VARIATIONS IN POND MICROBIOME DURING CULTURE OF Penaeus vannamei AND ON WSSV AND EHP INFECTION

Shrimp farming has been substantially progressing in India following the introduction of Penaeus vannamei in 2009. Production of vannamei in India has been consistently increasing and crossed 550,000 tonnes during 2018. Apart from the export earnings the fish and shellfish brings in, aquaculture activity supports about 14 million farmers in India. Despite the significant progress in scientific farming technology and strong import biosecurity measures of vannamei brooders, the sector still suffers from infectious aetiologies. Most important pathogens that currently plague the culture of whiteleg shrimps are white spot syndrome virus (WSSV) and Enterocytozoon hepatopenaei (EHP). While there are no effective therapeutic methods for the diseases due to these pathogens, the control measures mainly depend on BMPs and early diagnosis of infections. With the current understanding of the conceptual change in the induction of diseases and the paradigm shift from the one pathogen one disease model to a pathobiome scenario, the role of microbiome associated with the host and the environment, especially in case of aquatic animals, has become of paramount importance.          

In the current study, we have investigated the variations in the pond water microbiome using Illumina sequencing technology by sampling across the culture period in a healthy crop cycle from different ponds and also from ponds that were infected with EHP and WSSV. Principal coordinates analysis (PCoA) based on unweighted Unifrac and Bray-Curtis methods have shown that there is strong clustering of bacterial communities in a temporal manner across the progression of the culture period in normal vannamei culture pond water (Fig.1). While Proteobacteria predominated in all the ponds investigated, Gammaproteobacteria reached almost 67 to 82% towards the end of the crop of 105 and 120 DOC respectively. Analysis of WSSV and EHP infected pond microbiome also showed characteristic clustering specific to the aetiology. Further studies with more samples are being investigated to delineate the inferences.