Abdominal aortic aneurysm (AAA) is a life-threatening disease for which no definitive medical therapy has been established, partly because its underlying mechanisms remain incompletely understood. Given accumulating evidence suggesting microbial involvement in vascular inflammation, we conducted a detection-based investigation to identify bacterial DNA in aneurysmal tissues. We performed 16S ribosomal RNA (rRNA) gene sequencing of the aneurysmal wall, intraluminal thrombus, feces, saliva, and dental plaque collected from 32 patients undergoing open surgical repair of non-infectious AAA. Based on the sequencing data, diversity analyses were performed for each sample to characterize bacterial composition, and exploratory statistical analyses were conducted to examine associations between patient characteristics and the relative abundance of bacterial taxa. Oral-associated genera were frequently detected in aneurysm-derived samples, including Prevotella in 78%, Leptotrichia in 81%, and Capnocytophaga in 38% of aneurysmal wall or thrombus samples, whereas their detection in fecal samples was limited. Beta diversity analysis demonstrated significant compositional differences between fecal and oral samples (permutational multivariate analysis of variance [PERMANOVA], p < 0.01). These findings demonstrate the presence of bacterial DNA in aneurysmal tissues and provide descriptive evidence of microbial signatures in AAA.

During spaceflight, astronauts are exposed to extreme conditions such as microgravity, cosmic radiation, and confinement, which can cause a wide range of health problems. To elucidate the molecular mechanisms underlying these issues and to develop intervention strategies for maintaining physiological homeostasis during space missions, space life science research using mouse models is actively conducted on the International Space Station (ISS). However, because of the high cost and technical complexity of spaceflight experiments, it is essential to maximize the scientific value of each mission by ensuring broad accessibility to both data and biospecimens. To this end, we present the integrated biobank for Space Life Science (ibSLS; https://ibsls.megabank.tohoku.ac.jp ), a data-visualization and sample-sharing platform that provides access to transcriptomic and metabolomic datasets generated from Mouse Habitat Unit (MHU) missions conducted by the Japan Aerospace Exploration Agency (JAXA). The platform features a user-friendly interface, tools for cross-mission analysis, and links to human multi-omics databases to support cross-species interpretation. In addition, ibSLS facilitates biospecimen requests to support downstream research. By promoting open access to spaceflight-derived data and biological resources, ibSLS encourages the participation of researchers from diverse fields in space life science.

Defined microbial communities (DMCs; also known as SynComs) offer a promising strategy to enhance plant growth and stress tolerance by harnessing beneficial plant-associated microbes. However, the rational design and efficient exploration of complex DMC configurations remain challenging. Here, we present an interpretable model-guided framework that integrates plant phenotyping, microbial genomics, and machine learning to optimize DMC outcomes and identify microbial interactions relevant to plant performance. Using tomato as a model, we evaluated diverse DMC, temperature, and metabolite combinations in growth experiment and used a quality-controlled dataset comprising 301 plants representing 102 DMC compositions for predictive modeling. An Elastic Net regression model trained on plant biomass data and DMC composition features enabled prediction of unseen DMC outcomes, and incorporating genomic features substantially improved predictive performance, supporting the importance of functional potential in modeling community effects. We applied the model to prioritize and design improved DMCs, which were validated in laboratory assays and field trials. One model-guided DMC significantly enhanced plant growth in the field and improved heat stress tolerance under controlled conditions. Model interpretation and multi-omics analyses highlighted specific microbial interactions, including metabolite-associated relationships involving Sphingobium sp. and tomatine, that were linked to host stress-responsive gene expression. Together, our results demonstrate a scalable framework for predicting and prioritizing DMCs and identify candidate metabolite-associated microbial interactions that may contribute to plant growth promotion and abiotic stress tolerance.

