Figure 3. The gene regulation response to combinations of two antibiotics is largely explained by just two principal components.

(A) Schematic of experimental procedure for measuring gene expression responses to combinations of two antibiotics. Two-dimensional drug concentration gradients were set up on 96-well plates (left). One promoter-GFP reporter strain was grown on each plate (middle). For each condition in the two drug space, the expression level E_x is obtained as in Figure 2, yielding the matrix of expression levels E_x of promoter X. (B) Examples for different types of gene expression responses in two-dimensional concentration gradients of TMP and SPR. Expression level E_x is shown in color code: Blue indicates down-regulation, red up-regulation, and white no change in gene expression. The promoter cspA shows a conflicting response, sodA a consistent response, minC no response, and pheL responds only to TMP (cf. Figure 2B,C). In these examples, the expression level in the drug combination lies between the levels in the individual drugs which is the case for most promoters. Responses of other promoters are shown in Figures S1 and S2. Drug concentrations are in units of the Minimal Inhibitory Concentration (MIC, see Table 1). (C) Principal Component Analysis (PCA) is performed on the expression level matrices E_x, yielding the principal components (PCs) E_I, E_II,…. The scores $s_x^1,s_x^2,\dots$ capture how strongly each PC contributes to the total response of promoter X (Experimental Procedures). Bar charts: Variance explained by the first five PCs for drug combination of TMP-SPR (left bar chart) and TET-SPR (right bar chart). Most variability is explained by the 1^st PC, but the 2^nd PC is also important. Almost the entire data set is explained by the first three PCs which thus capture the most typical features of the responses of all promoters.