A novel, genetically encoded whole-cell biosensor for directed evolution of myrcene synthase in Escherichia coli

Chen, Chang; Li, Jiajia; Ge, Yao; Bao, Shaoheng; Wan, Xiukun; Wang, Fuli; Wang, Kang; Song, Tianyu; Han, Penggang; Liu, Tiangang; Jiang, Hui

doi:10.1016/j.bios.2023.115176

Cited by 13 publications

(13 citation statements)

References 26 publications

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“…Geraniol, linalool and myrcene were all generated with geranyl diphosphate as their precursor ( Figure 7 ). Linalool is synthesized by linalool synthase using geranyl diphosphate as a precursor or by linalool dehydratase catalyzed myrcene [ 42 ], and myrcene is produced from geranyl diphosphate by myrcene synthase [ 43 ]. The results showed that linalool and myrcene are detected in all selected Zingiberaceae plants, indicating the similarity in this pathway of the selected Zingiberaceae species.…”

Section: Discussionmentioning

confidence: 99%

Widely Targeted Volatilomics and Metabolomics Analysis Reveal the Metabolic Composition and Diversity of Zingiberaceae Plants

Zhang

Yuan

et al. 2023

Metabolites

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Zingiberaceae plants are widely used in the food and pharmaceutical industries; however, research on the chemical composition and interspecific differences in the metabolome and volatilome of Zingiberaceae plants is still limited. In this study, seven species of Zingiberaceae plants were selected, including Curcuma longa L., Zingiber officinale Rosc., Alpinia officinarum Hance, Alpinia tonkinensis Gagnep, Amomum tsaoko Crevost et Lemarie, Alpinia hainanensis K. Schum. and Amomum villosum Lour. Myristica fragrans Houtt. was also selected due to its flavor being similar to that of the Zingiberaceae plant. The metabolome and volatilome of selected plants were profiled by widely targeted approaches; 542 volatiles and 738 non-volatile metabolites were detected, and β-myrcene, α-phellandrene and α-cadinene were detected in all the selected plants, while chamigren, thymol, perilla, acetocinnamone and cis-α-bisabolene were exclusively detected in certain Zingiberaceae plants. Differential analysis showed that some terpenoids, such as cadalene, cadalene-1,3,5-triene, cadalene-1,3,8-triene and (E)-β-farnesene, and some lipids, including palmitic acid, linoleic acid and oleic acid were amongst the most varied compounds in Zingiberaceae plants. In conclusion, this study provided comprehensive metabolome and volatilome profiles for Zingiberaceae plants and revealed the metabolic differences between these plants. The results of this study could be used as a guide for the nutrition and flavor improvement of Zingiberaceae plants.

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Section: Discussionmentioning

confidence: 99%

Widely Targeted Volatilomics and Metabolomics Analysis Reveal the Metabolic Composition and Diversity of Zingiberaceae Plants

Zhang

Yuan

et al. 2023

Metabolites

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“…Nevertheless, enzymatic assays indicated that only four TALs displayed increased activity. Chen et al 25 .…”

Section: Mpek Assistance In Enzyme Mining and Evolutionmentioning

confidence: 99%

“…Moreover, considering that kcat and Km are intrinsically connected 15,25 , and there is no unified model that can learn this intrinsic connection, it is judicious to apply multi-task learning to learn this connection and predict kcat and Km simultaneously.…”

Section: Introductionmentioning

confidence: 99%

MPEK: a multi-task learning based on pre-trained language model for predicting enzymatic reaction kinetic parameters

Jiang,

Wang,

Yang

et al. 2024

Preprint

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Enzymatic reaction kinetics are central in analyzing enzymatic reaction mechanisms and target-enzyme optimization, and thus in biomanufacturing and other industries. The enzyme turnover number (kcat) and Michaelis constant (Km), key kinetic parameters for measuring enzyme catalytic efficiency are crucial for analyzing enzymatic reaction mechanisms and the directed evolution of target enzymes. Experimental determination of kcat and Km is costly in terms of time, labor, and cost. To consider the intrinsic connection between kcat and Km and further improve the prediction performance, we propose a universal pre-trained multi-task deep learning model, MPEK, to predict these parameters simultaneously while considering pH, temperature, and organismal information. MPEK achieved superior predictive performance on the whole test dataset. Using the same test dataset, MPEK outperformed other state-of-the-art models. More importantly, MPEK was able to reveal enzyme promiscuity and was sensitive to slight changes in the mutant enzyme sequence. In addition, in three case studies, it was shown MPEK has the potential for assisted enzyme mining and directed evolution. To facilitate in silico evaluation of enzyme catalytic efficiency, we have established a web server implementing this model (http://mathtc.nscc-tj.cn/mpek).

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“…For example, the strain expressing truncated linalool synthases showed an 8-fold increase in linalool production compared to the strain expressing with an untruncated enzyme [92]. For the synthesis of myrcene, the truncation of seven myrcene synthases from different sources revealed that trCsMS from Cannabis sativa exhibited the best activity [70]. Moreover, the activity of the same monoterpene synthase can be affected by different truncation positions.…”

Section: Engineering Of Terpene Synthasesmentioning

confidence: 99%

Biosynthesis Progress of High-Energy-Density Liquid Fuels Derived from Terpenes

Liu,

Lin,

Han

et al. 2024

Microorganisms

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High-energy-density liquid fuels (HED fuels) are essential for volume-limited aerospace vehicles and could serve as energetic additives for conventional fuels. Terpene-derived HED biofuel is an important research field for green fuel synthesis. The direct extraction of terpenes from natural plants is environmentally unfriendly and costly. Designing efficient synthetic pathways in microorganisms to achieve high yields of terpenes shows great potential for the application of terpene-derived fuels. This review provides an overview of the current research progress of terpene-derived HED fuels, surveying terpene fuel properties and the current status of biosynthesis. Additionally, we systematically summarize the engineering strategies for biosynthesizing terpenes, including mining and engineering terpene synthases, optimizing metabolic pathways and cell-level optimization, such as the subcellular localization of terpene synthesis and adaptive evolution. This article will be helpful in providing insight into better developing terpene-derived HED fuels.

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A novel, genetically encoded whole-cell biosensor for directed evolution of myrcene synthase in Escherichia coli

Cited by 13 publications

References 26 publications

Widely Targeted Volatilomics and Metabolomics Analysis Reveal the Metabolic Composition and Diversity of Zingiberaceae Plants

Widely Targeted Volatilomics and Metabolomics Analysis Reveal the Metabolic Composition and Diversity of Zingiberaceae Plants

MPEK: a multi-task learning based on pre-trained language model for predicting enzymatic reaction kinetic parameters

Biosynthesis Progress of High-Energy-Density Liquid Fuels Derived from Terpenes

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