Lipoteichoic acid composed of poly-glycerolphosphate containing l-lysine and involved in immunoglobulin A-inducing activity in Apilactobacillus genus.

Lipoteichoic acid (LTA) in the gram-positive bacterial cell wall acts as an immunomodulatory factor in host cells. The chemical structures vary among bacterial species and strains, and may be related to biological activities. In our previous work, much higher immunoglobulin A (IgA)-inducing activity was observed in cells of the Apilactobacillus genus (Apilactobacillus kosoi 10HT, Apilactobacillus apinorum JCM 30765T, and Apilactobacillus kunkeei JCM 16173T) than other lactic acid bacteria, and their LTA was responsible for the activity. In the present study, we elucidated the chemical structures of LTA from these Apilactobacillus strains to explore the structure-function relationship of the IgA-inducing activity. The 1H-nuclear magnetic resonance spectra suggested that their LTA structures were similar. All have a poly-glycerolphosphate main chain, which comprised 12 to 20 average number of the repeating units, with partial substitutions of glucose(α1-, glucosyl(α1-2)glucose(α1- (α-linked-kojibiose), and l-lysine at the C-2 hydroxy group of the glycerol residue. l-Lysine is a substituent never seen before in LTA, and is a probable characteristic of the Apilactobacillus genus. Removal of l-lysine residue from LTA by mild alkaline treatment decreased IgA induction in murine Peyer's patch experiments. The novel l-lysine residue in Apilactobacillus LTA plays a crucial role in the remarkably high IgA-inducing activity.

Optimization of medium components for protein production by Escherichia coli with a high-throughput pipeline that uses a deep neural network.

To optimize rapidly the medium for green fluorescent protein expression by Escherichia coli with an introduced plasmid, pRSET/emGFP, a single-cycle optimization pipeline was applied. The pipeline included a deep neural network (DNN) and mathematical optimization algorithms with simultaneous optimization of 18 medium components. To evaluate the DNN data sampling method, two methods, orthogonal array (OA) and Latin hypercube sampling (LHS), were used to design 64 initial media for each sampling method. The OA- and LHS-based data sampling resulted in green fluorescent protein fluorescence intensities of 0.088 × 103-1.85 × 104 and 3.30 × 103-1.50 × 104, respectively. Fifty DNN models were built using the OA and LHS datasets. Hold-out validation was performed using 15 % test of OA and LHS data. Mean square errors of the DNN models were 0.015-0.64, indicating the estimation accuracies were sufficient. However, the sensitivities of components in the DNN models varied and were grouped into six major classes by the index of k-means clustering. A representative model was selected for each class. Mathematical optimization algorithms using Bayesian optimization and genetic algorithm were applied to the representative models, and representative optimized medium (OM) compositions were selected by k-means clustering from the proposed OMs. A total of 54 OMs were obtained from the OA and LHS datasets. In the validating cultivation, the best OMs of OA and LHS were 2.12-fold and 2.13-fold higher, respectively, than those of the learning data.

Artificial intelligence-assisted analysis reveals amino acid effects and interactions on Limosilactobacillus fermentum growth.

To understand the growth of lactic acid bacteria (LAB), Limosilactobacillus fermentum, in response to medium compositions, a deep neural network (DNN) was designed using amino acids (AAs) as explanatory variables and LAB growth as the objective variable. Sixty-four different patterns of free AAs were set using an orthogonal array. The best DNN model had high accuracy with low mean square errors and predicted that Asp would affect LAB growth. Bayesian optimization (BO) using this model recommended an optimal growth media comprising maximum amounts of Asn, Asp, Lys, Thr, and Tyr and minimum amounts of Gln, Pro, and Ser. Furthermore, this proposed media was empirically validated to promote LAB growth. The absence of Gln, Ser, and Pro indicates that the different growth trends among the DNN-BO-optimized media were likely caused by the interactions among the AAs and the other components.

High throughput optimization of medium composition for Escherichia coli protein expression using deep learning and Bayesian optimization.

