微生物制氢工艺优化与生物反应的调控

氢作为一种清洁高效的可再生能源日益受到人们的重视。本文从微生物制氢的条件与代谢调控方面探讨了生物制氢的最新进展。目前常用产氢细菌进行了总结,分析了细菌的培养方式和工艺方法,探讨了影响生物制氢的各种因素(pH,温度,基质,离子浓度,反应器等)。在此基础之上,阐述了分子生物学技术在生物制氢中的应用及系统代谢调控。最后,对生物制氢今后的主要研究方向及前景进行了展望。     

大数据时代下的生态系统观测发展趋势与挑战

随着观测技术的发展, 生态学研究尺度不断扩大。生态系统观测从小规模合作、短时间个人观测向大规模、长时间、跨学科、多因子联合观测转变。传感器技术的革新带来了生态观测在时空尺度的扩展与精确度上的提升, 致使生态学观测数据的容量、产生速度与数据种类飞速增长。对生态系统数据获取、存储与管理的传统方法无疑不再能满足现代生态学研究的要求。因此, 我们建议以大数据时代的数据存储、管理与处理技术为基础, 整合生态物联观测网络(Internet of Ecology)、公民科学观测网络以及基于标准化数据管理的研究者网络互联, 建立整合生态系统观测平台来应对这一困境。为生态学研究者打造一站式生态观测服务, 是大数据时代下生态系统观测的大势所趋。     

全球协同落实《昆明-蒙特利尔全球生物多样性框架》的挑战与出路:基于SFIC模型的分析

《昆明-蒙特利尔全球生物多样性框架》(简称《昆蒙框架》)的落实是新阶段全球生物多样性治理的重中之重。本文基于相关文献资料查阅,引入协同治理模型(Startingconditions-Facilitativeleadership-Institutionaldesign-Collaborativeprocess,SFIC模型),旨在以一种整体性、系统性思路考察《昆蒙框架》落实面临的挑战,并分析总结应对策略,以期为《昆蒙框架》落实提供一定参考。首先,根据《昆蒙框架》落实对全球协同的客观需要,以及现有研究整体性分析思路缺乏的情况,引出本文使用的SFIC模型并说明适用性。然后,根据SFIC模型运行的要素,结合现实情况,分析了《昆蒙框架》落实面临的发展中国家与发达国家治理基础、合作关系、参与动机、信息沟通、信任建立、资金筹措、后续协商、制度设计、主体领导等方面的挑战。最后依照SFIC模型,从推动资源调动和发展中国家能力建设、促进三方援助合作、加强信息沟通共享、强化信任建设、发掘资金潜力、推进协商谈判、寻求制度约束性与激励性的平衡点、提高制度公正合理性、加强联合国责任机构领导力、发挥大国示范担当作用...     

放线菌工业菌种选育、过程优化与放大研究进展

放线菌属由于能够产生一系列结构复杂的生物活性物质而受到广泛关注, 这些活性代谢产物的大规模发酵生产在医药、农业等领域的应用中起着重要的作用。本文综述了近年来放线菌次级代谢产物产业化研究的一些新进展, 包括菌株的改造、生物过程优化和控制以及发酵放大技术, 并对这些方法和技术进行了讨论。     

人工智能时代发酵优化与放大技术的机遇与挑战

人工智能(artificial intelligence, AI)技术正引发一场新的产业革命,其成功应用正从信息产业迅速渗透到各行各业。传统的发酵工程技术受到巨大挑战的同时更多地迎来了发展变革的机遇。首先,合成生物技术飞速发展使高性能菌株的可获得性及获取效率显著提升,对传统低效的发酵优化放大技术提出很大挑战,亟需对发酵优化放大技术进行升级,以满足高通量菌种性能验证及工艺开发能力的需求;其次,发酵装备技术的持续发展为高效发酵优化技术的进步奠定了良好基础,加之人工智能技术特别是数字孪生与知识图谱等技术的应用,将为传统发酵技术的颠覆性发展带来巨大推动力。本文分别从合成生物时代对发酵优化技术的挑战、发酵优化与放大的核心技术、高通量发酵装备技术、数据可视化技术、数字孪生及知识图谱等智能技术在发酵优化放大中的应用等几个方面进行综述,并对未来工业发酵优化技术的场景以及未来发酵技术对人才培养等提出的新要求进行了展望。     

Modelling nutritional mutualisms: challenges and opportunities for data integration

