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Research article
Probiotic Properties and Optimization of Gamma-Aminobutyric Acid Production by Lactiplantibacillus plantarum FBT215
Department of Biological Science and Technology, Yonsei University, Wonju 26493, Republic of Korea
#Current address: National Institute of Infectious Disease, National Institute of Health, Cheong-ju, Republic of Korea
J. Microbiol. Biotechnol. 2022; 32(6): 783-791
Published June 28, 2022 https://doi.org/10.4014/jmb.2204.04029
Copyright © The Korean Society for Microbiology and Biotechnology.
Abstract
Keywords
Graphical Abstract
Introduction
Gamma-aminobutyric acid (GABA) is widespread in nature; it functions as an inhibitory neurotransmitter in the central nervous system [1]. GABA is present in plants, animals, and microorganisms, including bacteria and fungi [2]. Moreover, it influences various physiological responses such as antihypertensive effects, memory improvement, regulation of mood, and sleep induction [3]. Owing to these health benefits, GABA has gained wide attention [4].
GABA is commonly obtained through fermentation using mold, fungi, yeast, and bacteria [5]. Among these, lactic acid bacteria (LAB) have widely been studied as GABA producers not only because of their generally recognized as safe (GRAS) status but also their safety for human consumption the difficulty of human consumption of other microorganisms [6]. GABA-producing LAB are isolated from various fermented foods:
Microbial GABA production is influenced by factors, such as fermentation time, initial pH, glutamate concentration, and medium composition [14]. These factors could be optimized through a one-factor-at-a-time (OFAT) strategy or response surface methodology (RSM) [7, 13]. In the conventional OFAT strategy, only one independent factor is varied while keeping the others constant. Optimization of GABA production by LAB using the conventional OFAT approach is insufficient; it does not consider interactions among the individual factors in a complex system [15-18]. RSM, a statistical method, is a design of experiments (DoE) commonly used to evaluate the effects of different factors [19]. It can be used to predict an optimal condition through a sequence of designed experiments [20]. Therefore, RSM saves experimental resources by reducing the number of experiments for optimization [21].
In this study, GABA-producing
Materials and Methods
Isolation of GABA-Producing Lactic acid Bacteria
Ten varieties of Korean fermented foods were collected from the traditional market in Gangwon-do, Republic of Korea. Each sample was suspended in 0.85% (w/v) NaCl (saline) and spun down to remove the food particles. The supernatant was filtered through a 5 μm filter paper (Toyo Roshi Kaisha, Ltd., Japan). The GABA-producing LAB were screened as described previously [22]. Briefly, the samples were centrifuged at 3,000 ×
GABase Assay
Putative GABA-producing LAB isolates were quantified through a spectrophotometric assay using the GABase enzyme. The isolated sample was centrifuged at 3,000 ×
16S rDNA Sequencing and Identification of Adhesion-Related Gene Sequence
The universal primer set 27F (5’-AGAGTTTGATCMTGGCTCAG-3’) and 1492R (5’-GGTTACCTTGTT ACGACTT-3’) were used to identify the GABA producers [23]. SrtAF (5’-ATGAAGTCCAAGCAACA-3’) and SrtAR (5’- TTAATATTTGTTATTAAAATGACTTG-3’) were used for the amplification of the sortase A (SrtA). The PCR cycling conditions were: initial denaturation at 95°C/5 min, 35 cycles of denaturation at 95°C/30 sec, annealing at 55°C/30 sec, and extension at 72°C/30 sec, and a final extension at 72°C/7 min. DNA sequencing was performed at Macrogen (Republic of Korea). Sequence comparisons were performed using the Basic Local Alignment Search Tool (BLAST) available at the National Center for Biotechnology Information (NCBI; National Institutes of Health, USA). Sequence alignments were performed using BioEdit (Ibis Biosciences, USA).