To improve synthetic media for protein expression in Escherichia coli, a strategy using deep neural networks (DNN) and Bayesian optimization was performed in this study. To obtain training data for a deep learning algorithm, E. coli harvesting a plasmid pRSET/emGFP, which introduces the green fluorescence protein (GFP), was cultivated in 81 media designed using a Latin square in deepwell-scale cultivation. The media were composed of 31 components with three levels. The resultant GFP fluorescence intensities were evaluated using a fluorescence spectrometer, and the intensities were in the range 2.69-7.99 × 103. A deep neural network model was used to estimate the GFP fluorescence intensities from the culture media compositions, and accuracy was evaluated using cross-validation with 15% test data. Bayesian optimization using the best DNN model was used to calculate 20 representative compositions optimized for GFP expression. According to the validating cultivation, the simulated GFP expression levels included large errors between the estimated and experimental data. The DNN model was retrained using data from the validating cultivation, and secondary estimations were performed. The secondary estimations fit the corresponding experimental data well, and the best GFP fluorescence intensity was 1.4-fold larger than the best of the initial test composition.

Draft Genome Sequence of Lentilactobacillus kosonis NBRC 111893, Isolated from a Japanese Sugar-Vegetable Fermented Beverage called Kôso.

Lentilactobacillus kosonis NBRC 111893 is a species of heterolactic acid bacteria isolated from kôso, a Japanese sugar-vegetable fermented beverage. The draft genome sequence of L. kosonis NBRC 111893 is useful for understanding the features of the genus Lentilactobacillus and its possible uses in fermented foods.

Role of Lipoteichoic Acid from the Genus Apilactobacillus in Inducing a Strong IgA Response.

Lactic acid bacterium-containing fermentates provide beneficial health effects by regulating the immune response. A naturally fermented vegetable beverage, a traditional Japanese food, reportedly provides health benefits; however, the beneficial function of its bacteria has not been clarified. Apilactobacillus kosoi is the predominant lactic acid bacterium in the beverage. Using murine Peyer's patch cells, we compared the immunoglobulin A (IgA)-inducing activity of A. kosoi 10HT to those of 29 other species of lactic acid bacteria and found that species belonging to the genus Apilactobacillus (A. kosoi 10HT, A. apinorum JCM30765T, and A. kunkeei JCM16173T) possessed significantly higher activity than the others. Thereafter, lipoteichoic acids (LTAs), important immunostimulatory molecules of Gram-positive bacteria, were purified from the three Apilactobacillus species, and their IgA-inducing activity was compared to those of LTAs from Lactiplantibacillus plantarum JCM1149T and a probiotic strain, Lacticaseibacillus rhamnosus GG. The results revealed that LTAs from Apilactobacillus species had significantly higher activity than others. We also compared the LTA structure of A. kosoi 10HT with that of L. plantarum JCM1149T and L. rhamnosus GG. Although d-alanine or both d-alanine and carbohydrate residues were substituents of free hydroxyl groups in the polyglycerol phosphate structure in LTAs from strains JCM1149T and GG, d-alanine residues were not found in LTA from strain 10HT by 1H nuclear magnetic resonance (NMR) analysis. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) analysis of the glycolipid structure of LTA revealed that LTA from strain 10HT contained dihexosyl glycerol, whereas trihexosyl glycerol was detected in LTAs from other strains. These structural differences may be related to differences in IgA-inducing activity. IMPORTANCE The components of lactic acid bacteria that exert immunostimulatory effects are of increasing interest for therapeutic and prophylactic options, such as alternatives to antibiotics, cognitive enhancements, and vaccine adjuvants. LTAs act as immunostimulatory molecules in the host innate immune system by interacting with pattern recognition receptors. However, as LTA structures differ among species, detailed knowledge of the structure-function relationship for immunostimulatory effects is required. Comparisons of the IgA-inducing activity of LTAs have demonstrated that LTAs from the genus Apilactobacillus possess distinctive activities to stimulate mucosal immunity. The first analysis of the LTA structure from the genus Apilactobacillus suggests that it differs from structures of LTAs of related species of lactic acid bacteria. This knowledge is expected to aid in the development of functional foods containing lactic acid bacteria and pharmaceutical applications of immunostimulatory molecules from lactic acid bacteria.

