Biomedical subjects

Takuji Yamada

Publications and source records attributed to Takuji Yamada.

12 recordsLinked to original sources

PubMed2026

Prevalence and chronology of colibactin-associated mutational processes and their microbiome spectra in Japanese colorectal cancer.

The incidence of colorectal cancer (CRC) has risen in recent decades, with a disproportionate increase observed among younger individuals in Japan and other countries. The etiological contribution of the gut microbiota to CRC pathogenesis is recognized, yet the mechanisms involved remain to be fully clarified. Here we integrated whole-genome sequencing (WGS) and transcriptome profiling of CRC with whole-genome metagenomic sequencing of fecal samples to interrogate host-microbiome interactions at high resolution. Application of interpretable artificial intelligence enabled the stratification of CRC into four distinct microbiome-informed subtypes. WGS analysis identified mutational signatures SBS88 and ID18, linked to colibactin exposure, as early clonal events detected in 44.8% of non-hypermutated patients. Notably, these signatures were significantly more frequent among patients born after the 1960s. Microbiome-based subclassification revealed subtype-specific clinical and molecular features. Collectively, our findings indicate that colibactin exposure constitutes a prevalent and potentially modifiable risk factor for CRC in the Japanese population.

Humans↗

PubMed2026

Microbiome Datahub: an open-access platform integrating environmental metadata, taxonomy, and functional annotation for comprehensive metagenome-assembled genome datasets.

BACKGROUND: Metagenome-assembled genomes (MAGs) provide crucial insights into the genomic diversity of uncultured microbes. However, MAG datasets deposited in public repositories such as INSDC are often difficult to reuse due to heterogeneous quality, inconsistent taxonomic and functional annotations, and insufficiently curated environmental metadata. While secondary MAG databases such as MGnify, IMG/M, and SPIRE provide standardized resources, they reconstruct MAGs de novo from public metagenomic reads and therefore do not represent the original MAGs reported in publications. RESULTS: To address this gap, we developed Microbiome Datahub, an open-access platform that systematically aggregates and re-annotates original MAGs from INSDC. We collected 214,427 MAGs, predicted genes by DFAST, performed quality assessment with CheckM, standardized taxonomic assignments with GTDB-Tk, inferred 27 phenotypic traits using Bac2Feature, assigned proteins to MBGD ortholog clusters and KEGG Orthology IDs using PZLAST, and annotated environmental metadata with the Metagenome and Microbes Environmental Ontology. Across these MAGs, the average completeness was 80.5% and contamination 1.8%; notably, the most frequent values were >95% completeness and <1% contamination, indicating that the majority of MAGs are of high quality. Comparative analyses showed that Microbiome Datahub provides phylogenetically and environmentally diverse MAGs: while the majority originated from vertebrate gut environments, a substantial number were also recovered from other habitats such as groundwater, including nearly 10,000 MAGs from the Patescibacteria. Inference of 27 phenotypic traits, including optimum growth temperature, further revealed ecological differentiation across phyla. Protein clustering revealed 56 million identity 40% clusters, with the majority unique compared with MGnify and GlobDB, and ~19% of proteins unassigned to MBGD ortholog clusters, underscoring their novelty. CONCLUSIONS: Microbiome Datahub integrates MAG genome sequences, gene and protein predictions, quality metrics, environmental and taxonomic annotations, ortholog cluster assignments, and phenotype predictions, all accessible via a web interface, API, and bulk downloads. By combining original MAGs with curated metadata and functional annotations, Microbiome Datahub constitutes a comprehensive and reusable resource that will accelerate microbiome and microbial genomics research. Video Abstract.

Metagenome↗

PubMed2025

DeepES: deep learning-based enzyme screening to identify orphan enzyme genes.

MOTIVATION: Progress in sequencing technology has led to determination of large numbers of protein sequences, and large enzyme databases are now available. Although many computational tools for enzyme annotation were developed, sequence information is unavailable for many enzymes, known as orphan enzymes. These orphan enzymes hinder sequence similarity-based functional annotation, leading gaps in understanding the association between sequences and enzymatic reactions. RESULTS: Therefore, we developed DeepES, a deep learning-based tool for enzyme screening to identify orphan enzyme genes, focusing on biosynthetic gene clusters and reaction class. DeepES uses protein sequences as inputs and evaluates whether the input genes contain biosynthetic gene clusters of interest by integrating the outputs of the binary classifier for each reaction class. The validation results suggested that DeepES can capture functional similarity between protein sequences, and it can be implemented to explore orphan enzyme genes. By applying DeepES to 4744 metagenome-assembled genomes, we identified candidate genes for 236 orphan enzymes, including those involved in short-chain fatty acid production as a characteristic pathway in human gut bacteria. AVAILABILITY AND IMPLEMENTATION: DeepES is available at https://github.com/yamada-lab/DeepES. Model weights and the candidate genes are available at Zenodo (https://doi.org/10.5281/zenodo.11123900).

Deep Learning↗

PubMed2006

Extraction of phylogenetic network modules from the metabolic network.

