and miR-142, and down-regulation of miR-183/96/182 has been described in the RHO-P347S mouse retina, a model for a common form of inherited blindness. High-throughput LC-MS/MS was employed to analyse the protein expression of predicted targets for these miRNAs in RHO-P347S mouse retinas; 133 potential target genes were identified. Pathway over-representation analysis suggests G-protein signaling/visual transduction, and synaptic transmission for miR-1, and transmembrane transport, cell-adhesion, signal transduction and apoptosis for miR-183/96/182 as regulated functions in retina. Validation of miRNA-target mRNA interactions for miR-1, miR-96/182 and miR-96 targeting Ctbp2, Rac1 and Slc6a9, respectively, was demonstrated in vitro. In vivo interaction of miR-183/96/182 and Rac1 mRNA in retina was confirmed using miR-CATCH. Additional miRNAs (including miR-103-3p, miR-9-5p) were both predicted to target Rac1 mRNA and enriched by Rac1-miR-CATCH. Other Rac1-miR-CATCH-enriched miRNAs (including miR-125a/b-5p, miR-378a-3p) were not predicted to target Rac1. Furthermore, levels of ~25% of the retinal Rac1 interactors were determined by LC-MS/MS; expression of Rap1gds1 and Cav1 was elevated. Our data suggest significant utilisation of miRNA-based regulation in retina. Possibly more than 30 miRNAs interact with Rac1 in retina, targeting both UTRs and coding regions.

Protein and Signaling Networks in Vertebrate Photoreceptor Cells

Vertebrate photoreceptor cells are exquisite light detectors operating under very dim and bright illumination. The photoexcitation and adaptation machinery in photoreceptor cells consists of protein complexes that can form highly ordered supramolecular structures and control the homeostasis and mutual dependence of the secondary messengers cyclic guanosine monophosphate (cGMP) and Ca²⁺. The visual pigment in rod photoreceptors, the G protein-coupled receptor rhodopsin is organized in tracks of dimers thereby providing a signaling platform for the dynamic scaffolding of the G protein transducin. Illuminated rhodopsin is turned off by phosphorylation catalyzed by rhodopsin kinase (GRK1) under control of Ca²⁺-recoverin. The GRK1 protein complex partly assembles in lipid raft structures, where shutting off rhodopsin seems to be more effective. Re-synthesis of cGMP is another crucial step in the recovery of the photoresponse after illumination. It is catalyzed by membrane bound sensory guanylate cyclases (GCs) and is regulated by specific neuronal Ca²⁺-sensor proteins called guanylate cyclase-activating proteins (GCAPs). At least one GC (ROS-GC1) was shown to be part of a multiprotein complex having strong interactions with the cytoskeleton and being controlled in a multimodal Ca²⁺-dependent fashion. The final target of the cGMP signaling cascade is a cyclic nucleotide-gated (CNG) channel that is a hetero-oligomeric protein located in the plasma membrane and interacting with accessory proteins in highly organized microdomains. We summarize results and interpretations of findings related to the inhomogeneous organization of signaling units in photoreceptor outer segments.

Dissecting the calcium-induced differentiation of human primary keratinocytes stem cells by integrative and structural network analyses

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products ('di-chromatic'), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation.

The interaction network of rhodopsin involving the heterotrimeric G-protein transducin and the monomeric GTPase Rac1 is determined by distinct binding processes

The monomeric G-protein Rac1, a member of the family of Rho/Rac/Cdc42 GTPases, is involved in light-induced photoreceptor degeneration, but its specific role remains elusive. In particular, reports on Rac1 interacting with the visual pigment rhodopsin are puzzling and need a more quantitative examination. We probed the presence of Rac1 in rod outer segments by immunohistochemical staining of bovine retinae and western blot analysis of isolated rod outer segments. Rac1 was present throughout the whole retina except in the outer and inner nuclear layers, but was strongly expressed in photoreceptor cells. Rac1 was distributed in three different fractions of rod outer segments: one fraction was soluble in detergents, a second fraction cosegregated with lipid rafts, and a third fraction was associated with lipid bilayer free axonemal/cytoskeletal structures. We also investigated the interaction between rhodopsin and Rac1 by using surface plasmon resonance spectroscopy under dark and light conditions. Biophysical interaction studies revealed that Rac1 could interact with rhodopsin, but in a light-independent manner, and kinetic analysis indicated that binding of Rac1 occurred with lower affinity and speed than the association of transducin and rhodopsin. Thus, in dark-adapted rod cells, Rac1 cannot compete with transducin for binding to rhodopsin, and signalling can proceed normally. Instead, the concentration of transducin has to drop significantly so that Rac1 can bind to rhodopsin; in the outer segment, this occurs only under intense illumination, when transducin is translocated to the inner segment.

