Dataset Information

Cascade of deoxyribozymes for the colorimetric analysis of drug resistance in Mycobacterium tuberculosis.

ABSTRACT: A visual cascade detection system has been applied to the detection and analysis of drug-resistance profile of Mycobacterium tuberculosis complex (MTC), a causative agent of tuberculosis. The cascade system utilizes highly selective split RNA-cleaving deoxyribozyme (sDz) sensors. When activated by a complementary nucleic acid, sDz releases the peroxidase-like deoxyribozyme apoenzyme, which, in complex with a hemin cofactor, catalyzes the color change of the sample's solution. The excellent selectivity of the cascade has allowed for the detection of point mutations in the sequences of the MTC rpoB, katG, and gyrA genes, which are responsible for resistance to rifampin, isoniazid, and fluoroquinolone, respectively. When combined with isothermal nucleic acid sequence based amplification (NASBA), the assay was able to detect amplicons of 16S rRNA and katG mRNA generated from 0.1 pg and 10 pg total RNA taken for NASBA, respectively, in less than 2 h, producing a signal detectable with the naked eye. The proposed assay may become a prototype for point-of-care diagnosis of drug resistant bacteria with visual signal output.

SUBMITTER: Dhar BC

PROVIDER: S-EPMC7484165 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Cascade of deoxyribozymes for the colorimetric analysis of drug resistance in Mycobacterium tuberculosis.

Dhar Bidhan C BC Reed Adam J AJ Mitra Suvra S Rodriguez Sanchez Patricia P Nedorezova Daria D DD Connelly Ryan P RP Rohde Kyle H KH Gerasimova Yulia V YV

Biosensors & bioelectronics 20200613

A visual cascade detection system has been applied to the detection and analysis of drug-resistance profile of Mycobacterium tuberculosis complex (MTC), a causative agent of tuberculosis. The cascade system utilizes highly selective split RNA-cleaving deoxyribozyme (sDz) sensors. When activated by a complementary nucleic acid, sDz releases the peroxidase-like deoxyribozyme apoenzyme, which, in complex with a hemin cofactor, catalyzes the color change of the sample's solution. The excellent selec ...[more]

PMID: 32729510

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Project description:BackgroundEmergence of drug resistant varieties of tuberculosis is posing a major threat to global tuberculosis eradication programmes. Although several approaches have been explored to counter resistance, there has been limited success due to a lack of understanding of how resistance emerges in bacteria upon drug treatment. A systems level analysis of the proteins involved is essential to gain insights into the routes required for emergence of drug resistance.ResultsWe derive a genome-scale protein-protein interaction network for Mycobacterium tuberculosis H37Rv from the STRING database, with proteins as nodes and interactions as edges. A set of proteins involved in both intrinsic and extrinsic drug resistance mechanisms are identified from literature. We then compute shortest paths from different drug targets to the set of resistance proteins in the protein-protein interactome, to derive a sub-network relevant to study emergence of drug resistance. The shortest paths are then scored and ranked based on a new scheme that considers (a) drug-induced gene upregulation data, from microarray experiments reported in literature, for the individual nodes and (b) edge-hubness, a network parameter which signifies centrality of a given edge in the network. High-scoring paths identified from this analysis indicate most plausible pathways for the emergence of drug resistance. Different targets appear to have different propensities for four drug resistance mechanisms. A new concept of 'co-targets' has been proposed to counter drug resistance, co-targets being defined as protein(s) that need to be simultaneously inhibited along with the intended target(s), to check emergence of resistance to a given drug.ConclusionThe study leads to the identification of possible pathways for drug resistance, providing novel insights into the problem of resistance. Knowledge of important proteins in such pathways enables identification of appropriate 'co-targets', best examples being RecA, Rv0823c, Rv0892 and DnaE1, for drugs targeting the mycolic acid pathway. Insights obtained about the propensity of a drug to trigger resistance will be useful both for more careful identification of drug targets as well as to identify target-co-target pairs, both implementable in early stages of drug discovery itself. This approach is also inherently generic, likely to significantly impact drug discovery.

