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.

Figure 1

Evaluation of GABA production in supernatants from BHI and MRS cultures. TLC sheets with 1μL supernatants isolated from (a) BHI cultures, and (b) MRS cultures of after 75 h cultivation. 1μL of GABA 10 g/L in distilled water (lane ‘GABA’) represents the positive control, and the negative control is represented by the lane ‘M’, which corresponds to 1μL of culture medium. Strains: (1) B. animalis subsp. lactis BB121, (2) L. rhamnosus GG, (3) L. helveticus R00522, (4) B. coagulans MTCC 5856, (5) L. brevis DSM 20,054, (6) L. lactis CSK-C123, (7) L. lactis DS75843, (8) S. thermophilus ST-105, (9) L. acidophilus LA-5, (10) B. adolescentis DSM 24,849, (11) S. thermophilus 682A, (12) B. longum R01752.

Figure 2

Transcription factor-based sensor design. Panel a: Plasmid maps of the two transcription factor-based sensors. pPPro2 harbors the binding region of GabR (yellow line), the ribosome binding site (red box) and sfGFP gene (green arrow). pPPro3 harbors additionally the GabR gene (yellow arrow). Panel b: Dot plot with the values of green fluorescence normalized by optical density plotted against the different concentration of externally added GABA in the liquid cultures (black line for the C. glutamicum carrying pPPro2, grey line for the strain with pPPro3. Error bars represent the error calculated based on two biological replicates.

Figure 3

Transcription factor-based biosensor in NLRs. Panel a: brightfield microscopy of NLRs harboring the transcription factor-based biosensor. Panel b: Response curve of the transcription factor-based biosensor in NLRs upon addition of different concentrations of GABA. The values plotted represent the mean of the integrated green fluorescence measured with flow cytometry, while the error bars represent the standard deviation of the 2983, 3393, 2962, 2912, 3008 events recorded for each concetration tested (0–3 g/L GABA). Panel c: green fluorescence microscopy pictures of NLRs harboring the transcription factor-based biosensor (average occupation of 200 cells per NLR). The NLRs were incubated for 24 h at 37 C in 2xTY medium supplemented with (1) 0, (2) 0.08, (3) 0.3, (4) 0.8 and (5) 3 g/L GABA.

Figure 4

Growth-based biosensor. Panel a: Schematic drawing of the alanine metabolism in E. coli. Pyruvate can be converted over two pathways with enzymes encoded either by alaA/C or avtA to L-alanine. In the growth-based sensor these genes are knocked out and another gene gabaT is introduced to convert GABA into alanine. Panel b: The plasmid harboring gabaT: the red boxes represent RBS with various binding strength: red, weak binding; pink, strong binding. The blue arrow represents gabaT and the green arrow represents sfGFP. Panel c: Growth curve of the growth-based sensor in presence and absence of 2 mM GABA. The curve represents the mean value of 3 biological replicates.

Figure 5

Improved growth-based sensor in NLRs. Panel a: Brightfield and b: green fluorescence microscopy pictures of NLRs harboring the improved growth-bases biosensor (average occupation of 200 cells/NLR). The NLRs were incubated for 2 days at 37 °C in M9 medium supplemented with (1) 0, (2) 2, (3) 4, (4) 8, (5) 16 and (6) 32 mM GABA. Exposure time for (2–6) was 100 ms and for (1) 1 s. Panel c: Response curve of the growth-based biosensor in NLRs upon addition of different concentrations of GABA. The values plotted represent the mean of the integrated green fluorescence measured with flow cytometry, while the error bars represent the standard deviation of the 1667, 1887, 1024, 993, 1360, 1587 events recorded for each concentration (0–32 mM GABA).

Figure 6

Improved growth-based biosensor in NLRs in screening conditions. Left panels: (a) brightfield and (b) green fluorescence microscopy pictures (exposure time of 50 ms) of NLRs harboring the improved growth-based sensor. The NLRs were incubated for 3 days at 37 C in modified SHIME. The media was supplemented with either (1) 10 mM GABA or (3) 2 mM alanine. (2) represents the sample with SHIME medium only. Panel c: Green fluorescence of the growth-based biosensor in NLRs in SHIME medium with 2 mM alanine, 10 mM GABA or no additional molecule added (i.e. negative control, NC). The mean values of the integrated green fluorescence measured with flow cytometry are respectively: 126, 91 and 10 a.u.. The error bars represent the standard deviation of the 1268, 1245, 1257 events measured for the three samples cultivated with 2 mM Ala, 10 mM GABA and SHIME medium, respectively. The standard deviation values are 33, 73 and 42 a.u. Different letters denote significant differences at p < 0.001.