From proteomes to complexomes in the era of systems biology

Protein complexes carry out almost the entire signaling and functional processes in the cell. The protein complex complement of a cell, and its network of complex-complex interactions, is referred to here as the complexome. Computational methods to predict protein complexes from proteomics data, resulting in network representations of complexomes, have recently being developed. In addition, key advances have been made toward understanding the network and structural organization of complexomes. We review these bioinformatics advances, and their discovery-potential, as well as the merits of integrating proteomics data with emerging methods in systems biology to study protein complex signaling. It is envisioned that improved integration of proteomics and systems biology, incorporating the dynamics of protein complexes in space and time, may lead to more predictive models of cell signaling networks for effective modulation.

Structural bioinformatics of the interactome

The past decade has seen a dramatic expansion in the number and range of techniques available to obtain genome-wide information and to analyze this information so as to infer both the functions of individual molecules and how they interact to modulate the behavior of biological systems. Here, we review these techniques, focusing on the construction of physical protein-protein interaction networks, and highlighting approaches that incorporate protein structure, which is becoming an increasingly important component of systems-level computational techniques. We also discuss how network analyses are being applied to enhance our basic understanding of biological systems and their disregulation, as well as how these networks are being used in drug development.

Elution profile analysis of SDS-induced subcomplexes by quantitative mass spectrometry

Analyzing the molecular architecture of native multiprotein complexes via biochemical methods has so far been difficult and error prone. Protein complex isolation by affinity purification can define the protein repertoire of a given complex, yet, it remains difficult to gain knowledge of its substructure or modular composition. Here, we introduce SDS concentration gradient induced decomposition of protein complexes coupled to quantitative mass spectrometry and in silico elution profile distance analysis. By applying this new method to a cellular transport module, the IFT/lebercilin complex, we demonstrate its ability to determine modular composition as well as sensitively detect known and novel complex components. We show that the IFT/lebercilin complex can be separated into at least five submodules, the IFT complex A, the IFT complex B, the 14-3-3 protein complex and the CTLH complex, as well as the dynein light chain complex. Furthermore, we identify the protein TULP3 as a potential new member of the IFT complex A and showed that several proteins, classified as IFT complex B-associated, are integral parts of this complex. To further demonstrate EPASIS general applicability, we analyzed the modular substructure of two additional complexes, that of B-RAF and of 14-3-3-ε. The results show, that EPASIS provides a robust as well as sensitive strategy to dissect the substructure of large multiprotein complexes in a highly time- as well as cost-effective manner.

A comparative study of Whi5 and retinoblastoma proteins: from sequence and structure analysis to intracellular networks

Cell growth and proliferation require a complex series of tight-regulated and well-orchestrated events. Accordingly, proteins governing such events are evolutionary conserved, even among distant organisms. By contrast, it is more singular the case of “core functions” exerted by functional analogous proteins that are not homologous and do not share any kind of structural similarity. This is the case of proteins regulating the G1/S transition in higher eukaryotes–i.e., the retinoblastoma (Rb) tumor suppressor Rb—and budding yeast, i.e., Whi5. The interaction landscape of Rb and Whi5 is quite large, with more than one hundred proteins interacting either genetically or physically with each protein. The Whi5 interactome has been used to construct a concept map of Whi5 function and regulation. Comparison of physical and genetic interactors of Rb and Whi5 allows highlighting a significant core of conserved, common functionalities associated with the interactors indicating that structure and function of the network—rather than individual proteins—are conserved during evolution. A combined bioinformatics and biochemical approach has shown that the whole Whi5 protein is highly disordered, except for a small region containing the protein family signature. The comparison with Whi5 homologs from Saccharomycetales has prompted the hypothesis of a modular organization of structural disorder, with most evolutionary conserved regions alternating with highly variable ones. The finding of a consensus sequence points to the conservation of a specific phosphorylation rhythm along with two disordered sequence motifs, probably acting as phosphorylation-dependent seeds in Whi5 folding/unfolding. Thus, the widely disordered Whi5 appears to act as a hierarchical, “date hub” that has evolutionary assayed an original way of modular organization before being supplanted by the globular, multi-domain structured Rb, more suitable to cover the role of a “party hub”.

