In Silico Identification of New Putative Pathogenic Variants in the Neu1 Sialidase Gene Affecting Enzyme Function and Subcellular Localization

The NEU1 gene is the first identified member of the human sialidases, glycohydrolitic enzymes that remove the terminal sialic acid from oligosaccharide chains. Mutations in NEU1 gene are causative of sialidosis (MIM 256550), a severe lysosomal storage disorder showing autosomal recessive mode of inheritance. Sialidosis has been classified into two subtypes: sialidosis type I, a normomorphic, late-onset form, and sialidosis type II, a more severe neonatal or early-onset form. A total of 50 causative mutations are reported in HGMD database, most of which are missense variants. To further characterize the NEU1 gene and identify new functionally relevant protein isoforms, we decided to study its genetic variability in the human population using the data generated by two large sequencing projects: the 1000 Genomes Project (1000G) and the NHLBI GO Exome Sequencing Project (ESP). Together these two datasets comprise a cohort of 7595 sequenced individuals, making it possible to identify rare variants and dissect population specific ones. By integrating this approach with biochemical and cellular studies, we were able to identify new rare missense and frameshift alleles in NEU1 gene. Among the 9 candidate variants tested, only two resulted in significantly lower levels of sialidase activity (p<0.05), namely c.650T>C and c.700G>A. These two mutations give rise to the amino acid substitutions p.V217A and p.D234N, respectively. NEU1 variants including either of these two amino acid changes have 44% and 25% residual sialidase activity when compared to the wild-type enzyme, reduced protein levels and altered subcellular localization. Thus they may represent new, putative pathological mutations resulting in sialidosis type I. The in silico approach used in this study has enabled the identification of previously unknown NEU1 functional alleles that are widespread in the population and could be tested in future functional studies.     

Evidence for the early emergence of piperaquine-resistant Plasmodium falciparum malaria and modeling strategies to mitigate resistance

Multidrug-resistant Plasmodium falciparum parasites have emerged in Cambodia and neighboring countries in Southeast Asia, compromising the efficacy of first-line antimalarial combinations. Dihydroartemisinin + piperaquine (PPQ) treatment failure rates have risen to as high as 50% in some areas in this region. For PPQ, resistance is driven primarily by a series of mutant alleles of the P. falciparum chloroquine resistance transporter (PfCRT). PPQ resistance was reported in China three decades earlier, but the molecular driver remained unknown. Herein, we identify a PPQ-resistant pfcrt allele (China C) from Yunnan Province, China, whose genotypic lineage is distinct from the PPQ-resistant pfcrt alleles currently observed in Cambodia. Combining gene editing and competitive growth assays, we report that PfCRT China C confers moderate PPQ resistance while re-sensitizing parasites to chloroquine (CQ) and incurring a fitness cost that manifests as a reduced rate of parasite growth. PPQ transport assays using purified PfCRT isoforms, combined with molecular dynamics simulations, highlight differences in drug transport kinetics and in this transporter’s central cavity conformation between China C and the current Southeast Asian PPQ-resistant isoforms. We also report a novel computational model that incorporates empirically determined fitness landscapes at varying drug concentrations, combined with antimalarial susceptibility profiles, mutation rates, and drug pharmacokinetics. Our simulations with PPQ-resistant or -sensitive parasite lines predict that a three-day regimen of PPQ combined with CQ can effectively clear infections and prevent the evolution of PfCRT variants. This work suggests that including CQ in combination therapies could be effective in suppressing the evolution of PfCRT-mediated multidrug resistance in regions where PPQ has lost efficacy.     

Insight into Pleiotropic Drug Resistance ATP-binding Cassette Pump Drug Transport through Mutagenesis of Cdr1p Transmembrane Domains

