Optimized Biosynthetic Pathway for Nonnatural Amino Acids: An Efficient Approach for L-2-Aminobutyric Acid Production

IF 3.5 2区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Jianmiao Xu, Yuan Tao, Qilan Shan, Yan Feng, Yihong Wang, Zhiqiang Liu, Yuguo Zheng
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引用次数: 0

Abstract

L-2-Aminobutyric acid (L-2-ABA) is a nonnatural chiral α-amino acid which is widely used in various chiral pharmaceuticals and medical intermediates. Currently, the microbial metabolic engineering approach to enable Escherichia coli to produce L-2-ABA autonomously exists the problem of low synthesis efficiency, limiting its large-scale application. In this study, we successfully constructed a strain of E. coli that can produce L-2-ABA efficiently via multi-pathway transformation. Firstly, the growth defect of the start strain was restored by the help of screening transcriptional regulators. To maximize the accumulation of L-2-ABA, enhancements were made to the main synthetic pathways as well as cofactor systems and energy supply. Subsequently, transport proteins associated with osmotic stress tolerance were modified to improve adaptability of the strain during fermentation. Ultimately, the titer of L-2-ABA reached 42.14 g/L through the final strain ABAT38 in a 5-liter bioreactor, with a productivity of 0.40 g/L/h and a glucose conversion of 0.39 g/g, which exceeded the highest levels reported before. The strategies proposed in this study contribute to the production of L-2-ABA. At the same time, it has reference significance for the biosynthesis of related nonnatural amino acids with phosphoenolpyruvate as the intermediate metabolite.
非天然氨基酸的优化生物合成途径:l -2-氨基丁酸生产的有效途径
l -2-氨基丁酸(L-2-ABA)是一种非天然的手性α-氨基酸,广泛应用于各种手性药物和医药中间体。目前,利用微生物代谢工程方法使大肠杆菌自主生产L-2-ABA存在合成效率低的问题,限制了其大规模应用。在本研究中,我们成功构建了一株能够通过多途径转化高效产生L-2-ABA的大肠杆菌。首先,通过筛选转录调控因子,恢复了起始菌株的生长缺陷;为了最大限度地积累L-2-ABA,对主要合成途径、辅因子系统和能量供应进行了增强。随后,对与渗透胁迫耐受性相关的转运蛋白进行了修饰,以提高菌株在发酵过程中的适应性。最终菌株ABAT38在5升的生物反应器中,L-2- aba滴度达到42.14 g/L,产率为0.40 g/L/h,葡萄糖转化率为0.39 g/g,超过以往报道的最高水平。本研究提出的策略有助于L-2-ABA的产生。同时,对以磷酸烯醇丙酮酸为中间代谢物的相关非天然氨基酸的生物合成具有参考意义。
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来源期刊
Biotechnology and Bioengineering
Biotechnology and Bioengineering 工程技术-生物工程与应用微生物
CiteScore
7.90
自引率
5.30%
发文量
280
审稿时长
2.1 months
期刊介绍: Biotechnology & Bioengineering publishes Perspectives, Articles, Reviews, Mini-Reviews, and Communications to the Editor that embrace all aspects of biotechnology. These include: -Enzyme systems and their applications, including enzyme reactors, purification, and applied aspects of protein engineering -Animal-cell biotechnology, including media development -Applied aspects of cellular physiology, metabolism, and energetics -Biocatalysis and applied enzymology, including enzyme reactors, protein engineering, and nanobiotechnology -Biothermodynamics -Biofuels, including biomass and renewable resource engineering -Biomaterials, including delivery systems and materials for tissue engineering -Bioprocess engineering, including kinetics and modeling of biological systems, transport phenomena in bioreactors, bioreactor design, monitoring, and control -Biosensors and instrumentation -Computational and systems biology, including bioinformatics and genomic/proteomic studies -Environmental biotechnology, including biofilms, algal systems, and bioremediation -Metabolic and cellular engineering -Plant-cell biotechnology -Spectroscopic and other analytical techniques for biotechnological applications -Synthetic biology -Tissue engineering, stem-cell bioengineering, regenerative medicine, gene therapy and delivery systems The editors will consider papers for publication based on novelty, their immediate or future impact on biotechnological processes, and their contribution to the advancement of biochemical engineering science. Submission of papers dealing with routine aspects of bioprocessing, description of established equipment, and routine applications of established methodologies (e.g., control strategies, modeling, experimental methods) is discouraged. Theoretical papers will be judged based on the novelty of the approach and their potential impact, or on their novel capability to predict and elucidate experimental observations.
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