代谢工程中基因修饰与基因表达的工具

代谢工程利用重组DNA技术导入定向改造的基因 ,以改进微生物细胞的某些代谢特性 ,已经发展成为一个工业微生物育种和优化发酵过程的强有力工具。基因的修饰与表达是代谢工程的重要组成部分。本文介绍了近年来代谢工程中基因修饰与表达所用的工具方面的进展。     

Genetic engineering of peppermint for improved essential oil composition and yield

The biochemistry, organization, and regulation of essential oil metabolism in the epidermal oil glands of peppermint have been defined, and most of the genes encoding enzymes of the eight-step pathway to the principal monoterpene component (−)-menthol have been isolated. Using these tools for pathway engineering, two genes and two expression strategies have been employed to create transgenic peppermint plants with improved oil composition and yield. These experiments, along with related studies on other pathway genes, have led to a systematic, stepwise approach for the creation of a ‘super’ peppermint.     

New Applications for Phage Integrases

Within the last 25 years, bacteriophage integrases have rapidly risen to prominence as genetic tools for a wide range of applications from basic cloning to genome engineering. Serine integrases such as that from ?C31 and its relatives have found an especially wide range of applications within diverse micro-organisms right through to multi-cellular eukaryotes. Here, we review the mechanisms of the two major families of integrases, the tyrosine and serine integrases, and the advantages and disadvantages of each type as they are applied in genome engineering and synthetic biology. In particular, we focus on the new areas of metabolic pathway construction and optimization, biocomputing, heterologous expression and multiplexed assembly techniques. Integrases are versatile and efficient tools that can be used in conjunction with the various extant molecular biology tools to streamline the synthetic biology production line.     

Applications of genetically-encoded biosensors for the construction and control of biosynthetic pathways

Cells are filled with biosensors, molecular systems that measure the state of the cell and respond by regulating host processes. In much the same way that an engineer would monitor a chemical reactor, the cell uses these sensors to monitor changing intracellular environments and produce consistent behavior despite the variable environment. While natural systems derive a clear benefit from pathway regulation, past research efforts in engineering cellular metabolism have focused on introducing new pathways and removing existing pathway regulation. Synthetic biology is a rapidly growing field that focuses on the development of new tools that support the design, construction, and optimization of biological systems. Recent advances have been made in the design of genetically-encoded biosensors and the application of this class of molecular tools for optimizing and regulating heterologous pathways. Biosensors to cellular metabolites can be taken directly from natural systems, engineered from natural sensors, or constructed entirely in vitro. When linked to reporters, such as antibiotic resistance markers, these metabolite sensors can be used to report on pathway productivity, allowing high-throughput screening for pathway optimization. Future directions will focus on the application of biosensors to introduce feedback control into metabolic pathways, providing dynamic control strategies to increase the efficient use of cellular resources and pathway reliability.     

Metabolic engineering of bacteria

Yield and productivity are critical for the economics and viability of a bioprocess. In metabolic engineering the main objective is the increase of a target metabolite production through genetic engineering. Metabolic engineering is the practice of optimizing genetic and regulatory processes within cells to increase the production of a certain substance. In the last years, the development of recombinant DNA technology and other related technologies has provided new tools for approaching yields improvement by means of genetic manipulation of biosynthetic pathway. Industrial microorganisms like Escherichia coli, Actinomycetes, etc. have been developed as biocatalysts to provide new or to optimize existing processes for the biotechnological production of chemicals from renewable plant biomass. The factors like oxygenation, temperature and pH have been traditionally controlled and optimized in industrial fermentation in order to enhance metabolite production. Metabolic engineering of bacteria shows a great scope in industrial application as well as such technique may also have good potential to solve certain metabolic disease and environmental problems in near future.     

Engineering microbial cell factories for biosynthesis of isoprenoid molecules: beyond lycopene

The isoprenoid superfamily of compounds holds great potential for delivering commercial therapeutics, neutraceuticals and fine chemicals. As such, it has attracted widespread attention and prompted research aimed at metabolic engineering of the pathway for isoprenoid overproduction. The carotenoids in particular, because of their convenient colorimetric screening properties, have facilitated the investigation of new tools for pathway optimization. Because all isoprenoids share common metabolic precursors, genetic platforms resulting from work with carotenoids can be applied to the biosynthesis of other valuable products. In this review we summarize the many tools and methods that have been developed for isoprenoid pathway engineering, and the potential of these technologies for producing other molecules of this family, especially terpenoids.     

