In the flow of molecular miniaturized fungal diagnosis.

The diagnosis of fungal infections presents several challenges and limitations, stemming from the similarities in symptomatology, diversity of underlying pathogenic species, complexity of fungal biology, and scarcity of rapid, affordable, and point-of-care approaches. In this review, we assess technological advances enabling the conversion of cutting-edge laboratory molecular diagnostic methods to cost-effective microfluidic devices. The most promising strategies toward the design of DNA sequence-based fungal diagnostic systems, capable of capturing and deciphering the highly informative DNA of the pathogen and adapted for resource-limited settings, are discussed, bridging fungal biology, molecular genetics, microfluidics, and biosensors.

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.

In Candida glabrata, ERMES Component GEM1 Controls Mitochondrial Morphology, mtROS, and Drug Efflux Pump Expression, Resulting in Azole Susceptibility.

Mitochondrial dysfunction or morphological abnormalities in human pathogenic fungi are known to contribute to azole resistance; however, the underlying molecular mechanisms are unknown. In this study, we investigated the link between mitochondrial morphology and azole resistance in Candida glabrata, which is the second most common cause of human candidiasis worldwide. The ER-mitochondrial encounter structure (ERMES) complex is thought to play an important role in the mitochondrial dynamics necessary for mitochondria to maintain their function. Of the five components of the ERMES complex, deletion of GEM1 increased azole resistance. Gem1 is a GTPase that regulates the ERMES complex activity. Point mutations in GEM1 GTPase domains were sufficient to confer azole resistance. The cells lacking GEM1 displayed abnormalities in mitochondrial morphology, increased mtROS levels, and increased expression of azole drug efflux pumps encoded by CDR1 and CDR2. Interestingly, treatment with N-acetylcysteine (NAC), an antioxidant, reduced ROS production and the expression of CDR1 in Δgem1 cells. Altogether, the absence of Gem1 activity caused an increase in mitochondrial ROS concentration, leading to Pdr1-dependent upregulation of the drug efflux pump Cdr1, resulting in azole resistance.

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.

Insights into the Antimicrobial Activities and Metabolomes of Aquimarina (Flavobacteriaceae, Bacteroidetes) Species from the Rare Marine Biosphere.

Two novel natural products, the polyketide cuniculene and the peptide antibiotic aquimarin, were recently discovered from the marine bacterial genus Aquimarina. However, the diversity of the secondary metabolite biosynthetic gene clusters (SM-BGCs) in Aquimarina genomes indicates a far greater biosynthetic potential. In this study, nine representative Aquimarina strains were tested for antimicrobial activity against diverse human-pathogenic and marine microorganisms and subjected to metabolomic and genomic profiling. We found an inhibitory activity of most Aquimarina strains against Candida glabrata and marine Vibrio and Alphaproteobacteria species. Aquimarina sp. Aq135 and Aquimarina muelleri crude extracts showed particularly promising antimicrobial activities, amongst others against methicillin-resistant Staphylococcus aureus. The metabolomic and functional genomic profiles of Aquimarina spp. followed similar patterns and were shaped by phylogeny. SM-BGC and metabolomics networks suggest the presence of novel polyketides and peptides, including cyclic depsipeptide-related compounds. Moreover, exploration of the 'Sponge Microbiome Project' dataset revealed that Aquimarina spp. possess low-abundance distributions worldwide across multiple marine biotopes. Our study emphasizes the relevance of this member of the microbial rare biosphere as a promising source of novel natural products. We predict that future metabologenomics studies of Aquimarina species will expand the spectrum of known secondary metabolites and bioactivities from marine ecosystems.

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.

Development of Polythiourethane/ZnO-Based Anti-Fouling Materials and Evaluation of the Adhesion of Staphylococcus aureus and Candida glabrata Using Single-Cell Force Spectroscopy.

The attachment of bacteria and other microbes to natural and artificial surfaces leads to the development of biofilms, which can further cause nosocomial infections. Thus, an important field of research is the development of new materials capable of preventing the initial adhesion of pathogenic microorganisms. In this work, novel polymer/particle composite materials, based on a polythiourethane (PTU) matrix and either spherical (s-ZnO) or tetrapodal (t-ZnO) shaped ZnO fillers, were developed and characterized with respect to their mechanical, chemical and surface properties. To then evaluate their potential as anti-fouling surfaces, the adhesion of two different pathogenic microorganism species, Staphylococcus aureus and Candida glabrata, was studied using atomic force microscopy (AFM). Our results show that the adhesion of both S. aureus and C. glabrata to PTU and PTU/ZnO is decreased compared to a model surface polydimethylsiloxane (PDMS). It was furthermore found that the amount of both s-ZnO and t-ZnO filler had a direct influence on the adhesion of S. aureus, as increasing amounts of ZnO particles resulted in reduced adhesion of the cells. For both microorganisms, material composites with 5 wt.% of t-ZnO particles showed the greatest potential for anti-fouling with significantly decreased adhesion of cells. Altogether, both pathogens exhibit a reduced capacity to adhere to the newly developed nanomaterials used in this study, thus showing their potential for bio-medical applications.

