Metabolic reconstruction of the human pathogen Candida auris: using a cross-species approach for drug target prediction.

Candida auris is an emerging human pathogen, associated with antifungal drug resistance and hospital candidiasis outbreaks. In this work, we present iRV973, the first reconstructed Genome-scale metabolic model (GSMM) for C. auris. The model was manually curated and experimentally validated, being able to accurately predict the specific growth rate of C. auris and the utilization of several sole carbon and nitrogen sources. The model was compared to GSMMs available for other pathogenic Candida species and exploited as a platform for cross-species comparison, aiming the analysis of their metabolic features and the identification of potential new antifungal targets common to the most prevalent pathogenic Candida species. From a metabolic point of view, we were able to identify unique enzymes in C. auris in comparison with other Candida species, which may represent unique metabolic features. Additionally, 50 enzymes were identified as potential drug targets, given their essentiality in conditions mimicking human serum, common to all four different Candida models analysed. These enzymes represent interesting drug targets for antifungal therapy, including some known targets of antifungal agents used in clinical practice, but also new potential drug targets without any human homolog or drug association in Candida species.

YEASTRACT+: a portal for the exploitation of global transcription regulation and metabolic model data in yeast biotechnology and pathogenesis.

YEASTRACT+ (http://yeastract-plus.org/) is a tool for the analysis, prediction and modelling of transcription regulatory data at the gene and genomic levels in yeasts. It incorporates three integrated databases: YEASTRACT (http://yeastract-plus.org/yeastract/), PathoYeastract (http://yeastract-plus.org/pathoyeastract/) and NCYeastract (http://yeastract-plus.org/ncyeastract/), focused on Saccharomyces cerevisiae, pathogenic yeasts of the Candida genus, and non-conventional yeasts of biotechnological relevance. In this release, YEASTRACT+ offers upgraded information on transcription regulation for the ten previously incorporated yeast species, while extending the database to another pathogenic yeast, Candida auris. Since the last release of YEASTRACT+ (January 2020), a fourth database has been integrated. CommunityYeastract (http://yeastract-plus.org/community/) offers a platform for the creation, use, and future update of YEASTRACT-like databases for any yeast of the users' choice. CommunityYeastract currently provides information for two Saccharomyces boulardii strains, Rhodotorula toruloides NP11 oleaginous yeast, and Schizosaccharomyces pombe 972h-. In addition, YEASTRACT+ portal currently gathers 304 547 documented regulatory associations between transcription factors (TF) and target genes and 480 DNA binding sites, considering 2771 TFs from 11 yeast species. A new set of tools, currently implemented for S. cerevisiae and C. albicans, is further offered, combining regulatory information with genome-scale metabolic models to provide predictions on the most promising transcription factors to be exploited in cell factory optimisation or to be used as novel drug targets. The expansion of these new tools to the remaining YEASTRACT+ species is ongoing.

Genomic evolution towards azole resistance in Candida glabrata clinical isolates unveils the importance of CgHxt4/6/7 in azole accumulation.

The increasing prevalence of candidosis caused by Candida glabrata is related to its ability to acquire azole resistance. Although azole resistance mechanisms are well known, the mechanisms for azole import into fungal cells have remained obscure. In this work, we have characterized two hexose transporters in C. glabrata and further investigate their role as potential azole importers. Three azole susceptible C. glabrata clinical isolates were evolved towards azole resistance and the acquired resistance phenotype was found to be independent of CgPDR1 or CgERG11 mutations. Through whole-genome sequencing, CgHXT4/6/7 was found to be mutated in the three evolved strains, when compared to their susceptible parents. CgHxt4/6/7 and the 96% identical CgHxt6/7 were found to confer azole susceptibility and increase azole accumulation in C. glabrata cells, strikingly rescuing the susceptibility phenotype imposed by CgPDR1 deletion, while the identified loss-of-function mutation in CgHXT4/6/7, leads to increased azole resistance. In silico docking analysis shows that azoles display a strong predicted affinity for the glucose binding site of CgHxt4/6/7. Altogether, we hypothesize that hexose transporters, such as CgHxt4/6/7 and CgHxt6/7, may constitute a family of azole importers, involved in clinical drug resistance in fungal pathogens, and constituting promising targets for improved antifungal therapy.

Prediction of Gene and Genomic Regulation in Candida Species, Using the PathoYeastract Database: A Comparative Genomics Approach.

