Physiology of microbial cell and metabolic engineering

This review is devoted to the problems of the physiology and cell biology of microorganisms in relation to metabolic engineering. The latter is considered as a branch of fundamental and applied biotechnology aimed at controlling microbial metabolism by methods of genetic engineering and classical genetics and based on intimate knowledge of cell metabolism. Attention is also given to the problems associated with the metabolic limitation of microbial biosyntheses, analysis and control of metabolic fluxes, rigidity of metabolic pathways, the role of pleiotropic (global) regulatory systems in the control of metabolic fluxes, and prospects of physiological and evolutionary approaches in metabolic engineering.     

Physiology of microbial cells and metabolic engineering

This review is devoted to the problems of the physiology and cell biology of microorganisms in relation to metabolic engineering. The latter is considered as a branch of fundamental and applied biotechnology aimed at controlling microbial metabolism by methods of genetic engineering and classical genetics and based on intimate knowledge of cell metabolism. Attention is also given to the problems associated with the metabolic limitation of microbial biosyntheses, analysis and control of metabolic fluxes, rigidity of metabolic pathways, the role of pleiotropic (global) regulatory systems in the control of metabolic fluxes, and prospects of physiological and evolutionary approaches in metabolic engineering.     

Biosensors and their applications (review of the literature)

Different biosensors (potentiometric, voltampermetric, thermometric, optoelectronic, acoustoelectronic) are reviewed, and the main principles of their operation are discussed. Data on biosensor applications are systematized.     

基因敲除技术及其在微生物代谢工程方面的应用

应用基因工程技术对微生物细胞内的代谢通量进行重新设计,是获得高产高效的工业菌株的重要手段之一。基因敲除是20世纪80年代发展起来的一项重要的分子生物学技术,利用基因敲除技术可阻断细胞的代谢旁路。或通过引入突变位点改变目的产物的产量或质量而达到调节代谢流,优化代谢途径的目的。简单介绍了基因敲除技术的操作过程,重点讨论基因敲除技术的敲除策略及在微生物代谢工程方面的应用,并展望了相关技术在诸多领域的发展趋势。     

Use of genome-scale microbial models for metabolic engineering

Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metabolic network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction.     

Rapid sampling devices for metabolic engineering applications

A number of rapid sampling devices for metabolic engineering applications have been developed over the last years with the purpose of the estimation of in vivo metabolic concentrations and dynamics. This review outlines the designs and characteristics as well as the developments and changes in diverse approaches over the years. Primary performance parameters for these constructions are sampling time and rate and, for an accurate representation of the in vivo condition in cells, the reproducibility of results and easy handling throughout the sampling operation.     

OptORF: Optimal metabolic and regulatory perturbations for metabolic engineering of microbial strains

Background  

Computational modeling and analysis of metabolic networks has been successful in metabolic engineering of microbial strains for valuable biochemical production. Limitations of currently available computational methods for metabolic engineering are that they are often based on reaction deletions rather than gene deletions and do not consider the regulatory networks that control metabolism. Due to the presence of multi-functional enzymes and isozymes, computational designs based on reaction deletions can sometimes result in strategies that are genetically complicated or infeasible. Additionally, strains might not be able to grow initially due to regulatory restrictions. To overcome these limitations, we have developed a new approach (OptORF) for identifying metabolic engineering strategies based on gene deletion and overexpression.     

Channeling in native microbial pathways: Implications and challenges for metabolic engineering

Intracellular enzymes can be organized into a variety of assemblies, shuttling intermediates from one active site to the next. Eukaryotic compartmentalization within mitochondria and peroxisomes and substrate tunneling within multi-enzyme complexes have been well recognized. Intriguingly, the central pathways in prokaryotes may also form extensive channels, including the heavily branched glycolysis pathway. In vivo channeling through cascade enzymes is difficult to directly measure, but can be inferred from in vitro tests, reaction thermodynamics, transport/reaction modeling, analysis of molecular diffusion and protein interactions, or steady state/dynamic isotopic labeling. Channeling presents challenges but also opportunities for metabolic engineering applications. It rigidifies fluxes in native pathways by trapping or excluding metabolites for bioconversions, causing substrate catabolite repressions or inferior efficiencies in engineered pathways. Channeling is an overlooked regulatory mechanism used to control flux responses under environmental/genetic perturbations. The heterogeneous distribution of intracellular enzymes also confounds kinetic modeling and multiple-omics analyses. Understanding the scope and mechanisms of channeling in central pathways may improve our interpretation of robust fluxomic topology throughout metabolic networks and lead to better design and engineering of heterologous pathways.     

