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.“Fundação para a Ciência e a Tecnologia” (FCT) [Contract PTDC /BII-BIO/28216/2017] and by Programa Operacional Regional de Lisboa 2020 [LISBOA-01-0145-FEDER-022231], through the Biodata.pt Research Infrastructure. Funding received by iBB-Institute for Bioengineering and Biosciences from FCT [Contract UIDB/04565/2020]info:eu-repo/semantics/publishedVersio

Genome-scale metabolic model of the human pathogen C. albicans: aiming the identification of promising new drug targets

Candida albicans is the most common cause of invasive candidiasis, partly due to its ability to acquire drug resistance. With the rise in frequency of multidrug resistant clinical isolates, therapeutic options are running low. The identification of new drug targets and new drugs is crucial to overcome the increase in therapeutic failure. Currently, genome-scale metabolic models can be considered established tools for drug targeting. In this study, we propose the first genome-scale metabolic model for Candida albicans, iRV1930. The model consists of 1556 reactions, 1344 metabolites, 1053 genes, and 5 compartments. This model, currently under validation, proved accurate when predicting the capability of utilizing different carbon and nitrogen sources when compared to experimental data. This model was reconstructed using open source software tool, merlin 3.9.6, and is provided in the well-established systems biology markup language (SBML) format, thus, it can be used in most metabolic engineering platforms, such as OptFlux or Cobra. Altogether, this model provides a promising platform for global elucidation of the metabolism of C. albicans, currently being used to guide the identification of new drug targets to tackle human candidiasis.info:eu-repo/semantics/publishedVersio

Host-Pathogen Interactions Mediated by MDR Transporters in Fungi: As Pleiotropic as it Gets!

Fungal infections caused by Candida, Aspergillus, and Cryptococcus species are an increasing problem worldwide, associated with very high mortality rates. The successful prevalence of these human pathogens is due to their ability to thrive in stressful host niche colonization sites, to tolerate host immune system-induced stress, and to resist antifungal drugs. This review focuses on the key role played by multidrug resistance (MDR) transporters, belonging to the ATP-binding cassette (ABC), and the major facilitator superfamilies (MFS), in mediating fungal resistance to pathogenesis-related stresses. These clearly include the extrusion of antifungal drugs, with C. albicans CDR1 and MDR1 genes, and corresponding homologs in other fungal pathogens, playing a key role in this phenomenon. More recently, however, clues on the transcriptional regulation and physiological roles of MDR transporters, including the transport of lipids, ions, and small metabolites, have emerged, linking these transporters to important pathogenesis features, such as resistance to host niche environments, biofilm formation, immune system evasion, and virulence. The wider view of the activity of MDR transporters provided in this review highlights their relevance beyond drug resistance and the need to develop therapeutic strategies that successfully face the challenges posed by the pleiotropic nature of these transporters

Divergent Approaches to Virulence in <i>C. albicans</i> and <i>C. glabrata</i>: 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

Characterization of the <i>Candida glabrata</i> 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

Role of CgTpo4 in Polyamine and Antimicrobial Peptide Resistance: Determining Virulence in <i>Candida glabrata</i>

Candida glabrata is an emerging fungal pathogen whose success depends on its ability to resist antifungal drugs but also to thrive against host defenses. In this study, the predicted multidrug transporter CgTpo4 (encoded by ORF CAGL0L10912g) is described as a new determinant of virulence in C. glabrata, using the infection model Galleria mellonella. The CgTPO4 gene was found to be required for the C. glabrata ability to kill G. mellonella. The transporter encoded by this gene is also necessary for antimicrobial peptide (AMP) resistance, specifically against histatin-5. Interestingly, G. mellonella’s AMP expression was found to be strongly activated in response to C. glabrata infection, suggesting AMPs are a key antifungal defense. CgTpo4 was also found to be a plasma membrane exporter of polyamines, especially spermidine, suggesting that CgTpo4 is able to export polyamines and AMPs, thus conferring resistance to both stress agents. Altogether, this study presents the polyamine exporter CgTpo4 as a determinant of C. glabrata virulence, which acts by protecting the yeast cells from the overexpression of AMPs, deployed as a host defense mechanism

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

International audienceAbstract 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