Relating the disease mutation spectrum to the evolution of the cystic fibrosis transmembrane conductance regulator (CFTR)

Stability Prediction for Mutations in the Cytosolic Domains of Cystic Fibrosis Transmembrane Conductance Regulator

Cystic Fibrosis (CF) is caused by mutations to the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) chloride channel. CFTR is composed of two membrane spanning domains, two cytosolic nucleotide-binding domains (NBD1 and NBD2) and a largely unstructured R-domain. Multiple CF-causing mutations reside in the NBDs and some are known to compromise the stability of these domains. The ability to predict the effect of mutations on the stability of the cytosolic domains of CFTR and to shed light on the mechanisms by which they exert their effect is therefore important in CF research. With this in mind, we have predicted the effect on domain stability of 59 mutations in NBD1 and NBD2 using 15 different algorithms and evaluated their performances via comparison to experimental data using several metrics including the correct classification rate (CCR), and the squared Pearson correlation (R²) and Spearman's correlation (ρ) calculated between the experimental ΔT_m values and the computationally predicted ΔΔG values. Overall, the best results were obtained with FoldX and Rosetta. For NBD1 (35 mutations), FoldX provided R² and ρ values of 0.64 and -0.71, respectively, with an 86% correct classification rate (CCR). For NBD2 (24 mutations), FoldX R², ρ, and CCR were 0.51, -0.73, and 75%, respectively. Application of the Rosetta high-resolution protocol (Rosetta_hrp) to NBD1 yielded R², ρ, and CCR of 0.64, -0.75, and 69%, respectively, and for NBD2 yielded R², ρ, and CCR of 0.29, -0.27, and 50%, respectively. The corresponding numbers for the Rosetta's low-resolution protocol (Rosetta_lrp) were R² = 0.47, ρ = -0.69, and CCR = 69% for NBD1 and R² = 0.27, ρ = -0.24, and CCR = 63% for NBD2. For NBD1, both algorithms suggest that destabilizing mutations suffer from destabilizing vdW clashes, whereas stabilizing mutations benefit from favorable H-bond interactions. Two triple consensus approaches based on FoldX, Rosetta_lpr, and Rosetta_hpr were attempted using either "majority-voting" or "all-voting". The all-voting consensus outperformed the individual predictors, albeit on a smaller data set. In summary, our results suggest that the effect of mutations on the stability of CFTR's NBDs could be largely predicted. Since NBDs are common to all ABC transporters, these results may find use in predicting the effect and mechanism of the action of multiple disease-causing mutations in other proteins.

Curated multiple sequence alignment for the Adenomatous Polyposis Coli (APC) gene and accuracy of in silico pathogenicity predictions

Computational algorithms are often used to assess pathogenicity of Variants of Uncertain Significance (VUS) that are found in disease-associated genes. Most computational methods include analysis of protein multiple sequence alignments (PMSA), assessing interspecies variation. Careful validation of PMSA-based methods has been done for relatively few genes, partially because creation of curated PMSAs is labor-intensive. We assessed how PMSA-based computational tools predict the effects of the missense changes in the APC gene, in which pathogenic variants cause Familial Adenomatous Polyposis. Most Pathogenic or Likely Pathogenic APC variants are protein-truncating changes. However, public databases now contain thousands of variants reported as missense. We created a curated APC PMSA that contained >3 substitutions/site, which is large enough for statistically robust in silico analysis. The creation of the PMSA was not easily automated, requiring significant querying and computational analysis of protein and genome sequences. Of 1924 missense APC variants in the NCBI ClinVar database, 1800 (93.5%) are reported as VUS. All but two missense variants listed as P/LP occur at canonical splice or Exonic Splice Enhancer sites. Pathogenicity predictions by five computational tools (Align-GVGD, SIFT, PolyPhen2, MAPP, REVEL) differed widely in their predictions of Pathogenic/Likely Pathogenic (range 17.5–75.0%) and Benign/Likely Benign (range 25.0–82.5%) for APC missense variants in ClinVar. When applied to 21 missense variants reported in ClinVar and securely classified as Benign, the five methods ranged in accuracy from 76.2–100%. Computational PMSA-based methods can be an excellent classifier for variants of some hereditary cancer genes. However, there may be characteristics of the APC gene and protein that confound the results of in silico algorithms. A systematic study of these features could greatly improve the automation of alignment-based techniques and the use of predictive algorithms in hereditary cancer genes.