BACKGROUND: In bio-systems, genes, proteins and compounds are related to each other, thus forming complex networks. Although each organism has its individual network, some organisms contain common sub-networks based on function. Given a certain sub-network, the distribution of organisms common to it represents the diversity of its function. RESULTS: We extracted such "common" sub-networks, defined as "phylogenetic network modules," using phylogenetic profiles and cluster analysis. The enzymes in the same "phylogenetic network module" have similar phylogenetic profiles and related functions. These modules are shown to be phylogenetic building blocks. Furthermore, the network of the modules illustrated hierarchical feature as well as the network of enzymes involved in the metabolism. CONCLUSION: We conclude that phylogenetic network modules are evolutionary conserved functional units in the metabolic network. We claim that our concept of phylogenetic modules provides a more accurate understanding of the evolution of biological networks.

Animals↗

PubMed2005

An odorant-binding protein facilitates odorant transfer from air to hydrophilic surroundings in the blowfly.

Chemical sense-related lipophilic ligand-binding protein (CRLBP) is an insect odorant-binding protein (OBP) found abundantly in the taste and olfactory organs of the blowfly, Phormia regina. Through computational construction, a three-dimensional molecular model of a CRLBP indicated good fitting to a fluorescent ligand, 7-hydroxycoumarin (7-HC), in its ligand-binding pocket. By showing that the fluorescence of 7-HC bound to CRLBP migrated in a native electrophoresis gel, we confirmed that CRLBP formed a stable complex with 7-HC. In an odorant-binding experiment, 7-HC vapor odor was introduced by aeration to the aquatic solution containing CRLBP and its binding to CRLBP fluorospectrometrically quantified. Because olfactory organs as well as taste organs of flies respond to vapors, we suggest that CRLBP effectively transfers odorants from the air into aquatic surroundings by forming stable complexes with airborne molecules in both chemosensory organs.

Air↗

PubMed2005

VisANT: data-integrating visual framework for biological networks and modules.

VisANT is a web-based software framework for visualizing and analyzing many types of networks of biological interactions and associations. Networks are a useful computational tool for representing many types of biological data, such as biomolecular interactions, cellular pathways and functional modules. Given user-defined sets of interactions or groupings between genes or proteins, VisANT provides: (i) a visual interface for combining and annotating network data, (ii) supporting function and annotation data for different genomes from the Gene Ontology and KEGG databases and (iii) the statistical and analytical tools needed for extracting topological properties of the user-defined networks. Users can customize, modify, save and share network views with other users, and import basic network data representations from their own data sources, and from standard exchange formats such as PSI-MI and BioPAX. The software framework we employ also supports the development of more sophisticated visualization and analysis functions through its open API for Java-based plug-ins. VisANT is distributed freely via the web at http://visant.bu.edu and can also be downloaded for individual use.

Computer Graphics↗

PubMed2005

Comprehensive analysis and prediction of synthetic lethality using subcellular locations.

The lethality of a gene is a fundamental and representative measure for understanding the function of a gene and its associated bio-systems. Recently, many research groups have started focusing on the concept of synthetic lethality. The synthetic lethality between genes is defined by the combination of mutations in two genes causing cell death. Here, we confirm that synthetic lethality and cellular location have close relationships among the Saccharomyces cerevisiae genes. Furthermore, we attempt the prediction of candidate gene pairs with synthetic lethality. The prediction is based on the hierarchical aspect model (HAM) which learns from a data set of cellular location to estimate a likelihood value indicating the synthetic lethality between genes.

Cell Death↗

PubMed2004

Clustering under the line graph transformation: application to reaction network.

BACKGROUND: Many real networks can be understood as two complementary networks with two kind of nodes. This is the case of metabolic networks where the first network has chemical compounds as nodes and the second one has nodes as reactions. In general, the second network may be related to the first one by a technique called line graph transformation (i.e., edges in an initial network are transformed into nodes). Recently, the main topological properties of the metabolic networks have been properly described by means of a hierarchical model. While the chemical compound network has been classified as hierarchical network, a detailed study of the chemical reaction network had not been carried out. RESULTS: We have applied the line graph transformation to a hierarchical network and the degree-dependent clustering coefficient C(k) is calculated for the transformed network. C(k) indicates the probability that two nearest neighbours of a vertex of degree k are connected to each other. While C(k) follows the scaling law C(k) approximately k(-1.1) for the initial hierarchical network, C(k) scales weakly as k0.08 for the transformed network. This theoretical prediction was compared with the experimental data of chemical reactions from the KEGG database finding a good agreement. CONCLUSIONS: The weak scaling found for the transformed network indicates that the reaction network can be identified as a degree-independent clustering network. By using this result, the hierarchical classification of the reaction network is discussed.

Algorithms↗

PubMed2004

Extraction of phylogenetic network modules from prokayrote metabolic pathways.

