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.     

Viral perturbations of host networks reflect disease etiology

Many human diseases, arising from mutations of disease susceptibility genes (genetic diseases), are also associated with viral infections (virally implicated diseases), either in a directly causal manner or by indirect associations. Here we examine whether viral perturbations of host interactome may underlie such virally implicated disease relationships. Using as models two different human viruses, Epstein-Barr virus (EBV) and human papillomavirus (HPV), we find that host targets of viral proteins reside in network proximity to products of disease susceptibility genes. Expression changes in virally implicated disease tissues and comorbidity patterns cluster significantly in the network vicinity of viral targets. The topological proximity found between cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway linking HPV to Fanconi anemia.     

Systematic interactome mapping and genetic perturbation analysis of a C. elegans TGF-beta signaling network

To initiate a system-level analysis of C. elegans DAF-7/TGF-beta signaling, we combined interactome mapping with single and double genetic perturbations. Yeast two-hybrid (Y2H) screens starting with known DAF-7/TGF-beta pathway components defined a network of 71 interactions among 59 proteins. Coaffinity purification (co-AP) assays in mammalian cells confirmed the overall quality of this network. Systematic perturbations of the network using RNAi, both in wild-type and daf-7/TGF-beta pathway mutant animals, identified nine DAF-7/TGF-beta signaling modifiers, seven of which are conserved in humans. We show that one of these has functional homology to human SNO/SKI oncoproteins and that mutations at the corresponding genetic locus daf-5 confer defects in DAF-7/TGF-beta signaling. Our results reveal substantial molecular complexity in DAF-7/TGF-beta signal transduction. Integrating interactome maps with systematic genetic perturbations may be useful for developing a systems biology approach to this and other signaling modules.     

A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration

Many human inherited neurodegenerative disorders are characterized by loss of balance due to cerebellar Purkinje cell (PC) degeneration. Although the disease-causing mutations have been identified for a number of these disorders, the normal functions of the proteins involved remain, in many cases, unknown. To gain insight into the function of proteins involved in PC degeneration, we developed an interaction network for 54 proteins involved in 23 inherited ataxias and expanded the network by incorporating literature-curated and evolutionarily conserved interactions. We identified 770 mostly novel protein-protein interactions using a stringent yeast two-hybrid screen; of 75 pairs tested, 83% of the interactions were verified in mammalian cells. Many ataxia-causing proteins share interacting partners, a subset of which have been found to modify neurodegeneration in animal models. This interactome thus provides a tool for understanding pathogenic mechanisms common for this class of neurodegenerative disorders and for identifying candidate genes for inherited ataxias.     

An inter‐species protein–protein interaction network across vast evolutionary distance

In cellular systems, biophysical interactions between macromolecules underlie a complex web of functional interactions. How biophysical and functional networks are coordinated, whether all biophysical interactions correspond to functional interactions, and how such biophysical‐versus‐functional network coordination is shaped by evolutionary forces are all largely unanswered questions. Here, we investigate these questions using an “inter‐interactome” approach. We systematically probed the yeast and human proteomes for interactions between proteins from these two species and functionally characterized the resulting inter‐interactome network. After a billion years of evolutionary divergence, the yeast and human proteomes are still capable of forming a biophysical network with properties that resemble those of intra‐species networks. Although substantially reduced relative to intra‐species networks, the levels of functional overlap in the yeast–human inter‐interactome network uncover significant remnants of co‐functionality widely preserved in the two proteomes beyond human–yeast homologs. Our data support evolutionary selection against biophysical interactions between proteins with little or no co‐functionality. Such non‐functional interactions, however, represent a reservoir from which nascent functional interactions may arise.     

Systems properties of proteins encoded by imprinted genes

Genomically imprinted genes show parentally fixed mono-allelic expression and are important for the mammalian development. Dysregulation of genomic imprinting leads to several complex pathological conditions. Though the genetic and epigenetic regulation of imprinted genes has been well studied, their protein aspects are largely ignored. Here, we systematically studied a sub-network centered on proteins encoded by imprinted genes within human interactome. Using concepts of network biology, we uncover a highly connected, transitive and central network module of imprinted gene-products and their interacting partners (IGPN). The network is enriched in development, metabolism and cell cycle related functions and its malfunctioning ascribes error intolerance to human interactome network. Further, detailed analysis revealed that its higher centrality is determined by ‘date’ interactions among the proteins belonging to different functional classes than the ‘party’ interactions within the same functional class. Interestingly, a significant proportion of this network genetically associates with disease phenotypes. Moreover, the network comprises of gene-sets that are upregulated in leukemia, psychosis, obesity/diabetes and downregulated in autism. We conclude that imprinted gene-products are part of a functionally and topologically important module of human interactome and errors in this sub-network are intolerant to, otherwise robust, human interactome. The findings might also shed light on how imprinted genes, which are rather very few, coordinate at protein level to pleiotropically regulate growth and metabolism during embryonic and post-natal development.     

