基于动态代谢通量分析的发酵过程多目标优化

通过动态代谢通量分析方法建立发酵过程模型,提出了一种基于微观代谢信息的发酵过程多目标优化策略,该策略基于所建微观模型,根据动态特性将发酵过程分为菌体生长和产物合成两个阶段,进行特征分析并从微观通量层面分别设计优化目标与约束条件,采用多目标粒子群算法求得最优解。该方法用于青霉素发酵过程底物流加速率和p H的操作轨迹优化,仿真实验结果表明,采用基于微观通量的多目标优化策略能够提高产物终端浓度,表明优化策略的有效性。     

花生四烯酸发酵动态代谢通量分析模型

分析了高山被孢霉发酵生产花生四烯酸的动力学特征,建立了氮源与葡萄糖双底物限制动力学模型,并结合代谢流分析理论提出了花生四烯酸发酵动态代谢通量分析模型,通过非线性最小二乘法优化拟合获得参数.进一步实验表明这个模型具有较高的精确度,能很好地模拟发酵过程,并能很容易地获得不同发酵时间的代谢流分布.     

黑曲霉生产柠檬酸的控制论模型

黑曲霉发酵是工业生产柠檬酸的主要途径,研究该过程的动力学模型对更好地理解这一工业微生物的代谢机理有重要意义。基于黑曲霉(Aspergillus niger)柠檬酸发酵过程主要代谢途径的分析,构建了简化的碳代谢网络,建立了胞内物质和酶浓度的平衡模型。引入一阶闭环调节器模型描述发酵初期微生物酶系的建立过程。结合生物反应器模型,给出了重要宏观状态变量(如细胞物质浓度、基质浓度、产物浓度)和胞内酶浓度的动态仿真结果与实验值的对比。     

基于混合赛博模型的微生物代谢状态估计

微生物发酵过程中组分异常复杂,物化和生化反应混合交叠,多数状态不能直接测量。混合赛博模型结合了基元模式分析和赛博(cybernetic)模型控制作用,既考虑细胞内产物信息和代谢行为,又引入控制变量来调节催化酶的活性和合成,从而建立了微生物代谢过程的动力学方程,基于该模型可以实现对微生物体代谢状态的实时监测。针对聚羟基丁酸发酵过程,在代谢途径和基元模式分析基础上,对其混合赛博模型中非线性动态进行线性化,再采用扩展卡尔曼滤波对代谢过程状态进行估计。仿真结果表明,对于微生物代谢中一些重要状态变量具有良好的估计效果。     

微生物发酵过程优化控制技术进展

微生物发酵过程优化控制技术是发酵工程的重要技术。综述了近年来微生物发酵过程优化控制技术的研究现状,讨论了机理分析建模、黑箱建模、混合建模等发酵过程建模方法,对基于模型的优化控制策略进行了分析。指出了基于混合模型和多目标优化策略建立动态优化控制器,是微生物发酵过程优化控制的有效方法,并给出了实现优化控制需要解决的关键问题。     

代谢通量分析在酶合成过程中的应用研究进展

代谢通量分析可以有效预测微生物的代谢状况,指导生物合成过程,已在多个领域得到成功应用。本文概括分析了三大代谢通量分析技术（基于物料平衡、基于同位素示踪技术以及基于基因组尺度规模网络）在工业生物技术领域的应用,阐述了相关技术的优势及局限性。在此基础上重点论述了基于物料平衡及同位素示踪这两类通量分析技术在酶合成领域的研究进展,分析了代谢通量分析应用于复杂代谢产物可能存在的问题,指出如何将信号转导、转录调控等信息纳入代谢网络将成为未来酶合成过程代谢分析的研究重点。     

克雷伯氏杆菌发酵生产1,3-丙二醇的代谢通量优化分析

以克雷伯氏杆菌为研究对象,系统研究了1,3-丙二醇厌氧和微氧代谢途径.采用代谢通量分析法建立了代谢通量平衡模型,通过线性规划对1,3-丙二醇厌氧和微氧发酵进行了优化分析,得到其最优代谢通量分布和最大理论得率,并分析了比生长速率、底物浓度以及乙醇生成速率、氧气消耗速率、呼吸商对1,3-丙二醇得率的影响.     

