Analysis of clinical Candida parapsilosis isolates reveals copy number variation in key fluconazole resistance genes.

We used whole-genome sequencing to analyze a collection of 35 fluconazole-resistant and 7 susceptible Candida parapsilosis isolates together with coverage analysis and GWAS techniques to identify new mechanisms of fluconazole resistance. Phylogenetic analysis shows that although the collection is diverse, two persistent clinical lineages were identified. We identified copy number variation (CNV) of two genes, ERG11 and CDR1B, in resistant isolates. Two strains have a CNV at the ERG11 locus; the entire ORF is amplified in one, and only the promoter region is amplified in the other. We show that the annotated telomeric gene CDR1B is actually an artifactual in silico fusion of two highly similar neighboring CDR genes due to an assembly error in the C. parapsilosis CDC317 reference genome. We report highly variable copy numbers of the CDR1B region across the collection. Several strains have increased the expansion of the two genes into a tandem array of new chimeric genes. Other strains have experienced a deletion between the two genes creating a single gene with a reciprocal chimerism. We find translocations, duplications, and gene conversion across the CDR gene family in the C. parapsilosis species complex, showing that it is a highly dynamic family.

A secondary mechanism of action for triazole antifungals in Aspergillus fumigatus mediated by hmg1.

Triazole antifungals function as ergosterol biosynthesis inhibitors and are frontline therapy for invasive fungal infections, such as invasive aspergillosis. The primary mechanism of action of triazoles is through the specific inhibition of a cytochrome P450 14-α-sterol demethylase enzyme, Cyp51A/B, resulting in depletion of cellular ergosterol. Here, we uncover a clinically relevant secondary mechanism of action for triazoles within the ergosterol biosynthesis pathway. We provide evidence that triazole-mediated inhibition of Cyp51A/B activity generates sterol intermediate perturbations that are likely decoded by the sterol sensing functions of HMG-CoA reductase and Insulin-Induced Gene orthologs as increased pathway activity. This, in turn, results in negative feedback regulation of HMG-CoA reductase, the rate-limiting step of sterol biosynthesis. We also provide evidence that HMG-CoA reductase sterol sensing domain mutations previously identified as generating resistance in clinical isolates of Aspergillus fumigatus partially disrupt this triazole-induced feedback. Therefore, our data point to a secondary mechanism of action for the triazoles: induction of HMG-CoA reductase negative feedback for downregulation of ergosterol biosynthesis pathway activity. Abrogation of this feedback through acquired mutations in the HMG-CoA reductase sterol sensing domain diminishes triazole antifungal activity against fungal pathogens and underpins HMG-CoA reductase-mediated resistance.

Comparative genomics of Cryptococcus and Kwoniella reveals pathogenesis evolution and contrasting karyotype dynamics via intercentromeric recombination or chromosome fusion.

A large-scale comparative genomic analysis was conducted for the global human fungal pathogens within the Cryptococcus genus, compared to non-pathogenic Cryptococcus species, and related species from the sister genus Kwoniella. Chromosome-level genome assemblies were generated for multiple species of both genera, resulting in a dataset encompassing virtually all of their known diversity. Although Cryptococcus and Kwoniella have comparable genome sizes (about 19.2 and 22.9 Mb) and similar gene content, hinting at pre-adaptive pathogenic potential, our analysis found evidence in pathogenic Cryptococcus species of specific examples of gene gain (via horizontal gene transfer) and gene loss, which might represent evolutionary signatures of pathogenic development. Genome analysis also revealed a significant variation in chromosome number and structure between the two genera. By combining synteny analysis and experimental centromere validation, we found that most Cryptococcus species have 14 chromosomes, whereas most Kwoniella species have fewer (11, 8, 5 or even as few as 3). Reduced chromosome number in Kwoniella is associated with formation of giant chromosomes (up to 18 Mb) through repeated chromosome fusion events, each marked by a pericentric inversion and centromere loss. While similar chromosome inversion-fusion patterns were observed in all Kwoniella species with fewer than 14 chromosomes, no such pattern was detected in Cryptococcus. Instead, Cryptococcus species with less than 14 chromosomes, underwent chromosome reductions primarily through rearrangements associated with the loss of repeat-rich centromeres. Additionally, Cryptococcus genomes exhibited frequent interchromosomal translocations, including intercentromeric recombination facilitated by transposons shared between centromeres. Taken together, our findings advance our understanding of genomic changes possibly associated with pathogenicity in Cryptococcus and provide a foundation to elucidate mechanisms of centromere loss and chromosome fusion driving distinct karyotypes in closely related fungal species, including prominent global human pathogens.