Acid and Bile Tolerance
HPLC
GABA production was analyzed using HPLC (1260 Infinity series; Agilent Technologies) and a Poroshell120 HPH-C18 (4.6 mm × 150 mm × 4 μm; Agilent technologies). The pre-column
Optimization of GABA Production via OFAT Strategy
The OFAT strategy was used to determine the optimal conditions for GABA production by
Optimization of GABA Production via RSM
The RSM package in R software, version 4.1.2 (The R Foundation, Austria), was used to predict the optimal conditions for GABA production. RSM using the BBD model was performed, as described previously [7], with slight modifications. In brief, carbon concentration, nitrogen concentration, and initial pH were chosen as major factors influencing GABA production. Each factor was transformed into 3 coded levels (-1, 0, and 1). A second-order model was used to fit the data for the Y responses (GABA concentration). The Quadratic equation is as follows:
Sequence Accession Number
The 16S rRNA gene sequence of
Statistical Analysis
Assays were performed in triplicate, and the results were analyzed using IBM SPSS Statistics 25 (IBM Corp., USA). Data are presented as mean ± standard deviation in bar charts. One-way ANOVA and Tukey’s multiple range tests were used to evaluate the significant differences (
Results
Isolation and Identification of GABA-Producing LAB
Potential GABA-producing LAB strains were isolated from 10 varieties of Korean fermented foods. GABA production from the isolates was evaluated using a GABase assay. Ten isolates produced high amounts of GABA (54.37 ± 5.44 μg/ml to 144.02 ± 14.40 μg/ml, Fig. 1); among them, isolate FBT215, which is the highest GABA producer at 144.02 ± 14.40 μg/ml, was selected for further experiments. 16S rRNA gene sequencing identified isolate FBT215 as
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Fig. 1. The amount of GABA produced by LAB isolates cultured in modified-MRS broth supplemented with 50 mM MSG at 37°C for 48 h.
The GABA concentration was quantified using the GABase assay. GABA, gammaaminobutyric acid; LAB, lactic acid bacteria; MSG, monosodium glutamate.
Probiotic Properties: Acid Tolerance, Bile Tolerance, and Identification of an Adhesion-Related Gene
At pH 2.5, the viability of
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Fig. 2. Probiotic properties of
Lactiplantibacillus plantarum FBT215. (A) Acid tolerance ofL. plantarum FBT215 at pH 2.5, 3.0, and 6.0 (control). The cell viability was evaluated every hour for 2 h on an MRS agar plate. (B) Bile tolerance ofL. plantarum FBT215. The cell viability was calculated every 3 h for 6 h on an MRS agar plate. (C) Gel electrophoresis of sortase A coding gene. The amplicon was visualized using 1.2% (w/v) agarose gel. Lane M, molecular mass marker (Thermo Fisher Scientific, SM0311); 1, sortase A amplicon.
Optimization of GABA Production via OFAT Strategy
GABA production was analyzed using the OFAT strategy and HPLC to determine the optimal culture conditions for
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Fig. 3. The concentration of GABA produced by
Lactiplantibacillus plantarum FBT215 in modified-MRS broth. (A) The optimal temperature was determined by evaluating the GABA production at 25°C, 30°C, 37°C, 40°C, and 45°C in MRS broth supplemented with 50 mM MSG. (B) The optimal pH was determined by investigating the GABA production, at different pH conditions (pH 3.5-9.5), at 37°C in MRS broth supplemented with 50 mM MSG (C). The optimal incubation time was investigated for 96 h in MRS broth supplemented with 50 mM MSG at 37°C. (D) The optimum carbon source among nine different carbon sources (glucose, fructose, sucrose, lactose, galactose, xylose, mannose, mannitol, and lactulose) was determined by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (E) The optimal fructose concentration in the range of 1−5% was investigated by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (F) The optimum nitrogen source among seven different nitrogen sources (control, peptone, tryptone, soytone, proteose-peptone No. 3, malt extract, and beef extract) was determined by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (G) The optimal tryptone concentration in the range of 1−5% was determined by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (H) The optimal fructose-containing polymers among three different sources (Fructooligosaccharides, raffinose, and inulin) were determined by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (I) The effect of MSG supplementation was evaluated in the range of 25-250 mM by culturing in MRS broth at 37°C and pH 7.5 for 72 h. (J) The effect of PLP supplementation was evaluated in the range of 0–50 mM by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. MSG, monosodium glutamate; PLP, pyridoxal 5’-phosphate.