In the post-genomic era, it is important to analyze interaction networks that include genes, proteins, enzymes and compounds such as a metabolic pathway. Every organism has such networks individually. However, several parts of them are conserved in different organisms. The purpose of this analysis is to extract sub-networks composed of these common elements through the phylogenetic analysis. We extracted network modules from metabolic pathways using phylogenetic profile and cluster analysis. The enzymes of these modules are related by evolutionary and functional correlation. Our results give a valuable insight into the evolution of metabolic pathways.

Bacteria↗

PubMed2003

Feasibility and effect on blood pressure of 6-week trial of low sodium soy sauce and miso (fermented soybean paste).

A double-blind, randomized placebo-controlled study was conducted to evaluate the feasibility of the long-term use of low-sodium soy sauce and miso in the general Japanese population and its effect on blood pressure (BP). Forty men and 24 women were randomly allocated to a low-sodium group (n=32) or a control group (n=32). Low-sodium soy sauce and miso, which were approximately 25% and 20% lower in salt content than common soy sauce and miso, were used in the study. The change in BP after a 6-week intervention was evaluated. There were no significant differences in age, sex, body mass index, BP or hypertension between the 2 groups before intervention. After the 6-week intervention, no significant change in BP was observed in the entire cohort. However, in those aged 40 years and older, 6.4 mmHg net reduction in diastolic BP with no significant change in systolic BP was noted in the low-sodium group. Taste evaluation for the low-sodium seasoning was considerably good. Replacing soy sauce and miso of the common type with the low-sodium alternative is feasible in the general population and could be the basis for a salt reduction strategy in the Japanese diet.

Adult↗

PubMed2002

Essential role of NF-kappa B-inducing kinase in T cell activation through the TCR/CD3 pathway.

NF-kappa B-inducing kinase (NIK) is involved in lymphoid organogenesis in mice through lymphotoxin-beta receptor signaling. To clarify the roles of NIK in T cell activation through TCR/CD3 and costimulation pathways, we have studied the function of T cells from aly mice, a strain with mutant NIK. NIK mutant T cells showed impaired proliferation and IL-2 production in response to anti-CD3 stimulation, and these effects were caused by impaired NF-kappa B activity in both mature and immature T cells; the impaired NF-kappa B activity in mature T cells was also associated with the failure of maintenance of activated NF-kappa B. In contrast, responses to costimulatory signals were largely retained in aly mice, suggesting that NIK is not uniquely coupled to the costimulatory pathways. When NIK mutant T cells were stimulated in the presence of a protein kinase C (PKC) inhibitor, proliferative responses were abrogated more severely than in control mice, suggesting that both NIK and PKC control T cell activation in a cooperative manner. We also demonstrated that NIK and PKC are involved in distinct NF-kappa B activation pathways downstream of TCR/CD3. These results suggest critical roles for NIK in setting the threshold for T cell activation, and partly account for the immunodeficiency in aly mice.

Animals↗

PubMed2002

[Three patients with advanced nonresectable and recurrent gastric cancer responding to chronomodulation chemotherapy with tegafur + cisplatin + isovorin followed by CPT-11 administration].

Today, no effective chemotherapy regimen has been established for non-resectable or postoperative recurrent gastric cancer, and most such therapy seems to be palliative. Thus, a highly effective chemotherapy that allows good patient QOL is desired. We report three gastric cancer patients responding to chronomodulation chemotherapy (tegafur + cisplatin + Isovorin) based on circadian rhythms plus a new antitumor drug, CPT-11. The treatment protocol was tegafur 1,200 mg/body, days 1-12 (continuing 16 h, intravenously with 800 mg/body from 16 to 24 h, 400 mg/body from 24-8 h, for non-uniform administration), cisplatin 10 mg/body, days 1-5, 8-12, (16 h, one shot infusion), Isovorin 25 mg/body, days 1-5, 8-12 (16 h, one shot infusion), followed by CPT-11 100 mg/body, days 13 (one shot infusion). We performed 1 or 2 courses, and with 2 courses the CPT-11 dose was increased to 150 mg/body. The first patient was a 54-year-old female with advanced type 3 gastric cancer with liver metastasis (H3). After chemotherapy (2 courses), there was a 30% reduction in the advanced gastric cancer and a 95% reduction in the liver metastasis. The second patient was a 73-year-old male with recurrent type 1 gastric cancer in the remnant stomach 24 months after partial gastrectomy. After chemotherapy (1 course), there was a 45% reduction in advanced gastric recurrent cancer. The third patient was a 67-year-old male with advanced type 2 plus 3 gastric cancers with liver (H3) and abdominal lymph node metastases. After chemotherapy (1 course), there was a 70% reduction in the type 2 and 55% reduction in the type 3 advanced gastric cancer, and a 50% reduction in the liver metastasis and 35% reduction in the abdominal lymph node metastasis. The only adverse effect was grade 2 pancytopenia, gastrointestinal disorder, and alopecia. In conclusion, this regimen resulted in good intrachemotherapeutic QOL and was highly effective in advanced gastric cancer patients.

Adenocarcinoma↗