APP mouse models for Alzheimer's disease preclinical studies

Animal models of human diseases that accurately recapitulate clinical pathology are indispensable for understanding molecular mechanisms and advancing preclinical studies. The Alzheimer's disease (AD) research community has historically used first‐generation transgenic (Tg) mouse models that overexpress proteins linked to familial AD (FAD), mutant amyloid precursor protein (APP), or APP and presenilin (PS). These mice exhibit AD pathology, but the overexpression paradigm may cause additional phenotypes unrelated to AD. Second‐generation mouse models contain humanized sequences and clinical mutations in the endogenous mouse App gene. These mice show Aβ accumulation without phenotypes related to overexpression but are not yet a clinical recapitulation of human AD. In this review, we evaluate different APP mouse models of AD, and review recent studies using the second‐generation mice. We advise AD researchers to consider the comparative strengths and limitations of each model against the scientific and therapeutic goal of a prospective preclinical study.     

Towards the prediction of protein interaction partners using physical docking

Deciphering the whole network of protein interactions for a given proteome (‘interactome’) is the goal of many experimental and computational efforts in Systems Biology. Separately the prediction of the structure of protein complexes by docking methods is a well‐established scientific area. To date, docking programs have not been used to predict interaction partners. We provide a proof of principle for such an approach. Using a set of protein complexes representing known interactors in their unbound form, we show that a standard docking program can distinguish the true interactors from a background of 922 non‐redundant potential interactors. We additionally show that true interactions can be distinguished from non‐likely interacting proteins within the same structural family. Our approach may be put in the context of the proposed ‘funnel‐energy model’; the docking algorithm may not find the native complex, but it distinguishes binding partners because of the higher probability of favourable models compared with a collection of non‐binders. The potential exists to develop this proof of principle into new approaches for predicting interaction partners and reconstructing biological networks.     

Cellular mechanisms of mutant connexins in skin disease and hearing loss

It has been demonstrated that distinct germline mutations within four connexin (Cx) genes, Cx26, Cx30, Cx31, and Cx30.3, underlie hearing loss and/or epidermal disease. Here, we describe two Cx26 mutations associated with skin disease. With the goal of understanding the mechanism(s) of Cx-associated human disease and how different mutations within the same Cx protein can result in different disorders, we performed a number of functional analyses investigating the cellular effects of disease-associated Cx mutations in keratinocytes and other cell types. Epidermal disease-associated proteins studied were primarily cytoplasmic with limited trafficking ability. FACS analysis of WT and mutant EGFP-Cx31 transfected keratinocytes revealed a high percentage of cell death associated with the skin disease-associated mutant Cx31 proteins.     

Cellular Mechanisms of Mutant Connexins in Skin Disease and Hearing Loss

It has been demonstrated that distinct germline mutations within four connexin (Cx) genes, Cx26, Cx30, Cx31, and Cx30.3, underlie hearing loss and/or epidermal disease. Here, we describe two Cx26 mutations associated with skin disease. With the goal of understanding the mechanism(s) of Cx-associated human disease and how different mutations within the same Cx protein can result in different disorders, we performed a number of functional analyses investigating the cellular effects of disease-associated Cx mutations in keratinocytes and other cell types. Epidermal disease-associated proteins studied were primarily cytoplasmic with limited trafficking ability. FACS analysis of WT and mutant EGFP-Cx31 transfected keratinocytes revealed a high percentage of cell death associated with the skin disease-associated mutant Cx31 proteins.     

