In Silico Prediction of Novel Probiotic Species Limiting Pathogenic Vibrio Growth Using Constraint-Based Genome Scale Metabolic Modeling

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.

Competition-cooperation in the chemoautotrophic ecosystem of Movile Cave: first metagenomic approach on sediments

“…Microbial communities in the lower, wet and upper dry galleries were analyzed using MAG-based metabolic models (meta-GEM). The community metabolic modeling approach using metaGEM reconstruction and in silico simulation is only recently applied in different fields [70][71][72][73][74]. The community MRO and MIP distribution patterns support the expectation of lower nutrient availability in the dry gallery vs. the wet one.…”

Competition-cooperation in the chemoautotrophic ecosystem of Movile Cave – first metagenomic approach on sediments

“…Microbial communities in the lower, wet and upper, dry galleries were analyzed using MAG-based metabolic models (metaGEM). Community metabolic modeling approach using metaGEM reconstruction and in silico simulation is only recently applied in different fields [70][71][72][73][74]. The community MRO and MIP distribution patterns support the expectation of lower nutrient availability in the dry gallery vs. the wet one.…”

Probiotics as a Beneficial Modulator of Gut Microbiota and Environmental Stress for Sustainable Mass-Reared Ceratitis capitata

“…The advancement of sequencing technologies and related bioinformatic techniques enables the development of predictive models tailored to insect rearing conditions for the rational selection of new probiotics. In this context, the complete genome sequencing data of potential probiotic candidates have enabled the development of new effective approaches that serve as the basis for "in silico" screening of metabolic capability prediction and microbial interactions that operate in a microbial community following probiotic treatment [52,53]. Furthermore, the reproducibility of metagenomics results can enter interpretative variations at many steps of the SIT protocol, including long-term mass-rearing conditions, pupae irradiation, insect diet variability, etc., all of which may map variations in C. capitata intestinal microbiota.…”

“…This approach can be associated to the novel scientific discipline known as "Probiogenomics", which is a combination of "omics" methods using genomics, transcriptomics, metabolomics, and proteomics assays, that has been successfully applied in human health and aquaculture [51][52][53]. The "omics" assays provide indepth details of the molecular features related to physiology, functionality, and mechanisms of action of the microorganism [58].…”