Biology subjects

Oka, H.

Publications and source records attributed to Oka, H..

6 recordsLinked to original sources

bioRxiv2026

A pooled screening approach reveals bacterial chemoreceptors for short-chain carboxylic acids

Bacterial chemotaxis is a key process in host colonization and virulence, mediated by large repertoires of chemoreceptors. Despite their physiological and ecological importance, mapping these chemoreceptors to their cognate metabolic ligands remains a major challenge due to the vast number of potential interactions. To address this, we developed a pooled screening assay that enriches functional chemoreceptors from a gene library. Using this approach, we identified a previously uncharacterized group of chemoreceptors in Pseudomonas species with Cache_3-Cache_2 domains that sense short-chain C3 carboxylic acids. Sequence and computational structural analyses revealed that these chemoreceptors exhibit domain features similar to a recently reported C1 formate chemoreceptor despite substantial sequence divergence. Functional assays of representative chemoreceptors confirmed robust chemotactic responses to C3 carboxylic acids, with limited responses to formate. Integrating structural and molecular dynamics analyses suggests that increased binding pocket size and altered flexibility, relative to the formate chemoreceptor, facilitate recognition of larger C3 carboxylic acid ligands. Together, our approach provides a simple and scalable framework for mapping ligand-chemoreceptor interactions and enables systematic characterization across diverse metabolites.

microbiology↗

bioRxiv2025

Heterologous expression of carbonic anhydrase in Acinetobacter sp. Tol 5 for whole-cell biocatalysis

Carbonic anhydrase accelerates the hydration of carbon dioxide (CO2) and is an attractive biocatalyst for carbon capture and utilization. Acinetobacter sp. Tol 5 shows high adhesiveness via its cell-surface protein AtaA. We previously demonstrated its application to bacterial immobilization and gas-phase bioproduction. Here, we developed Tol 5 cells expressing carbonic anhydrase and evaluated CO2 conversion ability as whole-cell biocatalysts. A codon-optimized carbonic anhydrase from Sulfurihydrogenibium yellowstonense (SyCA) was produced in the cytoplasm, but the cells showed little activity as a whole-cell biocatalyst. To enhance activity, we fused six signal peptides (SPs) to SyCA for periplasmic expression. The Omp38-SP fusion of SyCA was properly processed to the mature size, yielding higher whole-cell activity. By contrast, the other constructs were either undetectable or remained unprocessed, resulting in lower activities. These results show that periplasmic expression of SyCA is important for efficient CO2 hydration in Tol 5 cells as whole-cell biocatalysts.

bioengineering↗

bioRxiv2023

Development of a fast feature extraction method for SARS-CoV-2 spike sequences using amino acid physicochemical properties

COVID-19 continues to spread today, leading to an accumulation of SARS-CoV-2 virus mutations in databases, and large amounts of genomic datasets are currently available. However, due to these large datasets, utilizing this amount of sequence data without random sampling is challenging. Major difficulties for downstream analyses include the increase in the dimension size along with the conversion of sequences into numerical values when using conventional amino acid representation methods, such as one-hot encoding and k-mer-based approaches that directly reflect sequences. Moreover, these sequences are deficient in physicochemical characteristics, such as structural information and hydrophilicity; hence, they fail to accurately represent the inherent function of the given sequences. In this study, we utilized the physicochemical properties of amino acids to develop a rapid and efficient approach for extracting feature parameters that are suitable for downstream processes of machine learning, such as clustering. A fixed-length feature vector representation of a spike sequence with reduced dimensionality was obtained by converting amino acid residues into physicochemical parameters. Next, t-distributed stochastic neighbor embedding (t- SNE), a method for dimensionality reduction and visualization of high-dimensional data, was performed, followed by density-based spatial clustering of applications with noise (DBSCAN). The results show that by using the physicochemical properties of amino acids rather than conventional methods that directly represent sequences into numerical values, SARS-CoV-2 spike sequences can be clustered with sufficient accuracy and a shorter runtime. Interestingly, the clusters obtained by using amino acid properties include subclusters that are distinct from those produced utilizing the method for the direct representation of amino acid sequences. A more detailed analysis indicated that the contributing parameters of this novel cluster identified exclusively when utilizing the physicochemical properties of amino acids significantly differ from one another. This suggests that representing amino acid sequences by physicochemical properties might enable the identification of clusters with enhanced sensitivity compared to conventional methods. Author summaryOne of the major causes of the global threat of SARS-CoV-2 is the rapid emergence of its variants. While analyzing these variants is crucial for understanding the mechanism of outbreaks, the expansion of database size is becoming a barrier for effective analysis. In this study, we provide an approach that allows researchers without vast computational resources to comprehensively analyze the variants of SARS-CoV-2 spike by representing the sequences using the physicochemical properties of amino acids. The result of clusters derived using this method demonstrates not only an accuracy comparable to the conventional approaches of directly converting sequences into numerical values but also indicates the potential for more detailed clustering outcomes. The results suggest that our approach is valuable for the rapid identification of characteristic residues in new variants of SARS-CoV-2 and other viruses that may arise in the future.

