Attributes of short linear motifs

Traditionally, protein-protein interactions were thought to be mediated by large, structured domains. However, it has become clear that the interactome comprises a wide range of binding interfaces with varying degrees of flexibility, ranging from rigid globular domains to disordered regions that natively lack structure. Enrichment for disorder in highly connected hub proteins and its correlation with organism complexity hint at the functional importance of disordered regions. Nevertheless, they have not yet been extensively characterised. Shifting the attention from globular domains to disordered regions of the proteome might bring us closer to elucidating the dense and complex connectivity of the interactome. An important class of disordered interfaces are the compact mono-partite, short linear motifs (SLiMs, or eukaryotic linear motifs (ELMs)). They are evolutionarily plastic and interact with relatively low affinity due to the limited number of residues that make direct contact with the binding partner. These features confer to SLiMs the ability to evolve convergently and mediate transient interactions, which is imperative to network evolution and to maintain robust cell signalling, respectively. The ability to discriminate biologically relevant SLiMs by means of different attributes will improve our understanding of the complexity of the interactome and aid development of bioinformatics tools for motif discovery. In this paper, the curated instances currently available in the Eukaryotic Linear Motif (ELM) database are analysed to provide a clear overview of the defining attributes of SLiMs. These analyses suggest that functional SLiMs have higher levels of conservation than their surrounding residues, frequently evolve convergently, preferentially occur in disordered regions and often form a secondary structure when bound to their interaction partner. These results advocate searching for small groupings of residues in disordered regions with higher relative conservation and a propensity to form the secondary structure. Finally, the most interesting conclusions are examined in regard to their functional consequences.     

Identification of the interactome between fish plasma proteins and Edwardsiella tarda reveals tissue-specific strategies against bacterial infection

Elucidating the complex pathogen-host interaction is essential for a comprehensive understanding of how these remarkable agents invade their hosts and how the hosts defend against these invaders. During the infection, pathogens interact intensively with host to enable their survival, which can be revealed through their interactome. Edwardsiella tarda is a Gram-negative bacterial pathogen causing huge economic loss in aquaculture and a spectrum of intestinal and extraintestinal diseases in humans. E. tarda is an ideal model for host-pathogen investigation as it infects fish in three distinct steps: entering the host, circulating through the blood and establishing infection. We adopted a previous established proteomic approach that inactivated E. tarda cells and covalent crosslink fish plasma proteins were used to capture plasma proteins and bacterial outer membrane proteins, respectively. By the combinatorial use of proteomic and biochemical approaches, six plasma proteins and seven outer membrane proteins (OMPs) were identified. Interactions among these proteins were validated with protein-array, far-Western blotting and co-immunoprecipitation. At last, seventeen plasma protein-bacteria protein⿿protein interaction were confirmed to be involved in the interaction network, forming a complex interactome. Compared to our previous results, different host proteins were detected, whereas some of the bacterial proteins were similar, which indicates that hosts adopt tissue-specific strategies to cope with the same pathogen during infection. Thus, our results provide a robust demonstration of both bacterial initiators and host receptors or interacting proteins to further explore infection and anti-infective mechanisms between hosts and microbes.     

Update on the proteomics of major arthropod vectors of human and animal pathogens

Vector‐borne diseases (VBDs) are defined as infectious diseases of humans and animals caused by pathogenic agents such as viruses, protists, bacteria, and helminths transmitted by the bite of blood‐feeding arthropod (BFA) vectors. VBDs represent a major public health threat in endemic areas, generally subtropical zones, and many are considered to be neglected diseases. Genome sequencing of some arthropod vectors as well as modern proteomic and genomic technologies are expanding our knowledge of arthropod–pathogen interactions. This review describes the proteomic approaches that have been used to investigate diverse biological questions about arthropod vectors, including the interplay between vectors and pathogens. Proteomic studies have identified proteins and biochemical pathways that may be involved in molecular crosstalk in BFA‐pathogen associations. Future work can build upon this promising start and functional analyses coupled with interactome bioassays will be carried out to investigate the role of candidate peptides and proteins in BFA‐human pathogen associations. Dissection of the host–pathogen interactome will be key to understanding the strategies and biochemical pathways used by BFAs to cope with pathogens.     

