Fast sampling and quenching procedures for microbial metabolic profiling

A reliable quantification of intracellular concentrations of intermediates in microorganisms depends on a proper sampling procedure and the subsequent fast inactivation of metabolism via quenching. A single device integrating both operations was developed and simultaneously the quenching procedure on cells was assessed too, without finding negative effects on viability or metabolite leakage. Moreover, supported by an experimental design, the influences of process parameters in its dynamic operation were characterized and optimized. The novel in-situ rapid sampling and quenching apparatus can be employed on any laboratory glass fermenters accessible from the top of the bioreactor.     

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.     

The yeast Zygosaccharomyces bailii: a new host for heterologous protein production, secretion and for metabolic engineering applications

Molecular tools for the production of heterologous proteins and metabolic engineering applications of the non-conventional yeast Zygosaccharomyces bailii were developed. The combination of Z. bailii's resistance to relatively high temperature, osmotic pressure and low pH values, with a high specific growth rate renders this yeast potentially interesting for exploitation for biotechnological purposes as well as for the understanding of the biological phenomena and mechanisms underlying the respective resistances. Looking forward to these potential applications, here we present the tools required for the production and the secretion of different heterologous proteins, and one example of a metabolic engineering application of this non-conventional yeast, employing the newly developed molecular tools.     

Ensemble Modeling for Robustness Analysis in engineering non-native metabolic pathways

Metabolic pathways in cells must be sufficiently robust to tolerate fluctuations in expression levels and changes in environmental conditions. Perturbations in expression levels may lead to system failure due to the disappearance of a stable steady state. Increasing evidence has suggested that biological networks have evolved such that they are intrinsically robust in their network structure. In this article, we presented Ensemble Modeling for Robustness Analysis (EMRA), which combines a continuation method with the Ensemble Modeling approach, for investigating the robustness issue of non-native pathways. EMRA investigates a large ensemble of reference models with different parameters, and determines the effects of parameter drifting until a bifurcation point, beyond which a stable steady state disappears and system failure occurs. A pathway is considered to have high bifurcational robustness if the probability of system failure is low in the ensemble. To demonstrate the utility of EMRA, we investigate the bifurcational robustness of two synthetic central metabolic pathways that achieve carbon conservation: non-oxidative glycolysis and reverse glyoxylate cycle. With EMRA, we determined the probability of system failure of each design and demonstrated that alternative designs of these pathways indeed display varying degrees of bifurcational robustness. Furthermore, we demonstrated that target selection for flux improvement should consider the trade-offs between robustness and performance.     

Opportunities and surprises in crops modified by transgenic technology: metabolic engineering of benzylisoquinoline alkaloid, gossypol and lysine biosynthetic pathways

The development of new or improved traits in plants, whether that is through traditional genetic modification and selection or through transgenic technologies, is associated with the potential risk of unintended changes with harmful or unacceptable consequences. The greater definition and precision of transgenic modification and the regulatory oversight of such technology may, however, confer advantages in safety and efficacy. This bears considerable relevance to the use of transgenic-based metabolic engineering in agricultural trait development. Metabolic engineering seeks to modify the amounts or chemical structures within selected biosynthetic routes without introducing inadvertent effects on other metabolic pathways. Examples discussed here include attempts to; (i) modify benzylisoquinoline alkaloid biosynthesis in poppy, (ii) improve the nutritional value of maize by increasing levels of free lysine, and (iii) increase the nutritional value of cottonseed by eliminating gossypol production. Clearly, evaluation of the efficacy (and unintended consequences) of such approaches is vital. A role for metabolomics in the compositional and metabolite analyses of new plant varieties derived from transgenic-based metabolic engineering is discussed. Major themes discussed in this review include; (i) the heightened level of scrutiny associated with genetically modified (GM) crop evaluations has markedly contributed to the safety in the adoption of transgenic technology, and (ii) the nature of any introduced trait may prove more relevant to safety assessments than the means by which the trait is introduced.     

Current status of the metabolic engineering of microorganisms for biohydrogen production

The improvement of H₂ production capabilities of hydrogen (H₂)-producing microorganisms is a challenging issue. Microorganisms have evolved for fast growth and substrate utilization rather than H₂ production. To develop good H₂-producing biocatalysts, many studies have focused on the redirection and/or reconstruction of cellular metabolisms. These studies included the elimination of enzymes and carbon pathways interfering or competing with H₂ production, the incorporation of non-native metabolic pathways leading to H₂ production, the utilization of various carbon substrates, the rectification of H₂-producting enzymes (nitrogenase and hydrogenase) and photophosphorylation systems, and in silico pathway flux analysis, among others. Owing to these studies, significant improvements in the yield and rate of H₂ production, and in the stability of H₂ production activity, were reached. This review presents and discusses the recent developments in biohydrogen production, with a focus on metabolic pathway engineering.     

Optimization of metabolic pathways for bioconversion of lignocellulose to ethanol through genetic engineering

The optimization of metabolic pathways is of fundamental importance for strategies aimed at improving the economics and yield of the lignocellulose-to-ethanol processes. Although Escherichia coli is capable of metabolizing a wide variety of substrates including hexoses and pentoses, its hexose metabolism is inferior to that of Zymomonas mobilis, an obligate, ethanologenic bacterium. We therefore inserted and expressed Z. mobilis genes encoding essential enzymes involved in the fermentation pathway, alcohol dehydrogenase II (adh II) and pyruvate decarboxylase (pdc), into E. coli, resulting in increased cell growth and ethanol production. Ethanol concentrations of > 30 g/L were obtained on 10% glucose. Additionally, since pyruvate is mainly assimilated through pyruvate formate lyase (pfl) and forms formic acid and acetyl coenzyme A, metabolic redirection was attempted through gene knockout by Red-mediated recombination to decrease the byproducts of pyruvate metabolism. Under microaerobic conditions, pflA- and pflB-mutants produced more ethanol (163% and 207%, respectively) relative to the parent strain, using glucose as a carbon source.     

