The role of protein complexes in human genetic disease

Many human genetic disorders are caused by mutations in protein‐coding regions of DNA. Taking protein structure into account has therefore provided key insight into the molecular mechanisms underlying human genetic disease. Although most studies have focused on the intramolecular effects of mutations, the critical role of the assembly of proteins into complexes is being increasingly recognized. Here, we review multiple ways in which consideration of protein complexes can help us to understand and explain the effects of pathogenic mutations. First, we discuss disorders caused by mutations that perturb intersubunit interactions in homomeric and heteromeric complexes. Second, we address how protein complex assembly can facilitate a dominant‐negative mechanism, whereby mutated subunits can disrupt the activity of wild‐type protein. Third, we show how mutations that change protein expression levels can lead to damaging stoichiometric imbalances. Finally, we review how mutations affecting different subunits of the same heteromeric complex often cause similar diseases, whereas mutations in different interfaces of the same subunit can cause distinct phenotypes.     

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.     

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.     

Protein Flexibility Facilitates Quaternary Structure Assembly and Evolution

The intrinsic flexibility of proteins allows them to undergo large conformational fluctuations in solution or upon interaction with other molecules. Proteins also commonly assemble into complexes with diverse quaternary structure arrangements. Here we investigate how the flexibility of individual protein chains influences the assembly and evolution of protein complexes. We find that flexibility appears to be particularly conducive to the formation of heterologous (i.e., asymmetric) intersubunit interfaces. This leads to a strong association between subunit flexibility and homomeric complexes with cyclic and asymmetric quaternary structure topologies. Similarly, we also observe that the more nonhomologous subunits that assemble together within a complex, the more flexible those subunits tend to be. Importantly, these findings suggest that subunit flexibility should be closely related to the evolutionary history of a complex. We confirm this by showing that evolutionarily more recent subunits are generally more flexible than evolutionarily older subunits. Finally, we investigate the very different explorations of quaternary structure space that have occurred in different evolutionary lineages. In particular, the increased flexibility of eukaryotic proteins appears to enable the assembly of heteromeric complexes with more unique components.     

A Massively Parallel Pipeline to Clone DNA Variants and Examine Molecular Phenotypes of Human Disease Mutations

Understanding the functional relevance of DNA variants is essential for all exome and genome sequencing projects. However, current mutagenesis cloning protocols require Sanger sequencing, and thus are prohibitively costly and labor-intensive. We describe a massively-parallel site-directed mutagenesis approach, “Clone-seq”, leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles. Using Clone-seq, we further develop a comparative interactome-scanning pipeline integrating high-throughput GFP, yeast two-hybrid (Y2H), and mass spectrometry assays to systematically evaluate the functional impact of mutations on protein stability and interactions. We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions. We also find that mutation pairs with similar molecular phenotypes in terms of both protein stability and interactions are significantly more likely to cause the same disease than those with different molecular phenotypes, validating the in vivo biological relevance of our high-throughput GFP and Y2H assays, and indicating that both assays can be used to determine candidate disease mutations in the future. The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.     

Cancer‐associated mutations are preferentially distributed in protein kinase functional sites

Protein kinases are a superfamily involved in many crucial cellular processes, including signal transmission and regulation of cell cycle. As a consequence of this role, kinases have been reported to be associated with many types of cancer and are considered as potential therapeutic targets. We analyzed the distribution of pathogenic somatic point mutations (drivers) in the protein kinase superfamily with respect to their location in the protein, such as in structural, evolutionary, and functionally relevant regions. We find these driver mutations are more clearly associated with key protein features than other somatic mutations (passengers) that have not been directly linked to tumor progression. This observation fits well with the expected implication of the alterations in protein kinase function in cancer pathogenicity. To explain the relevance of the detected association of cancer driver mutations at the molecular level in the human kinome, we compare these with genetically inherited mutations (SNPs). We find that the subset of nonsynonymous SNPs that are associated to disease, but sufficiently mild to the point of being widespread in the population, tend to avoid those key protein regions, where they could be more detrimental for protein function. This tendency contrasts with the one detected for cancer associated‐driver‐mutations, which seems to be more directly implicated in the alteration of protein function. The detailed analysis of protein kinase groups and a number of relevant examples, confirm the relation between cancer associated‐driver‐mutations and key regions for protein kinase structure and function. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Crystal structure of human Mre11: understanding tumorigenic mutations

Mre11 plays an important role in repairing damaged DNA by cleaving broken ends and by providing a platform for other DNA repair proteins. Various Mre11 mutations have been identified in several types of cancer. We have determined the crystal structure of the human Mre11 core (hMre11), which contains the nuclease and capping domains. hMre11 dimerizes through the interfaces between loop β3-α3 from one Mre11 and loop β4-β5 from another Mre11, and between loop α2-β3 from one Mre11 and helices α2 and α3 from another Mre11, and assembles into a completely different dimeric architecture compared with bacterial or archaeal Mre11 homologs. Nbs1 binds to the region containing loop α2-β3 which participates in dimerization. The hMre11 structure in conjunction with biochemical analyses reveals that many tumorigenic mutations are primarily associated with Nbs1 binding and partly with nuclease activities, providing a framework for understanding how mutations inactivate Mre11.     