Interaction of 4.1G and cGMP-gated channels in rod photoreceptor outer segments

In photoreceptors, the assembly of signaling molecules into macromolecular complexes is important for phototransduction and maintaining the structural integrity of rod outer segments (ROSs). However, the molecular composition and formation of these complexes are poorly understood. Using immunoprecipitation and mass spectrometry, 4.1G was identified as a new interacting partner for the cyclic-nucleotide gated (CNG) channels in ROSs. 4.1G is a widely expressed multifunctional protein that plays a role in the assembly and stability of membrane protein complexes. Multiple splice variants of 4.1G were cloned from bovine retina. A smaller splice variant of 4.1G selectively interacted with CNG channels not associated with peripherin-2-CNG channel complex. A combination of truncation studies and domain-binding assays demonstrated that CNG channels selectively interacted with 4.1G through their FERM and CTD domains. Using immunofluorescence, labeling of 4.1G was seen to be punctate and partially colocalized with CNG channels in the ROS. Our studies indicate that 4.1G interacts with a subset of CNG channels in the ROS and implicate this protein-protein interaction in organizing the spatial arrangement of CNG channels in the plasma membrane of outer segments.

Molecular complexes that direct rhodopsin transport to primary cilia

Rhodopsin is a key molecular constituent of photoreceptor cells, yet understanding of how it regulates photoreceptor membrane trafficking and biogenesis of light-sensing organelles, the rod outer segments (ROS) is only beginning to emerge. Recently identified sequence of well-orchestrated molecular interactions of rhodopsin with the functional networks of Arf and Rab GTPases at multiple stages of intracellular targeting fits well into the complex framework of the biogenesis and maintenance of primary cilia, of which the ROS is one example. This review will discuss the latest progress in dissecting the molecular complexes that coordinate rhodopsin incorporation into ciliary-targeted carriers with the recruitment and activation of membrane tethering complexes and regulators of fusion with the periciliary plasma membrane. In addition to revealing the fundamental principals of ciliary membrane renewal, recent advances also provide molecular insight into the ways by which disruptions of the exquisitely orchestrated interactions lead to cilia dysfunction and result in human retinal dystrophies and syndromic diseases that affect multiple organs, including the eyes.

Relevance of rhodopsin studies for GPCR activation

Rhodopsin, the dim-light photoreceptor present in the rod cells of the retina, is both a retinal-binding protein and a G protein-coupled receptor (GPCR). Due to this conjunction, it benefits from an arsenal of spectroscopy techniques that can be used for its characterization, while being a model system for the important family of Class A (also referred to as "rhodopsin-like") GPCRs. For instance, rhodopsin has been a crucial player in the field of GPCR structural biology. Until 2007, it was the only GPCR for which a high-resolution crystal structure was available, so all structure-activity analyses on GPCRs, from structure-based drug discovery to studies of structural changes upon activation, were based on rhodopsin. At present, about a third of currently available GPCR structures are still from rhodopsin. In this review, I show some examples of how these structures can still be used to gain insight into general aspects of GPCR activation. First, the analysis of the third intracellular loop in rhodopsin structures allows us to gain an understanding of the structural and dynamic properties of this region, which is absent (due to protein engineering or poor electron density) in most of the currently available GPCR structures. Second, a detailed analysis of the structure of the transmembrane domains in inactive, intermediate and active rhodopsin structures allows us to detect early conformational changes in the process of ligand-induced GPCR activation. Finally, the analysis of a conserved ligand-activated transmission switch in the transmembrane bundle of GPCRs in the context of the rhodopsin activation cycle, allows us to suggest that the structures of many of the currently available agonist-bound GPCRs may correspond to intermediate active states. While the focus in GPCR structural biology is inevitably moving away from rhodopsin, in other aspects rhodopsin is still at the forefront. For instance, the first studies of the structural basis of disease mutants in GPCRs, or the most detailed analysis of cellular GPCR signal transduction networks using a systems biology approach, have been carried out in rhodopsin. Finally, due again to its unique properties among GPCRs, rhodopsin will likely play an important role in the application of X-ray free electron laser crystallography to time-resolved structural biology in membrane proteins. Rhodopsin, thus, still remains relevant as a model system to study the molecular mechanisms of GPCR activation. This article is part of a Special Issue entitled: Retinal Proteins-You can teach an old dog new tricks.

