Biology subjects

Maniwa, Y.

Publications and source records attributed to Maniwa, Y..

5 recordsLinked to original sources

bioRxiv2026

Ductal myofibroblasts reactivate contractile program to stabilize alveolar architecture during lung regeneration

The alveolar sac architecture is essential for efficient gas exchange and must be precisely maintained throughout life; however, how this delicate structure is preserved during adult regeneration remains poorly understood. Using a mouse pneumonectomy model, we found that Lgr6+ Hhip+ ductal myofibroblasts, a poorly characterized mesenchymal population, are indispensable for maintaining alveolar integrity during lung regrowth. Comprehensive characterization using single-cell transcriptomics, mouse genetics, and pharmacological assays demonstrated that these ductal myofibroblasts secrete myogenic factors, most notably CCN4, to reactivate a myogenic program that converts them into contractile PA-DMFs, thereby preserving alveolar architecture. Lineage-tracing further revealed that these ductal myofibroblasts originate from embryonic MCAM- SMA+ distal progenitors via subepithelial TGF-{beta} signaling, serving as a lifelong guardian of alveolar structural integrity. Notably, cross-species analysis identified an analogous population of LGR6+ fibromyocytes in human respiratory bronchioles. Together, these findings indicate ductal myofibroblasts as a developmentally programmed cell population that reactivate a contractile program to structurally support the regeneration of adult lungs.

developmental biology↗

bioRxiv2026

Tumor Microenvironment Modulates Lineage Plasticity in Lung Squamous Cell Carcinoma

Lung squamous cell carcinoma (LUSC) is the second most common type of lung cancer, yet therapeutic options remain limited. A deeper understanding of its biology and molecular pathogenesis is essential for developing new treatment strategies. Here, we investigated the mechanisms of phenotypic plasticity in LUSC by comparing organoid-derived orthotopic lung models (ODOLs) and subcutaneous xenograft models (ODXs). ODXs showed greater tumor growth, squamous differentiation, and extracellular matrix (ECM) organization compared to ODOLs. Transcriptomic analyses revealed upregulation of multiple HIF1 and SOX2 target genes together with enhanced hypoxia signaling in ODXs. CRISPR/Cas9-mediated HIF1-knockout ODXs showed reduced SOX2 expression, tumor growth, and ECM organization, whereas SOX2-knockout ODXs reduced tumor growth without affecting HIF1 and ECM organization. These results indicate that HIF1 regulates squamous lineage maintenance through SOX2 and ECM remodeling. Spatial transcriptomics revealed enrichment of basal cell-like and squamous-differentiated tumor states in ODXs, whereas ODOLs displayed less differentiated phenotypes. These findings identify the tumor microenvironment as a critical determinant of lineage plasticity in LUSC and provide mechanistic insight into how hypoxia shapes tumor differentiation.

Cancer Biology↗

bioRxiv2023

SARS-CoV-2 Omicron XBB.1.5 may be a cautionary variant by in silico study

In this research, we aimed to predict the relative risk of the recent new variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on the basis of our previous research. We first performed molecular docking simulation analyses of the spike proteins with human angiotensin-converting enzyme 2 (ACE2) to determine the binding affinities to human cells of three new variants of SARS-CoV-2: Omicron BQ.1, XBB, and XBB.1.5 We then investigated the three variants to discover the evolutionary distance of the spike protein gene (S gene) from the Wuhan, Omicron BA.1, and Omicron BA.4/5 variants, to understand the changes in the S gene. The results indicated that the XBB.1.5 variant had the highest binding affinity of the spike protein with ACE2 and the longest evolutionary distance of the S gene. This in silico evidence suggested that the XBB.1.5 variant may produce infections that spread more widely and faster than can infections of preexisting variants.

bioinformatics↗

bioRxiv2022

Structural basis of Irgb6 inactivation by Toxoplasma gondii through the phosphorylation of switch I.

Upon infection with Toxoplasma gondii, host cells produce immune-related GTPases (IRGs) to kill the parasite. T. gondii counters this response by releasing ROP18 kinase, which inactivates IRG GTPases and inhibits their recruitment to the T. gondii parasitophorous vacuole (PV). However, the molecular mechanisms of this process are entirely unknown. Here we report the atomic structures of Irgb6 with a phosphomimetic mutation by ROP18. The mutant has lower GTPase activity and is not recruited to the PV membrane (PVM). The crystal structure shows the mutant exhibit a distinct conformation from the physiological nucleotide-free form, thus preventing GTPase cycling. This change allosterically modifies the conformation of the membrane-binding interface, preventing physiological PVM-binding. Docking simulation of PI5P also supports the impaired binding of the mutant to PVM. We thus demonstrate the structural basis for T. gondii escape from host cell-autonomous defense, and provide a structural model for regulating enzymatic activity by phosphorylation.

microbiology↗

bioRxiv2022

Prediction of infectivity of SARS-CoV2: Mathematical Model with Docking Simulation analysis between Spike Protein and ACE2

Variants of a coronavirus (SARS-CoV-2) have been spreading in a global pandemic. Improved understanding of the infectivity of future new variants is important so that effective countermeasures against them can be quickly undertaken. In our research reported here, we aimed to predict the infectivity of SARS-CoV-2 by using a mathematical model with molecular simulation analysis, and we used phylogenetic analysis to determine the evolutionary distance of the spike protein gene (S gene) of SARS-CoV-2. We subjected the six variants and the wild type of spike protein and human angiotensin-converting enzyme 2 (ACE2) to molecular docking simulation analyses to understand the binding affinity of spike protein and ACE2. We then utilized regression analysis of the correlation coefficient of the mathematical model and the infectivity of SARS-CoV-2 to predict infectivity. The evolutionary distance of the S gene correlated with the infectivity of SARS-CoV-2 variants. The coefficient of the mathematical model obtained with results of molecular docking simulation also correlated with the infectivity of SARS-CoV-2 variants. These results suggest that the data from the docking simulation for the receptor binding domain of variant spike proteins and human ACE2 were valuable for prediction of SARS-CoV-2 infectivity. In addition, we developed a mathematical model for prediction of SARS-CoV-2 variant infectivity by using binding affinity obtained via molecular docking and the evolutionary distance of the S gene.

bioinformatics↗