The ability of living organisms to survive changing environmental conditions is dependent on the implementation of gene expression programs underlying adaptation and fitness. Transcriptional networks can be exceptionally complex: a single transcription factor (TF) may regulate hundreds of genes, and multiple TFs may regulate a single gene-depending on the environmental conditions. Moreover, the same TF may act as an activator or repressor in distinct conditions. In turn, the activity of regulators themselves may be dependent on other TFs, as well as posttranscriptional and posttranslational regulation. These traits greatly contribute to the intricate networks governing gene expression programs.In this chapter, a step-by-step guide of how to use PathoYeastract, one of several interconnecting databases within the YEASTRACT+ portal, to predict gene and genomic regulation in Candida spp. is provided. PathoYeastract contains a set of analysis tools to study regulatory associations in human pathogenic yeasts, enabling: (1) the prediction and ranking of TFs that contribute to the regulation of individual genes; (2) the prediction of the genes regulated by a given TF; and (3) the prediction and ranking of TFs that regulate a genome-wide transcriptional response. These capabilities are illustrated, respectively, with the analysis of: (1) the TF network controlling the C. glabrata QDR2 gene; (2) the regulon controlled by the C. glabrata TF Rpn4; and (3) the regulatory network controlling the C. glabrata transcriptome-wide changes induced upon exposure to the antifungal drug fluconazole. The newest potentialities of this information system are explored, including cross-species network comparison. The results are discussed considering the performed queries and integrated with the current knowledge on the biological data for each case-study.

A Genome-Scale Metabolic Model for the Human Pathogen Candida Parapsilosis and Early Identification of Putative Novel Antifungal Drug Targets.

Candida parapsilosis is an emerging human pathogen whose incidence is rising worldwide, while an increasing number of clinical isolates display resistance to first-line antifungals, demanding alternative therapeutics. Genome-Scale Metabolic Models (GSMMs) have emerged as a powerful in silico tool for understanding pathogenesis due to their systems view of metabolism, but also to their drug target predictive capacity. This study presents the construction of the first validated GSMM for C. parapsilosis-iDC1003-comprising 1003 genes, 1804 reactions, and 1278 metabolites across four compartments and an intercompartment. In silico growth parameters, as well as predicted utilisation of several metabolites as sole carbon or nitrogen sources, were experimentally validated. Finally, iDC1003 was exploited as a platform for predicting 147 essential enzymes in mimicked host conditions, in which 56 are also predicted to be essential in C. albicans and C. glabrata. These promising drug targets include, besides those already used as targets for clinical antifungals, several others that seem to be entirely new and worthy of further scrutiny. The obtained results strengthen the notion that GSMMs are promising platforms for drug target discovery and guide the design of novel antifungal therapies.

Characterization of the Candida glabrata Transcription Factor CgMar1: Role in Azole Susceptibility.

The prevalence of antifungal resistance in Candida glabrata, especially against azole drugs, results in difficult-to-treat and potentially life-threatening infections. Understanding the molecular basis of azole resistance in C. glabrata is crucial to designing more suitable therapeutic strategies. In this study, the role of the transcription factor encoded by ORF CAGL0B03421g, here denominated as CgMar1 (Multiple Azole Resistance 1), in azole susceptibility was explored. Using RNA-sequencing, CgMar1 was found to regulate 337 genes under fluconazole stress, including several related to lipid biosynthesis pathways. In this context, CgMar1 and its target CgRSB1, encoding a predicted sphingoid long-chain base efflux transporter, were found to contribute to plasma membrane sphingolipid incorporation and membrane permeability, decreasing fluconazole accumulation. CgMar1 was found to associate with the promoter of CgRSB1, which contains two instances of the CCCCTCC consensus, found to be required for CgRSB1 activation during fluconazole stress. Altogether, a regulatory pathway modulating azole susceptibility in C. glabrata is proposed, resulting from what appears to be a neofunctionalization of a Hap1-like transcription factor.

Marine Sponge and Octocoral-Associated Bacteria Show Versatile Secondary Metabolite Biosynthesis Potential and Antimicrobial Activities against Human Pathogens.

Marine microbiomes are prolific sources of bioactive natural products of potential pharmaceutical value. This study inspected two culture collections comprising 919 host-associated marine bacteria belonging to 55 genera and several thus-far unclassified lineages to identify isolates with potentially rich secondary metabolism and antimicrobial activities. Seventy representative isolates had their genomes mined for secondary metabolite biosynthetic gene clusters (SM-BGCs) and were screened for antimicrobial activities against four pathogenic bacteria and five pathogenic Candida strains. In total, 466 SM-BGCs were identified, with antimicrobial peptide- and polyketide synthase-related SM-BGCs being frequently detected. Only 38 SM-BGCs had similarities greater than 70% to SM-BGCs encoding known compounds, highlighting the potential biosynthetic novelty encoded by these genomes. Cross-streak assays showed that 33 of the 70 genome-sequenced isolates were active against at least one Candida species, while 44 isolates showed activity against at least one bacterial pathogen. Taxon-specific differences in antimicrobial activity among isolates suggested distinct molecules involved in antagonism against bacterial versus Candida pathogens. The here reported culture collections and genome-sequenced isolates constitute a valuable resource of understudied marine bacteria displaying antimicrobial activities and potential for the biosynthesis of novel secondary metabolites, holding promise for a future sustainable production of marine drug leads.

