Biology subjects

Tsuji, H.

Publications and source records attributed to Tsuji, H..

7 recordsLinked to original sources

bioRxiv2026

TAB1 and ASP1 act antagonistically on cytokinin signaling to regulate axillary meristem formation in rice

Plants continuously develop shoot branches derived from axillary meristems. In rice (Oryza sativa), TILLERS ABSENT1 (TAB1), an ortholog of Arabidopsis WUSCHEL, plays an essential role in axillary meristem formation by promoting stem cell proliferation. Although several genes associated with TAB1 function have been identified, the molecular mechanisms underlying stem cell proliferation during axillary meristem formation remain poorly understood. Here we identify ABERRANT SPIKELET AND PANICLE1 (ASP1), a TOPLESS-like transcriptional corepressor, as a novel regulator of axillary meristem formation, and investigate downstream mechanisms regulated by TAB1 and ASP1. In asp1, the stem cell region was expanded, indicating that ASP1 negatively regulates stem cell proliferation. Notably, WOX4, a paralog of TAB1, was precociously expressed in asp1, possibly in association with expansion of the stem cell region. Genetic analysis further revealed that asp1 mutation rescued the loss of axillary meristems in tab1. Transcriptome analysis showed that several type-A RESPONSE REGULATOR (OsRR) genes, encoding negative regulators of cytokinin signaling, were upregulated in tab1 relative to wild type, asp1, and the tab1 asp1 double mutant. Consistently, fluorescence of the synthetic cytokinin reporter was absent during axillary meristem formation in tab1 but was detected in wild type and tab1 asp1. Moreover, overexpression of OsRR10 inhibited axillary meristem formation, phenocopying tab1. Collectively, these findings suggest that TAB1 activates cytokinin signaling by repressing type-A OsRR expression, whereas ASP1 negatively regulates cytokinin signaling by promoting the expression of these genes. Thus, rescue of the tab1 phenotype by asp1 mutation probably reflects restoration of cytokinin signaling.

plant biology↗

bioRxiv2024

Characterization of a marine bacteria through a novel metabologenomics approach

Exploiting microbial natural products is a key pursuit of the bioactive compound discovery field. Recent advances in modern analytical techniques have increased the volume of microbial genomes and their encoded biosynthetic products measured by mass spectrometry-based metabolomics. However, connecting multi-omics data to uncover metabolic processes of interest is still challenging. This results in a large portion of genes and metabolites remaining unannotated. Further exacerbating the annotation challenge, databases and tools for annotation and omics integration are scattered, requiring complex computations to annotate and integrate omics datasets. Here we performed a two-way integrative analysis combining genomics and metabolomics data to describe a new approach to characterize the marine bacterial isolate BRA006 and to explore its biosynthetic gene cluster (BGC) content as well as the bioactive compounds detected by metabolomics. We described BRA006 genomic content and structure by comparing Illumina and Oxford Nanopore MinION sequencing approaches. Digital DNA:DNA hybridization (dDDH) taxonomically assigned BRA006 as a potential new species of the Micromonospora genus. Starting from LC-ESI(+)-HRMS/MS data, and mapping the annotated enzymes and metabolites belonging to the same pathways, our integrative analysis allowed us to correlate the compound Brevianamide F to a new BGC, previously assigned to other function.

biochemistry↗

bioRxiv2024

Optimizing the detection of biological signals through a semi-automated feature selection tool

Untargeted metabolomics is often used in studies that aim to trace the metabolic profile in a broad context, with the data-dependent acquisition (DDA) mode being the most commonly used method. However, this approach has the limitation that not all detected ions are fragmented in the data acquisition process, in addition to the lack of specificity regarding the process of fragmentation of biological signals. The present work aims to extend the detection of biological signals and contribute to overcoming the fragmentation limits of the DDA mode with a dynamic procedure that combines experimental and in silico approaches. Metabolomic analysis was performed on three different species of actinomycetes using liquid chromatography coupled to mass spectrometry. The data obtained were preprocessed by the MZmine software and processed by the custom package, RegFilter. RegFilter allowed the coverage of the entire chromatographic run and the selection of precursor ions for fragmentation that were previously missed in DDA mode. Most of the ions selected by the tool could be annotated through three levels of annotation, presenting biological relevant candidates. In addition, the tool offers the possibility of creating local spectral libraries curated according to the users interests. Thus, the adoption of a dynamic analysis flow using RegFilter allowed for detection optimization of biological signals, previously absent in the DDA mode. In addition, this workflow enables the creation and search of in-house tailored custom libraries.

bioinformatics↗

bioRxiv2024

Compatibility of time-lapse dry incubator on in vitro production of bovine embryos