Nutritional mutualisms are ancient, widespread, and profoundly influential in biological communities and ecosystems. Although much is known about these interactions, comprehensive answers to fundamental questions, such as how resource availability and structured interactions influence mutualism persistence, are still lacking. Mathematical modelling of nutritional mutualisms has great potential to facilitate the search for comprehensive answers to these and other fundamental questions by connecting the physiological and genomic underpinnings of mutualisms with ecological and evolutionary processes. In particular, when integrated with empirical data, models enable understanding of underlying mechanisms and generalisation of principles beyond the particulars of a given system. Here, we demonstrate how mathematical models can be integrated with data to address questions of mutualism persistence at four biological scales: cell, individual, population, and community. We highlight select studies where data has been or could be integrated with models to either inform model structure or test model predictions. We also point out opportunities to increase model rigour through tighter integration with data, and describe areas in which data is urgently needed. We focus on plant‐microbe systems, for which a wealth of empirical data is available, but the principles and approaches can be generally applied to any nutritional mutualism.     

植物模式标本数据整合新的机遇与挑战

命名模式是分类群名称永久依附的成分,在分类学研究中有不可替代的价值。中国复杂的植物采集历史以及对中国植物标本开展研究的单位各异,导致我国植物模式标本零散分布于全球各大标本馆,给分类工作的开展带来了极大的困难。标本数字化的开展为模式标本数据整合提供了新的机遇,同时也给我们带来了人名和地名标准化以及模式类型确认等方面的挑战。我国于2006年开始对模式标本数据进行收集和整理,迄今已完成国内外20余家标本馆9万余条标本数据的收集。模式考证和模式类型清理是我们下一步亟须开展的工作,同时我们应将地名变更资料、人名考证资料进行整合并建立相应的数据库以推动模式标本数据的标准化。这将在很大程度上有助于我们摸清中国模式标本的家底。     

A hybrid mechanistic-empirical model for in silico mammalian cell bioprocess simulation

In cell culture processes cell growth and metabolism drive changes in the chemical environment of the culture. These environmental changes elicit reactor control actions, cell growth response, and are sensed by cell signaling pathways that influence metabolism. The interplay of these forces shapes the culture dynamics through different stages of cell cultivation and the outcome greatly affects process productivity, product quality, and robustness. Developing a systems model that describes the interactions of those major players in the cell culture system can lead to better process understanding and enhance process robustness. Here we report the construction of a hybrid mechanistic-empirical bioprocess model which integrates a mechanistic metabolic model with subcomponent models for cell growth, signaling regulation, and the bioreactor environment for in silico exploration of process scenarios. Model parameters were optimized by fitting to a dataset of cell culture manufacturing process which exhibits variability in metabolism and productivity. The model fitting process was broken into multiple steps to mitigate the substantial numerical challenges related to the first-principles model components. The optimized model captured the dynamics of metabolism and the variability of the process runs with different kinetic profiles and productivity. The variability of the process was attributed in part to the metabolic state of cell inoculum. The model was then used to identify potential mitigation strategies to reduce process variability by altering the initial process conditions as well as to explore the effect of changing CO₂ removal capacity in different bioreactor scales on process performance. By incorporating a mechanistic model of cell metabolism and appropriately fitting it to a large dataset, the hybrid model can describe the different metabolic phases in culture and the variability in manufacturing runs. This approach of employing a hybrid model has the potential to greatly facilitate process development and reactor scaling.     

The identification of enzyme targets for the optimization of a valine producing Corynebacterium glutamicum strain using a kinetic model

The enzyme targets for the rational optimization of a Corynebacterium glutamicum strain constructed for valine production are identified by analyzing the control of flux in the valine/leucine pathway. The control analysis is based on measurements of the intracellular metabolite concentrations and on a kinetic model of the reactions in the investigated pathway. Data‐driven and model‐based methods are used and evaluated against each other. The approach taken gives a quantitative evaluation of the flux control and it is demonstrated how the understanding of flux control is used to reach specific recommendations for strain optimization. The flux control coefficients (FCCs) with respect to the valine excretion rate were calculated, and it was found that the control is distributed mainly between the acetohydroxyacid synthase enzyme (FCC = 0.32), the branched chain amino acid transaminase (FCC = 0.27), and the exporting translocase (FCC = 0.43). The availability of the precursor pyruvate has substantial influence on the valine flux, whereas the cometabolites are less important as demonstrated by the calculation of the respective response coefficients. The model is further used to make in‐silico predictions of the change in valine flux following a change in enzyme level. A doubling of the enzyme level of valine translocase will result in an increase in valine flux of 31%. By optimizing the enzyme levels with respect to valine flux it was found that the valine flux can be increased by a factor 2.5 when the optimal enzyme levels are implemented. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2009     

