Retargeting of pre-set regions on chromosome for high gene expression in mammalian cells

We have developed a system to hunt and reuse special gene integration sites that allow for high and stable gene expression. A vector, named pRGFP8, was constructed. The plasmid pRGFP8 contains a reporter gene, gfp2 and two extraneous DNA fragments. The gene gfp2 makes it possible to screen the high expression regions on the chromosome. The extraneous DNA fragments can help to create the unique loci on the chromosome and increase the gene targeting frequency by increasing the homology. After transfection into Chinese hamster ovary cells (CHO) cells, the linearized pRGFP8 can integrate into the chromosome of the host cells and form the unique sites. With FACS, 90 millions transfected cells were sorted and the cells with strongest GFP expression were isolated, and then 8 stable high expression GFP CHO cell lines were selected as candidates for the new host cell. Taking the unique site created by pRGFP8 on the chromosome in the new host cells as a targeting locus, the gfp2 gene was replaced with the gene of interest, human ifngamma, by transfecting the targeting plasmid pRIH-IFN. Then using FACS, the cells with the dimmest GFP fluorescence were selected. These cells showed they had strong abilities to produce the protein of interest, IFN-gamma. During the gene targeting experiment, we found there is positive correlation between the fluorescence density of the GFP CHO host cells and the specific production rate of IFN-gamma. This result shows that the strategy in our expression system is correct: the production of the interesting protein increases with the increase fluorescence of the GFP host cells. This system, the new host cell lines and the targeting vector, can be utilized for highly expressing the gene of interest. More importantly, by using FACS, we can fully screen all the transfected cells, which can reduce the chances of losing the best cells.

“Unmixing” Tissue Gene Expression Signatures from Tumor Biopsies

Emergent molecular measurement methods, such as DNA microarray, qRTPCR, and many others, offer tremendous promise for the personalized treatment of cancer. These technologies measure the amount of specific proteins, RNA, DNA or other molecular targets from tumor specimens with the goal of “fingerprinting” individual cancers. Tumor specimens are heterogeneous; an individual specimen typically contains unknown amounts of multiple tissues types. Thus, the measured molecular concentrations result from an unknown mixture of tissue types, and must be normalized to account for the composition of the mixture. For example, a breast tumor biopsy may contain normal, dysplastic and cancerous epithelial cells, as well as stromal components (fatty and connective tissue) and blood and lymphatic vessels. Our diagnostic interest focuses solely on the dysplastic and cancerous epithelial cells. The remaining tissue components serve to “contaminate” the signal of interest. The proportion of each of the tissue components changes as a function of patient characteristics (e.g., age), and varies spatially across the tumor region. Because each of the tissue components produces a different molecular signature, and the amount of each tissue type is specimen dependent, we must estimate the tissue composition of the specimen, and adjust the molecular signal for this composition. Using the idea of a chemical mass balance, we consider the total measured concentrations to be a weighted sum of the individual tissue signatures, where weights are determined by the relative amounts of the different tissue types. We develop a compositional source apportionment model to estimate the relative amounts of tissue components in a tumor specimen. We then use these estimates to infer the tissuespecific concentrations of key molecular targets for sub-typing individual tumors. We anticipate these specific measurements will greatly improve our ability to discriminate between different classes of tumors, and allow more precise matching of each patient to the appropriate treatment

Effect of prolonged intravenous glucose and essential amino acid infusion on nitrogen balance, muscle protein degradation and ubiquitin-conjugating enzyme gene expression in calves

Background: Intravenous infusions of glucose and amino acids increase both nitrogen balance and muscle accretion. We hypothesised that co-infusion of glucose ( to stimulate insulin) and essential amino acids (EAA) would act additively to improve nitrogen balance by decreasing muscle protein degradation in association with alterations in muscle expression of components of the ubiquitin-proteasome proteolytic pathway. Methods: We examined the effect of a 5 day intravenous infusions of saline, glucose, EAA and glucose + EAA, on urinary nitrogen excretion and muscle protein degradation. We carried out the study in 6 restrained calves since ruminants offer the advantage that muscle protein degradation can be assessed by excretion of 3 methyl-histidine and multiple muscle biopsies can be taken from the same animal. On the final day of infusion blood samples were taken for hormone and metabolite measurement and muscle biopsies for expression of ubiquitin, the 14-kDa E2 ubiquitin conjugating enzyme, and proteasome sub-units C2 and C8. Results: On day 5 of glucose infusion, plasma glucose, insulin and IGF-1 concentrations were increased while urea nitrogen excretion and myofibrillar protein degradation was decreased. Co-infusion of glucose + EAA prevented the loss of urinary nitrogen observed with EAA infusions alone and enhanced the increase in plasma IGF-1 concentration but there was no synergistic effect of glucose + EAA on the decrease in myofibrillar protein degradation. Muscle mRNA expression of the ubiquitin conjugating enzyme, 14-kDa E2 and proteasome sub-unit C2 were significantly decreased, after glucose but not amino acid infusions, and there was no further response to the combined infusions of glucose + EAA. Conclusion: Prolonged glucose infusion decreases myofibrillar protein degradation, prevents the excretion of infused EAA, and acts additively with EAA to increase plasma IGF-1 and improve net nitrogen balance. There was no evidence of synergistic effects between glucose + EAA infusion on muscle protein degradation or expression of components of the ubiquitin-proteasome proteolytic pathway.