Lentilactobacillus kosonis sp. nov., isolated from kôso, a Japanese sugar-vegetable fermented beverage.

A novel lactic acid-producing, Gram-stain-positive, catalase-negative and rod-shaped strain, designated as strain C06_No.73T, was isolated from a traditional Japanese fermented beverage called kôso. According to the results of phylogenetic analysis based on 16S rRNA gene sequences, strain C06_No.73T belongs to the genus Lentilactobacillus. The closest type strain was Lentilactobacillus curieae CCTCC M 2011381T, with a sequence identity of 98.1 %. The identity values with other strains were all below 97 %. The isolate propagated under the conditions of 18-39 °C (optimum, 27 °C for 48 h incubation) and pH 4.0-7.0 (optimum, pH 6.5). The G+C content of its genomic DNA was determined to be 37.9 mol%. The main fatty acids were C16 : 0, C18 : 1 ω7c, C18 : 1 ω9c and C19 : 0 cyclopropane 11,12. The major polar lipid was identified as phosphatidylglycerol. No isoprenoid quinone was detected. The predominant cell-wall amino acids were lysine, alanine, glutamic acid and aspartic acid. Neither meso-diaminopimelic acid nor ornithine were detected. On the basis of this polyphasic taxonomic study, the isolate is concluded to represent a novel species, for which the name Lentilactobacillus kosonis sp. nov. is proposed. The type strain is C06_No.73T (=NBRC 111893T=BCRC 81282T).

Machine learning modeling of the effects of media formulated with various yeast extracts on heterologous protein production in Escherichia coli.

In microbial manufacturing, yeast extract is an important component of the growth media. The production of heterologous proteins often varies because of the yeast extract composition. To identify why this reduces protein production, the effects of yeast extract composition on the growth and green fluorescent protein (GFP) production of engineered Escherichia coli were investigated using a deep neural network (DNN)-mediated metabolomics approach. We observed 205 peaks from the various yeast extracts using gas chromatography-mass spectrometry. Principal component analyses of the peaks identified at least three different clusters. Using 20 different compositions of yeast extract in M9 media, the yields of cells and GFP in the yeast extract-containing media were higher than those in the control without yeast extract by approximately 3.0- to 5.0-fold and 1.5- to 2.0-fold, respectively. We compared machine learning models and found that DNN best fit the data. To estimate the importance of each variable, we performed DNN with a mean increase error calculation based on a permutation algorithm. This method identified the significant components of yeast extract. DNN learning with varying numbers of input variables provided the number of significant components. The influence of specific components on cell growth and GFP production was confirmed with a validation cultivation.

First Determination of Glycidyl Ester Species in Edible Oils by Reverse-Phase Ultra-Performance Liquid Chromatography Coupled with an Evaporative Light-Scattering Detector.

In this work, a new ultra-performance liquid chromatograph-evaporative light-scattering detector (UPLC-ELSD) method for quantitation of glycidyl esters (GE) contents in edible oils is presented. The method features complete separation of five GE species within 20 min by a C18 column and gradient elution with a mobile phase consisting of 85% and 2.5% methanol aqueous solutions. The coefficients of regression (R2) were all ≥0.9999 for the linear-quadratic regression curves of GE species in a concentration range of 5~80 µg/mL. The intraday and interday recoveries (%) of GE species in solvent were in a range of 81.3~107.3%, and the intraday and interday coefficients of variation (CVs, %) were all ≤8.6%. The average recovery (%) of GE species spiked in extra-virgin olive oil samples ranged from 88.3~107.8% and the intermediate precision (CV, %) of ≤14% indicated acceptable accuracy and precision. The method exhibited limit of quantification (LOQ) for each GE species (0.6 µg glycidol equivalents/g oil). The method was applied to determine GE concentrations of six commercial oil samples, and total glycidol equivalents were consistent with data obtained by GC-MS method. This UPLC-ELSD method could be adopted for precursory screening and research purposes to improve food safety when MS detectors are unavailable.

Impacts of Endocrine Disruptor di-n-Butyl Phthalate Ester on Microalga Chlorella vulgaris Verified by Approaches of Proteomics and Gene Ontology.