Genetic diversity and microevolution in clinical Cryptococcus isolates from Cameroon.

Cryptococcal meningitis is the second most common cause of death in people living with HIV/AIDS, yet we have a limited understanding of how cryptococcal isolates change over the course of infection. Cryptococcal infections are environmentally acquired, and the genetic diversity of these infecting isolates can also be geographically linked. Here, we employ whole genome sequences for 372 clinical Cryptococcus isolates from 341 patients with HIV-associated cryptococcal meningitis obtained via a large clinical trial, across both Malawi and Cameroon, to enable population genetic comparisons of isolates between countries. We see that isolates from Cameroon are highly clonal, when compared to those from Malawi, with differential rates of disruptive variants in genes with roles in DNA binding and energy use. For a subset of patients (22) from Cameroon, we leverage longitudinal sampling, with samples taken at days 7 and 14 post-enrollment, to interrogate the genetic changes that arise over the course of infection, and the genetic diversity of isolates within patients. We see disruptive variants arising over the course of infection in several genes, including the phagocytosis-regulating transcription factor GAT204. In addition, in 13% of patients sampled longitudinally, we see evidence for mixed infections. This approach identifies geographically linked genetic variation, signatures of microevolution, and evidence for mixed infections across a clinical cohort of patients affected by cryptococcal meningitis in Central Africa.

Cryptococcal meningitis, caused by Cryptococcus, results in approximately half a million deaths per year globally. We compare clinical Cryptococcus samples from Cameroon and Malawi to explore the genetic diversity of these isolates. We find instances of mixed-strain infections and identify genetic variants arising in Cryptococcus over disease.

Genome Sequence of Lichtheimia ornata, an Emerging Opportunistic Mucorales Pathogen.

Lichtheimia ornata is an emerging opportunistic Mucorales pathogen that is associated with fatal infections in immunocompromised individuals. While these environmentally acquired infections have rarely been reported to date, cases were noted in a recent analysis of coronavirus disease 2019 (COVID-19)-associated mucormycosis in India. Here, we report the annotated genome sequence of the environmental isolate CBS 291.66.

Impact of pathogen genetics on clinical phenotypes in a population of Talaromyces marneffei from Vietnam.

Talaromycosis, a severe and invasive fungal infection caused by Talaromyces marneffei, is difficult to treat and impacts those living in endemic regions of Southeast Asia, India, and China. While 30% of infections result in mortality, our understanding of the genetic basis of pathogenesis for this fungus is limited. To address this, we apply population genomics and genome-wide association study approaches to a cohort of 336 T. marneffei isolates collected from patients who enrolled in the Itraconazole vs Amphotericin B for Talaromycosis trial in Vietnam. We find that isolates from northern and southern Vietnam form two distinct geographical clades, with isolates from southern Vietnam associated with increased disease severity. Leveraging longitudinal isolates, we identify multiple instances of disease relapse linked to unrelated strains, highlighting the potential for multistrain infections. In more frequent cases of persistent talaromycosis caused by the same strain, we identify variants arising over the course of patient infections that impact genes predicted to function in the regulation of gene expression and secondary metabolite production. By combining genetic variant data with patient metadata for all 336 isolates, we identify pathogen variants significantly associated with multiple clinical phenotypes. In addition, we identify genes and genomic regions under selection across both clades, highlighting loci undergoing rapid evolution, potentially in response to external pressures. With this combination of approaches, we identify links between pathogen genetics and patient outcomes and identify genomic regions that are altered during T. marneffei infection, providing an initial view of how pathogen genetics affects disease outcomes.

