Engineering of cofactor preference and catalytic activity of methanol dehydrogenase by growth-coupled directed evolution

Methanol,produced from carbon dioxide,natural gas,and biomass,has drawn increasing attention as a promising green carbon feedstock for biomanufacturing due to its sustainable and energy-rich properties.Nicotinamide adenine dinucleotide(NAD+)-dependent methanol dehydrogenase(MDH)catalyzes the oxidation of methanol to formaldehyde via NADH generation,providing a highly active C1 intermediate and reducing power for subsequent biosynthesis.However,the unsatisfactory catalytic efficiency and cofactor bias of MDH significantly impede methanol valorization,especially in nicotinamide adenine dinucleotide phosphate(NADP+)-dependent biosynthesis.Herein,we employed synthetic NADH and NADPH auxotrophic Escherichia coli strains as growth-coupled selection platforms for the directed evolution of MDH from Bacillus stearothermophilus DSM 2334.NADH or NADPH generated by MDH-catalyzed methanol oxidation enabled the growth of synthetic cofactor auxotrophs,establishing a positive correlation between the cell growth rate and MDH activity.Using this principle,MDH mutants exhibiting a 20-fold improvement in catalytic efficiency(kcat/Km)and a 90-fold cofactor specificity switch from NAD+to NADP+without a decrease in specific enzyme activity,were efficiently screened from random and semi-rationally designed libraries.We envision that these mutants will advance methanol valorization and that the synthetic cofactor auxotrophs will serve as versatile selection platforms for the evolution of NAD(P)+-dependent enzymes.

Genome-scale CRISPRi screening:A powerful tool in engineering microbiology

Deciphering gene function is fundamental to engineering of microbiology.The clustered regularly interspaced short palindromic repeats(CRISPR)system has been adapted for gene repression across a range of hosts,creating a versatile tool called CRISPR interference(CRISPRi)that enables genome-scale analysis of gene function.This approach has yielded significant advances in the design of genome-scale CRISPRi libraries,as well as in applica-tions of CRISPRi screening in medical and industrial microbiology.This review provides an overview of the recent progress made in pooled and arrayed CRISPRi screening in microorganisms and highlights representative studies that have employed this method.Additionally,the challenges associated with CRISPRi screening are discussed,and potential solutions for optimizing this strategy are proposed.

A new era for paclitaxel biosynthesis is coming

Paclitaxel(Taxol)stands out as a tetracyclic diterpenoid natural product derived from the endangered plant Taxus.Recognized as a pivotal broad-spectrum anticancer drug,it has garnered widespread attention due to its low yield,intricate structure,unique anticancer mechanism,and remarkable efficacy(Tong et al.,2021).Although chemists achieved the total synthesis of paclitaxel 30 years ago,after decades of research,the natural biosynthetic pathway for its production remains an enigma(Ajikumar et al.,2010;Malci et al.,2023).A recent breakthrough,published in Molecular Plant by Alisdair R.Fernie's team,unveils a minimal gene set of 18 genes required for paclitaxel biosynthesis(Zhang et al.,2023),representing a significant mark toward unraveling the entire biosynthetic pathway and enhancing paclitaxel production efficiency.

Complete biosynthesis of the phenylethanoid glycoside verbascoside

Verbascoside,which was first discovered in 1963,is a well-known phenylethanoid glycoside(PhG)that exhibits antioxidant,anti-inflammatory,antimicrobial,and neuroprotective activities and contributes to the therapeutic effects of many medicinal plants.However,the biosynthetic pathway of verbascoside remains to be fully elucidated.Here,we report the identification of two missing enzymes in the verbascoside biosynthesis pathway by transcriptome mining and in vitro enzymatic assays.Specifically,a BAHD acyltransferase(hydroxycinnamoyl-CoA:salidroside hydroxycinnamoyltransferase[SHCT])was shown to catalyze the regioselective acylation of salidroside to form osmanthuside A,and a CYP98 hydroxylase(osmanthuside B 3,30-hydroxylase[OBH])was shown to catalyze meta-hydroxylations of the p-coumaroyl and tyrosol moieties of osmanthuside B to complete the biosynthesis of verbascoside.Because SHCTs and OBHs are found in many Lamiales species that produce verbascoside,this pathway may be general.The findings from the study provide novel insights into the formation of caffeoyl and hydroxytyrosol moieties in natural product biosynthetic pathways.In addition,with the newly acquired enzymes,we achieved heterologous production of osmanthuside B,verbascoside,and ligupurpuroside B in Escherichia coli;this work lays a foundation for sustainable production of verbascoside and other PhGs in micro-organisms.