新型生物絮凝剂REA-11的代谢模型建立与代谢网络分析

利用代谢通量分析方法,对谷氨酸棒杆菌Corynebacterium glutamicum CCTCC M201005分批发酵不同阶段和不同溶氧浓度下的代谢网络模型进行了计算,考察了代谢节点对絮凝剂REA-11合成的影响,并对C. glutamicum生长代谢过程中能量和还原力的产生及消耗问题进行分析.结果发现,磷酸戊糖途径(PP)通量在整个发酵过程中始终维持在较高的水平;REA-11合成通量随溶氧浓度的增加而降低,菌体合成通量则随溶氧水平的增加而增加;ATP通量的增加可以促进菌体生长,而与REA-11的合成呈负相关.     

以高产量、高产率、高生产强度为目标的发酵过程优化技术

以高产量、高底物转化率和高生产强度为目标,综合运用微生物反应计量学、生化反应和传递动力学、生物反应器工程及代谢工程理论,开发了:(1)基于微生物反应计量学的培养环境优化技术;(2)基于微生物代谢特性的分阶段培养技术;(3)基于反应动力学模型的优化技术;(4)基于代谢通量分析的优化技术;(5)基于系统观点的生物反应系统优化技术。将这些技术广泛应用于多种产品的发酵过程优化研究中并取得了成功。在此基础上总结出“简化、定量化、模型化和阶段化”的发酵过程优化基本原理,这一基本原理对提高我国发酵工业技术水平、促进生物食品产业的健康发展将起重要作用。     

基于代谢通量分析的SAM和GSH联产溶氧控制策略

为了提高S-腺苷甲硫氨酸(SAM)和谷胱甘肽(GSH)的联产量,考察了溶氧条件对Candida utilis CCTCC M209298发酵联产SAM和GSH的影响。采用代谢通量分析方法对不同转速下SAM和GSH联产发酵过程中的物质和能量代谢进行分析,确定了较优的溶氧控制策略:前9 h的发酵恒定转速350 r min 1,9 h后控制溶氧不低于30%。在此策略下,C.utilis CCTCC M 209298分批发酵生产SAM和GSH的联产量为520.7 mg L 1。最后分别从发酵动力学、代谢通量分析以及呼吸商变化规律对该溶氧控制策略促进SAM和GSH联合高产的原因进行了定量解释。     

应用群能量恒定粒子群优化算法的批次流加发酵过程批次间优化(英文)

An iterative optimization strategy for fed-batch fermentation process is presented by combining a run-to-run optimization with swarm energy conservation particle swarm optimization (SEC-PSO). SEC-PSO, which is designed with the concept of energy conservation, can solve the problem of premature convergence frequently appeared in standard PSO algorithm by partitioning its population into several sub-swarms according to the energy of the swarm and is used in the optimization strategy for parameter iden-tification and operation condition optimization. The run-to-run optimization exploits the repetitive nature of fed-batch processes in order to deal with the optimal problems of fed-batch fermentation process with inaccurate process model and unsteady process state. The kinetic model parameters, used in the operation condition optimization of the next run, are adjusted by calculating time-series data obtained from real fed-batch process in the run-to-run optimization. The simulation results show that the strategy can adjust its kinetic model dynamically and overcome the instability of fed-batch process effectively. Run-to-run strategy with SEC-PSO provides an effective method for optimization of fed-batch fermentation process.     

连续聚合过程中多牌号产品过渡的生产调度最优化

应用连续聚合过程中牌号切换的最优化模型，提出了以目标函数值为判别依据的多牌号切换的最优化调度策赂。对多牌号树脂的生产系统进行了调度最优化的仿真研究，并在安全生产的前提下，以动态规划的方法考察了6个聚乙烯树脂牌号的生产调度，计算了树脂牌号的最优生产序列以及相应的过渡料数量和过渡时间，并分析了计算结果的合理性。     

HEURISTIC FEED RATE PROFILES FOR OPTIMAL YIELD AND PRODUCTIVITY OF FED-BATCH BIOPROCESSES

The optimization of two important classes of fed-batch fermentation processes with respect to the limiting substrate feed rate is considered: (i) growth of one biomass on one limiting substrate, and (ii) growth and product formation on one substrate. For these two types of bioprocesses, two different performance criteria are compared: yield and productivity. Heuristic Teed rate profiles are derived based on (i) the optimal control solution according to the minimum principle, and (ii) the qualitative behavior of the specific rates for growth and possibly product formation. For biomass production processes, it is illustrated that the heuristic strategy coincides exactly with the optimal control solution, while its structure is independent of the performance index considered. For product formation processes, it is illustrated that the same heuristic approach can be used to optimize both yield and productivity in spite of the well known conflict between them.     

