Chandigarh Institute of Microbial Technology

Chandigarh, India

Chandigarh Institute of Microbial Technology

Chandigarh, India
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Makkar R.S.,279. Sweet Alyssum Dr | Cameotra S.S.,Chandigarh Institute of Microbial Technology | Banat I.M.,University of Ulster
AMB Express | Year: 2011

Biosurfactants are amphiphilic molecules that have both hydrophilic and hydrophobic moieties which partition preferentially at the interfaces such as liquid/liquid, gas/liquid or solid/liquid interfaces. Such characteristics enable emulsifying, foaming, detergency and dispersing properties. Their low toxicity and environmental friendly nature and the wide range of potential industrial applications in bioremediation, health care, oil and food processing industries makes them a highly sought after group of chemical compounds. Interest in them has also been encouraged because of the potential advantages they offer over their synthetic counterparts in many fields spanning environmental, food, biomedical, petrochemical and other industrial applications. Their large scale production and application however are currently restricted by the high cost of production and by the limited understanding of their interactions with cells and with the abiotic environment. In this paper, we review the current knowledge and latest advances in the search for cost effective renewable agro industrial alternative substrates for their production. © 2011. Makkar; licensee Springer.

Sachdev D.P.,University of Pune | Cameotra S.S.,Chandigarh Institute of Microbial Technology
Applied Microbiology and Biotechnology | Year: 2013

Agricultural productivity to meet growing demands of human population is a matter of great concern for all countries. Use of green compounds to achieve the sustainable agriculture is the present necessity. This review highlights the enormous use of harsh surfactants in agricultural soil and agrochemical industries. Biosurfactants which are reported to be produced by bacteria, yeasts, and fungi can serve as green surfactants. Biosurfactants are considered to be less toxic and eco-friendly and thus several types of biosurfactants have the potential to be commercially produced for extensive applications in pharmaceutical, cosmetics, and food industries. The biosurfactants synthesized by environmental isolates also has promising role in the agricultural industry. Many rhizosphere and plant associated microbes produce biosurfactant; these biomolecules play vital role in motility, signaling, and biofilm formation, indicating that biosurfactant governs plant-microbe interaction. In agriculture, biosurfactants can be used for plant pathogen elimination and for increasing the bioavailability of nutrient for beneficial plant associated microbes. Biosurfactants can widely be applied for improving the agricultural soil quality by soil remediation. These biomolecules can replace the harsh surfactant presently being used in million dollar pesticide industries. Thus, exploring biosurfactants from environmental isolates for investigating their potential role in plant growth promotion and other related agricultural applications warrants details research. Conventional methods are followed for screening the microbial population for production of biosurfactant. However, molecular methods are fewer in reaching biosurfactants from diverse microbial population and there is need to explore novel biosurfactant from uncultured microbes in soil biosphere by using advanced methodologies like functional metagenomics. © 2012 The Author(s).

Khan N.,Chandigarh Institute of Microbial Technology
Journal of Innate Immunity | Year: 2015

Tuberculosis (TB) is one of the leading killer infectious diseases. TB patients are inflicted with devastating side effects and the toxicity of a lengthy drug regime, accentuating an urgent need to explore newer and safer treatment methods. Recently, an improved understanding of host-pathogen interaction has opened new avenues for TB treatment, including immunotherapy. This has emboldened us to devise a novel strategy to restrict Mycobacterium tuberculosis(Mtb) growth by activating dendritic cells (DCs) through the NOD-2 and TLR-4 molecules of innate immunity. Triggered DCs show a robust release of cytokines and nitric oxide, autophagy and improved migration towards the lymph nodes, and consequently impede the intracellular survival of Mtb. Of note, this approach enhanced the efficacy of TB drugs by reducing their dose to a 5-fold lesser concentration than recommended. In vivo administration of ligands of NOD-2 (NOD-2L) and TLR-4 (TLR-4L) substantially increased the pool of effector memory CD4 and CD8 T cells. Additionally, NOD-2L and TLR-4L, in conjunction with the reduced dose of isoniazid, substantially declined the Mtb burden in the lungs. In the future, adjunct therapy involving NOD-2L, TLR-4L and TB drugs may have enough potential to reduce the dose and duration of treatment of TB patients. © 2015 S. Karger AG, Basel Copyright © 2015, S. Karger AG. All rights reserved.