二氧化碳到己糖的人工合成

土地短缺及环境恶化导致依赖光合作用的糖制造技术面临诸多挑战.当前人工CO_(2)-糖合成技术在立体选择性转化、降低能量消耗、扩展产物谱等方面亟待突破.本文设计了低ATP消耗、路线短且普适性强的CO_(2)-糖路线,能量转化效率高于传统制糖方法.结合酶工程技术获得了催化性能优异的酶元件,构建了化学-酶转化体系,实现转化CO_(2)合成葡萄糖、阿洛酮糖等己糖分子,具有较高的产物选择性和碳转化率,CO_(2)-糖合成效率为目前报道最高水平.本研究为创制结构多样性糖及其衍生物,解决人类食糖与健康、工业发酵等糖需求提供蓝图和方案.

pUGTdb:A comprehensive database of plant UDP-dependent glycosyltransferases

Dear Editor,Plant UDP-dependent glycosyltransferases(UGTs),belonging to the carbohydrate-active enzyme glycosyltransferase 1 family(Louveau and Osbourn,2019),not only play important roles in adaptation to various environments(Cai et al.,2020;Pastorczyk-Szlenkier and Bednarek,2021)but also endow plant natural products with great pharmaceutical and ecological significance(Margolin et al.,2020).In recent years,an increasing number of plant UGTs have been characterized to function in the biosynthesis of many bioactive compounds such as ginsenosides(Wei et al.,2015),breviscapine(Liu et al.,2018),and rubusoside(Xu et al.,2022).

用农作物秸秆高效生物合成人造淀粉和单细胞蛋白

全球人口快速增长和气候变化正在引发可能的粮食危机.本研究开发了一种利用现有且丰富的农业废弃物(秸秆)高效合成人造淀粉和微生物蛋白的新技术.利用没有辅酶的体外多酶分子机器和酿酒酵母进行一锅法生物转化,将预处理玉米秸秆中的纤维素进行酶水解合成人造淀粉,同时在有氧条件下发酵生产微生物蛋白.低成本去除β-葡萄糖糖苷酶的商业化纤维素酶以及在酿酒酵母细胞表面展示骨架蛋白用于固定淀粉磷酸化酶和纤维二糖磷酸化酶,构成一个多酶分子机器与酵母的复合体系,从而实现稀酸预处理秸秆的高效纤维素水解;利用纤维素水解中间产物的底物穿梭效应(从纤维素到微生物),快速消除葡萄糖对纤维素酶的产物抑制,比富含商业β-葡萄糖苷酶的纤维素酶混合物表现出更好的纤维素水解速率.动物实验结果显示,人造直链淀粉摄入引起缓慢平缓的血糖水平变化,表明直链淀粉作为预防肥胖和糖尿病的健康食品的应用前景.利用农业废弃物资源高效生物合成人造淀粉和微生物蛋白是解决粮食危机,实现农业可持续发展的重要途径之一.

Origin and evolution of the main starch biosynthetic enzymes

Starch,a semi-crystalline energy storage form primarily found in plant plastids plays a crucial role in various food or no-food applications.Despite the starch biosynthetic pathway’s main enzymes have been characterized,their origin and evolution remained a subject of debate.In this study,we conducted the comprehensive phylogenetic and structural analysis of three types of starch biosynthetic enzymes:starch synthase(SS),starch branching enzyme(SBE)and isoamylase-type debranching enzyme(ISA)from 51,151 annotated genomes.Our findings provide valuable insights into the possible scenario for the origin and evolution of the starch biosynthetic pathway.Initially,the ancestor of SBE can be traced back to an unidentified bacterium that existed before the formation of the last eukaryotic common ancestor(LECA)via horizontal gene transfer(HGT).This transfer event likely provided the eukaryote ancestor with the ability to synthesize glycogen.Furthermore,during the emergence of Archaeplastida,one clade of SS was transferred from Deltaproteobacteria by HGT,while ISA and the other clade of SS originated from Chlamydiae through endosymbiosis gene transfer(EGT).Both these transfer events collectively contributed to the establishment of the original starch biosynthetic pathway.Subsequently,after the divergence of Viridiplantae from Rhodophyta,all three enzymes underwent multiple duplications and N-terminus extension domain modifications,resulting in the formation of functionally specialized isoforms and ultimately leading to the complete starch biosynthetic pathway.By shedding light on the evolutionary origins of key enzymes involved in the starch biosynthetic pathway,this study provides important insights into the evolutionary events of plants.

