Biology subjects

Morimoto, N.

Publications and source records attributed to Morimoto, N..

4 recordsLinked to original sources

bioRxiv2026

A Generalizable Deep Learning Model for Automated 3D Segmentation of Orthopteran Head Anatomy in Micro-CT

Deep learning tools are increasingly used today, particularly in medical segmentation. A gap nonetheless remains in automating segmentation for insects. This work addresses the following question: can a generalist segmentation model, trained on several phylogenetically related orthopteran species, reliably automate head tissue segmentation from micro-CT images? To answer this, we used nnU-Net, a self-configuring 3D deep learning segmentation framework originally developed for medical imaging, whose core function, learning to recognize tissues of interest, applies directly to this context. Six anatomical classes were automated, comparing two training strategies: sequential fine-tuning, which adds species one at a time under the assumption that progressive learning would strengthen predictive power, and from-scratch training, in which the model learns the entire dataset simultaneously. The fine-tuning model (ModelB) reached a Dice coefficient (a measure of overlap between automated segmentation and manual ground truth, ranging from 0 to 1) of 0.7715, compared to 0.7664 for the from-scratch model (ModelC). Although both models produced accurate automated segmentations, no significant difference was found between the two training strategies (paired Wilcoxon test, n = 24, p = 0.243). Despite a dataset limited to 20 individuals and the absence of one method clearly outperforming the other, the models remain usable across the three species studied (Gryllus bimaculatus, Loxoblemmus equestris, L. doenitzi), including in the presence of pronounced sexual dimorphism. It reduces a 20 hour segmentation task to under a minute.

developmental biology↗

bioRxiv2025

Functional characterization of red-shifted rhodopsin channels from giant viruses explored by a machine-learning model for long-wavelength optogenetics

Channelrhodopsins (ChRs) are light-gated ion channels. These proteins are widely used in optogenetics to optically manipulate neural activity. However, manipulation using short-wavelength light to activate ChRs causes cell toxicity and is hampered by low tissue penetration. To overcome these difficulties, although several red-shifted ChR variants have been identified, further red-shift is required for more efficient and noninvasive neural control. While molecular screening of ChRs requires high-cost experiments, recent machine-learning-based protein functionality prediction enables more efficient selection of target proteins for characterization. Here, we constructed an elastic-net machine-learning model trained on 1,163 experimental data to predict the maximum absorption wavelength ({lambda}max) of uncharacterized ChRs. The model suggested several red-shifted candidates, and we identified a viral rhodopsin channel, ChR024, with the second-longest{lambda} max as a cation-conducting ChR ({lambda}max = [~]578 nm) after Chrimson ({lambda}max = [~]580 nm). This result demonstrates the high impact of ML on reducing the screening costs of functional proteins.

biophysics↗

bioRxiv2024

Beta-Glucanase superfamily identified by sequential, functional, and structural analyses

{beta}-1,2-Glucans are natural glucose polymers that play important physiological roles, including as symbiotic or pathogenic factors and in osmoregulation. Phylogenetically new glycoside hydrolase (GH) families have recently been identified from {beta}-1,2-glucanase (SGL) sequences from bacteria (GH144) and a fungus (GH162). In this study, we identified four phylogenetically new groups (Groups 1-4), and determined that these families, together with GH144, GH162, and GH189, a family of transglycosylase domains in cyclic {beta}-1,2-glucan synthases, form a superfamily. Biochemical analysis of six proteins in these groups revealed that the proteins in Groups 1-3 showed hydrolytic activity specific to {beta}-1,2-glucan. The kinetic parameters of the enzymes of Groups 1-3 were similar to GH144 and GH162 SGLs, indicating that these enzymes were SGLs. Optical rotation analysis revealed that the SGLs followed an anomer-inverting mechanism. Structural analysis and prediction of the proteins in Groups 1-4, GH144, GH162, and GH189 suggested that Groups 1-3 and GH144 had the same reaction mechanism. Nevertheless, Groups 1-3 were dispersed irregularly in the superfamily. Overall, we determined that Groups 1-3 were new GH families, GHxxx, GHyyy, and GHzzz, respectively, and proposed that this superfamily be called an SGL superfamily because of the phylogenetical, functional, and structural relationships within the superfamily. HighlightsWide variety of glycoside hydrolases is far beyond our understanding. Functional and structural analysis identified three new glycoside hydrolase families. Molecular evolution with irregular changes in reaction mechanism was revealed.

biochemistry↗

bioRxiv2018

The sustained release of basic fibroblast growth factor accelerates angiogenesis and the survival of the inactivated dermis by high hydrostatic pressure

We developed a novel skin regeneration therapy combining nevus tissue inactivated by high hydrostatic pressure (HHP) in the reconstruction of the dermis with a cultured epidermal autograft (CEA). The issue with this treatment is the unstable survival of CEA on the inactivated dermis. In this study, we applied collagen/gelatin sponge (CGS), which can sustain the release of basic fibroblast growth factor (bFGF), to the inactivated skin in order to accelerate angiogenesis. Murine skin grafts from C57BL6J/Jcl mice (8 mm in diameter) were prepared, inactivated by HHP and cryopreserved. One month later, the grafts were transplanted subcutaneously onto the back of other mice and covered by CGS impregnated with saline or bFGF. Grafts were taken after one, two and eight weeks, at which point the survival was evaluated through the histology and angiogenesis-related gene expressions were determined by real-time polymerase chain reaction. Histological sections showed that the dermal cellular density and newly formed capillaries in the bFGF group were significantly higher than in the control group. The relative expression of FGF-2, PDGF-A and VEGF-A genes in the bFGF group was significantly higher than in the control group at Week 1. This study suggested that the angiogenesis into grafts was accelerated, which might improve the survival in combination with the sustained release of bFGF by CGSs.

bioengineering↗