Panwar B.,Chandigarh Institute of Microbial Technology
BMC genomics | Year: 2010

Aminoacyl tRNA synthetases (aaRSs) catalyse the first step of protein synthesis in all organisms. They are responsible for the precise attachment of amino acids to their cognate transfer RNAs. There are twenty different types of aaRSs, unique for each amino acid. These aaRSs have been divided into two classes, each comprising ten enzymes. It is important to predict and classify aaRSs in order to understand protein synthesis. In this study, all models were developed on a non-redundant dataset containing 117 aaRSs and an equal number of non-aaRSs, in which no two sequences have more than 30% similarity. First, we applied the similarity search technique, BLAST, and achieved a maximum accuracy of 67.52%. We observed that 62% of tRNA synthetases contain one or more domains from amongst the following four PROSITE domains: PS50862, PS00178, PS50860 and PS50861. An SVM-based model was developed to discriminate between aaRSs, and non-aaRSs, and achieved a maximum MCC of 0.68 with accuracy of 83.73%, using selective dipeptide composition. We developed a hybrid approach and achieved a maximum MCC of 0.72 with accuracy of 85.49%, where SVM model developed using selected dipeptide composition and information of four PROSITE domains. We further developed an SVM-based model for classifying the aaRSs into class-1 and class-2, using selective dipeptide composition and achieved an MCC of 0.79. We also observed that two domains (PS00178, PS50889) in class-1 and three domains (PS50862, PS50860, PS50861) in class-2 were preferred. A hybrid method was developed using these domains as descriptor, along with selected dipeptide composition, and achieved an MCC of 0.87 with a sensitivity of 94.55% and an accuracy of 93.19%. All models were evaluated using a five-fold cross-validation technique. We have analyzed protein sequences of aaRSs (class-1 and class-2) and non-aaRSs and identified interesting patterns. The high accuracy achieved by our SVM models using selected dipeptide composition demonstrates that certain types of dipeptide are preferred in aaRSs. We were able to identify PROSITE domains that are preferred in aaRSs and their classes, providing interesting insights into tRNA synthetases. The method developed in this study will be useful for researchers studying aaRS enzymes and tRNA biology. The web-server based on the above study, is available at

Raghava G.P.,Chandigarh Institute of Microbial Technology
BMC bioinformatics | Year: 2014

BACKGROUND: In past number of methods have been developed for predicting post-translational modifications in proteins. In contrast, limited attempt has been made to understand post-transcriptional modifications. Recently it has been shown that tRNA modifications play direct role in the genome structure and codon usage. This study is an attempt to understand kingdom-wise tRNA modifications particularly uridine modifications (UMs), as majority of modifications are uridine-derived.RESULTS: A three-steps strategy has been applied to develop an efficient method for the prediction of UMs. In the first step, we developed a common prediction model for all the kingdoms using a dataset from MODOMICS-2008. Support Vector Machine (SVM) based prediction models were developed and evaluated by five-fold cross-validation technique. Different approaches were applied and found that a hybrid approach of binary and structural information achieved highest Area under the curve (AUC) of 0.936. In the second step, we used newly added tRNA sequences (as independent dataset) of MODOMICS-2012 for the kingdom-wise prediction performance evaluation of previously developed (in the first step) common model and achieved performances between the AUC of 0.910 to 0.949. In the third and last step, we used different datasets from MODOMICS-2012 for the kingdom-wise individual prediction models development and achieved performances between the AUC of 0.915 to 0.987.CONCLUSIONS: The hybrid approach is efficient not only to predict kingdom-wise modifications but also to classify them into two most prominent UMs: Pseudouridine (Y) and Dihydrouridine (D). A webserver called tRNAmod ( has been developed, which predicts UMs from both tRNA sequences and whole genome.

Kumar A.,Chandigarh Institute of Microbial Technology
Expert reviews in molecular medicine | Year: 2011

Mycobacterium tuberculosis (Mtb) is a metabolically flexible pathogen that has the extraordinary ability to sense and adapt to the continuously changing host environment experienced during decades of persistent infection. Mtb is continually exposed to endogenous reactive oxygen species (ROS) as part of normal aerobic respiration, as well as exogenous ROS and reactive nitrogen species (RNS) generated by the host immune system in response to infection. The magnitude of tuberculosis (TB) disease is further amplified by exposure to xenobiotics from the environment such as cigarette smoke and air pollution, causing disruption of the intracellular prooxidant-antioxidant balance. Both oxidative and reductive stresses induce redox cascades that alter Mtb signal transduction, DNA and RNA synthesis, protein synthesis and antimycobacterial drug resistance. As reviewed in this article, Mtb has evolved specific mechanisms to protect itself against endogenously produced oxidants, as well as defend against host and environmental oxidants and reductants found specifically within the microenvironments of the lung. Maintaining an appropriate redox balance is critical to the clinical outcome because several antimycobacterial prodrugs are only effective upon bioreductive activation. Proper homeostasis of oxido-reductive systems is essential for Mtb survival, persistence and subsequent reactivation. The progress and remaining deficiencies in understanding Mtb redox homeostasis are also discussed.

