Abstract
Microbial metabolomics is a challenge strategy that allows a comprehensive analysis of metabolites within a microorganism and may support a new approach in microbial research, including the microbial diagnosis. Thus, the aim of this research was to in-depth explore a metabolomics strategy based on the use of an advanced multidimensional gas chromatography for the comprehensive mapping of cellular metabolites of C. albicans and non-C. albicans (C. glabrata and C. tropicalis) and therefore contributing for the development of a comprehensive platform for fungal detection management and for species distinction in early growth times (6 h). The volatile fraction comprises 126 putatively identified metabolites distributed over several chemical families: acids, alcohols, aldehydes, hydrocarbons, esters, ketones, monoterpenic and sesquiterpenic compounds, norisoprenoids, phenols and sulphur compounds. These metabolites may be related with different metabolic pathways, such as amino acid metabolism and biosynthesis, fatty acids metabolism, aromatic compounds degradation, mono and sesquiterpenoid synthesis and carotenoid cleavage. These results represent an enlargement of ca. 70% of metabolites not previously reported for C. albicans, 91% for C. glabrata and 90% for C. tropicalis. This study represents the most detailed study about Candida species exometabolome, allowing a metabolomic signature of each species, which signifies an improvement towards the construction of a Candida metabolomics platform whose application in clinical diagnostics can be crucial to guide therapeutic interventions.
Highlights
Fungal pathogens can cause life threatening invasive infections, chronic conditions and recurrent superficial infections
The epidemiology of Candida infections is constantly changing due to changes in medical practices, but approximately 95% of all cases of Candida infections result from five species: Candida albicans, Candida glabrata, Candida parapsilosis, Candida tropicalis and Candida krusei [2]
The implemented methodology based on headspace solid-phase microextraction (HS-SPME)/GC×GC–ToFMS was shown to be suitable for the profiling of Candida species exometabolome, which represent the crucial step in the construction of a metabolomics workflow
Summary
Fungal pathogens can cause life threatening invasive infections (fungemia and meningitis), chronic conditions (asthma) and recurrent superficial infections (oral and vaginal candidiasis). Species belonging to the genera Aspergillus, Candida and Cryptococcus are the most prevalent cause of invasive infections, and recent data indicate that Candida infections account for 80% of all systemic fungal infections worldwide [2]. Candida spp. exist as commensals of the skin, mouth and gastrointestinal tract. Their growth and spread are controlled by epithelial barriers and defenses of the innate immune system. While Candida spp. are normal flora of the human body, they possess the ability to transition to pathogens causing life-threatening systemic infections [3,4,5]. The presence of candidemia results in an increase in mortality and costs associated with prolonged hospitalization, making Candida spp. a clinical concern and an economic concern as well [6]
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