系统代谢工程在微生物定向进化中的应用

系统生物学的迅速发展使人们能够从整体水平上理解细胞的生理生化特性并调控其代谢.系统代谢工程的主要应用之一是以系统生物学为基础对微生物进行定向进化,以期增强细胞对环境胁迫的耐受性,提高目标产品的产量.前者多采用全局转录机制工程和逆代谢工程的方法;后者主要通过设计并导入最优化路径,重构代谢网络及基因的模拟敲除和湿法验证等策略实现.本文综述了利用系统代谢工程解决细胞生物工程几个主要问题的技术及其应用进展.     

从碳代谢流角度新解代谢工程策略

代谢工程通过改造微生物代谢过程,进而利用微生物生产各种有用的医药、化学产品及工业原料.本文从细胞代谢中碳代谢流的角度入手,将代谢工程的传统与新型策略进行分类解析.其中,传统代谢工程手段主要对目标代谢路径的关键酶进行改造,通过过表达或基因敲除增大目的代谢路径碳代谢流.然而,在代谢路径改造需要进行多基因表达的情况下,传统手段在如何最佳表达多种酶使碳流通畅上会受到很大限制.本文提出利用高碳流路径,通过简单基因改造以获得高效目标产物生产的新策略.同时,随着合成生物学与系统生物学的发展,精细调控多基因表达成为可能.本文进一步举例讨论了代谢工程中粗略与精细调控基因表达水平对碳流的影响,以期对教学与前沿科研有助.     

微生物代谢工程原理与应用

代谢工程是利用分子生物学原理系统分析细胞代谢网络,并通过DNA重组技术和应用分析生物学相关的遗传学手段对细胞进行有精确目标的基因操作,改变微生物原有的代谢或调节系统,实现目的产物代谢活性的提高。代谢工程综合了生物化学、化学工程、数学分析等多学科内容,是当前国内外学者研究热点之一。论述了微生物代谢工程的理论基础及其应用进展和前景。     

苯丙氨酸生物合成的研究进展

代谢工程是利用分子生物学原理系统分析代谢途径,设计合理的遗传修饰策略从而优化细胞的生物学特性,本对代谢工程及其在氨基酸生产上的应用进行了简单的回顾,比较了苯丙氨酸的几种合成途径,重点综述了苯丙氨酸生物合成的代谢途径,相关酶及其调控方式,代谢流和转运系统的分析研究,并对苯丙氨酸生产策略的优化及未来发展进行了展望。     

基因组尺度分析和代谢工程策略

代谢工程是近年来发展起来的新技术,随着各种组学技术的发展,高通量数据整合方法用于分析细胞的代谢网络,改造代谢途径,以提高目标产物的产量。本文就代谢工程的发展状况,基因组尺度的分析技术,以及代谢工程策略进行了综述。分析了生物信息学和系统生物学方法在代谢途径构建和代谢网络分析中的作用,并就存在的问题和可能的解决途径进行了阐述。     

放线菌次级代谢途径的设计

近来有关放线菌次级产物生物合成的分子遗传学和生物化学方面的进展为我们改造其代谢途径提供了一个明确的方向。近年来,对微生物的初级代谢途径进行基因改造取得了成功,但放线菌的次级代谢工程产物却都没有达到中试或生产规模。进展如此缓慢的主要原因是放线菌自身复杂的代谢途径以及细胞循环中复杂的调节方式及其特异性。目前人们着力于通过基因操作改造酶,从而重新设计以其催化产物为基本骨架的代谢途径,最终产生修饰的或新的天然终产物。本文将讨论达到此目的的几种设计策略。     

微生物代谢工程的研究进展和展望

代谢工程技术是构建微生物细胞工厂的重要方法,其主要目标是通过基因工程等手段将目标代谢产物产量最大化。然而基因工程等操作往往会影响细胞生长速率,导致其生产强度降低。随着合成生物学及相关技术的发展,多种调控策略被应用于代谢工程领域以解决上述问题。通过这些调控可以有效地解决细胞生长与产物合成之间的竞争关系,平衡代谢途径,避免中间代谢产物的过量积累。对这些策略的研究及应用进行了概述和展望。     

微生物细胞工厂的代谢调控

代谢调控是构建微生物细胞工厂的重要技术手段.随着合成生物学技术的不断突破,挖掘和人工设计的高质量调控元件大幅度提升了对细胞代谢网络的改造能力;代谢调控研究也已从单基因的静态调控发展到系统水平上的智能精确动态调控.文中简要综述了近30年来代谢途径表达调控技术在代谢工程领域的研究进展.     

