De novo induction of platelet-specific CD4+CD25+ regulatory T cells from CD4+CD25– cells in patients with idiopathic thrombocytopenic purpura
Blood Zhang et al.
113: 2568
Supplemental materials for: Zhang et al
Generation of Dendritic cells
Briefly, CD14+ monocytes were separated from PBMCs of ITP patients using immunomagnetic CD14 microbeads (Miltenyi Biotech) and cultured for 5 days in complete RPMI 1640 medium supplemented with 15% fetal bovine serum, 1000U/mL rhGM-CSF and 1000U/mL rhIL-4 (R&D Systems, Minneapolis, MN). For mature DCs (mDCs), fresh medium containing rhGM-CSF and rhIL-4 plus 1000U/mL rhTNF-α (R&D Systems) was added to the cultures on day 5 and cultured for 2 additional days. For fluorescence-activated cell sorting (FACS) analysis monocytes or DCs were incubated for 20-minute at 4°C with FITC- or PE-labeled mAbs against HLA-DR, CD83 and CD86 (BD PharMingen, San Diego, CA) and analyzed on a FACScalibur (Becton Dickinson, Mountain View, CA).
Microarray analysis
RNA isolation. GP-iTreg-treated imDCs were negatively selected by depleting iTreg with CD4 magnetic beads (Miltenyi Biotech) before RNA isolation after co-culture with GPIIb/IIIa-iTreg. Total RNA was extracted from GP-iTreg-treated or untreated imDCs generated from the same patient according to the manufacturer’s instructions. RNA was further purified with an RNA clean-up kit (Macherey-Nagel, Germany) and quantified by using of spectrophotometer. RNA quality from each sample was assessed by visualization of the 28S/18S ribosomal RNA ratio on 1.2% formamide agarose gel.
Labeling and hybridizations. We employed two-channel microarray technology including 22K 70-mer oligonucleotide microarrays to interrogate the expression profiling of GP-iTreg-treated or untreated imDCs according to a previous published protocol of CapitalBio Corporation (Beijing, China).1 The experiments were reproduced for 5 independent patients.
Microarray data analysis. Raw data was extracted from the TIFF images using LuxScan 3.0 software (CapitalBio). A spot-exclusion method was adopted to filter faint spots in which genes whose signal intensities were in the lowest 50% were excluded from further analysis.1 Then an intensity-dependent LOWESS program in the R language package was used to normalize the two channel ratio values. As a measure of technical replication, each experiment also had a corresponding dye swap.
We used Gene Cluster 3.0 and Eisen’s Treeview software (Stanford University, Palo Alto, CA) to compare similarities among individual samples. Cy3/Cy5 ratios were log-transformed (base 2), median centered by arrays and genes, and hierarchically clustered (average linkage correlation metric). To determine gene products with a significant increase of expression, we interrogated our data sets for an increase in average intensity of at least 2 fold after 24-hour of co-culture. Statistical comparisons were done by using the one class method in significance analysis of microarray (SAM) software 3.0 (Stanford University). In order to identify the functional classes of selected genes and the biochemical pathways involved in induction of tolerance, the selected genes were submitted to BIOCARTA database freely available at http://www.biorag.org.
Quantitative RT-PCR
Total RNA obtained from DCs as described in “Microarray analysis” was used to generate cDNA with oligo (dT) primers using SuperScript II RNase H-Reverse Transcriptase Kit (Invitrogen). Quantitative RT-PCR was performed in a Light Cycler (Roche Diagnostics, Mannheim, Germany) using a SYBR Green I PCR kit (Roche) in triplicates. The average threshold cycles (Ct) of the duplicates were used to calculate the fold changes between GP-iTreg-modulated or unmodulated imDCs. The amplification reactions were performed with 10 µM of each primer. The resulting data were analyzed with the comparative Ct method for relative gene expression quantification. Specificity of the expected products was demonstrated by melting curves analysis. Glyceraldehyde-3-phosphate dehydrogenase was used as an internal control to normalize for the abundance of mRNA in each sample.
REFERENCE
1. Patterson TA, Lobenhofer EK, Fulmer-Smentek SB, et al. Performance comparison of one-color and two-color platforms within the MicroArray Quality Control (MAQC) project. Nat Biotechnol. 2006; 24:1140-1150.
