cell type: primary human monocyte-derived macrophages differentiation factor: MCSF
Treatment protocol
Please see growth protocol.
Growth protocol
With approval from the institutional review board, peripheral blood mononuclear cells were isolated from human peripheral blood using Histopaque (Sigma, St.Louis, MO) followed by negative isolation with magnetic beads (Stem cell, Vancouver, Canada). Monocyte purity was 96.2 ± 0.2 % as assessed by CD14 expression. After red blood cell lysis and several wash steps with 1 mM EDTA, monocytes were essentially free from platelet contamination as demonstrated by virtual absence of CD41 positivity in flow cytometry (data not shown). Monocytes were cultured in macrophage serum-free medium (Gibco, Carlsbard, CA) supplemented with Nutridoma SP (Roche, Indianapolis, IN) and penicillin/streptomycin (Sigma, St. Louis, MO) for six days in the presence of 100 ng/ml rhMCSF (Peprotech, Rocky Hill, NJ) or 1 µM rhCXCL4 (Peprotech). The concentration of 1 µM rhCXCL4 was chosen because this concentration was previously demonstrated to be sufficient to induce macrophage differentiation from monocytes (13). Furthermore, our own preliminary experiments confirmed that after six days, this concentration induced expression of typical macrophage markers like CD11b or CD68 to a similar extent as MCSF (Fig. 1 and data not shown).
Extracted molecule
total RNA
Extraction protocol
For each condition RNA was isolated from macrophages derived from two donors using columns including a DNAse-step followed by reverse transcription (all reagents from Qiagen, Valencia, CA).
Label
biotin
Label protocol
Standard Affymetrix protocol.
Hybridization protocol
Standard Affymetrix protocol.
Scan protocol
Signal intensity values were obtained from the Affymetrix MicroArray Suite software (MAS 5.0).
Description
MCSF_A
Data processing
Microarray gene expression intensities were normalized to ensure that all chips have the same interquartile ranges (IQR). In addition, they were log-transformed with base 2, which transforms the right-skewed distribution closer to a normal distribution. For statistical analysis, an open source statistical software package R (www.r-project.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 and heat-map analysis, and self-organizing maps (SOM), especially the last two widely used in microarray data analysis. The annotation information available from the Affymetrix web site (www.affymetrix.com) was used to identify the genes represented on the HG-U133A chip for the various classes of genes analyze. We eliminated nonexpressed (within 2 SD from zero in all conditions) and housekeeping genes [not significantly regulated with false discovery rate (FDR) <0.05]. We analyzed the regulated genes in two approaches; candidate gene analysis using LPE, HEM, and heat-map analysis, and unbiased analysis of all regulated genes without prior knowledge such using hierarchical clustering analysis.
