Abstract
In India, tuberculosis is an enormous public health problem. This study provides the first description of molecular diversity of the Mycobacterium tuberculosis complex (MTBC) from Sikkim, India. A total of 399 Acid Fast Bacilli sputum positive samples were cultured on Lőwenstein–Jensen media and genetic characterisation was done by spoligotyping and 24-loci MIRU-VNTR typing. Spoligotyping revealed the occurrence of 58 different spoligotypes. Beijing spoligotype was the most dominant type constituting 62.41% of the total isolates and was associated with Multiple Drug Resistance. Minimum Spanning tree analysis of 249 Beijing strains based on 24-loci MIRU-VNTR analysis identified 12 clonal complexes (Single Locus Variants). The principal component analysis was used to visualise possible grouping of MTBC isolates from Sikkim belonging to major spoligotypes using 24-MIRU VNTR profiles. Artificial intelligence-based machine learning (ML) methods such as Random Forests (RF), Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used to predict dominant spoligotypes of MTBC using MIRU-VNTR data. K-fold cross-validation and validation using unseen testing data set revealed high accuracy of ANN, RF, and SVM for predicting Beijing, CAS1_Delhi, and T1 Spoligotypes (93–99%). However, prediction using the external new validation data set revealed that the RF model was more accurate than SVM and ANN.
Highlights
IntroductionThis study provides the first description of molecular diversity of the Mycobacterium tuberculosis complex (MTBC) from Sikkim, India
In India, tuberculosis is an enormous public health problem
To visualize possible clustering of Mycobacterium tuberculosis complex (MTBC) isolates according to spoligotypes, we reduced the multidimensional MIRU-VNTR data into a few principal components
Summary
This study provides the first description of molecular diversity of the Mycobacterium tuberculosis complex (MTBC) from Sikkim, India. 399 MTBC isolates from Sikkim using spoligotyping and 24-loci Mycobacterial Interspersed Repetitive UnitVariable Number of Tandem Repeats (MIRU-VNTR) typing. Numerous studies have shown that 24-loci MIRU-VNTR genetic markers have high discriminatory power, provide deep insight into MTBC Spoligotypes and sub-Spoligotypes and can be used as a very good alternative method for IS6110 restriction fragment length polymorphism (RFLP) which has numerous limitations[45,46,47,48]. Our study aimed to understand the genetic diversity of clinical isolates of MTBC from pulmonary tuberculosis cases from Sikkim a remote state in North-eastern India where the burden of tuberculosis is an emerging public health concern
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have