Biology subjects

Omori, S.

Publications and source records attributed to Omori, S..

6 recordsLinked to original sources

bioRxiv2026

AI-enabled discovery of small molecules targeting complementary pathways for hair follicle rejuvenation

Hair thinning arises from multi-faceted dysfunction within the hair follicle, driven by both intrinsic cellular pathways and pathways responding to extrinsic hormonal and microenvironmental cues. Here, we present an AI-enabled discovery framework to discover small molecules that promote hair follicle rejuvenation. This framework integrates graph neural networks trained on phenotypic screening data with structure-based virtual screening to prioritize compounds that modulate complementary biological pathways. Through AI-enabled screening, hit-to-lead optimization, and medicinal chemistry, we identified four compounds that increase follicle dermal papilla cell viability, stabilize hypoxia signaling by inhibiting prolyl hydroxylase domain protein 2 (PHD2), and suppress androgen-mediated follicular miniaturization by inhibiting 5-reductases (5-ARs). RNA sequencing analyses confirmed pathway engagement, and functional validation across primary cells and a 3D hair follicle organoid model demonstrated high activity and cellular specificity. The lead compounds were incorporated into a water-based formulation, where they demonstrated robust solubility and combinatorial efficacy to increase sprouting length of follicle organoids. These results establish an AI-enabled platform for discovering multi-pathway modulators of hair follicle rejuvenation.

bioengineering↗

bioRxiv2026

Clinical isolates of Mycobacterium avium complex reveal an M. intracellulare-associated IL-17/neutrophilic pulmonary immune program in a murine disease model

Mycobacterium avium complex (MAC) is the leading cause of nontuberculous mycobacterial pulmonary disease (NTM-PD) and mainly comprises M. avium (MAV) and M. intracellulare (MI). Host-pathogen interactions may contribute to the heterogeneous clinical course of MAC pulmonary disease (MAC-PD); however, species- or isolate-associated differences in virulence and host immune responses induced by MAC strains remain poorly understood. Here, we established a panel of MAC clinical isolates exhibiting persistent pulmonary infection in mice and performed transcriptomic analyses to evaluate pulmonary immune responses. Although MAC infections induced broadly shared inflammatory responses, MI infection elicited a robust IL-17/neutrophilic inflammatory signature, whereas MAV infection showed relative enrichment of IFN-{gamma}/cytotoxicity-associated responses, indicating differences in the balance of their immune gene expression programs. The MI-associated IL-17/neutrophilic program remained evident at the isolate level and after adjustment for pulmonary growth phenotype. RT-qPCR and flow cytometric analyses using the representative isolate pair FKJ-1 (MI) and FKJ-8 (MAV) further supported the differential induction of these immune signatures in infected lungs. To define the cellular basis of these immune programs, we performed single-cell RNA sequencing on lungs infected with FKJ-1 and FKJ-8. Infection with the representative MI isolate was associated with increased Il17a-expressing CD4+ T cells and {gamma}{delta} T cells, neutrophilic inflammation, and the expansion of inflammatory macrophages. Taken together, these findings demonstrate that within a selected panel of persistent MAC clinical isolates, MI infection is associated with a robust IL-17/neutrophilic pulmonary immune program, providing a preclinical framework for dissecting species- and isolate-associated host-pathogen interactions in MAC-PD.

immunology↗

bioRxiv2025

Strain-dependent disease progression and necrotizing granuloma formation induced by virulent Mycobacterium avium complex strains in a murine model

Mycobacterium avium complex (MAC) is the leading cause of non-tuberculous mycobacterial pulmonary disease (NTM-PD), a chronic infection with a heterogeneous clinical course. Although murine models of MAC-PD have been developed, reproducing the key features of progressive human disease, including diverse pathological features and therapeutic sensitivities, remains challenging. In this study, we evaluated five clinical MAC strains, including a newly identified highly virulent isolate, NBRC112750, in immunocompetent BALB/c mice. Among these, FKJ-1 and NBRC112750 induced progressive pulmonary infection with increasing bacterial burdens and extensive lung involvement by 25 weeks post-infection. Notably, both strains led to the formation of necrotizing granulomas resembling those observed in M. tuberculosis-infected C3HeB/FeJ mice. These lesions featured neutrophilic infiltration, foamy macrophages, and collagen encapsulation. Using FKJ-1 strain, we also established an inhalation infection model, in which low-dose exposure reproduced necrotizing granulomas. Despite in vitro drug susceptibility, FKJ-1 infection exhibited poor response to standard therapy, highlighting strain-dependent variability in treatment efficacy. These findings establish a murine model that reflects both key pathological and therapeutic aspects of MAC-PD and provides a valuable platform for investigating MAC pathogenesis and evaluating novel therapies.

