**5. In silico approaches for probiotics selection**

The conventional approaches of validating and selecting new probiotics using *in vitro* and *in vivo* assays are still not yielding robust results. Indeed, the molecular mechanisms through which probiotic microorganisms benefit insect health are, in fact, largely unknown. Thus, in order to fully benefit from probiotics, methodological evolution is required to discover a new potential probiotic. 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. Such data could be combined with bioinformatics tools to modulate microbial composition within insects on a personalized beneficial population basis. Currently, the taxonomic microbiome characterization as well as the relative abundance of each taxonomic level is increasingly being combined with metagenomics sequencing of 16S rRNA V3-V4 hypervariable regions data through various existing NGS platforms sequencing technologies (pyrosequencing (www.454. com); sequencing-by-synthesis (www.illumina.com); sequencing-by-ligation (www.solid.appliedbiosystems.com); semiconductor sequencing (www.lifetechnolog ies.com); and nanoball sequencing (www.genomics.cn)). As a result, the taxonomic classification of metagenomic sequencing data of intestinal microbiota as well as diversity studies after probiotic treatment can reveal the probiotic potential parameters of bacteria candidates such as viability after mass-rearing, persistence or transience post-irradiation, capacity for intestinal colonization in the host, and effect on gut community structure [54]. Moreover, the integration of metagenomic data in various software programs (e.g., Prodigal, PICRUST, etc.) and Web-based bioinformatic pipelines (e.g., MicFunPred, available at: http://micfunpred.microdm. net.in/ [55]; Microbiome Analyst, available at: https://www.microbiomeanalyst.ca [56]; Galaxy/Hutlab, available at: https://huttenhower.sph.harvard.edu/galaxy [57]) can be used as a metagenome genes prediction approach to identify the likely functions of the intestinal microbiota before and after probiotic treatment for interpretive variations. Various functional databases, such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) level 1 to 3, Gene Ontology Resource (GO), Clusters of Orthologous Genes (COG), and Carbohydrate Active Enzymes (CAZY), can be used for the identification and functional analysis of genes related to metabolic pathways. For instance, using NGS and bioinformatics platforms to examine changes in the composition and metabolic processes of medfly intestinal microorganisms after probiotic supplementation in the diet of the larval and adult stages serves as a reference for further studies and application of probiotics for SIT improvement.

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 [51–53]. The "omics" assays provide indepth details of the molecular features related to physiology, functionality, and mechanisms of action of the microorganism [58]. Based on the available whole genome sequence (WGS), "Probiogenomics" approach can be used to gene prediction of probiotic metabolic function [59]. However, there are a number of stressors that the probiotics must deal with during insect mass-rearing, including the composition of the larval and adult diets, irradiation, etc., which can affect their viability and abundance in the insect's digestive system. Consequently, the functional prediction would not be sufficient. Such models can be used not only for discovery and prediction, but also for elucidating the mechanisms of action of potential probiotic microbes on insect health, as well as for accurately identifying probiotics in multistrain mixes and the presence of potential contaminants [60]. Nonetheless, none will replace the need for *in vivo* assessments, which remain the gold standard for probiotic efficacy in the SIT mass-rearing process (**Figure 1**).

*Probiotics as a Beneficial Modulator of Gut Microbiota and Environmental Stress… DOI: http://dx.doi.org/10.5772/intechopen.110126*

#### **Figure 1.**

*Probiotics selection strategy for mass-reared* Ceratitis capitata *for SIT application. Pathway1: Classical approach using "*in vitro*" and "*in vivo*" assays; Pathway2: Integration of potential probiotic strain into SIT procedures; Pathway3: Probiogenomic approach using different "omics" methods and functional prediction; Pathway4: Probiotic selection using metagenomics analysis and functional prediction of genes related to metabolic pathways.*
