Going fishing: how to get what you want from a fungal genetic screen.

Five years ago, as I was starting my lab, I wrote about two functional genomic screens in fungi that had inspired me (mSphere 4:e00299-19, https://doi.org/10.1128/mSphere.00299-19). Now, I want to discuss some of the principles and questions that I ask myself and my students as we embark on our own screens. A good screen, whether it is a genetic or chemical screen, can be the starting point for new discovery and an excellent basis for the beginning of a scientific research project. However, screens are often criticized for being "fishing expeditions." To stretch this metaphor to the extreme, this is because people are worried that we do not know how to fish, that we will come home without any fish, bring home the wrong fish, or not know what to do with a fish if we caught it. How you set up the screen and analyze the results determines whether the screen will be useful. In this mini-review, and in the spirit of teaching a scientist to fish, I will discuss recent excellent fungal genetic and chemical screens that illustrate some of the key aspects of a successful screen.

The many faces of Candida auris: Phenotypic and strain variation in an emerging pathogen.

Candida auris is an emerging fungal pathogen with unusual evolutionary history-there are multiple distinct phylogeographic clades showing a near simultaneous transition from a currently unknown reservoir to nosocomial pathogen. Each of these clades has experienced different selective pressures over time, likely resulting in selection for genotypes with differential fitness or phenotypic consequences when introduced to new environments. We also observe diversification within clades, providing additional opportunities for phenotypic differences. These differences can have large impacts on pathogenic potential, drug resistance profile, evolutionary trajectory, and transmissibility. In recent years, there have been significant advances in our understanding of strain-specific behavior in other microbes, including bacterial and fungal pathogens, and we have an opportunity to take this strain variation into account when describing aspects of C. auris biology. Here, we critically review the literature to gain insight into differences at both the strain and clade levels in C. auris, focusing on phenotypes associated with clinical disease or transmission. Our goal is to integrate clinical and epidemiological perspectives with molecular perspectives in a way that would be valuable for both audiences. Identifying differences between strains and understanding which phenotypes are strain specific will be crucial for understanding this emerging pathogen, and an important caveat when describing the analysis of a singular isolate.

CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair.

Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Cryptococcus neoformans, a prevalent human fungal pathogen greatly diverged from model yeasts, approximately 60% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a C. neoformans Co-Expression Network (CryptoCEN), successfully recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. With 100% predictive accuracy, we used CryptoCEN to identify 13 new DNA damage response genes, underscoring the utility of guilt-by-association for determining gene function. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes.

Non-canonical activation of IRE1α during Candida albicans infection enhances macrophage fungicidal activity.

Infection by intracellular pathogens can trigger activation of the IRE1α branch of the unfolded protein response (UPR), which then modulates innate immunity and infection outcomes during bacterial or viral infection. However, the mechanisms by which infection activates IRE1α have not been fully elucidated. While recognition of microbe-associated molecular patterns can activate IRE1α, it is unclear whether this depends on the canonical role of IRE1α in detecting misfolded proteins. Here, we report that Candida albicans infection of macrophages results in IRE1α activation through C-type lectin receptor signaling, reinforcing a role for IRE1α as a central regulator of host responses to infection by a broad range of pathogens. However, IRE1α activation was not preceded by protein misfolding in response to either C. albicans infection or lipopolysaccharide treatment, implicating a non-canonical mode of IRE1α activation after recognition of microbial patterns. Investigation of the phenotypic consequences of IRE1α activation in macrophage antimicrobial responses revealed that IRE1α activity enhances the fungicidal activity of macrophages. Macrophages lacking IRE1α activity displayed inefficient phagolysosomal fusion, enabling C. albicans to evade fungal killing and escape the phagosome. Together, these data provide mechanistic insight for the non-canonical activation of IRE1α during infection, and reveal central roles for IRE1α in macrophage antifungal responses.

A Candida auris-specific adhesin, Scf1, governs surface association, colonization, and virulence.