基于动态优化和反馈控制的聚合反应过程牌号切换策略

针对单反应器多牌号聚合物生产过程, 提出一种结合动态优化和反馈控制的牌号切换策略。以实验室规模的连续搅拌釜式反应器中苯乙烯聚合牌号切换为对象, 以原料消耗最少为优化目标, 利用迭代动态规划求得切换过程中反应条件和产品性能指标的优化轨迹。引入针对反应温度的路径约束, 使优化后的切换轨迹更易跟踪实现, 防止过渡过程中变量的剧烈波动。仿真结果表明, 这一切换策略可以显著减少牌号切换过渡时间及过渡过程中原料的消耗量, 并能够有效克服进料温度变化的干扰。     

Study on Optimal Strategy of Grade Transition in Industrial Fluidized Bed Gas-Phase Polyethylene Production Process

A model of grade transition is presented for a commercialized fluidized bed gas-phase polyethylene production process. The quantity of off-specification product and the time of grade transition can be minimized by the optimization of operating variables, such as polymerization temperature, the ratio of hydrogen to ethylene, the ratio of co-monomer to ethylene, feed rate of catalyst, and bed level. A new performance index, the ratio of melt flow (MFR), is included in the objective function, for restraining the sharp adjustment of operation variables and narrowing the distribution of molecular weight of the resin. It is recommended that catalyst feed rate and bed level are decreased in order to reduce the grade transition time and the quantity of off-specification product. This optimization problem is solved by an algorithm of sequential quadratic programming (SQP) in MATLAB. There is considerable difference between the forward transition and reverse transition of grade with regard to the operating variab     

Maximizing batch fermentation efficiency by constrained model-based optimization and predictive control of adenosine triphosphate turnover

We present a constrained model-based optimization and predictive control framework to maximize the production efficiency of batch fermentations based on the core idea of manipulating adenosine triphosphate (ATP) wasting. In many bioprocesses, enforced ATP wasting —rerouting ATP use towards an energetically possibly suboptimal path— allows increasing the metabolic flux towards the product, thereby enhancing product yields and specific productivities. However, this often comes at the expense of lower biomass yields and reduced volumetric productivities. To maximize the overall efficiency, we formulate ATP wasting as a model-based optimal control problem. This allows for balancing trade-offs between different objectives such as product yield and volumetric productivity for batch fermentations. Unlike static metabolic control, one obtains a higher degree of flexibility, adaptability, and competitiveness. This can be advantageous towards achieving a sustainable and economically efficient biotechnology industry. To compensate for model-plant mismatch, disturbances, and uncertainties, we propose not only solving the optimal control problem once. Instead, we exploit the concept of moving horizon model predictive control combined with constraint-based dynamic modeling to capture the fermentation dynamics. The approach is underlined considering the industrially relevant bioproduction of lactate by Escherichia coli. We discuss practical challenges for the described control strategy and provide an outlook towards future developments.     

利用状态空间模型和不敏卡尔曼滤波的分批补料发酵过程在线估计(英文)

On-line estimation of unmeasurable biological variables is important in fermentation processes, directly influencing the optimal control performance of the fermentation system as well as the quality and yield of the targeted product. In this study, a novel strategy for state estimation of fed-batch fermentation process is proposed. By combining a simple and reliable mechanistic dynamic model with the sample-based regressive measurement model, a state space model is developed. An improved algorithm, swarm energy conservation particle swarm optimization (SECPSO), is presented for the parameter identification in the mechanistic model, and the support vector machines (SVM) method is adopted to establish the nonlinear measurement model. The unscented Kalman filter (UKF) is designed for the state space model to reduce the disturbances of the noises in the fermentation process. The proposed on-line estimation method is demonstrated by the simulation experiments of a penicillin fed-batch fermentation process.     

N, O-羧甲基壳聚糖复合纳滤膜的制备及其对酒厂发酵废水的截留效果

N, O-carboxymethyl chitosan （NOCC） composite nanofiltration （NF） membranes were prepared by coating and cross-linking. The fermentation effluent from a wine factory was treated with the resulting NOCC/polysulfone （PSF） composite NF membranes. The permeate flux and the removal efficiencies of the resulting NF membranes for the color, chemical oxygen demand （CODcr）, total organic carbon （TOC）, and conductivity of the fermentation effluent were investigated in relation to the driving pressure, the feed flow, and the operation time. The permeate flux and the removal efficiencies were found to increase with the increase of the driving pressure or the feed flow. At 0.40 MPa and ambient temperature the removal efficiencies were 95.5%, 70.7%, 72.6%, and 31.6% for color, CODcr, TOC, and conductivity, respectively. The membrane was found to be stable over a 10-h ooeration for the fermentation effluent treatment.