Snapshot of Mycobacterium tuberculosis Phylogenetics from an Indian State of Arunachal Pradesh Bordering China.

Uncontrolled transmission of Mycobacterium tuberculosis (M. tuberculosis, MTB) drug resistant strains is a challenge to control efforts of the global tuberculosis program. Due to increasing multi-drug resistant (MDR) cases in Arunachal Pradesh, a northeastern state of India, the tracking and tracing of these resistant MTB strains is crucial for infection control and spread of drug resistance. This study aims to correlate the phenotypic DST, genomic DST (gDST) and phylogenetic analysis of MDR-MTB strains in the region. Of the total 200 samples 22 (11%) patients suspected of MDR-TB and 160 (80%) previously treated MDR-TB cases, 125 (62.5%) were identified as MTB. MGIT-960 SIRE DST detected 71/125 (56.8%) isolates as MDR/RR-MTB of which 22 (30.9%) were detected resistant to second-line drugs. Whole-genome sequencing of 65 isolates and their gDST found Ser315Thr mutation in katG (35/45; 77.8%) and Ser531Leu mutation in rpoB (21/41; 51.2%) associated with drug resistance. SNP barcoding categorized the dataset with Lineage2 (41; 63.1%) being predominant followed by Lineage3 (10; 15.4%), Lineage1 (8; 12.3%) and Lineage4 (6; 9.2%) respectively. Phylogenetic assignment by cgMLST gave insights of two Beijing sub-lineages viz; 2.2.1 (SNP difference < 19) and 2.2.1.2 (SNP difference < 9) associated with recent ongoing transmission in Arunachal Pradesh. This study provides insights in identifying two virulent Beijing sub-lineages (sub-lineage 2.2.1 and 2.2.1.2) with ongoing transmission of TB drug resistance in Arunachal Pradesh.

Mutations in SARS-CoV-2 Leading to Antigenic Variations in Spike Protein: A Challenge in Vaccine Development.

Objectives The spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus has been unprecedentedly fast, spreading to more than 180 countries within 3 months with variable severity. One of the major reasons attributed to this variation is genetic mutation. Therefore, we aimed to predict the mutations in the spike protein (S) of the SARS-CoV-2 genomes available worldwide and analyze its impact on the antigenicity. Materials and Methods Several research groups have generated whole genome sequencing data which are available in the public repositories. A total of 1,604 spike proteins were extracted from 1,325 complete genome and 279 partial spike coding sequences of SARS-CoV-2 available in NCBI till May 1, 2020 and subjected to multiple sequence alignment to find the mutations corresponding to the reported single nucleotide polymorphisms (SNPs) in the genomic study. Further, the antigenicity of the predicted mutations inferred, and the epitopes were superimposed on the structure of the spike protein. Results The sequence analysis resulted in high SNPs frequency. The significant variations in the predicted epitopes showing high antigenicity were A348V, V367F and A419S in receptor binding domain (RBD). Other mutations observed within RBD exhibiting low antigenicity were T323I, A344S, R408I, G476S, V483A, H519Q, A520S, A522S and K529E. The RBD T323I, A344S, V367F, A419S, A522S and K529E are novel mutations reported first time in this study. Moreover, A930V and D936Y mutations were observed in the heptad repeat domain and one mutation D1168H was noted in heptad repeat domain 2. Conclusion S protein is the major target for vaccine development, but several mutations were predicted in the antigenic epitopes of S protein across all genomes available globally. The emergence of various mutations within a short period might result in the conformational changes of the protein structure, which suggests that developing a universal vaccine may be a challenging task.

Azithromycin resistance mechanisms in typhoidal salmonellae in India: A 25 years analysis.