Synthetic microbial communities (SynComs) represent a promising approach to enhance crop growth and stress resilience through microbiome engineering. However, the systematic design and field validation of SynComs remain limited. Here, we present a predictive framework for SynCom optimization, integrating plant phenotyping, microbial genomics, and machine learning. Using tomato as a model, we tested over 800 SynCom–temperature combinations consisting of root endophytic bacteria and rhizosphere metabolites. An Elastic Net regression model trained on plant biomass data accurately predicted the performance of unseen SynComs, with prediction accuracy plateauing at ∼5% (301/6144) of all possible SynCom–temperature combinations. Incorporating genomic features significantly improved model performance, whereas microbiome compositional data alone were not informative. We applied the model to design novel SynComs, which were tested in both laboratory and field conditions using a commercial tomato cultivar. The model-informed SynCom enhanced plant growth in field trials and improved heat stress tolerance under controlled laboratory conditions. Multi-omics analyses and feature importance metrics identified specific microbial taxa, including Sphingobium sp., whose enrichment was linked to host plant metabolite (e.g., tomatine) and stress-responsive gene expression. Our results demonstrate a scalable strategy for the predictive design of beneficial microbiomes to improve resilient crop performance under real-world conditions. ### Competing Interest Statement The authors have declared no competing interest. Japan Science and Technology Agency CREST, JPMJCR15O2, JPMJCR17O2 GteX Program Japan, JPMJGX23B2 RIKEN TRIP Initiative

Introduction Diarrhea-predominant irritable bowel syndrome (IBS-D) is a common disorder of gut-brain interaction. In Japan, IBS-D is treated using Japanese traditional medicine (Kampo medicine); however, its clinical effects and influence on the gut microbiome are unknown. The purpose of this study was 1) to compare the characteristics of IBS-D patients with healthy controls (HCs), and 2) to investigate the effect of Kampo medicine on the symptoms and gut microbiome of patients with IBS-D. Methods We conducted two studies stepwise. First, we compared the clinical characteristics and gut microbiome of the patients with IBS-D to HCs. Second, we conducted a single-arm prospective clinical study to investigate the effectiveness and safety of Kampo treatment for IBS-D and its effects on gut microbiome alterations in patients with IBS-D. Newly diagnosed male patients with IBS-D received a four-week Kampo treatment (hangeshashinto or rikkunshito). Data on overall clinical improvement, scores on quality of life (QOL), gastrointestinal symptoms, diarrhea, anxiety, and depression were obtained. Fecal microbiomes were analyzed at four time points: (1) before treatment with remission; (2) before treatment with exacerbation; (3) after treatment; and (4) four weeks after treatment. Results Study 1: No significant difference was observed in the variety of gut microbiome (alpha diversity) between HCs and IBS-D patients. Study 2: After treatment, 81 % of the patients with IBS-D showed clinical improvement. Compared with the baseline, significant improvement was observed in IBS-related QOL, diarrhea, and trait anxiety scores after treatment and after follow-up, with no adverse effects. Microbiome analysis revealed significantly increased alpha diversity, decreased Blautia abundance, and increased Oscillospira abundance after treatment and 4 weeks after treatment compared with those during the exacerbation period before Kampo treatment. Conclusion Our study shows that no significant difference was observed in gut microbiome diversity between the patients with IBS-D and HCs. After Kampo treatment, abdominal symptoms and anxiety in male IBS-D patients were observed to improve and microbial diversity with specific microbial alterations appeared to be restored. These findings suggest that Kampo medicine could be considered as a potential approach for the symptoms and dysbiosis of IBS-D.