'Pathway drug cocktail': targeting Ras signaling based on structural pathways

Tumors bearing Ras mutations are notoriously difficult to treat. Drug combinations targeting the Ras protein or its pathway have also not met with success. 'Pathway drug cocktails', which are combinations aiming at parallel pathways, appear more promising; however, to be usefully exploited, a repertoire of classified pathway combinations is desirable. This challenge would be facilitated by the availability of the structural network of signaling pathways. When integrated with functional and systems level clinical data, they can be powerful in advancing novel therapeutic platforms. Based on structural knowledge, drug cocktails may tear into multiple cellular processes that drive tumorigenesis, and help in deciphering the interrelationship between Ras mutations and the rewired Ras network. The pathway drug cocktail paradigm can be applied to other signaling protein targets.

Exploring the rate-limiting steps in visual phototransduction recovery by bottom-up kinetic modeling

Background

Phototransduction in vertebrate photoreceptor cells represents a paradigm of signaling pathways mediated by G-protein-coupled receptors (GPCRs), which share common modules linking the initiation of the cascade to the final response of the cell. In this work, we focused on the recovery phase of the visual photoresponse, which is comprised of several interacting mechanisms.

Results

We employed current biochemical knowledge to investigate the response mechanisms of a comprehensive model of the visual phototransduction pathway. In particular, we have improved the model by implementing a more detailed representation of the recoverin (Rec)-mediated calcium feedback on rhodopsin kinase and including a dynamic arrestin (Arr) oligomerization mechanism. The model was successfully employed to investigate the rate limiting steps in the recovery of the rod photoreceptor cell after illumination. Simulation of experimental conditions in which the expression levels of rhodospin kinase (RK), of the regulator of the G-protein signaling (RGS), of Arr and of Rec were altered individually or in combination revealed severe kinetic constraints to the dynamics of the overall network.

Conclusions

Our simulations confirm that RGS-mediated effector shutdown is the rate-limiting step in the recovery of the photoreceptor and show that the dynamic formation and dissociation of Arr homodimers and homotetramers at different light intensities significantly affect the timing of rhodopsin shutdown. The transition of Arr from its oligomeric storage forms to its monomeric form serves to temper its availability in the functional state. Our results may explain the puzzling evidence that overexpressing RK does not influence the saturation time of rod cells at bright light stimuli. The approach presented here could be extended to the study of other GPCR signaling pathways.

Interface-resolved network of protein-protein interactions

We define an interface-interaction network (IIN) to capture the specificity and competition between protein-protein interactions (PPI). This new type of network represents interactions between individual interfaces used in functional protein binding and thereby contains the detail necessary to describe the competition and cooperation between any pair of binding partners. Here we establish a general framework for the construction of IINs that merges computational structure-based interface assignment with careful curation of available literature. To complement limited structural data, the inclusion of biochemical data is critical for achieving the accuracy and completeness necessary to analyze the specificity and competition between the protein interactions. Firstly, this procedure provides a means to clarify the information content of existing data on purported protein interactions and to remove indirect and spurious interactions. Secondly, the IIN we have constructed here for proteins involved in clathrin-mediated endocytosis (CME) exhibits distinctive topological properties. In contrast to PPI networks with their global and relatively dense connectivity, the fragmentation of the IIN into distinctive network modules suggests that different functional pressures act on the evolution of its topology. Large modules in the IIN are formed by interfaces sharing specificity for certain domain types, such as SH3 domains distributed across different proteins. The shared and distinct specificity of an interface is necessary for effective negative and positive design of highly selective binding targets. Lastly, the organization of detailed structural data in a network format allows one to identify pathways of specific binding interactions and thereby predict effects of mutations at specific surfaces on a protein and of specific binding inhibitors, as we explore in several examples. Overall, the endocytosis IIN is remarkably complex and rich in features masked in the coarser PPI, and collects relevant detail of protein association in a readily interpretable format.