Moving towards a new era of genomics in the neuronal ceroid lipofuscinoses

The neuronal ceroid lipofuscinoses (NCL) are a group of disorders defined by shared clinical and pathological features, including seizures and progressive decline in vision, neurocognition, and motor functioning, as well as accumulation of autofluorescent lysosomal storage material, or ‘ceroid lipofuscin’. Research has revealed thirteen distinct genetic subtypes. Precisely how the gene mutations lead to the clinical phenotype is still incompletely understood, but recent research progress is starting to shed light on disease mechanisms, in both gene-specific and shared pathways. As the application of new sequencing technologies to genetic disease diagnosis has grown, so too has the spectrum of clinical phenotypes caused by mutations in the NCL genes. Most genes causing NCL have probably been identified, underscoring the need for a shift towards applying genomics approaches to achieve a deeper understanding of the molecular basis of the NCLs and related disorders. Here, we summarize the current understanding of the thirteen identified NCL genes and the proteins they encode, touching upon the spectrum of clinical manifestations linked to each of the genes, and we highlight recent progress leading to a broader understanding of key pathways involved in NCL disease pathogenesis and commonalities with other neurodegenerative diseases.     

e-MutPath: computational modeling reveals the functional landscape of genetic mutations rewiring interactome networks

Understanding the functional impact of cancer somatic mutations represents a critical knowledge gap for implementing precision oncology. It has been increasingly appreciated that the interaction profile mediated by a genomic mutation provides a fundamental link between genotype and phenotype. However, specific effects on biological signaling networks for the majority of mutations are largely unknown by experimental approaches. To resolve this challenge, we developed e-MutPath (edgetic Mutation-mediated Pathway perturbations), a network-based computational method to identify candidate ‘edgetic’ mutations that perturb functional pathways. e-MutPath identifies informative paths that could be used to distinguish disease risk factors from neutral elements and to stratify disease subtypes with clinical relevance. The predicted targets are enriched in cancer vulnerability genes, known drug targets but depleted for proteins associated with side effects, demonstrating the power of network-based strategies to investigate the functional impact and perturbation profiles of genomic mutations. Together, e-MutPath represents a robust computational tool to systematically assign functions to genetic mutations, especially in the context of their specific pathway perturbation effect.     

The orphan disease networks

The low prevalence rate of orphan diseases (OD) requires special combined efforts to improve diagnosis, prevention, and discovery of novel therapeutic strategies. To identify and investigate relationships based on shared genes or shared functional features, we have conducted a bioinformatic-based global analysis of all orphan diseases with known disease-causing mutant genes. Starting with a bipartite network of known OD and OD-causing mutant genes and using the human protein interactome, we first construct and topologically analyze three networks: the orphan disease network, the orphan disease-causing mutant gene network, and the orphan disease-causing mutant gene interactome. Our results demonstrate that in contrast to the common disease-causing mutant genes that are predominantly nonessential, a majority of orphan disease-causing mutant genes are essential. In confirmation of this finding, we found that OD-causing mutant genes are topologically important in the protein interactome and are ubiquitously expressed. Additionally, functional enrichment analysis of those genes in which mutations cause ODs shows that a majority result in premature death or are lethal in the orthologous mouse gene knockout models. To address the limitations of traditional gene-based disease networks, we also construct and analyze OD networks on the basis of shared enriched features (biological processes, cellular components, pathways, phenotypes, and literature citations). Analyzing these functionally-linked OD networks, we identified several additional OD-OD relations that are both phenotypically similar and phenotypically diverse. Surprisingly, we observed that the wiring of the gene-based and other feature-based OD networks are largely different; this suggests that the relationship between ODs cannot be fully captured by the gene-based network alone.     

Network-Based Study Reveals Potential Infection Pathways of Hepatitis-C Leading to Various Diseases

Protein-protein interaction network-based study of viral pathogenesis has been gaining popularity among computational biologists in recent days. In the present study we attempt to investigate the possible pathways of hepatitis-C virus (HCV) infection by integrating the HCV-human interaction network, human protein interactome and human genetic disease association network. We have proposed quasi-biclique and quasi-clique mining algorithms to integrate these three networks to identify infection gateway host proteins and possible pathways of HCV pathogenesis leading to various diseases. Integrated study of three networks, namely HCV-human interaction network, human protein interaction network, and human proteins-disease association network reveals potential pathways of infection by the HCV that lead to various diseases including cancers. The gateway proteins have been found to be biologically coherent and have high degrees in human interactome compared to the other virus-targeted proteins. The analyses done in this study provide possible targets for more effective anti-hepatitis-C therapeutic involvement.     

