Development of a workflow for the selection, identification and optimization of lactic acid bacteria with high γ-aminobutyric acid production

Abstract

Lactic acid bacteria produce γ-aminobutyric acid (GABA) as an acid stress response. GABA is a neurotransmitter that may improve sleep and resilience to mental stress. This study focused on the selection, identification and optimization of a bacterial strain with high GABA production, for development as a probiotic supplement. The scientific literature and an industry database were searched for probiotics and potential GABA producers. In silico screening was conducted to identify genes involved in GABA production. Subsequently, 17 candidates were screened for in vitro GABA production using thin layer chromatography, which identified three candidate probiotic strains Levilactobacillus brevis DSM 20054, Lactococcus lactis DS75843and Bifidobacterium adolescentis DSM 24849 as producing GABA. Two biosensors capable of detecting GABA were developed: 1. a transcription factor-based biosensor characterized by the interaction with the transcriptional regulator GabR was developed in Corynebacterium glutamicum; and 2. a growth factor-based biosensor was built in Escherichia coli, which used auxotrophic complementation by expressing 4-aminobutyrate transaminase (GABA-T) that transfers the GABA amino group to pyruvate, hereby forming alanine. Consequently, the feasibility of developing a workflow based on co-culture with producer strains and a biosensor was tested. The three GABA producers were identified and the biosensors were encapsulated in nanoliter reactors (NLRs) as alginate beads in defined gut-like conditions. The E. coli growth factor-based biosensor was able to detect changes in GABA concentrations in liquid culture and under gut-like conditions. L. brevis and L. lactis were successfully encapsulated in the NLRs and showed growth under miniaturized intestinal conditions.