基因组尺度代谢网络研究进展

基因组尺度代谢网络从基因组序列出发,结合基因、蛋白质、代谢数据库和实验数据,从系统的角度定量研究生命体的代谢过程,了解各个组分之间的相互作用关系。这类网络模型对于生命活动理论研究和优良工程菌的构建都具有重要的理论和实践意义。以下结合作者的实际研究经验,对基因组尺度代谢网络从重构到模拟直至应用进行了较为详细的介绍,并讨论了一些目前存在的难题和未来的研究方向。     

Systems approaches to succinic acid-producing microorganisms

Succinic acid is a cellular metabolite belonging to the C4-dicarboxylic acid family, and the fermentative production of succinic acid via the use of recombinant microorganisms has recently become the focus of an increasing amount of attention. Considering the difficulty inherent to the direct application of natural succinic acid producers to the industrial process, a variety of systems biology studies have been conducted regarding the development of enhanced succinic acid production systems. This review shows how the metabolic processes of microorganisms, includingEscherichia coli andMannheimia succiniciproducens, have been optimized in order to achieve enhanced succinic acid production. First, their metabolic networks were constructed on the basis of complete genome sequences, after which their metabolic characteristics were estimated viain silico computer modeling. Metabolic engineering strategies were designed in accordance with the results ofin silico modeling and metabolically engineered versions of bothE. coli andM. succiniciproducens have been constructed. The succinic acid productivity and yield obtained using metabolically engineered bacteria was significantly higher than that obtained using wild-type bacteria.     

代谢工程发展20年

代谢工程从上世纪90年代初期发展至今已有20年历史,对微生物发酵工业的发展起到了极大的推动作用。以下回顾了代谢工程发展至今的三个重要阶段,讨论了各阶段中代谢工程在技术方面的进展及其对微生物发酵工业的促进作用。最后还讨论了代谢工程将来发展中的关键问题及解决策略。     

燃料乙醇工程菌的代谢工程进展

能源问题是现今经济发展面临的主要问题之一,伴随着21世纪生物发展的步伐,基于微生物合成生物学、蛋白组学和代谢组学的研究进展,利用组合基因的无标记基因删除与重组DNA等技术,构建以廉价的可再生生物原料为碳源、高效合成生物乙醇的发酵工程菌已成为研究热点。我们简要总结了以大肠杆菌、啤酒酵母和运动发酵单胞菌为宿主的乙醇代谢工程改造的相关进展。     

Applications of genome‐scale metabolic reconstructions

The availability and utility of genome‐scale metabolic reconstructions have exploded since the first genome‐scale reconstruction was published a decade ago. Reconstructions have now been built for a wide variety of organisms, and have been used toward five major ends: (1) contextualization of high‐throughput data, (2) guidance of metabolic engineering, (3) directing hypothesis‐driven discovery, (4) interrogation of multi‐species relationships, and (5) network property discovery. In this review, we examine the many uses and future directions of genome‐scale metabolic reconstructions, and we highlight trends and opportunities in the field that will make the greatest impact on many fields of biology.     

基于代谢网络预测菌种基因改造靶点方法的研究进展

高产特定产品的人工细胞工厂的构建需要对野生菌株进行大量的基因工程改造,近年来随着大量基因组尺度代谢网络模型的构建,人们提出了多种基于代谢网络分析预测基因改造靶点以使某一目标化合物合成最优的方法。这些方法利用基因组尺度代谢网络模型中的反应计量关系约束和反应不可逆性约束等,通过约束优化的方法预测可使产物合成最大化的改造靶点,避免了传统的通过相关途径的直观分析确定靶点的方法的局限性和主观性,为细胞工厂的理性设计提供了新的思路。以下结合作者的实际研究经验,对这些菌种优化方法的原理、优缺点及适用性等进行详细介绍,并讨论了目前存在的主要问题和未来的研究方向,为人们针对不同目标产品选择合适的方法及预测结果的可靠性评估提供了指导。     

系统生物学和合成生物学研究在生物燃料生产菌株改造中的应用

基于生物质资源生产环境友好的生物燃料,对经济和社会的可持续发展具有重要意义,但其生产成本高的问题十分突出,而高效生产菌株的获得是解决这一问题的根本出路。以下综述了利用系统生物学研究所获得的信息进行菌种改造的过程,重点论述了生产菌株胁迫耐受性方面的研究进展,并讨论了系统生物学、合成生物学和代谢工程技术在改造生物燃料生产菌株中的应用,展望了合成生物学在构建高效生物能源生产菌株方面应用的前景。     

