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 plasma insulin and branched-chain amino acids on skeletal muscle protein synthesis in fasted lambs

The increase in fractional rate of protein synthesis (K-s) in the skeletal muscle of growing rats during the transition from fasted to fed state has been explained by the synergistic action of a rise in plasma insulin and branched-chain amino acids (BCAA). Since growing lambs Also exhibit an increase in K-s with level of feed intake, the objective of the present study was to determine if this synergistic relationship between insulin and BCAA also occurs in ruminant animals. Six 30 kg fasted (72 h) lambs (8 months of age) received each of four treatments, which were based on continuous infusion into the jugular vein for 6 h of: (1) saline (155 mmol NaCl/l); (2) a mixture of BCAA (0.778 mumol leucine, 0.640 mumol isoleucine and 0.693 mumol valine/min.kg); (3) 18.7 mumol glucose/min.kg (to induce endogenous insulin secretion): (4) co-infusion of BCAA and glucose. Within each period all animals received the same isotope of phenylalanine, (Phe) as follows: (1) L-[1-C-13]Phe; (2) L-phenyl-[ring H-2(5)]-alanine; (3) L-[N-15]Phe; (4) L-[ring 2,6-H-3]Phe. Blood was sampled serially during infusions to measure plasma concentrations of insulin, glucose and amino acids, and plasma free Phe isotopic activity; biopsies were taken 6 h after the beginning of infusions to determine K-s in in. longissimus dorsi and vastus muscle. Compared with control (saline-infused) lambs, K-s was increased by an average of 40% at the end of glucose infusion, but this effect was not statistically significant in either of the muscles sampled. BCAA infusion, alone or in combination with glucose, also had no significant effect on K-s compared with control sheep. K-s was approximately 60% greater for vastus muscle than for m. longissimus dorsi (P<0.01), regardless of treatment. It is concluded that there are signals other than insulin and BCAA that are responsible for the feed-induced increase in K-s in muscle of growing ruminant animals.

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.

Intracellular signalling pathways regulating the adaptation of skeletal muscle to exercise and nutritional changes

The focus of the present review is to assimilate current knowledge concerning the differing signalling transduction cascades that control muscle mass development and affect skeletal muscle phenotype following exercise or nutritional uptake. Effects of mechanical loading on protein synthesis are discussed. Muscle growth control is regulated by the interplay of growth promoting and growth suppressing factors, which act in concert. Much emphasis has been placed on understanding how increases in the rate of protein synthesis are induced in skeletal muscle during the adaptive process. One key point to emerge is that protein synthesis following resistance exercise or increased nutrient availability is mediated through changes in signal transduction involving the phosphorylation of mTOR and sequential activation of downstream targets. On the other hand, AMPK activation plays an important role in the inhibition of protein synthesis by suppressing the function of multiple translation regulators of the mTOR signalling pathway in response to cellular energy depletion and low metabolic conditions. The effects of exercise and/or nutritional uptake on the activation of signalling molecules that regulate protein synthesis are highlighted, providing a better understanding of the molecular changes in the cell.

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.