The fungal ATP-binding cassette (ABC) transporter Cdr1 protein (Cdr1p), responsible for clinically significant drug resistance, is composed of two transmembrane domains (TMDs) and two nucleotide binding domains (NBDs). We have probed the nature of the drug binding pocket by performing systematic mutagenesis of the primary sequences of the 12 transmembrane segments (TMSs) found in the TMDs. All mutated proteins were expressed equally well and localized properly at the plasma membrane in the heterologous host Saccharomyces cerevisiae, but some variants differed significantly in efflux activity, substrate specificity, and coupled ATPase activity. Replacement of the majority of the amino acid residues with alanine or glycine yielded neutral mutations, but about 42% of the variants lost resistance to drug efflux substrates completely or selectively. A predicted three-dimensional homology model shows that all the TMSs, apart from TMS4 and TMS10, interact directly with the drug-binding cavity in both the open and closed Cdr1p conformations. However, TMS4 and TMS10 mutations can also induce total or selective drug susceptibility. Functional data and homology modeling assisted identification of critical amino acids within a drug-binding cavity that, upon mutation, abolished resistance to all drugs tested singly or in combinations. The open and closed Cdr1p models enabled the identification of amino acid residues that bordered a drug-binding cavity dominated by hydrophobic residues. The disposition of TMD residues with differential effects on drug binding and transport are consistent with a large polyspecific drug binding pocket in this yeast multidrug transporter.     

Genetic Mutations Associated with Isoniazid Resistance in Mycobacterium tuberculosis: A Systematic Review

Background

Tuberculosis (TB) incidence and mortality are declining worldwide; however, poor detection of drug-resistant disease threatens to reverse current progress toward global TB control. Multiple, rapid molecular diagnostic tests have recently been developed to detect genetic mutations in Mycobacterium tuberculosis (Mtb) genes known to confer first-line drug resistance. Their utility, though, depends on the frequency and distribution of the resistance associated mutations in the pathogen population. Mutations associated with rifampicin resistance, one of the two first-line drugs, are well understood and appear to occur in a single gene region in >95% of phenotypically resistant isolates. Mutations associated with isoniazid, the other first-line drug, are more complex and occur in multiple Mtb genes.

Objectives/Methodology

A systematic review of all published studies from January 2000 through August 2013 was conducted to quantify the frequency of the most common mutations associated with isoniazid resistance, to describe the frequency at which these mutations co-occur, and to identify the regional differences in the distribution of these mutations. Mutation data from 118 publications were extracted and analyzed for 11,411 Mtb isolates from 49 countries.

Principal Findings/Conclusions

Globally, 64% of all observed phenotypic isoniazid resistance was associated with the katG315 mutation. The second most frequently observed mutation, inhA-15, was reported among 19% of phenotypically resistant isolates. These two mutations, katG315 and inhA-15, combined with ten of the most commonly occurring mutations in the inhA promoter and the ahpC-oxyR intergenic region explain 84% of global phenotypic isoniazid resistance. Regional variation in the frequency of individual mutations may limit the sensitivity of molecular diagnostic tests. Well-designed systematic surveys and whole genome sequencing are needed to identify mutation frequencies in geographic regions where rapid molecular tests are currently being deployed, providing a context for interpretation of test results and the opportunity for improving the next generation of diagnostics.     

Multiplexing mutation rate assessment: determining pathogenicity of Msh2 variants in Saccharomyces cerevisiae

Despite the fundamental importance of mutation rate as a driving force in evolution and disease risk, common methods to assay mutation rate are time-consuming and tedious. Established methods such as fluctuation tests and mutation accumulation experiments are low-throughput and often require significant optimization to ensure accuracy. We established a new method to determine the mutation rate of many strains simultaneously by tracking mutation events in a chemostat continuous culture device and applying deep sequencing to link mutations to alleles of a DNA-repair gene. We applied this method to assay the mutation rate of hundreds of Saccharomyces cerevisiae strains carrying mutations in the gene encoding Msh2, a DNA repair enzyme in the mismatch repair pathway. Loss-of-function mutations in MSH2 are associated with hereditary nonpolyposis colorectal cancer, an inherited disorder that increases risk for many different cancers. However, the vast majority of MSH2 variants found in human populations have insufficient evidence to be classified as either pathogenic or benign. We first benchmarked our method against Luria–Delbrück fluctuation tests using a collection of published MSH2 missense variants. Our pooled screen successfully identified previously characterized nonfunctional alleles as high mutators. We then created an additional 185 human missense variants in the yeast ortholog, including both characterized and uncharacterized alleles curated from ClinVar and other clinical testing data. In a set of alleles of known pathogenicity, our assay recapitulated ClinVar’s classification; we then estimated pathogenicity for 157 variants classified as uncertain or conflicting reports of significance. This method is capable of studying the mutation rate of many microbial species and can be applied to problems ranging from the generation of high-fidelity polymerases to measuring the frequency of antibiotic resistance emergence.     

