4 resultados para New mutations

em Indian Institute of Science - Bangalore - Índia


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Mutations in the autosomal genes TMPRSS3, TMC1, USHIC, CDH23 and TMIE are known to cause hereditary hearing loss. To study the contribution of these genes to autosomal recessive, non-syndromic hearing loss (ARNSHL) in India, we examined 374 families with the disorder to identify potential mutations. We found four mutations in TMPRSS3, eight in TMC1, ten in USHIC, eight in CDH23 and three in TMIE. Of the 33 potentially pathogenic variants identified in these genes, 23 were new and the remaining have been previously reported. Collectively, mutations in these five genes contribute to about one-tenth of ARNSHL among the families examined. New mutations detected in this study extend the allelic heterogeneity of the genes and provide several additional variants for structure-function correlation studies. These findings have implications for early DNA-based detection of deafness and genetic counseling of affected families in the Indian subcontinent.

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The genome of Helicobacter pylori is rich in restrictionmodification (RM) systems. Approximately 4% of the genome codes for components of RM systems. hpyAVIBM, which codes for a phase-variable C5 cytosine methyltransferase (MTase) from H. pylori, lacks a cognate restriction enzyme. Over-expression of M.HpyAVIB in Escherichia coli enhances the rate of mutations. However, when the catalytically inactive F9N or C82W mutants of M.HpyAVIB were expressed in E. coli, mutations were not observed. The M.HpyAVIB gene itself was mutated to give rise to different variants of the MTase. M.HpyAVIB variants were purified and differences in kinetic properties and specificity were observed. Intriguingly, purified MTase variants showed relaxed substrate specificity. Homologues of hpyAVIBM homologues amplified and sequenced from different clinical isolates showed similar variations in sequence. Thus, hpyAVIBM presents an interesting example of allelic variations in H. pylori where changes in the nucleotide sequence result in proteins with new properties.

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Resistance to therapy limits the effectiveness of drug treatment in many diseases. Drug resistance can be considered as a successful outcome of the bacterial struggle to survive in the hostile environment of a drug-exposed cell. An important mechanism by which bacteria acquire drug resistance is through mutations in the drug target. Drug resistant strains (multi-drug resistant and extensively drug resistant) of Mycobacterium tuberculosis are being identified at alarming rates, increasing the global burden of tuberculosis. An understanding of the nature of mutations in different drug targets and how they achieve resistance is therefore important. An objective of this study is to first decipher sequence as well as structural bases for the observed resistance in known drug resistant mutants and then to predict positions in each target that are more prone to acquiring drug resistant mutations. A curated database containing hundreds of mutations in the 38 drug targets of nine major clinical drugs, associated with resistance is studied here. Mutations have been classified into those that occur in the binding site itself, those that occur in residues interacting with the binding site and those that occur in outer zones. Structural models of the wild type and mutant forms of the target proteins have been analysed to seek explanations for reduction in drug binding. Stability analysis of an entire array of 19 mutations at each of the residues for each target has been computed using structural models. Conservation indices of individual residues, binding sites and whole proteins are computed based on sequence conservation analysis of the target proteins. The analyses lead to insights about which positions in the polypeptide chain have a higher propensity to acquire drug resistant mutations. Thus critical insights can be obtained about the effect of mutations on drug binding, in terms of which amino acid positions and therefore which interactions should not be heavily relied upon, which in turn can be translated into guidelines for modifying the existing drugs as well as for designing new drugs. The methodology can serve as a general framework to study drug resistant mutants in other micro-organisms as well.

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Following transmission, HIV-1 adapts in the new host by acquiring mutations that allow it to escape from the host immune response at multiple epitopes. It also reverts mutations associated with epitopes targeted in the transmitting host but not in the new host. Moreover, escape mutations are often associated with additional compensatory mutations that partially recover fitness costs. It is unclear whether recombination expedites this process of multi-locus adaptation. To elucidate the role of recombination, we constructed a detailed population dynamics model that integrates viral dynamics, host immune response at multiple epitopes through cytotoxic T lymphocytes, and viral evolution driven by mutation, recombination, and selection. Using this model, we compute the expected waiting time until the emergence of the strain that has gained escape and compensatory mutations against the new host's immune response, and reverted these mutations at epitopes no longer targeted. We find that depending on the underlying fitness landscape, shaped by both costs and benefits of mutations, adaptation proceeds via distinct dominant pathways with different effects of recombination, in particular distinguishing escape and reversion. When adaptation at a single epitope is involved, recombination can substantially accelerate immune escape but minimally affects reversion. When multiple epitopes are involved, recombination can accelerate or inhibit adaptation depending on the fitness landscape. Specifically, recombination tends to delay adaptation when a purely uphill fitness landscape is accessible at each epitope, and accelerate it when a fitness valley is associated with each epitope. Our study points to the importance of recombination in shaping the adaptation of HIV-1 following its transmission to new hosts, a process central to T cell-based vaccine strategies. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license.