Neha Jain

In silico subtractive genomics for target identification in human bacterial pathogens

Target identification is the first step in the drug and vaccine discovery process; in silico subtractive genomics is widely used in this process. Using this approach, in recent years, a large number of targets have been identified for bacterial pathogens that are either drug resistant or for which no suitable vaccine is available; most such reports concern a specific pathogen. The in silico method reduces the time as well as the cost of target screening. Although a powerful technique that can be applied to a wide range of pathogens, there are many pitfalls in the analysis and interpretation of the data. We review this approach, including targets that have been identified with this technique and various other aspects, including advantages and disadvantages. We also discuss our own experiences using this technology. Drug Dev Res 72: 162–177, 2011.

Proteome scale comparative modeling for conserved drug and vaccine targets identification in Corynebacterium pseudotuberculosis

Corynebacterium pseudotuberculosis (Cp) is a pathogenic bacterium that causes caseous lymphadenitis (CLA), ulcerative lymphangitis, mastitis, and edematous to a broad spectrum of hosts, including ruminants, thereby threatening economic and dairy industries worldwide. Currently there is no effective drug or vaccine available against Cp. To identify new targets, we adopted a novel integrative strategy, which began with the prediction of the modelome (tridimensional protein structures for the proteome of an organism, generated through comparative modeling) for 15 previously sequenced C. pseudotuberculosis strains. This pan-modelomics approach identified a set of 331 conserved proteins having 95-100% intra-species sequence similarity. Next, we combined subtractive proteomics and modelomics to reveal a set of 10 Cp proteins, which may be essential for the bacteria. Of these, 4 proteins (tcsR, mtrA, nrdI, and ispH) were essential and non-host homologs (considering man, horse, cow and sheep as hosts) and satisfied all criteria of being putative targets. Additionally, we subjected these 4 proteins to virtual screening of a drug-like compound library. In all cases, molecules predicted to form favorable interactions and which showed high complementarity to the target were found among the top ranking compounds. The remaining 6 essential proteins (adk, gapA, glyA, fumC, gnd, and aspA) have homologs in the host proteomes. Their active site cavities were compared to the respective cavities in host proteins. We propose that some of these proteins can be selectively targeted using structure-based drug design approaches (SBDD). Our results facilitate the selection of C. pseudotuberculosis putative proteins for developing broad-spectrum novel drugs and vaccines. A few of the targets identified here have been validated in other microorganisms, suggesting that our modelome strategy is effective and can also be applicable to other pathogens.

A novel in silico reverse-transcriptomics-based identification and blood-based validation of a panel of sub-type specific biomarkers in lung cancer

Lung cancer accounts for the highest number of cancer-related deaths worldwide. Early diagnosis significantly increases the disease-free survival rate and a large amount of effort has been expended in screening trials and the development of early molecular diagnostics. However, a gold standard diagnostic strategy is not yet available. Here, based on miRNA expression profile in lung cancer and using a novel in silico reverse-transcriptomics approach, followed by analysis of the interactome; we have identified potential transcription factor (TF) markers that would facilitate diagnosis of subtype specific lung cancer. A subset of seven TF markers has been used in a microarray screen and was then validated by blood-based qPCR using stage-II and IV non-small cell lung carcinomas (NSCLC). Our results suggest that overexpression of HMGA1, E2F6, IRF1, and TFDP1 and downregulation or no expression of SUV39H1, RBL1, and HNRPD in blood is suitable for diagnosis of lung adenocarcinoma and squamous cell carcinoma sub-types of NSCLC. Here, E2F6 was, for the first time, found to be upregulated in NSCLC blood samples. The miRNA-TF-miRNA interaction based molecular mechanisms of these seven markers in NSCLC revealed that HMGA1 and TFDP1 play vital roles in lung cancer tumorigenesis. The strategy developed in this work is applicable to any other cancer or disease and can assist in the identification of potential biomarkers.

Complete genome sequence of Corynebacterium pseudotuberculosis biovar ovis strain P54B96 isolated from antelope in South Africa obtained by rapid next generation sequencing technology

The Actinobacteria, Corynebacterium pseudotuberculosis strain P54B96, a nonmotile, non-sporulating and a mesophile bacterium, was isolated from liver, lung and mediastinal lymph node lesions in an antelope from South Africa. This strain is interesting in the sense that it has been found together with non-tuberculous mycobacteria (NTMs) which could nevertheless play a role in the lesion formation. In this work, we describe a set of features of C. pseudotuberculosis P54B96, together with the details of the complete genome sequence and annotation. The genome comprises of 2.34 Mbp long, single circular genome with 2,084 protein-coding genes, 12 rRNA, 49 tRNA and 62 pseudogenes and a G+C content of 52.19%. The analysis of the genome sequence provides means to better understanding the molecular and genetic basis of virulence of this bacterium, enabling a detailed investigation of its pathogenesis.

Complete Genome Sequence of Corynebacterium pseudotuberculosis Strain CIP 52.97, Isolated from a Horse in Kenya

In this work, we report the whole-genome sequence of Corynebacterium pseudotuberculosis bv. equi strain CIP 52.97 (Collection Institut Pasteur), isolated in 1952 from a case of ulcerative lymphangitis in a Kenyan horse, which has evidently caused significant losses to agribusiness. Therefore, obtaining this genome will allow the detection of important targets for postgenomic studies, with the aim of minimizing problems caused by this microorganism.

Determining miRNA-disease associations using bipartite graph modelling

Exploring miRNA-disease interactions is critical to identify the impact of a disease on other diseases. Mapping this problem to a graph theoretical concept offers a unique perspective to study unseen relationships among diseases. In our work, maximum weighted matching has been used after mapping the miRNA-disease associations as a bipartite graph. We also address the limitation of this approach using disease ranking scheme and the results are presented.

Tight controlled expression and secretion of Lactobacillus brevis SlpA in Lactococcus lactis.

Prokaryotes commonly present outer cell wall structures composed of a crystalline array of proteinaceous subunits, known as surface layers (S-layers). The ORF encoding the S-layer protein (SlpA) of Lactobacillus brevis was cloned into Lactococcus lactis under the transcriptional control of the xylose-inducible expression system (XIES). SlpA was secreted into the extracellular medium, as determined by immunoblotting, and assays on the kinetics of SlpA production revealed that repression of the system with glucose did not require the depletion of xylose from the medium that allows transitory ORF expression. The successful use of XIES to express S-layer proteins in the versatile and generally recognized as safe species L. lactis opens new possibilities for an efficient production and isolation of SlpA S-layer protein for its various applications in biotechnology and importantly as an antigen-carrying vehicle.