Periodontitis is a chronic inflammatory disease driven by microbial dysbiosis, yet the microbial signatures associated with severity remain incompletely understood. This study investigated changes in subgingival microbial composition across clinically defined severity groups and evaluated the performance of microbiome-based machine-learning models for classifying periodontitis severity. Subgingival plaque samples from 84 patients were analyzed using 16S rRNA gene sequencing. Microbial diversity showed a modest decreasing trend with increasing severity, although differences were not statistically significant. Five machine learning models were applied to classify periodontitis. Random Forest and XGBoost achieved AUC values of 0.98, indicating statistically significant classification performance (p < 0.05) after feature selection. Validation using three external cohorts demonstrated substantial performance variability across populations, reflecting differences in oral microbiome composition, sample type, and periodontal status definitions. Feature importance analysis identified Fusobacterium, Campylobacter, Stomatobaculum, Leptotrichia and Segatella as key contributors to periodontitis severity classification, consistent with their established roles in periodontal dysbiosis. These findings highlight the potential of microbiome-based models for classifying periodontitis severity while underscoring the need to incorporate diverse populations and robust feature-selection strategies to enhance generalizability.

This study was performed to investigate the changes in microbial communities and metabolites during the long-term fermentation of commercially manufactured anchovy sauce. Samples of commercial anchovy sauce were collected from large-scale fermentation tanks with fermentation periods of up to 7.87 years. The complex bacterial community was simplified to two genera, Tetragenococcus and Halanaerobium, after approximately 0.55 years of fermentation. Although genera, such as Saccharomyces, Cladosporium, Candida, and Aspergillus, were relatively dominant, no clear pattern was identified in fungal community analysis. The longitudinal metabolite profile demonstrated that approximately half (55.8%) of the metabolites present in anchovy sauce were produced within a year of fermentation due to rapid fermentation. Despite the static microbial community, the contents of several metabolites including amino acids and biogenic amines changed continuously during the long-term fermentation of anchovy sauce. This study provides novel insights into the changes in microbiota and metabolites in fish sauce produced without any starter inoculation.

This study investigated the impact of Korean rice wine (makgeolli) consumption on human gut microbiota and compared it with that of other alcoholic beverages, including soju (Korean spirit), beer, and red wine. A randomized, cross-over trial design was employed, and fecal samples were collected from 18 healthy adults before and after the consumption of rice wine or control liquor. Microbiota of each fecal sample was analyzed targeting V3-V4 region, utilizing MiSeq system and QIIME2 analysis. Significant alterations in the relative abundance of the Actinobacteria and certain genera were observed after rice wine intervention. Additionally, rice wine consumption induced distinct alterations in the gut microbiota compared with other liquor consumptions. The relative abundance of lactic acid bacteria in the gut microbiota varied among the participants, with an elevated detection frequency of Enterococcus and Lactobacillus genera observed following rice wine consumption. In summary, this study provides the first comprehensive insight into the unique effect of rice wine consumption on the human gut microbiota, distinguishing it from other liquors.

Garlic generally inhibits the growth of microorganisms; however, the mechanism underlying its selective impact on the growth of various kimchi microorganisms is unknown. We investigated the effects of garlic on the microbial community and metabolites in kimchi during fermentation. Difference in color and white colony-forming yeast were found only in kimchi without garlic on the 100th day of fermentation. The microbial community in kimchi without garlic showed a relatively high proportion of Lactobacillus, but a low proportion of Leuconostoc. The levels of homoserine were correlated with the initial quantities of garlic added. Meanwhile, the levels of 11 metabolites, including putrescine and GABA, differed between the groups as the fermentation period progressed. Metabolic differences were confirmed by applying Lactobacillus and Leuconostoc to a kimchi model system. These results show that the garlic addition can produce different metabolites by controlling the ratio of Lactobacillus and Leuconostoc in kimchi.

This study aimed to examine the impacts of essential and optional ingredients on the microbial and metabolic profiles of kimchi during 100 days of fermentation, using a mix-omics approach. Kimchi manufactured without essential ingredients (e.g., red pepper, garlic, ginger, green onion, and radish) had lower lactic acid content. The absence of garlic was associated with a higher proportion of Latilactobacillus and Lactococcus, while the absence of red pepper was associated with a greater proportion of Leuconostoc than the control group. In addition, red pepper and garlic served as primary determinants of the levels of organic acids and biogenic amines. Sugar was positively correlated with the levels of melibiose, and anchovy sauce was positively correlated with the levels of amino acids such as methionine, leucine, and glycine. These findings contribute to a fundamental understanding of how ingredients influence kimchi fermentation, offering valuable insights for optimizing kimchi production to meet various preferences.

