Figure 3

Principal component analysis (PCA) and heat map of proteome data. A: Principal component analysis of the proteome data in a 2D graph of PC1 and PC2. The biplot shows proteome data (scores) as labelled dots and treatment effect (loadings) as vectors for the expressing (E) and control (C) strain) at different oxygen concentrations in the inlet gas (21, 11 or 8% O2). Vectors that are close together are highly correlated in terms of the observed proteome for each treatment while vectors that are orthogonal are poorly correlated. PC1 correlates well with the change in oxygen conditions as the projection of the tips of the arrows on PC1 axis indicate. The effect of the 8% conditions appears stronger than the effect of 11% and both effects clearly differ from the 21% reference on each strain as indicated by the projections.B: Heat map presentation of a hierarchical cluster of the 45 proteins that show significantly different (p ≤ 0.05) relative abundances in both strains (expressing (E) and control (C) strain) at different oxygen concentrations in the inlet gas (21, 11 or 8). The green colour represents low and pink colour represents high expression levels.