Publications by authors named "Musashi Takenaka"

Background: Computational mining of useful enzymes and biosynthesis pathways is a powerful strategy for metabolic engineering. Through systematic exploration of all conceivable combinations of enzyme reactions, including both known compounds and those inferred from the chemical structures of established reactions, we can uncover previously undiscovered enzymatic processes. The application of the novel alternative pathways enables us to improve microbial bioproduction by bypassing or reinforcing metabolic bottlenecks.

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Article Synopsis
  • Engineering microbial production of secondary metabolites is limited by the known enzymes, but machine learning can identify new specialized enzymes for biosynthesis pathways.
  • The study focuses on benzylisoquinoline alkaloids, highlighting the use of different pathways in bacteria, plants, and yeast for potential sustainable biomanufacturing.
  • Machine learning helps predict and select missing link enzymes from plant genes, leading to enhanced production of these alkaloids by combining pathways through newly discovered aromatic enzymes.
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Data-driven engineering of microbes has been demonstrated for the sustainable production of high-performance chemicals. Metabolic profiling analysis is essential to increase the productivity of target compounds. However, improvement of comprehensive analysis methodologies is required for the high demands of metabolic engineering.

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Actinobacteria plays a key role in the cycling of organic matter in soils. They secret biomass-degrading enzymes that allow it to produce the unique metabolites that originate in plant biomass. Although past studies have focused on these unique metabolites, a large-scale screening of Actinobacteria is yet to be reported to focus on their biomass-degrading ability.

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DNA-duplex interactions in thymines and adenins are used as a linker for the novel methodology of Atomic Force Microscope-Systematic Evolution of Ligands by EXpotential enrichment (AFM-SELEX). This study used the hydrogen bonds in 10 mer of both thymines (T10) and adenines (A10). Initially, the interactive force in T10-A10 was measured by AFM, which returned an average interactive force of approximately 350pN.

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The surface of yeast cells has been an attractive interface for the effective use of cellulose. Surface enzymes, however, are difficult to visualize and evaluate. In this study, two kinds of unique anchoring regions were used to display the cellulase, endoglucanase (EG), on a yeast cell surface.

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An atomic force microscope (AFM) can measure the adhesion force between a sample and a cantilever while simultaneously applying a rupture force during the imaging of a sample. An AFM should be useful in targeting specific proteins on a cell surface. The present study proposes the use of an AFM to measure the adhesion force between targeting receptors and their ligands, and to map the targeting receptors.

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