AimPeriodontitis is a potential risk factor for preterm birth (PTB) in women; however, the causal relationship or the exact mechanism remain unknown. This study aimed to compare the oral microbiome features of mothers with full-term birth (FTB) with those who had preterm delivery. MethodsThis study prospectively enrolled 60 women (30 mothers with PTB and 30 mothers with FTB), and subgingival plaque samples were collected and analysed by metagenomic 16S rDNA sequencing. Clinical measurements, including periodontal probing depth, clinical attachment level, modified gingival index (mGI) and plaque index, were performed to determine the periodontal state of the participants. Medical and obstetric data were collected as well. ResultsAmong the periodontal measurements, mGI score, reflecting the level of gingival inflammation, exhibited a statistically significant association with PTB (adjusted odds ratio 2.705, 95% confidence interval 1.074-6.811, p = .035). When subgroup analysis was conducted based on mean mGI scores (mGI >= 2, high inflammation [HI] versus mGI < 2, low inflammation [LI]), microbiome analysis revealed clear distinctions in microbial compositions between PTB and FTB mothers in both the HI and LI groups. Especially in the HI group, alpha diversity exhibited a decreasing trend in PTB mothers compared to FTB mothers. Beta diversity also revealed significant differences between the two groups. In Linear Discriminant Analysis Effect Size analysis, certain anaerobic taxa, including the genera Spirochaetes, Treponema and Porphyromonas, were relatively abundant in the FTB/HI group, whereas the PTB/HI group showed a high abundance of the order Actinomycetales. Network analysis showed that the FTB/HI had relatively stronger connectivity in microbial composition than the PTB/HI group. Dysbiosis ratio of plaque microbiome, in terms of periodontitis, was significantly lower in PTB/HI group compared to FTB/HI group. ConclusionThe compositions of maternal subgingival microbiomes differed between PTB and FTB mothers in both the high and low levels of gingival inflammation groups. In the presence of high level of gingival inflammation, dysbiosis in plaque microbiome, in terms of periodontitis, was decreased in PTB mothers compared to FTB mothers.

In fermented foods, including kimchi, salinity is a crucial factor that influences preservation and quality. We aimed to investigate the physicochemical characteristics, microbiota, and metabolites of kimchi fermented at varying salinities over 200 days. Kimchi cabbages were soaked in 3%, 10%, and 20% (w/v) saline solutions for 10 h to prepare low-, middle-, and high-salinity kimchi, respectively. Although the salinity level of kimchi had a significant impact on its appearance, microbial community, and metabolite content in the early stages (until the 5th day), these differences diminished as fermentation progressed. The dominant lactic acid bacteria genera varied based on salinity, with Lactobacillus and Weissella proliferating in high-salinity kimchi, whereas Leuconostoc dominated regardless of salinity. During long-term fermentation, salinity influenced the levels of certain metabolites, including lactic acid, 4-aminobutyric acid, and putrescine. This study provides insights into the role of salt and the effects of salinity on kimchi quality during long-term fermentation.

Age-related gut microbes and urine metabolites were investigated in 568 healthy individuals using metataxonomics and metabolomics. The richness and evenness of the fecal microbiota significantly increased with age, and the abundance of 16 genera differed between the young and old groups. Additionally, 17 urine metabolites contributed to the differences between the young and old groups. Among the microbes that differed by age, Bacteroides and Prevotella 9 were confirmed to be correlated with some urine metabolites. The machine learning algorithm eXtreme gradient boosting (XGBoost) was shown to produce the best performing age predictors, with a mean absolute error of 5.48 years. The accuracy of the model improved to 4.93 years with the inclusion of urine metabolite data. This study shows that the gut microbiota and urine metabolic profiles can be used to predict the age of healthy individuals with relatively good accuracy.