Much of the work inside the cell is carried out by proteins interacting with other proteins. Each edge in a protein-protein interaction network reflects these functional interactions and each node a separate protein, creating a complex structure that nevertheless follows well-established global and local patterns related to robust protein function. However, this network is not detailed enough to assess whether a particular protein can bind multiple interaction partners simultaneously through distinct interfaces, or whether the partners targeting a specific interface share similar structural or chemical properties. By breaking each protein node into its constituent interface nodes, we generate and assess such a detailed new network. To sample protein binding interactions broadly and accurately beyond those seen in crystal structures, our method combines computational interface assignment with data from biochemical studies. Using this approach we are able to assign interfaces to the majority of known interactions between proteins involved in the clathrin-mediated endocytosis pathway in yeast. Analysis of this interface-interaction network provides novel insights into the functional specificity of protein interactions, and highlights elements of cooperativity and competition among the proteins. By identifying diverse multi-protein complexes, interface-interaction networks also provide a map for targeted drug development.

Molecular signatures of G-protein-coupled receptors

G-protein-coupled receptors (GPCRs) are physiologically important membrane proteins that sense signalling molecules such as hormones and neurotransmitters, and are the targets of several prescribed drugs. Recent exciting developments are providing unprecedented insights into the structure and function of several medically important GPCRs. Here, through a systematic analysis of high-resolution GPCR structures, we uncover a conserved network of non-covalent contacts that defines the GPCR fold. Furthermore, our comparative analysis reveals characteristic features of ligand binding and conformational changes during receptor activation. A holistic understanding that integrates molecular and systems biology of GPCRs holds promise for new therapeutics and personalized medicine.

Isotope coded protein labeling coupled immunoprecipitation (ICPL-IP): a novel approach for quantitative protein complex analysis from native tissue

High confidence definition of protein interactions is an important objective toward the understanding of biological systems. Isotope labeling in combination with affinity-based isolation of protein complexes has increased in accuracy and reproducibility, yet, larger organisms--including humans--are hardly accessible to metabolic labeling and thus, a major limitation has been its restriction to small animals, cell lines, and yeast. As composition as well as the stoichiometry of protein complexes can significantly differ in primary tissues, there is a great demand for methods capable to combine the selectivity of affinity-based isolation as well as the accuracy and reproducibility of isotope-based labeling with its application toward analysis of protein interactions from intact tissue. Toward this goal, we combined isotope coded protein labeling (ICPL)(1) with immunoprecipitation (IP) and quantitative mass spectrometry (MS). ICPL-IP allows sensitive and accurate analysis of protein interactions from primary tissue. We applied ICPL-IP to immuno-isolate protein complexes from bovine retinal tissue. Protein complexes of immunoprecipitated β-tubulin, a highly abundant protein with known interactors as well as the lowly expressed small GTPase RhoA were analyzed. The results of both analyses demonstrate sensitive and selective identification of known as well as new protein interactions by our method.

Retinal glycoprotein enrichment by concanavalin a enabled identification of novel membrane autoantigen synaptotagmin-1 in equine recurrent uveitis

Complete knowledge of autoantigen spectra is crucial for understanding pathomechanisms of autoimmune diseases like equine recurrent uveitis (ERU), a spontaneous model for human autoimmune uveitis. While several ERU autoantigens were identified previously, no membrane protein was found so far. As there is a great overlap between glycoproteins and membrane proteins, the aim of this study was to test whether pre-enrichment of retinal glycoproteins by ConA affinity is an effective tool to detect autoantigen candidates among membrane proteins. In 1D Western blots, the glycoprotein preparation allowed detection of IgG reactions to low abundant proteins in sera of ERU patients. Synaptotagmin-1, a Ca2+-sensing protein in synaptic vesicles, was identified as autoantigen candidate from the pre-enriched glycoprotein fraction by mass spectrometry and was validated as a highly prevalent autoantigen by enzyme-linked immunosorbent assay. Analysis of Syt1 expression in retinas of ERU cases showed a downregulation in the majority of ERU affected retinas to 24%. Results pointed to a dysregulation of retinal neurotransmitter release in ERU. Identification of synaptotagmin-1, the first cell membrane associated autoantigen in this spontaneous autoimmune disease, demonstrated that examination of tissue fractions can lead to the discovery of previously undetected novel autoantigens. Further experiments will address its role in ERU pathology.