From the first touch to biofilm establishment by the human pathogen Candida glabrata: a genome-wide to nanoscale view.

Candida glabrata is an opportunistic pathogen that adheres to human epithelial mucosa and forms biofilm to cause persistent infections. In this work, Single-cell Force Spectroscopy (SCFS) was used to glimpse at the adhesive properties of C. glabrata as it interacts with clinically relevant surfaces, the first step towards biofilm formation. Following a genetic screening, RNA-sequencing revealed that half of the entire transcriptome of C. glabrata is remodeled upon biofilm formation, around 40% of which under the control of the transcription factors CgEfg1 and CgTec1. Using SCFS, it was possible to observe that CgEfg1, but not CgTec1, is necessary for the initial interaction of C. glabrata cells with both abiotic surfaces and epithelial cells, while both transcription factors orchestrate biofilm maturation. Overall, this study characterizes the network of transcription factors controlling massive transcriptional remodelling occurring from the initial cell-surface interaction to mature biofilm formation.

A new regulator in the crossroads of oxidative stress resistance and virulence in Candida glabrata: The transcription factor CgTog1.

Candida glabrata is a prominent pathogenic yeast which exhibits a unique ability to survive the harsh environment of host immune cells. In this study, we describe the role of the transcription factor encoded by the gene CAGL0F09229g, here named CgTog1 after its Saccharomyces cerevisiae ortholog, as a new determinant of C. glabrata virulence. Interestingly, Tog1 is absent in the other clinically relevant Candida species (C. albicans, C. parapsilosis, C. tropicalis, C. auris), being exclusive to C. glabrata. CgTog1 was found to be required for oxidative stress resistance and for the modulation of reactive oxygen species inside C. glabrata cells. Also, CgTog1 was observed to be a nuclear protein, whose activity up-regulates the expression of 147 genes and represses 112 genes in C. glabrata cells exposed to H2O2, as revealed through RNA-seq-based transcriptomics analysis. Given the importance of oxidative stress response in the resistance to host immune cells, the effect of CgTOG1 expression in yeast survival upon phagocytosis by Galleria mellonella hemocytes was evaluated, leading to the identification of CgTog1 as a determinant of yeast survival upon phagocytosis. Interestingly, CgTog1 targets include many whose expression changes in C. glabrata cells after engulfment by macrophages, including those involved in reprogrammed carbon metabolism, glyoxylate cycle and fatty acid degradation. In summary, CgTog1 is a new and specific regulator of virulence in C. glabrata, contributing to oxidative stress resistance and survival upon phagocytosis by host immune cells.

Genome-Scale Metabolic Model of the Human Pathogen Candida albicans: A Promising Platform for Drug Target Prediction.

Candida albicans is one of the most impactful fungal pathogens and the most common cause of invasive candidiasis, which is associated with very high mortality rates. With the rise in the frequency of multidrug-resistant clinical isolates, the identification of new drug targets and new drugs is crucial in overcoming the increase in therapeutic failure. In this study, the first validated genome-scale metabolic model for Candida albicans, iRV781, is presented. The model consists of 1221 reactions, 926 metabolites, 781 genes, and four compartments. This model was reconstructed using the open-source software tool merlin 4.0.2. It is provided in the well-established systems biology markup language (SBML) format, thus, being usable in most metabolic engineering platforms, such as OptFlux or COBRA. The model was validated, proving accurate when predicting the capability of utilizing different carbon and nitrogen sources when compared to experimental data. Finally, this genome-scale metabolic reconstruction was tested as a platform for the identification of drug targets, through the comparison between known drug targets and the prediction of gene essentiality in conditions mimicking the human host. Altogether, this model provides a promising platform for global elucidation of the metabolic potential of C. albicans, possibly guiding the identification of new drug targets to tackle human candidiasis.

Candida glabrata Transcription Factor Rpn4 Mediates Fluconazole Resistance through Regulation of Ergosterol Biosynthesis and Plasma Membrane Permeability.

