代谢网络定量分析研究进展

综述了代谢工程中代谢控制分析、代谢通量分析、生化系统理论、途径分析、控制论模型等定量分析方法的基本理论,以实例说明了这些方法的应用,并对代谢分析方法的发展进行了展望。     

基元模式分析在生物网络和途径分析中的应用

基元模式分析是应用最广泛的代谢途径分析方法。基元模式分析的研究对象从代谢网络发展到信号传导网络;研究尺度从细胞到生物反应器,甚至生态系统;数学描述从稳态分解到动态解析;研究领域从微生物代谢到人类疾病。以下综述了基元模式分析的算法和软件开发现状,以及其在代谢途径与鲁棒性、代谢通量分解、稳态代谢通量分析、动态模型与生物过程模拟、网络结构与调控、菌株设计和信号传导网络等方面的应用。开发新的算法解决组合爆炸问题,探索基元模式与代谢调控的关系以及提高菌株设计算法效率是今后基元模式的重要发展方向。     

应用最大熵原理通过酶控制通量预测突变体的通量分布

在代谢工程和系统生物学领域, 计算机模拟比以往更为有效的应用于生物过程的分析和优化。胞内代谢通量可以用代谢通量分析和基元模式分析来估算。由于测定数据的不足和误差, 以及基元途径的冗余, 经常很难得到准确的代谢通量分布数据。本研究提出一种基于最大熵原理的算法来计算基元模式系数。欠定和不确定条件下, 通过胞外代谢通量数据估算胞内代谢通量分布。为了检验算法的可行性, 对杂交瘤细胞、枯草芽孢杆菌和大肠杆菌的胞内代谢通量分布做了估算。本研究提出的基于最大熵原理的优化算法避免了对细胞状态的生理学假设。与其他目标函数相比, 可以更为可靠和可行的估算胞内代谢通量分布。     

城市物质代谢的生态效率——以深圳市为例

城市可持续发展研究的关键是城市物质代谢通量及其效率研究,但物质代谢通量仅能反映代谢速率,而其生态效率则能反映支持社会经济发展的物质代谢能力。从工业、生活的源头循环(减少原生资源的消耗)和末端循环(减少污染物的产生)角度,构建城市物质代谢生态效率的度量模型,并依据中国城市化发展进程,选定深圳市作为研究区,核算城市水、能量和废物代谢通量以及代谢的生态效率。结果表明:随着深圳市社会经济的快速发展,水、能源和废物代谢通量呈现出增长势头,但代谢的生态效率不断提高。1998～2004年间,GDP增长2.7倍,城市水和电的代谢通量分别增长1.5倍和3.0倍;工业增加值增长3.7倍,工业水、电、能源和废物的代谢通量分别增长1.9、3.5、2.7倍和2.0倍;常住人口增长1.5倍,居民水和电的代谢通量分别增长1.8倍和1.7倍;资源效率提高1.8倍,环境效率提高3.7倍,生态效率提高2.3倍。虽然深圳市物质代谢的生态效率在提高,但是随着物质资源的日益稀缺,物质代谢的生态效率仍需进一步提高,而提高城市物质代谢生态效率的关键是资源效率和环境效率的协同发展,以及逐步构建废物资源化的循环链条。     

基于酶约束的代谢网络模型研究进展及其应用

基因组尺度代谢网络模型已经成功地应用于指导代谢工程改造,但由于传统通量平衡分析法仅考虑化学计量学和反应方向约束,模拟得到的是理论最优结果,对一些现象如代谢溢流、底物层级利用等无法准确描述。近年来人们通过在代谢网络模型中引入新的蛋白量、热力学等约束发展了新的约束优化计算方法,可以更准确真实地模拟细胞在不同条件下的代谢行为。文中主要对近年来提出的多种酶约束模型进行评述,对酶约束引入的基本思路、酶约束的数学方程表示及优化目标设定、引入酶约束后对代谢通量计算结果的影响及酶约束模型在代谢工程菌种改造中的应用等进行了全面深入的介绍,并提出了已有各种方法存在的主要问题,展望了相关方法的未来发展方向。通过引入新的约束,代谢网络模型能够更精确模拟和预测细胞在环境和基因扰动下的代谢行为,为代谢工程菌种改造提供更准确可靠的指导。     

大肠杆菌苏氨酸合成途径动力学模型的构建与分析

动力学模型分析有利于理解生物系统的调控机制,从而为高效细胞工厂的理性设计提供指导。基于以往发表的相关途径动力学模型和测量的酶动力学数据,开发了大肠杆菌苏氨酸合成途径的动力学模型。模型包含从天冬氨酸至苏氨酸的合成途径及葡萄糖开始的为合成途径提供前体以及能量的代谢途径。与以往模型不同的是新模型中考虑了能量和还原力的平衡,从而使模型模拟的系统自身成为一个不需要从外界提供能量和还原力的自洽系统。模型稳态分析的结果表明PTS、G6PDH和HDH等反应对苏氨酸合成反应的通量控制系数较大,通过过表达这些反应的酶可以有效增加苏氨酸合成反应的通量。     

