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At least 433 records · Page 24Linked to original sources

PubMed2006

Engineering of a xylose metabolic pathway in Corynebacterium glutamicum.

The aerobic microorganism Corynebacterium glutamicum was metabolically engineered to broaden its substrate utilization range to include the pentose sugar xylose, which is commonly found in agricultural residues and other lignocellulosic biomass. We demonstrated the functionality of the corynebacterial xylB gene encoding xylulokinase and constructed two recombinant C. glutamicum strains capable of utilizing xylose by cloning the Escherichia coli gene xylA encoding xylose isomerase, either alone (strain CRX1) or in combination with the E. coli gene xylB (strain CRX2). These genes were provided on a high-copy-number plasmid and were under the control of the constitutive promoter trc derived from plasmid pTrc99A. Both recombinant strains were able to grow in mineral medium containing xylose as the sole carbon source, but strain CRX2 grew faster on xylose than strain CRX1. We previously reported the use of oxygen deprivation conditions to arrest cell replication in C. glutamicum and divert carbon source utilization towards product production rather than towards vegetative functions (M. Inui, S. Murakami, S. Okino, H. Kawaguchi, A. A. Vertès, and H. Yukawa, J. Mol. Microbiol. Biotechnol. 7:182-196, 2004). Under these conditions, strain CRX2 efficiently consumed xylose and produced predominantly lactic and succinic acids without growth. Moreover, in mineral medium containing a sugar mixture of 5% glucose and 2.5% xylose, oxygen-deprived strain CRX2 cells simultaneously consumed both sugars, demonstrating the absence of diauxic phenomena relative to the new xylA-xylB construct, albeit glucose-mediated regulation still exerted a measurable influence on xylose consumption kinetics.

Aldose-Ketose Isomerases↗

PubMed2001

Biochemical engineering of natural product biosynthesis pathways.

Metabolic engineering of natural products is a science that has been built on the goals of traditional strain improvement with the availability of modern molecular biological technologies. In the past 15 years, the state of the art in metabolic engineering of natural products has advanced from the first proof-of-principle experiment based on minimal known genetics to a commonplace event using highly specific and sophisticated gene manipulation methods. With the availability of genes, host organisms, vector systems, and standard molecular biological tools, it is expected that metabolic engineering will be translated into industrial reality.

Bacteria↗

PubMed2006

Engineering isoflavone metabolism with an artificial bifunctional enzyme.

Plant secondary metabolism has been a focus of research in recent years due to its significant roles in plant defense and in human medicine and nutrition. A protein engineering strategy was designed to more effectively manipulate plant secondary metabolite (isoflavonoid) biosynthesis. A bifunctional isoflavone synthase/chalcone isomerase (IFS/CHI) enzyme was constructed by in-frame gene fusion, and expressed in yeast and tobacco. The fusion protein was targeted to the endoplasmic reticulum (ER) membrane and the individual enzymatic functions of its component fragments were retained when assayed in yeast. Petals and young leaves of IFS/CHI transgenic tobacco plants produced higher levels of the isoflavone genistein and genistein glycosides as a ratio of total flavonoids produced than did plants transformed with IFS alone. Thus, through a combined molecular modeling, in vitro protein engineering and in planta metabolic engineering approach, it was possible to increase the potential for accumulation of isoflavonoid compounds in non-legume plants. Construction of bifunctional enzymes will simplify the transformation of plants with multiple pathway genes, and such enzymes may find broad uses for enzyme (e.g., cytochrome P450 family) and biochemical pathway engineering.

Artificial Gene Fusion↗

PubMed2004

Mapping phenotypic landscapes using DNA micro-arrays.

Inverse metabolic engineering is a useful approach for engineering phenotypes in biological systems. The overarching objective of this approach is to combine the power of evolutionary engineering approaches with the precision of constructive metabolic engineering strategies. Often the difficulty in this approach is elucidating the genetic basis of the phenotypes that emerge as a result of evolutionary mechanisms. As a result of advances in genomics technologies, several techniques now exist that substantially improve researchers ability to identify such genes. Metabolic engineers now have the ability to map phenotypic landscapes of considerable genetic diversity, which should improve understanding of the relationships that exist among phenotype, genotype, and environment. In this mini-review, we will discuss several of such genomics tools that may be useful in developing inverse metabolic engineering strategies and, in particular, mapping phenotypic landscapes.

Animals↗

PubMed2000

Plant one-carbon metabolism and its engineering.