Intrinsically disordered regions regulate the activities of ATP binding cassette transporters

ATP binding cassette (ABC) proteins are a large family of membrane proteins present in all kingdoms of life. These multi-domain proteins are comprised, at minimum, of two membrane-spanning domains (MSD1, MSD2) and two cytosolic nucleotide binding domains (NBD1, NBD2). ATP binding and hydrolysis at the NBDs enables ABC proteins to actively transport solutes across membranes, regulate activities of other proteins, or function as channels. Like most eukaryotic membrane proteins, ABC proteins contain intrinsically disordered regions (IDRs). These conformationally dynamic regions in ABC proteins possess residual structure, are sites of phosphorylation, and mediate protein-protein interactions. Here, we review the role of IDRs in regulating ABC protein activity.

Comparative sequence analyses of rhodopsin and RPE65 reveal patterns of selective constraint across hereditary retinal disease mutations

Retinitis pigmentosa (RP) comprises several heritable diseases that involve photoreceptor, and ultimately retinal, degeneration. Currently, mutations in over 50 genes have known links to RP. Despite advances in clinical characterization, molecular characterization of RP remains challenging due to the heterogeneous nature of causal genes, mutations, and clinical phenotypes. In this study, we compiled large datasets of two important visual genes associated with RP: rhodopsin, which initiates the phototransduction cascade, and the retinoid isomerase RPE65, which regenerates the visual cycle. We used a comparative evolutionary approach to investigate the relationship between interspecific sequence variation and pathogenic mutations that lead to degenerative retinal disease. Using codon-based likelihood methods, we estimated evolutionary rates (dN/dS) across both genes in a phylogenetic context to investigate differences between pathogenic and nonpathogenic amino acid sites. In both genes, disease-associated sites showed significantly lower evolutionary rates compared to nondisease sites, and were more likely to occur in functionally critical areas of the proteins. The nature of the dataset (e.g., vertebrate or mammalian sequences), as well as selection of pathogenic sites, affected the differences observed between pathogenic and nonpathogenic sites. Our results illustrate that these methods can serve as an intermediate step in understanding protein structure and function in a clinical context, particularly in predicting the relative pathogenicity (i.e., functional impact) of point mutations and their downstream phenotypic effects. Extensions of this approach may also contribute to current methods for predicting the deleterious effects of candidate mutations and to the identification of protein regions under strong constraint where we expect pathogenic mutations to occur.

Longevity and plasticity of CFTR provide an argument for noncanonical SNP organization in hominid DNA

Like many other ancient genes, the cystic fibrosis transmembrane conductance regulator (CFTR) has survived for hundreds of millions of years. In this report, we consider whether such prodigious longevity of an individual gene – as opposed to an entire genome or species – should be considered surprising in the face of eons of relentless DNA replication errors, mutagenesis, and other causes of sequence polymorphism. The conventions that modern human SNP patterns result either from purifying selection or random (neutral) drift were not well supported, since extant models account rather poorly for the known plasticity and function (or the established SNP distributions) found in a multitude of genes such as CFTR. Instead, our analysis can be taken as a polemic indicating that SNPs in CFTR and many other mammalian genes may have been generated—and continue to accrue—in a fundamentally more organized manner than would otherwise have been expected. The resulting viewpoint contradicts earlier claims of ‘directional’ or ‘intelligent design-type’ SNP formation, and has important implications regarding the pace of DNA adaptation, the genesis of conserved non-coding DNA, and the extent to which eukaryotic SNP formation should be viewed as adaptive.