陆地生态系统碳水通量贡献区评价综述

综述了通量贡献区研究的基本理论、最新进展、研究热点与难点,旨在促进中国区域碳水通量数据空间代表性的定量评价.通量贡献区是通量观测点上风向的空间代表区域,能够反映代表区域对应下垫面的源区内每一点对观测点的通量贡献权重影响,主要受观测高度、空气动力学粗糙度和大气稳定度等因素的影响.通量贡献区通常随着观测高度的增加、空气动力学粗糙度的降低和大气稳定度的增加而变大,反之则变小.通量贡献区的评价模型包括解析模型、拉格朗日随机模型、大涡模拟和闭合模型四类.通量贡献区的评价结果可以广泛应用于通量数据质量评价、实验设计的指导、与遥感技术结合的区域尺度的总初级生产力的估算、城市CO2通量变化的评估以及能量闭合的评价等研究.最新研究表明,对流边界层的通量贡献区存在负的通量贡献区域;有裸地存在的情况下解析模型通常会低估裸地对观测通量的贡献;与水平地面处的通量贡献区相比,山谷处通量贡献区变小而山脊处的通量贡献区变大.通量贡献区模型研究应进一步考虑大气中的平流效应、湍流的非高斯扩散以及建立冠层内部的通量贡献区模型.解决森林冠层内流场的不均匀性、冠层重叠问题、冠层湍流的不稳定性是建立适合冠层内部通量贡献区模型的前提条件.在理想条件的气体释放验证试验的基础上,需要开展复杂条件下的相关试验.     

乳酸钠促进法夫酵母虾青素合成代谢流作用分析

【目的】研究乳酸钠(一种糖代谢产物)的加入对法夫酵母JMU-VDL668发酵过程中细胞生长和虾青素合成的影响。【方法】分别在摇瓶和7 L发酵罐实验基础上,采用代谢通量分析的方法分析添加乳酸钠对法夫酵母菌株JMU-VDL668合成虾青素代谢流的影响。【结果】在7 L发酵罐实验中添加乳酸钠,虾青素产量最高可达17.70 mg/L,与对照组相比提高26%。代谢通量分析表明,乳酸钠可以调节丙酮酸、乙酰辅酶A节点处的代谢通量分布,乳酸在乳酸脱氢酶的作用下可以直接进入代谢网络的后半程,乙酰辅酶A的通量和进入TCA循环的通量得到了显著加强。【结论】乳酸钠的加入提供了更多的乙酰辅酶A等前体物质和能量供给,因此促进了虾青素的合成。     

小球藻联产油脂和虾青素的基元模式分析

构建了包含虾青素合成途径的小球藻代谢网络模型,集成文献报道同位素标定的小球藻代谢通量数据,估算了胞内代谢通量分布。在正常和缺氮培养条件下,虾青素的代谢通量分别为0.38和0.35。计算得到基元模式共640条,通过最大熵原理算法求取了正常培养和缺氮培养条件下的基元模式概率。存在4条关键基元模式,在2种培养条件下,其基元模式概率之和分别为60.95%和77.53%。虾青素的最大理论合成产率为11.27%,但是这4条关键基元模式并不包括虾青素的合成反应。     

用光合-蒸散耦合模型模拟冬小麦水热通量的日变化

从SPAC理论出发,建立了一个冬小麦光合和蒸散的耦合模型．感热通量和潜热通量采用Shuttleworth-Wallace的双层模型计算,并通过冠层阻力的参数化,将光合作用与蒸腾作用耦合起来．用涡度相关方法,观测了感热通量和潜热通量,对模型进行了验证．结果表明,模拟值与观测值比较一致,模型可以很好地模拟感热通量和潜热通量的日变化过程．对模型的敏感性分析发现,冬小麦蒸腾比较敏感的参数有凋萎点、气孔导度参数、叶对红外辐射的反射率和光响应曲线凸度;土壤蒸发只对土壤阻力参数的敏感性较强．本模型对水热通量与环境因子作用过程的理论研究和指导农田的灌溉制度等有一定的意义．     

Markov Chain Monte Carlo Algorithm based metabolic flux distribution analysis on Corynebacterium glutamicum

MOTIVATION: Metabolic flux analysis via a (13)C tracer experiment has been achieved using a Monte Carlo method with the assumption of system noise as Gaussian noise. However, an unbiased flux analysis requires the estimation of fluxes and metabolites jointly without the restriction on the assumption of Gaussian noise. The flux distributions under such a framework can be freely obtained with various system noise and uncertainty models. RESULTS: In this paper, a stochastic generative model of the metabolic system is developed. Following this, the Markov Chain Monte Carlo (MCMC) approach is applied to flux distribution analysis. The disturbances and uncertainties in the system are simplified as truncated Gaussian multiplicative models. The performance in a real metabolic system is illustrated by the application to the central metabolism of Corynebacterium glutamicum. The flux distributions are illustrated and analyzed in order to understand the underlying flux activities in the system. AVAILABILITY: Algorithms are available upon request.     

