Biology subjects

Toya, Y.

Publications and source records attributed to Toya, Y..

3 recordsLinked to original sources

bioRxiv2026

OpenMebius2: GUI-based software for 13C-metabolic flux analysis with tracer labeling pattern suggestions for accurate flux predictions

13C-metabolic flux analysis (13C-MFA) is a crucial technique that experimentally determines metabolic flux distribution. Although precision of each flux strongly depends on tracer labeling pattern, its optimization remains challenging. We developed an integrated platform, OpenMebius2, a graphical user interface (GUI)-based software for 13C-MFA that includes a tracer labeling pattern suggestion function to support subsequent experiments. The proposed function leverages metabolic flux distributions and their 95 % confidence intervals obtained using low-cost 13C-labeled substrates to evaluate hypothetical parallel labeling scenarios and predict improvements in flux estimation precision. Availability and implementationThis software runs on Linux, macOS, and Windows. The source code and binary files are available at https://github.com/metabolic-engineering/OpenMebius2 under the PolyForm Noncommercial License 1.0.0.

bioengineering↗

bioRxiv2025

Fine modulation of carbon flow in the central carbon metabolism via ribosome-binding site modification in Escherichia coli

Optimization of flux distribution in central carbon metabolism is important to improve the microbial productivity. As the number of precursors required for synthesis differs for each target compound, optimal flux distribution also varies. A library of mutant strains with diverse flux distributions can aid in optimal strain screening. Therefore, in this study, we aimed to construct a library of Escherichia coli strains with stepwise changes in flux distribution by introducing mutations into the ribosome-binding sites of key enzyme genes on its chromosome. We focused on the flux ratios at the glucose-6-phosphate and acetyl-CoA nodes to enhance mevalonate production. Mutations were introduced into the ribosome-binding sites of pgi and gltA to vary the flux ratios of the two pathway branches. Furthermore, a combinatorial repression library comprising 16 strains was constructed by varying pgi and gltA expression at four levels, and a plasmid expressing mevalonate synthesis genes was introduced into each strain. Batch cultures were performed to obtain strains with mevalonate titers and yields were 2.4- and 3.4-fold higher than those of the parent strain. Overall, our combinatorial suppression library of pgi and gltA facilitated the effective identification of mutants with optimal metabolism for mevalonate production.

molecular biology↗

bioRxiv2025

A Method for Predicting Enzyme Substrate Specificity Residues Using Homologous Sequence Information

Identifying amino acid residues that are critical for the catalytic function of enzymes is essential for elucidating reaction mechanisms, facilitating drug discovery, and advancing protein engineering. However, experimentally and computationally distinguishing residues that maintain structural integrity from those directly involved in enzymatic function remains a major challenge. In this study, we developed a methodology to identify amino acid residues that influence substrate specificity in enzymes with homologous structures. We framed the sequence comparison as a classification problem, treating each residue as a feature, thereby enabling the rapid and objective identification of key residues responsible for functional differences. To validate the proposed method, we applied it to three enzyme pairs-- trypsin/chymotrypsin, adenylyl cyclase/guanylyl cyclase, and lactate dehydrogenase (LDH)/malate dehydrogenase (MDH). The results confirmed the accurate prediction of previously identified specificity-determining residues. Furthermore, we conducted experiments on the LDH/MDH pair and successfully introduced mutations into key residues to alter substrate specificity, enabling LDH to utilize oxaloacetate while maintaining its expression levels. These findings demonstrate the potential of this method for efficiently identifying residues that govern substrate specificity. We have further developed this approach into a practical tool, the EZSCAN: Enzyme Substrate-specificity and Conservation Analysis Navigator (https://ezscan.pe-tools.com/), which enables rapid identification of amino acid residues critical for enzyme function. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/656053v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@d97b76org.highwire.dtl.DTLVardef@38bbe8org.highwire.dtl.DTLVardef@b8b6edorg.highwire.dtl.DTLVardef@f1b858_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