Embryo culture is crucial to achieve successful outcomes in assisted reproductive technology (ART) for cattle. This study explored the innovative use of dry incubators integrated with time-lapse monitoring systems for bovine embryo culture, building on their advantages in human medicine, such as reduced contamination risk, stable temperature control, and lower gas consumption. Our research demonstrates the feasibility of this approach, showing that although the osmotic pressure gradually increases over the culture period, it remains below the critical threshold for developmental impairment. Embryos cultured in dry incubators exhibited morphokinetics comparable to those cultured in conventional humidified time-lapse incubators. Furthermore, RNA-seq revealed that the transcriptomic profiles of blastocysts cultured in dry incubators closely matched those of blastocysts cultured in humidified incubators. These findings highlight the significant potential of dry incubators with time-lapse monitoring systems for the in vitro production of bovine embryos, marking a promising advancement in assisted reproductive technologies for the livestock industry and research setting.

developmental biology↗

bioRxiv2023

Simple ways to avoid collecting highly 137Cs-contaminated Aralia elata buds

Collection and cooking of wild vegetables have provided seasonal enjoyments for Japanese local people as provisioning and cultural ecosystem services. However, the Fukushima Daiichi Nuclear Power Plant accident in March 2011 caused extensive radiocesium contamination of wild vegetables. Restrictions on commercial shipments of wild vegetables have been in place for the last 10 years. Some species, including buds of Aralia elata, are currently showing radiocesium concentrations both above and below the Japanese reference level for food (100 Bq/kg), suggesting that there are factors decreasing and increasing the 137Cs concentration. Here, we evaluated easy-to-measure environmental variables (dose rate at the soil surface, organic soil layer thickness, slope steepness, and presence/absence of decontamination practices) and the 137Cs concentrations of 40 A. elata buds at 38 locations in Fukushima Prefecture to provide helpful information on avoiding collecting highly contaminated buds. The 137Cs concentrations in A. elata buds increased significantly with increases in the dose rate at the soil surface. Meanwhile, the 137Cs concentration in A. elata buds were not reduced by decontamination practices. These findings suggest that measuring the latest dose rate at the soil surface at the base of A. elata plants is a helpful way to avoid collecting buds with higher 137Cs concentrations and aid in the management of species in polluted regions.

ecology↗

bioRxiv2021

Liquid-liquid phase separation of florigen activation complex induces flowering

Floral transition, regulated by the systemic action of the mobile florigen protein FLOWERING LOCUS T (FT), is essential for successful plant reproduction1. How FT controls downstream gene expression remains incompletely understood, although it relies on the florigen activation complex (FAC), a core component of FT function2-4. The FAC is a nucleus-localized transcriptional activator of genes encoding MADS-box transcription factors critical to reproductive development and consists of florigen FT; a scaffold 14-3-3 protein that is a key component for complex assembly; and FD, a basic leucine-zipper protein that recruits the FAC to DNA. Here we report that the FAC exhibits phase separation. In rice shoot apical meristem cells, rice florigen Heading date 3a (Hd3a) fused to the green fluorescent protein formed speckles in the nucleus. The FAC speckle is formed in a FAC-dependent manner in tobacco cells. Recombinant Hd3a, but not OsFD1, phase-separated in vitro, and this effect was enhanced in the presence of 14-3-3 protein. Furthermore, mutations affecting functionally important residues in the pocket region or C-terminal disordered region of Hd3a affected FAC phase separation, providing a biochemical framework for the proteins effect on flowering. The ability to form condensates via phase transition represents a previously unknown mechanism for gene activation by the FAC.

plant biology↗

bioRxiv2019

Learning from Synthetic Dataset for Crop Seed Instance Segmentation

Incorporating deep learning in the image analysis pipeline has opened the possibility of introducing precision phenotyping in the field of agriculture. However, to train the neural network, a sufficient amount of training data must be prepared, which requires a time-consuming manual data annotation process that often becomes the limiting step. Here, we show that an instance segmentation neural network (Mask R-CNN) aimed to phenotype the barley seed morphology of various cultivars, can be sufficiently trained purely by a synthetically generated dataset. Our attempt is based on the concept of domain randomization, where a large amount of image is generated by randomly orienting the seed object to a virtual canvas. After training with such a dataset, performance based on recall and the average Precision of the real-world test dataset achieved 96% and 95%, respectively. Applying our pipeline enables extraction of morphological parameters at a large scale, enabling precise characterization of the natural variation of barley from a multivariate perspective. Importantly, we show that our approach is effective not only for barley seeds but also for various crops including rice, lettuce, oat, and wheat, and thus supporting the fact that the performance benefits of this technique is generic. We propose that constructing and utilizing such synthetic data can be a powerful method to alleviate human labor costs needed to prepare the training dataset for deep learning in the agricultural domain.

bioinformatics↗