Evolution- and structure-based computational strategy reveals the impact of deleterious missense mutations on MODY 2 (maturity-onset diabetes of the young, type 2)

Heterozygous mutations in the central glycolytic enzyme glucokinase (GCK) can result in an autosomal dominant inherited disease, namely maturity-onset diabetes of the young, type 2 (MODY 2). MODY 2 is characterised by early onset: it usually appears before 25 years of age and presents as a mild form of hyperglycaemia. In recent years, the number of known GCK mutations has markedly increased. As a result, interpreting which mutations cause a disease or confer susceptibility to a disease and characterising these deleterious mutations can be a difficult task in large-scale analyses and may be impossible when using a structural perspective. The laborious and time-consuming nature of the experimental analysis led us to attempt to develop a cost-effective computational pipeline for diabetic research that is based on the fundamentals of protein biophysics and that facilitates our understanding of the relationship between phenotypic effects and evolutionary processes. In this study, we investigate missense mutations in the GCK gene by using a wide array of evolution- and structure-based computational methods, such as SIFT, PolyPhen2, PhD-SNP, SNAP, SNPs&GO, fathmm, and Align GVGD. Based on the computational prediction scores obtained using these methods, three mutations, namely E70K, A188T, and W257R, were identified as highly deleterious on the basis of their effects on protein structure and function. Using the evolutionary conservation predictors Consurf and Scorecons, we further demonstrated that most of the predicted deleterious mutations, including E70K, A188T, and W257R, occur in highly conserved regions of GCK. The effects of the mutations on protein stability were computed using PoPMusic 2.1, I-mutant 3.0, and Dmutant. We also conducted molecular dynamics (MD) simulation analysis through in silico modelling to investigate the conformational differences between the native and the mutant proteins and found that the identified deleterious mutations alter the stability, flexibility, and solvent-accessible surface area of the protein. Furthermore, the functional role of each SNP in GCK was identified and characterised using SNPeffect 4.0, F-SNP, and FASTSNP. We hope that the observed results aid in the identification of disease-associated mutations that affect protein structure and function. Our in silico findings provide a new perspective on the role of GCK mutations in MODY2 from an evolution-based structure-centric point of view. The computational architecture described in this paper can be used to predict the most appropriate disease phenotypes for large-genome sequencing projects and to provide individualised drug therapy for complex diseases such as diabetes.

Functional architecture of the CFTR chloride channel

Cystic fibrosis is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR), a member of the ATP-binding cassette (ABC) family of membrane transport proteins. CFTR is unique among ABC proteins in that it functions not as an active transporter but as an ATP-gated Cl(-) channel. As an ion channel, the function of the CFTR transmembrane channel pore that mediates Cl(-) movement has been studied in great detail. On the other hand, only low resolution structural data is available on the transmembrane parts of the protein. The structure of the channel pore has, however, been modeled on the known structure of active transporter ABC proteins. Currently, significant barriers exist to building a unified view of CFTR pore structure and function. Reconciling functional data on the channel with indirect structural data based on other proteins with very different transport functions and substrates has proven problematic. This review summarizes current structural and functional models of the CFTR Cl(-) channel pore, including a comprehensive review of previous electrophysiological investigations of channel structure and function. In addition, functional data on the three-dimensional arrangement of pore-lining helices, as well as contemporary hypotheses concerning conformational changes in the pore that occur during channel opening and closing, are discussed. Important similarities and differences between different models of the pore highlight current gaps in our knowledge of CFTR structure and function. In order to fill these gaps, structural and functional models of the membrane-spanning pore need to become better integrated.

Defining the disease liability of variants in the cystic fibrosis transmembrane conductance regulator gene

Allelic heterogeneity in disease-causing genes presents a substantial challenge to the translation of genomic variation to clinical practice. Few of the almost 2,000 variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene have empirical evidence that they cause cystic fibrosis. To address this gap, we collected both genotype and phenotype data for 39,696 cystic fibrosis patients in registries and clinics in North America and Europe. Among these patients, 159 CFTR variants had an allele frequency of ≥0.01%. These variants were evaluated for both clinical severity and functional consequence with 127 (80%) meeting both clinical and functional criteria consistent with disease. Assessment of disease penetrance in 2,188 fathers of cystic fibrosis patients enabled assignment of 12 of the remaining 32 variants as neutral while the other 20 variants remained indeterminate. This study illustrates that sourcing data directly from well-phenotyped subjects can address the gap in our ability to interpret clinically-relevant genomic variation.