Application of fuzzy-logic models for metabolic control analysis

A priori information or valuable qualitative knowledge can be incorporated explicitly to describe enzyme kinetics making use of fuzzy-logic models. Although restricted to linear relationships, it is shown that fuzzy-logic augmented models are not only able to capture non-linear features of enzyme kinetics but also allow the proper mathematical treatment of metabolic control analysis. The explicit incorporation of valuable qualitative knowledge is crucial, particularly when handling data estimated from in vivo kinetics studies, since this experimental information is scarce and usually contains measurement errors. Therefore, data-driven techniques, such as the one presented in this work, form a serious alternative to established kinetics approaches.     

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.     

Metabolic flux control analysis of branch points: an improved approach to obtain flux control coefficients from large perturbation data

An overview of published approaches for the metabolic flux control analysis of branch points revealed that often not all fundamental constraints on the flux control coefficients have been taken into account. This has led to contradictory statements in literature on the minimum number of large perturbation experiments required to estimate the complete set of flux control coefficients C(J) for a metabolic branch point. An improved calculation procedure, based on approximate Lin-log reaction kinetics, is proposed, providing explicit analytical solutions of steady state fluxes and metabolite concentrations as a function of large changes in enzyme levels. The obtained solutions allow direct calculation of elasticity ratios from experimental data and subsequently all C(J)-values from the unique relation between elasticity ratio's and flux control coefficients. This procedure ensures that the obtained C(J)-values satisfy all fundamental constraints. From these it follows that for a three enzyme branch point only one characterised or two uncharacterised large flux perturbations are sufficient to obtain all C(J)- values. The improved calculation procedure is illustrated with four experimental cases.     

On-line optimization of glutamate production based on balanced metabolic control by RQ

In glutamate fermentations by Corynebacterium glutamicum, higher glutamate concentration could be achieved by constantly controlling dissolved oxygen concentration (DO) at a lower level; however, by-product lactate also severely accumulated. The results of analyzing activities changes of the two key enzymes, glutamate and lactate dehydrogenases involved with the fermentation, and the entire metabolic network flux analysis showed that the lactate overproduction was because the metabolic flux in TCA cycle was too low to balance the glucose glycolysis rate. As a result, the respiratory quotient (RQ) adaptive control based “balanced metabolic control” (BMC) strategy was proposed and used to regulate the TCA metabolic flux rate at an appropriate level to achieve the metabolic balance among glycolysis, glutamate synthesis, and TCA metabolic flux. Compared with the best results of various DO constant controls, the BMC strategy increased the maximal glutamate concentration by about 15% and almost completely repressed the lactate accumulation with competitively high glutamate productivity.     

Kinetic properties required for sustained or paradoxical control of metabolic fluxes under large changes in enzyme activities

The effect that an increase in the activity of an enzyme has on its flux normally decreases with activity increase. To achieve a large increase in flux by manipulating a single step would therefore require a high initial effect that maintains or increases when the activity is increased, what has been called sustained or paradoxical control. Using metabolic control analysis for large responses, we derive conditions for sustained or paradoxical control in terms of elasticity coefficients. These are used to characterise types of rate laws contributing to this behaviour. The result that simple pathways, with normal kinetics, subject to large activity changes can lead to paradoxical control behaviour suggests that this type of pattern may be much more ubiquitous than could have, in principle, been suspected.     

Sensitivity analysis of stoichiometric networks: an extension of metabolic control analysis to non-steady state trajectories

A sensitivity analysis of general stoichiometric networks is considered. The results are presented as a generalization of Metabolic Control Analysis, which has been concerned primarily with system sensitivities at steady state. An expression for time-varying sensitivity coefficients is given and the Summation and Connectivity Theorems are generalized. The results are compared to previous treatments. The analysis is accompanied by a discussion of the computation of the sensitivity coefficients and an application to a model of phototransduction.     

An update on microbial carotenoid production: application of recent metabolic engineering tools

Carotenoids are ubiquitous pigments synthesized by plants, fungi, algae, and bacteria. Industrially, carotenoids are used in pharmaceuticals, neutraceuticals, and animal feed additives, as well as colorants in cosmetics and foods. Scientific interest in dietary carotenoids has increased in recent years because of their beneficial effects on human health, such as lowering the risk of cancer and enhancement of immune system function, which are attributed to their antioxidant potential. The availability of carotenoid genes from carotenogenic microbes has made possible the synthesis of carotenoids in non-carotenogenic microbes. The increasing interest in microbial sources of carotenoid is related to consumer preferences for natural additives and the potential cost effectiveness of creating carotenoids via microbial biotechnology. In this review, we will describe the recent progress made in metabolic engineering of non-carotenogenic microorganisms with particular focus on the potential of Escherichia coli for improved carotenoid productivity. Amitabha Das and Sang-Hwal Yoon contributed equally to this work.     