Candida auris is an emerging fungal pathogen responsible for health care-associated outbreaks that arise from persistent surface and skin colonization. We characterized the arsenal of adhesins used by C. auris and discovered an uncharacterized adhesin, Surface Colonization Factor (Scf1), and a conserved adhesin, Iff4109, that are essential for the colonization of inert surfaces and mammalian hosts. SCF1 is apparently specific to C. auris, and its expression mediates adhesion to inert and biological surfaces across isolates from all five clades. Unlike canonical fungal adhesins, which function through hydrophobic interactions, Scf1 relies on exposed cationic residues for surface association. SCF1 is required for C. auris biofilm formation, skin colonization, virulence in systemic infection, and colonization of inserted medical devices.

CryptoCEN: A Co-Expression Network for Cryptococcus neoformans reveals novel proteins involved in DNA damage repair.

Elucidating gene function is a major goal in biology, especially among non-model organisms. However, doing so is complicated by the fact that molecular conservation does not always mirror functional conservation, and that complex relationships among genes are responsible for encoding pathways and higher-order biological processes. Co-expression, a promising approach for predicting gene function, relies on the general principal that genes with similar expression patterns across multiple conditions will likely be involved in the same biological process. For Cryptococcus neoformans, a prevalent human fungal pathogen greatly diverged from model yeasts, approximately 60% of the predicted genes in the genome lack functional annotations. Here, we leveraged a large amount of publicly available transcriptomic data to generate a C. neoformans Co-Expression Network (CryptoCEN), successfully recapitulating known protein networks, predicting gene function, and enabling insights into the principles influencing co-expression. With 100% predictive accuracy, we used CryptoCEN to identify 13 new DNA damage response genes, underscoring the utility of guilt-by-association for determining gene function. Overall, co-expression is a powerful tool for uncovering gene function, and decreases the experimental tests needed to identify functions for currently under-annotated genes.

Imaging-Based Screening Identifies Modulators of the eIF3 Translation Initiation Factor Complex in Candida albicans.

Fungal pathogens like Candida albicans can cause devastating human disease. Treatment of candidemia is complicated by the high rate of resistance to common antifungal therapies. Additionally, there is host toxicity associated with many antifungal compounds due to the conservation between essential mammalian and fungal proteins. An attractive new approach for antimicrobial development is to target virulence factors: non-essential processes that are required for the organism to cause disease in human hosts. This approach expands the potential target space while reducing the selective pressure toward resistance, as these targets are not essential for viability. In C. albicans, a key virulence factor is the ability to transition to hyphal morphology. We developed a high-throughput image analysis pipeline to distinguish between yeast and filamentous growth in C. albicans at the single cell level. Based on this phenotypic assay, we screened the FDA drug repurposing library of 2,017 compounds for their ability to inhibit filamentation and identified 33 compounds that block the hyphal transition in C. albicans with IC50 values ranging from 0.2 to 150 µM. Multiple compounds showed a phenyl sulfone chemotype, prompting further analysis. Of these phenyl sulfones, NSC 697923 displayed the most efficacy, and by selecting for resistant mutants, we identified eIF3 as the target of NSC 697923 in C. albicans.

Candida albicans selection for human commensalism results in substantial within-host diversity without decreasing fitness for invasive disease.

Candida albicans is a frequent colonizer of human mucosal surfaces as well as an opportunistic pathogen. C. albicans is remarkably versatile in its ability to colonize diverse host sites with differences in oxygen and nutrient availability, pH, immune responses, and resident microbes, among other cues. It is unclear how the genetic background of a commensal colonizing population can influence the shift to pathogenicity. Therefore, we examined 910 commensal isolates from 35 healthy donors to identify host niche-specific adaptations. We demonstrate that healthy people are reservoirs for genotypically and phenotypically diverse C. albicans strains. Using limited diversity exploitation, we identified a single nucleotide change in the uncharacterized ZMS1 transcription factor that was sufficient to drive hyper invasion into agar. We found that SC5314 was significantly different from the majority of both commensal and bloodstream isolates in its ability to induce host cell death. However, our commensal strains retained the capacity to cause disease in the Galleria model of systemic infection, including outcompeting the SC5314 reference strain during systemic competition assays. This study provides a global view of commensal strain variation and within-host strain diversity of C. albicans and suggests that selection for commensalism in humans does not result in a fitness cost for invasive disease.

