Evaluation of different vector design strategies for the expression of recombinant monoclonal antibody in CHO cells

Monoclonal antibodies (mAbs) have emerged as the most promising category of recombinant proteins due to their high efficiency for the treatment of a wide range of human diseases. The complex nature of mAbs creates a great deal of challenges in both upstream and downstream manufacturing processes. Proportional expression and correct folding and assembly of the light chain and heavy chain are required for efficient production of the mAbs. In this regard, expression vector design has proven to have profound effects on the antibody expression level as well as its stability and quality. Here, we have explored the efficiency of different vector design strategies for the expression of a recombinant IgG1 antibody in Chinese hamster ovary (CHO) cells. The antibody expression level was analyzed in transient expression and stable cell pools followed by expression analysis on single-cell clones. While detectable amounts of antibody were observed in all three systems, dual-promoter single-vector system showed the highest expression level in transient and stable expression as well as the highest productivity among clonal cells. Our results here show the importance of vector design for successful production of whole mAbs in CHO cells.     

雨水花园设计的生态表达

雨水花园设计的生态表达是对雨水花园设计中有雨水花园特色的生态性要素和有雨水生态特征的设计表达方法的探讨。雨水花园设计中有特色的生态过程主要有雨水处理的生态过程、花园生态系统中植物生态过程以及人感知雨水生态的精神生态过程。基于现阶段雨水花园设计实践,在生态综合效应下,建构了由有特征的生态性要素、生态显露设计和生态技术联盟组成的雨水花园设计生态表达图式。     

Rapid establishment of high-producing cell lines using dicistronic vectors with glutamine synthetase as the selection marker

Recombinant proteins are useful tools in biological research, drug development, and drug screening. Specially designed expression vectors have been developed to introduce cDNA for recombinant protein expression in mammalian cells. We have combined a discistronic mRNA design for expression of the recombinant protein, using glutamine synthetase (GS) for selection. A soluble form of human interleukin-4 receptor alpha chain was used as the model protein. The dicistronic vectors were compared to a standard expression vector in CHO-K1 cells in parallel experiments. Our data showed that a dicistronic vector containing an internal ribosome entry site (IRES) of the encephalomyocarditis virus (ECMV) was superior to a conventional expression vector in both levels of protein expression and amplification efficiency. The productivity of these clones was stable without selection pressure for an extended period of time. The GS selection system within a dicistronic vector design can achieve rapid and efficient gene amplification for protein production.     

Design and Analysis of Two-Phase Experiments for Gene Expression Microarrays—Part I

Summary .   Gene expression microarray experiments are intrinsically two-phase experiments. Messenger RNA (mRNA), required for the microarray experiment, must first be derived from plants or animals that are exposed to a set of treatments in a previous experiment (Phase 1). The mRNA is then used in the subsequent laboratory-based microarray experiment (Phase 2) from which gene expression is measured and ultimately analyzed. We show that obtaining a valid test for the effects of treatments on gene expression depends on the design of both the Phase 1 and Phase 2 experiments. Examples show that the multiple dye-swap design at Phase 2 is more robust than the alternating loop design in the absence of prior knowledge of the relative size of variation in the Phase 1 and Phase 2 experiments.     

Design and analysis of two-phase experiments for gene expression microarrays-part I.

Gene expression microarray experiments are intrinsically two-phase experiments. Messenger RNA (mRNA), required for the microarray experiment, must first be derived from plants or animals that are exposed to a set of treatments in a previous experiment (Phase 1). The mRNA is then used in the subsequent laboratory-based microarray experiment (Phase 2) from which gene expression is measured and ultimately analyzed. We show that obtaining a valid test for the effects of treatments on gene expression depends on the design of both the Phase 1 and Phase 2 experiments. Examples show that the multiple dye-swap design at Phase 2 is more robust than the alternating loop design in the absence of prior knowledge of the relative size of variation in the Phase 1 and Phase 2 experiments.     

