Gut microbiome variation based on 16S rRNA gene amplicon sequencing of the wild and domesticated broodstock populations of black tiger shrimp (Penaeus monodon) in the Indo-Pacific region

Gut microbiome variation has functional importance on host fitness, ecology, and evolution, but the scope and basis of microbial diversity for marine shrimp are still not fully understood. The aim of present study is to characterize the gut microbiomes of five Penaeus monodon broodstocks populations of wild and aquaculture environments within the Indo-Pacific region. We conducted data analysis of 16S rRNA gene amplicons using Qiime2 and Microbiomeanalyst and functional prediction by FAPROTAX (Functional Annotation of Prokaryotic Taxa). Our results identified considerable variation in the gut microbiomes of wild and cultured shrimps, presumably reflecting differences in diet, host genetic divergence, and host-bacteria co-evolution. While wild shrimp broodstocks had higher gut microbial diversity, a pronounced divergence of core microbiota was detected in PCOA analysis for both wild and cultured shrimp populations with altered community structure and predicted metabolic functions. Proteobacteria was observed to be dominated in the gut microbiome in all P. monodon populations, whereas Gracilibacteria and Fusobacteriia were only found in domesticated populations. Interestingly, probiotic bacteria such as genus Enterococcus and Lactobacillus were observed to be the core genus for both wild populations with range from 1.08% to 17.67%. LEfSe analysis detected significant enrichment of beneficial/opportunistic pathogens from the gut microbiome of each host population, suggesting possible biomarkers for host health monitoring. Our results provide insights into the deterministic factors contributing to the interpopulation variation in the P. monodon microbiome, highlighting potential future research directions in areas such as host-bacteria co-evolution and holobiome, which may enable the assessment of host-species genomic divergence across environmental gradients.