A modular modulation method for achieving increases in metabolite production

Increasing the production of overproducing strains represents a great challenge. Here, we develop a modular modulation method to determine the key steps for genetic manipulation to increase metabolite production. The method consists of three steps: (i) modularization of the metabolic network into two modules connected by linking metabolites, (ii) change in the activity of the modules using auxiliary rates producing or consuming the linking metabolites in appropriate proportions and (iii) determination of the key modules and steps to increase production. The mathematical formulation of the method in matrix form shows that it may be applied to metabolic networks of any structure and size, with reactions showing any kind of rate laws. The results are valid for any type of conservation relationships in the metabolite concentrations or interactions between modules. The activity of the module may, in principle, be changed by any large factor. The method may be applied recursively or combined with other methods devised to perform fine searches in smaller regions. In practice, it is implemented by integrating to the producer strain heterologous reactions or synthetic pathways producing or consuming the linking metabolites. The new procedure may contribute to develop metabolic engineering into a more systematic practice. © 2015 American Institute of Chemical Engineers Biotechnol. Prog., 31:656–667, 2015     

Yeast Systems Biology: Model Organism and Cell Factory

For thousands of years, the yeast Saccharomyces cerevisiae (S. cerevisiae) has served as a cell factory for the production of bread, beer, and wine. In more recent years, this yeast has also served as a cell factory for producing many different fuels, chemicals, food ingredients, and pharmaceuticals. S. cerevisiae, however, has also served as a very important model organism for studying eukaryal biology, and even today many new discoveries, important for the treatment of human diseases, are made using this yeast as a model organism. Here a brief review of the use of S. cerevisiae as a model organism for studying eukaryal biology, its use as a cell factory, and how advances in systems biology underpin developments in both these areas, is provided.     

Redox homeostasis phenotypes in RubisCO-deficient Rhodobacter sphaeroides via ensemble modeling

Photosynthetic bacteria are capable of carrying out the fundamental biological processes of carbon dioxide assimilation and photosynthesis. In this work, ensemble modeling (EM) was used to examine the behavior of mutant strains of the nonsulfur purple photosynthetic bacterium Rhodobacter sphaeroides containing a blockage in the primary CO(2) assimilatory pathway, which is responsible for cellular redox balance. When the Calvin-Benson-Bassham (CBB) pathway is nonfunctional, spontaneous adaptive mutations have evolved allowing for the use of at least two separate alternative redox balancing routes enabling photoheterotrophic growth to occur. The first of these routes expresses the nitrogenase complex, even in the presence of normal repressing ammonia levels, dissipating excess reducing power via its inherent hydrogenase activity to produce large quantities of hydrogen gas. The second of these routes may dissipate excess reducing power through reduction of sulfate by the formation of hydrogen sulfide. EM was used here to investigate metabolism of R. sphaeroides and clearly shows that inactivation of the CBB pathway affects the organism's ability to achieve redox balance, which can be restored via the above-mentioned alternative redox routes. This work demonstrates that R. sphaeroides is capable of adapting alternative ways via mutation to dissipate excess reducing power when the CBB pathway is inactive, and that EM is successful in describing this behavior.     

Thermodynamic analysis of biodegradation pathways

Microorganisms provide a wealth of biodegradative potential in the reduction and elimination of xenobiotic compounds in the environment. One useful metric to evaluate potential biodegradation pathways is thermodynamic feasibility. However, experimental data for the thermodynamic properties of xenobiotics is scarce. The present work uses a group contribution method to study the thermodynamic properties of the University of Minnesota Biocatalysis/Biodegradation Database. The Gibbs free energies of formation and reaction are estimated for 914 compounds (81%) and 902 reactions (75%), respectively, in the database. The reactions are classified based on the minimum and maximum Gibbs free energy values, which accounts for uncertainty in the free energy estimates and a feasible concentration range relevant to biodegradation. Using the free energy estimates, the cumulative free energy change of 89 biodegradation pathways (51%) in the database could be estimated. A comparison of the likelihood of the biotransformation rules in the Pathway Prediction System and their thermodynamic feasibility was then carried out. This analysis revealed that when evaluating the feasibility of biodegradation pathways, it is important to consider the thermodynamic topology of the reactions in the context of the complete pathway. Group contribution is shown to be a viable tool for estimating, a priori, the thermodynamic feasibility and the relative likelihood of alternative biodegradation reactions. This work offers a useful tool to a broad range of researchers interested in estimating the feasibility of the reactions in existing or novel biodegradation pathways. Biotechnol. Bioeng. 2009;103: 532–541. © 2009 Wiley Periodicals, Inc.     

