HUMAN :: Human aortic endothelial cells (EC) culture

P.         Human aortic endothelial cells (EC) culture

1.         EC isolation and culture (C. Romanoski)
2.         EC treatments with oxidized phospholipids (C. Romanoski)
3.         Expression arrays (C. Romanoski)
4.         Genotyping (C. Romanoski)
5.         Association analyses (C. Romanoski)
6.         Superoxide measurements (S. Lee)
7.         Network analysis (C. Romanoski)

 

1.         EC isolation and culture (C. Romanoski)

HAECs were isolated from aortic explants of 149 unique heart transplant donors in the UCLA transplant program and grown to confluence in 100mm dishes. We confirmed that greater than 95% of the cells were Factor 8 positive and took up dil-acetyl LDL. In more recent studies we have demonstrated in multiple EC preparations that greater than 95% of the cells were PECAM positive.

 


2.         EC treatments with oxidized phospholipids (C. Romanoski)

            At 90% - 100% confluence, cells were treated in 6-well dishes for 4 hours in duplicate with either media (1% serum) or with 40 ug/ml Ox-PAPC. Ox-PAPC was prepared from PAPC purchased from Avanti Polar Lipids (Alabaster, Alabama). 47 HAEC cultures were treated with one preparation of Ox-PAPC, 44 cultures were treated with a second batch of Ox-PAPC, 5 donors were treated concurrently by batches 1 and 2, and the remaining 62 cultures were treated with another batch of Ox-PAPC. This ‘batch effect’ was removed in downstream analysis by normalizing expression values between groups with ComBat (http://jlab.byu.edu/ComBat/Abstract.html). Among these samples were duplicate cultures from 9 donors (6 male and 3 female). Duplicate cultures were used for network construction but omitted from association testing to avoid overrepresentation of genotypes. Duplicates were analyzed to demonstrate that expression profiles are conserved within HAEC donors.

 


3.         Expression arrays (C. Romanoski)

Cytoplasmic RNA was extracted with the RNeasy kit and treated with DNase (Qiagen, Valencia, CA). RNA concentrations were measured with the NanoDrop 2000 (Thermo Fisher Scientific, Waltham, MA) and quality checked with the Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA).
RNA was prepared for hybridization to Affymetrix HT-HU133A microarrays using a standard protocol. 629 arrays were used to quantify gene expression. This corresponded to 158 cultures with expression data for both control and Ox-PAPC conditions. In general, duplicate arrays were averaged to determine control and Ox-PAPC expression values. However, in 12 cases, expression per condition was based on a single array. In addition, 1 culture had triplicate Ox-PAPC arrays and 4 cultures had quadruplicate Ox-PAPC arrays that were averaged to determine Ox-PAPC expression values. Before averaging, intensity values were normalized with the robust multi-array average (RMA) normalization method in R 2.5.0 using the justRMA function of the affy package of Bioconductor (www.bioconductor.org). An alternative CDF file was used to filter probes so that only intensity data from properly aligned probes, according to the NCBI transcriptome build 36, were used in downstream analysis. Sex was determined from heterozygous genotype calls on the X chromosome and revealed that 108 of the donors were male and 41 were female. Transcript expression was used to cluster the microarray samples and confirmed that no outlier arrays were used in downstream analysis. We did not remove probes in probe sets containing SNPs because they did not significantly cause artificial eQTL.

 


4.         Genotyping (C. Romanoski)

Genomic DNA was isolated from HAECs using the DNeasy kit with RNase treatment (Qiagen). For SNP Genotyping, samples were randomly arrayed into three 96-well micro titer plates at 50ng/ul. Per Affymetrix Genome-wide Human SNP Array 6.0 assay protocol, 2 x 250ng of gDNA were digested by restriction enzymes NspI and StyI separately and products were ligated to respective adaptors (Affymetrix Human SNP 6.0 assay). PCR was used to amplify ligation products that were checked for size and quality by QIAxcel (Qiagen, Valencia, CA). Labeled PCR products were hybridized to the Human SNP 6.0 array. Array hybridization, washing, and scanning were performed according to the Affymetrix recommendations. Scanned images were subjected to visual inspection and a chip quality report was generated by the Affymetrix GeneChip Operating System (command console) and the Genotyping console (Affymetrix). The image data was processed using the Affymetrix Genotyping Console using the Birdsuite algorithm to determine the specific hybridizing signal for each SNP call and copy number detection.