The aim of this study was to investigate the differences in characteristics of the fermented food kimchi based on the regions where it is produced. A total of 108 kimchi samples were collected from five different provinces in Korea to analyze the recipes, metabolites, microbes, and sensory characteristics. Overall, 18 ingredients (including salted anchovy and seaweed), 7 quality indicators (such as salinity and moisture content), 14 genera of microorganisms (mainly Tetragenococcus and Weissella belonging to LAB), and 38 metabolites contributed to the characteristics of kimchi by region. Kimchi from the southern and northern regions showed distinct metabolite profile (collected 108 kimchi) and flavor profile differences (kimchi manufactured using the standard regional recipes). This is the first study to investigate the terroir effect of kimchi by identifying differences in ingredients, metabolites, microbes, and sensory characteristics based on the region of production, and the correlations between these factors.

This study aimed to examine the impacts of essential and optional ingredients on the microbial and metabolic profiles of kimchi during 100 days of fermentation, using a mix-omics approach. Eleven different kimchi groups were fermented using various ingredient compositions, by either excluding essential ingredients or including optional ingredients. The kimchi groups without red pepper or garlic exhibited distinct microbial and metabolic profiles throughout the fermentation period. The groups containing either all ingredients or anchovy sauce displayed similar metabolic profiles with significant differences in amino acid content compared with the control group. A strong correlation between microbes and metabolites was observed in the groups without essential ingredients, whereas a strong correlation was noted between the ingredients and metabolites in the groups with optional ingredients. These findings contribute to fundamental understanding the influence of ingredients on kimchi fermentation and provide valuable insights for kimchi manufacturing targeting for various qualities.

To brew rice wine, a saccharification agent is critical to provide sugars necessary for yeast to ferment alcohol. Nuruk, a traditional Korean saccharification agent, contains saccharification enzymes and various microorganisms, including fungi and lactic acid bacteria (LAB). To investigate the effect of saccharification agents on Korean rice wine (makgeolli), we analyzed makgeolli brewed with different saccharification agents, such as koji and nuruk. In contrast to koji makgeolli, nuruk makgeolli had a distinct microbial profile with higher proportion of LAB. Comparing the microbial profiles of the saccharification agents and makgeolli revealed that the dominant microorganisms in the makgeolli were possibly derived from the saccharification agents. Several metabolites also exhibited distinct profiles depending on the saccharification agent generating the total metabolic profile difference of makgeolli samples. Collectively, the saccharification agent could provide dominant microorganisms in the makgeolli microbiota, leading to a distinct microbial and metabolic profile of makgeolli depending on its type.

Recent studies have confirmed that gut microbiota differs according to race or country in many diseases, including mild cognitive impairment (MCI) and Alzheimer's disease. However, no study has analyzed the characteristics of Korean MCI patients. This study was performed to observe the association between gut microbiota and MCI in the Korean elderly and to identify potential markers for Korean MCI patients. For this purpose, we collected fecal samples from Korean subjects who were divided into an MCI group (n = 40) and control group (n = 40) for 16S rRNA gene amplicon sequencing. Although no significant difference was observed in the overall microbial community profile, the relative abundance of several genera, including Bacteroides, Prevotella, and Akkermansia, showed significant differences between the two groups. In addition, the relative abundance of Prevotella was negatively correlated with that of Bacteroides (r = 0.733). This study may provide Korean-specific basic data for comparing the characteristics of the gut microbiota between Korean and non-Korean MCI patients.

Makgeolli, the traditional Korean rice wine, is generally considered to contain lactic acid bacteria (LAB) despite its bacterial inoculation-free brewing process. The existence of LAB in makgeolli often presents inconsistent trends in microbial profiles and cell numbers. Therefore, to establish LAB-related insights, 94 commercial non-pasteurized products were collected and microbial communities and metabolites were analyzed using 16S rRNA amplicon sequencing and GC-MS, respectively. All samples contained various LAB genera and species, with an average viable cell number of 5.61 log CFU/mL. Overall, 10 LAB genera and 25 LAB species were detected; the most abundant and frequent LAB genus was Lactobacillus. There was no significant change in the LAB composition profile or lactic acid content during low-temperature storage, indicating the presence of LAB did not significantly affect the quality of makgeolli under low-temperature storage conditions. Overall, this study contributes to understand the microbial profile and role of LAB in makgeolli.