Biotechnological interventions for harnessing podophyllotoxin from plant and fungal species: current status,challenges, and opportunities for its commercialization

Podophyllotoxin is an aryltetralin lignan synthesized in several plant species, which is used in chemotherapies for cancers and tumor treatment. More potent semisynthetic derivatives of podophyllotoxin such as etoposide and teniposide are being developed and evaluated for their efficacy. To meet the ever increasing pharmaceutical needs, species having podophyllotoxin are uprooted extensively leading to the endangered status of selective species mainly Sinopodophyllum hexandrum. This has necessitated bioprospection of podophyllotoxin from different plant species to escalate the strain on this endangered species. The conventional and non-conventional mode of propagation and bioprospection with the integration of biotechnological interventions could contribute to sustainable supply of podophyllotoxin from the available plant resources. This review article is focused on the understanding of different means of propagation, development of genomic information, and its implications for elucidating podophyllotoxin biosynthesis and metabolic engineering of pathways. In addition, various strategies for sustainable production of this valuable metabolite are also discussed, besides a critical evaluation of future challenges and opportunities for the commercialization of podophyllotoxin.     

Dynamic gene expression regulation model for growth and penicillin production in Penicillium chrysogenum

As is often the case for microbial product formation, the penicillin production rate of Penicillium chrysogenum has been observed to be a function of the growth rate of the organism. The relation between the biomass specific rate of penicillin formation (q_p) and growth rate (µ) has been measured under steady state conditions in carbon limited chemostats resulting in a steady state q_p(µ) relation. Direct application of such a relation to predict the rate of product formation during dynamic conditions, as they occur, for example, in fed‐batch experiments, leads to errors in the prediction, because q_p is not an instantaneous function of the growth rate but rather lags behind because of adaptational and regulatory processes. In this paper a dynamic gene regulation model is presented, in which the specific rate of penicillin production is assumed to be a linear function of the amount of a rate‐limiting enzyme in the penicillin production pathway. Enzyme activity assays were performed and strongly indicated that isopenicillin‐N synthase (IPNS) was the main rate‐limiting enzyme for penicillin‐G biosynthesis in our strain. The developed gene regulation model predicts the expression of this rate limiting enzyme based on glucose repression, fast decay of the mRNA encoding for the enzyme as well as the decay of the enzyme itself. The gene regulation model was combined with a stoichiometric model and appeared to accurately describe the biomass and penicillin concentrations for both chemostat steady‐state as well as the dynamics during chemostat start‐up and fed‐batch cultivation. Biotechnol. Bioeng. 2010;106: 608–618. © 2010 Wiley Periodicals, Inc.     

Validation of a model for process development and scale-up of packed-bed solid-state bioreactors.

We have validated our previously described model for scale-up of packed-bed solid-state fermenters (Weber et al., 1999) with experiments in an adiabatic 15-dm(3) packed-bed reactor, using the fungi Coniothyrium minitans and Aspergillus oryzae. Effects of temperature on respiration, growth, and sporulation of the biocontrol fungus C. minitans on hemp impregnated with a liquid medium were determined in independent experiments, and the first two effects were translated into a kinetic model, which was incorporated in the material and energy balances of the packed-bed model. Predicted temperatures corresponded well with experimental results. As predicted, large amounts of water were lost due to evaporative cooling. With hemp as support no shrinkage was observed, and temperatures could be adequately controlled, both with C. minitans and A. oryzae. In experiments with grains, strong shrinkage of the grains was expected and observed. Nevertheless, cultivation of C. minitans on oats succeeded because this fungus did not form a tight hyphal network between the grains. However, cultivation of A. oryzae failed because shrinkage combined with the strong hyphal network formed by this fungus resulted in channeling, local overheating of the bed, and very inhomogeneous growth of the fungus. For cultivation of C. minitans on oats and for cultivation of A. oryzae on wheat and hemp, no kinetic models were available. Nevertheless, the enthalpy and water balances gave accurate temperature predictions when online measurements of oxygen consumption were used as input. The current model can be improved by incorporation of (1) gas-solids water and heat transfer kinetics to account for deviations from equilibrium observed with fast-growing fungi such as A. oryzae, and (2) the dynamic response of the fungus to changes in temperature, which were neglected in the isothermal kinetic experiments.