Resistance to vemurafenib resulting from a novel mutation in the BRAFV600E kinase domain

Resistance to the BRAF inhibitor vemurafenib poses a significant problem for the treatment of BRAFV600E‐positive melanomas. It is therefore critical to prospectively identify all vemurafenib resistance mechanisms prior to their emergence in the clinic. The vemurafenib resistance mechanisms described to date do not result from secondary mutations within BRAFV600E. To search for possible mutations within BRAFV600E that can confer drug resistance, we developed a systematic experimental approach involving targeted saturation mutagenesis, selection of drug‐resistant variants, and deep sequencing. We identified a single nucleotide substitution (T1514A, encoding L505H) that greatly increased drug resistance in cultured cells and mouse xenografts. The kinase activity of BRAFV600E/L505H was higher than that of BRAFV600E, resulting in cross‐resistance to a MEK inhibitor. However, BRAFV600E/L505H was less resistant to several other BRAF inhibitors whose binding sites were further from L505 than that of PLX4720. Our results identify a novel vemurafenib‐resistant mutant and provide insights into the treatment for melanomas bearing this mutation.     

Predicting Mendelian Disease-Causing Non-Synonymous Single Nucleotide Variants in Exome Sequencing Studies

Exome sequencing is becoming a standard tool for mapping Mendelian disease-causing (or pathogenic) non-synonymous single nucleotide variants (nsSNVs). Minor allele frequency (MAF) filtering approach and functional prediction methods are commonly used to identify candidate pathogenic mutations in these studies. Combining multiple functional prediction methods may increase accuracy in prediction. Here, we propose to use a logit model to combine multiple prediction methods and compute an unbiased probability of a rare variant being pathogenic. Also, for the first time we assess the predictive power of seven prediction methods (including SIFT, PolyPhen2, CONDEL, and logit) in predicting pathogenic nsSNVs from other rare variants, which reflects the situation after MAF filtering is done in exome-sequencing studies. We found that a logit model combining all or some original prediction methods outperforms other methods examined, but is unable to discriminate between autosomal dominant and autosomal recessive disease mutations. Finally, based on the predictions of the logit model, we estimate that an individual has around 5% of rare nsSNVs that are pathogenic and carries ∼22 pathogenic derived alleles at least, which if made homozygous by consanguineous marriages may lead to recessive diseases.     

Targeted Sequencing of the Mitochondrial Genome of Women at High Risk of Breast Cancer without Detectable Mutations in BRCA1/2

Breast Cancer is a complex multifactorial disease for which high-penetrance mutations have been identified. Approaches used to date have identified genomic features explaining about 50% of breast cancer heritability. A number of low- to medium penetrance alleles (per-allele odds ratio < 1.5 and 4.0, respectively) have been identified, suggesting that the remaining heritability is likely to be explained by the cumulative effect of such alleles and/or by rare high-penetrance alleles. Relatively few studies have specifically explored the mitochondrial genome for variants potentially implicated in breast cancer risk. For these reasons, we propose an exploration of the variability of the mitochondrial genome in individuals diagnosed with breast cancer, having a positive breast cancer family history but testing negative for BRCA1/2 pathogenic mutations. We sequenced the mitochondrial genome of 436 index breast cancer cases from the GENESIS study. As expected, no pathogenic genomic pattern common to the 436 women included in our study was observed. The mitochondrial genes MT-ATP6 and MT-CYB were observed to carry the highest number of variants in the study. The proteins encoded by these genes are involved in the structure of the mitochondrial respiration chain, and variants in these genes may impact reactive oxygen species production contributing to carcinogenesis. More functional and epidemiological studies are needed to further investigate to what extent variants identified may influence familial breast cancer risk.     

Linear amplicons as precursors of amplified circles in methotrexate-resistant Leishmania tarentolae.

Gene amplification is frequently observed in Leishmania cells selected for drug resistance. By gene targeting we have tagged both alleles of the H locus of Leishmania tarentolae with the neomycin and hygromycin phosphotransferase genes ( neo and hyg ). Selection of these recombinant parasites for low level methotrexate resistance led to amplification of the H locus as part of linear amplicons. The availability of tags has permitted us to determine that both alleles can be amplified in the same cell and that chromosomal deletions are frequent. When methotrexate concentration was increased in subsequent selection steps, circles were observed in several mutants. We have introduced a hyg marker into linear amplicons to test whether the circles originated from linear amplicons. After selection with a high methotrexate concentration, circles with the hyg marker were observed, showing that circles can indeed be formed from linear amplicons. The tagging of H locus alleles permits appreciation of the extent of genetic rearrangements leading to amplicon formation in Leishmania cells selected for drug resistance.     