Imaging-based screening identifies modulators of the eIF3 translation initiation factor complex in Candida albicans.

Fungal pathogens like Candida albicans can cause devastating human disease. Treatment of candidemia is complicated by the high rate of resistance to common antifungal therapies. Additionally, there is host toxicity associated with many antifungal compounds due to the conservation between essential mammalian and fungal proteins. An attractive new approach for antimicrobial development is to target virulence factors: non-essential processes that are required for the organism to cause disease in human hosts. This approach expands the potential target space while reducing the selective pressure towards resistance, as these targets are not essential for viability. In C. albicans, a key virulence factor is the ability to transition to hyphal morphology. We developed a high-throughput image analysis pipeline to distinguish between yeast and filamentous growth in C. albicans at the single cell level. Based on this phenotypic assay, we screened the FDA drug repurposing library of 2,017 compounds for their ability to inhibit filamentation and identified 33 compounds that block the hyphal transition in C. albicans with IC 50 values ranging from 0.2 to 150 µM. Multiple compounds showed a phenyl vinyl sulfone chemotype, prompting further analysis. Of these phenyl vinyl sulfones, NSC 697923 displayed the most efficacy, and by selecting for resistant mutants, we identified eIF3 as the target of NSC 697923 in C. albicans .

Forward and reverse genetic dissection of morphogenesis identifies filament-competent Candida auris strains.

Candida auris is an emerging healthcare-associated pathogen of global concern. Recent reports have identified C. auris isolates that grow in cellular aggregates or filaments, often without a clear genetic explanation. To investigate the regulation of C. auris morphogenesis, we applied an Agrobacterium-mediated transformation system to all four C. auris clades. We identified aggregating mutants associated with disruption of chitin regulation, while disruption of ELM1 produced a polarized, filamentous growth morphology. We developed a transiently expressed Cas9 and sgRNA system for C. auris that significantly increased targeted transformation efficiency across the four C. auris clades. Using this system, we confirmed the roles of C. auris morphogenesis regulators. Morphogenic mutants showed dysregulated chitinase expression, attenuated virulence, and altered antifungal susceptibility. Our findings provide insights into the genetic regulation of aggregating and filamentous morphogenesis in C. auris. Furthermore, the genetic tools described here will allow for efficient manipulation of the C. auris genome.

Leveraging machine learning essentiality predictions and chemogenomic interactions to identify antifungal targets.

Fungal pathogens pose a global threat to human health, with Candida albicans among the leading killers. Systematic analysis of essential genes provides a powerful strategy to discover potential antifungal targets. Here, we build a machine learning model to generate genome-wide gene essentiality predictions for C. albicans and expand the largest functional genomics resource in this pathogen (the GRACE collection) by 866 genes. Using this model and chemogenomic analyses, we define the function of three uncharacterized essential genes with roles in kinetochore function, mitochondrial integrity, and translation, and identify the glutaminyl-tRNA synthetase Gln4 as the target of N-pyrimidinyl-ß-thiophenylacrylamide (NP-BTA), an antifungal compound.

A small molecule produced by Lactobacillus species blocks Candida albicans filamentation by inhibiting a DYRK1-family kinase.

The fungus Candida albicans is an opportunistic pathogen that can exploit imbalances in microbiome composition to invade its human host, causing pathologies ranging from vaginal candidiasis to fungal sepsis. Bacteria of the genus Lactobacillus are colonizers of human mucosa and can produce compounds with bioactivity against C. albicans. Here, we show that some Lactobacillus species produce a small molecule under laboratory conditions that blocks the C. albicans yeast-to-filament transition, an important virulence trait. It remains unexplored whether the compound is produced in the context of the human host. Bioassay-guided fractionation of Lactobacillus-conditioned medium linked this activity to 1-acetyl-ß-carboline (1-ABC). We use genetic approaches to show that filamentation inhibition by 1-ABC requires Yak1, a DYRK1-family kinase. Additional biochemical characterization of structurally related 1-ethoxycarbonyl-ß-carboline confirms that it inhibits Yak1 and blocks C. albicans biofilm formation. Thus, our findings reveal Lactobacillus-produced 1-ABC can prevent the yeast-to-filament transition in C. albicans through inhibition of Yak1.