The environmental factors were maintained at the optimal levels for the subsequent experiments. Several nutritional factors were assessed to enhance GABA production. Fructose was the best carbon source (553.57 ± 8.65 μg/ml); however, GABA production was enhanced in sucrose-containing broth (387.36 ± 19.85 μg/ml) when compared to that with glucose (286.17 ± 9.00 μg/ml), which represents the commercial MRS broth (Fig. 3D). However, lactose, galactose, xylose, maltose, mannitol, and lactulose did not improve GABA production compared to media with glucose. The optimal fructose concentration was 1% (w/v, 1502.40 ± 21.04 μg/ml, Fig. 3E). Tryptone was the best nitrogen source for GABA production (321.21 ± 11.53 μg/ml, Fig. 3F); peptone, soytone, proteose-peptone No. 3, malt extract, and beef extract did not improve GABA production compared to that in the commercial MRS broth (241.53 ± 7.19 μg/ml). The optimal tryptone concentration was 2% (w/v) and 3% (w/v) (330.17 ± 3.83 μg/ml and 334.41 ± 1.63 μg/ml, respectively, Fig. 3G). GABA production decreased with the addition of inulin and raffinose; however, the addition of fructooligosaccharides (FOS) enhanced GABA production (Fig. 3H).
The influence of MSG and PLP was evaluated in MRS-based broth. GABA production increased depending on MSG concentration (25 mM to 200 mM; 85.26 ± 1.88 μg/ml to 238.43 ± 4.44 μg/ml, respectively, Fig. 3I). The GABA production was maintained at 225 mM MSG; however, it was slightly decreased at 250 mM (236.15 ± 2.12 μg/ml). The addition of PLP influenced the GABA production by
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Table 1 . Box-Behnken design matrix and the predicted GABA concentrations.
Factors Symbol Coded variable levels -1 0 1 Fructose conc. (%, w/v) X 10.5 1 1.5 Tryptone conc. (%, w/v) X 21 3 5 Initial pH X 35.5 7.5 9.5 Run X 1X 2X 3Y (μg/ml)1 0 -1 1 40.13 2 0 1 -1 548.68 3 0 -1 -1 690.12 4 0 1 1 49.41 5 -1 0 1 36.38 6 1 0 -1 565.14 7 -1 0 -1 717.65 8 1 0 1 52.84 9 -1 1 0 162.66 10 1 -1 0 633.74 11 -1 -1 0 100.74 12 1 1 0 320.72 13 0 0 0 2221.16 14 0 0 0 2168.85 15 0 0 0 2251.79
Optimization of GABA Production via RSM
The optimal nutritional factors for GABA production were determined using the OFAT strategy; fructose and tryptone were the best carbon and nitrogen sources, respectively. Subsequently, the initial pH and the two nutritional factors were optimized using the RSM with the BBD model. The three variables were coded to three levels, and GABA production was calculated based on the average of triplicates. Data were analyzed using the quadratic regression model, and the critical variables were identified through backward elimination. As a result, the following equation was used.
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Table 2 . ANOVA for GABA production.
Factors Sum of square Mean square F value Pr(>F) FO( X 1,X 2,X 3)742972 247657 13.601 0.0077 TWI( X 1,X 2,X 3)47962 15987 0.878 0.5117 PQ( X 1,X 2,X 3)8552763 2850921 156.564 2.31E-05 Residuals 91046 18209 Lack of fit 87529 29176 16.588 0.0573 Pure error 3518 1759 Multiple R2: 0.9903 Adjusted R2: 0.9730
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Fig. 4. Three-dimensional response surface plots illustrating the effect of each variable on GABA production by
L. plantarum FBT215. (A) GABA concentration by the interaction between fructose concentration and tryptone concentration. (B) GABA concentration by the interaction between fructose concentration and initial pH. (C) GABA concentration by the interaction between tryptone concentration and initial pH.
Discussion
GABA is a major inhibitory neurotransmitter in the CNS; its beneficial effects are widely recognized. In this study, we investigated the basic probiotic properties of GABA-producing
The survival of probiotic bacteria in the gastrointestinal tract is incumbent on their acid and bile tolerance [24].