Di-n-butyl phthalate (DBP) is an extensively used plasticizer. Most investigations on DBP have been concentrated on its environmental distribution and toxicity to humans. However, information on the effects of plasticizers on algal species is scarce. This study verified the impacts of endocrine disruptor di-n-butyl phthalate ester on microalga Chlorella vulgaris by approaches of proteomics and gene ontology. The algal acute biotoxicity results showed that the 24h-EC50 of DBP for C. vulgaris was 4.95 mg L-1, which caused a decrease in the chlorophyll a content and an increase in the DBP concentration of C. vulgaris. Proteomic analysis led to the identification of 1257 C. vulgaris proteins. Sixty-one more proteins showed increased expression, compared to proteins with decreased expression. This result illustrates that exposure to DBP generally enhances protein expression in C. vulgaris. GO annotation showed that both acetolactate synthase (ALS) and GDP-L-fucose synthase 2 (GER2) decreased more than 1.5-fold after exposure to DBP. These effects could inhibit both the valine biosynthetic process and the nucleotide-sugar metabolic process in C. vulgaris. The results of this study demonstrate that DBP could inhibit growth and cause significant changes to the biosynthesis-relevant proteins in C. vulgaris.

Influence of caramel and molasses addition on acrylamide and 5-hydroxylmethylfurfural formation and sensory characteristics of non-centrifugal cane sugar during manufacturing.

BACKGROUND: The aims of this study are to (i) evaluate the effects of color enhancers, caramel (C) and molasses (M), on acrylamide and 5-hydroxylmethylfurfural (HMF) formation in non-centrifugal cane sugar (NCS) and to (ii) perform nine-point hedonic scale and evaluation of sensory attributes, encompassing the appearance, flavor, texture and aftertaste, by 71 consumers on NCS, NCS_C, and NCS products made with a blend of molasses and sugar (NCS_MS) and steam processing (NCS_S). RESULTS: With the addition of molasses and caramel at the maximum allowable level of 5 g kg-1 in sugarcane juice, significantly greater acrylamide or HMF did not accumulate in NCS_C and NCS_M during the thermal manufacturing process, while color values of NCS_C significantly changed (P < 0.05). The increases in acrylamide and HMF contents were influenced by pH because they were produced by the Maillard reaction. Hedonic responses showed that NCS_MS was rated with the highest score for overall acceptance, whereas NCS_S, with the lowest content of acrylamide, exhibited the lowest score for every attribute. In addition, the appearance acceptance score of NCS_C was significantly higher than that of NCS (P < 0.05). Significant differences were also found between NCS and NCS_C in the frequency of 9 of 16 items with which consumers selected to characterize the appearance in a check-all-that-apply questionnaire (P < 0.05). CONCLUSIONS: The association between hedonic evaluations and sensory profiles in visual attributes of NCS_C indicated that caramel could be a promising addition in Maillard reaction-mitigated NCS products to improve consumer preferences through color strengthening without safety concerns. © 2020 Society of Chemical Industry.

Enzyme-assisted Extraction of Bioactive Phytochemicals from Japanese Peppermint (Mentha arvensis L. cv. 'Hokuto').

In this study, we provide a method for obtaining essential oil from Mentha arvensis L. in large quantities. Three types of polysaccharide-degrading enzymes were investigated, namely cellulase A "Amano" 3, cellulase T "Amano" 4, and hemicellulase "Amano" 90. The optimum extraction conditions were the combined use of 2 wt% cellulase T and 2 wt% hemicellulase 90, and 3 h of incubation. Enzymeassisted extraction increased the amount of the essential oil from 2.2 mL to 3.0 mL, compared with the amount extracted without an enzyme.

Conversion and Hydrothermal Decomposition of Major Components of Mint Essential Oil by Small-Scale Subcritical Water Treatment.