Chronic ethanol consumption significantly increases the risk of colorectal cancer. The pathogenesis of ethanol-related colorectal cancer involves oxidative stress and inflammation induced by ethanol in the colon and rectum, as well as dysfunction of the gut barrier and greater intestinal permeability. Previously, we demonstrated that chronic oral ethanol administration in mice leads to dysbiosis of the fecal microbiota, similar to that which characterizes human inflammatory bowel disease. In addition, this ethanol-induced gut pathophysiology was alleviated by the oral administration of sesaminol, a lignan derived from sesame that is known for its potent antioxidant activity. In the present study, we investigated the effects of oral sesaminol administration on the fecal microbiota and short-chain fatty acid (SCFA) profiles of mice that were chronically orally administered ethanol or not. Chronic ethanol administration reduced the abundances of fecal bacterial taxa that produce butyric acid, thereby reducing the fecal butyric acid content. The oral administration of sesaminol (2.5 mg/d) mitigated the ethanol-induced dysbiosis of the gut microbiota and increased the luminal SCFA content, and particularly that of butyric acid. The effects of oral sesaminol administration on ethanol-induced gut pathophysiology may be mediated, at least in part, by the anti-inflammatory and gut barrier-protective properties of butyric acid.

With the number of samples increasing in many biobanks, one of the most pressing tasks is recording the correct relationships between information and the specimens. Genomic information is useful in determining the identity of these specimens. The Tohoku Medical Megabank Organization is running one of the largest biobanks in Japan. Here, we introduce a management system, which includes the development of a new probe set for the MassARRAY system for use during the production of proliferating T cells (T cells) and lymphoblastoid cell lines (LCLs). We selected single nucleotide variants that could be detected by next-generation sequencing and showed high resolution with ∼0.5 minor allele frequencies. After checking the set of probes against 96 samples from 48 people, we obtained no contradictory results in comparison with our genome sequence information. When we applied the set to our 3035 LCLs and 2256 T cells, the result showed 98.93% consistency with the corresponding genomic information. We surveyed the handling records of the 1.07% of samples that showed inconsistencies, and found that most had resulted from human errors (ID swapping between samples) during manual operations. After improving a few error-prone protocols, the error rate dropped to 0.47% for LCLs and 0% for T cells. Overall, the system that we developed shows high accuracy with easy and fast operability, and provides a good opportunity to improve the validation procedure to facilitate high-quality banking, especially in cases involving genomic information.

Abstract Understanding the physiological changes associated with aging and the associated disease risks is essential to establish biomarkers as indicators of biological aging. This study used the NMR-measured plasma metabolome to calculate age-specific metabolite indices. In doing so, the scope of the study was deliberately simplified to capture general trends and insights into age-related changes in metabolic patterns. In addition, changes in metabolite concentrations with age were examined in detail, with the period from 55–59 to 60–64 years being a period of significant metabolic change, particularly in men, and from 45–49 to 50–54 years in females. These results illustrate the different variations in metabolite concentrations by sex and provide new insights into the relationship between age and metabolic diseases.

The gastrointestinal (GI) tract harbors trillions of microorganisms known to influence human health and disease, and next-generation sequencing (NGS) now enables the in-depth analysis of their diversity and functions. Although a significant amount of research has been conducted on the GI microbiome, comprehensive metagenomic datasets covering the entire tract are scarce due to cost and technical challenges. Despite the widespread use of fecal samples, integrated datasets encompassing the entire digestive process, beginning at the mouth and ending with feces, are lacking. With this study, we aimed to fill this gap by analyzing the complete metagenome of the GI tract, providing insights into the dynamics of the microbiota and potential therapeutic avenues. In this study, we delved into the complex world of the GI microbiota, which we examined in five healthy Japanese subjects. While samples from the whole GI flora and fecal samples provided sufficient bacteria, samples obtained from the stomach and duodenum posed a challenge. Using a principal coordinate analysis (PCoA), clear clustering patterns were identified; these revealed significant diversity in the duodenum. Although this study was limited by its small sample size, the flora in the overall GI tract showed unwavering consistency, while the duodenum exhibited unprecedented phylogenetic diversity. A visual heat map illustrates the discrepancy in abundance, with Fusobacteria and Bacilli dominating the upper GI tract and Clostridia and Bacteroidia dominating the fecal samples. Negativicutes and Actinobacteria were found throughout the digestive tract. This study demonstrates that it is possible to continuously collect microbiome samples throughout the human digestive tract. These findings not only shed light on the complexity of GI microbiota but also provide a basis for future research.