The optimal conditions for efficient GABA production by
The OFAT strategy is traditionally employed to optimize the responses of interest. Several studies aimed to optimize the conditions for enhancing GABA production by LAB [15-18]. However, the method has limitations because the interactions of individual factors cannot be considered in a complex system; it can only be evaluated at specific points [33]. Therefore, RSM with the CCD model was assessed for optimizing GABA production in an
In the beginning, GABA was chemically synthesized to meet demands, but this synthesis method was replaced due to the higher yields and lower costs of the biosynthetic process [40]. In this study, optimization of GABA production by
In summary, the basic probiotic properties of the LAB strain
Acknowledgments
This work was supported by a grant from the Commercializations Promotion Agency for R&D Outcomes (COMPA), funded by the Ministry of Science and ICT, Republic of Korea (Project Number: 1711150496).
Conflict of Interest
The authors have no financial conflicts of interest to declare.
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Related articles in JMB
Article
Research article
J. Microbiol. Biotechnol. 2022; 32(6): 783-791
Published online June 28, 2022 https://doi.org/10.4014/jmb.2204.04029
Copyright © The Korean Society for Microbiology and Biotechnology.
Probiotic Properties and Optimization of Gamma-Aminobutyric Acid Production by Lactiplantibacillus plantarum FBT215
Jaegon Kim, Myung-Hyun Lee, Min-Sun Kim, Gyeong-Hwuii Kim#, and Sung-Sik Yoon*
Department of Biological Science and Technology, Yonsei University, Wonju 26493, Republic of Korea
#Current address: National Institute of Infectious Disease, National Institute of Health, Cheong-ju, Republic of Korea
Correspondence to:Sung-Sik Yoon sungsik@yonsei.ac.kr
Abstract
Gamma-aminobutyric acid (GABA) improves various physiological illnesses, including diabetes, hypertension, depression, memory lapse, and insomnia in humans. Therefore, interest in the commercial production of GABA is steadily increasing. Lactic acid bacteria (LAB) have widely been reported as a GABA producer and are safe for human consumption. In this study, GABA-producing LAB were preliminarily identified and quantified via GABase assay. The acid and bile tolerance of the L. plantarum FBT215 strain were evaluated. The one-factor-at-a-time (OFAT) strategy was applied to determine the optimal conditions for GABA production using HPLC. Response surface methodology (RSM) with Box-Behnken design was used to predict the optimum GABA production. The strain FBT215 was shown to be acid and bile tolerant. The optimization of GABA production via the OFAT strategy resulted in an average GABA concentration of 1688.65 ± 14.29 μg/ml, while it was 1812.16 ± 23.16 μg/ml when RSM was applied. In conclusion, this study provides the optimum culture conditions for GABA production by the strain FBT215 and indicates that L. plantarum FBT215 is potentially promising for commercial functional probiotics with health claims.
Keywords: Gamma-aminobutyric acid, Lactiplantibacillus plantarum, probiotic properties, optimization, one-factor-at-a-time strategy, response surface methodology
Introduction
Gamma-aminobutyric acid (GABA) is widespread in nature; it functions as an inhibitory neurotransmitter in the central nervous system [1]. GABA is present in plants, animals, and microorganisms, including bacteria and fungi [2]. Moreover, it influences various physiological responses such as antihypertensive effects, memory improvement, regulation of mood, and sleep induction [3]. Owing to these health benefits, GABA has gained wide attention [4].
GABA is commonly obtained through fermentation using mold, fungi, yeast, and bacteria [5]. Among these, lactic acid bacteria (LAB) have widely been studied as GABA producers not only because of their generally recognized as safe (GRAS) status but also their safety for human consumption the difficulty of human consumption of other microorganisms [6]. GABA-producing LAB are isolated from various fermented foods:
Microbial GABA production is influenced by factors, such as fermentation time, initial pH, glutamate concentration, and medium composition [14]. These factors could be optimized through a one-factor-at-a-time (OFAT) strategy or response surface methodology (RSM) [7, 13]. In the conventional OFAT strategy, only one independent factor is varied while keeping the others constant. Optimization of GABA production by LAB using the conventional OFAT approach is insufficient; it does not consider interactions among the individual factors in a complex system [15-18]. RSM, a statistical method, is a design of experiments (DoE) commonly used to evaluate the effects of different factors [19]. It can be used to predict an optimal condition through a sequence of designed experiments [20]. Therefore, RSM saves experimental resources by reducing the number of experiments for optimization [21].