Human Histone Interaction Networks: An Old Concept,New Trends

To elucidate the properties of human histone interactions on the large scale, we perform a comprehensive mapping of human histone interaction networks by using data from structural, chemical cross-linking and various high-throughput studies. Histone interactomes derived from different data sources show limited overlap and complement each other. It inspires us to integrate these data into the combined histone global interaction network which includes 5308 proteins and 10,330 interactions. The analysis of topological properties of the human histone interactome reveals its scale free behavior and high modularity. Our study of histone binding interfaces uncovers a remarkably high number of residues involved in interactions between histones and non-histone proteins, 80–90% of residues in histones H3 and H4 have at least one binding partner. Two types of histone binding modes are detected: interfaces conserved in most histone variants and variant specific interfaces. Finally, different types of chromatin factors recognize histones in nucleosomes via distinct binding modes, and many of these interfaces utilize acidic patches among other sites. Interaction networks are available at https://github.com/Panchenko-Lab/Human-histone-interactome.     

Three-dimensional reconstruction of protein networks provides insight into human genetic disease

To better understand the molecular mechanisms and genetic basis of human disease, we systematically examine relationships between 3,949 genes, 62,663 mutations and 3,453 associated disorders by generating a three-dimensional, structurally resolved human interactome. This network consists of 4,222 high-quality binary protein-protein interactions with their atomic-resolution interfaces. We find that in-frame mutations (missense point mutations and in-frame insertions and deletions) are enriched on the interaction interfaces of proteins associated with the corresponding disorders, and that the disease specificity for different mutations of the same gene can be explained by their location within an interface. We also predict 292 candidate genes for 694 unknown disease-to-gene associations with proposed molecular mechanism hypotheses. This work indicates that knowledge of how in-frame disease mutations alter specific interactions is critical to understanding pathogenesis. Structurally resolved interaction networks should be valuable tools for interpreting the wealth of data being generated by large-scale structural genomics and disease association studies.     

A protein domain-based interactome network for C. elegans early embryogenesis

Many protein-protein interactions are mediated through independently folding modular domains. Proteome-wide efforts to model protein-protein interaction or "interactome" networks have largely ignored this modular organization of proteins. We developed an experimental strategy to efficiently identify interaction domains and generated a domain-based interactome network for proteins involved in C. elegans early-embryonic cell divisions. Minimal interacting regions were identified for over 200 proteins, providing important information on their domain organization. Furthermore, our approach increased the sensitivity of the two-hybrid system, resulting in a more complete interactome network. This interactome modeling strategy revealed insights into C. elegans centrosome function and is applicable to other biological processes in this and other organisms.     

Dissecting Disease Inheritance Modes in a Three-Dimensional Protein Network Challenges the “Guilt-by-Association” Principle

To better understand different molecular mechanisms by which mutations lead to various human diseases, we classified 82,833 disease-associated mutations according to their inheritance modes (recessive versus dominant) and molecular types (in-frame [missense point mutations and in-frame indels] versus truncating [nonsense mutations and frameshift indels]) and systematically examined the effects of different classes of disease mutations in a three-dimensional protein interactome network with the atomic-resolution interface resolved for each interaction. We found that although recessive mutations affecting the interaction interface of two interacting proteins tend to cause the same disease, this widely accepted “guilt-by-association” principle does not apply to dominant mutations. Furthermore, recessive truncating mutations in regions encoding the same interface are much more likely to cause the same disease, even for interfaces close to the N terminus of the protein. Conversely, dominant truncating mutations tend to be enriched in regions encoding areas between interfaces. These results suggest that a significant fraction of truncating mutations can generate functional protein products. For example, TRIM27, a known cancer-associated protein, interacts with three proteins (MID2, TRIM42, and SIRPA) through two different interfaces. A dominant truncating mutation (c.1024delT [p.Tyr342Thrfs^∗30]) associated with ovarian carcinoma is located between the regions encoding the two interfaces; the altered protein retains its interaction with MID2 and TRIM42 through the first interface but loses its interaction with SIRPA through the second interface. Our findings will help clarify the molecular mechanisms of thousands of disease-associated genes and their tens of thousands of mutations, especially for those carrying truncating mutations, often erroneously considered “knockout” alleles.     