平台化学品短链支链脂肪酸和短链支链醇的微生物代谢工程

短链支链脂肪酸和短链支链醇均为重要的平台化学品,是合成多种高附加值产品的前体物质,市场需求巨大。目前两者的生产主要是利用基于石化原料的化学合成法。化学合成法存在着严重依赖化石燃料、反应效率低以及极易造成环境污染等缺点。微生物代谢工程的快速发展为这些平台化学品的生产提供了一条极具潜力的生物合成路线。利用微生物代谢工程技术构建生产这些平台化学品的微生物细胞工厂具有绿色清洁、可持续发展和经济效益好等独特优势。本文系统综述了近年来微生物代谢工程技术在短链支链脂肪酸和短链支链醇合成方面的研究进展,包括所涉及的宿主菌株、关键酶、代谢途径及其改造等,并探讨了未来的发展前景。     

Intracellular metabolism analysis of Clostridium cellulovorans via modeling integrating proteomics,metabolomics and fermentation

A consolidated bioprocess for cellulosic n-butanol production has been developed by engineering Clostridium cellulovorans to overexpress a bifunctional aldehyde/alcohol dehydrogenase. Rational metabolic engineering is important to further improve butanol production. This study aimed to investigate intracellular metabolism and identify the key regulators of cellulosic butanol formation in C. cellulovorans via integrated Omics and fermentation kinetics data analysis. First, comparative proteomics and metabolomics analyses of wild type and n-butanol producing mutant strain were conducted, which quantified 624 host cell proteins and 474 primary and secondary metabolites. Compared to wild type, most cellulases in cellulolysis were up-regulated, but three glycolysis enzymes and three enzymes in central pathway were down-regulated in the n-butanol producing strain. Second, a dynamic model integrating Omics and fermentation data was developed to identify key regulators in butanol biosynthesis, which were ranked by further metabolic control analysis. Finally, rational metabolic engineering was performed in C. cellulovorans by overexpressing two genes (thl and hbd) identified as important factors limiting butanol biosynthesis, which improved butanol yield and C4/C2 ratio. This study demonstrated a research approach to integrate multi-Omics and fermentation data of C. cellulovorans and guide its rational metabolic engineering, which can also be applied to other microorganisms.     

NMR-derived developmental metabolic trajectories: an approach for visualizing the toxic actions of trichloroethylene during embryogenesis

Fish embryo toxicity tests for chemical risk assessment have traditionally been based upon non-specific endpoints including morphological abnormalities, hatching success, and mortality. Here we extend the application of ¹H NMR-based metabolomics in environmental toxicology by adding a suite of metabolic endpoints to the Japanese medaka (Oryzias latipes) embryo assay, with the goal to provide more sensitive, specific and unbiased biomarkers of toxicity. Medaka were exposed throughout embryogenesis to five concentrations of trichloroethylene (TCE; 0, 8.76, 21.9, 43.8, 87.6, 175 mg/L) and the relative sensitivities of the traditional and metabolomic endpoints compared. While the no-observable-adverse-effect-level for hatching success, the most sensitive traditional indicator, was 164 mg/L TCE, metabolic perturbations were detected at all exposure concentrations. Principal components analysis (PCA) highlighted a dose-response relationship between the NMR spectra of medaka extracts. In addition, 12 metabolites that exhibited highly significant dose-response relationships were identified, which indicated an energetic cost to TCE exposure. Next, embryos were exposed to 0, 0.88, 8.76 mg/L TCE and sampled on each of the 8 days of development. Projections of 66 two-dimensional J-resolved NMR spectra were obtained, and PCA revealed developmental metabolic trajectories that characterized the basal and TCE-perturbed changes in the entire NMR-visible metabolome throughout embryogenesis. Although no significant increases in mortality, gross deformity or developmental retardation were observed relative to the control group, TCE-induced metabolic perturbations were observed on day 8. In conclusion, these results support the continued development of NMR-based metabolomics as a rapid and reproducible tool for biomarker discovery and environmental risk assessment.     

