Abstract
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.
Highlights
Microbes naturally exist as a community with a complex web of interactions that define the microbial community structure
The in silico analysis presented in this study revealed that L. sakei strain benefited from metabolites generated from V. harveyi, exhibiting a parasitic relationship by experiencing growth benefit
The growth improvement effect of mannitol on Lactobacillus reported by Liong and Shah (2005) and limiting effect on V. harveyi observed in our study indicate the role of this sugar alcohol in the parasitic interactions
Summary
Microbes naturally exist as a community with a complex web of interactions that define the microbial community structure. In Silico Prediction of Probiotic Species has provided a potential resource for constructing genome-scale metabolic models (GSM) that serve as a basis to explore metabolic capabilities in microbial communities. Constraintbased modeling is a well-established approach that has been successfully applied for in silico prediction of microbial interactions (Henson et al, 2019; Fang et al, 2020). This approach has been applied from individual to consortium of species with the potential to discern the metabolic capabilities and interactions that operate in a microbial community (Heinken and Thiele, 2015b; Magnúsdóttir et al, 2017). The major Vibrio species affecting shrimp aquaculture include V. parahaemolyticus, V. vulnificus, V. furnissii, V. campbellii, V. harveyi, V. alginolyticus, and V. anguillarum (Saulnier et al, 2000; Kumar et al, 2020), leading to vibriosis
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