Transgenic caraway, Carum carvi L.: a model species for metabolic engineering

Regeneration in caraway was obtained via two different routes. Hypocotyls showed delayed shoot formation after a callus phase and at relatively low frequencies. In contrast, high-frequency, direct regeneration occurred when cotyledonary node explants were used. Transient expression of β-glucuronidase was monitored after inoculation of both explant types with Agrobacterium tumefaciens AGL0(pMOG410). Gene transfer was more efficient when using cotyledonary node explants. This explant type also proved to be the best for stable transformation resulting in transgenic plants. Several parameters determining regeneration and transformation efficiency were tested. The percentage of explants giving one to numerous transgenic plants could be as high as 13%. This system for the rapid production of many transgenic caraway plants opens up possibilities for studying metabolic engineering with this crop. Received: 8 October 1996 / Revision received: 2 January 1997 / Accepted: 2 February 1997     

Development and application of a differential method for reliable metabolome analysis in Escherichia coli

Quantitative metabolomics of microbial cultures requires well-designed sampling and quenching procedures. We successfully developed and applied a differential method to obtain a reliable set of metabolome data for Escherichia coli K12 MG1655 grown in steady-state, aerobic, glucose-limited chemostat cultures. From a rigorous analysis of the commonly applied quenching procedure based on cold aqueous methanol, it was concluded that it was not applicable because of release of a major part of the metabolites from the cells. No positive effect of buffering or increasing the ionic strength of the quenching solution was observed. Application of a differential method in principle requires metabolite measurements in total broth and filtrate for each measurement. Different methods for sampling of culture filtrate were examined, and it was found that direct filtration without cooling of the sample was the most appropriate. Analysis of culture filtrates revealed that most of the central metabolites and amino acids were present in significant amounts outside the cells. Because the turnover time of the pools of extracellular metabolites is much larger than that of the intracellular pools, the differential method should also be applicable to short-term pulse response experiments without requiring measurement of metabolites in the supernatant during the dynamic period.     

Flux analysis and metabolomics for systematic metabolic engineering of microorganisms

Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and ¹³C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering.     

A gender-specific discriminator in Sprague-Dawley rat urine: the deployment of a metabolic profiling strategy for biomarker discovery and identification

The use of nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography-mass spectrometry (LC-MS) as complementary analytical techniques for open metabolic profiling is illustrated in the context of defining urinary biochemical discriminators between male and female Sprague-Dawley rats. Subsequent to the discovery of a female-specific urinary discriminator by LC-MS, further LC, MS, and NMR methods have been applied in a coordinated effort to identify this urinary component. Thereafter, the biological relevance and context of the identified component, in this case a steroid metabolite, has been achieved. This approach will be deployed in future studies of disease, drug efficacy, and toxicity to discover and identify biologically relevant markers.     

Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

Dissecting and engineering metabolic and regulatory networks of thermophilic bacteria for biofuel production

Interest in thermophilic bacteria as live-cell catalysts in biofuel and biochemical industry has surged in recent years, due to their tolerance of high temperature and wide spectrum of carbon-sources that include cellulose. However their direct employment as microbial cellular factories in the highly demanding industrial conditions has been hindered by uncompetitive biofuel productivity, relatively low tolerance to solvent and osmic stresses, and limitation in genome engineering tools. In this work we review recent advances in dissecting and engineering the metabolic and regulatory networks of thermophilic bacteria for improving the traits of key interest in biofuel industry: cellulose degradation, pentose–hexose co-utilization, and tolerance of thermal, osmotic, and solvent stresses. Moreover, new technologies enabling more efficient genetic engineering of thermophiles were discussed, such as improved electroporation, ultrasound-mediated DNA delivery, as well as thermo-stable plasmids and functional selection systems. Expanded applications of such technological advancements in thermophilic microbes promise to substantiate a synthetic biology perspective, where functional parts, module, chassis, cells and consortia were modularly designed and rationally assembled for the many missions at industry and nature that demand the extraordinary talents of these extremophiles.     

Evaluation of a protocol for metabolic profiling studies on human blood plasma by combined ultra-performance liquid chromatography/mass spectrometry: From extraction to data analysis

The investigation presented here describes a protocol designed to perform high-throughput metabolic profiling analysis on human blood plasma by ultra-performance liquid chromatography/mass spectrometry (UPLC/MS). To address whether a previous extraction protocol for gas chromatography (GC)/MS-based metabolic profiling of plasma could be used for UPLC/MS-based analysis, the original protocol was compared with similar methods for extraction of low-molecular-weight compounds from plasma via protein precipitation. Differences between extraction methods could be observed, but the previously published extraction method was considered the best. UPLC columns with three different stationary phases (C8, C18, and phenyl) were used in identical experimental runs consisting of a total of 60 injections of extracted male and female plasma samples. The C8 column was determined to be the best for metabolic profiling analysis on plasma. The acquired UPLC/MS data of extracted male and female plasma samples was subjected to principal component analysis (PCA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA). Furthermore, a strategy for compound identification was applied here, demonstrating the strength of high-mass-accuracy time-of-flight (TOF)/MS analysis in metabolic profiling.