Modern theories of metabolic control and their applications

Existing, qualitative notions with respect to the way in which enzyme properties control metabolism are discussed in the light of the control analysis developed by H. Kacser and J. A. Burns ((1973) in: Rate Control of Biological Processes, Davies DD, ed., Cambridge University Press, pp. 63–104) and R. Heinrich and T. A. Rapoport ((1974) Eur. 3. Biochem.42, 89–95), and recent experimental data. Points at which the existing notions should be adjusted are: (i) Metabolic control is shared by enzymes rather than confined to one rate-limiting enzyme per pathway. (if) Whether an enzyme exercises strong control on a flux cannot be deduced solely from its own properties, nor is it directly related to its distance from equilibrium. With respect to metabolic control, enzymes should be classified into four groups, rather than two (reversible versus irreversible). (iii) The distribution of control among the enzymes depends on the metabolic conditions. (iv) Control structures of metabolic pathways probably differ with the function of that pathway.     

An integrated network visualization framework towards metabolic engineering applications

Background

Over the last years, several methods for the phenotype simulation of microorganisms, under specified genetic and environmental conditions have been proposed, in the context of Metabolic Engineering (ME). These methods provided insight on the functioning of microbial metabolism and played a key role in the design of genetic modifications that can lead to strains of industrial interest. On the other hand, in the context of Systems Biology research, biological network visualization has reinforced its role as a core tool in understanding biological processes. However, it has been scarcely used to foster ME related methods, in spite of the acknowledged potential.

Results

In this work, an open-source software that aims to fill the gap between ME and metabolic network visualization is proposed, in the form of a plugin to the OptFlux ME platform. The framework is based on an abstract layer, where the network is represented as a bipartite graph containing minimal information about the underlying entities and their desired relative placement. The framework provides input/output support for networks specified in standard formats, such as XGMML, SBGN or SBML, providing a connection to genome-scale metabolic models. An user-interface makes it possible to edit, manipulate and query nodes in the network, providing tools to visualize diverse effects, including visual filters and aspect changing (e.g. colors, shapes and sizes). These tools are particularly interesting for ME, since they allow overlaying phenotype simulation results or elementary flux modes over the networks.

Conclusions

The framework and its source code are freely available, together with documentation and other resources, being illustrated with well documented case studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0420-0) contains supplementary material, which is available to authorized users.     

Introduction and expression of genes for metabolic engineering applications in Saccharomyces cerevisiae

Metabolic pathway engineering in the yeast Saccharomyces cerevisiae leads to improved production of a wide range of compounds, ranging from ethanol (from biomass) to natural products such as sesquiterpenes. The introduction of multienzyme pathways requires precise control over the level and timing of expression of the associated genes. Gene number and promoter strength/regulation are two critical control points, and multiple studies have focused on modulating these in yeast. This MiniReview focuses on methods for introducing genes and controlling their copy number and on the many promoters (both constitutive and inducible) that have been successfully employed. The advantages and disadvantages of the methods will be presented, and applications to pathway engineering will be highlighted.     

Biosensors: current applications and future potential

Biological molecules such as enzymes and antibodies display a unique capacity to recognize and respond to other molecules in a way which can be exploited in the development of analytical devices. In a biosensor, the biological recognition system creates a physiochemical change proximal to a suitable transducer and thereby converts the concentration of the analyte into a quantifiable electrical signal. The design and construction of these devices requires an imaginative combination of biological, chemical, physical and engineering disciplines. Biosensors will find application in a variety of analytical fields.     

