Presentation Title

Computational Approach to Study Probiotics

Presenter Information

Jiayu DaiFollow

Advisor Information

Dhundy Bastola

Location

MBSC Gallery Room 308 - G

Presentation Type

Oral Presentation

Start Date

4-3-2022 12:30 PM

End Date

4-3-2022 1:45 PM

Abstract

Methods to select candidate probiotic strains with specific functions is an important problem of the probiotic industry, which has caught the attention of many researchers. Many of the recent projects studying probiotic functions have conducted experiments in laboratories where expertise in molecular biology and biotechnology is available. However, only handful of them further aggregated these probiotics based on their metabolic abilities/functions. The process of functional characterization of probiotics is currently limiting but is necessary to provide help to consumers. Access to such knowledge will help user recognize what bacteria to choose for certain purposes. Therefore, in this study, computational pipeline was developed to group 159 known probiotics based on their functional abilities defined by associated enzymes and biochemical pathways. Results showed four major groups of bacteria. Finally, a user-friendly interface using Shiny® called ProGut was built, based on probiotic metabolic abilities and grouping results.

This document is currently not available here.

COinS
 
Mar 4th, 12:30 PM Mar 4th, 1:45 PM

Computational Approach to Study Probiotics

MBSC Gallery Room 308 - G

Methods to select candidate probiotic strains with specific functions is an important problem of the probiotic industry, which has caught the attention of many researchers. Many of the recent projects studying probiotic functions have conducted experiments in laboratories where expertise in molecular biology and biotechnology is available. However, only handful of them further aggregated these probiotics based on their metabolic abilities/functions. The process of functional characterization of probiotics is currently limiting but is necessary to provide help to consumers. Access to such knowledge will help user recognize what bacteria to choose for certain purposes. Therefore, in this study, computational pipeline was developed to group 159 known probiotics based on their functional abilities defined by associated enzymes and biochemical pathways. Results showed four major groups of bacteria. Finally, a user-friendly interface using Shiny® called ProGut was built, based on probiotic metabolic abilities and grouping results.