Directed evolution of a neutrophilic and mesophilic methanol dehydrogenase based on high-throughput and accurate measurement of formaldehyde

Methanol is a promising one-carbon feedstock for biomanufacturing,which can be sustainably produced from carbon dioxide and natural gas.However,the efficiency of methanol bioconversion is limited by the poor catalytic properties of nicotinamide adenine dinucleotide(NAD^(+))-dependent methanol dehydrogenase(Mdh)that oxidizes methanol to formaldehyde.Herein,the neutrophilic and mesophilic NAD^(+)-dependent Mdh from Bacillus stearothermophilus DSM 2334(Mdh_(Bs))was subjected to directed evolution for enhancing the catalytic activity.The combination of formaldehyde biosensor and Nash assay allowed high-throughput and accurate measurement of formaldehyde and facilitated efficient selection of desired variants.Mdh_(Bs)variants with up to 6.5-fold higher K_(cat)/K_(M)value for methanol were screened from random mutation libraries.The T153 residue that is spatially proximal to the substrate binding pocket has significant influence on enzyme activity.The beneficial T153P mutation changes the interaction network of this residue and breaks theα-helix important for substrate binding into two shortα-helices.Reconstructing the interaction network of T153 with surrounding residues may represent a promising strategy to further improve Mdh_(Bs),and this study provides an efficient strategy for directed evolution of Mdh.

Enzyme Commission Number Prediction and Benchmarking with Hierarchical Dual-core Multitask Learning Framework

Enzyme commission(EC)numbers,which associate a protein sequence with the biochemical reactions it catalyzes,are essential for the accurate understanding of enzyme functions and cellular metabolism.Many ab initio computational approaches were proposed to predict EC numbers for given input protein sequences.However,the prediction performance(accuracy,recall,and precision),usability,and efficiency of existing methods decreased seriously when dealing with recently discovered proteins,thus still having much room to be improved.Here,we report HDMLF,a hierarchical dual-core multitask learning framework for accurately predicting EC numbers based on novel deep learning techniques.HDMLF is composed of an embedding core and a learning core;the embedding core adopts the latest protein language model for protein sequence embedding,and the learning core conducts the EC number prediction.Specifically,HDMLF is designed on the basis of a gated recurrent unit framework to perform EC number prediction in the multi-objective hierarchy,multitasking manner.Additionally,we introduced an attention layer to optimize the EC prediction and employed a greedy strategy to integrate and fine-tune the final model.Comparative analyses against 4 representative methods demonstrate that HDMLF stably delivers the highest performance,which improves accuracy and F1 score by 60%and 40%over the state of the art,respectively.An additional case study of tyrB predicted to compensate for the loss of aspartate aminotransferase aspC,as reported in a previous experimental study,shows that our model can also be used to uncover the enzyme promiscuity.Finally,we established a web platform,namely,ECRECer(https://ecrecer.biodesign.ac.cn),using an entirely could-based serverless architecture and provided an offline bundle to improve usability.

Reconstruction and metabolic profiling of the genome-scale metabolic network model of Pseudomonas stutzeri A1501

Pseudomonas stutzeri A1501 is a non-fluorescent denitrifying bacteria that belongs to the gram-negative bacterial group.As a prominent strain in the fields of agriculture and bioengineering,there is still a lack of comprehensive understanding regarding its metabolic capabilities,specifically in terms of central metabolism and substrate utilization.Therefore,further exploration and extensive studies are required to gain a detailed insight into these aspects.This study reconstructed a genome-scale metabolic network model for P.stutzeri A1501 and conducted extensive curations,including correcting energy generation cycles,respiratory chains,and biomass composition.The final model,iQY1018,was successfully developed,covering more genes and reactions and having higher prediction accuracy compared with the previously published model iPB890.The substrate utilization ability of 71 carbon sources was investigated by BIOLOG experiment and was utilized to validate the model quality.The model prediction accuracy of substrate utilization for P.stutzeri A1501 reached 90%.The model analysis revealed its new ability in central metabolism and predicted that the strain is a suitable chassis for the production of Acetyl CoA-derived products.This work provides an updated,high-quality model of P.stutzeri A1501for further research and will further enhance our understanding of the metabolic capabilities.