建模符合代谢工程:iPichia共识模型作为Komagataella phaffii代谢研究的基础

IF 3.7 3区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Pınar Kocabaş
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引用次数: 0

摘要

Komagataella phaffii(同毕赤酵母)已经成为重组蛋白表达最常用的宿主之一,利用甲醇(Mut +)的菌株被用来生产400多种不同的蛋白质。全测序和功能注释基因组的可用性极大地促进了系统生物学研究,并使该物种的基因组尺度代谢模型(GEMs)的产生成为可能。在本研究中,系统地合并了之前发表的两个GEMs (Kp.1.0和iAUKM),以建立一个统一的共识模型,称为iPichia,首次提供了更完整的法菲氏K.代谢描述。然后通过GECKO 3.0框架引入酶容量限制,扩展了iPichia GEM,得到了Komagataella phaffii的酶约束基因组规模模型(ecPichia GEM)。由此建立的ecPichia GEM是首个法菲Komagataella phaffii酶约束基因组尺度代谢模型。利用文献数据对ecPichia GEM的生长预测性能进行了评估。与蛋白约束的ecPichia GEM、Kp.1.0和iAUKM GEMs进行基因重要性分析。此后,该模型被应用于发现代谢工程的有希望的目标,旨在生产双abolene -一种工业上相关的倍半萜,用于生物燃料和香料应用。总的来说,这些结果强调了酶约束代谢模型作为支持工业生物技术领域合理菌株开发的工具的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
Biochemical Engineering Journal
Biochemical Engineering Journal 工程技术-工程:化工
CiteScore
7.10
自引率
5.10%
发文量
380
审稿时长
34 days
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.
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