Interactome mapping for analysis of complex phenotypes: insights from benchmarking binary interaction assays

Protein interactions mediate essentially all biological processes and analysis of protein-protein interactions using both large-scale and small-scale approaches has contributed fundamental insights to the understanding of biological systems. In recent years, interactome network maps have emerged as an important tool for analyzing and interpreting genetic data of complex phenotypes. Complementary experimental approaches to test for binary, direct interactions, and for membership in protein complexes are used to explore the interactome. The two approaches are not redundant but yield orthogonal perspectives onto the complex network of physical interactions by which proteins mediate biological processes. In recent years, several publications have demonstrated that interactions from high-throughput experiments can be equally reliable as the high quality subset of interactions identified in small-scale studies. Critical for this insight was the introduction of standardized experimental benchmarking of interaction and validation assays using reference sets. The data obtained in these benchmarking experiments have resulted in greater appreciation of the limitations and the complementary strengths of different assays. Moreover, benchmarking is a central element of a conceptual framework to estimate interactome sizes and thereby measure progress toward near complete network maps. These estimates have revealed that current large-scale data sets, although often of high quality, cover only a small fraction of a given interactome. Here, I review the findings of assay benchmarking and discuss implications for quality control, and for strategies toward obtaining a near-complete map of the interactome of an organism.

Popular computational methods to assess multiprotein complexes derived from label-free affinity purification and mass spectrometry (AP-MS) experiments

Advances in sensitivity, resolution, mass accuracy, and throughput have considerably increased the number of protein identifications made via mass spectrometry. Despite these advances, state-of-the-art experimental methods for the study of protein-protein interactions yield more candidate interactions than may be expected biologically owing to biases and limitations in the experimental methodology. In silico methods, which distinguish between true and false interactions, have been developed and applied successfully to reduce the number of false positive results yielded by physical interaction assays. Such methods may be grouped according to: (1) the type of data used: methods based on experiment-specific measurements (e.g., spectral counts or identification scores) versus methods that extract knowledge encoded in external annotations (e.g., public interaction and functional categorisation databases); (2) the type of algorithm applied: the statistical description and estimation of physical protein properties versus predictive supervised machine learning or text-mining algorithms; (3) the type of protein relation evaluated: direct (binary) interaction of two proteins in a cocomplex versus probability of any functional relationship between two proteins (e.g., co-occurrence in a pathway, sub cellular compartment); and (4) initial motivation: elucidation of experimental data by evaluation versus prediction of novel protein-protein interaction, to be experimentally validated a posteriori. This work reviews several popular computational scoring methods and software platforms for protein-protein interactions evaluation according to their methodology, comparative strengths and weaknesses, data representation, accessibility, and availability. The scoring methods and platforms described include: CompPASS, SAINT, Decontaminator, MINT, IntAct, STRING, and FunCoup. References to related work are provided throughout in order to provide a concise but thorough introduction to a rapidly growing interdisciplinary field of investigation.

SAPIN: a framework for the structural analysis of protein interaction networks

SUMMARY

Protein interaction networks are widely used to depict the relationships between proteins. These networks often lack the information on physical binary interactions, and they do not inform whether there is incompatibility of structure between binding partners. Here, we introduce SAPIN, a framework dedicated to the structural analysis of protein interaction networks. SAPIN first identifies the protein parts that could be involved in the interaction and provides template structures. Next, SAPIN performs structural superimpositions to identify compatible and mutually exclusive interactions. Finally, the results are displayed using Cytoscape Web.

AVAILABILITY

The SAPIN server is available at http://sapin.crg.es.

CONTACT

jae-seong.yang@crg.eu or christina.kiel@crg.eu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics Online.