Correlation of Gene Expression and Genome Mutation in Single B-Cells

High-throughput measurement of gene-expression and immune receptor repertoires have recently become powerful tools in the study of adaptive immune response. However, despite their now-widespread use, both tend to discard cell identity by treating cell populations in bulk, and therefore lose the correlation between genetic variability and gene-expression at the single cell level. In order to recover this information, we developed a method to simultaneously measure gene expression profiles and genome mutations in single cells. We applied this method by quantifying the relationships between gene expression and antibody mutation in ensembles of individual B-cells from immunized mice. The results reveal correlations reflecting the manner in which information propagates between a B-cell’s antigen receptors, its gene expression, and its mutagenic machinery, and demonstrate the power of this approach to illuminate both heterogeneity and physiology in cell populations.     

MADE4: an R package for multivariate analysis of gene expression data

SUMMARY: MADE4, microarray ade4, is a software package that facilitates multivariate analysis of microarray gene-expression data. MADE4 accepts a wide variety of gene-expression data formats. MADE4 takes advantage of the extensive multivariate statistical and graphical functions in the R package ade4, extending these for application to microarray data. In addition, MADE4 provides new graphical and visualization tools that aid in interpretation of multivariate analysis of microarray data.     

A family-based test for correlation between gene expression and trait values

Advances in microarray technology have made it attractive to combine information on clinical traits, marker genotypes, and comprehensive gene expression from family studies to dissect complex disease genetics. Without accounting for family structure, methods that test for association between a trait and gene-expression levels can be misleading. We demonstrate that the standard unstratified test based on Pearson's correlation coefficient can produce spurious results when applied to family data, and we present a stratified family expression association test (FEXAT). We illustrate the utility of the FEXAT via simulation and an application to gene-expression data from lymphoblastoid cell lines from four CEPH families. The FEXAT has a smaller estimated false-discovery rate than the standard test when within-family correlations are of interest, and it detects biologically plausible correlations between beta catenin and genes in the WNT-activation pathway in humans that the standard test does not.     

Technological advances and genomics in metazoan parasites

Molecular biology has provided the means to identify parasite proteins, to define their function, patterns of expression and the means to produce them in quantity for subsequent functional analyses. Whole genome and expressed sequence tag programmes, and the parallel development of powerful bioinformatics tools, allow the execution of genome-wide between stage or species comparisons and meaningful gene-expression profiling. The latter can be undertaken with several new technologies such as DNA microarray and serial analysis of gene expression. Proteome analysis has come to the fore in recent years providing a crucial link between the gene and its protein product. RNA interference and ballistic gene transfer are exciting developments which can provide the means to precisely define the function of individual genes and, of importance in devising novel parasite control strategies, the effect that gene knockdown will have on parasite survival.     

Engineering genes for predictable protein expression

The DNA sequence used to encode a polypeptide can have dramatic effects on its expression. Lack of readily available tools has until recently inhibited meaningful experimental investigation of this phenomenon. Advances in synthetic biology and the application of modern engineering approaches now provide the tools for systematic analysis of the sequence variables affecting heterologous expression of recombinant proteins. We here discuss how these new tools are being applied and how they circumvent the constraints of previous approaches, highlighting some of the surprising and promising results emerging from the developing field of gene engineering.     

The future of metabolic engineering and synthetic biology: towards a systematic practice

Industrial biotechnology promises to revolutionize conventional chemical manufacturing in the years ahead, largely owing to the excellent progress in our ability to re-engineer cellular metabolism. However, most successes of metabolic engineering have been confined to over-producing natively synthesized metabolites in E. coli and S. cerevisiae. A major reason for this development has been the descent of metabolic engineering, particularly secondary metabolic engineering, to a collection of demonstrations rather than a systematic practice with generalizable tools. Synthetic biology, a more recent development, faces similar criticisms. Herein, we attempt to lay down a framework around which bioreaction engineering can systematize itself just like chemical reaction engineering. Central to this undertaking is a new approach to engineering secondary metabolism known as 'multivariate modular metabolic engineering' (MMME), whose novelty lies in its assessment and elimination of regulatory and pathway bottlenecks by re-defining the metabolic network as a collection of distinct modules. After introducing the core principles of MMME, we shall then present a number of recent developments in secondary metabolic engineering that could potentially serve as its facilitators. It is hoped that the ever-declining costs of de novo gene synthesis; the improved use of bioinformatic tools to mine, sort and analyze biological data; and the increasing sensitivity and sophistication of investigational tools will make the maturation of microbial metabolic engineering an autocatalytic process. Encouraged by these advances, research groups across the world would take up the challenge of secondary metabolite production in simple hosts with renewed vigor, thereby adding to the range of products synthesized using metabolic engineering.