Whole blood transcriptome analysis is a valuable approachin medical research, primarily due to the ease of sample collection and the richness of the information obtained. Since the expression profile of individual genes in the analysis is influenced by medical traits and demographic attributes such as age and gender, there has been a growing demand for a comprehensive database for blood transcriptome analysis. Here, we performed whole blood RNA sequencing (RNA-seq) analysis on 576 participants stratified by age (20-30s and 60-70s) and gender from cohorts of the Tohoku Medical Megabank (TMM). A part of female segment included pregnant women. We did not exclude the globin gene family in our RNA-seq study, which enabled us to identify instances of hereditary persistence of fetal hemoglobin based on the HBG1 and HBG2 expression information. Comparing stratified populations allowed us to identify groups of genes associated with age-related changes and gender differences. We also found that the immune response status, particularly measured by neutrophil-to-lymphocyte ratio (NLR), strongly influences the diversity of individual gene expression profiles in whole blood transcriptome analysis. This stratification has resulted in a data set that will be highly beneficial for future whole blood transcriptome analysis in the Japanese population.

Modern medicine is increasingly focused on personalized medicine, and multi-omics data is crucial in understanding biological phenomena and disease mechanisms. Each ethnic group has its unique genetic background with specific genomic variations influencing disease risk and drug response. Therefore, multi-omics data from specific ethnic populations are essential for the effective implementation of personalized medicine. Various prospective cohort studies, such as the UK Biobank, All of Us and Lifelines, have been conducted worldwide. The Tohoku Medical Megabank project was initiated after the Great East Japan Earthquake in 2011. It collects biological specimens and conducts genome and omics analyses to build a basis for personalized medicine. Summary statistical data from these analyses are available in the jMorp web database (https://jmorp.megabank.tohoku.ac.jp), which provides a multidimensional approach to the diversity of the Japanese population. jMorp was launched in 2015 as a public database for plasma metabolome and proteome analyses and has been continuously updated. The current update will significantly expand the scale of the data (metabolome, genome, transcriptome, and metagenome). In addition, the user interface and backend server implementations were rewritten to improve the connectivity between the items stored in jMorp. This paper provides an overview of the new version of the jMorp.

Abstract Understanding the physiological changes associated with aging and the associated disease risks is essential to establish biomarkers as indicators of biological aging. This study used the NMR-measured plasma metabolome to calculate age-specific metabolite indices. In doing so, the scope of the study was deliberately simplified to capture general trends and insights into age-related changes in metabolic patterns. In addition, changes in metabolite concentrations with age were examined in detail, with the period from 55-59 to 60-64 years being a period of significant metabolic change, particularly in men, and from 45-49 to 50-54 years in females. These results illustrate the different variations in metabolite concentrations by sex and provide new insights into the relationship between age and metabolic diseases.

α-Tomatine is a major saponin that accumulates in tomatoes (Solanum lycopersicum). We previously reported that α-tomatine secreted from tomato roots modulates root-associated bacterial communities, particularly by enriching the abundance of Sphingobium belonging to the family Sphingomonadaceae. To further characterize the α-tomatine-mediated interactions between tomato plants and soil bacterial microbiota, we first cultivated tomato plants in pots containing different microbial inoculants originating from three field soils. Four bacterial genera, namely, Sphingobium, Bradyrhizobium, Cupriavidus, and Rhizobacter, were found to be commonly enriched in tomato root-associated bacterial communities. We constructed a pseudo-rhizosphere system using a mullite ceramic tube as an artificial root to investigate the influence of α-tomatine in modifying bacterial communities. The addition of α-tomatine from the artificial root resulted in the formation of a concentration gradient of α-tomatine that mimicked the tomato rhizosphere, and distinctive bacterial communities were observed in the soil close to the artificial root. Sphingobium was enriched according to the α-tomatine concentration gradient, whereas Bradyrhizobium, Cupriavidus, and Rhizobacter were not enriched in α-tomatine-treated soil. The tomato root-associated bacterial communities were similar to the soil bacterial communities in the vicinity of artificial root-secreting exudates; however, hierarchical cluster analysis revealed a distinction between root-associated and pseudo-rhizosphere bacterial communities. These results suggest that the pseudo-rhizosphere device at least partially creates a rhizosphere environment in which α-tomatine enhances the abundance of Sphingobium in the vicinity of the root. Enrichment of Sphingobium in the tomato rhizosphere was also apparent in publicly available microbiota data, further supporting the tight association between tomato roots and Sphingobium mediated by α-tomatine.