Prediction of phenotypes of missense mutations in human proteins from biological assemblies

Single nucleotide polymorphisms (SNPs) are the most frequent variation in the human genome. Nonsynonymous SNPs that lead to missense mutations can be neutral or deleterious, and several computational methods have been presented that predict the phenotype of human missense mutations. These methods use sequence‐based and structure‐based features in various combinations, relying on different statistical distributions of these features for deleterious and neutral mutations. One structure‐based feature that has not been studied significantly is the accessible surface area within biologically relevant oligomeric assemblies. These assemblies are different from the crystallographic asymmetric unit for more than half of X‐ray crystal structures. We find that mutations in the core of proteins or in the interfaces in biological assemblies are significantly more likely to be disease‐associated than those on the surface of the biological assemblies. For structures with more than one protein in the biological assembly (whether the same sequence or different), we find the accessible surface area from biological assemblies provides a statistically significant improvement in prediction over the accessible surface area of monomers from protein crystal structures (P = 6e‐5). When adding this information to sequence‐based features such as the difference between wildtype and mutant position‐specific profile scores, the improvement from biological assemblies is statistically significant but much smaller (P = 0.018). Combining this information with sequence‐based features in a support vector machine leads to 82% accuracy on a balanced dataset of 50% disease‐associated mutations from SwissVar and 50% neutral mutations from human/primate sequence differences in orthologous proteins. Proteins 2013. © 2012 Wiley Periodicals, Inc.     

Distinct properties of glycine receptor β+/α- interface: unambiguously characterizing heteromeric interface reconstituted in homomeric protein

The glycine receptor (GlyR) exists either in homomeric α or heteromeric αβ forms. Its agonists bind at extracellular subunit interfaces. Unlike subunit interfaces from the homomeric α GlyR, subunit interfaces from the heteromeric αβ GlyR have not been characterized unambiguously because of the existence of multiple types of interface within single receptors. Here, we report that, by reconstituting β+/α- interfaces in a homomeric GlyR (αChb+a- GlyR), we were able to functionally characterize the αβ GlyR β+/α- interfaces. We found that the β+/α- interface had a higher agonist sensitivity than that of the α+/α- interface. This high sensitivity was contributed primarily by loop A. We also found that the β+/α- interface differentially modulates the agonist properties of glycine and taurine. Using voltage clamp fluorometry, we found that the conformational changes induced by glycine binding to the β+/α- interface were different from those induced by glycine binding to the α+/α- interface in the α GlyR. Moreover, the distinct conformational changes found at the β+/α- interface in the αChb+a- GlyR were also found in the heteromeric αβ GlyR, which suggests that the αChb+a- GlyR reconstitutes structural components and recapitulates functional properties, of the β+/α- interface in the heteromeric αβ GlyR. Our investigation not only provides structural and functional information about the GlyR β+/α- interface, which could direct GlyR β+/α- interface-specific drug design, but also provides a general methodology for unambiguously characterizing properties of specific protein interfaces from heteromeric proteins.     

Reproducible Analysis of Post-Translational Modifications in Proteomes—Application to Human Mutations

Background

Protein post-translational modifications (PTMs) are an important aspect of protein regulation. The number of PTMs discovered within the human proteome, and other proteomes, has been rapidly expanding in recent years. As a consequence of the rate in which new PTMs are identified, analysis done in one year may result in different conclusions when repeated in subsequent years. Among the various functional questions pertaining to PTMs, one important relationship to address is the interplay between modifications and mutations. Specifically, because the linear sequence surrounding a modification site often determines molecular recognition, it is hypothesized that mutations near sites of PTMs may be more likely to result in a detrimental effect on protein function, resulting in the development of disease.