工业微生物中NADH的代谢调控

NADH是微生物代谢网络中的一种关键辅因子。调节微生物胞内NADH的形式与浓度是定向改变和优化微生物细胞代谢功能, 实现代谢流最大化、快速化地导向目标代谢产物的重要手段之一。以下在详尽总结了NADH生理功能的基础上, 从生化工程(添加外源电子受体、不同氧化还原态底物及NAD合成前体物, 调节培养环境和氧化还原电势)和代谢工程(过量表达NADH代谢相关酶、缺失NADH竞争途径及引入NADH外源代谢途径)两方面分析、归纳了NADH代谢调控策略, 进而凝练出调控NADH/NAD+比率调节微生物细胞代谢功能研究方面亟待解决的3个科学问题及可能的解决途径。     

丝状真菌代谢工程研究进展

丝状真菌(Filamentous fungi)作为重要的工业发酵微生物,在有机酸、蛋白质及次级代谢产物等关键生物基产品生产方面发挥着重要作用.自20世纪90年代代谢工程理念提出以来,尤其是代谢工程使能技术的创新及发展,极大地促进了丝状真菌细胞工厂的构建及其在工业发酵领域的应用.文中将系统介绍近年来丝状真菌代谢工程技术的...     

微生物模块化共培养工程的应用及控制策略

传统的微生物合成方法通常依赖于单一工程菌株,通过代谢工程改造合成目标产物.由于关键的辅因子、前体和能量被引入到复杂的化合物合成途径中,加重了工程菌株的代谢负担,因而常常会影响目标产物产量.而模块化共培养工程已经成为一种有效进行异源生物合成并有望大大提高产物产量的新方法.在模块化共培养工程中,不同模块菌群之间的相互协调对...     

Expanding Metabolic Capabilities Using Novel Pathway Designs: Computational Tools and Case Studies

Design and selection of efficient metabolic pathways is critical for the success of metabolic engineering endeavors. Convenient pathways should not only produce the target metabolite in high yields but also are required to be thermodynamically feasible under production conditions, and to prefer efficient enzymes. To support the design and selection of such pathways, different computational approaches have been proposed for exploring the feasible pathway space under many of the above constraints. In this review, an overview of recent constraint‐based optimization frameworks for metabolic pathway prediction, as well as relevant pathway engineering case studies that highlight the importance of rational metabolic designs is presented. Despite the availability and suitability of in silico design tools for metabolic pathway engineering, scarce—although increasing—application of computational outcomes is found. Finally, challenges and limitations hindering the broad adoption and successful application of these tools in metabolic engineering projects are discussed.     

Microbial 1-butanol production: Identification of non-native production routes and in silico engineering interventions

The potential of engineering microorganisms with non-native pathways for the synthesis of long-chain alcohols has been identified as a promising route to biofuels. We describe computationally derived predictions for assembling pathways for the production of biofuel candidate molecules and subsequent metabolic engineering modifications that optimize product yield. A graph-based algorithm illustrates that, by culling information from BRENDA and KEGG databases, all possible pathways that link the target product with metabolites present in the production host are identified. Subsequently, we apply our recent OptForce procedure to pinpoint reaction modifications that force the imposed product yield in Escherichia coli. We demonstrate this procedure by suggesting new pathways and genetic interventions for the overproduction of 1-butanol using the metabolic model for Escherichia coli. The graph-based search method recapitulates all recent discoveries based on the 2-ketovaline intermediate and hydroxybutyryl-CoA but also pinpointes one novel pathway through thiobutanoate intermediate that to the best of our knowledge has not been explored before.     

Effects of introducing heterologous pathways on microbial metabolism with respect to metabolic optimality

Although optimality of microbial metabolism under genetic and environmental perturbations is well studied, the effects of introducing heterologous reactions on the overall metabolism are not well understood. This point is important in the field of metabolic engineering because heterologous reactions are more frequently introduced into various microbial hosts. The genome-scale metabolic simulations of Escherichia coli strains engineered to produce 1,4-butanediol, 1,3-propanediol, and amorphadiene suggest that microbial metabolism shows much different responses to the introduced heterologous reactions in a strain-specific manner than typical gene knockouts in terms of the energetic status (e.g., ATP and biomass generation) and chemical production capacity. The 1,4-butanediol and 1,3-propanediol producers showed greater metabolic optimality than the wild-type strains and gene knockout mutants for the energetic status, while the amorphadiene producer was metabolically less optimal. For the optimal chemical production capacity, additional gene knockouts were most effective for the strain producing 1,3-propanediol, but not for the one producing 1,4-butanediol. These observations suggest that strains having heterologous metabolic reactions have metabolic characteristics significantly different from those of the wild-type strain and single gene knockout mutants. Finally, comparison of the theoretically predicted and ¹³C-based flux values pinpoints pathways with non-optimal flux values, which can be considered as engineering targets in systems metabolic engineering strategies. To our knowledge, this study is the first attempt to quantitatively characterize microbial metabolisms with different heterologous reactions. The suggested potential reasons behind each strain’s different metabolic responses to the introduced heterologous reactions should be carefully considered in strain designs.     

