Engineering allosteric inhibition of homoserine dehydrogenase by semi-rational saturation mutagenesis screening

Liu, Xinyang; Liu, Jiao; Liu, Zhemin; Qiao, Qianqian; Ni, Xiaomeng; Yang, Jinxing; Sun, Guannan; Li, Fanghe; Zhou, Wenjuan; Guo, Xuan; Chen, Jiuzhou; Jia, Shiru; Zheng, Yu; Zheng, Ping; Sun, Jibin

doi:10.3389/fbioe.2023.1336215

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…However, the crystal structure of CgHSD (P08499, the HSD of Corynebacterium glutamicum) remains unreported, and the subunit structure is absent from UniProt databases. DeepSub predicts CgHSD to be a homotetramer, consistent with prior research confirming its oligomeric state via size-exclusion chromatography (SEC) [26]. However, QUEEN incorrectly predicts it as a homodimer in this particular example (Table 3).…”

Section: Case Studysupporting

confidence: 77%

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DeepSub: Utilizing Deep Learning for Predicting the Number of Subunits in Homo-Oligomeric Protein Complexes

Deng,

Wu,

Lin

et al. 2024

IJMS

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The molecular weight (MW) of an enzyme is a critical parameter in enzyme-constrained models (ecModels). It is determined by two factors: the presence of subunits and the abundance of each subunit. Although the number of subunits (NS) can potentially be obtained from UniProt, this information is not readily available for most proteins. In this study, we addressed this gap by extracting and curating subunit information from the UniProt database to establish a robust benchmark dataset. Subsequently, we propose a novel model named DeepSub, which leverages the protein language model and Bi-directional Gated Recurrent Unit (GRU), to predict NS in homo-oligomers solely based on protein sequences. DeepSub demonstrates remarkable accuracy, achieving an accuracy rate as high as 0.967, surpassing the performance of QUEEN. To validate the effectiveness of DeepSub, we performed predictions for protein homo-oligomers that have been reported in the literature but are not documented in the UniProt database. Examples include homoserine dehydrogenase from Corynebacterium glutamicum, Matrilin-4 from Mus musculus and Homo sapiens, and the Multimerins protein family from M. musculus and H. sapiens. The predicted results align closely with the reported findings in the literature, underscoring the reliability and utility of DeepSub.

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Section: Case Studysupporting

confidence: 77%

“…exclusion chromatography (SEC) [26]. However, QUEEN incorrectly predicts it as a homodimer in this particular example (Table 3).…”

Section: Case Studymentioning

confidence: 94%

DeepSub: Utilizing Deep Learning for Predicting the Number of Subunits in Homo-Oligomeric Protein Complexes

Deng,

Wu,

Lin

et al. 2024

IJMS

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Metabolic engineering of Corynebacterium glutamicum: Unlocking its potential as a key cell factory platform for organic acid production

Li,

Zhang

et al. 2024

Biotechnology Advances

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Fine-Regulating the Carbon Flux of l-Isoleucine Producing Corynebacterium glutamicum WM001 for Efficient l-Threonine Production

Zhao,

Zhang,

Zhou

et al. 2024

ACS Synth. Biol.

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L-Threonine, an essential amino acid, is widely used in various industries, with an annually growing demand. However, the present Corynebacterium glutamicum strains are difficult to achieve industrialization of L-threonine due to low yield and purity. In this study, we engineered an L-isoleucine-producing C. glutamicum WM001 to efficiently produce L-threonine by finely regulating the carbon flux. First, the threonine dehydratase in WM001 was mutated to lower the level of L-isoleucine production, then the homoserine dehydrogenase and aspartate kinase were mutated to release the feedback inhibition of L-threonine, and the resulting strain TWZ006 produced 14.2 g/L L-threonine. Subsequently, aspartate ammonia-lyase and aspartate transaminase were overexpressed to accumulate the precursor L-aspartate. Next, phosphoenolpyruvate carboxylase, pyruvate carboxylase and pyruvate kinase were overexpressed, and phosphoenolpyruvate carboxykinase, oxaloacetate decarboxylase were inactivated to fine-regulate the carbon flux among oxaloacetate, pyruvate and phosphoenolpyruvate. The resulting strain TWZ017 produced 21.5 g/L L-threonine. Finally, dihydrodipicolinate synthase was mutated with strong allosteric inhibition from L-lysine to significantly decrease byproducts accumulation, L-threonine export was optimized, and the final engineered strain TWZ024/pXTuf-thrE produced 78.3 g/L of Lthreonine with the yield of 0.33 g/g glucose and the productivity of 0.82 g/L/h in a 7 L bioreactor. To the best of our knowledge, this represents the highest L-threonine production in C. glutamicum, providing possibilities for industrial-scale production.

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Engineering allosteric inhibition of homoserine dehydrogenase by semi-rational saturation mutagenesis screening

Cited by 3 publications

References 28 publications

DeepSub: Utilizing Deep Learning for Predicting the Number of Subunits in Homo-Oligomeric Protein Complexes

DeepSub: Utilizing Deep Learning for Predicting the Number of Subunits in Homo-Oligomeric Protein Complexes

Metabolic engineering of Corynebacterium glutamicum: Unlocking its potential as a key cell factory platform for organic acid production

Fine-Regulating the Carbon Flux of l-Isoleucine Producing Corynebacterium glutamicum WM001 for Efficient l-Threonine Production

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