Project description:Tuberculosis (TB) is the leading cause of death by an infectious disease, and global TB control efforts are increasingly threatened by drug resistance in Mycobacterium tuberculosis. Unlike most bacteria, where lateral gene transfer is an important mechanism of resistance acquisition, resistant M. tuberculosis arises solely by de novo chromosomal mutation. Using whole-genome sequencing data from two natural populations of M. tuberculosis, we characterized the population genetics of known drug resistance loci using measures of diversity, population differentiation, and convergent evolution. We found resistant subpopulations to be less diverse than susceptible subpopulations, consistent with ongoing transmission of resistant M. tuberculosis. A subset of resistance genes ("sloppy targets") were characterized by high diversity and multiple rare variants; we posit that a large genetic target for resistance and relaxation of purifying selection contribute to high diversity at these loci. For "tight targets" of selection, the path to resistance appeared narrower, evidenced by single favored mutations that arose numerous times in the phylogeny and segregated at markedly different frequencies in resistant and susceptible subpopulations. These results suggest that diverse genetic architectures underlie drug resistance in M. tuberculosis and that combined approaches are needed to identify causal mutations. Extrapolating from patterns observed for well-characterized genes, we identified novel candidate variants involved in resistance. The approach outlined here can be extended to identify resistance variants for new drugs, to investigate the genetic architecture of resistance, and when phenotypic data are available, to find candidate genetic loci underlying other positively selected traits in clonal bacteria. IMPORTANCEMycobacterium tuberculosis, the causative agent of tuberculosis (TB), is a significant burden on global health. Antibiotic treatment imposes strong selective pressure on M. tuberculosis populations. Identifying the mutations that cause drug resistance in M. tuberculosis is important for guiding TB treatment and halting the spread of drug resistance. Whole-genome sequencing (WGS) of M. tuberculosis isolates can be used to identify novel mutations mediating drug resistance and to predict resistance patterns faster than traditional methods of drug susceptibility testing. We have used WGS from natural populations of drug-resistant M. tuberculosis to characterize effects of selection for advantageous mutations on patterns of diversity at genes involved in drug resistance. The methods developed here can be used to identify novel advantageous mutations, including new resistance loci, in M. tuberculosis and other clonal pathogens.

Project description:Background: Tuberculosis (TB) remains a significant global public health issue, despite advances in diagnostic technologies, substantial global efforts, and the availability of effective chemotherapies. Mycobacterium tuberculosis, a species of pathogenic bacteria resistant to currently available anti-TB drugs, is on the rise, threatening national and international TB-control efforts. This systematic review and meta-analysis aims to estimate the pooled prevalence of drug-resistant TB (DR-TB) in Ethiopia. Materialsand Methods: A systematic literature search was undertaken using PubMed/MEDLINE, HINARI, the Web of Science, ScienceDirect electronic databases, and Google Scholar (1 January 2011 to 30 November 2020). After cleaning and sorting the records, the data were analyzed using STATA 11. The study outcomes revealed the weighted pooled prevalence of any anti-tuberculosis drug resistance, any isoniazid (INH) and rifampicin (RIF) resistance, monoresistance to INH and RIF, and multidrug-resistant TB (MDR-TB) in newly diagnosed and previously treated patients with TB. Results: A total of 24 studies with 18,908 patients with TB were included in the final analysis. The weighted pooled prevalence of any anti-TB drug resistance was 14.25% (95% confidence interval (CI): 7.05-21.44%)), whereas the pooled prevalence of any INH and RIF resistance was found in 15.62% (95%CI: 6.77-24.47%) and 9.75% (95%CI: 4.69-14.82%) of patients with TB, respectively. The pooled prevalence for INH and RIF-monoresistance was 6.23% (95%CI: 4.44-8.02%) and 2.33% (95%CI: 1.00-3.66%), respectively. MDR-TB was detected in 2.64% (95%CI: 1.46-3.82%) of newly diagnosed cases and 11.54% (95%CI: 2.12-20.96%) of retreated patients with TB, while the overall pooled prevalence of MDR-TB was 10.78% (95%CI: 4.74-16.83%). Conclusions: In Ethiopia, anti-tuberculosis drug resistance is widespread. The estimated pooled prevalence of INH and RIF-monoresistance rates were significantly higher in this review than in previous reports. Moreover, MDR-TB in newly diagnosed cases remained strong. Thus, early detection of TB cases, drug-resistance testing, proper and timely treatment, and diligent follow-up of TB patients all contribute to the improvement of DR-TB management and prevention. Besides this, we urge that a robust, routine laboratory-based drug-resistance surveillance system be implemented in the country.

Dataset Information

Cascade of deoxyribozymes for the colorimetric analysis of drug resistance in Mycobacterium tuberculosis.

Publications

Cascade of deoxyribozymes for the colorimetric analysis of drug resistance in Mycobacterium tuberculosis.

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