Correlation of drug resistance with single nucleotide variations through genome analysis and experimental validation in a multi-drug resistant clinical isolate of M. tuberculosis.

BACKGROUND: Genome sequencing and genetic polymorphism analysis of clinical isolates of M. tuberculosis is carried out to gain further insight into molecular pathogenesis and host-pathogen interaction. Therefore the functional evaluation of the effect of single nucleotide variation (SNV) is essential. At the same time, the identification of invariant sequences unique to M. tuberculosis contributes to infection detection by sensitive methods. In the present study, genome analysis is accompanied by evaluation of the functional implication of the SNVs in a MDR clinical isolate VPCI591. RESULT: By sequencing and comparative analysis of VPCI591 genome with 1553 global clinical isolates of M. tuberculosis (GMTV and tbVar databases), we identified 141 unique strain specific SNVs. A novel intergenic variation in VPCI591 in the putative promoter/regulatory region mapping between embC (Rv3793) and embA (Rv3794) genes was found to enhance the expression of embAB, which correlates with the high resistance of the VPCI591 to ethambutol. Similarly, the unique combination of three genic SNVs in RNA polymerase ß gene (rpoB) in VPCI591 was evaluated for its effect on rifampicin resistance through molecular docking analysis. The comparative genomics also showed that along with variations, there are genes that remain invariant. 173 such genes were identified in our analysis. CONCLUSION: The genetic variation in M. tuberculosis clinical isolate VPCI591 is found in almost all functional classes of genes. We have shown that SNV in rpoB gene mapping outside the drug binding site along with two SNVs in the binding site can contribute to quantitative change in MIC for rifampicin. Our results show the collective effect of SNVs on the structure of the protein, impacting the interaction between the target protein and the drug molecule in rpoB as an example. The study shows that intergenic variations bring about quantitative changes in transcription in embAB and in turn can lead to drug resistance.

Distinguishing between biochemical and cellular function: Are there peptide signatures for cellular function of proteins?

The genome annotation and identification of gene function depends on conserved biochemical activity. However, in the cell, proteins with the same biochemical function can participate in different cellular pathways and cannot complement one another. Similarly, two proteins of very different biochemical functions are put in the same class of cellular function; for example, the classification of a gene as an oncogene or a tumour suppressor gene is not related to its biochemical function, but is related to its cellular function. We have taken an approach to identify peptide signatures for cellular function in proteins with known biochemical function. ATPases as a test case, we classified ATPases (2360 proteins) and kinases (517 proteins) from the human genome into different cellular function categories such as transcriptional, replicative, and chromatin remodelling proteins. Using publicly available tool, MEME, we identify peptide signatures shared among the members of a given category but not between cellular functional categories; for example, no motif sharing is seen between chromatin remodelling and transporter ATPases, similarly between receptor Serine/Threonine Kinase and Receptor Tyrosine Kinase. There are motifs shared within each category with significant E value and high occurrence. This concept of signature for cellular function was applied to developmental regulators, the polycomb and trithorax proteins which led to the prediction of the role of INO80, a chromatin remodelling protein, in development. This has been experimentally validated earlier for its role in homeotic gene regulation and its interaction with regulatory complexes like the Polycomb and Trithorax complex. Proteins 2017; 85:682-693. © 2016 Wiley Periodicals, Inc.

Indian genetic disease database.

Indians, representing about one-sixth of the world population, consist of several thousands of endogamous groups with strong potential for excess of recessive diseases. However, no database is available on Indian population with comprehensive information on the diseases common in the country. To address this issue, we present Indian Genetic Disease Database (IGDD) release 1.0 (http://www.igdd.iicb.res.in)--an integrated and curated repository of growing number of mutation data on common genetic diseases afflicting the Indian populations. Currently the database covers 52 diseases with information on 5760 individuals carrying the mutant alleles of causal genes. Information on locus heterogeneity, type of mutation, clinical and biochemical data, geographical location and common mutations are furnished based on published literature. The database is currently designed to work best with Internet Explorer 8 (optimal resolution 1440 × 900) and it can be searched based on disease of interest, causal gene, type of mutation and geographical location of the patients or carriers. Provisions have been made for deposition of new data and logistics for regular updation of the database. The IGDD web portal, planned to be made freely available, contains user-friendly interfaces and is expected to be highly useful to the geneticists, clinicians, biologists and patient support groups of various genetic diseases.

Suppression of Toll-like receptor 2-mediated proinflammatory responses by Mycobacterium tuberculosis protein Rv3529c.

Microorganisms are known to devise various strategies to thwart protective responses by the host. One such strategy is to incorporate sequences and domains in their genes/proteins that have similarity to various domains of the host proteins. In this study, we report that Mycobacterium tuberculosis protein Rv3529c exhibits significant similarity to the death domain of the TLR pathway adaptor protein MyD88. Incubation of macrophages with Rv3529c specifically inhibited TLR2-mediated proinflammatory responses. This included attenuated oxidative burst, reduced phosphorylation of MAPK-ERK, reduced activation of transcription factor NF-κB and reduced secretion of proinflammatory cytokines IFN-γ, IL-6, and IL-17A with a concomitant increased secretion of suppressor cytokines IL-10 and TGF-ß. Importantly, Rv3529c significantly inhibited TLR2-induced association of MyD88 with IRAK1 by competitively binding with IRAK1. Further, Rv3529c mediated inhibition of apoptosis and phagosome-lysosome fusion. Lastly, incubation of macrophages with Rv3529c increased bacterial burden inside macrophages. The data presented show another strategy evolved by M. tuberculosis toward immune evasion that centers on incorporating sequences in proteins that are similar to crucial proteins in the innate immune system of the host.

Rv1458c: a new diagnostic marker for identification of Mycobacterium tuberculosis complex in a novel duplex PCR assay.

PURPOSE: We explored the efficiency of Rv1458c, the gene encoding a putative ABC drug transporter specific for the Mycobacterium tuberculosis complex (MTBC), as a diagnostic marker. METHODOLOGY: A 190 bp region of Rv1458c and a 300 bp region of hsp65 were targeted in a novel duplex PCR assay and the results were compared with those for PCR restriction analysis(PRA) using the restriction enzymes NruI and BamHI. Species identification of a subset of the isolates (n=50) was confirmed by sequencing. Clinical isolates of M. tuberculosis (n=426) obtained from clinically suspected patients of pulmonary tuberculosis and mycobacterial (n=13) and non-mycobacterial (n=8) reference strains were included in the study. RESULTS: The duplex PCR assay correctly identified 320/426 isolates as MTBC and 106/426 isolates as non-tuberculous mycobacteria(NTM). The test was 100 % specific and sensitive when compared with NruI/BamHI PCR restriction analysis and highlighted the use of Rv1458c as a diagnostic marker for MTBC. CONCLUSION: The duplex PCR assay could be developed for use as a screening test to identify MTBC in clinical specimens in peripheral laboratories with limited resources.

Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis.

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.