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Pheromones are odoriferous volatile chemical cues produced by animals for communication among conspecifics so as to regulate their social behaviors. In general, the odor compounds are recognized by receptors in the nasal cavity. Odorant-binding protein (OBP), a lipocalin family protein, mediates the air-borne odor cues to nasal receptors through nasal mucus. The presence of OBP in several mammalian species is well documented but to-date there is no report of a nasal OBP in buffalo. Hence, the present study was undertaken to investigate if OBP is present in buffalo nasal mucus. Uni- and two-dimensional gel electrophoresis of the nasal mucus suggested the presence of OBP, which was confirmed using mass spectrometry. In silico homology model of the OBP was generated and its structural similarity with other mammalian OBPs was assessed. Finally, molecular-docking and -dynamics simulations analysis revealed the efficiency of buffalo nasal OBP (bunOBP) to bind with buffalo pheromones as well as other reported chemical cues. Taken together, the occurrence of nasal OBP in buffalo and its putative role in odor binding are reported for the first time. The potential association of this protein with estrus-specific volatiles could be taken to advantage for non-invasive detection of estrus in buffaloes.

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Background:Buffaloes are silent heat animals and lacunae in their estrus detection results a substantial economic loss in developing countries. Many advanced tools to aid heat detection have been developed but are neither affordable nor easily interpretable by marginal farmers.Aim:The present investigation was made to develop a cost-effective estrus detection model by combining several known estrus predicting parameters.Materials and Methods:Various signs of estrus were classified under major parameters such as visual, cow behavioral, bull behavioral, biochemical, and gyneco-clinical. Expression of those parameters was observed in buffaloes, and the percentage of positive estrus detection was calculated for each combination of estrus prediction parameters.Results:The present result concludes that the model comprises of five parameters group with several signals with twenty-six different combinations. It was observed that the expression of individual combinations and their corresponding estrus detection efficiency varies significantly, i.e., detection efficiency rises as the number of combination increases.Conclusion:Combination of three parameters would provide an estrus detection efficiency >70% and suggested for an easy estrus detection. This would be a cost-effective model for farmers and benefits in enhancing buffalo population/reproduction.