The macrophage-derived protein PTMA induces filamentation of the human fungal pathogen Candida albicans.

Evasion of killing by immune cells is crucial for fungal survival in the host. For the human fungal pathogen Candida albicans, internalization by macrophages induces a transition from yeast to filaments that promotes macrophage death and fungal escape. Nutrient deprivation, alkaline pH, and oxidative stress have been implicated as triggers of intraphagosomal filamentation; however, the impact of other host-derived factors remained unknown. Here, we show that lysates prepared from macrophage-like cell lines and primary macrophages robustly induce C. albicans filamentation. Enzymatic treatment of lysate implicates a phosphorylated protein, and bioactivity-guided fractionation coupled to mass spectrometry identifies the immunomodulatory phosphoprotein PTMA as a candidate trigger of C. albicans filamentation. Immunoneutralization of PTMA within lysate abolishes its activity, strongly supporting PTMA as a filament-inducing component of macrophage lysate. Adding to the known repertoire of physical factors, this work implicates a host protein in the induction of C. albicans filamentation within immune cells.

Metagenomic Sequencing for Direct Identification of Candida auris Colonization.

Candida auris is an emerging multidrug-resistant yeast that is associated with skin colonization and deadly bloodstream infections, especially in ventilator skilled nursing facilities. An ongoing question is how this organism colonizes the skin of these patients and whether the skin microbiome provides a measure of colonization resistance against C. auris. Now, Huang et al. (X. Huang, R. M. Welsh, C. Deming, D. M. Proctor, et al., mSphere 6:e00287-21, 2021, https://doi.org/10.1128/mSphere.00287-21) demonstrate a method for shotgun metagenomic analysis of the skin to generate a profile of fungal colonization that is highly correlative with culture-based methods. These methods are likely to assist in the diagnosis of C. auris and the identification of microbiome-associated risk factors that predict invasive disease.

Morphological cell profiling of SARS-CoV-2 infection identifies drug repurposing candidates for COVID-19.

The global spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the associated disease COVID-19, requires therapeutic interventions that can be rapidly identified and translated to clinical care. Traditional drug discovery methods have a >90% failure rate and can take 10 to 15 y from target identification to clinical use. In contrast, drug repurposing can significantly accelerate translation. We developed a quantitative high-throughput screen to identify efficacious agents against SARS-CoV-2. From a library of 1,425 US Food and Drug Administration (FDA)-approved compounds and clinical candidates, we identified 17 hits that inhibited SARS-CoV-2 infection and analyzed their antiviral activity across multiple cell lines, including lymph node carcinoma of the prostate (LNCaP) cells and a physiologically relevant model of alveolar epithelial type 2 cells (iAEC2s). Additionally, we found that inhibitors of the Ras/Raf/MEK/ERK signaling pathway exacerbate SARS-CoV-2 infection in vitro. Notably, we discovered that lactoferrin, a glycoprotein found in secretory fluids including mammalian milk, inhibits SARS-CoV-2 infection in the nanomolar range in all cell models with multiple modes of action, including blockage of virus attachment to cellular heparan sulfate and enhancement of interferon responses. Given its safety profile, lactoferrin is a readily translatable therapeutic option for the management of COVID-19.

Adaptive immunity induces mutualism between commensal eukaryotes.

