Individual patient’s transcriptional response occurred at a variable rate.

<p>320 gene list, differentially expressed genes derived from comparing the untreated expression profiles and their corresponding end of treatment (6 months) expression profiles in the South Africa 2011 Active TB Training Set. <b>(A)</b> Heatmap of South Africa 2011 cohort Active TB Training Set, normalised to the median of all transcripts, shows hierarchical clustered transcripts differentiating over time per individual. <b>(B)</b> Each patient’s temporal molecular response diminishes in the Active TB Training Set cohort.</p

Demographic and laboratory characteristics of patients and healthy controls in training and test sets.

<p>Median values [min-max range]; AA = African-American, C = Caucasian, H = Hispanic, O = Other; M = Male, F = Female; WBC = White Blood Count; RBC = Red Blood Cell count; MCV = Mean Corpuscular Volume; MCH = Mean Corpuscular Hemoglobin; MCHC = Mean Corpuscular Hemoglobin Concentration; RDW = Red blood cell Distribution Width; MPV = Mean Platelet Volume; ESR = Erythrocyte Sedimentation Rate; CRP = C-reactive Protein;</p>*<p>only 1 sample.</p><p>Statistics: for categorical variables, Fisher's exact test is used; for continuous variables, Mann-Whitney test is used.</p

Specific module subsets correlate with laboratory results.

<p><b>A.</b> Heatmap representing correlation (Spearman R) between module percent expression in columns and continuous laboratory parameters in rows. Hierarchical clustering (Euclidian distance) was applied in both dimensions. <b>B.</b> Connection network representing correlation between molecular nodes (modules) in blue and clinical nodes (laboratory parameters) in green. Spearman R correlation greater than 0.3 are represented.</p

Change in treatment specific signature is validated in an independent UK cohort.

<p>320 gene list derived from the differentially expressed genes between the untreated and 6 month treated samples in the treated South Africa 2011 cohort. <b>(A)</b> Heatmap of the treated UK 2011 Cohort, normalised to the median of all transcripts, shows diminution of the treatment specific transcriptional signature in the UK cohort in response to successful anti-TB treatment. <b>(B)</b> Temporal molecular response shows significant changes in response at 2 weeks in the UK cohort (linear mixed models, bars represent mean & 95% confidence intervals, *** = p<0.001, ** = p<0.01, * = p<0.05). <b>(C)</b> A diminished response can be seen in each patient by their temporal molecular response.</p

The osteoarticular infection signature displays increased blood coagulation.

<p>We compared the transcriptional signatures from patients with pneumonia and patients with osteoarticular infections. To properly balance osteoarticular and pneumonia groups, patients with pneumonia with a draw index less than 0.75 (nine patients) were selected (active disease). Nine patients with osteoarticular infection were selected with matching MDTH so that global quantitative signature was equivalent between the two groups. Nine healthy controls were selected from the training and nine from the test set (18 healthy controls in total) as reference. <b>A. Top left panel:</b> mean module map for the nine patients with osteoarticular infections compared to the 18 healthy controls. <b>Bottom left panel:</b> mean module map for the 9 patients with staphylococcal pneumonia compared to the 18 healthy controls. <b>Top right panel:</b> substraction map of osteoarticular infections minus pneumonia. Only differences greater than 40% are represented. <b>Bottom right panel</b>: Annotation legend for modules identified. <b>B.</b> Heatmap representing genes differentially expressed (t-test, <0.05, no correction) between osteoarticular infections and pneumonia (hierarchical clustering, Pearson). 190 genes were upregulated 1.5-fold or more in osteoarticular infections versus pneumonia and healthy controls. 185 genes were upregulated 1.5-fold or more in pneumonia versus osteoarticular infections and healthy controls. <b>C.</b> Area chart representing PANTHER comparison for pathway enrichment between the two lists from C.</p

Numbers enrolled and assigned to cohorts.

<p><b>(A)</b> South Africa: A total of 67 active and latent TB patients were enrolled into the untreated South Africa 2011 Cohort. A total of 29 active TB patients were included in the treated South Africa 2011 Cohort. 15 were randomised into the Active TB Training Set and 14 into the Active TB Test Set. <b>(B)</b> UK: A total of 8 active TB patients were enrolled into the treated UK 2011 Cohort.</p

Distribution of bacterial isolate characteristics by infection localization, presentation and cluster.