Thermal stabilities of four major components (l-menthol, l-menthone, piperitone, and l-menthyl acetate) of Japanese mint essential oil were evaluated via subcritical water treatment. To improve experimental throughput for measuring compound stabilities, a small-scale subcritical water treatment method using ampoule bottles was developed and employed. A mixture of the four major components was treated in subcritical water at 180-240 °C for 5-60 min, and then analyzed by gas chromatography. The results indicated that the order of thermal resistance, from strongest to weakest, was: l-menthyl acetate, l-menthol, piperitone, and l-menthone. In individual treatments of mint flavor components, subsequent conversions of l-menthyl acetate to l-menthol, l-menthol to l-menthone, l-menthone to piperitone, and piperitone to thymol were observed in individual treatments at 240 °C for 60 min. As the mass balance between piperitone and thymol was low, the hydrothermal decomposition of the components was considered to have occurred intensely during, or after the conversion. These results explained the degradation of mint essential oil components under subcritical water conditions and provided the basis for optimizing the extraction conditions of mint essential oils using subcritical water.

Effect of ethanol extract from Lactobacillus plantarum TWK10-fermented soymilk on wound healing in streptozotocin-induced diabetic rat.

Wound healing is a highly dynamic phenomenon comprising numerous coordinated steps including homeostasis/coagulation, inflammation, migration, proliferation, and remodeling. Diabetes mellitus (DM) is a multisystem chronic epidemic that prolongs inflammation in wounds and is associated with impaired healing. This study aimed to investigate the effect of an ethanol extract from Lactobacillus plantarum TWK10 (TWK10)-fermented soymilk on wound healing. The anti-inflammatory effects of the ethanol extract of TWK10-fermented soymilk on lipopolysaccharide-stimulated RAW264.7 macrophage cells were examined. The ethanol extract of TWK10-fermented soymilk (100 µg/mL) significantly decreased nitric oxide production from 11.34 ± 0.74 µM to 8.24 ± 2.02 µM (p < 0.05) and enhanced proliferation in Detroit 551 cells cultured in high-glucose medium; the cell number peaked at 128.44 ± 7.67% (compared to the untreated control) at 600 µg/mL. An ethanol extract of TWK10-fermented soymilk + vaseline-treated rat model of streptozotocin-induced diabetic wounds was generated herein, and the following groups were formed herein: normal control (NC), blank control (BC), low dose group (LD, 0.24 mg/wound), intermediate dose (MD, 0.48 mg/wound), and high dose (HD, 2.40 mg/wound). On day 14 after wound infliction, the wound area in the LD, MD, and HD groups was significantly decreased to 10.2, 8.4, and 8.5% respectively (p < 0.05). Moreover, in the LD, MD, and, HD groups, tumor necrosis factor-α, interleukin 6, and matrix metalloproteinase-9 were downregulated in the wounded skin. These results show that the topical application of the ethanol extract of TWK10-fermented soymilk is beneficial for enhancing wound healing and for the closure of diabetic wounds.

Draft Genome Sequence of Sporolactobacillus inulinus NBRC 111894, Isolated from Kôso, a Japanese Sugar-Vegetable Fermented Beverage.

Sporolactobacillus inulinus NBRC 111894 is a species of endospore-forming lactic acid bacteria isolated from kôso, a Japanese sugar-vegetable fermented beverage. The draft genome sequence of S. inulinus NBRC 111894 is useful for understanding the differences between S. inulinus strains and their conserved characteristics.

Draft Genome Sequence of Lactobacillus kosoi NBRC 113063, Isolated from Kôso, a Japanese Sugar-Vegetable Fermented Beverage.

Lactobacillus kosoi NBRC 113063 is a fructophilic species isolated from kôso, a Japanese sugar-vegetable fermented beverage. The draft genome sequence of Lactobacillus kosoi NBRC 113063 is useful for understanding the carbohydrate metabolism of fructophilic lactic acid bacteria.

Lactobacillus kosoi sp. nov., a fructophilic species isolated from kôso, a Japanese sugar-vegetable fermented beverage.

