Bioinformatics pipeline for predicting drug resistant Mycobacterium tuberculosis from whole genome sequencing data to identify the role Efflux pumps


Identification: AR-S


Description

Bioinformatics pipeline for predicting drug resistant Mycobacterium tuberculosis from whole genome sequencing data to identify the role Efflux pumps
BACKGROUND
Tuberculosis ( has a very high global burden, around 10 0 million people developed TB disease in 2017 Pakistan ranks 5 th amongst high TB burden countries Tackling drug resistance is critical to ending the TB epidemic Identification of MTB drug resistance based on culture and drug sensitivity testing takes 8 12 weeks. Hence there is an urgent need for rapid genotypic based methods for identification of drug resistance in MTB Active efflux of drugs mediated by efflux pumps that confer drug resistance is one of the mechanisms Whole genome sequencing ( based of target genes allows identifications of single nucleotide polymorphisms ( that may be associated with drug resistance).
METHODS
We focused on 10 efflux pump genes and identified SNPs and INDELs ( (Insertion / deletions). Further we will run the same on 25 Efflux pumps genes in 800 MTB isolates The data and its phenotypic drug susceptibility testing ( information were identified using ReSeqTB platform and extracted the SRA numbers of these isolates which were than download from ENA database We developed customized
pipeline to identify efflux gene targeted variants.
RESULTS
In the preliminary analysis, on three MTB isolates we were able to get a total of 39 SNPs and 4 INDELS (ranging from 10 47 bp) The SNPS were then further annotated using TBVAR that identified a deleterious mutation (G/ on 228168 position in Rv 0194 (multidrug ABC transporter) in three of the isolates that were from MDR, Pre XDR and XDR datasets and a novel SNP on position 228069 (G/A). Further, in this work we will analyze four sets of MTB phenotypes (multidrug resistant MDR, Extensively drug resistant XDR, and MDR fluoroquinolone resistant Pre XDR) comprising of n= 800 isolates from all 7 lineages.
CONCLUSION
Through this we will establish a novel bioinformatics pipeline to analyze MTB genomes for SNPs in the genes of interest. The same can be applied to other pathogens The future for rapid diagnosis and treatment of drug resistant TB is the combination of WGS based diagnostics.

Author(s)

Credits

Credits: None available.

You must be logged in and own this product in order to post comments.

Print Certificate
Completed on: token-completed_on
Print Transcript
Please select the appropriate credit type:
/
test_id: 
credits: 
completed on: 
rendered in: 
* - Indicates answer is required.
token-content

token-speaker-name
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
token-index
token-content
/
/
token-index
token-content
token-index
token-content