Prediction of estrus cyclicity in Asian elephants (Elephas maximus) through estimation of fecal progesterone metabolite: development of an enzyme-linked immuno-sorbent assay

Asian elephants (Elephas maximus), prominent “flagship species”, are listed under the category of endangered species (EN - A2c, ver. 3.1; IUCN Red List 2009) and there is a need for their conservation. This requires understanding demographic and reproductive dynamics of the species. Monitoring reproductive status of any species is traditionally being carried out through invasive blood sampling and this is restrictive for large animals such as wild or semi-captive elephants due to legal, ethical, and practical reasons. Hence, there is a need for a non-invasive technique to assess reproductive cyclicity profiles of elephants, which will help in the species’ conservation strategies. In this study, we developed an indirect competitive enzyme linked immuno-sorbent assay (ELISA) to estimate the concentration of one of the progesterone-metabolites i.e., allopregnanolone (5α-P-3OH) in fecal samples of Asian elephants. We validated the assay which had a sensitivity of 0.25 μM at 90% binding with an EC₅₀ value of 1.37 μM. Using female elephants, kept under semi-captive conditions in the forest camps of Mudumalai Wildlife Sanctuary, Tamil Nadu and Bandipur National Park, Karnataka, India, we measured fecal progesterone-metabolite (5α-P-3OH) concentrations in six animals and showed their clear correlation with those of serum progesterone, measured by a standard radio-immuno assay. Statistical analyses using a Linear Mixed Effect model showed a positive correlation (P < 0.1) between the profiles of fecal 5α-P-3OH (range: 0.5-10 μg/g) and serum progesterone (range: 0.1-1.8 ng/mL). Therefore, our studies show, for the first time, that the fecal progesterone-metabolite assay could be exploited to predict estrus cyclicity and to potentially assess the reproductive status of captive and free-ranging female Asian elephants, thereby helping to plan their breeding strategy.