Integrating computational methods to retrofit enzymes to synthetic pathways

Microbial production of desired compounds provides an efficient framework for the development of renewable energy resources. To be competitive to traditional chemistry, one requirement is to utilize the full capacity of the microorganism to produce target compounds with high yields and turnover rates. We use integrated computational methods to generate and quantify the performance of novel biosynthetic routes that contain highly optimized catalysts. Engineering a novel reaction pathway entails addressing feasibility on multiple levels, which involves handling the complexity of large-scale biochemical networks while respecting the critical chemical phenomena at the atomistic scale. To pursue this multi-layer challenge, our strategy merges knowledge-based metabolic engineering methods with computational chemistry methods. By bridging multiple disciplines, we provide an integral computational framework that could accelerate the discovery and implementation of novel biosynthetic production routes. Using this approach, we have identified and optimized a novel biosynthetic route for the production of 3HP from pyruvate.     

酿酒酵母代谢工程技术

自20世纪90年代初期诞生以来,代谢工程历经了30年的快速发展。作为代谢工程的首选底盘细胞之一,酿酒酵母细胞工厂已被广泛应用于大量大宗化学品和新型高附加值生物活性物质的生物制造,在能源、医药和环境等领域取得了巨大的突破。近年来,合成生物学、生物信息学以及机器学习等相关技术也极大地促进了代谢工程的技术发展和应用。文中回顾了近30年来酿酒酵母代谢工程重要的技术发展,首先总结了经典代谢工程的常用方法和策略,以及在此基础上发展而来的系统代谢工程和合成生物学驱动的代谢工程技术。最后结合最新技术发展趋势,展望了未来酿酒酵母代谢工程发展的新方向。     

单萜类化合物的微生物合成

单萜类化合物是萜类化合物的一种,一般具有挥发性和较强的香气,部分单萜还具有抗氧化、抗菌、抗炎等生理活性,是医药、食品和化妆品工业的重要原料.近年来,利用微生物异源合成单萜类化合物的研究引起了科研人员的广泛关注,但因产量低、生产成本高等限制了其大规模应用.合成生物学的迅猛发展为微生物生产单萜类化合物提供了新的手段,通过改...     

Identification of a 21 amino acid peptide conferring 3-hydroxypropionic acid stress-tolerance to Escherichia coli

We report the identification of a novel small open reading frame in Escherichia coli. The sORF (called iroK) encodes a 21 amino cid peptide, which when translated confers a 133% (ca. 20 g/L) increase in resistance to 3-hydroxypropionic acid. We show that iroK conferred tolerance is additive to previously identified tolerance mechanisms involving relief of inhibited metabolism, yet does not involve altered 3-HP transport. This result demonstrates the continued surprises that microbial genomes hold and emphasize the importance of comprehensive discovery methods in future strain and metabolic engineering efforts.     

Genome-scale models of bacterial metabolism: reconstruction and applications

Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities.     

应用代谢网络模型解析工业微生物胞内代谢

为了快速、高效地理解工业微生物胞内代谢特征,寻找潜在的代谢工程改造靶点,基因组规模代谢网络模型(GSMM)作为一种系统生物学工具越来越受到人们的关注。文中在回顾GSMM 20年发展历程的基础上,分析了当前GSMM的研究现状,总结了GSMM的构建及分析方法,从预测细胞表型和指导代谢工程两个方面阐述了GSMM在解析工业微生物胞内代谢中的应用,并展望了GSMM未来的发展趋势。     

Protein Abundance Prediction Through Machine Learning Methods

Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing the protein pool. Protein abundance is impacted by translation kinetics, which rely on features of codons. In this study, we evaluated the effect of codon usage bias of genes on protein abundance. Notably, we observed differences regarding codon usage patterns between genes coding for highly abundant proteins and genes coding for less abundant proteins. Analysis of synonymous codon usage and evolutionary selection showed a clear split between the two groups. Our machine learning models predicted protein abundances from codon usage metrics with remarkable accuracy, achieving strong correlation with experimental data. Upon integration of the predicted protein abundance in enzyme-constrained genome-scale metabolic models, the simulated phenotypes closely matched experimental data, which demonstrates that our predictive models are valuable tools for systems metabolic engineering approaches.