MAIN TEXT: In this review, we discuss alternative carbon metabolism as a metabolic adaptation strategy for the pathogenesis of C. glabrata. As the glyoxylate cycle is an important pathway in the utilization of alternative carbon sources, we also highlight the key metabolic enzymes in the glyoxylate cycle and its necessity for the pathogenesis of C. glabrata. Finally, we explore the transcriptional regulatory network of the glyoxylate cycle.
CONCLUSION: Considering evidence from Candida albicans and Saccharomyces cerevisiae, this review summarizes the current knowledge of the glyoxylate cycle as an alternative carbon metabolic pathway of C. glabrata.
METHODS: In this study, the metabolic responses of C. glabrata under acetate growth condition was explored using high-throughput transcriptomic and proteomic approaches.
RESULTS: Collectively, a total of 1482 transcripts (26.96%) and 242 proteins (24.69%) were significantly up- or down-regulated. Both transcriptome and proteome data revealed that the regulation of alternative carbon metabolism in C. glabrata resembled other fungal pathogens such as Candida albicans and Cryptococcus neoformans, with up-regulation of many proteins and transcripts from the glyoxylate cycle and gluconeogenesis, namely isocitrate lyase (ICL1), malate synthase (MLS1), phosphoenolpyruvate carboxykinase (PCK1) and fructose 1,6-biphosphatase (FBP1). In the absence of glucose, C. glabrata shifted its metabolism from glucose catabolism to anabolism of glucose intermediates from the available carbon source. This observation essentially suggests that the glyoxylate cycle and gluconeogenesis are potentially critical for the survival of phagocytosed C. glabrata within the glucose-deficient macrophages.
CONCLUSION: Here, we presented the first global metabolic responses of C. glabrata to alternative carbon source using transcriptomic and proteomic approaches. These findings implicated that reprogramming of the alternative carbon metabolism during glucose deprivation could enhance the survival and persistence of C. glabrata within the host.
OBJECTIVES: This study aimed to identify the glucose sensing pathway related genes of C. glabrata and to analyze the regulation pattern of these genes in response to different surrounding glucose concentrations through the quantitative real time polymerase chain reaction (qRT-PCR).
MATERIALS AND METHODS: Phylogenetic analysis was carried out on predicted amino acid sequences of C. glabrata and S. cerevisiae to compare their degree of similarity. In addition, the growth of C. glabrata in response to different amounts of glucose (0%, 0.01%, 0.1%, 1% and 2%) was evaluated via the spot dilution assay on prepared agar medium. Besides, the SNF3 and RGT2, which act as putative glucose sensors, and the RGT1 and MIG1, which act as putative transcriptional regulators and selected downstream hexose transporters (HXTs), were analysed through qRT-PCR analysis for the gene expression level under different glucose concentrations.
RESULTS: Comparative analysis of predicted amino acids in the phylogenetic tree showed high similarity between C. glabrata and S cerevisiae. Besides, C. glabrata demonstrated the capability to grow in glucose levels as low as 0.01% in the spot dilution assay. In qRT-PCR analysis, differential expressions were observed in selected genes when C. glabrata was subjected to different glucose concentrations.
CONCLUSIONS: The constructed phylogenetic tree suggests the close evolutionary relationship between C. glabrata and S. cerevisiae. The capability of C. glabrata to grow in extremely low glucose environments and the differential expression of selected glucose-sensing related genes suggested the possible role of these genes in modulating the growth of C. glabrata in response to different glucose concentrations. This study helps deepen our understanding of the glucose sensing mechanism in C. glabrata and serves to provide fundamental data that may assist in unveiling this mechanism as a potential drug target.