The ability to acquire azole resistance is an emblematic trait of the fungal pathogen Candida glabrata Understanding the molecular basis of azole resistance in this pathogen is crucial for designing more suitable therapeutic strategies. This study shows that the C. glabrata transcription factor (TF) CgRpn4 is a determinant of azole drug resistance. RNA sequencing during fluconazole exposure revealed that CgRpn4 regulates the expression of 212 genes, activating 80 genes and repressing, likely in an indirect fashion, 132 genes. Targets comprise several proteasome and ergosterol biosynthesis genes, including ERG1, ERG2, ERG3, and ERG11 The localization of CgRpn4 to the nucleus increases upon fluconazole stress. Consistent with a role in ergosterol and plasma membrane homeostasis, CgRpn4 is required for the maintenance of ergosterol levels upon fluconazole stress, which is associated with a role in the upkeep of cell permeability and decreased intracellular fluconazole accumulation. We provide evidence that CgRpn4 directly regulates ERG11 expression through the TTGCAAA binding motif, reinforcing the relevance of this regulatory network in azole resistance. In summary, CgRpn4 is a new regulator of the ergosterol biosynthesis pathway in C. glabrata, contributing to plasma membrane homeostasis and, thus, decreasing azole drug accumulation.

YEASTRACT+: a portal for cross-species comparative genomics of transcription regulation in yeasts.

The YEASTRACT+ information system (http://YEASTRACT-PLUS.org/) is a wide-scope tool for the analysis and prediction of transcription regulatory associations at the gene and genomic levels in yeasts of biotechnological or human health relevance. YEASTRACT+ is a new portal that integrates the previously existing YEASTRACT (http://www.yeastract.com/) and PathoYeastract (http://pathoyeastract.org/) databases and introduces the NCYeastract (Non-Conventional Yeastract) database (http://ncyeastract.org/), focused on the so-called non-conventional yeasts. The information in the YEASTRACT database, focused on Saccharomyces cerevisiae, was updated. PathoYeastract was extended to include two additional pathogenic yeast species: Candida parapsilosis and Candida tropicalis. Furthermore, the NCYeastract database was created, including five biotechnologically relevant yeast species: Zygosaccharomyces baillii, Kluyveromyces lactis, Kluyveromyces marxianus, Yarrowia lipolytica and Komagataella phaffii. The YEASTRACT+ portal gathers 289 706 unique documented regulatory associations between transcription factors (TF) and target genes and 420 DNA binding sites, considering 247 TFs from 10 yeast species. YEASTRACT+ continues to make available tools for the prediction of the TFs involved in the regulation of gene/genomic expression. In this release, these tools were upgraded to enable predictions based on orthologous regulatory associations described for other yeast species, including two new tools for cross-species transcription regulation comparison, based on multi-species promoter and TF regulatory network analyses.

Divergent Approaches to Virulence in C. albicans and C. glabrata: Two Sides of the Same Coin.

Candida albicans and Candida glabrata are the two most prevalent etiologic agents of candidiasis worldwide. Although both are recognized as pathogenic, their choice of virulence traits is highly divergent. Indeed, it appears that these different approaches to fungal virulence may be equally successful in causing human candidiasis. In this review, the virulence mechanisms employed by C. albicans and C. glabrata are analyzed, with emphasis on the differences between the two systems. Pathogenesis features considered in this paper include dimorphic growth, secreted enzymes and signaling molecules, and stress resistance mechanisms. The consequences of these traits in tissue invasion, biofilm formation, immune system evasion, and macrophage escape, in a species dependent manner, are discussed. This review highlights the observation that C. albicans and C. glabrata follow different paths leading to a similar outcome. It also highlights the lack of knowledge on some of the specific mechanisms underlying C. glabrata pathogenesis, which deserve future scrutiny.

Microevolution of the pathogenic yeasts Candida albicans and Candida glabrata during antifungal therapy and host infection.

Infections by the pathogenic yeasts Candida albicans and Candida glabrata are among the most common fungal diseases. The success of these species as human pathogens is contingent on their ability to resist antifungal therapy and thrive within the human host. C. glabrata is especially resilient to azole antifungal treatment, while C. albicans is best known for its wide array of virulence features. The core mechanisms that underlie antifungal resistance and virulence in these pathogens has been continuously addressed, but the investigation on how such mechanisms evolve according to each environment is scarcer. This review aims to explore current knowledge on micro-evolution experiments to several treatment and host-associated conditions in C. albicans and C. glabrata. The analysis of adaptation strategies that evolve over time will allow to better understand the mechanisms by which Candida species are able to achieve stable phenotypes in real-life scenarios, which are the ones that should constitute the most interesting drug targets.