Methods and Results

We wrote an application programming interface (API) to make analysis of ProteomeScout, a comprehensive database of PTMs and protein information, easy and reproducible. We used this API to analyze the relationship between PTMs and human mutations associated with disease (based on the ‘Clinical Significance’ annotation from dbSNP). Proteins containing pathogenic mutations demonstrated a significant study bias which was controlled for by analyzing only well-studied proteins, based on their having at least one pathogenic mutation. We found that pathogenic mutations are significantly more likely to lie within eight amino acids of a phosphoserine, phosphotyrosine or ubiquitination site when compared to mutations in general, based on a Fisher’s Exact test. Despite the skew of pathogenic mutations occurring on positively charged arginines, we could not account for this relationship based only on residue type. Finally, we hypothesize a potential mechanism for a pathogenic mutation on RAF1, based on its proximity to a phosphorylation site, which represents a subtle regulation difference that may explain why its biochemical effect has failed to be uncovered previously. The combination of the API and a dynamically expanding PTM database will make the reanalysis of this question and other systems-level questions easier in the future.     

Using model proteins to quantify the effects of pathogenic mutations in Ig-like proteins

It has proved impossible to purify some proteins implicated in disease in sufficient quantities to allow a biophysical characterization of the effect of pathogenic mutations. To overcome this problem we have analyzed 37 different disease-causing mutations located in the L1 and IL2Rgamma proteins in well characterized related model proteins in which mutations that are identical or equivalent to pathogenic mutations were introduced. We show that data from these models are consistent and that changes in stability observed can be correlated to severity of disease, to correct trafficking within the cell and to in vitro ligand binding studies. Interestingly, we find that any mutations that cause a loss of stability of more than 2 kcal/mol are severely debilitating, even though some model proteins with these mutations can be easily expressed and analyzed. Furthermore we show that the severity of mutation can be predicted by a DeltaDeltaG(evolution) scale, a measure of conservation. Our results demonstrate that model proteins can be used to analyze disease-causing mutations when wild-type proteins are not stable enough to carry mutations for biophysical analysis.     

Systematic characterization of pan‐cancer mutation clusters

Cancer genome sequencing has shown that driver genes can often be distinguished not only by the elevated mutation frequency but also by specific nucleotide positions that accumulate changes at a high rate. However, properties associated with a residue's potential to drive tumorigenesis when mutated have not yet been systematically investigated. Here, using a novel methodological approach, we identify and characterize a compendium of 180 hotspot residues within 160 human proteins which occur with a significant frequency and are likely to have functionally relevant impact. We find that such mutations (i) are more prominent in proteins that can exist in the on and off state, (ii) reflect the identity of a tumor of origin, and (iii) often localize within interfaces which mediate interactions with other proteins or ligands. Following, we further examine structural data for human protein complexes and identify a number of additional protein interfaces that accumulate cancer mutations at a high rate. Jointly, these analyses suggest that disruption and dysregulation of protein interactions can be instrumental in switching functions of cancer proteins and activating downstream changes.     

Guanine Holes Are Prominent Targets for Mutation in Cancer and Inherited Disease

Single base substitutions constitute the most frequent type of human gene mutation and are a leading cause of cancer and inherited disease. These alterations occur non-randomly in DNA, being strongly influenced by the local nucleotide sequence context. However, the molecular mechanisms underlying such sequence context-dependent mutagenesis are not fully understood. Using bioinformatics, computational and molecular modeling analyses, we have determined the frequencies of mutation at G•C bp in the context of all 64 5′-NGNN-3′ motifs that contain the mutation at the second position. Twenty-four datasets were employed, comprising >530,000 somatic single base substitutions from 21 cancer genomes, >77,000 germline single-base substitutions causing or associated with human inherited disease and 16.7 million benign germline single-nucleotide variants. In several cancer types, the number of mutated motifs correlated both with the free energies of base stacking and the energies required for abstracting an electron from the target guanines (ionization potentials). Similar correlations were also evident for the pathological missense and nonsense germline mutations, but only when the target guanines were located on the non-transcribed DNA strand. Likewise, pathogenic splicing mutations predominantly affected positions in which a purine was located on the non-transcribed DNA strand. Novel candidate driver mutations and tissue-specific mutational patterns were also identified in the cancer datasets. We conclude that electron transfer reactions within the DNA molecule contribute to sequence context-dependent mutagenesis, involving both somatic driver and passenger mutations in cancer, as well as germline alterations causing or associated with inherited disease.     

Comparison of Mitochondrial Mutation Spectra in Ageing Human Colonic Epithelium and Disease: Absence of Evidence for Purifying Selection in Somatic Mitochondrial DNA Point Mutations

Human ageing has been predicted to be caused by the accumulation of molecular damage in cells and tissues. Somatic mitochondrial DNA (mtDNA) mutations have been documented in a number of ageing tissues and have been shown to be associated with cellular mitochondrial dysfunction. It is unknown whether there are selective constraints, which have been shown to occur in the germline, on the occurrence and expansion of these mtDNA mutations within individual somatic cells. Here we compared the pattern and spectrum of mutations observed in ageing human colon to those observed in the general population (germline variants) and those associated with primary mtDNA disease. The pathogenicity of the protein encoding mutations was predicted using a computational programme, MutPred, and the scores obtained for the three groups compared. We show that the mutations associated with ageing are randomly distributed throughout the genome, are more frequently non-synonymous or frameshift mutations than the general population, and are significantly more pathogenic than population variants. Mutations associated with primary mtDNA disease were significantly more pathogenic than ageing or population mutations. These data provide little evidence for any selective constraints on the occurrence and expansion of mtDNA mutations in somatic cells of the human colon during human ageing in contrast to germline mutations seen in the general population.     