Temperature Sensitivity Conferred by ligA Alleles from Psychrophilic Bacteria upon Substitution in Mesophilic Bacteria and a Yeast Species

We have assembled a collection of 13 psychrophilic ligA alleles that can serve as genetic elements for engineering mesophiles to a temperature-sensitive (TS) phenotype. When these ligA alleles were substituted into Francisella novicida, they conferred a TS phenotype with restrictive temperatures between 33 and 39°C. When the F. novicida ligA hybrid strains were plated above their restrictive temperatures, eight of them generated temperature-resistant variants. For two alleles, the mutations that led to temperature resistance clustered near the 5′ end of the gene, and the mutations increased the predicted strength of the ribosome binding site at least 3-fold. Four F. novicida ligA hybrid strains generated no temperature-resistant variants at a detectable level. These results suggest that multiple mutations are needed to create temperature-resistant variants of these ligA gene products. One ligA allele was isolated from a Colwellia species that has a maximal growth temperature of 12°C, and this allele supported growth of F. novicida only as a hybrid between the psychrophilic and the F. novicida ligA genes. However, the full psychrophilic gene alone supported the growth of Salmonella enterica, imparting a restrictive temperature of 27°C. We also tested two ligA alleles from two Pseudoalteromonas strains for their ability to support the viability of a Saccharomyces cerevisiae strain that lacked its essential gene, CDC9, encoding an ATP-dependent DNA ligase. In both cases, the psychrophilic bacterial alleles supported yeast viability and their expression generated TS phenotypes. This collection of ligA alleles should be useful in engineering bacteria, and possibly eukaryotic microbes, to predictable TS phenotypes.     

Mutant alleles of Schizosaccharomyces pombe rad9(+) alter hydroxyurea resistance, radioresistance and checkpoint control

Schizosaccharomyces pombe rad9 mutations can render cells sensitive to hydroxyurea (HU), gamma-rays and UV light and eliminate associated checkpoint controls. In vitro mutagenesis was performed on S.pombe rad9 and altered alleles were transplaced into the genome to ascertain the functional significance of five groups of evolutionarily conserved amino acids. Most targeted regions were changed to alanines, whereas rad9-S3 encodes a protein devoid of 22 amino acids normally present in yeast but absent from mammalian Rad9 proteins. We examined whether these rad9 alleles confer radiation and HU sensitivity and whether the sensitivities correlate with checkpoint control deficiencies. One rad9 mutant allele was fully active, whereas four others demonstrated partial loss of function. rad9-S1, which contains alterations in a BH3-like domain, conferred HU resistance but increased sensitivity to gamma-rays and UV light, without affecting checkpoint controls. rad9-S2 reduced gamma-ray sensitivity marginally, without altering other phenotypes. Two alleles, rad9-S4 and rad9-S5, reduced HU sensitivity, radiosensitivity and caused aberrant checkpoint function. HU-induced checkpoint control could not be uncoupled from drug resistance. These results establish unique as well as overlapping functional domains within Rad9p and provide evidence that requirements of the protein for promoting resistance to radiation and HU are not identical.     

Accessible Mutational Trajectories for the Evolution of Pyrimethamine Resistance in the Malaria Parasite Plasmodium vivax

Antifolate antimalarials, such as pyrimethamine, have experienced a dramatic reduction in therapeutic efficacy as resistance has evolved in multiple malaria species. We present evidence from one such species, Plasmodium vivax, which has experienced sustained selection for pyrimethamine resistance at the dihydrofolate reductase (DHFR) locus since the 1970s. Using a transgenic Saccharomyces cerevisiae model expressing the P. vivax DHFR enzyme, we assayed growth rate and resistance of all 16 combinations of four DHFR amino acid substitutions. These substitutions were selected based on their known association with drug resistance, both in natural isolates and in laboratory settings, in the related malaria species P. falciparum. We observed a strong correlation between the resistance phenotypes for these 16 P. vivax alleles and previously observed resistance data for P. falciparum, which was surprising since nucleotide diversity levels and common polymorphic variants of DHFR differ between the two species. Similar results were observed when we expressed the P. vivax alleles in a transgenic bacterial system. This suggests common constraints on enzyme evolution in the orthologous DHFR proteins. The interplay of negative trade-offs between the evolution of novel resistance and compromised endogenous function varies at different drug dosages, and so too do the major trajectories for DHFR evolution. In simulations, it is only at very high drug dosages that the most resistant quadruple mutant DHFR allele is favored by selection. This is in agreement with common polymorphic DHFR data in P. vivax, from which this quadruple mutant is missing. We propose that clinical dosages of pyrimethamine may have historically been too low to select for the most resistant allele, or that the fitness cost of the most resistant allele was untenable without a compensatory mutation elsewhere in the genome.     

