Specificity of the osmotic stress response in Candida albicans highlighted by quantitative proteomics

Abstract

Stress adaptation is critical for the survival of microbes in dynamic environments, and in particular, for fungal pathogens to survive in and colonise host niches. Proteomic analyses have the potential to significantly enhance our understanding of these adaptive responses by providing insight into post-transcriptional regulatory mechanisms that contribute to the outputs, as well as testing presumptions about the regulation of protein levels based on transcript profiling. Here, we used label-free, quantitative mass spectrometry to re-examine the response of the major fungal pathogen of humans, Candida albicans, to osmotic stress. Of the 1,262 proteins that were identified, 84 were down-regulated in response to 1M NaCl, reflecting the decrease in ribosome biogenesis and translation that often accompanies stress. The 64 up-regulated proteins included central metabolic enzymes required for glycerol synthesis, a key osmolyte for this yeast, as well as proteins with functions during stress. These data reinforce the view that adaptation to salt stress involves a transient reduction in ribosome biogenesis and translation together with the accumulation of the osmolyte, glycerol. The specificity of the response to salt stress is highlighted by the small proportion of quantified C. albicans proteins (5%) whose relative elevated abundances were statistically significant.

Figure 1

Semi quantitative profiling of C. albicans proteomes under normal and salt-stressed conditions. (a) SDS PAGE separation of three biological C. albicans replicates/cultures grown under different (control (−) vs. salt-stressed (+)) conditions. The gels from which these lanes were taken are shown in Supplementary Fig. 1. (b) Deconvoluted base peak intensity chromatograms of tryptic peptide digests of the salt-stressed and control proteomes. The peptide abundances are represented by the dot size, showing regulated Rhr2 as an example. (c) Protein abundances in descending order as a function of (control) protein abundance index.

Figure 2

Quantitative and qualitative comparison of label-free proteome profiles. (a) Quantitative comparison of log-log protein abundance distributions, demonstrating biological reproducibility (control A vs. control B, control B vs. Control C, etc.) and biological variation due to salt stress (control A vs. salt A, control A vs. salt B, etc.). (b) Venn intersection, qualitative comparison between the two treatments groups, control vs. salt-stressed.

Figure 3

Cluster analysis of C. albicans label free LC-MS proteomic data under normal and salt-stressed growth conditions. (a) Univariate, significance (p) vs fold-change analyses highlighting several significant de-regulated proteins of interest. (b) Unsupervised multivariate PCA and (c) hierarchical clustering analyses.

Figure 4

Expression changes in functional protein groupings under salt-stress conditions. (a) The proteome data were subclassified based on UniProt controlled vocabulary “keywords” and mean label-free abundances for each protein were compared between salt-stressed and control cells. The first (top left) panel emphasises the changes in those proteins assessed as significantly altered, summarised in Table 1. For the subsequent eight panels, the stability of the overall proteomes is emphasised for some major functional clusters. (b) The label-free abundances of each protein in the same eight clusters are plotted on a common set of axes, to illustrate the overall proteome stability across a broad dynamic range.

Figure 5

Clusters and enriched GO terms for proteins that were up- or down-regulated in response to salt stress. (a) Protein abundances were subjected to soft clustering analysis using a fuzzy c-means approach and only two clear clusters were evident; a cluster of 105 proteins down-regulated under conditions of salt stress (left panel), and a separate cluster of 110 proteins whose abundance increased under salt stress (right panel). Proteins with a membership value >0.5 in both clusters were subsequently used in GO enrichment tests (b). The most enriched GOBP (upper plot) and GOMF (lower plot) terms, based on a hypergeometric distribution, are shown.

Figure 6

Impact of osmotic stress on central carbon metabolism. (a) Pathway annotation illustrating those enzymes that were detected, and their fold changes in response to the osmotic stress (see scale, top left). Any enzyme not detected in these experiments is coloured grey. The changes in selected representative proteins are illustrated in panel (b). For some proteins, it was possible to compare the proteome data with transcriptomic data generated by Enjalbert et al. in terms of relative expression of specific proteins compared to the cognate transcripts (c).