Accumulated clinical and biomedical evidence indicates that the gut microbiota and their metabolites affect brain function and behavior in various central nervous system disorders. This study was performed to investigate the changes in brain metabolites and composition of the fecal microbial community following injection of amyloid β (Aβ) and donepezil treatment of Aβ-injected mice using metataxonomics and metabolomics. Aβ treatment caused cognitive dysfunction, while donepezil resulted in the successful recovery of memory impairment. The Aβ + donepezil group showed a significantly higher relative abundance of Verrucomicrobia than the Aβ group. The relative abundance of 12 taxa, including Blautia and Akkermansia, differed significantly between the groups. The Aβ + donepezil group had higher levels of oxalate, glycerol, xylose, and palmitoleate in feces and oxalate, pyroglutamic acid, hypoxanthine, and inosine in brain tissues than the Aβ group. The levels of pyroglutamic acid, glutamic acid, and phenylalanine showed similar changes in vivo and in vitro using HT-22 cells. The major metabolic pathways in the brain tissues and gut microbiota affected by Aβ or donepezil treatment of Aβ-injected mice were related to amino acid pathways and sugar metabolism, respectively. These findings suggest that alterations in the gut microbiota might influence the induction and amelioration of Aβ-induced cognitive dysfunction via the gut–brain axis. This study could provide basic data on the effects of Aβ and donepezil on gut microbiota and metabolites in an Aβ-induced cognitive impairment mouse model.

This study was performed to investigate the succession of various microorganisms naturally present in raw ingredients and the changes in metabolites following long-term fermentation of kimchi. Kimchi was stored at 4 degrees C for 500 days, and the composition of the microbial community and the nature of metabolites were analyzed using metataxonomics and metabolomics. We confirmed that the taxa belonging to Leuconostoc and Weissella were dominant in the early stages of fermentation, while Latilactobacillus and Levilactobacillus were dominant in the middle and late fermentation stages, respectively. In the eukaryotic community, Cladosporium was dominant in the early stages, while Pichia and Hanseniaspora tended to increase in the middle and late fermentation stages. The longitudinal metabolite profile demonstrated that about half (55.7%) of the metabolites present in kimchi after 500 days of fermentation were produced within 15 days of fermentation due to rapid fermentation in the initial stage. These results revealed that even in a closed environment, the viable microbiota in fermented vegetables are not static but dynamic, and the composition of metabolites evolves accordingly during long-term fermentation.

Obesity can be caused by microbes producing metabolites; it is thus important to determine the correlation between gut microbes and metabolites. This study aimed to identify gut microbiota-metabolomic signatures that change with a high-fat diet and understand the underlying mechanisms. To investigate the profiles of the gut microbiota and metabolites that changed after a 60% fat diet for 8 weeks, 16S rRNA gene amplicon sequencing and gas chromatography-mass spectrometry (GC-MS)-based metabolomic analyses were performed. Mice belonging to the HFD group showed a significant decrease in the relative abundance of Bacteroidetes but an increase in the relative abundance of Firmicutes compared to the control group. The relative abundance of Firmicutes, such as Lactococcus, Blautia, Lachnoclostridium, Oscillibacter, Ruminiclostridium, Harryflintia, Lactobacillus, Oscillospira, and Erysipelatoclostridium, was significantly higher in the HFD group than in the control group. The increased relative abundance of Firmicutes in the HFD group was positively correlated with fecal ribose, hypoxanthine, fructose, glycolic acid, ornithine, serum inositol, tyrosine, and glycine. Metabolic pathways affected by a high fat diet on serum were involved in aminoacyl-tRNA biosynthesis, glycine, serine and threonine metabolism, cysteine and methionine metabolism, glyoxylate and dicarboxylate metabolism, and phenylalanine, tyrosine, and trypto-phan biosynthesis. This study provides insight into the dysbiosis of gut microbiota and metabolites altered by HFD and may help to understand the mechanisms underlying obesity mediated by gut microbiota.

Jasmonic acid (JA) and ethylene (ET) signaling modulate plant defense against necrotrophic pathogens. These hormone pathways lead to transcriptional reprogramming, which is a major part of plant immunity and requires the roles of transcription factors. ET response factors are responsible for the transcriptional regulation of JA/ET-responsive defense genes, among which ORA59 functions as a key regulator of this process and has been implicated in the JA-ET crosstalk. Here, we identified the ERELEE4 as an ORA59-binding cis-element, in addition to the well-characterized GCC box, demonstrating that ORA59 regulates JA/ET-responsive genes through direct binding to these elements in the gene promoters. Notably, ORA59 exhibited differential preference for the GCC box and ERELEE4, depending on whether ORA59 activation is achieved by JA and ET, respectively. Our results provide insights into how ORA59 can generate specific patterns of gene expression dynamics through JA and ET hormone pathways.