<p>TQ: Transcriptionally Quiescent.</p

Specific treatment response signature significantly diminishes at 2 weeks onwards.

<p>A specific TB treatment response signature was derived from significantly differentially expressed genes between untreated samples in the South Africa Active TB Training Set and their corresponding 6 month samples, 320 transcripts. <b>(A)</b> Heatmap of South Africa 2011 Active TB Training Set, normalised to the median of all transcripts, shows transcripts differentiating over time in response to treatment. <b>(B)</b> Temporal molecular response further shows significant and early changes in response to TB treatment in the Active TB Training Set (linear mixed models, bars represent mean & 95% confidence intervals, *** = p<0.001, ** = p<0.01, * = p<0.05). <b>(C)</b> Heatmap of South Africa 2011 Active TB Test Set, normalised to the median of all transcripts, shows transcripts differentiating over time in response to treatment. <b>(D)</b> Temporal molecular response also shows in the Active TB Test Set significant and early changes in response to TB treatment. <b>(E)</b> IPA of the 320 transcripts showing the most significant pathways. <b>(F)</b> Venn diagram shows many overlapping genes between the active TB 664-transcript signature and the treatment specific 320-signature.</p

The <i>S. aureus</i> infection whole blood transcriptional signature is characterized by over-expression of myeloid lineage transcripts and under-expression of lymphoid lineage transcripts.

<p><b>A.</b> Statistical group comparison between 22 healthy subjects and 40 patients with acute <i>S. aureus</i> infection (non-parametric test, α = 0.01, Benjamini-Hochberg multiple testing correction, 1.25 fold change) yielded 1,422 differentially expressed transcripts. Transcripts were organized by hierarchical clustering (Spearman) according to similarities in expression profiles. Each row represents a transcript and each column an individual subject. Normalized log ratio levels are indicated by red (over-expressed) or blue (under-expressed), as compared to the median of healthy controls. <b>B.</b> The same 1,422 transcript list and hierarchical clustering were applied to an independent test set of 22 healthy controls and 59 patients with acute <i>S. aureus</i> infection. Sample hierarchical clustering (Spearman) was performed on the 1,422 transcript list in the test set. <b>C.</b> Average modular transcriptional fingerprrint for <i>S. aureus</i> patients as compared to healthy controls in the training set. <b>D.</b> Average modular transcriptional profile for <i>S. aureus</i> patients as compared to healthy controls in the test set. <b>E.</b> Module functional annotations legend. <b>F.</b> Scatter plot comparing module expression between training (x-axis) and test (y-axis) sets. Spearman correlation was applied.</p

Individual analysis identifies heterogeneous components of the blood signature to <i>S. aureus</i>.

<p><b>A.</b> Column scatter plot representing the distribution of individual molecular distance to health (MDTH) in healthy controls and <i>S. aureus</i> patients. The list of all transcripts composing the modules was used as reference to calculate individual MDTH (***: p<0.001, Mann-Whitney). Horizontal bars represent the group median. Patients with MDTH within healthy range (n = 25) were categorized as transcriptionally quiescent (TQ) and represented in grey. <b>B.</b> Unsupervised hierarchical clustering of the 10,972 transcripts expressed in at least one of the 143 samples (2-fold normalized, 100 difference in raw data) from the combined training and test sets. <b>C.</b> The modular signature was derived for individual transcriptionally active patients (n = 74) as compared to the median of the healthy control group for the corresponding patient set (training or test). Four major clusters (C1 through C4) of patients were obtained by K-means clustering and reorganized into a single heatmap, with modules in rows and patients in columns. Molecular distance to health for individual samples is represented as a line chart on top of the heatmap. <b>D.</b> Zoom on modules with specific over-expression patterns across the four clusters. <b>E.</b> MDTH and clinical lab measurements distribution by cluster. Five or six-group non-parametric ANOVA (Kruskal-Wallis) with Dunn's post-hoc test was applied. (*: p<0.05, **: p<0.01, ***: p<0.001). <b>F.</b> Bar charts representing the percent distribution of infection localization, clinical presentation and bacterial strain for the five clusters of patients identified.</p