基于约束的基因组规模代谢网络模型构建方法研究进展

基因组规模代谢网络模型(Genome-scale metabolic network model,GSMM)正成为细胞代谢特性研究的重要工具,经过多年发展相关理论方法取得了诸多进展.近年来,在基础GSMM模型基础上,通过整合基因组、转录组、蛋白组和热力学数据,实现基于各种约束的GSMM构建,在基因靶点识别、系统代谢工程...     

In vitro prototyping of limonene biosynthesis using cell-free protein synthesis

Metabolic engineering of microorganisms to produce sustainable chemicals has emerged as an important part of the global bioeconomy. Unfortunately, efforts to design and engineer microbial cell factories are challenging because design-build-test cycles, iterations of re-engineering organisms to test and optimize new sets of enzymes, are slow. To alleviate this challenge, we demonstrate a cell-free approach termed in vitro Prototyping and Rapid Optimization of Biosynthetic Enzymes (or iPROBE). In iPROBE, a large number of pathway combinations can be rapidly built and optimized. The key idea is to use cell-free protein synthesis (CFPS) to manufacture pathway enzymes in separate reactions that are then mixed to modularly assemble multiple, distinct biosynthetic pathways. As a model, we apply our approach to the 9-step heterologous enzyme pathway to limonene in extracts from Escherichia coli. In iterative cycles of design, we studied the impact of 54 enzyme homologs, multiple enzyme levels, and cofactor concentrations on pathway performance. In total, we screened over 150 unique sets of enzymes in 580 unique pathway conditions to increase limonene production in 24 h from 0.2 to 4.5 mM (23–610 mg/L). Finally, to demonstrate the modularity of this pathway, we also synthesized the biofuel precursors pinene and bisabolene. We anticipate that iPROBE will accelerate design-build-test cycles for metabolic engineering, enabling data-driven multiplexed cell-free methods for testing large combinations of biosynthetic enzymes to inform cellular design.     

Network methods for describing sample relationships in genomic datasets: application to Huntington’s disease

Background

We consider the possibility of engineering metabolic pathways in a chassis organism in order to synthesize novel target compounds that are heterologous to the chassis. For this purpose, we model metabolic networks through hypergraphs where reactions are represented by hyperarcs. Each hyperarc represents an enzyme-catalyzed reaction that transforms set of substrates compounds into product compounds. We follow a retrosynthetic approach in order to search in the metabolic space (hypergraphs) for pathways (hyperpaths) linking the target compounds to a source set of compounds.

Results

To select the best pathways to engineer, we have developed an objective function that computes the cost of inserting a heterologous pathway in a given chassis organism. In order to find minimum-cost pathways, we propose in this paper two methods based on steady state analysis and network topology that are to the best of our knowledge, the first to enumerate all possible heterologous pathways linking a target compounds to a source set of compounds. In the context of metabolic engineering, the source set is composed of all naturally produced chassis compounds (endogenuous chassis metabolites) and the target set can be any compound of the chemical space. We also provide an algorithm for identifying precursors which can be supplied to the growth media in order to increase the number of ways to synthesize specific target compounds.

Conclusions

We find the topological approach to be faster by several orders of magnitude than the steady state approach. Yet both methods are generally scalable in time with the number of pathways in the metabolic network. Therefore this work provides a powerful tool for pathway enumeration with direct application to biosynthetic pathway design.     

Systems Metabolic Engineering Meets Machine Learning: A New Era for Data‐Driven Metabolic Engineering

The recent increase in high‐throughput capacity of ‘omics datasets combined with advances and interest in machine learning (ML) have created great opportunities for systems metabolic engineering. In this regard, data‐driven modeling methods have become increasingly valuable to metabolic strain design. In this review, the nature of ‘omics is discussed and a broad introduction to the ML algorithms combining these datasets into predictive models of metabolism and metabolic rewiring is provided. Next, this review highlights recent work in the literature that utilizes such data‐driven methods to inform various metabolic engineering efforts for different classes of application including product maximization, understanding and profiling phenotypes, de novo metabolic pathway design, and creation of robust system‐scale models for biotechnology. Overall, this review aims to highlight the potential and promise of using ML algorithms with metabolic engineering and systems biology related datasets.     

ATP调控策略及其在微生物代谢产物合成中的应用

辅因子工程是代谢工程的一个新兴分支领域,主要通过直接调控细胞内关键酶的辅因子,如ATP/ADP、NADH/NAD+、NADPH/NADP+等的浓度和形式来实现代谢流的最大化,快速地将物质流导向目标代谢物。ATP作为一种重要辅因子参与微生物细胞内大量的酶催化反应,将物质代谢途径串联或并联成复杂的网络体系,最终使得物质代谢流的分配受到牵制。因此ATP调控策略有望成为微生物菌株改造的有利工具,用于提高目标代谢物的浓度和生产能力,强化微生物对于环境的耐受以及促进底物利用等。文中将重点论述目前常用的有效ATP调控策略以及ATP调控对于细胞代谢的影响,以期为微生物细胞工厂的高效构建提供参考。