 


5.         Association analyses (C. Romanoski)

SNPs used in association analysis were included when (i) they had minor allele frequencies > 5%, (ii) they were in Hardy-Weinberg Equilibrium (p-value > 0.001), and (iii) they had <10% missing data. This resulted in 718,374 SNPs that were used for association testing of distal- variants. The 147 unique donors that had complete expression and genotyping data (2 of the 149 unique donors lacked genotyping data) were used in association analysis. Genotype-gene expression associations (ie. eQTL) were tested using linear regression with the ‘–linear’ option in PLINK v1.4.

Since our HAEC population was derived from aortic explants of anonymous heart transplant donors, information individuals was unknown. We sought to ascertain the population structure of the subset of 96 HAEC donors in this study that were investigated previously. As to interrogate whether gross population stratification caused spurious associations we clustered the autosomal genotypes of the HAEC donors together with members of the 3 HapMap populations. The results showed that our population was predominately Caucasian, and that removal of a few genetically different donors had little effect on global eQTLs. The results from this analysis have been extrapolated to the expanded set of 149 donors in the current study.

 


6.         Superoxide measurements (S. Lee)

In development.

 


7.         Network analysis (C. Romanoski)

Duplicate expression measurements were averaged per condition and per donor. The 2000 most Ox-PAPC regulated genes were identified by comparing the untreated and Ox-PAPC treated values across the population with a paired t-test. The 2000 most Ox-PAPC regulated genes corresponded to those with t-test p-values <1.0e-28. 2000 genes were used so that the network would be inclusive of the most significant genes that were differentially expressed in response to Ox-PAPC, yet small enough to be visualized. Average transcript measurements for the 2000 transcripts in both conditions were used in network construction. The pair-wise adjacency matrix between genes was used to determine ‘topological overlap’ between gene pairs. Topological overlap is a function that takes into account the pair-wise correlation between genes as well as the number of common neighbors of gene pairs. The topological overlap matrix was raised to the power of 12 to emphasize the difference between transcripts with many connections and transcripts with few connections to other transcripts. The topological overlap matrix was used to identify ‘modules’ of highly co-expressed genes and the clustering dendogram of the topological overlap matrix was cut with the ‘dynamic hybrid’ method to define modules. We identified 11 modules, identified by arbitrarily assigned colors. The ‘grey module’ was not considered a true module because it contained the genes with dissimilar expression patterns. All of these analyses were performed in R using the freely accessible Weighted Gene Co-expression Network Analysis (WGCNA) software package: (www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA). Network visualization as displayed in the second reference above (PMID: 20170901) was performed in Cytoscape v2.6.3. See the supplementary methods of this article for further details.


Romanoski CE, Che N, Yin F, Mai N, Pouldar D, Civelek M, Pan C, Lee S, Vakili L, Yang WP, Kayne P, Mungrue IN, Araujo JA, Berliner JA, Lusis AJ. Network for activation of human endothelial cells by oxidized phospholipids: a critical role of heme oxygenase 1. Circ Res. 2011 Aug 19;109(5):e27-41. Epub 2011 Jul 7. PMID: 21737788.

Romanoski CE, Lee S, Kim MJ, Ingram-Drake L, Plaisier CL, Yordanova R, Tilford C, Guan B, He A, Gargalovic PS, Kirchgessner TG, Berliner JA, Lusis AJ. Systems genetics analysis of gene-by-environment interactions in human cells. Am J Hum Genet. 2010 Mar 12;86(3):399-410. Epub 2010 Feb 18. PMID: 20170901.