To identify genes with similar expression profiles mathematical clustering methods were used, with the resulting hierarchy displayed as dendrograms. 16s rRNA was used as an internal control. The use of an internal control was necessary as the number of genes expressed under different hormonal conditions varied substantially and no single gene was constitutively selleckchem expressed. This method of normalization was particularly important in comparing samples grown in charcoal-stripped, hormone-free media to those in hormone-supplemented cultures. Microarray data accession number The entire microarray data recorded in Gene Expression Omnibus (GEO) database with accession number: GSE24119.

Results and discussion Whole transcriptome microarray data confirmed by qRT-PCR analyses We used a whole genome Affymetrix microarray approach to measure the transcriptional responses of C. trachomatis grown in ECC-1 cells supplemented with the female sex hormones, estradiol and progesterone. The resultant data was extracted and filtered through Affymetrix’s Gene Chip Operating System (GOCS) version 1.4, and processed using the MAS5 algorithm. Candidate MLN2238 mw lists of genes were further refined by selecting genes with a greater than 2-fold up/down-regulation and a p-value of <0.05. Replicate data sets were processed individually and

then cross-correlated with each other to find Grape seed extract statistically significant changes in gene expression. A total of 16 chlamydial arrays were analysed, with the four culture conditions

(no hormone, E, P, E+P), enabling us to have four replicates for each test condition. To confirm the accuracy and reliability of our microarray data, we chose 19 genes that were either up or down-regulated by microarray for analysis by quantitative RT-PCR (Table 1). For 17 of these 19 genes there was complete agreement between the microarray results and the qRT-PCR results. In all cases the fold changes measured by qRT-PCR were larger than those recorded using the microarray assay. For the two genes that were not consistent between the two methodologies, the microarray method gave a down-regulation of transcription whereas the qRT-PCR method showed no change in the transcriptional response. Table 1 Comparison of expression folds change obtained by microarray analysis with fold change obtained by qRT-PCR. Gene name Affymetrix fold change qRT-PCR fold change gseA 13.30 up 27.94 up nqr2 9.20 up 17.32 up ytgD 9.05 up 14.07 up ydaO 5.98 up 12.51 up pdhA 5.78 up 17.30 up recA 4.12 up 7.92 up lplA 2 3.89 up 7.41 up trpB 3.80 up 11.87 up incA 3.10 up 18.04 up fli1 2.25 up 6.80 up sdhB 22.53 Down 6.8 Down trxB 31.44 Down 5.19 Down pyrH 21.54 Down No change miaA 33.91 Down 11.74 Down cysS 19.09 Down 7.03 Down nrdA 30.06 Down 5.16 Down pbp3 33.53 Down 9.43 Down ychF 21.29 Down No change yggV 31.84 Down 12.11 Down Approximately 25% of the C.