Mathematical modeling of translation initiation for the estimation of its efficiency to computationally design mRNA sequences with desired expression levels in prokaryotes

Background  

Within the emerging field of synthetic biology, engineering paradigms have recently been used to design biological systems with novel functionalities. One of the essential challenges hampering the construction of such systems is the need to precisely optimize protein expression levels for robust operation. However, it is difficult to design mRNA sequences for expression at targeted protein levels, since even a few nucleotide modifications around the start codon may alter translational efficiency and dramatically (up to 250-fold) change protein expression. Previous studies have used ad hoc approaches (e.g., random mutagenesis) to obtain the desired translational efficiencies for mRNA sequences. Hence, the development of a mathematical methodology capable of estimating translational efficiency would greatly facilitate the future design of mRNA sequences aimed at yielding desired protein expression levels.     

含有分裂型内含肽DnaE基因的表达盒设计、合成及高效表达载体的构建

目的:建立一种简便、快捷的基因从头设计、优化与合成策略,进行含有分裂型内含肽DnaE基因的表达盒全合成并构建高效表达载体。方法:以免费软件GeneDesign 3.0为主要平台,同时结合Tandem Repeats Finder、UNAFold等不同生物信息学软件,对含有DnaE基因、合适酶切位点的表达盒进行设计与分段合成;合成寡核苷酸片段通过重叠PCR进行组装与克隆。结果:利用建立的设计流程,合成了大小为44～64 nt的14段寡核苷酸片段,通过重叠PCR,实现了14段寡核苷酸片段的一次性组装,经过克隆、酶切鉴定、序列分析得到了序列完全正确的表达载体。结论:建立了一套有效的、基于免费软件的基因从头设计与合成的策略,构建了可以用于环肽小分子文库表达与筛选的表达载体。     

A simple strategy for generation of gene knockdown constructs with convergent H1 and U6 promoters

RNA interference (RNAi) is a powerful tool for functional genetic studies in model organisms and mammalian cells. To facilitate rapid construction of gene knockdown constructs and RNAi libraries for known genes of mammalian cells, a new and simple strategy to produce small interfering RNA (siRNA) expression vectors with two opposing polymerase III promoters was developed. The design involved a one-step PCR amplification and single cloning procedure to construct a dual promoter siRNA expression vector. The forward primer is identical for all PCR reactions, only a single reverse primer that contains the siRNA targeting sequence has to be synthesized in the construction of each individual vector. This single primer design is cost-effective and it reduces the risk of sequence errors during synthesis of long oligos. Sense and antisense strands of siRNA duplexes were transcribed from the same template and this eliminated the need to synthesize long hairpin-forming oligonucleotides. Our study demonstrated that this vector design could mediate potent inhibition of expression of both exogenous and endogenous genes in mammalian cells.     

Evaluation of experimental designs for two-color cDNA microarrays.

The major goal of two-color cDNA microarray experiments is to measure the relative gene expression level (i.e., relative amount of mRNA) of each gene between samples in studies of gene expression. More specifically, given an N-sample experiment, we need all N(N - 1)/2 relative expression levels of all sample pairs of each gene for identification of the differentially expressed genes and for clustering of gene expression patterns. However, the intensities observed from two-color cDNA microarray experiments do not simply represent the relative gene expression level. They are composed of signal (gene expression level), noise, and other factors. In discussions on the experimental design of two-color cDNA microarray experiments, little attention has been given to the fact that different combinations of test and control samples will produce microarray intensities data with varying intrinsic composition of factors. As a consequence, not all experimental designs for two-color cDNA microarray experiments are able to provide all possible relative gene expression levels. This phenomenon has never been addressed. To obtain all possible relative gene expression levels, a novel method for two-color cDNA microarray experimental design evaluation is necessary that will allow the making of an accurate choice. In this study, we propose a model-based approach to illustrate how the factor composition of microarray intensities changed with different experimental designs in two-color cDNA microarray experiments. By analyzing 12 experimental designs (including 5 general forms), we demonstrate that not all experimental designs are able to provide all possible relative gene expression levels due to the differences in factor composition. Our results indicate that whether an experimental design can provide all possible relative expression levels of all sample pairs for each gene should be the first criterion to be considered in an evaluation of experimental designs for two-color cDNA microarray experiments.     

Normalization of two-channel microarrays accounting for experimental design and intensity-dependent relationships

In normalizing two-channel expression arrays, the ANOVA approach explicitly incorporates the experimental design in its model, and the MA plot-based approach accounts for intensity-dependent biases. However, both approaches can lead to inaccurate normalization in fairly common scenarios. We propose a method called efficient Common Array Dye Swap (eCADS) for normalizing two-channel microarrays that accounts for both experimental design and intensity-dependent biases. Under reasonable experimental designs, eCADS preserves differential expression relationships and requires only a single array per sample pair.     