Functional integrative levels in the human interactome recapitulate organ organization

Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This ‘Largest Common Interactome Network’ represents a ‘functional interactome core’. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.     

The IDL of E. coli SSB links ssDNA and protein binding by mediating protein–protein interactions

The E. coli single strand DNA binding protein (SSB) is essential to viability where it functions in two seemingly disparate roles: it binds to single stranded DNA (ssDNA) and to target proteins that comprise the SSB interactome. The link between these roles resides in a previously under‐appreciated region of the protein known as the intrinsically disordered linker (IDL). We present a model wherein the IDL is responsible for mediating protein–protein interactions critical to each role. When interactions occur between SSB tetramers, cooperative binding to ssDNA results. When binding occurs between SSB and an interactome partner, storage or loading of that protein onto the DNA takes place. The properties of the IDL that facilitate these interactions include the presence of repeats, a putative polyproline type II helix and, PXXP motifs that may facilitate direct binding to the OB‐fold in a manner similar to that observed for SH3 domain binding of PXXP ligands in eukaryotic systems.     

The mechanism of action of the SSB interactome reveals it is the first OB‐fold family of genome guardians in prokaryotes

The single‐stranded DNA binding protein (SSB) is essential to all aspects of DNA metabolism in bacteria. This protein performs two distinct, but closely intertwined and indispensable functions in the cell. SSB binds to single‐stranded DNA (ssDNA) and at least 20 partner proteins resulting in their regulation. These partners comprise a family of genome guardians known as the SSB interactome. Essential to interactome regulation is the linker/OB‐fold network of interactions. This network of interactions forms when one or more PXXP motifs in the linker of SSB bind to an OB‐fold in a partner, with interactome members involved in competitive binding between the linker and ssDNA to their OB‐fold. Consequently, when linker‐binding occurs to an OB‐fold in an interactome partner, proteins are loaded onto the DNA. When linker/OB‐fold interactions occur between SSB tetramers, cooperative ssDNA‐binding results, producing a multi‐tetrameric complex that rapidly protects the ssDNA. Within this SSB‐ssDNA complex, there is an extensive and dynamic network of linker/OB‐fold interactions that involves multiple tetramers bound contiguously along the ssDNA lattice. The dynamic behavior of these tetramers which includes binding mode changes, sliding as well as DNA wrapping/unwrapping events, are likely coupled to the formation and disruption of linker/OB‐fold interactions. This behavior is essential to facilitating downstream DNA processing events. As OB‐folds are critical to the essence of the linker/OB‐fold network of interactions, and they are found in multiple interactome partners, the SSB interactome is classified as the first family of prokaryotic, oligosaccharide/oligonucleotide binding fold (OB‐fold) genome guardians.     

Heat shock partially dissociates the overlapping modules of the yeast protein-protein interaction network: a systems level model of adaptation

Network analysis became a powerful tool giving new insights to the understanding of cellular behavior. Heat shock, the archetype of stress responses, is a well-characterized and simple model of cellular dynamics. S. cerevisiae is an appropriate model organism, since both its protein-protein interaction network (interactome) and stress response at the gene expression level have been well characterized. However, the analysis of the reorganization of the yeast interactome during stress has not been investigated yet. We calculated the changes of the interaction-weights of the yeast interactome from the changes of mRNA expression levels upon heat shock. The major finding of our study is that heat shock induced a significant decrease in both the overlaps and connections of yeast interactome modules. In agreement with this the weighted diameter of the yeast interactome had a 4.9-fold increase in heat shock. Several key proteins of the heat shock response became centers of heat shock-induced local communities, as well as bridges providing a residual connection of modules after heat shock. The observed changes resemble to a 'stratus-cumulus' type transition of the interactome structure, since the unstressed yeast interactome had a globally connected organization, similar to that of stratus clouds, whereas the heat shocked interactome had a multifocal organization, similar to that of cumulus clouds. Our results showed that heat shock induces a partial disintegration of the global organization of the yeast interactome. This change may be rather general occurring in many types of stresses. Moreover, other complex systems, such as single proteins, social networks and ecosystems may also decrease their inter-modular links, thus develop more compact modules, and display a partial disintegration of their global structure in the initial phase of crisis. Thus, our work may provide a model of a general, system-level adaptation mechanism to environmental changes.     

