Dr. Rajendran Kooloth Valappil

Dr. Rajendran Kooloth Valappil

Dr. Rajendran Kooloth Valappilis
Central Institute of Fisheries Education

Dr. Rajendran Kooloth Valappil is a Principal Scientist and currently Head of the Aquatic Environment & Health Management Division, ICAR-CIFE, Mumbai. His current research includes shrimp virology, innate immune mechanisms and development of high throughput diagnostics for shrimp viruses. He has undertaken a wide range of research projects on aquatic animal health in Indian and overseas laboratories. He was a Korea Science and Engineering Foundation (KOSEF) post-doctoral fellow and worked on white spot syndrome virus (WSSV); He worked with CSIRO, Australia, for three years on developing specific pathogen-free domesticated lines of shrimp. He was also a recipient of Fulbright-Nehru Senior Research Fellowship and worked at the Auburn University, USA, on pathogen recognition receptors of fish. He has published 40 research articles in international journals. Recently, he and his team have reported Enetrocytozoon hepatopenaei infection from Indian shrimp farms for the first time. The latest project he has been involved with is ‘Defence genes of tiger shrimp (Penaeus monodon) with respect to bacteria (Vibrio  harveyi ) and white spot virus (WSSV) infection”

In the new project, the focus will be to undertake a comprehensive study on the shrimp farms located in the west coast of India.  The study involves characterisation of microbiome community structure and pathogen content in the shrimp and shrimp ponds using metagenomics; Determination of pathogen occurrence in pond ecosystem outside of crop species to measure pathogen diversity, reservoirs, alternative hosts and potential aetiological agents; Understanding how pond microbiome and host health vary under different conditions across time and identifying molecular biomarkers of these changes.  Further, assessment of the effect of probiotic treatment and farmer intervention methods on pond microbiome and pathogen prevalence will be carried out. The data generated will be used for developing models to predict disease risk. Finally, the project outcome will be extended to small-scale farmers for disease mitigation, training and disease diagnosis toward best management practices (BMP).