tuberculosis treatment includes broad-spectrum antibiotics such as rifampicin, streptomycin and fluoroquinolones, which are also used against other pathogenic bacteria. We developed Drug Resistance Associated Genes database (DRAGdb), a manually curated repository of mutational data of drug resistance associated genes (DRAGs) across ESKAPE (i.e. Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) pathogens, and other bacteria with a special focus on Mycobacterium tuberculosis (MTB). Analysis of mutations in drug-resistant genes listed in DRAGdb suggested both homoplasy and pleiotropy to be associated with resistance. Homoplasy was observed in six genes namely gidB, gyrA, gyrB, rpoB, rpsL and rrs. For these genes, drug resistance-associated mutations at codon level were conserved in MTB, ESKAPE and many other bacteria. Pleiotropy was exemplified by a single nucleotide mutation that was associated with resistance to amikacin, gentamycin, rifampicin and vancomycin in Staphylococcus aureus. DRAGdb data also revealed that mutations in some genes such as pncA, inhA, katG and embA,B,C were specific to Mycobacterium species. for inhA and pncA, the mutations in the promoter region along with those in coding regions were associated with resistance to isoniazid and pyrazinamide respectively. In summary, the DRAGdb database is a compilation of all the major MTB drug resistance genes across bacterial species, which allows identification of homoplasy and pleiotropy phenomena of DRAGs. There is a rise in the use of broad spectrum antibiotics such as rifamycins, aminoglycosides and fluoroquinolones against tuberculosis (TB), as well as common bacterial infections such as gastro-intestinal infections 1-3. The multi-and extensively drug-resistant (MDR and XDR) Mycobacterium tuberculosis (MTB) pose a global threat to public health as new resistance mechanisms are developing and making the treatment for patients prolonged and expensive. Drug resistance is not restricted to TB, but also observed in common bacterial infections such as pneumonia and foodborne infections 4,5. Genome-wide analysis of MDR and XDR MTB reveals that drug resistance arises due to mutations in the gene and/or the promoter region. Drug resistance associated mutations are linked to increasing drug efflux, modifications of the drugs or their targets 6-8. The accessibility to next-generation sequencing technologies and characterization of bacteria specific drug resistance allows the extensive study of other pathogenic bacteria as well 9-11. Antibiotic resistance mutations specific to pathogenic bacteria are available. The Infectious Diseases Society of America has grouped Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa and Enterobacter spp. as ESKAPE pathogens that are capable of 'escaping' the actions of antibiotics thereby developing antibiotic resistance 12. The ESKAPE pathogens are the leading cause of Hospi...
Two-component systems (TCSs) are central to the ability of Mycobacterium tuberculosis to respond to stress. One such paired TCS is SenX3-RegX3, which responds to phosphate starvation. Here we show that RegX3 is required for M. tuberculosis to withstand low pH, one of the challenges encountered by the bacterium in the host environment, and that RegX3 activates the cytosolic redox sensor WhiB3 to launch an appropriate response to acid stress. We show that the whiB3 promoter of M. tuberculosis harbors a RegX3 binding motif. Electrophoretic mobility shift assays (EMSAs) show that phosphorylated RegX3 (RegX3-P) (but not its unphosphorylated counterpart) binds to this motif, whereas a DNA binding mutant, RegX3 (K204A) fails to do so. Mutation of the putative RegX3 binding motif on the whiB3 promoter, abrogates the binding of RegX3-P. The significance of this binding is established by demonstrating that the expression of whiB3 is significantly attenuated under phosphate starvation or under acid stress in the regX3-inactivated mutant, regX3. Green fluorescent protein (GFP)-based reporter assays further confirm the requirement of RegX3 for the activation of the whiB3 promoter. The compromised survival of regX3 under acid stress and its increased trafficking to the lysosomal compartment are reversed upon complementation with either regX3 or whiB3, suggesting that RegX3 exerts its effects in a WhiB3dependent manner. Finally, using an in vitro granuloma model, we show that granuloma formation is compromised in the absence of regX3, but restored upon complementation with either regX3 or whiB3. Our findings provide insight into an important role of RegX3 in the network that regulates the survival of M. tuberculosis under acid stress similar to that encountered in its intracellular niche. Our results argue strongly in favor of a role of the RegX3-WhiB3 axis in establishment of M. tuberculosis infection.
Plasmacytoid dendritic cells (pDCs) express Toll like receptors (TLRs) that modulate the immune response by production of type I interferons. Here, we report that sphingosine kinase 1 (SphK1) which produces the bioactive sphingolipid metabolite, sphingosine 1‐phosphate (S1P), plays a critical role in the pDC functions and interferon production. Although dispensable for the pDC development, SphK1 is essential for the pDC activation and production of type I IFN and pro‐inflammatory cytokines stimulated by TLR7/9 ligands. SphK1 interacts with TLRs and specific inhibition or deletion of SphK1 in pDCs mitigates uptake of CpG oligonucleotide ligands by TLR9 ligand. In the pristane‐induced murine lupus model, pharmacological inhibition of SphK1 or its genetic deletion markedly decreased the IFN signature, pDC activation, and glomerulonephritis. Moreover, increases in the SphK1 expression and S1P levels were observed in human lupus patients. Taken together, our results indicate a pivotal regulatory role for the SphK1/S1P axis in maintaining the balance between immunosurveillance and immunopathology and suggest that specific SphK1 inhibitors might be a new therapeutic avenue for the treatment of type I IFN‐linked autoimmune disorders.
PPIMpred is a web server that allows high-throughput screening of small molecules for targeting specific protein–protein interactions, namely Mdm2/P53, Bcl2/Bak and c-Myc/Max. Three different kernels of support vector machine (SVM), namely, linear, polynomial and radial basis function (RBF), and two other machine learning techniques including Naive Bayes and Random Forest were used to train the models. A fivefold cross-validation technique was used to measure the performance of these classifiers. The RBF kernel of SVM outperformed and/or was comparable with all other methods with accuracy values of 83%, 79% and 90% for Mdm2/P53, Bcl2/Bak and c-Myc/Max, respectively. About 80% of the predicted SVM scores of training/testing datasets from Mdm2/P53 and Bcl2/Bak have significant IC50 values and docking scores. The proposed models achieved an accuracy of 66–90% with blind sets. The three mentioned (Mdm2/P53, Bcl2/Bak and c-Myc/Max) proposed models were screened in a large dataset of 265 242 small chemicals from National Cancer Institute open database. To further realize the robustness of this approach, hits with high and random SVM scores were used for molecular docking in AutoDock Vina wherein the molecules with high and random predicted SVM scores yielded moderately significant docking scores (p-values < 0.1). In addition to the above-mentioned classification scheme, this web server also allows users to get the structural and chemical similarities with known chemical modulators or drug-like molecules based on Tanimoto coefficient similarity search algorithm. PPIMpred is freely available at .
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