A novel Gram-positive, fructophilic, catalase negative, and rod-shaped strain, designated strain 10HT was isolated from kôso, a Japanese sugar-vegetable fermented beverage obtained from a food processing factory in Saku City, Nagano Prefecture, Japan. Phylogenetic analysis based on 16S rRNA gene sequences revealed strain 10HT to belong to the genus Lactobacillus, with closely related type strains being Lactobacillus kunkeei YH-15T (95.5% sequence similarity), Lactobacillus ozensis Mizu2-1T (95.4% sequence similarity), and Lactobacillus apinorum Fhon13NT (95.3% sequence similarity). The isolate was found to grow at 18-39 °C (optimum 27 °C), pH 4.0-7.0 (optimum pH 6.5) and in the presence of 0-2% NaCl (optimum 0% NaCl). The G + C content of its genomic DNA was determined to be 30.5 mol%. The major fatty acid (≥ 10%) components identified included C16:0, C19:0 cyclo ω7c, C19:0 cyclo ω9c, and C18:1 ω9c. The polar lipids were identified as lysophosphatidylethanolamine, phosphatidylethanolamine and glycolipids. The predominant isoprenoid quinones (> 10%) were identified as MK-7, MK-8, MK-9 and MK-10. The amino acid composition of the cell wall was detected as comprising Asp, Glu, Ala, and Lys but the strain lacks meso-diaminopimelic acid. As with other fructophilic lactic acid bacteria, such as L. kunkeei and L. apinorum, strain 10HT was found to prefer D-fructose to D-glucose as a growth substrate. On the basis of these genetic and phenotypic results, the isolate is concluded to represent a novel species, for which the name Lactobacillus kosoi is proposed. The type strain is 10HT (= NBRC 113063T = BCRC 81100T).

Phosphorylation of Isoflavones by Bacillus subtilis BCRC 80517 May Represent Xenobiotic Metabolism.

The soy isoflavones daidzein (DAI) and genistein (GEN) have beneficial effects on human health. However, their oral bioavailability is hampered by their low aqueous solubility. Our previous study revealed two water-soluble phosphorylated conjugates of isoflavones, daidzein 7-O-phosphate and genistein 7-O-phosphate, generated via biotransformation by Bacillus subtilis BCRC80517 cultivated with isoflavones. In this study, two novel derivatives of isoflavones, daidzein 4'-O-phosphate and genistein 4'-O-phosphate, were identified by HPLC-ESI-MS/MS and 1H, 13C, and 31P NMR, and their biotransformation roadmaps were proposed. Primarily, isoflavone glucosides were deglycosylated and then phosphorylated predominantly into 7-O-phosphate conjugates with traces of 4'-O-phosphate conjugates. Inevitably, trace quantities of glucosides were converted into 6″-O-succinyl glucosides. GEN was more efficiently phosphorylated than DAI. Nevertheless, the presence of GEN prolonged the time until the exponential phase of cell growth, whereas the other isoflavones showed little effect on cell growth. Our findings provide new insights into the novel microbial phosphorylation of isoflavones involved in xenobiotic metabolism.

Changes in the bacterial community in the fermentation process of kôso, a Japanese sugar-vegetable fermented beverage.

Kôso is a Japanese fermented beverage made with over 20 kinds of vegetables, mushrooms, and sugars. The changes in the bacterial population of kôso during fermentation at 25 °C over a period of 10 days were studied using 454 pyrosequencing of the 16S rRNA gene. The analysis detected 224 operational taxonomic units (OTUs) clustered from 8 DNA samples collected on days 0, 3, 7, and 10 from two fermentation batches. Proteobacteria were the dominant phylum in the starting community, but were replaced by Firmicutes within three days. Seventy-eight genera were identified from the 224 OTUs, in which Bifidobacterium, Leuconostoc, Lactococcus, and Lactobacillus dominated, accounting for over 96% of the total bacterial population after three days' fermentation. UniFrac-Principal Coordinate Analysis of longitudinal fermented samples revealed dramatic changes in the bacterial community in kôso, resulting in significantly low diversity at the end of fermentation as compared with the complex starting community.

Draft Genome Sequence of Lactobacillus farciminis NBRC 111452, Isolated from Kôso, a Japanese Sugar-Vegetable Fermented Beverage.

Here, we report the draft genome sequence of the Lactobacillus farciminis strain NBRC 111452, isolated from kôso, a Japanese sugar-vegetable fermented beverage. This genome information is of potential use in studies of Lactobacillus farciminis as a probiotic.