Impact of obesity and leptin treatment on adipocyte gene expression in Psammomys obesus

We examined the effects of leptin treatment on the expression of key genes in adipocyte metabolism in Psammomys obesus (P. obesus), a polygenic rodent model of obesity. Lean and obese P. obesus were given three daily intraperitoneal injections of either saline or leptin (total of 45 mg/kg per day) for 7 days. In lean animals, leptin treatment led to reductions in food intake, body weight and fat mass. Pair-fed animals matched for the reduction in food intake of the lean leptin-treated animals demonstrated similar reductions in body weight and fat mass. In obese P. obesus, leptin treatment failed to have any effect on body weight or body fat mass, indicating leptin resistance. Lipoprotein lipase, hormone-sensitive lipase and peroxisome proliferator activated receptor gamma 2 mRNA levels were significantly reduced in lean leptin-treated animals, whereas pair-fed animals were similar to lean controls. Uncoupling protein 2 and glycerol phosphate acyltransferase were also reduced in the lean leptin-treated animals, but not significantly so. Obese animals did not show any gene expression changes after leptin treatment. In conclusion, high circulating concentrations of leptin in lean P. obesus resulted in decreased gene expression of a number of key lipid enzymes, independent of changes in food intake, body weight and fat mass. These effects of leptin were not found in obese P. obesus.

Hub-based reliable gene expression algorithm to classify ER+ and ER- breast cancer subtypes

Identifying gene signatures that are associatedwith the estrogen receptor based breast cancer samples is achallenging problem that has significant implications in breastcancer diagnosis and treatment. Various existing approaches foridentifying gene signatures have been developed but are not ableto achieve the satisfactory results because of their severallimitations. Subnetwork-based approaches have shown to be arobust classification method that uses interaction datasets suchas protein-protein interaction datasets. It has been reported thatthese interaction datasets contain many irrelevant interactionsthat have no biological meaning associated with them, and thusit is essential to filter out those interactions which can improvethe classification results. In this paper, we therefore, proposed ahub-based reliable gene expression algorithm (HRGE) thateffectively extracts the significant biologically-relevantinteractions and uses hub-gene topology to generate thesubnetwork based gene signatures for ER+ and ER- breastcancer subtypes. The proposed approach shows the superiorclassification accuracy amongst the other existing classifiers, inthe validation dataset.

Paracrine control of milk protein gene expression in tammar wallaby

Stephen utilised the unique lactation strategy of the tammar wallaby to identify factors within the mammary gland that determine the composition of milk and how the milk composition changes throughout lactation in order to provide immunity both to the nursing mammary gland and the suckling.

Integrated RNA extraction and RT-PCR for semi-quantitative gene expression studies on a microfluidic device

This paper describes the development of a microfluidic methodology, using RNA extraction and reverse transcription PCR, for investigating expression levels of cytochrome P450 genes. Cytochrome P450 enzymes are involved in the metabolism of xenobiotics, including many commonly prescribed drugs, therefore information on their expression is useful in both pharmaceutical and clinical settings. RNA extraction, from rat liver tissue or primary rat hepatocytes, was performed using a silica-based solid-phase extraction technique. Following elution of the purified RNA, amplification of target sequences for the housekeeping gene, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and the cytochrome P450 gene CYP1A2, was carried out using a one-step reverse transcription PCR. Once the microfluidic methodology had been optimized, analysis of control and 3-methylcholanthrene-induced primary rat hepatocytes were used to evaluate the system. As expected, GAPDH was consistently expressed, whereas CYP1A2 levels were found to be raised in the drug-treated samples. The proposed system offers an initial platform for development of both rapid throughput analyzers for pharmaceutical drug screening and point-of-care diagnostic tests to aid provision of drug regimens, which can be tailor-made to the individual patient.