Impact of pathogen genetics on clinical phenotypes in a population of Talaromyces marneffei from Vietnam.

Talaromycosis, a severe and invasive fungal infection caused by Talaromyces marneffei , is difficult to treat and impacts those living in endemic regions of southeast Asia, India, and China. While 30% of infections result in mortality, our understanding of the genetic basis of pathogenesis for this fungus is limited. To address this, we apply population genomics and genome wide association study approaches to a cohort of 336 T. marneffei isolates collected from patients who enrolled in the Itraconazole versus Amphotericin B for Talaromycosis (IVAP) trial in Vietnam. We find that isolates from northern and southern Vietnam form two distinct geographical clades, with isolates from southern Vietnam associated with increased disease severity. Leveraging longitudinal isolates, we identify multiple instances of disease relapse linked to unrelated strains, highlighting the potential for multi-strain infections. In more frequent cases of persistent talaromycosis caused by the same strain, we identify variants arising over the course of patient infections that impact genes predicted to function in the regulation of gene expression and secondary metabolite production. By combining genetic variant data with patient metadata for all 336 isolates, we identify pathogen variants significantly associated with multiple clinical phenotypes. In addition, we identify genes and genomic regions under selection across both clades, highlighting loci undergoing rapid evolution, potentially in response to external pressures. With this combination of approaches, we identify links between pathogen genetics and patient outcomes and identify genomic regions that are altered during T. marneffei infection, providing an initial view of how pathogen genetics affects disease outcomes.

Comparing genomic variant identification protocols for Candida auris.

Genomic analyses are widely applied to epidemiological, population genetic and experimental studies of pathogenic fungi. A wide range of methods are employed to carry out these analyses, typically without including controls that gauge the accuracy of variant prediction. The importance of tracking outbreaks at a global scale has raised the urgency of establishing high-accuracy pipelines that generate consistent results between research groups. To evaluate currently employed methods for whole-genome variant detection and elaborate best practices for fungal pathogens, we compared how 14 independent variant calling pipelines performed across 35 Candida auris isolates from 4 distinct clades and evaluated the performance of variant calling, single-nucleotide polymorphism (SNP) counts and phylogenetic inference results. Although these pipelines used different variant callers and filtering criteria, we found high overall agreement of SNPs from each pipeline. This concordance correlated with site quality, as SNPs discovered by a few pipelines tended to show lower mapping quality scores and depth of coverage than those recovered by all pipelines. We observed that the major differences between pipelines were due to variation in read trimming strategies, SNP calling methods and parameters, and downstream filtration criteria. We calculated specificity and sensitivity for each pipeline by aligning three isolates with chromosomal level assemblies and found that the GATK-based pipelines were well balanced between these metrics. Selection of trimming methods had a greater impact on SAMtools-based pipelines than those using GATK. Phylogenetic trees inferred by each pipeline showed high consistency at the clade level, but there was more variability between isolates from a single outbreak, with pipelines that used more stringent cutoffs having lower resolution. This project generated two truth datasets useful for routine benchmarking of C. auris variant calling, a consensus VCF of genotypes discovered by 10 or more pipelines across these 35 diverse isolates and variants for 2 samples identified from whole-genome alignments. This study provides a foundation for evaluating SNP calling pipelines and developing best practices for future fungal genomic studies.

Genome-Wide Identification of Variants Associated with Antifungal Drug Resistance.