In this study, GABA-producing
Materials and Methods
Isolation of GABA-Producing Lactic acid Bacteria
Ten varieties of Korean fermented foods were collected from the traditional market in Gangwon-do, Republic of Korea. Each sample was suspended in 0.85% (w/v) NaCl (saline) and spun down to remove the food particles. The supernatant was filtered through a 5 μm filter paper (Toyo Roshi Kaisha, Ltd., Japan). The GABA-producing LAB were screened as described previously [22]. Briefly, the samples were centrifuged at 3,000 ×
GABase Assay
Putative GABA-producing LAB isolates were quantified through a spectrophotometric assay using the GABase enzyme. The isolated sample was centrifuged at 3,000 ×
16S rDNA Sequencing and Identification of Adhesion-Related Gene Sequence
The universal primer set 27F (5’-AGAGTTTGATCMTGGCTCAG-3’) and 1492R (5’-GGTTACCTTGTT ACGACTT-3’) were used to identify the GABA producers [23]. SrtAF (5’-ATGAAGTCCAAGCAACA-3’) and SrtAR (5’- TTAATATTTGTTATTAAAATGACTTG-3’) were used for the amplification of the sortase A (SrtA). The PCR cycling conditions were: initial denaturation at 95°C/5 min, 35 cycles of denaturation at 95°C/30 sec, annealing at 55°C/30 sec, and extension at 72°C/30 sec, and a final extension at 72°C/7 min. DNA sequencing was performed at Macrogen (Republic of Korea). Sequence comparisons were performed using the Basic Local Alignment Search Tool (BLAST) available at the National Center for Biotechnology Information (NCBI; National Institutes of Health, USA). Sequence alignments were performed using BioEdit (Ibis Biosciences, USA).
Acid and Bile Tolerance
HPLC
GABA production was analyzed using HPLC (1260 Infinity series; Agilent Technologies) and a Poroshell120 HPH-C18 (4.6 mm × 150 mm × 4 μm; Agilent technologies). The pre-column
Optimization of GABA Production via OFAT Strategy
The OFAT strategy was used to determine the optimal conditions for GABA production by
Optimization of GABA Production via RSM
The RSM package in R software, version 4.1.2 (The R Foundation, Austria), was used to predict the optimal conditions for GABA production. RSM using the BBD model was performed, as described previously [7], with slight modifications. In brief, carbon concentration, nitrogen concentration, and initial pH were chosen as major factors influencing GABA production. Each factor was transformed into 3 coded levels (-1, 0, and 1). A second-order model was used to fit the data for the Y responses (GABA concentration). The Quadratic equation is as follows:
Sequence Accession Number
The 16S rRNA gene sequence of
Statistical Analysis
Assays were performed in triplicate, and the results were analyzed using IBM SPSS Statistics 25 (IBM Corp., USA). Data are presented as mean ± standard deviation in bar charts. One-way ANOVA and Tukey’s multiple range tests were used to evaluate the significant differences (
Results
Isolation and Identification of GABA-Producing LAB
Potential GABA-producing LAB strains were isolated from 10 varieties of Korean fermented foods. GABA production from the isolates was evaluated using a GABase assay. Ten isolates produced high amounts of GABA (54.37 ± 5.44 μg/ml to 144.02 ± 14.40 μg/ml, Fig. 1); among them, isolate FBT215, which is the highest GABA producer at 144.02 ± 14.40 μg/ml, was selected for further experiments. 16S rRNA gene sequencing identified isolate FBT215 as
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Figure 1. The amount of GABA produced by LAB isolates cultured in modified-MRS broth supplemented with 50 mM MSG at 37°C for 48 h.
The GABA concentration was quantified using the GABase assay. GABA, gammaaminobutyric acid; LAB, lactic acid bacteria; MSG, monosodium glutamate.
Probiotic Properties: Acid Tolerance, Bile Tolerance, and Identification of an Adhesion-Related Gene
At pH 2.5, the viability of
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Figure 2. Probiotic properties of
Lactiplantibacillus plantarum FBT215. (A) Acid tolerance ofL. plantarum FBT215 at pH 2.5, 3.0, and 6.0 (control). The cell viability was evaluated every hour for 2 h on an MRS agar plate. (B) Bile tolerance ofL. plantarum FBT215. The cell viability was calculated every 3 h for 6 h on an MRS agar plate. (C) Gel electrophoresis of sortase A coding gene. The amplicon was visualized using 1.2% (w/v) agarose gel. Lane M, molecular mass marker (Thermo Fisher Scientific, SM0311); 1, sortase A amplicon.
