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Context Mastitis is an inflammation of mammary gland parenchyma, and is an unending cause of economic loss to the dairy industry. The interest in research on biomarker discovery for the diagnosis of bovine mastitis stems largely from the need to identify reliable biomarkers. Aim To determine the putative biomarkers of mastitis by using bioinformatics analysis, and experimental validation of pro-inflammatory cytokines and oxidative stress biomarkers of the mammary gland in healthy and diseased animals. Methods Various in silico analysis tools were applied to screen for gene expression in mastitis. Milk, as well as blood samples, was collected aseptically from the animals, which were then classified into three groups; namely, clinical, subclinical and control. Samples were subjected to assay of pro-inflammatory cytokines and oxidative biomarkers using enzyme-linked immunosorbent assay kits and the prescribed methodology respectively. Key results In silico analysis revealed that mastitis reduces the expression of fat metabolism and immune system-related genes, whereas it increased the expression of inflammatory genes. On laboratory analysis of cytokines and acute phase protein, it was revealed that interleukin-1∝, interleukin-8 and haptoglobin were significantly (P < 0.01) increased in both blood serum and milk whey in subclinical and clinical mastitis cows. On analysis of oxidative biomarkers, our results showed that oxidative stress was significantly (P < 0.05) increased with progression of mastitis in dairy cows. There was a significant (P < 0.05) increase in the blood serum level of malondialdehyde and nitric oxide, and a decrease in the level of anti-oxidant enzymes – glutathione peroxidase, superoxide dismutase and catalase – compared with healthy animals. Conclusion In conclusion, bioinformatics analysis of high-throughput gene expression revealed the involvement of multiple pathways, including the inflammatory pathway, fatty acid pathway and triglyceride synthesis pathway, in mastitis. Experimental validation confirmed that interleukin-8 and haptoglobin are putative early diagnostic markers for mastitis in dairy cattle. This study also concluded that milk can be used for the detection of cytokines as a non-invasive technique.

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The availability of complete genome sequences of H. pylori 26695 has provided a wealth of information enabling us to carry out in silico studies to identify new molecular targets for pharmaceutical treatment. In order to construe the structural and functional information of complete proteome, use of computational methods are more relevant since these methods are reliable and provide a solution to the time consuming and expensive experimental methods. Out of 1590 predicted protein coding genes in H. pylori, experimentally determined structures are available for only 145 proteins in the PDB. In the absence of experimental structures, computational studies on the three dimensional (3D) structural organization would help in deciphering the protein fold, structure and active site. Functional annotation of each protein was carried out based on structural fold and binding site based ligand association. Most of these proteins are uncharacterized in this proteome and through our annotation pipeline we were able to annotate most of them. We could assign structural folds to 464 uncharacterized proteins from an initial list of 557 sequences. Of the 1195 known structural folds present in the SCOP database, 411 (34% of all known folds) are observed in the whole H. pylori 26695 proteome, with greater inclination for domains belonging to α/β class (36.63%). Top folds include P-loop containing nucleoside triphosphate hydrolases (22.6%), TIM barrel (16.7%), transmembrane helix hairpin (16.05%), alpha-alpha superhelix (11.1%) and S-adenosyl-L-methionine-dependent methyltransferases (10.7%).