Genomic approaches are widely applied to study the genetic basis of antifungal drug resistance in clinical isolates and experimental studies. Whole-genome sequencing of clinical isolates can comprehensively identify mutations associated with drug resistance and their frequency across fungal populations. In addition, genome comparison of serially collected isolates, such as from patient samples or in vitro drug selection experiments, will identify a small number of changes that can be evaluated for association with drug resistance. Here, we provide a detailed protocol for the computational analysis of genome sequences to identify variants associated with drug resistance.

Multimodal analysis of the COVID-19-associated mucormycosis outbreak in Delhi, India indicates the convergence of clinical and environmental risk factors.

BACKGROUND: The aetiology of the major outbreak of COVID-19-associated mucormycosis (CAM) in India in spring 2021 remains incompletely understood. Herein, we provide a multifaceted and multi-institutional analysis of clinical, pathogen-related, environmental and healthcare-related factors during CAM outbreak in the metropolitan New Delhi area. METHODS: We reviewed medical records of all patients diagnosed with biopsy-proven CAM (n = 50) at 7 hospitals in the New Delhi, and NCR area in April-June 2021. Two multivariate logistic regression models were used to compare clinical characteristics of CAM cases with COVID-19-hospitalised contemporary patients as controls (n = 69). Additionally, meteorological parameters and mould spore concentrations in outdoor air were analysed. Selected hospital fomites were cultured. Mucorales isolates from CAM patients were analysed by ITS sequencing and whole-genome sequencing (WGS). RESULTS: Independent risk factors for CAM identified by multivariate analysis were previously or newly diagnosed diabetes mellitus, active cancer and severe COVID-19 infection. Supplemental oxygen, remdesivir therapy and ICU admission for COVID-19 were associated with reduced CAM risk. The CAM incidence peak was preceded by an uptick in environmental spore concentrations in the preceding 3-4 weeks that correlated with increasing temperature, high evaporation and decreasing relative humidity. Rhizopus was the most common genus isolated, but we also identified two cases of the uncommon Mucorales, Lichtheimia ornata. WGS found no clonal population of patient isolates. No Mucorales were cultured from hospital fomites. CONCLUSIONS: An intersection of host and environmental factors contributed to the emergence of CAM. Surrogates of access to advanced COVID-19 treatment were associated with lower CAM risk.

Comparison of long- and short-read metagenomic assembly for low-abundance species and resistance genes.

Recent technological and computational advances have made metagenomic assembly a viable approach to achieving high-resolution views of complex microbial communities. In previous benchmarking, short-read (SR) metagenomic assemblers had the highest accuracy, long-read (LR) assemblers generated the most contiguous sequences and hybrid (HY) assemblers balanced length and accuracy. However, no assessments have specifically compared the performance of these assemblers on low-abundance species, which include clinically relevant organisms in the gut. We generated semi-synthetic LR and SR datasets by spiking small and increasing amounts of Escherichia coli isolate reads into fecal metagenomes and, using different assemblers, examined E. coli contigs and the presence of antibiotic resistance genes (ARGs). For ARG assembly, although SR assemblers recovered more ARGs with high accuracy, even at low coverages, LR assemblies allowed for the placement of ARGs within longer, E. coli-specific contigs, thus pinpointing their taxonomic origin. HY assemblies identified resistance genes with high accuracy and had lower contiguity than LR assemblies. Each assembler type's strengths were maintained even when our isolate was spiked in with a competing strain, which fragmented and reduced the accuracy of all assemblies. For strain characterization and determining gene context, LR assembly is optimal, while for base-accurate gene identification, SR assemblers outperform other options. HY assembly offers contiguity and base accuracy, but requires generating data on multiple platforms, and may suffer high misassembly rates when strain diversity exists. Our results highlight the trade-offs associated with each approach for recovering low-abundance taxa, and that the optimal approach is goal-dependent.

Similar evolutionary trajectories in an environmental Cryptococcus neoformans isolate after human and murine infection.