Biochemical features of microbial keratinases and their production and applications

Keratinases are exciting proteolytic enzymes that display the capability to degrade the insoluble protein keratin. These enzymes are produced by diverse microorganisms belonging to the Eucarya, Bacteria, and Archea domains. Keratinases display a great diversity in their biochemical and biophysical properties. Most keratinases are optimally active at neutral to alkaline pH and 40–60°C, but examples of microbial keratinolysis at alkalophilic and thermophilic conditions have been well documented. Several keratinases have been associated to the subtilisin family of serine-type proteases by analysis of their protein sequences. Studies with specific substrates and inhibitors indicated that keratinases are often serine or metalloproteases with preference for hydrophobic and aromatic residues at the P1 position. Keratinolytic enzymes have several current and potential applications in agroindustrial, pharmaceutical, and biomedical fields. Their use in biomass conversion into biofuels may address the increasing concern on energy conservation and recycling.     

甲基营养微生物的甲醛代谢途径及其在环境生物技术中的应用

甲醛是一种毒性很高的一碳化合物,甲基营养菌是一类能在有高浓度甲醛的环境中生存的微生物,它们体内有多种降解甲醛的氧化途径和将甲醛转化为细胞组分的同化途径。丝氨酸途径和酮糖单磷酸途径是同时存在于甲基营养型细菌中的两种甲醛同化途径,木酮糖单磷酸途径是甲基营养型酵母菌中独有的甲醛同化途径。为了充分挖掘甲基营养型微生物在环境生物技术中的潜在应用价值,最近有很多研究尝试利用甲基营养微生物的细胞及其甲醛代谢途径关键酶开发甲醛污染检测方法和生物治理技术,对这方面的研究进展进行综述。     

Computational design of auxotrophy-dependent microbial biosensors for combinatorial metabolic engineering experiments

Combinatorial approaches in metabolic engineering work by generating genetic diversity in a microbial population followed by screening for strains with improved phenotypes. One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via http://www.cs.technion.ac.il/~tomersh/tools).     

Process design for microbial plastic factories: metabolic engineering of polyhydroxyalkanoates

Implementing several metabolic engineering strategies, either individually or in combination, it is possible to construct microbial plastic factories to produce a variety of polyhydroxyalkanoate (PHA) biopolymers with desirable structures and material properties. Approaches include external substrate manipulation, inhibitor addition, recombinant gene expression, host cell genome manipulation and, most recently, protein engineering of PHA biosynthetic enzymes. In addition, mathematical models and molecular methods can be used to elucidate metabolically engineered systems and to identify targets for performance improvement.     

遗传改造微生物代谢途径生产新型柴油燃料的研究进展

生物柴油是一种能替代柴油的可再生燃料,然而通过植物油料化学转酯化生产的第一代生物柴油在性能和生产工艺上有很多缺点。近年来随着合成生物学和代谢工程的迅速发展,通过选择合适的微生物并利用各种生物技术改造其代谢合成途径,如脂肪酸合成途径、异戊二烯合成途径,研究人员能利用微生物直接生产性能更加优越、品质更高的新型第二代生物柴油——长链烷烃。文章总结了目前遗传改造微生物代谢途径生产新型柴油的研究进展,并指出目前该领域存在的问题以及今后的发展方向。     

Central metabolic fluxes in the endosperm of developing maize seeds and their implications for metabolic engineering

1?C labeling experiments performed with kernel cultures showed that developing maize endosperm is more efficient than other non-photosynthetic tissues such as sunflower and maize embryos at converting maternally supplied substrates into biomass. To characterize the metabolic fluxes in endosperm, maize kernels were labeled to isotopic steady state using 13C-labeled glucose. The resultant labeling in free metabolites and biomass was analyzed by NMR and GC-MS. After taking into account the labeling of substrates supplied by the metabolically active cob, the fluxes through central metabolism were quantified by computer-aided modeling. The flux map indicates that 51-69% of the ATP produced is used for biomass synthesis and up to 47% is expended in substrate cycling. These findings point to potential engineering targets for improving yield and increasing oil contents by, respectively, reducing substrate cycling and increasing the commitment of plastidic carbon into fatty acid synthesis at the level of pyruvate kinase.