microbiology↗

bioRxiv2025

Title Mafb Deficiency in Myeloid Cells Increases Susceptibility to Mycobacterium tuberculosis Infection in Mice

v-Maf avian musculoaponeurotic fibrosarcoma oncogene homolog B (MAFB) is a candidate gene associated with early tuberculosis onset identified by a genome-wide association study. Here, we investigated the role of Mafb in susceptibility to Mycobacterium tuberculosis (Mtb) infection in myeloid-specific Mafb-knockout (Mafb-cKO) mice. We infected bone marrow-derived macrophages (BMMs) from Mafb-cKO mice and Mafb-cKO mice with Mtb. The absence of Mafb promoted Mtb proliferation in BMMs. RNA sequencing (RNA-seq) revealed activation of the metabolic process and impairment of the response to type interferons (IFNs) in Mtb-infected BMMs from Mafb-cKO mice, which conforms to our previous findings in Mtb-infected human macrophages with MAFB knockdown. Mafb deficiency increased mortality and bacterial burden in the lungs and spleens during Mtb infection in mice. RNA-seq revealed weakened leukocyte or lymphocyte chemotaxis in Mtb-infected Mafb-cKO mouse lungs. Flow cytometry demonstrated an alteration in the proportion of immune cells in Mtb-infected mouse lungs due to Mafb deficiency. Together, Mafb in myeloid cells is involved not only in the functional antibacterial process of macrophages but also in immune cell recruitment in the lungs, thereby contributing to host defense against Mtb infection.

immunology↗

bioRxiv2023

Elevator motion of chloride ion transporter SLC26A9 induced by STAS domain

The anion exchanger SLC26A9, consisting of the transmembrane (TM) domain and the cytoplasmic STAS domain, plays an essential role in regulating chloride transport across cell membranes. Recent studies have indicated that C-terminal helices block the entrance of the putative ion transport pathway. However, the precise functions of the STAS domain and C-terminal helix, as well as the underlying molecular mechanisms governing the transport process, remain poorly understood. In this study, we performed molecular dynamics simulations of three distinct models of human SLC26A9: full-length (FL), STAS domain removal ({Delta}STAS), and C-terminus removal ({Delta}C), to investigate their conformational dynamics and ion binding properties. Stable binding of ions to the binding sites was exclusively observed in the {Delta}C model in these simulations. Comparing the FL and {Delta}C simulations, the {Delta}C model displayed enhanced motion of the STAS domain. Furthermore, comparing the {Delta}STAS and {Delta}C simulations, the {Delta}STAS simulation failed to exhibit stable ion bindings to the sites despite the absence of the C-terminus blocking the ion transmission pathway in both systems. These results suggest that the removal of the C-terminus not only unblocks the access of ions to the permeation pathway but also triggers STAS domain motion, gating the TM domain to promote ions entry into their binding site. Further analysis revealed that the asymmetric motion of STAS domain leads to the expansion of the ion permeation pathway within the TM domain, resulting in the stiffening of the flexible TM12 helix near the ion binding site. This structural change in the TM12 helix stabilizes chloride ion binding, which is essential for SLC26A9 elevator motion. Overall, our study provides new insights into the molecular mechanisms of SLC26A9 transport and may pave the way for the development of novel treatments for diseases associated with dysregulated ion transport. SIGNIFICANCEWe explored the mechanism by which the human protein SLC26A9 transports chloride in the cell. SLC26A9 is a potential therapeutic target for patients with cystic fibrosis, as by targeting drugs to it, it may be possible to restore chloride ion transport in epithelial cells. To design therapeutic drugs, it is essential to understand how the protein works. Our findings support an elevator-type mechanism, in which chloride ions bind to SLC26A9 inside the cell and are then released by the protein to the extracellular environment. We find that the STAS domain of SLC26A9 has critical roles in binding chloride and induces conformational changes in the transmembrane domain that facilitate chloride transport.

biophysics↗

bioRxiv2021

Prediction and Characterization of Disorder-Order Transition Regions in Proteins by Deep Learning

The biological functions of proteins are traditionally thought to depend on well-defined three-dimensional structures, but many experimental studies have shown that disordered regions lacking fixed three-dimensional structures also have crucial biological roles. In some of these regions, disorder-order transitions are also involved in various biological processes, such as protein-protein interaction and ligand binding. Therefore, it is crucial to study disordered regions and structural transitions for further understanding of protein functions and folding. Owing to the costs and time requirements of experimental identification of natively disordered or transitional regions, the development of effective computational methods is a key research goal. In this study, we used overall residue dependencies and deep representation learning for prediction and reused the obtained disordered regions for the prediction of disorder-order transitions. Two similar and related prediction tasks were combined. Firstly, we developed a novel deep learning method, Res-BiLstm, for residue-wise disordered region prediction. Our method outperformed other predictors with respect to almost all criteria, as evaluated using an independent test set. For disorder-order transition prediction, we proposed a transfer learning method, Res-BiLstm-NN, with an acceptable but unbalanced performance, yielding reasonable results. To grasp underlining biophysical principles of disorder-order transitions, we performed qualitative analyses on the obtained results and discovered that most transitions have strong disordered or ordered preferences, and more transitions are consistent with the ordered state than the disordered state, different from conventional wisdom. To the best of our knowledge, this is the first sizable-scale study of transition prediction. Availabilityhttps://github.com/Yanzziang/Transition_Disorder_Prediction Contactkengo@ecei.tohoku.ac.jp

bioinformatics↗