Evidence map›Paper›PMID 38879464›Full record

ArticleMicrobial cell factories2024

Integrated pathway mining and selection of an artificial CYP79-mediated bypass to improve benzylisoquinoline alkaloid biosynthesis.

Musashi Takenaka, Kouhei Kamasaka, Kim Daryong, Keiko Tsuchikane, Seiha Miyazawa, Saeko Fujihana, Yoshimi Hori, Christopher J Vavricka, Akira Hosoyama, Hiroko Kawasaki and 6 more

Abstract read
In one paragraph

Article in Microbial cell factories, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Frontiers in pharmacology · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Musashi TakenakaBacchus Bio innovation Co. Ltd, 6-3-7-505 Minatojima Minamimachi, Chuo-ku, Kobe, 650-0047, Japan.
Kouhei KamasakaGraduate School of Science, Technology and Innovation, Kobe University, 1-1 Rokkodai, Nada, Kobe, 657-8501, Japan.
Kim DaryongNational Institute of Technology and Evaluation, 2-49-10 Nishihara, Shibuya-ku, Tokyo, 1510066, Japan.
Keiko TsuchikaneNational Institute of Technology and Evaluation, 2-49-10 Nishihara, Shibuya-ku, Tokyo, 1510066, Japan.
Seiha MiyazawaNational Institute of Technology and Evaluation, 2-49-10 Nishihara, Shibuya-ku, Tokyo, 1510066, Japan.
Saeko FujihanaBacchus Bio innovation Co. Ltd, 6-3-7-505 Minatojima Minamimachi, Chuo-ku, Kobe, 650-0047, Japan.
Yoshimi HoriGraduate School of Science, Technology and Innovation, Kobe University, 1-1 Rokkodai, Nada, Kobe, 657-8501, Japan.
Christopher J VavrickaDepartment of Biotechnology and Life Science, Graduate School of Engineering, Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei, Tokyo, 184-8588, Japan.
Akira HosoyamaNational Institute of Technology and Evaluation, 2-49-10 Nishihara, Shibuya-ku, Tokyo, 1510066, Japan.
Hiroko KawasakiNational Institute of Technology and Evaluation, 2-49-10 Nishihara, Shibuya-ku, Tokyo, 1510066, Japan.
Tomokazu ShiraiCenter for Sustainable Resource Science, RIKEN, 1-7-22 Suehiro, Tsurumi, Yokohama, Kanagawa, 230-0045, Japan.
Michihiro ArakiGraduate School of Science, Technology and Innovation, Kobe University, 1-1 Rokkodai, Nada, Kobe, 657-8501, Japan.
Akira NakagawaResearch Institute for Bioresources and Biotechnology, Ishikawa Prefectural University, 1-308, Suematsu, Nonoichi city, Ishikawa, Japan.
Hiromichi MinamiResearch Institute for Bioresources and Biotechnology, Ishikawa Prefectural University, 1-308, Suematsu, Nonoichi city, Ishikawa, Japan.
Akihiko KondoBacchus Bio innovation Co. Ltd, 6-3-7-505 Minatojima Minamimachi, Chuo-ku, Kobe, 650-0047, Japan.
Tomohisa HasunumaGraduate School of Science, Technology and Innovation, Kobe University, 1-1 Rokkodai, Nada, Kobe, 657-8501, Japan. hasunuma@port.kobe-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputational 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. Benzylisoquinoline alkaloids (BIAs) are a diverse group of plant-derived compounds with important pharmaceutical properties. BIA biosynthesis has developed into a prime example of metabolic engineering and microbial bioproduction. The early bottleneck of BIA production in Escherichia coli consists of 3,4-dihydroxyphenylacetaldehyde (DHPAA) production and conversion to tetrahydropapaveroline (THP). Previous studies have selected monoamine oxidase (MAO) and DHPAA synthase (DHPAAS) to produce DHPAA from dopamine and oxygen; however, both of these enzymes produce toxic hydrogen peroxide as a byproduct.

resultsIn the current study, in silico pathway design is applied to relieve the bottleneck of DHPAA production in the synthetic BIA pathway. Specifically, the cytochrome P450 enzyme, tyrosine N-monooxygenase (CYP79), is identified to bypass the established MAO- and DHPAAS-mediated pathways in an alternative arylacetaldoxime route to DHPAA with a peroxide-independent mechanism. The application of this pathway is proposed to result in less formation of toxic byproducts, leading to improved production of reticuline (up to 60 mg/L at the flask scale) when compared with that from the conventional MAO pathway.

conclusionsThis study showed improved reticuline production using the bypass pathway predicted by the M-path computational platform. Reticuline production in E. coli exceeded that of the conventional MAO-mediated pathway. The study provides a clear example of the integration of pathway mining and enzyme design in creating artificial metabolic pathways and suggests further potential applications of this strategy in metabolic engineering.

Indexed as

BenzylisoquinolinesEscherichia coliMetabolic Engineering3,4-Dihydroxyphenylacetic AcidBiosynthetic PathwaysComputer SimulationCytochrome P-450 Enzyme SystemTetrahydropapaveroline3,4-Dihydroxyphenylacetic AcidBenzylisoquinolinesCytochrome P-450 Enzyme SystemTetrahydropapaveroline3,4-dihydroxyphenylacetaldoximeArtificial metabolic pathwayBenzylisoquinoline alkaloid productionComputational enzyme miningCytochrome P450Tyrosine N-monooxygenase

Identifiers

PMID38879464
PMCPMC11179272

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.