R. toruloides 甲羟戊酸途径基因在提高 S. cerevisiae 中异戊二烯产量方面的潜力:对 GGPPS 和 HMG-CoA 还原酶的评估

IF 3.4 3区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Enzyme and Microbial Technology Pub Date : 2023-12-13 DOI:10.1016/j.enzmictec.2023.110374
Sri Harsha Adusumilli , Govinda Rao Dabburu , Manish kumar , Prateek Arora , Banani Chattopadhyaya , Diptimayee Behera , Anand Kumar Bachhawat
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引用次数: 0

摘要

需要改进甲羟戊酸途径的酶,以便在酿酒酵母(Saccharomyces cerevisiae)中获得较高的异戊烯酸产量。红酵母 Rhodosporidium toruloides 能产生大量类胡萝卜素,可能在进化过程中自然产生了大量异戊烯酸。来自这类酵母的酶很可能是有希望改进的候选酶。为此,我们系统地研究了 R. toruloides 甲羟戊酸途径中的各种酶,并在 S. cerevisiae 中定制合成、表达和评估了六种关键酶。通过目视类胡萝卜素筛选,发现 R. toruloides 的两种节点酶--香叶基焦磷酸合成酶(RtGGPPS)和截短的 HMG-CoA 还原酶(RttHMG)--对细胞生产异戊烯类化合物具有显著优势。对这两种酶进行了进一步分析,并尝试进一步改进。从体外活性测定和体内生产异源二萜类香紫苏醇的情况来看,RtGGGPPS 被证实优于 S. cerevisiae 酶。通过合理诱变产生了四个突变体,但无法进一步提高活性。就 RttHMG 而言,对该酶的功能评估显示,尽管它在 S. cerevisiae 中运行良好,但却非常不稳定。我们通过突变催化区的一个保守丝氨酸成功地稳定了该酶,但这并没有改变酶的活性本身。对突变体的体内评估显示,它可以提高香紫苏醇的产量。因此,这两种来自红酵母的酶是异源异戊二烯生产的极佳候选酶。
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The potential of R. toruloides mevalonate pathway genes in increasing isoprenoid yields in S. cerevisiae: Evaluation of GGPPS and HMG-CoA reductase

The enzymes of the mevalonate pathway need to be improved to achieve high yields of isoprenoids in the yeast Saccharomyces cerevisiae. The red yeast Rhodosporidium toruloides produces high levels of carotenoids and may have evolved to carry a naturally high flux of isoprenoids. Enzymes from such yeasts are likely to be promising candidates for improvement. Towards this end, we have systematically investigated the various enzymes of the mevalonate pathway of R. toruloides and custom synthesized, expressed, and evaluated six key enzymes in S. cerevisiae. The two nodal enzymes geranyl pyrophosphate synthase (RtGGPPS) and truncated HMG-CoA reductase (RttHMG) of R. toruloides showed a significant advantage to the cells for isoprenoid production as seen by a visual carotenoid screen. These two were analyzed further, and attempts were also made at further improvement. RtGGPPS was confirmed to be superior to the S. cerevisiae enzyme, as seen from in vitro activity determinations and in vivo production of the heterologous diterpenoid sclareol. Four mutants were created through rational mutagenesis but were unable to improve the activity further. In the case of RttHMG, functional evaluation of the enzyme revealed that it was very unstable despite functioning very well in S. cerevisiae. We succeeded in stabilizing the enzyme through mutation of a conserved serine in the catalytic region, which did not alter the enzyme activity per se. In vivo evaluation of the mutant revealed that it could enable better sclareol yields. Therefore, these two enzymes from the red yeast are excellent candidates for heterologous isoprenoid production.

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来源期刊
Enzyme and Microbial Technology
Enzyme and Microbial Technology 生物-生物工程与应用微生物
CiteScore
7.60
自引率
5.90%
发文量
142
审稿时长
38 days
期刊介绍: Enzyme and Microbial Technology is an international, peer-reviewed journal publishing original research and reviews, of biotechnological significance and novelty, on basic and applied aspects of the science and technology of processes involving the use of enzymes, micro-organisms, animal cells and plant cells. We especially encourage submissions on: Biocatalysis and the use of Directed Evolution in Synthetic Biology and Biotechnology Biotechnological Production of New Bioactive Molecules, Biomaterials, Biopharmaceuticals, and Biofuels New Imaging Techniques and Biosensors, especially as applicable to Healthcare and Systems Biology New Biotechnological Approaches in Genomics, Proteomics and Metabolomics Metabolic Engineering, Biomolecular Engineering and Nanobiotechnology Manuscripts which report isolation, purification, immobilization or utilization of organisms or enzymes which are already well-described in the literature are not suitable for publication in EMT, unless their primary purpose is to report significant new findings or approaches which are of broad biotechnological importance. Similarly, manuscripts which report optimization studies on well-established processes are inappropriate. EMT does not accept papers dealing with mathematical modeling unless they report significant, new experimental data.
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