Biology subjects

Hori, H.

Publications and source records attributed to Hori, H..

6 recordsLinked to original sources

bioRxiv2026

Dual-site specificity of the archaeal tRNA m2G methyltransferase Trm14

N2-methylguanosine (m2G) is widely found at multiple positions in tRNAs across the three domains of life. Tryptophan tRNA from Thermococcus kodakarensis contains m2G at position 67. We previously proposed that the tRNA m2G methyltransferase Trm14 is responsible for m2G67 formation in tRNATrp from T. kodakarensis, although Trm14 was originally identified as the enzyme catalyzing m2G6 formation in tRNACys in Methanocaldococcus jannaschii. Thus, it remained unclear whether Trm14 could also methylate G67. Here, we characterized archaeal Trm14. Biochemical analyses using recombinant T. kodakarensis Trm14 revealed that the enzyme catalyzes m2G formation at positions 6 and 67 in T. kodakarensis tRNACys and tRNATrp transcripts, respectively. Mass spectrometric analyses demonstrated the loss of m2G6 and m2G67 in native tRNACys and tRNATrp, respectively, from a T. kodakarensis trm14 gene disruptant strain, providing direct evidence for the dual-site specificity of T. kodakarensis Trm14. The growth phenotype of the trm14 gene disruptant strain was comparable to that of the wild-type strain. In contrast, a trm14/trm11 double disruptant, in which trm11 encodes the tRNA m2G10/m22G10 methyltransferase, exhibited severe growth retardation at 95 {degrees}C. This suggests that m2G6/m2G67 and m2G10/m22G10 cooperatively contribute to cellular fitness at high temperatures. Biochemical analyses revealed that Trm14 methylates all 46 T. kodakarensis tRNA transcripts. Furthermore, we found that recombinant M. jannaschii Trm14 methylated both positions. In contrast, the bacterial ortholog TrmN modified only position 6 in tRNA. Overall, this study expands our understanding of archaeal Trm14 by demonstrating its broader substrate specificity and the physiological significance of these modifications under hyperthermophilic conditions.

molecular biology↗

bioRxiv2026

Optimized tRNA Structure-seq reveals robust tRNA secondary structures in S. cerevisiae under mild stress conditions

RNA structure plays a crucial role in diverse biological processes beyond the translation of genetic information. Therefore, the development of reliable methods for RNA structure prediction is essential for understanding RNA structure-related functions, however accurate and comprehensive RNA structure prediction remains challenging. Here, we focus on secondary structure prediction of transfer RNA (tRNA) using structure probing coupled with next-generation sequencing (tRNA Structure-seq). In silico prediction of Saccharomyces cerevisiae tRNA secondary structures achieves only 56.9% accuracy on average. Incorporation of dimethyl sulfate (DMS) probing data improve prediction accuracy to 87.4%, which is still not sufficient for practical tRNA structure prediction. To overcome this, we optimized the tRNA Structure-seq analysis pipeline by explicitly incorporating natural tRNA modifications detected in tRNA sequencing data and by refining pseudo-free energy parameters specifically optimized for tRNA structure prediction. Using this optimized pipeline, the average prediction accuracy is remarkably improved to 94%. Furthermore, analysis of multiple structural conformations predicted from DMS probing data indicates that S. cerevisiae tRNAs predominantly adopt the canonical cloverleaf secondary structure under in vivo conditions. Finally, we examined tRNA structures under mild stress conditions, including heat stress, osmotic stress, and antibiotic stress. These perturbations had minimal effects on in vivo tRNA secondary structure, demonstrating that S. cerevisiae tRNAs maintain structural stability under physiologically relevant stress conditions. In summary, our results establish an optimized tRNA Structure-seq analysis that enables highly accurate tRNA secondary structure prediction and reveals the intrinsic robustness of tRNA structures in living cells.

molecular biology↗

bioRxiv2025

A transfer RNA methyltransferase with an unusual domain composition catalyzes 2'-O-methylation at position 6 in tRNA.

Thermococcus kodakarensis tRNATrp contains 2'-O-methylcytidine at position 6 (Cm6). However, the tRNA methyltransferase responsible for the modification has not been identified. Using comparative genomics we predicted TK1257 as a candidate for the modification. Biochemical and mass spectrometry studies of purified recombinant TK1257 gene product show it to possess a tRNA methyltransferase activity for Cm6 formation. This protein has a highly unusual composition of domains, containing N-terminal ferredoxin-like, SPOUT catalytic and THUMP domains. Previous to this study, all known THUMP-related tRNA methyltransferases were shown to contain a Rossmann fold catalytic domain and the nucleosides they produced were N2-methylguanosine and/or N2, N2-dimethylguanosine. Therefore, our findings extend the knowledge of architecture of tRNA methyltransferases. We named the TK1257 gene product TrmTS and showed it can synthesize Am6 and Um6 as well as Cm6. A trmTS gene deletion strain showed slight growth retardation at high temperatures. Site-directed mutagenesis studies based on structural model revealed catalytically and structurally important amino acid residues in TrmTS and identified a TrmTS-specific linker is structurally essential. We showed that TrmTS recognizes the 3'-CCA terminal region and a stretch loop connected with at least two stems in RNA. Finally, we constructed a model of the binding between TrmTS and tRNA.

