Gene expression profiling of individual hypothalamic nuclei from single animals using laser capture microdissection and microarrays

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Abstract

In order to identify novel genes involved in appetite and body weight regulation we have developed a microarray based method suitable for detecting small changes in gene expression in discrete groups of hypothalamic neurons. The method is based on a combination of stereological sampling, laser capture microdissection (LCM), PCR based amplification (SuperAmp™), and one-color cDNA microarray analysis.

To validate the method we assessed and compared fasting induced changes in mRNA levels of Neuropeptide Y (NPY) and proopiomelanocortin (POMC) in the hypothalamic arcuate nucleus (ARC) of diet-induced obese rats using cDNA microarrays, quantitative PCR and in situ hybridization. All methods revealed statistically significant fasting-induced changes in NPY and POMC expression. An additional 3480 differentially expressed probes (fold change >1.22, t-test p = 0.05) were identified in the microarray analysis.

Our findings demonstrate a consistent gene expression pattern across three different gene expression detection methods and strongly suggest that LCM coupled microarray analysis combined with SuperAmp™ can be used as a semi-quantitative mRNA profiling tool. Importantly, the sensitivity of the method greatly improves the usefulness of the microarray technology for gene expression profiling in non-homogeneous tissues such as the brain.

Introduction

Although the microarray technology has surpassed its 10 years anniversary, the full potential of the technology as a target discovery engine remains to be unravelled. The use of cDNA microarrays has expanded greatly as the quality of data has increased, and particularly commercial one-dye platforms generate very consistent results (Kuo et al., 2006). Laser capture microdissection has been introduced as an efficient and precise method to sample subgroups of cells in heterogeneous tissues such as the brain. Even though it seems natural to combine array technologies with the LCM techniques, the minute amounts of tissue – and hence useful RNA – obtained during LCM has hampered such an approach (at least on individual test samples). Recently, however, a PCR based amplification method (SuperAmp™) was demonstrated to generate sufficient quantities of cRNA/cDNA for microarray analysis from as little as 100–1000 cells (Appay et al., 2007). With these technological advances in mind the present study was initiated to develop a method for microarray profiling of discrete hypothalamic nuclei from individual rats. Especially, the ability to perform array analysis without prior pooling of tissue would avoid data interpretation limitations from pooled tissue samples, i.e. allow the possibility to exclude biological outliers and hence enable correlations between phenotype and gene expression. In addition, we wanted to develop a method sensitive enough for detecting relatively small gene expression changes.

Section snippets

Animals

Sixteen male diet-induced obese rats (app. 22 weeks old; Rheoscience in-house breeding colony) were maintained under a 12/12 LD cycle (lights on at 06:00) with stable temperature (22 ± 1 °C) and humidity (50 ± 5%) conditions. Animals were housed individually. During acclimatization the rats had ad libitum access to an energy-dense high-fat diet (HE; 4.41 kcal/g—energy %: carbohydrate 51.4 kcal%, fat 31.8 kcal%, protein 16.8 kcal%; diet #12266B; Research Diets, New Jersey, USA) and water. The rats were

Microarray analysis

Our optimized microarray method is depicted in Fig. 1. Following microarray normalization and filtering a total of 9389 probe-sets remained. Of these, 3480 probe-sets were demonstrated to be differently expressed between the two groups (Welch t-test, p = 0.05) with a total number of 467 probes being expected as false positives (based on a false discovery rate (FDR) of 5%). Finally, Benjamini & Hochberg multiple testing corrections reduced the number of regulated probes sets to 398 (FDR 5% of 398 = 

Discussion

In the present study we have step by step improved existing methods for the determination of the gene expression of discrete cell groups hereby providing a method for the analysis of complex processes associated with the small changes in the expression of a variety of genes, not only in the hypothalamic control of energy homeostasis (Li et al., 2002), but for brain gene expression studies in general.

A microarray experiment relies heavily on the quality of the starting material why the

Acknowledgements

We are greatly thankful to Andreas Bosio, Philip Just Larsen and Karin Bjerre for critical discussions.

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