Increased precision of microbial RNA quantification using NASBA with an internal control

Detection and quantification of low abundance target RNA has wide utility in the fields of clinical diagnostics, environmental monitoring, gene expression analysis, and biodefense. Nucleic acid based sequence amplification (NASBA) is an isothermal amplification method that provides the sensitivity needed for these applications. However, the requirement for three separate enzymes in NASBA often results in a greater variability between replicate samples than that seen in PCR-based assays. To overcome this problem, we have adapted the bioMérieux Nuclisens Basic Kit and Nuclisens EasyQ Analyzer along with the introduction of a synthetic internal control RNA (IC-RNA) for quantification of potentially any RNA sequence. Using the rbcL gene from the Florida red tide organism Karenia brevis as our target, we describe a simple method to accurately quantify the native target by computing the ratio of the time to positivity (TTP) values for both the wild-type and IC-RNA, and plotting this ratio against the starting number of target molecules or cells. By utilizing this simple method, we have significantly increased our accuracy and precision of prediction over the standard TTP calculations.     

Authentication of beef production systems using a metabolomic-based approach

There is a need for new, non-invasive, rapid and reliable analytical methodologies that can easily be implemented and used for authentication of cattle production systems and the meat derived from them. Easily quantifiable markers could strengthen the current tracing methods for beef authentication. This study investigated the use of a nuclear magnetic resonance-based metabolomic approach as a tool to authenticate beef on the basis of the pre-slaughter production system. Urine and muscle samples were collected from animals fed either pasture outdoor, a barley-based concentrate indoor, silage followed by pasture outdoor or silage followed by pasture outdoor with concentrate over 1 year. A metabolomic analysis was performed on urine (n = 68) and muscle (n = 98) samples collected from animals on the different diets. The results showed that separation according to production system was possible indicating the potential use of this approach in beef authentication. Identification of the major discriminating peaks in urine led to the identification of potential markers of production system including creatinine, glucose, hippurate, pyruvate, phenylalanine, phenylacetylglycine and three unassigned resonances.     

一株嗜热厌氧杆菌的分离、鉴定及其代谢特征

【目的】分离、保护油藏嗜热微生物资源,解析其主要的代谢特征。【方法】利用Hungte厌氧分离技术从大港油田埕海一区油层采出液中分离出厌氧菌株BF1。通过生理生化特征分析、16S rRNA基因序列比对与电化学分析,确定BF1的分类地位及其S元素代谢对腐蚀电流的影响。【结果】菌株BF1为严格嗜热厌氧革兰氏阴性杆菌,顶端产芽孢、不运动,菌体大小为0.42μm×(1.6 5.4)μm,单生、成对或成串生长。其温度生长范围为45°C 75°C(最适温度60°C);pH生长范围在4.5 8.5(最适pH 6.5)之间,比生长速率(μm)0.99 h 1,倍增时间为42 min。能利用葡萄糖、松三糖、棉子糖、甘露糖、乳糖、纤维二糖、果糖、核糖等碳水化合物,利用葡萄糖发酵的产物是乙醇、乙酸、CO2及少量的H2。菌株BF1能还原亚硫酸盐与硫代硫酸盐产生H2S,其耐受上限分别为50 mmol/L和75 mmol/L;还原硫代硫酸钠(50 mmol/L)后其极化电阻由2 099/cm2降低至776/cm2,腐蚀电流由9.936e-006 A提高至3.25e-005 A。细胞膜脂肪酸主要由高级饱和脂肪酸组成,含量最丰富的为十五烷酸占70.6%。菌株BF1的DNA(G+C)mol%含量为34.0%,其16S rRNA与Thermoanaerobacter pseudethanolicus DSM 2355T相似性最高,为98.3%,与T.brockii subsp.brockii DSM 1457T次之,为98.0%。菌株BF1的许多生理、生化特征与T.pseudethanolicus DSM 2355T和T.brockii subsp.brockii DSM 1457T有着明显的差别,如倍增时间、最适生长温度及底物利用等;而菌株BF1的细胞膜脂肪酸组成与T.pseude-thanolicus DSM 2355T也不相同。【结论】菌株BF1可能是Thermoanaerobacter属中的一个新种,其确切分类地位还需要进一步进行DNA分子杂交;其代谢元素硫提高腐蚀电流密度,可能会对油田管道与设备造成腐蚀。     

Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models

Rational metabolic engineering methods are increasingly employed in designing the commercially viable processes for the production of chemicals relevant to pharmaceutical, biotechnology, and food and beverage industries. With the growing availability of omics data and of methodologies capable to integrate the available data into models, mathematical modeling and computational analysis are becoming important in designing recombinant cellular organisms and optimizing cell performance with respect to desired criteria. In this contribution, we used the computational framework ORACLE (Optimization and Risk Analysis of Complex Living Entities) to analyze the physiology of recombinant Escherichia coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid (TCA) cycle and the novel BDO production route. Interestingly, among the enzymes between the glucose uptake and the BDO pathway, the enzymes belonging to the lower branch of TCA cycle have been identified as the most important for improving BDO production and yield. We also quantified the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth, and byproduct formation. Independent earlier experiments on this strain confirmed that the computationally obtained conclusions are consistent with the experimentally tested designs, and the findings of the present studies can provide guidance for future work on strain improvement. Overall, these studies demonstrate the potential and effectiveness of ORACLE for the accelerated design of microbial cell factories.     

In silico analysis of lactate producing metabolic network in Lactococcus lactis

Today the importance of in silico experiment grows bigger than before by the advance of computing power. More detailed mathematical modeling handled by simulation can produce more reasonable and meaningful results. In this research, we suggest the metabolic network of Lactococcus lactis for aerobic condition. Using a mathematical model, we observed the effect of enzymes on lactate production using flux distribution analysis, metabolic control analysis, and in silico experiment by biochemical simulation software. Each analysis showed some different results because of their characteristics but some key enzymes for lactate production were found from them.     

The bright frontiers of microbial metabolic optogenetics

In recent years, light-responsive systems from the field of optogenetics have been applied to several areas of metabolic engineering with remarkable success. By taking advantage of light's high tunability, reversibility, and orthogonality to host endogenous processes, optogenetic systems have enabled unprecedented dynamical controls of microbial fermentations for chemical production, metabolic flux analysis, and population compositions in co-cultures. In this article, we share our opinions on the current state of this new field of metabolic optogenetics.We make the case that it will continue to impact metabolic engineering in increasingly new directions, with the potential to challenge existing paradigms for metabolic pathway and strain optimization as well as bioreactor operation.     

Steady-state analysis of metabolic pathways: comparing the double modulation method and the lin-log approach

The increasing interest in studying enzyme kinetics under in vivo conditions requires practical methods to estimate control parameters from experimental data. In contrast to currently established approaches of dynamic modelling, this paper addresses the steady-state analysis of metabolic pathways. Within the framework of metabolic control analysis (MCA), elasticity coefficients are used to describe the control properties of a local enzyme reaction. The double modulation method is one of the first experimental approaches to estimate elasticity coefficients from measurements of steady-state flux rates and metabolite concentrations. We propose a generalized form of the double modulation method and compare it to the recently developed linear-logarithmic approach.     

Process engineering for microbial production of 3-hydroxypropionic acid

Due to concerns about the unsustainability and predictable shortage of fossil feedstocks, research efforts are currently being made to develop new processes for production of commodities using alternative feedstocks. 3-Hydroxypropionic acid (CAS 503–66-2) was recognised by the US Department of Energy as one of the most promising value-added chemicals that can be obtained from biomass. This article aims at reviewing the various strategies implemented thus far for 3-hydroxypropionic acid bioproduction. Special attention is given here to process engineering issues. The variety of possible metabolic pathways is also described in order to highlight how process design can be guided by their understanding. The most recent advances are described here in order to draw up a panorama of microbial 3-hydroxypropionic acid production: best performances to date, remaining hurdles and foreseeable developments. Important milestones have been achieved, and process metrics are getting closer to commercial relevance. New strategies are continuously being developed that involve new microbial strains, new technologies, or new carbon sources in order to overcome the various hurdles inherent to the different microbial routes.     

A computational tool for the simulation and optimization of microbial strains accounting integrated metabolic/regulatory information

Background and scope

Recently, a number of methods and tools have been proposed to allow the use of genome-scale metabolic models for the phenotype simulation and optimization of microbial strains, within the field of Metabolic Engineering (ME). One of the limitations of most of these algorithms and tools is the fact that only metabolic information is taken into account, disregarding knowledge on regulatory events.

Implementation and performances

This work proposes a novel software tool that implements methods for the phenotype simulation and optimization of microbial strains using integrated models, encompassing both metabolic and regulatory information. This tool is developed as a plug-in that runs over OptFlux, a computational platform that aims to be a reference tool for the ME community.

Availability

The plug-in is made available in the OptFlux web site (www.optflux.org) together with examples and documentation.