Plant specialized metabolites (PSMs) are often stored as glycosides within cells and released from the roots with some chemical modifications. While isoflavones are known to function as symbiotic signals with rhizobia and to modulate the soybean rhizosphere microbiome, the underlying mechanisms of root-to-soil delivery are poorly understood. In addition to transporter-mediated secretion, the hydrolysis of isoflavone glycosides in the apoplast by an isoflavone conjugate-hydrolyzing β-glucosidase (ICHG) has been proposed but not yet verified. To clarify the role of ICHG in isoflavone supply to the rhizosphere, we have isolated two independent mutants defective in ICHG activity from a soybean high-density mutant library. In the ichg mutants, the isoflavone contents and composition in the root apoplast and root exudate significantly changed. When grown in a field, the lack of ICHG activity considerably reduced isoflavone aglycone contents in roots and the rhizosphere soil, although the transcriptomes showed no distinct differences between the ichg mutants and WTs. Despite the change in isoflavone contents and composition of the root and rhizosphere of the mutants, root and rhizosphere bacterial communities were not distinctive from those of the WTs. Root bacterial communities and nodulation capacities of the ichg mutants did not differ from the WTs under nitrogen-deficient conditions, either. Taken together, these results indicate that ICHG elevates the accumulation of isoflavones in the soybean rhizosphere but is not essential in isoflavone-mediated plant-microbe interactions.

ABSTRACT Plant roots exude various organic compounds, including plant specialized metabolites (PSMs), into the rhizosphere. The secreted PSMs enrich specific microbial taxa to shape the rhizosphere microbiome, which is crucial for the healthy growth of the host plants. PSMs often exhibit biological activities; in turn, some microorganisms possess the capability to either resist or detoxify them. Saponins are structurally diverse triterpene-type PSMs that are mainly produced by angiosperms. They are generally considered as plant defense compounds. We have revealed that α-tomatine, a steroid-type saponin secreted from tomato (Solanum lycopersicum) roots, increases the abundance of Sphingobium bacteria. To elucidate the mechanisms underlying the α-tomatine-mediated enrichment of Sphingobium, we isolated Sphingobium spp. from tomato roots and characterized their saponin-catabolizing abilities. We obtained the whole-genome sequence of Sphingobium sp. RC1, which degrades steroid-type saponins but not oleanane-type ones, and performed a gene cluster analysis together with a transcriptome analysis of α-tomatine degradation. The in vitro characterization of candidate genes identified six enzymes that hydrolyzed the different sugar moieties of steroid-type saponins at different positions. In addition, the enzymes involved in the early steps of the degradation of sapogenins (i.e., aglycones of saponins) were identified, suggesting that orthologs of the known bacterial steroid catabolic enzymes can metabolize sapogenins. Furthermore, a comparative genomic analysis revealed that the saponin-degrading enzymes were present exclusively in certain strains of Sphingobium spp., most of which were isolated from tomato roots or α-tomatine-treated soil. Taken together, these results suggest a catabolic pathway for highly bioactive steroid-type saponins in the rhizosphere. IMPORTANCE Saponins are a group of plant specialized metabolites with various bioactive properties, both for human health and soil microorganisms. Our previous works demonstrated that Sphingobium is enriched in both soils treated with a steroid-type saponin, such as tomatine, and in the tomato rhizosphere. Despite the importance of saponins in plant–microbe interactions in the rhizosphere, the genes involved in the catabolism of saponins and their aglycones (sapogenins) remain largely unknown. Here we identified several enzymes that catalyzed the degradation of steroid-type saponins in a Sphingobium isolate from tomato roots, RC1. A comparative genomic analysis of Sphingobium revealed the limited distribution of genes for saponin degradation in our saponin-degrading isolates and several other isolates, suggesting the possible involvement of the saponin degradation pathway in the root colonization of Sphingobium spp. The genes that participate in the catabolism of sapogenins could be applied to the development of new industrially valuable sapogenin molecules.