Systematic protein–protein interaction mapping for clinically relevant human GPCRs

G‐protein‐coupled receptors (GPCRs) are the largest family of integral membrane receptors with key roles in regulating signaling pathways targeted by therapeutics, but are difficult to study using existing proteomics technologies due to their complex biochemical features. To obtain a global view of GPCR‐mediated signaling and to identify novel components of their pathways, we used a modified membrane yeast two‐hybrid (MYTH) approach and identified interacting partners for 48 selected full‐length human ligand‐unoccupied GPCRs in their native membrane environment. The resulting GPCR interactome connects 686 proteins by 987 unique interactions, including 299 membrane proteins involved in a diverse range of cellular functions. To demonstrate the biological relevance of the GPCR interactome, we validated novel interactions of the GPR37, serotonin 5‐HT4d, and adenosine ADORA2A receptors. Our data represent the first large‐scale interactome mapping for human GPCRs and provide a valuable resource for the analysis of signaling pathways involving this druggable family of integral membrane proteins.     

Intracellular Bacteria Encode Inhibitory SNARE-Like Proteins

Pathogens use diverse molecular machines to penetrate host cells and manipulate intracellular vesicular trafficking. Viruses employ glycoproteins, functionally and structurally similar to the SNARE proteins, to induce eukaryotic membrane fusion. Intracellular pathogens, on the other hand, need to block fusion of their infectious phagosomes with various endocytic compartments to escape from the degradative pathway. The molecular details concerning the mechanisms underlying this process are lacking. Using both an in vitro liposome fusion assay and a cellular assay, we showed that SNARE-like bacterial proteins block membrane fusion in eukaryotic cells by directly inhibiting SNARE-mediated membrane fusion. More specifically, we showed that IncA and IcmG/DotF, two SNARE-like proteins respectively expressed by Chlamydia and Legionella, inhibit the endocytic SNARE machinery. Furthermore, we identified that the SNARE-like motif present in these bacterial proteins encodes the inhibitory function. This finding suggests that SNARE-like motifs are capable of specifically manipulating membrane fusion in a wide variety of biological environments. Ultimately, this motif may have been selected during evolution because it is an efficient structural motif for modifying eukaryotic membrane fusion and thus contribute to pathogen survival.     

Effector proteins translocated by Legionella pneumophila: strength in numbers

The Gram-negative bacterium Legionella pneumophila is a parasite of eukaryotic cells. It has evolved to survive and replicate in a wide range of protozoan hosts and can also infect human alveolar macrophages as an opportunistic pathogen. Crucially for the infection process, L. pneumophila uses a type IV secretion system called Dot/Icm to translocate bacterial proteins into host cells. In recent years a large number of Dot/Icm-translocated proteins have been identified. The study of these proteins, referred to as effectors, is providing valuable insight into the mechanism by which an intracellular pathogen can manipulate eukaryotic cellular processes to traffic and replicate in host cells.     

Information Flow Analysis of Interactome Networks

Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein–protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we combine gene expression data with interaction data in C. elegans and construct an interactome network for muscle-specific genes. We find that genes that rank high in terms of information flow in the muscle interactome network but not in the entire network tend to play important roles in muscle function. This framework for studying tissue-specific networks by the information flow model can be applied to other tissues and other organisms as well.