MFA for overdetermined systems reviewed and compared with rna expression data to elucidate the difference in shikimate yield between carbon- and phosphate-limited continuous cultures of E. coli W3110.shik1

The present contribution focuses on the mathematical techniques used to solve steady state metabolic models for the case of an overdetermined system. Even when parts of the system are underdetermined it is possible to solve the model partially and obtain statistically meaningful results. This is illustrated with data gathered from a set of E. coli W3110.shik1 phosphate- or carbon-limited continuous cultures. It is shown that the low yield in shikimate for C-limited cultures is not due to a lower flux going to the shikimate pathway but is caused by a high secretion of byproducts. Carbon-limited cultures could be better for shikimate production than carbon-abundant cultures provided the byproduct secretion is reduced. Finally, flux calculations are compared with RNA expression data.     

Flux analysis uncovers key role of functional redundancy in formaldehyde metabolism

Genome-scale analysis of predicted metabolic pathways has revealed the common occurrence of apparent redundancy for specific functional units, or metabolic modules. In many cases, mutation analysis does not resolve function, and instead, direct experimental analysis of metabolic flux under changing conditions is necessary. In order to use genome sequences to build models of cellular function, it is important to define function for such apparently redundant systems. Here we describe direct flux measurements to determine the role of redundancy in three modules involved in formaldehyde assimilation and dissimilation in a bacterium growing on methanol. A combination of deuterium and ¹⁴C labeling was used to measure the flux through each of the branches of metabolism for growth on methanol during transitions into and out of methylotrophy. The cells were found to differentially partition formaldehyde among the three modules depending on the flux of methanol into the cell. A dynamic mathematical model demonstrated that the kinetic constants of the enzymes involved are sufficient to account for this phenomenon. We demonstrate the role of redundancy in formaldehyde metabolism and have uncovered a new paradigm for coping with toxic, high-flux metabolic intermediates: a dynamic, interconnected metabolic loop.     

Tandem mass spectrometry: a novel approach for metabolic flux analysis

The goal of metabolic flux analysis (MFA) is the accurate estimation of intracellular fluxes in metabolic networks. Here, we introduce a new method for MFA based on tandem mass spectrometry (MS) and stable-isotope tracer experiments. We demonstrate that tandem MS provides more labeling information than can be obtained from traditional full scan MS analysis and allows estimation of fluxes with better precision. We present a modeling framework that takes full advantage of the additional labeling information obtained from tandem MS for MFA. We show that tandem MS data can be computed for any network model, any compound and any tandem MS fragmentation using linear mapping of isotopomers. The inherent advantages of tandem MS were illustrated in two network models using simulated and literature data. Application of tandem MS increased the observability of the models and improved the precision of estimated fluxes by 2- to 5-fold compared to traditional MS analysis.     

Understanding flux in plant metabolic networks

The revolutionary growth in our ability to identify the 'parts list' of cellular infrastructure in plants in detail, and to alter it with precision, challenges us to develop methods to quantify how these parts function. For components of metabolism, this means mapping fluxes at the level of metabolic networks. Advances in experimental, analytical and software tools for metabolic flux analysis now allow maps of the fluxes through central metabolism to be obtained from the results of stable-isotope-labeling experiments. Such maps have led to notable successes in understanding and engineering metabolic function in microorganisms. Recent studies in plants are giving insight into particular fluxes, such as those of the pentose phosphate pathway, and into general phenomena, such as substrate- or futile-cycles and compartmentation. The importance of experimental design and statistical analysis have been illustrated, and analyses of fluxes in heterotrophic plant tissues have been carried out recently.     

Incorporating metabolic flux ratios into constraint-based flux analysis by using artificial metabolites and converging ratio determinants

One of the well-established approaches for the quantitative characterization of large-scale underdetermined metabolic network is constraint-based flux analysis, which quantifies intracellular metabolic fluxes to characterize the metabolic status. The system is typically underdetermined, and thus usually is solved by linear programming with the measured external fluxes as constraints. Thus, the intracellular flux distribution calculated may not represent the true values. (13)C-constrained flux analysis allows more accurate determination of internal fluxes, but is currently limited to relatively small metabolic networks due to the requirement of complicated mathematical formulation and limited parameters available. Here, we report a strategy of employing such partial information obtained from the (13)C-labeling experiments as additional constraints during the constraint-based flux analysis. A new methodology employing artificial metabolites and converging ratio determinants (CRDs) was developed for improving constraint-based flux analysis. The CRDs were determined based on the metabolic flux ratios obtained from (13)C-labeling experiments, and were incorporated into the mass balance equations for the artificial metabolites. These new mass balance equations were used as additional constraints during the constraint-based flux analysis with genome-scale E. coli metabolic model, which allowed more accurate determination of intracellular metabolic fluxes.