{"title":"建模符合代谢工程:iPichia共识模型作为Komagataella phaffii代谢研究的基础","authors":"Pınar Kocabaş","doi":"10.1016/j.bej.2025.109940","DOIUrl":null,"url":null,"abstract":"<div><div><em>Komagataella phaffii</em> (syn. <em>Pichia pastoris</em>) has become one of the most commonly employed hosts for recombinant protein expression, with methanol-utilizing (Mut⁺) strains being used to produce more than 400 different proteins. The availability of fully sequenced and functionally annotated genomes has greatly facilitated systems biology studies and enabled the generation of genome-scale metabolic models (GEMs) for this species. In this study, two previously published GEMs (Kp.1.0 and <em>i</em>AUKM) were systematically merged in order to build a unified consensus model, referred to as <em>i</em>Pichia, that offers a more complete description of <em>K. phaffii</em> metabolism for the first time. <em>i</em>Pichia GEM was then extended by introducing enzyme capacity limitations through the GECKO 3.0 framework, yielding an enzyme-constrained genome-scale model (ecPichia GEM) for <em>Komagataella phaffii</em>. The resulting ecPichia GEM is the first enzyme constraint genome scale metabolic model for <em>Komagataella phaffii.</em> The predictive performance of ecPichia GEM for growth was evaluated using data from the literature. Gene essentiality analyses were carried with <em>i</em>Pichia compared to protein-constrained ecPichia GEM, Kp.1.0 and <em>i</em>AUKM GEMs. Thereafter, the model was applied to uncover promising targets for metabolic engineering aimed at producing bisabolene — an industrially relevant sesquiterpene used in both biofuel and fragrance applications. Overall, the results underline the effectiveness of enzyme-constrained metabolic modeling as a tool to support rational strain development in the field of industrial biotechnology.</div></div>","PeriodicalId":8766,"journal":{"name":"Biochemical Engineering Journal","volume":"225 ","pages":"Article 109940"},"PeriodicalIF":3.7000,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling meets metabolic engineering: The iPichia consensus model as basis for metabolic studies in Komagataella phaffii\",\"authors\":\"Pınar Kocabaş\",\"doi\":\"10.1016/j.bej.2025.109940\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div><em>Komagataella phaffii</em> (syn. <em>Pichia pastoris</em>) has become one of the most commonly employed hosts for recombinant protein expression, with methanol-utilizing (Mut⁺) strains being used to produce more than 400 different proteins. The availability of fully sequenced and functionally annotated genomes has greatly facilitated systems biology studies and enabled the generation of genome-scale metabolic models (GEMs) for this species. In this study, two previously published GEMs (Kp.1.0 and <em>i</em>AUKM) were systematically merged in order to build a unified consensus model, referred to as <em>i</em>Pichia, that offers a more complete description of <em>K. phaffii</em> metabolism for the first time. <em>i</em>Pichia GEM was then extended by introducing enzyme capacity limitations through the GECKO 3.0 framework, yielding an enzyme-constrained genome-scale model (ecPichia GEM) for <em>Komagataella phaffii</em>. The resulting ecPichia GEM is the first enzyme constraint genome scale metabolic model for <em>Komagataella phaffii.</em> The predictive performance of ecPichia GEM for growth was evaluated using data from the literature. Gene essentiality analyses were carried with <em>i</em>Pichia compared to protein-constrained ecPichia GEM, Kp.1.0 and <em>i</em>AUKM GEMs. Thereafter, the model was applied to uncover promising targets for metabolic engineering aimed at producing bisabolene — an industrially relevant sesquiterpene used in both biofuel and fragrance applications. Overall, the results underline the effectiveness of enzyme-constrained metabolic modeling as a tool to support rational strain development in the field of industrial biotechnology.</div></div>\",\"PeriodicalId\":8766,\"journal\":{\"name\":\"Biochemical Engineering Journal\",\"volume\":\"225 \",\"pages\":\"Article 109940\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biochemical Engineering Journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1369703X25003146\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biochemical Engineering Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1369703X25003146","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}
Modeling meets metabolic engineering: The iPichia consensus model as basis for metabolic studies in Komagataella phaffii
Komagataella phaffii (syn. Pichia pastoris) has become one of the most commonly employed hosts for recombinant protein expression, with methanol-utilizing (Mut⁺) strains being used to produce more than 400 different proteins. The availability of fully sequenced and functionally annotated genomes has greatly facilitated systems biology studies and enabled the generation of genome-scale metabolic models (GEMs) for this species. In this study, two previously published GEMs (Kp.1.0 and iAUKM) were systematically merged in order to build a unified consensus model, referred to as iPichia, that offers a more complete description of K. phaffii metabolism for the first time. iPichia GEM was then extended by introducing enzyme capacity limitations through the GECKO 3.0 framework, yielding an enzyme-constrained genome-scale model (ecPichia GEM) for Komagataella phaffii. The resulting ecPichia GEM is the first enzyme constraint genome scale metabolic model for Komagataella phaffii. The predictive performance of ecPichia GEM for growth was evaluated using data from the literature. Gene essentiality analyses were carried with iPichia compared to protein-constrained ecPichia GEM, Kp.1.0 and iAUKM GEMs. Thereafter, the model was applied to uncover promising targets for metabolic engineering aimed at producing bisabolene — an industrially relevant sesquiterpene used in both biofuel and fragrance applications. Overall, the results underline the effectiveness of enzyme-constrained metabolic modeling as a tool to support rational strain development in the field of industrial biotechnology.
期刊介绍:
The Biochemical Engineering Journal aims to promote progress in the crucial chemical engineering aspects of the development of biological processes associated with everything from raw materials preparation to product recovery relevant to industries as diverse as medical/healthcare, industrial biotechnology, and environmental biotechnology.
The Journal welcomes full length original research papers, short communications, and review papers* in the following research fields:
Biocatalysis (enzyme or microbial) and biotransformations, including immobilized biocatalyst preparation and kinetics
Biosensors and Biodevices including biofabrication and novel fuel cell development
Bioseparations including scale-up and protein refolding/renaturation
Environmental Bioengineering including bioconversion, bioremediation, and microbial fuel cells
Bioreactor Systems including characterization, optimization and scale-up
Bioresources and Biorefinery Engineering including biomass conversion, biofuels, bioenergy, and optimization
Industrial Biotechnology including specialty chemicals, platform chemicals and neutraceuticals
Biomaterials and Tissue Engineering including bioartificial organs, cell encapsulation, and controlled release
Cell Culture Engineering (plant, animal or insect cells) including viral vectors, monoclonal antibodies, recombinant proteins, vaccines, and secondary metabolites
Cell Therapies and Stem Cells including pluripotent, mesenchymal and hematopoietic stem cells; immunotherapies; tissue-specific differentiation; and cryopreservation
Metabolic Engineering, Systems and Synthetic Biology including OMICS, bioinformatics, in silico biology, and metabolic flux analysis
Protein Engineering including enzyme engineering and directed evolution.