Strain C5-48 T , an anaerobic intestinal bacterium that potentially accumulates acetaldehyde at levels exceeding its minimum mutagenic concentration (50 µM) in the colon and rectum, was isolated from the feces of a patient with alcoholism. The 16S rRNA gene sequence of strain C5-48 T showed high similarity to the corresponding sequences of Lachnoclostridium edouardi Marseille-P3397 T (95.7%) and Clostridium fessum SNUG30386 T (94.7%). However, phylogenetic analysis using the sequences of the 16S rRNA, rpoB , and hsp60 genes and whole-genome analysis strongly suggested that C5-48 T should be included in the genus Enterocloster . The novelty of strain C5-48 T was further confirmed by comprehensive average nucleotide identity (ANI) calculations based on its whole-genome sequence, which showed appreciable ANI values with known Enterocloster species ( e.g ., 74.3% and 73.4% with Enterocloster bolteae WAL 16351 T and Enterocloster clostridioformis ATCC 25537 T , respectively). The temperature range for growth of strain C5-48 T was 15–37 °C with an optimum of 37 °C. The pH range for growth was 5.5–10.5 with an optimum of 7.5. The major constituents of the cell membrane lipids of strain C5-48 T were 16:0, 14:0, and 18:1 ω 7 c dimethyl acetal fatty acids. On the basis of the genotypic and phenotypic properties, Enterocloster alcoholdehydrogenati sp. nov. is proposed, with the type strain C5-48 T (= JCM 33305 T = DSM 109474 T ).

Background: Since dementia is preventable with early interventions, biomarkers that assist in diagnosing early stages of dementia, such as mild cognitive impairment (MCI), are urgently needed. Methods: Multiomics analysis of amnestic MCI (aMCI) peripheral blood (n = 25) was performed covering the tran-scriptome, microRNA, proteome, and metabolome. Validation analysis for microRNAs was conducted in an inde-pendent cohort (n = 12). Artificial intelligence was used to identify the most important features for predicting aMCI. Findings: We found that hsa-miR-4455 is the best biomarker in all omics analyses. The diagnostic index tak-ing a ratio of hsa-miR-4455 to hsa-let-7b-3p predicted aMCI patients against healthy subjects with 97% over-all accuracy. An integrated review of multiomics data suggested that a subset of T cells and the GCN (general control nonderepressible) pathway are associated with aMCI. Interpretation: The multiomics approach has enabled aMCI biomarkers with high specificity and illuminated the accompanying changes in peripheral blood. Future large-scale studies are necessary to validate candidate biomarkers for clinical use. (c) 2022 The Author(s). Published by Elsevier Masson SAS. This is an open access article under the CC BY-NC -ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Background In the TSUBAKI study, bardoxolone methyl significantly increased measured and estimated glomerular filtration rates (GFR) in patients with multiple forms of chronic kidney disease (CKD), including Japanese patients with type 2 diabetes and stage 3–4 CKD. Since bardoxolone methyl targets the nuclear factor erythroid 2–related factor 2 pathway, this exploratory analysis of the TSUBAKI study investigated the impact of the regulatory single nucleotide polymorphism, rs6721961, on the effects of bardoxolone methyl. Methods Japanese patients aged 20–79 years with type 2 diabetes and stage 3–4 CKD were randomized to bardoxolone methyl 5–15 mg/day (titrated as tolerated) or placebo for 16 weeks. Genotype frequency, clinical characteristics, renal function, and adverse events were primarily assessed. Results Of 104 patients (bardoxolone methyl n = 55, placebo n = 49); 57% were genotype C/C, 32% C/A and 12% A/A. The frequency of the A/A genotype was higher among patients with diabetic kidney disease than in the general Japanese population (~ 5%). Measured and estimated GFRs increased from baseline in all genotypes receiving bardoxolone methyl. There were no significant differences between genotypes for safety parameters, including blood pressure, bodyweight, and levels of B-type natriuretic peptide, or in the type and frequency of adverse events, suggesting that the efficacy and safety of bardoxolone methyl are unaffected by the rs6721961 polymorphism-617 (C→A) genotype. Conclusions Our approach of combining genome analysis with clinical trials for an investigational drug provides important and useful clues for exploring the efficacy and safety of the drug. Trial registration ClinicalTrials.gov; NCT02316821.