biochemistry↗

bioRxiv2024

Transcriptional landscape of the dorsal raphe serotonin neurons rendering stress resiliency

Major depressive disorder (MDD) is a serious and large social problem, yet the pathophysiology of MDD and the action mechanism of antidepressants are still poorly understood. A number of studies have reported that activation and inactivation of serotonin neurons in the dorsal raphe nucleus (DRN) cause antidepressant-like effects and depressive-like behaviors, respectively. Also, their physiological neural activities are increased when mice were chronically administered an SSRI and decreased in mice exposed to chronic social defeat stress (CSDS), a mouse model of depression. However, the molecular mechanism underlying these neural activity changes in DRN serotonin neurons remains unclear. In this study, we performed a DRN serotonin neuron-specific comprehensive gene expression analysis by using Translating Ribosome Affinity Purification (TRAP) technology in both chronic SSRI-treated mice as a model of antidepressant treatment and CSDS mice as a model of depression. It revealed that many gene expression changes were the opposite between SSRI-treated mice and CSDS-susceptible mice. Among these, we identified S100a10 as a prodepressive gene in DRN serotonin neurons, and we found that Interleukin-4 (IL-4) - Signal Transducer and Activator of Transcription 6 (STAT6) pathway and 5-HT1B receptor were the upstream and downstream molecules of S100a10, respectively. Our findings provide insights into molecular mechanisms underlying the action of antidepressants and stress resiliency.

pharmacology and toxicology↗

bioRxiv2022

CCPLS reveals cell-type-specific spatial dependence of transcriptomes in single cells

MotivationCell-cell communications regulate internal cellular states, e.g., gene expression and cell functions, and play pivotal roles in normal development and disease states. Furthermore, single-cell RNA sequencing methods have revealed cell-to-cell expression variability of highly variable genes (HVGs), which is also crucial. Nevertheless, the regulation on cell-to-cell expression variability of HVGs via cell-cell communications is still largely unexplored. The recent advent of spatial transcriptome methods has linked gene expression profiles to the spatial context of single cells, which has provided opportunities to reveal those regulations. The existing computational methods extract genes with expression levels influenced by neighboring cell types. However, limitations remain in the quantitativeness and interpretability: they neither focus on HVGs nor consider the effects of multiple neighboring cell types. ResultsHere, we propose CCPLS (Cell-Cell communications analysis by Partial Least Square regression modeling), which is a statistical framework for identifying cell-cell communications as the effects of multiple neighboring cell types on cell-to-cell expression variability of HVGs, based on the spatial transcriptome data. For each cell type, CCPLS performs PLS regression modeling and reports coefficients as the quantitative index of the cell-cell communications. Evaluation using simulated data showed our method accurately estimated the effects of multiple neighboring cell types on HVGs. Furthermore, applications to the two real datasets demonstrate that CCPLS can extract biologically interpretable insights from the inferred cell-cell communications. AvailabilityThe R package is available at https://github.com/bioinfo-tsukuba/CCPLS. The data are available at https://github.com/bioinfo-tsukuba/CCPLS_paper. Contactharuka.ozaki@md.tsukuba.ac.jp Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2019

Massive parallel variant characterization identifies NUDT15 alleles associated with thiopurine toxicity

As a prototype of genomics-guided precision medicine, individualized thiopurine dosing based on pharmacogenetics is a highly effective way to mitigate hematopoietic toxicity of this class of drugs. Recently, NUDT15 deficiency was identified as a novel genetic cause of thiopurine toxicity, and NUDT15-informed preemptive dose reduction is quickly adopted in clinical settings. To exhaustively identify pharmacogenetic variants in this gene, we developed massively parallel NUDT15 function assays to determine variants effect on protein abundance and thiopurine cytotoxicity. Of the 3,097 possible missense variants, we characterized the abundance of 2,922 variants and found 54 hotspot residues at which variants resulted in complete loss of protein stability. Analyzing 2,935 variants in the thiopurine cytotoxicity-based assay, we identified 17 additional residues where variants altered NUDT15 activity without affecting protein stability. We identified structural elements key to NUDT15 stability and/or catalytical activity with single amino-acid resolution. Functional effects for NUDT15 variants accurately predicted toxicity risk alleles in 2,398 patients treated with thiopurines, with 100% sensitivity and specificity, in contrast with poor performance of bioinformatic prediction algorithms. In conclusion, our massively parallel variant function assays identified 1,103 deleterious NUDT15 variants, providing a comprehensive reference of variant function and vastly improving the ability to implement pharmacogenetics-guided thiopurine treatment individualization.

genomics↗