A pet cockatoo was the suspected source of Cryptococcus neoformans recovered from an immunocompromised patient with cryptococcosis based on molecular analyses available in 2000. Here, we report whole genome sequence analysis of the clinical and cockatoo strains. Both are closely related MATα strains belonging to the VNII lineage, confirming that the human infection likely originated from pet bird exposure. The two strains differ by 61 single nucleotide polymorphisms, including eight nonsynonymous changes involving seven genes. To ascertain whether changes in these genes are selected for during mammalian infection, we passaged the cockatoo strain in mice. Remarkably, isolates obtained from mouse tissue possess a frameshift mutation in one of the seven genes altered in the human sample (LQVO5_000317), a gene predicted to encode an SWI-SNF chromatin-remodeling complex protein. In addition, both cockatoo and patient strains as well as mouse-passaged isolates obtained from brain tissue had a premature stop codon in a homologue of ZFC3 (LQVO5_004463), a predicted single-zinc finger containing protein, which is associated with larger capsules when deleted and reverted to a full-length protein in the mouse-passaged isolates obtained from lung tissue. The patient strain and mouse-passaged isolates show variability in virulence factors, with differences in capsule size, melanization, rates of nonlytic expulsion from macrophages, and amoeba predation resistance. Our results establish that environmental strains undergo genomic and phenotypic changes during mammalian passage, suggesting that animal virulence can be a mechanism for genetic change and that the genomes of clinical isolates may provide a readout of mutations acquired during infection.

Analysis of clinical Candida parapsilosis isolates reveals copy number variation in key fluconazole resistance genes.

We used whole-genome sequencing to analyse a collection of 35 fluconazole resistant and 7 susceptible Candida parapsilosis isolates together with coverage analysis and GWAS techniques to identify new mechanisms of fluconazole resistance. Phylogenetic analysis shows that although the collection is diverse, two probable outbreak groups were identified. We identified copy number variation of two genes, ERG11 and CDR1B, in resistant isolates. Two strains have a CNV at the ERG11 locus; the entire ORF is amplified in one, and only the promoter region is amplified in the other. We show the annotated telomeric gene CDR1B is actually an artefactual in silico fusion of two highly similar neighbouring CDR genes due to an assembly error in the C. parapsilosis CDC317 reference genome. We report highly variable copy numbers of the CDR1B region across the collection. Several strains have increased expansion of the two genes into a tandem array of new chimeric genes. Other strains have experienced a deletion between the two genes creating a single gene with a reciprocal chimerism. We find translocations, duplications, and gene conversion across the CDR gene family in the C. parapsilosis species complex, showing that it is a highly dynamic family.

Genomic Variation across a Clinical Cryptococcus Population Linked to Disease Outcome.

Cryptococcus neoformans is the causative agent of cryptococcosis, a disease with poor patient outcomes that accounts for approximately 180,000 deaths each year. Patient outcomes may be impacted by the underlying genetics of the infecting isolate; however, our current understanding of how genetic diversity contributes to clinical outcomes is limited. Here, we leverage clinical, in vitro growth and genomic data for 284 C. neoformans isolates to identify clinically relevant pathogen variants within a population of clinical isolates from patients with human immunodeficiency virus (HIV)-associated cryptococcosis in Malawi. Through a genome-wide association study (GWAS) approach, we identify variants associated with the fungal burden and the growth rate. We also find both small and large-scale variation, including aneuploidy, associated with alternate growth phenotypes, which may impact the course of infection. Genes impacted by these variants are involved in transcriptional regulation, signal transduction, glycosylation, sugar transport, and glycolysis. We show that growth within the central nervous system (CNS) is reliant upon glycolysis in an animal model and likely impacts patient mortality, as the CNS yeast burden likely modulates patient outcome. Additionally, we find that genes with roles in sugar transport are enriched in regions under selection in specific lineages of this clinical population. Further, we demonstrate that genomic variants in two genes identified by GWAS impact virulence in animal models. Our approach identifies links between the genetic variation in C. neoformans and clinically relevant phenotypes and animal model pathogenesis, thereby shedding light on specific survival mechanisms within the CNS and identifying the pathways involved in yeast persistence. IMPORTANCE Infection outcomes for cryptococcosis, most commonly caused by C. neoformans, are influenced by host immune responses as well as by host and pathogen genetics. Infecting yeast isolates are genetically diverse; however, we lack a deep understanding of how this diversity impacts patient outcomes. To better understand both clinical isolate diversity and how diversity contributes to infection outcomes, we utilize a large collection of clinical C. neoformans samples that were isolated from patients enrolled in a clinical trial across 3 hospitals in Malawi. By combining whole-genome sequence data, clinical data, and in vitro growth data, we utilize genome-wide association approaches to examine the genetic basis of virulence. Genes with significant associations display virulence attributes in both murine and rabbit models, demonstrating that our approach can identify potential links between genetic variants and patho-biologically significant phenotypes.