Chronic consumption of excess ethanol is one of the major risk factors for colorectal cancer (CRC), and the pathogenesis of ethanol-related CRC (ER-CRC) involves ethanol-induced oxidative-stress and inflammation in the colon and rectum, as well as gut leakiness. In this study, we hypothesised that oral administration of sesaminol, a sesame lignan, lowers the risk of ER-CRC because we found that it is a strong antioxidant with very low prooxidant activity. This hypothesis was examined using a mouse model, in which 2.0% v/v ethanol was administered ad libitum for 2 weeks with or without oral gavage with sesaminol (2.5 mg per day). Oral sesaminol administration suppressed the ethanol-induced colonic lesions and the ethanol-induced elevation of the colonic levels of oxidative stress markers (8-hydroxy-2'-deoxyguanosine, malondialdehyde, and 4-hydroxyalkenals). It consistently suppressed the chronic ethanol-induced expressions of cytochrome P450-2E1 and inducible nitric oxide synthase and upregulated heme oxygenase-1 expression, probably via the nuclear factor erythroid-derived 2-like 2 pathway in the mouse colon. Oral sesaminol administration also suppressed the chronic ethanol-induced elevation of colonic inflammation marker levels, such as those of tumour necrosis factor-α, interleukin-6, and monocyte chemoattractant protein-1, probably via the nuclear factor-kappa B pathway. Moreover, it prevented the chronic ethanol-induced gut leakiness by restoring tight junction proteins, giving rise to lower plasma endotoxin levels compared with those of ethanol-administered mice. All of these results suggest that dietary supplementation of sesaminol may lower the risk of ER-CRC by suppressing each of the above-mentioned steps in ER-CRC pathogenesis.

Abstract The identification of unknown chemicals has emerged as a significant issue in untargeted metabolome analysis owing to the limited availability of purified standards for identification; this is a major bottleneck for the accumulation of reusable metabolome data in systems biology. Public resources for discovering and prioritizing the unknowns that should be subject to practical identification, as well as further detailed study of spending costs and the risks of misprediction, are lacking. As such a resource, we released databases, Food-, Plant- and Thing-Metabolome Repository (http://metabolites.in/foods, http://metabolites.in/plants, and http://metabolites.in/things, referred to as XMRs) in which the sample-specific localization of unknowns detected by liquid chromatography–mass spectrometry in a wide variety of samples can be examined, helping to discover and prioritize the unknowns. A set of application programming interfaces for the XMRs facilitates the use of metabolome data for large-scale analysis and data mining. Several applications of XMRs, including integrated metabolome and genome analyses, are presented. Expanding the concept of XMRs will accelerate the identification of unknowns and increase the discovery of new knowledge.