Biology subjects

Ota, R.

Publications and source records attributed to Ota, R..

4 recordsLinked to original sources

bioRxiv2025

Prediction of quantitative function of artificially-designed protein from structural information

Artificially designed proteins are widely used in applications such as optogenetics and biosensing. While experimental optimization of these proteins is effective, it is also costly and labor-intensive. To address this challenge, computational approaches have been developed, primarily relying on sequence-based features. However, protein function is inherently tied to its three-dimensional (3D) structure, and incorporating structural information could enable more accurate predictions and provide deeper biological interpretability. Here, we proposed a structure-based analysis framework called Foldinsight for predicting protein functionalities. In our framework, we first predict protein structures from sequences using AlphaFold2 and then utilize these structures to predict protein properties. Since proteins vary in the number of atoms and lack direct atomic correspondence, we applied molecular field mapping, which captures the energy states surrounding a protein and converts them into fixed-length numerical vectors. This transformation enables the application of machine learning, allowing protein properties to be predicted from structure-derived features. Applying this framework to channelrhodopsin mutants, we achieved predictive performance comparable to sequence-based models. Additionally, our structure-based analysis successfully identified key structural regions contributing to functional differences, highlighting the advantage of incorporating structural data into predictive modeling.

bioinformatics↗

bioRxiv2023

Integration of shoot-derived polypeptide signals by root TGA transcription factors is essential for survival under fluctuating nitrogen environments

Unlike plants in the field, which experience significant temporal fluctuations in environmental conditions, plants in the laboratory are typically grown in controlled, stable environments. Therefore, signaling pathways evolved for survival in continuously fluctuating environments often remain functionally latent in laboratory settings. Here, we show that TGA1 and TGA4 act as hub transcription factors through which the expression of genes involved in high-affinity nitrate uptake are regulated in response to shoot-derived phloem mobile polypeptides, CEP DOWNSTREAM 1 (CEPD1), CEPD2 and CEPD-like 2 (CEPDL2) as nitrogen (N) deficiency signals, and Glutaredoxin S1 (GrxS1) to GrxS8 as N sufficiency signals. CEPD1/2/CEPDL2 and GrxS1-S8 competitively bind to TGA1/4 in roots, with the former acting as transcription coactivators that enhance the uptake of nitrate, while the latter function as corepressor complexes together with TOPLESS to limit nitrate uptake. Arabidopsis plants deficient in TGA1/4 maintain basal nitrate uptake and exhibit growth similar to wild-type plants in a stable N environment, but were impaired in regulation of nitrate acquisition in response to shoot N demand, leading to defective growth under continuously fluctuating N environments where rhizosphere nitrate ions switch periodically between deficient and sufficient states. TGA1/4 are crucial transcription factors that enable plants to survive under fluctuating and challenging N environmental conditions.

plant biology↗

bioRxiv2022

Atypical small GTPase RABL3 interacts with RAB11 to regulate early ciliogenesis in human cells

Primary cilia are near-ubiquitously assembled on cells in the human body and are broadly associated with genetic diseases and cancers. In the early stage of ciliogenesis, the ciliary vesicle (CV) is formed on the mother centriole, which nucleates the primary cilium. However, the regulatory mechanisms underlying CV formation have not yet been fully elucidated. Here, we found that the atypical small GTPase RAB-Like 3 (RABL3) is necessary to assemble primary cilia in human cells. RABL3 directly interacts with RAB11, which is involved in CV formation. RABL3 localizes around the centrosome during early ciliogenesis, reminiscent of RAB11 dynamics. Furthermore, RABL3 positively controls the CV formation like RAB11. These findings suggest that RABL3 plays an important role, in cooperation with RAB11, in CV formation during early ciliogenesis.

cell biology↗

bioRxiv2018

A novel cell segmentation method for developing embryos using machine learning

Cell segmentation is crucial in the study of morphogenesis in developing embryos, but it is limited in its accuracy. In this study we provide a novel method for cell segmentation using machine-learning, termed Cell Segmenter using Machine Learning (CSML). CSML performed better than state-of-the-art methods, such as RACE and watershed, in the segmentation of ectodermal cells in the Xenopus embryo. CSML required only one whole embryo image for training a Fully Convolutional Network classifier, and it took 20 seconds per each image to return a segmented image. To validate its accuracy, we compared it to other methods in assessing several indicators of cell shape. We also examined the generality by measuring its performance in segmenting independent images. Our data demonstrates the superiority of CSML, and we expect this application to significantly improve efficiency in cell shape studies.

developmental biology↗