Optimization of GABA Production via OFAT Strategy
GABA production was analyzed using the OFAT strategy and HPLC to determine the optimal culture conditions for
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Figure 3. The concentration of GABA produced by
Lactiplantibacillus plantarum FBT215 in modified-MRS broth. (A) The optimal temperature was determined by evaluating the GABA production at 25°C, 30°C, 37°C, 40°C, and 45°C in MRS broth supplemented with 50 mM MSG. (B) The optimal pH was determined by investigating the GABA production, at different pH conditions (pH 3.5-9.5), at 37°C in MRS broth supplemented with 50 mM MSG (C). The optimal incubation time was investigated for 96 h in MRS broth supplemented with 50 mM MSG at 37°C. (D) The optimum carbon source among nine different carbon sources (glucose, fructose, sucrose, lactose, galactose, xylose, mannose, mannitol, and lactulose) was determined by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (E) The optimal fructose concentration in the range of 1−5% was investigated by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (F) The optimum nitrogen source among seven different nitrogen sources (control, peptone, tryptone, soytone, proteose-peptone No. 3, malt extract, and beef extract) was determined by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (G) The optimal tryptone concentration in the range of 1−5% was determined by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (H) The optimal fructose-containing polymers among three different sources (Fructooligosaccharides, raffinose, and inulin) were determined by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. (I) The effect of MSG supplementation was evaluated in the range of 25-250 mM by culturing in MRS broth at 37°C and pH 7.5 for 72 h. (J) The effect of PLP supplementation was evaluated in the range of 0–50 mM by culturing in MRS broth supplemented with 50 mM MSG, at 37°C and pH 7.5, for 72 h. MSG, monosodium glutamate; PLP, pyridoxal 5’-phosphate.
The environmental factors were maintained at the optimal levels for the subsequent experiments. Several nutritional factors were assessed to enhance GABA production. Fructose was the best carbon source (553.57 ± 8.65 μg/ml); however, GABA production was enhanced in sucrose-containing broth (387.36 ± 19.85 μg/ml) when compared to that with glucose (286.17 ± 9.00 μg/ml), which represents the commercial MRS broth (Fig. 3D). However, lactose, galactose, xylose, maltose, mannitol, and lactulose did not improve GABA production compared to media with glucose. The optimal fructose concentration was 1% (w/v, 1502.40 ± 21.04 μg/ml, Fig. 3E). Tryptone was the best nitrogen source for GABA production (321.21 ± 11.53 μg/ml, Fig. 3F); peptone, soytone, proteose-peptone No. 3, malt extract, and beef extract did not improve GABA production compared to that in the commercial MRS broth (241.53 ± 7.19 μg/ml). The optimal tryptone concentration was 2% (w/v) and 3% (w/v) (330.17 ± 3.83 μg/ml and 334.41 ± 1.63 μg/ml, respectively, Fig. 3G). GABA production decreased with the addition of inulin and raffinose; however, the addition of fructooligosaccharides (FOS) enhanced GABA production (Fig. 3H).
The influence of MSG and PLP was evaluated in MRS-based broth. GABA production increased depending on MSG concentration (25 mM to 200 mM; 85.26 ± 1.88 μg/ml to 238.43 ± 4.44 μg/ml, respectively, Fig. 3I). The GABA production was maintained at 225 mM MSG; however, it was slightly decreased at 250 mM (236.15 ± 2.12 μg/ml). The addition of PLP influenced the GABA production by
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Table 1 . Box-Behnken design matrix and the predicted GABA concentrations..