Mutation patterns of amino acid tandem repeats in the human proteome

Background

Amino acid tandem repeats are found in nearly one-fifth of human proteins. Abnormal expansion of these regions is associated with several human disorders. To gain further insight into the mutational mechanisms that operate in this type of sequence, we have analyzed a large number of mutation variants derived from human expressed sequence tags (ESTs).

Results

We identified 137 polymorphic variants in 115 different amino acid tandem repeats. Of these, 77 contained amino acid substitutions and 60 contained gaps (expansions or contractions of the repeat unit). The analysis showed that at least about 21% of the repeats might be polymorphic in humans. We compared the mutations found in different types of amino acid repeats and in adjacent regions. Overall, repeats showed a five-fold increase in the number of gap mutations compared to adjacent regions, reflecting the action of slippage within the repetitive structures. Gap and substitution mutations were very differently distributed between different amino acid repeat types. Among repeats containing gap variants we identified several disease and candidate disease genes.

Conclusion

This is the first report at a genome-wide scale of the types of mutations occurring in the amino acid repeat component of the human proteome. We show that the mutational dynamics of different amino acid repeat types are very diverse. We provide a list of loci with highly variable repeat structures, some of which may be potentially involved in disease.     

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.     

Mechanisms of RecQ helicases in pathways of DNA metabolism and maintenance of genomic stability

Helicases are molecular motor proteins that couple the hydrolysis of NTP to nucleic acid unwinding. The growing number of DNA helicases implicated in human disease suggests that their vital specialized roles in cellular pathways are important for the maintenance of genome stability. In particular, mutations in genes of the RecQ family of DNA helicases result in chromosomal instability diseases of premature aging and/or cancer predisposition. We will discuss the mechanisms of RecQ helicases in pathways of DNA metabolism. A review of RecQ helicases from bacteria to human reveals their importance in genomic stability by their participation with other proteins to resolve DNA replication and recombination intermediates. In the light of their known catalytic activities and protein interactions, proposed models for RecQ function will be summarized with an emphasis on how this distinct class of enzymes functions in chromosomal stability maintenance and prevention of human disease and cancer.     

The Intolerance of Regulatory Sequence to Genetic Variation Predicts Gene Dosage Sensitivity

Noncoding sequence contains pathogenic mutations. Yet, compared with mutations in protein-coding sequence, pathogenic regulatory mutations are notoriously difficult to recognize. Most fundamentally, we are not yet adept at recognizing the sequence stretches in the human genome that are most important in regulating the expression of genes. For this reason, it is difficult to apply to the regulatory regions the same kinds of analytical paradigms that are being successfully applied to identify mutations among protein-coding regions that influence risk. To determine whether dosage sensitive genes have distinct patterns among their noncoding sequence, we present two primary approaches that focus solely on a gene’s proximal noncoding regulatory sequence. The first approach is a regulatory sequence analogue of the recently introduced residual variation intolerance score (RVIS), termed noncoding RVIS, or ncRVIS. The ncRVIS compares observed and predicted levels of standing variation in the regulatory sequence of human genes. The second approach, termed ncGERP, reflects the phylogenetic conservation of a gene’s regulatory sequence using GERP++. We assess how well these two approaches correlate with four gene lists that use different ways to identify genes known or likely to cause disease through changes in expression: 1) genes that are known to cause disease through haploinsufficiency, 2) genes curated as dosage sensitive in ClinGen’s Genome Dosage Map, 3) genes judged likely to be under purifying selection for mutations that change expression levels because they are statistically depleted of loss-of-function variants in the general population, and 4) genes judged unlikely to cause disease based on the presence of copy number variants in the general population. We find that both noncoding scores are highly predictive of dosage sensitivity using any of these criteria. In a similar way to ncGERP, we assess two ensemble-based predictors of regional noncoding importance, ncCADD and ncGWAVA, and find both scores are significantly predictive of human dosage sensitive genes and appear to carry information beyond conservation, as assessed by ncGERP. These results highlight that the intolerance of noncoding sequence stretches in the human genome can provide a critical complementary tool to other genome annotation approaches to help identify the parts of the human genome increasingly likely to harbor mutations that influence risk of disease.