Modulation of Molecular Chaperones in Huntington’s Disease and Other Polyglutamine Disorders

Polyglutamine expansion mutations in specific proteins underlie the pathogenesis of a group of progressive neurodegenerative disorders, including Huntington’s disease, spinal and bulbar muscular atrophy, dentatorubral-pallidoluysian atrophy, and several spinocerebellar ataxias. The different mutant proteins share ubiquitous expression and abnormal proteostasis, with misfolding and aggregation, but nevertheless evoke distinct patterns of neurodegeneration. This highlights the relevance of the full protein context where the polyglutamine expansion occurs and suggests different interactions with the cellular proteostasis machinery. Molecular chaperones are key elements of the proteostasis machinery and therapeutic targets for neurodegeneration. Here, we provide a focused review on Hsp90, Hsp70, and their co-chaperones, and how their genetic or pharmacological modulation affects the proteostasis and disease phenotypes in cellular and animal models of polyglutamine disorders. The emerging picture is that, in principle, Hsp70 modulation may be more amenable for long-term treatment by promoting a more selective clearance of mutant proteins than Hsp90 modulation, which may further decrease the necessary wild-type counterparts. It seems, nevertheless, unlikely that a single Hsp70 modulator will benefit all polyglutamine diseases. Indeed, available data, together with insights from effects on tau and alpha-synuclein in models of Alzheimer’s and Parkinson’s diseases, indicates that Hsp70 modulators may lead to different effects on the proteostasis of different mutant and wild-type client proteins. Future studies should include the further development of isoform selective inhibitors, namely to avoid off-target effects on Hsp in the mitochondria, and their characterization in distinct polyglutamine disease models to account for client protein-specific differences.     

Aggregation of polyQ‐extended proteins is promoted by interaction with their natural coiled‐coil partners

Polyglutamine (polyQ) diseases are genetically inherited neurodegenerative disorders. They are caused by mutations that result in polyQ expansions of particular proteins. Mutant proteins form intranuclear aggregates, induce cytotoxicity and cause neuronal cell death. Protein interaction data suggest that polyQ regions modulate interactions between coiled‐coil (CC) domains. In the case of the polyQ disease spinocerebellar ataxia type‐1 (SCA1), interacting proteins with CC domains further enhance aggregation and toxicity of mutant ataxin‐1 (ATXN1). Here, we suggest that CC partners interacting with the polyQ region of a mutant protein, increase its aggregation while partners that interact with a different region reduce the formation of aggregates. Computational analysis of genetic screens revealed that CC‐rich proteins are highly enriched among genes that enhance pathogenicity of polyQ proteins, supporting our hypothesis. We therefore suggest that blocking interactions between mutant polyQ proteins and their CC partners might constitute a promising preventive strategy against neurodegeneration.     

Hepatitis C virus infection protein network

A proteome‐wide mapping of interactions between hepatitis C virus (HCV) and human proteins was performed to provide a comprehensive view of the cellular infection. A total of 314 protein–protein interactions between HCV and human proteins was identified by yeast two‐hybrid and 170 by literature mining. Integration of this data set into a reconstructed human interactome showed that cellular proteins interacting with HCV are enriched in highly central and interconnected proteins. A global analysis on the basis of functional annotation highlighted the enrichment of cellular pathways targeted by HCV. A network of proteins associated with frequent clinical disorders of chronically infected patients was constructed by connecting the insulin, Jak/STAT and TGFβ pathways with cellular proteins targeted by HCV. CORE protein appeared as a major perturbator of this network. Focal adhesion was identified as a new function affected by HCV, mainly by NS3 and NS5A proteins.     

The Color Loci of Mice – A Genetic Century

Color loci in mammals are those genetic loci in which mutations can affect pigmentation of the hair, skin, and/or eyes. In the mouse, over 800 phenotypic alleles are now known, at 127 identified color loci. As the number of color loci passed 100 only recently, we celebrate this ‘century’ with an overview of these loci, especially the 59 that have been cloned and sequenced. These fall into a number of functional groups representing melanocyte development and differentiation, melanosomal components, organelle biogenesis, organelle transport, control of pigment‐type switching, and some systemic effects. A human ortholog has been identified in all cases, and the majority of these human genes are found to be loci for human disorders, often affecting other body systems as well as pigmentation. We expect that a significant number of color loci remain to be identified. Nonetheless, the large number known already provide a treasury of resources for reconstruction of the mechanisms, at the subcellular, cellular and tissue levels, that produce a functional pigmentary system and contribute to the normal development and functioning of many other organ systems. The mutant mice also provide valuable models for the study of human disease.     

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.