The metabolism of one-carbon (C1) units is vital to plants. It involves unique enzymes and takes place in four subcellular compartments. Plant C1 biochemistry has remained relatively unexplored, partly because of the low abundance or the lability of many of its enzymes and intermediates. Fortunately, DNA sequence databases now make it easier to characterize known C1 enzymes and to discover new ones, to identify pathways that might carry high C1 fluxes, and to use engineering to redirect C1 fluxes and to understand their control better.

Carbon↗

PubMed2004

Probing metabolic pathways with isotopic tracers: insights from mammalian metabolic physiology.

Metabolic Engineering offers an opportunity to forge a link between metabolic physiologists, working with mammalian systems and metabolic engineers. Many parallels may be drawn between the specific modification of metabolic networks to improve cellular properties and the analysis of metabolic networks in search of causes of disease. At the core of both fields is the measurement of fluxes. This issue of Metabolic Engineering highlights important topics: mammalian metabolic physiology where estimating fluxes is challenging. The challenges come from compartmentation of metabolites, from dilution of tracer by endogenous pools, and from the difficulty of sampling relevant pools. The common theme across these investigations is the use of isotopic tracers. The wide variety of tracers and tracer analysis techniques in use in mammalian metabolic physiology reflects the complexity of the systems under study. In presenting these examples from the field of mammalian metabolic physiology, our goal is to strengthen the linkages between physiologists and engineers as we develop our knowledge and appreciation of the complexity of metabolic networks.

Animals↗

PubMed2005

Revealing metabolic phenotypes in plants: inputs from NMR analysis.

Assessing the performance of the plant metabolic network, with its varied biosynthetic capacity and its characteristic subcellular compartmentation, remains a considerable challenge. The complexity of the network is such that it is not yet possible to build large-scale predictive models of the fluxes it supports, whether on the basis of genomic and gene expression analysis or on the basis of more traditional measurements of metabolites and their interconversions. This limits the agronomic and biotechnological exploitation of plant metabolism, and it undermines the important objective of establishing a rational metabolic engineering strategy. Metabolic analysis is central to removing this obstacle and currently there is particular interest in harnessing high-throughput and/or large-scale analyses to the task of defining metabolic phenotypes. Nuclear magnetic resonance (NMR) spectroscopy contributes to this objective by providing a versatile suite of analytical techniques for the detection of metabolites and the fluxes between them. The principles that underpin the analysis of plant metabolism by NMR are described, including a discussion of the measurement options for the detection of metabolites in vivo and in vitro, and a description of the stable isotope labelling experiments that provide the basis for metabolic flux analysis. Despite a relatively low sensitivity, NMR is suitable for high-throughput system-wide analyses of the metabolome, providing methods for both metabolite fingerprinting and metabolite profiling, and in these areas NMR can contribute to the definition of plant metabolic phenotypes that are based on metabolic composition. NMR can also be used to investigate the operation of plant metabolic networks. Labelling experiments provide information on the operation of specific pathways within the network, and the quantitative analysis of steady-state labelling experiments leads to the definition of large-scale flux maps for heterotrophic carbon metabolism. These maps define multiple unidirectional fluxes between branch-points in the metabolic network, highlighting the existence of substrate cycles and discriminating in favourable cases between fluxes in the cytosol and plastid. Flux maps can be used to define a functionally relevant metabolic phenotype and the extensive application of such maps in microbial systems suggests that they could have important applications in characterising the genotypes produced by plant genetic engineering.

Biotechnology↗

PubMed2003

6-Deoxyerythronolide B analogue production in Escherichia coli through metabolic pathway engineering.

The erythromycin precursor polyketide 6-deoxyerythronolide B (6-dEB) is produced from one propionyl-CoA starter unit and six (2S)-methylmalonyl-CoA extender units. In vitro studies have previously demonstrated that the loading module of 6-deoxyerythronolide B synthase (DEBS) exhibits relaxed substrate specificity and is able to accept butyryl-CoA, leading to the production of polyketides with butyrate starter units. We have shown that we can produce butyryl-CoA at levels of up to 50% of the total CoA pool in Escherichia coli cells that overexpress the acetoacetyl-CoA:acetyl-CoA transferase, AtoAD (EC 2.8.3.8), in media supplemented with butyrate. The DEBS polyketide synthase (PKS) used butyryl-CoA and methylmalonyl-CoA supplied in vivo by the AtoAD and methylmalonyl-CoA mutase pathways, respectively, to produce 15-methyl-6-dEB. Priming DEBS with endogenous butyryl-CoA affords an alternative and more direct route to 15-Me-6-dEB than that provided by the chemobiosynthesis method [Jacobsen, J. R., et al. (1997) Science 277, 367-369], which relies on priming a mutant DEBS with an exogenously fed diketide thioester. The approach described here demonstrates the utility of metabolic engineering in E. coli to introduce precursor pathways for the production of novel polyketides.