Understanding anthelmintic resistance: the need for genomics and genetics

Anthelmintic resistance is a major problem for the control of many parasitic nematode species and has become a major constraint to livestock production in many parts of the world. In spite of its increasing importance, there is still a poor understanding of the molecular and genetic basis of resistance. It is unclear which mutations contribute most to the resistance phenotype and how resistance alleles arise, are selected and spread in parasite populations. The main strategy used to identify mutations responsible for anthelmintic resistance has been to undertake experimental studies on candidate genes. These genes have been chosen predominantly on the basis of our knowledge of drug mode-of-action and the identification of mutations that can confer resistance in model organisms. The application of these approaches to the analysis of benzimidazole and ivermectin resistance is reviewed and the reasons for their relative success or failure are discussed. The inherent limitation of candidate gene studies is that they rely on very specific and narrow assumptions about the likely identity of resistance-associated genes. In contrast, forward genetic and functional genomic approaches do not make such assumptions, as illustrated by the successful application of these techniques in the study of insecticide resistance. Although there is an urgent need to apply these powerful approaches to anthelmintic resistance research, the basic methodologies and resources are still lacking. However, these are now being developed for the trichostrongylid nematode Haemonchus contortus and the current progress and research priorities in this area are discussed.     

Natural and Unanticipated Modifiers of RNAi Activity in Caenorhabditis elegans

Organisms used as model genomics systems are maintained as isogenic strains, yet evidence of sequence differences between independently maintained wild-type stocks has been substantiated by whole-genome resequencing data and strain-specific phenotypes. Sequence differences may arise from replication errors, transposon mobilization, meiotic gene conversion, or environmental or chemical assault on the genome. Low frequency alleles or mutations with modest effects on phenotypes can contribute to natural variation, and it has proven possible for such sequences to become fixed by adapted evolutionary enrichment and identified by resequencing. Our objective was to identify and analyze single locus genetic defects leading to RNAi resistance in isogenic strains of Caenorhabditis elegans. In so doing, we uncovered a mutation that arose de novo in an existing strain, which initially frustrated our phenotypic analysis. We also report experimental, environmental, and genetic conditions that can complicate phenotypic analysis of RNAi pathway defects. These observations highlight the potential for unanticipated mutations, coupled with genetic and environmental phenomena, to enhance or suppress the effects of known mutations and cause variation between wild-type strains.     

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.     

Accurate prediction of the functional significance of single nucleotide polymorphisms and mutations in the ABCA1 gene

The human genome contains an estimated 100,000 to 300,000 DNA variants that alter an amino acid in an encoded protein. However, our ability to predict which of these variants are functionally significant is limited. We used a bioinformatics approach to define the functional significance of genetic variation in the ABCA1 gene, a cholesterol transporter crucial for the metabolism of high density lipoprotein cholesterol. To predict the functional consequence of each coding single nucleotide polymorphism and mutation in this gene, we calculated a substitution position-specific evolutionary conservation score for each variant, which considers site-specific variation among evolutionarily related proteins. To test the bioinformatics predictions experimentally, we evaluated the biochemical consequence of these sequence variants by examining the ability of cell lines stably transfected with the ABCA1 alleles to elicit cholesterol efflux. Our bioinformatics approach correctly predicted the functional impact of greater than 94% of the naturally occurring variants we assessed. The bioinformatics predictions were significantly correlated with the degree of functional impairment of ABCA1 mutations (r² = 0.62, p = 0.0008). These results have allowed us to define the impact of genetic variation on ABCA1 function and to suggest that the in silico evolutionary approach we used may be a useful tool in general for predicting the effects of DNA variation on gene function. In addition, our data suggest that considering patterns of positive selection, along with patterns of negative selection such as evolutionary conservation, may improve our ability to predict the functional effects of amino acid variation.