Pathogenic fungi reside in the intestinal microbiota but rarely cause disease. Little is known about the interactions between fungi and the immune system that promote commensalism. Here we investigate the role of adaptive immunity in promoting mutual interactions between fungi and host. We find that potentially pathogenic Candida species induce and are targeted by intestinal immunoglobulin A (IgA) responses. Focused studies on Candida albicans reveal that the pathogenic hyphal morphotype, which is specialized for adhesion and invasion, is preferentially targeted and suppressed by intestinal IgA responses. IgA from mice and humans directly targets hyphal-enriched cell-surface adhesins. Although typically required for pathogenesis, C. albicans hyphae are less fit for gut colonization1,2 and we show that immune selection against hyphae improves the competitive fitness of C. albicans. C. albicans exacerbates intestinal colitis3 and we demonstrate that hyphae and an IgA-targeted adhesin exacerbate intestinal damage. Finally, using a clinically relevant vaccine to induce an adhesin-specific immune response protects mice from C. albicans-associated damage during colitis. Together, our findings show that adaptive immunity suppresses harmful fungal effectors, with benefits to both C. albicans and its host. Thus, IgA uniquely uncouples colonization from pathogenesis in commensal fungi to promote homeostasis.

Mitochondrial perturbation reduces susceptibility to xenobiotics through altered efflux in Candida albicans.

Candida albicans is a leading human fungal pathogen, which can cause superficial infections or life-threatening systemic disease in immunocompromised individuals. The ability to transition between yeast and filamentous forms is a major virulence trait of C. albicans, and a key regulator of this morphogenetic transition is the molecular chaperone Hsp90. To explore the mechanisms governing C. albicans morphogenesis in response to Hsp90 inhibition, we performed a functional genomic screen using the gene replacement and conditional expression collection to identify mutants that are defective in filamentation in response to the Hsp90 inhibitor, geldanamycin. We found that transcriptional repression of genes involved in mitochondrial function blocked filamentous growth in response to the concentration of the Hsp90 inhibitor used in the screen, and this was attributable to increased resistance to the compound. Further exploration revealed that perturbation of mitochondrial function reduced susceptibility to two structurally distinct Hsp90 inhibitors, geldanamycin and radicicol, such that filamentous growth was restored in the mitochondrial mutants by increasing the compound concentration. Deletion of two representative mitochondrial genes, MSU1 and SHY1, enhanced cellular efflux and reduced susceptibility to diverse intracellularly acting compounds. Additionally, screening a C. albicans efflux pump gene deletion library implicated Yor1 in the efflux of geldanamycin and Cdr1, in the efflux of radicicol. Deletion of these transporter genes restored sensitivity to Hsp90 inhibitors in MSU1 and SHY1 homozygous deletion mutants, thereby enabling filamentation. Taken together, our findings suggest that mitochondrial dysregulation elevates cellular efflux and consequently reduces susceptibility to xenobiotics in C. albicans.

DeORFanizing Candida albicans Genes using Coexpression.

Functional characterization of open reading frames in nonmodel organisms, such as the common opportunistic fungal pathogen Candida albicans, can be labor-intensive. To meet this challenge, we built a comprehensive and unbiased coexpression network for C. albicans, which we call CalCEN, from data collected from 853 RNA sequencing runs from 18 large-scale studies deposited in the NCBI Sequence Read Archive. Retrospectively, CalCEN is highly predictive of known gene function annotations and can be synergistically combined with sequence similarity and interaction networks in Saccharomyces cerevisiae through orthology for additional accuracy in gene function prediction. To prospectively demonstrate the utility of the coexpression network in C. albicans, we predicted the function of underannotated open reading frames (ORFs) and identified CCJ1 as a novel cell cycle regulator in C. albicans This study provides a tool for future systems biology analyses of gene function in C. albicans We provide a computational pipeline for building and analyzing the coexpression network and CalCEN itself at http://github.com/momeara/CalCENIMPORTANCECandida albicans is a common and deadly fungal pathogen of humans, yet the genome of this organism contains many genes of unknown function. By determining gene function, we can help identify essential genes, new virulence factors, or new regulators of drug resistance, and thereby give new targets for antifungal development. Here, we use information from large-scale RNA sequencing (RNAseq) studies and generate a C. albicans coexpression network (CalCEN) that is robust and able to predict gene function. We demonstrate the utility of this network in both retrospective and prospective testing and use CalCEN to predict a role for C4_06590W/CCJ1 in cell cycle. This tool will allow for a better characterization of underannotated genes in pathogenic yeasts.