Thakur N.,Chandigarh Institute of Microbial Technology | Qureshi A.,Chandigarh Institute of Microbial Technology | Kumar M.,Chandigarh Institute of Microbial Technology
Nucleic Acids Research | Year: 2012

In the battle against viruses, antiviral peptides (AVPs) had demonstrated the immense potential. Presently, more than 15 peptide-based drugs are in various stages of clinical trials. Emerging and re-emerging viruses further emphasize the efforts to accelerate antiviral drug discovery efforts. Despite, huge importance of the field, no dedicated AVP resource is available. In the present study, we have collected 1245 peptides which were experimentally checked for antiviral activity targeting important human viruses like influenza, HIV, HCV and SARS, etc. After removing redundant peptides, 1056 peptides were divided into 951 training and 105 validation data sets. We have exploited various peptides sequence features, i.e. motifs and alignment followed by amino acid composition and physicochemical properties during 5-fold cross validation using Support Vector Machine. Physiochemical properties-based model achieved maximum 85 accuracy and 0.70 Matthew's Correlation Coefficient (MCC). Performance of this model on the experimental validation data set showed 86 accuracy and 0.71 MCC which is far better than the general antimicrobial peptides prediction methods. Therefore, AVPpred-the first web server for predicting the highly effective AVPs would certainly be helpful to researchers working on peptide-based antiviral development. The web server is freely available at © 2012 The Author(s).

Arora P.K.,Chandigarh Institute of Microbial Technology
PLoS ONE | Year: 2012

A 4-Chloro-2-nitrophenol (4C2NP) decolourizing strain RKJ 700 was isolated from soil collected from a pesticide contaminated site of India and identified as Bacillus subtilis on the basis of the 16S rRNA gene sequence analysis. Bacillus subtilis RKJ 700 decolourized 4C2NP up to concentration of 1.5 mM in the presence of additional carbon source. The degradation pathway of 4C2NP was studied and 4-chloro-2-aminophenol, 4-chloro-2-acetaminophenol and 5-chloro-2-methylbenzoxazole (5C2MBZ) were identified as metabolites by high performance liquid chromatography and gas chromatography-mass spectrometry. Resting cell studies showed that Bacillus subtilis RKJ 700 depleted 4C2NP completely with stoichiometric formation of 5C2MBZ. This is the first report of (i) the degradation of 4C2NP at high concentration (1.5 mM) and, (ii) the formation of 5C2MBZ by a soil bacterium. © 2012 Pankaj Kumar Arora.

Srinivasan V.B.,Chandigarh Institute of Microbial Technology | Rajamohan G.,Chandigarh Institute of Microbial Technology
Antimicrobial Agents and Chemotherapy | Year: 2013

Klebsiella pneumoniae has been frequently associated with nosocomial infections. Efflux systems are ubiquitous transporters that also function in drug resistance. Genome analysis of K. pneumoniae strain NTUH-K2044 revealed the presence of ∼15 putative drug efflux systems. We discuss here for the first time the characterization of a putative SMR-type efflux pump, an ebrAB homolog (denoted here as kpnEF) with respect to Klebsiella physiology and the multidrug-resistant phenotype. Analysis of hypermucoviscosity revealed direct involvement of kpnEF in capsule synthesis. The ΔkpnEF mutant displayed higher sensitivity to hyperosmotic (∼2.8-fold) and high bile (∼4.0-fold) concentrations. Mutation in kpnEF resulted in increased susceptibility to cefepime, ceftriaxone, colistin, erythromycin, rifampin, tetracycline, and streptomycin; mutated strains changed from being resistant to being susceptible, and the resistance was restored upon complementation. The kpnEF mutant displayed enhanced sensitivity toward structurally related compounds such as sodium dodecyl sulfate, deoxycholate, and dyes, including clinically relevant disinfectants such as benzalkonium chloride, chlorhexidine, and triclosan. The prevalence of kpnEF in clinical strains broadens the diversity of antibiotic resistance in K. pneumoniae. Experimental evidence of CpxR binding to the efflux pump promoter and quantification of its expression in a cpxAR mutant background demonstrated kpnEF to be a member of the Cpx regulon. This study helps to elucidate the unprecedented biological functions of the SMR-type efflux pump in Klebsiella spp. Copyright © 2013, American Society for Microbiology. All Rights Reserved.

Thakur N.,Chandigarh Institute of Microbial Technology | Qureshi A.,Chandigarh Institute of Microbial Technology | Kumar M.,Chandigarh Institute of Microbial Technology
Nucleic Acids Research | Year: 2012

RNAi technology has been emerging as a potential modality to inhibit viruses during past decade. In literature a few siRNA databases have been reported that focus on targeting human and mammalian genes but experimentally validated viral siRNA databases are lacking. We have developed VIRsiRNAdb, a manually curated database having comprehensive details of 1358 siRNA/shRNA targeting viral genome regions. Further, wherever available, information regarding alternative efficacies of above 300 siRNAs derived from different assays has also been incorporated. Important fields included in the database are siRNA sequence, virus subtype, target genome region, cell type, target object, experimental assay, efficacy, off-target and siRNA matching with reference viral sequences. Database also provides the users with facilities of advance search, browsing, data submission, linking to external databases and useful siRNA analysis tools especially siTarAlign which align the siRNA with reference viral genomes or user defined sequences. VIRsiRNAdb contains extensive details of siRNA/shRNA targeting 42 important human viruses including influenza virus, hepatitis B virus, HPV and SARS Corona virus. VIRsiRNAdb would prove useful for researchers in picking up the best viral siRNA for antiviral therapeutics development and also for developing better viral siRNA design tools. The database is freely available at © The Author(s) 2011. Published by Oxford University Press.

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