Introduction

Cellular lipidomics is the analysis of metabolism, transport, and localization of lipids within cells (1). The quantitation of lipids and biochemical analysis of lipid metabolism are integral parts of this concept. The rapid advancement of lipid species profiling has been driven by a substantial progress in chromatography and mass spectrometry (2). Expression profiling of lipid-related genes and definition of regulatory networks still remain to be integrated for a holistic view of lipidomics. Microarrays and the development of high-throughput real-time qPCR systems have enabled researchers to perform a comprehensive transcriptomic analysis of all lipid-related genes. Microarrays cover the complete genomes from various species. However, in any given cell type, only a fraction of all lipid-related genes is expressed and regulated at the mRNA level. Moreover, microarrays have a lower dynamic range and are less precise and sensitive than qRT-PCR.

Our aim was to use the Applied Biosystems TaqMan technology (3) for the quantitative analysis of informative lipid-regulated genes in microglia and macrophages. Of particular interest was to study the dynamic gene expression under conditions mimicking sterol overload, inflammation, and ω3-fatty acid stimulation.

Gene Content of the Lipidomic TaqMan Array

We have initially identified lipid-related genes in genome-wide profiling experiments with DNA-microarrays which displayed expression in microglia and macrophages, showed differentially expressed transcripts in lipid-stimulation and cytokine-activation experiments, and were under the control of the key transcription factors of lipid metabolism. We selected 41 genes that fulfilled these criteria and grouped them into four major ontologies: sterol metabolism, fatty acid metabolism, lipid droplet, and transcription factors (Table 1). In addition to these 41 lipidomic genes, we added four reference genes for normalization, and three inflammation markers for validation of pro-inflammatory stimulation experiments.

Table 1.

Phagocytes As Targets for Expression Profiling

Phagocytes connect immune response with lipid metabolism. To evaluate our gene compilation, we monitored the mRNA expression in microglia, the cell line BV-2, and bone marrow-derived macrophages. The cells were stimulated for 24 hours with 10 µM of the LXR and RXR agonists T0901317 and 9-cis retinoic acid (RA) to mimic sterol loading, 20 ng/mL lipopolysaccharide (LPS) and 50 ng/mL interferon-gamma (Ifn-γ) for pro-inflammatory stress, and 20 ng/mL LPS plus 100 µM docosahexaenoic acid (DHA) as an anti-inflammatory lipid agonist. This approach enabled the crosswise comparison of cell types and a dynamic view on gene expression modulated by bioactive compounds.

TaqMan Array Workflow

Configuration of the Lipidomic TaqMan Array

The lipidomic TaqMan Array Cards are based on the 384-well microfluidic card format 48, designed for use with the Applied Biosystems 7900HT Fast Real-time PCR System (http://taqmanarray.appliedbiosystems.com). The standard workflow is carried out with two technical duplicates of four different samples on eight ports of the same card. Biological replicates should be performed in order to allow statistic analysis of the data. The 2-µL reactions decrease sample consumption and the preloaded primers and probes reduce pipetting steps. TaqMan Array Plates are 96-well microtiter plates that have TaqMan Assays dried down in every well postion. Although the reaction volume is larger (20 µL/well), TaqMan Array Plates can be used on more real-time PCR instruments and may be more accessible to researchers. The same 48 assays were configured onto TaqMan Array Plates and the same samples run for comparison.

Running TaqMan Array Cards and Plates

Total RNA was isolated and checked with the Nanodrop 100 System and the Agilent 2100 bioanalyzer. First-strand cDNA sythesis was carried out with MMLV reverse transcriptase. 100 ng of cDNA (RNA-equivalent) were loaded together with 2× TaqMan Gene Expression Master Mix for a total of 100 µL per port. The TaqMan Array Cards were spun and sealed before loading into a 7900HT Fast Real-time PCR System (Figure 1). The provided SDS setup files were loaded into the Applied Biosystems SDS Software v2.3 and new plate documents were generated automatically. Relative quantification runs were performed with the default thermal cycling conditions. The same samples were analyzed on TaqMan Array Plates using universal cycling conditions on a 7900HT Fast Real-time PCR System.

Figure 1. Schematic overview of the gene expression study in microglia and macrophages using the Lipidomic TaqMan Array Cards. (Click to enlarge)

TaqMan Array Cards Results

Real-time Data Analysis using SDS RQ Manager

Relative gene expression values were obtained from the six TaqMan Array Cards using the comparative Ct method for relative quantification, which is implemented in the Applied Biosystems Relative Quantification (RQ) Manager Software v1.2. In this analysis, quantity is expressed relative to a calibrator cDNA sample, which is set to 1 and all other quantities are expressed as an n-fold difference relative to this cDNA sample. In our experiments, we selected cDNA from unstimulated cells as calibrators for the individual stimulations. The most stable reference gene, Gapdh, was selected as an endogenous control. After calculating the relative expression, mean RQ values were visualized as a 3-D bar graph (Figure 2). The results obtained with the Lipidomic TaqMan Array Cards were reproduced and confirmed using TaqMan Array Plates.

Figure 2. Differential expression analysis of 41 lipid-related genes and inflammatory markers covered by the Lipidomic TaqMan Array Cards. (Click to enlarge)

These results showed that stimulation of all three myeloid cell types with T0901317 + 9-cis RA had an inductive effect on several genes of lipid metabolism (Figure 2A), the pro-inflammatory stimuli LPS and Ifn-γ strongly repressed most lipid-related genes, with the exception of Cox2 (Figure 2B), and co-incubation with DHA attenuated the repressing effect of LPS (Figure 2C). These data also implicate that bone-marrow–derived macrophages display a highly dynamic lipid-related transcriptome, whereas gene expression in primary brain microglia and the BV-2 cell line is regulated at a lower level.

Real-time StatMiner™ Analysis

In the next step, TaqMan Array Cards were analyzed using the Integromics RealTime StatMiner™ package. RealTime StatMiner™ integrates the open source software BioConductor R into an advanced bioinformatics tool optimized for real-time PCR including TaqMan Array Cards data (Figure 1). The application allows the simultaneous processing of several TaqMan Array Cards, quality control, data normalization with endogenous control algorithms, clustering, and relative quantification with different statistical analyses (see also www.integromics. com/StatMiner.php).

As an example, we present here the final results of RealTime StatMiner™ relative quantification of LPS + Ifn-γ stimulated versus unstimulated macrophages (Figure 3). Gapdh was selected as the most stable endogenous control using the implemented NormFinder algorithm. Benjamini-Hochberg adjustment of the False Discovery Rate was applied at a p-value of 0.05. Twenty-one lipid-related genes were significantly regulated (Figure 3, bottom) and most of the remaining genes (Figure 3, top) showed a strong tendency of down-regulation, validating the analyses with SDS RQ Manager.

Figure 3. Log10RQ bar chart of non-signifcant (top) and significant expression changes (bottom). (Click to enlarge)

Conclusion

The Lipidomic TaqMan Array Cards and TaqMan Array Plates are optimized tools for high-throughput quantitative transcript analysis of the most dynamic lipid-related genes in phagocytes and many other cells. Its combination with the RealTime StatMiner further enables researchers to generate statistically evaluated high-quality data. This technology will be very useful for transcriptomics as part of the rapidly progressing field of lipidomics.