Juvenile-mature wood transition in pine: correlation between wood properties and candidate gene expression profiles

There is a strong desire to exploit transcriptomics data from model species for the genetic improvement of non-model crops. Here, we use gene expression profiles from the commercial model Pinus taeda to identify candidate genes implicated in juvenile-mature wood transition in the non-model relative, P. sylvestris. Re-analysis of 'public domain' SAGE data from xylem tissues of P. taeda revealed 283 mature-abundant and 396 juvenile-abundant tags (P < 0.01), of which 70 and 137, respectively matched to genes with known function. Based on sequence similarity, we then isolated 16 putative homologues of genes that in P. taeda exhibited widest divergence in expression between juvenile and mature samples. Candidate expression levels in P. sylvestris were almost invariably differential between juvenile and mature woody tissue samples among two cohorts of five trees collected from the same seed source and selected for genetic uniformity by genetic distance analysis. However, the direction of differential expression was not always consistent with that described in the original P. taeda SAGE data. Correlation was observed between gene expression and juvenile-mature wood anatomical characteristics by OPLS analysis. Four candidates (alpha-tubulin, porin MIP1, lipid transfer protein and aquaporin like protein) apparently had greatest influence on the wood traits measured. Speculative function of these genes in relation to juvenile-mature wood transition is briefly explored. Thus, we demonstrate the feasibility of exploiting SAGE data from a model species to identify consistently differentially expressed candidates in a related non-model species.

Use of global gene expression patterns in mechanistic studies of oestrogen action in MCF7 human breast cancer cells

Over the years, the MCF7 human breast cancer cell line has provided a model system for the study of cellular and molecular mechanisms in oestrogen regulation of cell proliferation and in progression to oestrogen and antioestrogen independent growth. Global gene expression profiling has shown that oestrogen action in MCF7 cells involves the coordinated regulation of hundreds of genes across a wide range of functional groupings and that more genes are down regulated than upregulated. Adaptation to long-term oestrogen deprivation, which results in loss of oestrogen-responsive growth, involves alterations to gene patterns not only at early time points (0-4 weeks) but continuing through to later times (20-55 weeks), and even involves alterations to patterns of oestrogen-regulated gene expression. Only 48% of the genes which were regulated >= 2-fold by oestradiol in oestrogen-responsive cells retained this responsiveness after long-term oestrogen deprivation but other genes developed de novo oestrogen regulation. Long-term exposure to fulvestrant, which resulted in loss of growth inhibition by the antioestrogen, resulted in some very large fold changes in gene expression up to 10,000-fold. Comparison of gene profiles produced by environmental chemicals with oestrogenic properties showed that each ligand gave its own unique expression profile which suggests that environmental oestrogens entering the human breast may give rise to a more complex web of interference in cell function than simply mimicking oestrogen action at inappropriate times. (C) 2009 Elsevier Ltd. All rights reserved.

Comparison of the global gene expression profiles produced by methylparaben, n-butylparaben and 17 beta-oestradiol in MCF7 human breast cancer cells

Since the alkyl esters of p-hydroxybenzoic acid (parabens) can be measured intact in the human breast and possess oestrogenic properties, it has been suggested that they could contribute to an aberrant burden of oestrogen signalling in the human breast and so play a role in the rising incidence of breast cancer. However, although parabens have been shown to regulate a few single genes (reporter genes, pS2, progesterone receptor) in a manner similar to that of 17 beta-oestradiol, the question remains as to the full extent of the similarity in the overall gene profile induced in response to parabens compared with 17 beta-oestradiol. The GE-Amersham CodeLink 20 K human expression microarray system was used to profile the expression of 19881 genes in MCF7 human breast cancer cells following a 7-day exposure to 5 x 10(-4) m methylparaben, 10(-5) m n-butylparaben and 10(-8) m 17 beta-oestradiol. At these concentrations, the parabens gave growth responses in MCF7 cells of similar magnitude to 17 beta-oestradiol. The study identified genes which are upregulated or downregulated to a similar extent by methylparaben, n-butylparaben and 17 beta-oestradiol. However, the majority of genes were not regulated in the same way by all three treatments. Some genes responded differently to parabens from 17 beta-oestradiol, and furthermore, differences in expression of some genes could be detected even between the two individual parabens. Therefore, although parabens possess oestrogenic properties, their mimicry in terms of global gene expression patterns is not perfect and differences in gene expression profiles could result in consequences to the cells that are not identical to those following exposure to 17 beta-oestradiol. Copyright (c) 2006 John Wiley & Sons, Ltd.