Acetoacetates↗

PubMed2002

Engineering of molecular and cellular biocatalysts: selected contributions by James E. Bailey.

James (Jay) E. Bailey was a pioneer in biotechnology and biochemical engineering. During his 30 years in academia he made seminal contributions to many fields of chemical engineering science, including catalysis and reaction engineering, bioprocess engineering, mathematical modeling of cellular processes, recombinant DNA technology, enzyme engineering, and metabolic engineering. This article celebrates some of his contributions to the engineering of molecular and cellular biocatalysts, and identifies the influence he had on current and future research in biotechnology.

Biochemistry↗

PubMed2006

Bio-ethanol--the fuel of tomorrow from the residues of today.

The increased concern for the security of the oil supply and the negative impact of fossil fuels on the environment, particularly greenhouse gas emissions, has put pressure on society to find renewable fuel alternatives. The most common renewable fuel today is ethanol produced from sugar or grain (starch); however, this raw material base will not be sufficient. Consequently, future large-scale use of ethanol will most certainly have to be based on production from lignocellulosic materials. This review gives an overview of the new technologies required and the advances achieved in recent years to bring lignocellulosic ethanol towards industrial production. One of the major challenges is to optimize the integration of process engineering, fermentation technology, enzyme engineering and metabolic engineering.

Agriculture↗

PubMed2005

Application of hammerhead ribozymes in filamentous fungi.

Metabolic engineering in filamentous fungi is a emerging field of research as many fungi produce high value primary and secondary metabolites. Ribozyme technology can be used as a tool for metabolic engineering to influence metabolic pathways and to knock down the expression of specific genes of interest. Hammerhead ribozymes can target virtually any mRNA sequence of choice and prevent gene expression on the post-transcriptional level. They are thus a versatile tool for timed and spatial elimination of unwanted gene products. As current research has only investigated the application of ribozymes in bacteria, yeast and mammalian cells, we decided to carry out a study on whether this technology can also function with filamentous fungi. We employed a sensitive, quantitative reporter-based model system as a proof of concept, using the Escherichia coli beta-glucuronidase transcript (uidA) as the target mRNA and Aspergillus giganteus as the host. This system was used to validate the in vivo activities of seven different hammerhead ribozymes, which were selected by in silico analysis of the uidA mRNA. All ribozymes tested were able to reduce the reporter activity up to a maximum of 100%, demonstrating that ribozyme technology is indeed a useful tool in fungal metabolic engineering.

Aspergillus↗

PubMed2025

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets.

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Escherichia coli↗

PubMed2026

Mechanistic Perspectives From Genomics and Pangenomics of Medicinal and Aromatic Plants: Linking Genome Architecture to Phytochemical Diversity.

Medicinal and aromatic plants (MAPs) produce a remarkable diversity of specialized metabolites with significant pharmaceutical, nutraceutical, and industrial value. Although advances in long-read sequencing, chromosome-scale genome assembly, and pangenomics have greatly expanded genomic resources, the mechanistic links between genome architecture and phytochemical diversity remain incompletely understood. The present review synthesizes current evidence describing how structural genomic variation may contribute to phytochemical diversity, while acknowledging that many proposed genome-to-metabolite relationships require further experimental validation. Examples illustrate how genome architecture is associated with specialized-metabolite biosynthesis through multiple regulatory processes. However, the strength of supporting evidence varies considerably among MAP species. Moreover, relatively few genome-to-metabolite relationships have been confirmed through direct functional validation. We further discuss how pangenomics, multiomics integration, genome editing, synthetic biology, and artificial intelligence support the discovery, validation, and engineering of specialized metabolic pathways. Casual conclusions are evaluated according to the strength of available evidence, highlighting where causal relationships have been experimentally established and where conclusions remain primarily association-based. Overall, this review provides an integrated conceptual and evidence-based perspective summarizing proposed relationships between genome architecture and phytochemical diversity and outlines future priorities for functional genomics, precision breeding, metabolic engineering, and sustainable utilization of MAPs.

artificial intelligence↗

PubMed2026

Membrane and proteome allocation constraints in Escherichia coli models during overflow metabolism.