Experimental design for gene expression microarrays

We examine experimental design issues arising with gene expression microarray technology. Microarray experiments have multiple sources of variation, and experimental plans should ensure that effects of interest are not confounded with ancillary effects. A commonly used design is shown to violate this principle and to be generally inefficient. We explore the connection between microarray designs and classical block design and use a family of ANOVA models as a guide to choosing a design. We combine principles of good design and A-optimality to give a general set of recommendations for design with microarrays. These recommendations are illustrated in detail for one kind of experimental objective, where we also give the results of a computer search for good designs.     

Optimal design and analysis of genetic studies on gene expression

Whole-genome profiling of gene expression in a segregating population has the potential to identify the regulatory consequences of natural allelic variation. Costs of such studies are high and require that resources--microarrays and population--are used as efficiently as possible. We show that current studies can be improved significantly by a new design for two-color microarrays. Our "distant pair design" profiles twice as many individuals as there are arrays, cohybridizes individuals with dissimilar genomes, gives more weight to known regulatory loci if wished, and therewith maximizes the power for decomposing expression variation into regulatory factors. It can also exploit a large population (larger than twice the number of available microarrays) as a useful resource to select the most dissimilar pairs of individuals from. Our approach identifies more regulatory factors than alternative strategies do in computer simulations for realistic genome sizes, and similar promising results are obtained in an application on Arabidopsis thaliana. Our results will aid the design and analysis of future studies on gene expression and will help to shed more light on gene regulatory networks.     

Inducible product gene expression technology tailored to bioprocess engineering

Bioprocess engineering has developed as a discipline to design optimal culture conditions and bioreactor operation protocols for production cell lines engineered for constitutive expression of desired protein pharmaceuticals. With the advent of heterologous gene regulation systems it has become possible to fine-tune expression of difficult-to-produce protein pharmaceuticals to optimal levels and to conditionally engineer cell metabolism for the best production performance. However, most of the small-molecules used to trigger expression of product or metabolic engineering product genes are incompatible with downstream processing regulations or process economics. Recent progress in product gene control design has resulted in the development of bioprocess-compatible regulation systems, which are responsive to physical parameters such as temperature or physiologic trigger molecules that are either an inherent part of host cell metabolism or intrinsic components of licensed protein-free cell culture media, such as redox status, vitamin H and gaseous acetaldehyde. While all of these systems have been shown to fine-tune product gene expression independent of the host cell metabolism some of them can be plugged into metabolic networks to capture critical physiologic parameters and convert them into an optimal production response. Assembly of individual product gene control modalities into synthetic networks has recently enabled construction of autonomously regulated time-delay or cell density-sensitive gene circuits, which trigger population-wide induction of product gene expression at a predefined time or culture density. We provide a comprehensive overview on the latest developments in the design of bioprocess-compatible product gene control systems.     

RNA干扰分子的制作

小干扰RNA是一种能够在各种生物体和细胞(包括蠕虫、果蝇、植物、哺乳动物)中减弱基因表达的有效工具。在哺乳动物中转染的siRNA能够抑制特殊基因的表达,这已经证明是探索基因功能、基因敲除、抗病毒研究、基因治疗的有效方法。简单、有效、特异性地抑制基因的表达具有巨大的科学、商业和医学治疗价值。如何设计和制作siRNA是影响RNA干扰效率的一个很重要的方面。本文就siRNA的设计和制作等方面作扼要的介绍。     

An automated high-throughput screening method for the identification of high-yield, soluble protein variants using cell-free expression and systematic truncation

A highly automated method for rapidly identifying soluble protein variants with good expression yields has been developed. This method is based on a commercially available in vitro protein expression system. It consists of two polymerase chain reactions (PCR) followed by in vitro protein expression and protein quantification by dot blot. The PCR protocols have been improved and optimized to allow automation using commercial fluid handling devices. A PCR primer design program has also been implemented to streamline protein variant design. This automated protocol is highly reliable and has tremendously improved the throughput of expression screening as compared to conventional cell-based methods and manual in vitro methods. We have applied this method to 32 problematic targets from the TB Structural Genomics Consortium. Experimental results of these studies are reported.