bioinformatics↗

bioRxiv2023

Different Physical Parameters in the Bonds between Platelet Glycoprotein Ibalpha with von Willebrand factor and with Coagulant Factor XI -Results from the Molecular Dynamic Simulation-

BackgroundBoth von Willebrand factor (VWF) and coagulation factor XI (FXI) bind with platelet membrane glycoprotein (GP) Ib. However, the differences in the physical parameters in the bonds between VWF-GPIb and FXI-GPIb mediating different biological functions are unclear. MethodsThe FXI molecule was arranged in 9 different initial positions around the structure of GPIb bound to VWF. The position coordinate and velocity vectors of all atoms constructing VWF, GPIb, and FXI were calculated in each 2 femto (10-15) second using the Chemistry at HARvard Macromolecular Mechanics (CHARMM) force field. The physical parameters of VWF-GPIb and FXI-GPIb bonds were calculated by molecular dynamic (MD) simulations. ResultsMD calculation revealed 2.8 to 11.3 times greater positional fluctuations in atoms constructing FXI-GPIb as compared to those constructing VWF-GPIb (RMSDs: 5.9{+/-}1.5 to 18.1{+/-}7.9 [A] for FXI-GPIb vs 1.6{+/-}0.1 to 2.1{+/-}0.3 [A] for VWF-GPIb). The absolute value of non-covalent binding energy generated in FXI-GPIb (65.5{+/-}79.7 to 517.6{+/-}54.2 kcal/mol) was smaller than that generated in VWF-GPIb (678.5{+/-}58.3 to 1000.4{+/-}75.1 kcal/mol). The binding structure of VWF-GPIb was stable and was only minimally influenced by the presence of FXI-GPIb binding. ConclusionsOur MD calculation results revealed that atoms constructing the VWF-GPIb bond are physically more stable and produce more non-covalent binding energy than the bond of FXI-GPIb. The physical parameters in the VWF-GPIb bond were not largely influenced by FXI binding with GPIb.

bioengineering↗

bioRxiv2021

Construction of transcript regulation mechanism prediction models based on binding motif environment of transcription factor AoXlnR in Aspergillus oryzae

Recent study revealed that there are thousands of genes that remain unaffected by increased AoXlnR expression, despite the presence of one or more AoXlnR-binding motifs in their promoter region. Given this knowledge, we designed this study to construct several predictive models for determining whether a gene can exhibit a differential response to changes in AoXlnR expression. These models were constructed using 3D DNA shape information determined using the sequence around the AoXlnR binding motifs with classification as functional or nonfunctional. These models were created using a support vector machine followed by the evaluations designed to determine whether these DNA shape-based models can correctly classify functional motifs in terms of area under the receiver operating characteristic curve. The results showed that the differential expression levels of genes located downstream of the AoXlnR motif are closely related to specific DNA shape information around the binding motifs. Furthermore, we found that the parameters contributing to differential expressions differed depending on the number of motifs in the promoter region by comparing the prediction models using regions with only one binding DNA motif and those with multiple binding DNA motifs. Author SummaryDNA-binding transcription factors (TFs) play a central role in transcriptional regulation mechanisms, mainly through their specific binding to target sites on the genome and regulation of the expression of downstream genes. Therefore, a comprehensive analysis of the function of these TFs will lead to the understanding of various biological mechanisms. However, the functions of TFs in vivo are diverse and complicated, and the identified binding sites on the genome are not necessarily involved in the regulation of downstream gene expression. In this study, we investigated whether DNA structural information around the binding site of transcription factors can be used to predict the involvement of the binding site in the regulation of the expression of genes located downstream of the binding site. Specifically, we calculated the structural parameters based on the DNA shape around the DNA binding motif located upstream of the gene whose expression is directly regulated by the transcription factor AoXlnR from Aspergillus oryzae, and showed that the presence or absence of expression regulation can be predicted from the sequence information with high accuracy by machine learning incorporating these parameters.

genomics↗

bioRxiv2019

Field evaluation of a quantitative, and rapid malaria diagnostic system using a fluorescent Blue-ray optical device

We improved a previously developed quantitative malaria diagnostic system based on fluorescent Blue-ray optical device. Here, we first improved the diagnostic system to enable fully automated operation and the field application was evaluated in Kenya. We detected Plasmodium falciparum in blood samples collected from 288 individuals aged 1-16 years using nested polymerase chain reaction (nPCR), rapid diagnostic test (RDT), and automated system. Compared to RDT, the automated system exhibited a higher sensitivity (100%; 95% confidence interval [CI], 93.3-100%) and specificity (92.8%; 95%CI, 88.5-95.8%). The limit of detection was 0.0061%. Linear regression analysis revealed a correlation between the automated system and microscopic examination for detecting parasitemia (adjusted R2 value=0.63, P=1.13x10-12). The automated system exhibited a stable quantification of parasitemia and a higher diagnostic accuracy for parasitemia than RDT. This indicates the potential of this system as a valid alternative to conventional methods used at local health facilities, which lack basic infrastructure.

physiology↗