Candida glabrata: Pathogenicity and Resistance Mechanisms for Adaptation and Survival.
Hassan YahayaShu Yih ChewLeslie Thian-Lung ThanPublished in: Journal of fungi (Basel, Switzerland) (2021)
Candida glabrata is a yeast of increasing medical relevance, particularly in critically ill patients. It is the second most isolated Candida species associated with invasive candidiasis (IC) behind C. albicans. The attributed higher incidence is primarily due to an increase in the acquired immunodeficiency syndrome (AIDS) population, cancer, and diabetic patients. The elderly population and the frequent use of indwelling medical devices are also predisposing factors. This work aimed to review various virulence factors that facilitate the survival of pathogenic C. glabrata in IC. The available published research articles related to the pathogenicity of C. glabrata were retrieved and reviewed from four credible databases, mainly Google Scholar, ScienceDirect, PubMed, and Scopus. The articles highlighted many virulence factors associated with pathogenicity in C. glabrata, including adherence to susceptible host surfaces, evading host defences, replicative ageing, and producing hydrolytic enzymes (e.g., phospholipases, proteases, and haemolysins). The factors facilitate infection initiation. Other virulent factors include iron regulation and genetic mutations. Accordingly, biofilm production, tolerance to high-stress environments, resistance to neutrophil killings, and development of resistance to antifungal drugs, notably to fluconazole and other azole derivatives, were reported. The review provided evident pathogenic mechanisms and antifungal resistance associated with C. glabrata in ensuring its sustenance and survival.
Keyphrases
- candida albicans
- biofilm formation
- pseudomonas aeruginosa
- healthcare
- systematic review
- risk factors
- free survival
- type diabetes
- papillary thyroid
- genome wide
- randomized controlled trial
- copy number
- saccharomyces cerevisiae
- metabolic syndrome
- middle aged
- antimicrobial resistance
- insulin resistance
- big data
- lymph node metastasis