Systematic truncations of chromosome 4 and their responses to antifungals in Candida albicans

The role of gene copy number variation in antimicrobial resistance in human fungal pathogens

Faced with the burden of increasing resistance to antifungals in many fungal pathogens and the constant emergence of new drug-resistant strains, it is essential to assess the importance of various resistance mechanisms. Fungi have relatively plastic genomes and can tolerate genomic copy number variation (CNV) caused by aneuploidy and gene amplification or deletion. In many cases, these genomic changes lead to adaptation to stressful conditions, including those caused by antifungal drugs. Here, we specifically examine the contribution of CNVs to antifungal resistance. We undertook a thorough literature search, collecting reports of antifungal resistance caused by a CNV, and classifying the examples of CNV-conferred resistance into four main mechanisms. We find that in human fungal pathogens, there is little evidence that gene copy number plays a major role in the emergence of antifungal resistance compared to other types of mutations. We discuss why we might be underestimating their importance and new approaches being used to study them.

In-vitro Evaluation of the Antifungal Property of Cold-Pressed Coconut oil Against Drug-Resistant Candida albicans and in-Silico Bioactivity Against Candidapepsin-2

Objective: This study focuses on Candida albicans, a significant fungal pathogen in humans, particularly affecting immunocompromised individuals and developing resistance to commonly used antifungal drugs. To address this challenge, the research assessed the in-vitro anti-candida properties of cold-pressed coconut oil. Additionally, the study conducted an in-silico evaluation of the oil's bioactive compounds against candidapepsin-2, an enzyme crucial in the virulence and pathogenesis of Candida infections. Materials and Methods: Extracted coconut oil was tested for its sterility and evaluated for its antifungal activity in-vitro using the agar well-diffusion methods with fluconazole as a positive control. Growth kinetics assay and synergism activity with fluconazole were also assessed. The coconut oil was quantitatively screened for its bioactive compounds using gas chromatography coupled to a mass spectrophotometer (GC-MS) and the resulting bioactive compounds were assessed for absorption, distribution, metabolism, excretion and toxicity (ADMET) properties using the SWISSADME tool. Compounds that met Lipinski's rule of five (ROF) were subjected to molecular docking against candidapepsin-2 using the Biovia (Discovery) docking tool. Results: The test isolates exhibited zones of inhibition ranging from 47–76 mm to the extract (100%) compared to 12–42 mm exhibited against fluconazole (400 mg) and 2–3 mm in plates containing only agar with MICs and MFCs ranging from 1.57–6.25% and 3.13 −12.5% against the extract compared to the control drug where MICs and MFCs of 6.25–12.5% and 12.5–25.0% were observed, respectively. The coconut extract exerted a concentration-dependent effect on the test isolates over time as higher extract concentrations decreased the optical density of cells to 0.001–0.06 at 72 h of incubation. Equal proportions of the extract + fluconazole exerted greater inhibitory potentials on the test isolates compared with those of low extract proportions. The synergistic-antagonistic antifungal assay showed enhanced sensitivity of the resistant isolates. Of the eleven (11) bioactive compounds quantitatively screened, only nine (9) met Lipinski's ROF and also returned favourable pharmacokinetics comparable to fluconazole. Docking scores for the bioactive compounds ranged from −2.0 to −3.0 kcal/mol. The most recurring amino acid residues following molecular docking were ILE and THR. Conclusion: The bioactive compounds showed desirable activities in-vitro, especially in synergy with fluconazole against the drug-resistant Candida species and in-silico and thus, require further studies to validate their potential use in the management of Candida-related infections.

Molecular Diagnostics for Invasive Fungal Diseases: Current and Future Approaches

Invasive fungal diseases (IFDs) comprise a growing healthcare burden, especially given the expanding population of immunocompromised hosts. Early diagnosis of IFDs is required to optimise therapy with antifungals, especially in the setting of rising rates of antifungal resistance. Molecular techniques including nucleic acid amplification tests and whole genome sequencing have potential to offer utility in overcoming limitations with traditional phenotypic testing. However, standardisation of methodology and interpretations of these assays is an ongoing undertaking. The utility of targeted Aspergillus detection has been well-defined, with progress in investigations into the role of targeted assays for Candida, Pneumocystis, Cryptococcus, the Mucorales and endemic mycoses. Likewise, whilst broad-range polymerase chain reaction assays have been in use for some time, pathology stewardship and optimising diagnostic yield is a continuing exercise. As costs decrease, there is also now increased access and experience with whole genome sequencing, including metagenomic sequencing, which offers unparalleled resolution especially in the investigations of potential outbreaks. However, their role in routine diagnostic use remains uncommon and standardisation of techniques and workflow are required for wider implementation.

The challenges of the genome-based identification of antifungal resistance in the clinical routine

The increasing number of chronic and life-threatening infections caused by antimicrobial resistant fungal isolates is of critical concern. Low DNA sequencing cost may facilitate the identification of the genomic profile leading to resistance, the resistome, to rationally optimize the design of antifungal therapies. However, compared to bacteria, initiatives for resistome detection in eukaryotic pathogens are underdeveloped. Firstly, reported mutations in antifungal targets leading to reduced susceptibility must be extensively collected from the literature to generate comprehensive databases. This information should be complemented with specific laboratory screenings to detect the highest number possible of relevant genetic changes in primary targets and associations between resistance and other genomic markers. Strikingly, some drug resistant strains experience high-level genetic changes such as ploidy variation as much as duplications and reorganizations of specific chromosomes. Such variations involve allelic dominance, gene dosage increments and target expression regime effects that should be explicitly parameterized in antifungal resistome prediction algorithms. Clinical data indicate that predictors need to consider the precise pathogen species and drug levels of detail, instead of just genus and drug class. The concomitant needs for mutation accuracy and assembly quality assurance suggest hybrid sequencing approaches involving third-generation methods will be utilized. Moreover, fatal fast infections, like fungemia and meningitis, will further require both sequencing and analysis facilities are available in-house. Altogether, the complex nature of antifungal resistance demands extensive sequencing, data acquisition and processing, bioinformatic analysis pipelines, and standard protocols to be accomplished prior to genome-based protocols are applied in the clinical setting.