Nitrogen species such as ammonia and nitrite are considered as major stressors in modern aquaculture practices. We developed enrichments of ammonia oxidising bacteria (AOB) and nitrite oxidising bacteria (NOB) for effective mitigation of nitrogenous wastes in the shrimp culture operations. The objective of this study was to understand the microbial community composition of AoB and noB enrichments using the V3-V4 region of the 16S rDNA gene by Illumina MiSeq sequencing. The analysis revealed 2948 and 1069 OTUs at 97% similarity index and Shannon alpha diversity index of 7.64 and 4.85 for AOB and NOB enrichments, respectively. Comparative analysis showed that a total of 887 OTUs were common among AOB and NOB enrichments. The AOB and NOB enrichment were dominated by Eubacteria at 96% and 99.7% respectively. Proteobacterial phylum constituted 31.46% (AOB) and 39.75% (NOB) and dominated by α-Proteobacteria (20%) in AOB and γ-Proteobacteria (16%) in NOB. Among the species in AOB enrichment (2,948) two sequences were assigned to ammonia oxidising bacterial group belonging to Nitrosomonas, and Nitrosococcus genera and two belonged to archaeon group comprising Nitrosopumilus and candidatus Nitrososphaeraea genera. The NOB enrichment was predominated by Nitrospiraceae and Thermodesulfovibrionaceae. further, the data revealed the presence of heterotrophic bacteria contributing to the process of nitrification and form microcosm with the AOB and NOB. PICRUSt analysis predicted the presence of 24 different nitrogen cycling genes involved in nitrification, denitrification, ammonia and nitrogen transporter family, nitrate reduction and ammonia assimilation. The study confirms the presence of many lesser known nitrifying bacteria along with well characterised nitrifiers. Aquaculture is an important economic activity supplying quality animal protein, generating employment and providing foreign exchange. Fish and fishery products are the most traded food items in the world, and an estimated 45% of the fish produced enters the international market. In terms of value, shrimp/prawn is the second most traded item next only to salmon in the USD 152 billion global seafood market 1. In the modern-day intensive and semi-intensive shrimp aquaculture, management of accumulating metabolic wastes, especially in zero water exchange systems has been a major challenge. Accumulation of nitrogenous wastes generated by animal excreta and degradation of uneaten feed leads to deterioration of culture environment and stress to farmed animals 2-4. Ammonia is the primary end product of protein metabolism in most aquatic animals 5 and is also produced following microbial decomposition of organic wastes. Increase in the levels of nitrogenous species in the shrimp haemolymph leads to reduced food intake, increased oxygen consumption, increased excretion of nitrogen, and altered protein concentrations cause moderate to high mortality 6. Further, the ammonia (>5 ppm) and nitrite
The prevalence of bacterial diseases and the application of probiotics to prevent them is a common practice in shrimp aquaculture. A wide range of bacterial species/strains is utilized in probiotic formulations, with proven beneficial effects. However, knowledge of their role in inhibiting the growth of a specific pathogen is restricted. In this study, we employed constraint-based genome-scale metabolic modeling approach to screen and identify the beneficial bacteria capable of limiting the growth of V. harveyi, a common pathogen in shrimp culture. Genome-scale models were built for 194 species (including strains from the genera Bacillus, Lactobacillus, and Lactococcus and the pathogenic strain V. harveyi) to explore the metabolic potential of these strains under different nutrient conditions in a consortium. In silico-based phenotypic analysis on 193 paired models predicted six candidate strains with growth enhancement and pathogen suppression. Growth simulations reveal that mannitol and glucoronate environments mediate parasitic interactions in a pairwise community. Furthermore, in a mannitol environment, the shortlisted six strains were purely metabolite consumers without donating metabolites to V. harveyi. The production of acetate by the screened species in a paired community suggests the natural metabolic end product’s role in limiting pathogen survival. Our study employing in silico approach successfully predicted three novel candidate strains for probiotic applications, namely, Bacillus sp 1 (identified as B. licheniformis in this study), Bacillus weihaiensis Alg07, and Lactobacillus lindneri TMW 1.1993. The study is the first to apply genomic-scale metabolic models for aquaculture applications to detect bacterial species limiting Vibrio harveyi growth.
Purpose The aquaculture sector is a major contributor to the economic and nutritional security for a number of countries. India’s total seafood exports for the year 2017–2018 accounted for US$ Million 7082. One of the major setbacks in this sector is the frequent outbreaks of diseases often due to bacterial pathogens. Vibriosis is one of the major diseases caused by bacteria of Vibrio spp., causing significant economic loss to the aquaculture sector. The objective of this study was to understand the genetic composition of Vibrio spp. Methods Thirty-five complete genomes were downloaded from GenBank comprising seven vibrio species, namely, Vibrio alginolyticus, V. anguillarum, V. campbellii, V. harveyi, V. furnissii, V. parahaemolyticus, and V. vulnificus. Pan-genome analysis was carried out with coding sequences (CDS) generated from all the Vibrio genomes. In addition, genomes were mined for genes coding for toxin-antitoxin systems, antibiotic resistance, genomic islands, and virulence factors. Results Results revealed an open pan-genome comprising of 2004 core, 8249 accessory, and 6780 unique genes. Downstream analysis of genomes and the identified unique genes resulted in 312 antibiotic resistance genes, 430 genes coding for toxin and antitoxin systems along with 4802, and 4825 putative virulent genes from genomic island regions and unique gene sets, respectively. Conclusion Pan-genome and other downstream analytical procedures followed in this study have the potential to predict strain-specific genes and their association with habitat and pathogenicity.
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