The allocation of finite cellular resources is a fundamental principle that dictates microbial metabolic strategies and gives rise to complex phenomena, such as overflow metabolism, characterized by the production of respiro-fermentative by-products, including acetate, during rapid growth. Although proteome-constrained models have successfully predicted overflow metabolism in Escherichia coli, they often overlook the distinct biophysical and energetic costs associated with protein localization. The cellular membrane, in particular, represents a critical and constrained compartment where competition for space and synthesis machinery can create significant metabolic bottlenecks. To investigate this, we developed the membrane-associated constrained flux balance analysis (MAFBA), a scalable, genome-scale metabolic model that introduces a tunable constraint on the total protein mass allocated to the cellular membrane. Our model demonstrates that the overall and membrane-associated proteome allocation constraints interact to improve the accuracy of predicting the onset of overflow metabolism. It mechanistically reveals that at high growth rates, competition for limited membrane allocation forces a trade-off between growth-essential functions and respiratory capacity, leading to acetate production. Furthermore, MAFBA quantitatively explains the widely observed experimental phenomenon that expressing heterologous membrane proteins imposes a significantly higher metabolic burden than expressing cytosolic proteins. This study establishes membrane resource allocation as a key constraint governing bacterial physiology, acting in concert with overall proteome limitations. The resulting MAFBA framework provides a powerful and accessible tool for synthetic biology and metabolic engineering, enabling the prediction of metabolic costs associated with expressing membrane-bound proteins and guiding strain design strategies, holding promise for applications in bioproduction and metabolic engineering.

Escherichia coli↗

PubMed1998

Redesigning metabolic networks using mathematical programming

The design of new generation bioprocessing plants is increasingly dependent on the design of process-compatible microorganisms. The latter, whether through genetic or physiological manipulations, can be greatly assisted by metabolic engineering. An emerging powerful tool in metabolic engineering research is computer-assisted cell design using mathematical programming. In this work, the problem of optimizing cellular metabolic networks has been formulated as a Mixed Integer Nonlinear Programming (MINLP) model. The model can assist genetic engineers to identify which cellular enzymes should be modified, and the new levels of activity required to produce an optimal network. Results are presented from the tricarboxylic acid cycle in Dictyostelium discoideum. Copyright 1998 John Wiley & Sons, Inc.

Journal Article↗

PubMed2003

Metabolic oligosaccharide engineering as a tool for glycobiology.

Oligosaccharides transact information exchange at the cell surface and modulate the activities and distribution of proteins within cells. Recently, the ability to modify monosaccharide structures within cellular glycans through metabolic processes has offered a new avenue for biological studies. The technique of metabolic oligosaccharide engineering has been used to disrupt glycan biosynthesis, chemically modify cell surfaces, probe metabolic flux inside cells, and to identify specific glycoprotein subtypes from the proteome.

Animals↗

PubMed2005

Biotechnological production and applications of coenzyme Q10.

Coenzyme Q10 is widely used as an essential component of ATP generation in the oxidative phosphorylation process and as an antioxidant preventing lipid peroxidation and scavenging superoxide. It is also recommended as a supplement to 3-hydroxy-3-methylglutaryl coenzyme A reductase inhibitors. Research efforts on the production of coenzyme Q10 by microorganisms focus on the development of potent strains by conventional mutagenesis and metabolic engineering, analysis and modification of the key metabolic pathways and optimization of fermentation strategies. Especially, random mutants with drugs resistance show a high coenzyme Q10 concentration. Metabolic engineering techniques have been applied to improve coenzyme Q10 production. The key enzymes involved in the coenzyme Q10 biosynthesis pathway have been cloned and expressed in Escherichia coli. The rational design of metabolic pathways in combination with engineering optimization of fermentation processes could facilitate the development of viable bioconversion processes.

Antioxidants↗

PubMed2004

Control of fluxes towards antibiotics and the role of primary metabolism in production of antibiotics.

Yield improvements in antibiotic-producing strains have classically been obtained through random mutagenesis and screening. An attractive alternative to this strategy is the rational design of producer strains via metabolic engineering, an approach that offers the possibility to increase yields while avoiding the problems of by-product formation and altered morphological properties, which frequently arise in mutagenized strains. An important aspect in the design of strains with improved yields by metabolic engineering is the identification of rate-controlling enzymatic reactions in the metabolic network. Here we describe and discuss available methods for identification of these steps, both in antibiotic biosynthesis pathways and in the primary metabolism, which serves as the supplier of precursors and cofactors for the secondary metabolism. Finally, the importance of precursor and cofactor supply from primary metabolism in the biosynthesis of different types of antibiotics is discussed and recent developments in metabolic engineering towards increased product yields in antibiotic producing strains are reviewed.

Anti-Bacterial Agents↗