Background & objectives: : Azithromycin has been in use as an alternate treatment option for enteric fever even when the guidelines on the susceptibility testing were not available. There is lack of data on susceptibility and mechanisms of resistance of azithromycin in Salmonella Typhi and S. Paratyphi A. The aim of the present study was to determine the azithromycin susceptibility and resistance mechanisms in typhoidal salmonellae isolates archived in a tertiary care centre in north India for a period of 25 years. Methods: : Azithromycin susceptibility was determined in 602 isolates of S. Typhi (469) and S. Paratyphi A (133) available as archived collection isolated during 1993 to 2016, by disc diffusion and E-test method.PCR was done for ereA, ermA, ermB, ermC, mefA, mphA and msrA genes from plasmid and genomic DNA and sequencing was done to detect mutations in acrR, rplD and rplV genes. Results: : Azithromycin susceptibility was seen in 437/469 [93.2%; 95% confidence interval (CI), 90.5 to 95.1%] isolates of S. Typhi. Amongst 133 isolates of S. Paratyphi A studied, minimum inhibitory concentration (MIC) of ≤16 mg/l was found in 102 (76.7%; 95% CI, 68.8 to 83.0). MIC value ranged between 1.5 and 32 mg/l with an increasing trend in MIC50and MIC90with time. Mutations were found in acrR in one and rplV in two isolates of S. Typhi. No acquired mechanism for macrolide resistance was found. Interpretation & conclusions: : Azithromycin could be considered as a promising agent against typhoid fever on the basis of MIC distribution in India. However, due to emergence of resistance in some parts, there is a need for continuous surveillance of antimicrobial susceptibility and resistance mechanisms. There is also a need to determine the breakpoints for S. Paratyphi A.

NGSPanPipe: A Pipeline for Pan-genome Identification in Microbial Strains from Experimental Reads.

Recent advancements in sequencing technologies have decreased both time span and cost for sequencing the whole bacterial genome. High-throughput Next-Generation Sequencing (NGS) technology has led to the generation of enormous data concerning microbial populations publically available across various repositories. As a consequence, it has become possible to study and compare the genomes of different bacterial strains within a species or genus in terms of evolution, ecology and diversity. Studying the pan-genome provides insights into deciphering microevolution, global composition and diversity in virulence and pathogenesis of a species. It can also assist in identifying drug targets and proposing vaccine candidates. The effective analysis of these large genome datasets necessitates the development of robust tools. Current methods to develop pan-genome do not support direct input of raw reads from the sequencer machine but require preprocessing of reads as an assembled protein/gene sequence file or the binary matrix of orthologous genes/proteins. We have designed an easy-to-use integrated pipeline, NGSPanPipe, which can directly identify the pan-genome from short reads. The output from the pipeline is compatible with other pan-genome analysis tools. We evaluated our pipeline with other methods for developing pan-genome, i.e. reference-based assembly and de novo assembly using simulated reads of Mycobacterium tuberculosis. The single script pipeline (pipeline.pl) is applicable for all bacterial strains. It integrates multiple in-house Perl scripts and is freely accessible from https://github.com/Biomedinformatics/NGSPanPipe .

RASOnD-a comprehensive resource and search tool for RAS superfamily oncogenes from various species.

BACKGROUND: The Ras superfamily plays an important role in the control of cell signalling and division. Mutations in the Ras genes convert them into active oncogenes. The Ras oncogenes form a major thrust of global cancer research as they are involved in the development and progression of tumors. This has resulted in the exponential growth of data on Ras superfamily across different public databases and in literature. However, no dedicated public resource is currently available for data mining and analysis on this family. The present database was developed to facilitate straightforward accession, retrieval and analysis of information available on Ras oncogenes from one particular site. DESCRIPTION: We have developed the RAS Oncogene Database (RASOnD) as a comprehensive knowledgebase that provides integrated and curated information on a single platform for oncogenes of Ras superfamily. RASOnD encompasses exhaustive genomics and proteomics data existing across diverse publicly accessible databases. This resource presently includes overall 199,046 entries from 101 different species. It provides a search tool to generate information about their nucleotide and amino acid sequences, single nucleotide polymorphisms, chromosome positions, orthologies, motifs, structures, related pathways and associated diseases. We have implemented a number of user-friendly search interfaces and sequence analysis tools. At present the user can (i) browse the data (ii) search any field through a simple or advance search interface and (iii) perform a BLAST search and subsequently CLUSTALW multiple sequence alignment by selecting sequences of Ras oncogenes. The Generic gene browser, GBrowse, JMOL for structural visualization and TREEVIEW for phylograms have been integrated for clear perception of retrieved data. External links to related databases have been included in RASOnD. CONCLUSIONS: This database is a resource and search tool dedicated to Ras oncogenes. It has utility to cancer biologists and cell molecular biologists as it is a ready source for research, identification and elucidation of the role of these oncogenes. The data generated can be used for understanding the relationship between the Ras oncogenes and their association with cancer. The database updated monthly is freely accessible online at http://202.141.47.181/rasond/ and http://www.aiims.edu/RAS.html.