Factors Symbol Coded variable levels -1 0 1 Fructose conc. (%, w/v) X 10.5 1 1.5 Tryptone conc. (%, w/v) X 21 3 5 Initial pH X 35.5 7.5 9.5 Run X 1X 2X 3Y (μg/ml)1 0 -1 1 40.13 2 0 1 -1 548.68 3 0 -1 -1 690.12 4 0 1 1 49.41 5 -1 0 1 36.38 6 1 0 -1 565.14 7 -1 0 -1 717.65 8 1 0 1 52.84 9 -1 1 0 162.66 10 1 -1 0 633.74 11 -1 -1 0 100.74 12 1 1 0 320.72 13 0 0 0 2221.16 14 0 0 0 2168.85 15 0 0 0 2251.79
Optimization of GABA Production via RSM
The optimal nutritional factors for GABA production were determined using the OFAT strategy; fructose and tryptone were the best carbon and nitrogen sources, respectively. Subsequently, the initial pH and the two nutritional factors were optimized using the RSM with the BBD model. The three variables were coded to three levels, and GABA production was calculated based on the average of triplicates. Data were analyzed using the quadratic regression model, and the critical variables were identified through backward elimination. As a result, the following equation was used.
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Table 2 . ANOVA for GABA production..
Factors Sum of square Mean square F value Pr(>F) FO( X 1,X 2,X 3)742972 247657 13.601 0.0077 TWI( X 1,X 2,X 3)47962 15987 0.878 0.5117 PQ( X 1,X 2,X 3)8552763 2850921 156.564 2.31E-05 Residuals 91046 18209 Lack of fit 87529 29176 16.588 0.0573 Pure error 3518 1759 Multiple R2: 0.9903 Adjusted R2: 0.9730
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Figure 4. Three-dimensional response surface plots illustrating the effect of each variable on GABA production by
L. plantarum FBT215. (A) GABA concentration by the interaction between fructose concentration and tryptone concentration. (B) GABA concentration by the interaction between fructose concentration and initial pH. (C) GABA concentration by the interaction between tryptone concentration and initial pH.
Discussion
GABA is a major inhibitory neurotransmitter in the CNS; its beneficial effects are widely recognized. In this study, we investigated the basic probiotic properties of GABA-producing
The survival of probiotic bacteria in the gastrointestinal tract is incumbent on their acid and bile tolerance [24].
The optimal conditions for efficient GABA production by
The OFAT strategy is traditionally employed to optimize the responses of interest. Several studies aimed to optimize the conditions for enhancing GABA production by LAB [15-18]. However, the method has limitations because the interactions of individual factors cannot be considered in a complex system; it can only be evaluated at specific points [33]. Therefore, RSM with the CCD model was assessed for optimizing GABA production in an
In the beginning, GABA was chemically synthesized to meet demands, but this synthesis method was replaced due to the higher yields and lower costs of the biosynthetic process [40]. In this study, optimization of GABA production by
In summary, the basic probiotic properties of the LAB strain
Acknowledgments
This work was supported by a grant from the Commercializations Promotion Agency for R&D Outcomes (COMPA), funded by the Ministry of Science and ICT, Republic of Korea (Project Number: 1711150496).
Conflict of Interest
The authors have no financial conflicts of interest to declare.
Fig 1.
Fig 2.
Fig 3.
Fig 4.
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Table 1 . Box-Behnken design matrix and the predicted GABA concentrations..
Factors Symbol Coded variable levels -1 0 1 Fructose conc. (%, w/v) X 10.5 1 1.5 Tryptone conc. (%, w/v) X 21 3 5 Initial pH X 35.5 7.5 9.5 Run X 1X 2X 3Y (μg/ml)1 0 -1 1 40.13 2 0 1 -1 548.68 3 0 -1 -1 690.12 4 0 1 1 49.41 5 -1 0 1 36.38 6 1 0 -1 565.14 7 -1 0 -1 717.65 8 1 0 1 52.84 9 -1 1 0 162.66 10 1 -1 0 633.74 11 -1 -1 0 100.74 12 1 1 0 320.72 13 0 0 0 2221.16 14 0 0 0 2168.85 15 0 0 0 2251.79
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Table 2 . ANOVA for GABA production..
Factors Sum of square Mean square F value Pr(>F) FO( X 1,X 2,X 3)742972 247657 13.601 0.0077 TWI( X 1,X 2,X 3)47962 15987 0.878 0.5117 PQ( X 1,X 2,X 3)8552763 2850921 156.564 2.31E-05 Residuals 91046 18209 Lack of fit 87529 29176 16.588 0.0573 Pure error 3518 1759 Multiple R2: 0.9903 Adjusted R2: 0.9730
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