Halitosis is mainly caused by the action of oral microbes. The purpose of this study was to investigate the differences in salivary microbes and metabolites between subjects with and without halitosis. Of the 52 participants, 22 were classified into the halitosis group by the volatile sulfur compound analysis on breath samples. The 16S rRNA gene amplicon sequencing and metabolomics approaches were used to investigate the difference in microbes and metabolites in saliva of the control and halitosis groups. The profiles of microbiota and metabolites were relatively different between the halitosis and control groups. The relative abundances of Prevotella, Alloprevotella, and Megasphaera were significantly higher in the halitosis group. In contrast, the relative abundances of Streptococcus, Rothia, and Haemophilus were considerably higher in the control group. The levels of 5-aminovaleric acid and n-acetylornithine were significantly higher in the halitosis group. The correlation between identified metabolites and microbiota reveals that Alloprevotella and Prevotella might be related to the cadaverine and putrescine pathways that cause halitosis. This study could provide insight into the mechanisms of halitosis.

Jasmonic acid (JA) and ethylene (ET) signaling modulate plant defense against necrotrophic pathogens in a synergistic and interdependent manner, while JA and ET also have independent roles in certain processes, e.g. in responses to wounding and flooding, respectively. These hormone pathways lead to transcriptional reprogramming, which is a major part of plant immunity and requires the roles of transcription factors. ET response factors are responsible for the transcriptional regulation of JA/ET-responsive defense genes, of which ORA59 functions as a key regulator of this process and has been implicated in the JA-ET crosstalk. We previously demonstrated that Arabidopsis (Arabidopsis thaliana) GDSL LIPASE 1 (GLIP1) depends on ET for gene expression and pathogen resistance. Here, promoter analysis of GLIP1 revealed ERELEE4 as the critical cis-element for ET-responsive GLIP1 expression. In a yeast one-hybrid screening, ORA59 was isolated as a specific transcription factor that binds to the ERELEE4 element, in addition to the well-characterized GCC box. We found that ORA59 regulates JA/ET-responsive genes through direct binding to these elements in gene promoters. Notably, ORA59 exhibited a differential preference for GCC box and ERELEE4, depending on whether ORA59 activation is achieved by JA and ET, respectively. JA and ET induced ORA59 phosphorylation, which was required for both activity and specificity of ORA59. Furthermore, RNA-seq and virus-induced gene silencing analyses led to the identification of ORA59 target genes of distinct functional categories in JA and ET pathways. Our results provide insights into how ORA59 can generate specific patterns of gene expression dynamics through JA and ET hormone pathways.

The purpose of this study is to investigate the effect of fungi on kimchi metabolites during fermentation. A gas chromatography-mass spectrometry (GC-MS) based metabolite profiling approach in combination with principal component analysis (PCA) is performed to differentiate metabolites produced by fungi or bacteria. To avoid bacterial growth, kimchi is treated with 100 μg/mL of ampicillin every three days from 30 to 50 days of fermentation. The relative content of the major fungi at 50 days of fermentation, between the control group and the ampicillin treatment group, was not significantly different. The administration of ampicillin changed the metabolites in kimchi by affecting the growth of kimchi bacteria. Based on the pattern of change of each metabolite, the changed metabolites are grouped into four categories: (1) metabolites produced or consumed by fungi, (2) metabolites involving both fungi and bacteria, (3) metabolites produced or consumed by bacteria, and (4) metabolites of undetermined origin. Alanine, thymine, galacturonic acid, and malonic acid can be regarded as the metabolites produced by fungi between 30 and 50 days of fermentation. In contrast, malic acid, oxaloacetic acid, galactitol, glucose, and mannitol are presumed to be the metabolites mainly consumed by fungi. This study is meaningful as the first study conducted by inhibiting growth of bacteria to identify the metabolites contributed by fungi or bacteria in the kimchi fermentation process. These results could be used to make customized kimchi that controls the production of desired metabolites by selectively controlling the formation of microbial communities in the kimchi industry.