Human blood was drawn from the antecubital veins of healthy blood donors and provided as buffy coats by the Virginia Blood Services (Richmond, VA). The mononuclear fractions were pooled from four unidentified donors to decrease individual variations in monocytes. Mixed peripheral blood mononuclear cells (PBMCs) were isolated by Histopaque 1.077 (Sigma Diagnostics, Inc., St. Louis, MO). Following centrifugation, the mononuclear layer was removed and washed with PBS containing 0.02% ethylenediaminetetraacetate (EDTA). The pellet was resuspended in 1X H-lyse Buffer (R&D Systems Inc., Minneapolis, MN), and washed with wash buffer. From these PBMCs, monocytes were isolated using a negative selection monocyte isolation kit and LS columns (Miltenyi Biotec, Bergisch Gladbach, Germany). The purity of the isolated fraction was > 97% as estimated by flow cytometry using anti-CD14.
Growth protocol
Monocytes were cultured in Macrophage Serum-Free Medium (MSFM, Invitrogen, Carlsbad, CA) in the presence of 1% media supplement nutridoma-HU (Roche Molecular Biochemicals, Indianapolis, IN) and 100 nM M-CSF for 6 days, after which the cells showed the expected morphological signs of macrophage differentiation. Human monocyte-derived macrophages (MDM) were incubated with minimally modified LDL (mmLDL) (100 µg/ml) for 2 days to induce foam cell formation.
Extracted molecule
total RNA
Extraction protocol
Cells were washed with PBS twice. mRNA was isolated using RNEasy Kits (Qiagen, Valencia, CA) according to manufacturer’s instructions.
Label
biotin
Label protocol
Labeling of samples was performed according to standard Affymetrix protocols.
Hybridization protocol
Hybridization of cRNA was performed according to standard Affymetrix protocols.
Scan protocol
Scanning was performed according to standard Affymetrix protocols.
Description
Gene expression in monocyte-derived macophages stimulated with mmLDL for two days.
Data processing
Signal intensity values were obtained from the Affymetrix MicroArray Suite software (MAS 5.0). Of 22,283 probe sets on the HG-U133A chip, 78 internal control probes were removed and 22,215 probe sets representing 12,978 gene products were analyzed. Microarray gene expression intensities were normalized in order to ensure that all 22 array chips have the same inter-quartile ranges (IQR). In addition, they were log-transformed with base 2, which allows transforms the right-skewed distribution closer to a normal distribution. For statistical analysis, an open source statistical software package R (www.rproject.org) was used, which includes the local pooled error (LPE) test for differential expression discovery under two conditions, the heterogeneous error model (HEM) for differential expression discovery under multiple conditions, hierarchical clustering & heatmap analysis, and self-organizing maps (SOM), especially the last two widely used in microarray data analysis. The annotation information available from the Affymetrix website (www.affymetix.com) was used to identify the genes represented on the HG-U133A chip for the various classes of genes analyzed. We eliminated non-expressed (within 2 SD from zero in all conditions) and housekeeping genes (not expressed).