The molecular and genetic basis of antifungal resistance in the emerging fungal pathogen Candida auris.

Fungal infections are responsible for significant morbidity and mortality. Resistance to the limited number of agents in the antifungal armamentarium among pathogenic fungi represents a growing public health threat. Particularly concerning is the emerging fungal pathogen Candida auris that frequently exhibits resistance to the triazole class of antifungals and amphotericin B, and for which isolates resistant to all of the major antifungal classes have been reported. In this brief review, we provide an overview of what is currently known about the molecular and genetic basis for antifungal resistance in this fungal pathogen.

The importance of antimicrobial resistance in medical mycology.

Prior to the SARS-CoV-2 pandemic, antibiotic resistance was listed as the major global health care priority. Some analyses, including the O'Neill report, have predicted that deaths due to drug-resistant bacterial infections may eclipse the total number of cancer deaths by 2050. Although fungal infections remain in the shadow of public awareness, total attributable annual deaths are similar to, or exceeds, global mortalities due to malaria, tuberculosis or HIV. The impact of fungal infections has been exacerbated by the steady rise of antifungal drug resistant strains and species which reflects the widespread use of antifungals for prophylaxis and therapy, and in the case of azole resistance in Aspergillus, has been linked to the widespread agricultural use of antifungals. This review, based on a workshop hosted by the Medical Research Council and the University of Exeter, illuminates the problem of antifungal resistance and suggests how this growing threat might be mitigated.

First Patient-to-Patient Intrahospital Transmission of Clade I Candida auris in France Revealed after a Two-Month Incubation Period.

Candida auris is a recently described emerging pathogen in hospital settings. Five genetic clades have been delineated, with each clade being isolated from specific geographic regions. We here describe the first transmission between 2 patients (P0 and P1) of a clade I C. auris strain imported into our burn intensive care unit from the Middle East. The strains have been investigated with whole-genome sequencing, which validated the high similarity of the genomes between isolates from P0 and P1. We repeatedly screened the two patients and contact patients (i.e., other patients present in the same hospital ward at the time of the first positive sample from P0 or P1; n = 49; 268 tests) with fungal culture and a C. auris-specific quantitative PCR assay to assess transmission patterns. We observed that P1 developed C. auris colonization between 41 and 61 days after potential exposure to P0 contamination, despite three negative screening tests as recommended by our national authorities. This study illustrates that transmission of C. auris between patients can lead to long-term incubation times before the detection of colonization. The recommended screening strategy may not be optimal and should be improved in the light of our findings. IMPORTANCE While large outbreaks of C. auris in hospital settings have been described, few clear cases of direct transmission have been documented. We here investigated the transmission of C. auris clade I between two patients with a 41- to 61-day delay between exposure and the development of colonization. This may lead to changes in the recommendations concerning treatment of C. auris cases, as an incubation period of this length is one of the first to be reported.