Levels of MIP-1a and MIP-1b were less than the

Levels of MIP-1a and MIP-1b were less than the level of GAPDH mRNA (dCT,0) in most CVS samples (Figure 1). Although the mRNA of most inflammatory molecules tested was elevated, there was a range of 5 – .10 dCT between the samples for all target mRNA (Figure 1). This indicates a wide variation in the TA 01 biological activity expression levels of inflammatory mediators among the animals because a difference of 3 dCT between samples corresponds to a 10 fold difference in mRNA concentration. In the CVS samples collected 8 months later in November 2011 (Time point 2), the mRNA levels of the 9 inflammatory mediators assessed were similar to those found in the Time point 1 CVS samples (Figures 1 and 2). The mRNA levels of proinflammatory mediators (TNF, IL-6, MIP-1a or MIP1b IFNa and MIG) assessed at both time points in 25 animals were compared (Figure 2). Only 2? of the 25 animals had a 10-fold difference in the expression levels of TNF, IL-6, MIP-1a or MIP1b IFNa, MIG (Figure 2). Thus, based on mRNA levels of proinflammatory cytokines in CVS, the degree of cervicovaginal inflammation in captive rhesus macaques spans a broad range from minimal to severe but the level of inflammation in an individual animal is stable at least over an 8-month period. Correlation network analysis of mRNA levels of the different host genes at Time point 1 (March 2011) showed strong (.0.7 coefficient) positive independent correlations between TNF mRNA levels and MIP1a and MIP1b mRNA levels (Figure 3a).sequencesa Freq.b Genus 93 76 62 69 41 83 83 79 52 34 59 7 28 38Porphyromonas 17 Prevotella Sneathia 14Porphyromonas 26 Proteiniphilum 8 Sneathia Mobiluncus Prevotella Atopobium Anaerovorax 8 7 5 4Proteiniphilum 6 CatonellaCampylobacter 4 Peptoniphilus Mobiluncus Anaerovorax Ignavigranum Dialister Lactobacillus Exilispira Allisonella 4 3 3 2 2 2 2Anaerosphaera 3 Catonella Soehngenia Parvimonas Peptoniphilus Gardnerella Lactobacillus Butyricicoccus 3 3 3 2 2 2AnaerosphaeraaAverage of sequences. Percent of macaques with .1 of sequences corresponding to this genus. doi:10.1371/journal.pone.0052992.tbStatistical AnalysisThe microbiome features, cytokines and chemokines were correlated using a Spearman’s correlation function and then filtered for correlations .0.70 and p,0.05. These correlates were 24195657 calculated using a custom R module and the correlations and corresponding attributes were imported into Cytoscape [27] for visualization of the network models. The Intersection of theFigure 5. Genera of macaque lower genital tract bacteria. The genital microbiota in 21 macaques was identified at two times (approximately 8 months apart). Each group of two bars represents the relative proportions of 16S sequences indentifying bacterial genera in one macaque at 24195657 calculated using a custom R module and the correlations and corresponding attributes were imported into Cytoscape [27] for visualization of the network models. The Intersection of theFigure 5. Genera of macaque lower genital tract bacteria. The genital microbiota in 21 macaques was identified at two times (approximately 8 months apart). Each group of two bars represents the relative proportions of 16S sequences indentifying bacterial genera in one macaque at 15826876 the two different time points. Only the 15 most predominant genera are displayed for clarity. doi:10.1371/journal.pone.0052992.gCervicovaginal Inflammation in Rhesus MacaquesFigure 6. Network of statistical correlations between microbiota. A. Strong (.0.7) correlations between Microbiota at time point 1. B. Intersection of strong correlations that existed at both time 1 and time 2. Pink circles bacterial DNA levels. The blue lines indicate a positive correlation between the parameters in the circles and the width of the line is proportional to the strength of the correlation. doi:10.1371/journal.pone.0052992.gIn addition, there was a strong positive correlation between the mRNA levels of MIP1a and MIP1b (Figure 3a). At Time point 2 (November 2011.