mSphere of Influence: Decoding Transcriptional Regulatory Networks To Illuminate the Mechanisms of Microbial Pathogenicity

When HSFs bring the heat-mapping the transcriptional circuitries of HSF-type regulators in Candida albicans

Heat shock factor (HSF)-type regulators are stress-responsive transcription factors widely distributed among eukaryotes, including fungi. They carry a four-stranded winged helix-turn-helix DNA-binding domain considered as the signature domain for HSFs. The genome of the opportunistic yeast Candida albicans encodes four HSF members, namely, Sfl1, Sfl2, Skn7, and the essential regulator, Hsf1. C. albicans HSFs do not only respond to heat shock and/or temperature variation but also to CO2 levels, oxidative stress, and quorum sensing, acting this way as central decision makers. In this minireview, I follow on the heels of my mSphere of Influence commentary (2020) to provide an overview of the repertoire of HSF regulators in Saccharomyces cerevisiae and C. albicans and describe how their genetic perturbation in C. albicans, coupled with genome-wide expression and location analyses, allow to map their transcriptional circuitry. I highlight how they can regulate, in common, a crucial developmental program: filamentous growth.

Robust, Comprehensive Molecular, and Phenotypical Characterisation of Atypical Candida albicans Clinical Isolates From Bogotá, Colombia

Candida albicans is commensal in human microbiota and is known to be the commonest opportunistic pathogen, having variable clinical outcomes that can lead to up to 60% mortality. Such wide clinical behaviour can be attributed to its phenotypical plasticity and high genetic diversity. This study characterised 10 Colombian clinical isolates which had already been identified as C. albicans by molecular tests; however, previous bioinformatics analysis of protein mass spectra and phenotypical characteristics has shown that this group of isolates has atypical behaviour, sharing characteristics of both C. africana and C. albicans. This study was aimed at evaluating atypical isolates' pathogenic capability in the Galleria mellonella model; susceptibility profiles were determined and MLST was used for molecular characterisation. Cluster analysis, enabling unbiased bootstrap to classify the isolates and establish their cluster membership and e-BURST, was used for establishing clonal complexes (CC). Both approaches involved using representative MLST data from the 18 traditional C. albicans clades, as well as C. albicans-associated and minor species. Ten atypical isolates were distributed as follows: 6/10 (B71, B41, B60, R6, R41, and R282) were grouped into a statistically well-supported atypical cluster (AC) and constituted a differentiated CC 6; 2/10 of the isolates were clearly grouped in clade 1 and were concurrent in CC 4 (B80, B44). Another 2/10 atypical isolates were grouped in clade 10 and concurred in CC 7 (R425, R111); most atypical isolates were related to geographically distant isolates and some represented new ST. Isolates B41 and R41 in the AC had greater virulence. Isolate B44 was fluconazole-resistant and was grouped in clade 1. The atypical nature of the isolates studied here was demonstrated by the contrast between phenotypical traits (C. africana-like), molecular markers (C. albicans-like), virulence, and antifungal resistance, highlighting the widely described genetic plasticity for this genus. Our results showed that the atypical isolates forming well-differentiated groups belonged to C. albicans. Our findings could contribute towards developing molecular epidemiology approaches for managing hospital-acquired infection.