Evidence map›Paper›PMID 42436509›Full record

ArticleJournal of biological engineering2026

An advanced genome engineering platform for Komagataella phaffii enabling versatile in vivo DNA assembly and multiplex integration.

Yujung Choi, Ayoung Kim, Nam Kyu Kang

Abstract read
In one paragraph

Article in Journal of biological engineering, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Yujung ChoiDepartment of Chemical Engineering, College of Engineering, Kyung Hee University, Yongin, 17104, Republic of Korea.
Ayoung KimDepartment of Chemical Engineering, College of Engineering, Kyung Hee University, Yongin, 17104, Republic of Korea.
Nam Kyu KangDepartment of Chemical Engineering, College of Engineering, Kyung Hee University, Yongin, 17104, Republic of Korea. nkkang@khu.ac.kr.

Funding

Korea Evaluation Institute of Industrial Technology 20025698National Research Foundation of Korea RS-2025-02214232
6 · The paper itself

Abstract

backgroundThe transition toward a sustainable bioeconomy necessitates the development of robust microbial platforms capable of C1 chemical valorization, particularly the conversion of methanol into high-value chemicals. Komagataella phaffii is a premier methylotrophic host for such applications due to its natural methanol utilization pathways and high-density fermentation capabilities. However, its potential as a C1-based synthetic biology chassis has been hampered by inefficient homologous recombination and the technical complexity of multigene pathway integration. To accelerate the design-build-test-learn (DBTL) cycle for methanol-based biomanufacturing, a more sophisticated and high-throughput genome engineering toolkit is required.

resultsWe report the development of an HR-enhanced K. phaffii chassis (dKR) achieved by synergistically deleting Ku70 and overexpressing RAD52 at the chromosomal level. This engineering markedly improved the robustness and reproducibility of CRISPR/Cas9-mediated genome editing, increasing integration efficiency from 15.3% in the wild-type to 68.1% in the dKR chassis when using short 50-bp homology arms. The platform demonstrated exceptional capacity for vector-free multi-fragment assembly, achieving an integration efficiency of 86.5% for nine linear DNA fragments. Furthermore, the implementation of a tRNA-ribozyme CRISPR system enabled simultaneous multi-locus integration at three distinct genomic sites with 44.6% efficiency. Notably, the chassis supported direct in vivo plasmid assembly of ten fragments (9 fragments + 1 backbone) with 44.8% efficiency, effectively bypassing E. coli-based cloning. Functional validation via a carotenoid biosynthetic pathway resulted in β-carotene production while maintaining normal cellular growth and metabolic productivity.

conclusionThis study established a versatile genome-engineering platform that advances K. phaffii from a protein-expression host to a broadly applicable biological engineering chassis. By enabling streamlined cellular design and reproducible multigene integration, the platform supports applications spanning synthetic biology, metabolic engineering, and bioproduction. More broadly, the approach illustrates how rational manipulation of DNA repair pathways can enhance genome engineering performance in non-conventional hosts, providing transferable design principles relevant to biological engineering across multiple domains.

Indexed as

CRISPR/Cas9In vivo DNA assemblyKomagataella phaffiiMultiplex genome editing

Identifiers

PMID42436509
PMCPMC13640322

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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.