Carrier-Mediated Drug Uptake in Fungal Pathogens.

Candida, Aspergillus, and Cryptococcus species are the most frequent cause of severe human fungal infections. Clinically relevant antifungal drugs are scarce, and their effectiveness are hampered by the ability of fungal cells to develop drug resistance mechanisms. Drug effectiveness and drug resistance in human pathogens is very often affected by their "transportome". Many studies have covered a panoply of drug resistance mechanisms that depend on drug efflux pumps belonging to the ATP-Binding Cassette and Major Facilitator Superfamily. However, the study of drug uptake mechanisms has been, to some extent, overlooked in pathogenic fungi. This review focuses on discussing current knowledge on drug uptake systems in fungal pathogens, highlighting the need for further studies on this topic of great importance. The following subjects are covered: (i) drugs imported by known transporter(s) in pathogenic fungi; and (ii) drugs imported by known transporter(s) in the model yeast Saccharomyces cerevisiae or in human parasites, aimed at the identification of their homologs in pathogenic fungi. Besides its contribution to increase the understanding of drug-pathogen interactions, the practical implications of identifying drug importers in human pathogens are discussed, particularly focusing on drug development strategies.

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.

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.

Genome-Wide Response to Drugs and Stress in the Pathogenic Yeast Candida glabrata.

Candida glabrata is the second most common cause of candidemia worldwide and its prevalence has continuously increased over the last decades. C. glabrata infections are especially worrisome in immunocompromised patients, resulting in serious systemic infections, associated to high mortality rates. Intrinsic resistance to azole antifungals, widely used drugs in the clinical setting, and the ability to efficiently colonize the human host and medical devices, withstanding stress imposed by the immune system, are thought to underlie the emergence of C. glabrata. There is a clear clinical need to understand drug and stress resistance in C. glabrata. The increasing prevalence of multidrug resistant isolates needs to be addressed in order to overcome the decrease of viable therapeutic strategies and find new therapeutic targets. Likewise, the understanding of the mechanisms underlying its impressive ability thrive under oxidative, nitrosative, acidic and metabolic stresses, is crucial to design drugs that target these pathogenesis features. The study of the underlying mechanisms that translate C. glabrata plasticity and its competence to evade the immune system, as well as survive host stresses to establish infection, will benefit from extensive scrutiny. This chapter provides a review on the contribution of genome-wide studies to uncover clinically relevant drug resistance and stress response mechanisms in the human pathogenic yeast C. glabrata.

Candida Biofilms: Threats, Challenges, and Promising Strategies.

Candida species are fungal pathogens known for their ability to cause superficial and systemic infections in the human host. These pathogens are able to persist inside the host due to the development of pathogenicity and multidrug resistance traits, often leading to the failure of therapeutic strategies. One specific feature of Candida species pathogenicity is their ability to form biofilms, which protects them from external factors such as host immune system defenses and antifungal drugs. This review focuses on the current threats and challenges when dealing with biofilms formed by Candida albicans, Candida glabrata, Candida tropicalis, and Candida parapsilosis, highlighting the differences between the four species. Biofilm characteristics depend on the ability of each species to produce extracellular polymeric substances (EPS) and display dimorphic growth, but also on the biofilm substratum, carbon source availability and other factors. Additionally, the transcriptional control over processes like adhesion, biofilm formation, filamentation, and EPS production displays great complexity and diversity within pathogenic yeasts of the Candida genus. These differences not only have implications in the persistence of colonization and infections but also on antifungal resistance typically found in Candida biofilm cells, potentiated by EPS, that functions as a barrier to drug diffusion, and by the overexpression of drug resistance transporters. The ability to interact with different species in in vivo Candida biofilms is also a key factor to consider when dealing with this problem. Despite many challenges, the most promising strategies that are currently available or under development to limit biofilm formation or to eradicate mature biofilms are discussed.

The PathoYeastract database: an information system for the analysis of gene and genomic transcription regulation in pathogenic yeasts.

We present the PATHOgenic YEAst Search for Transcriptional Regulators And Consensus Tracking (PathoYeastract - http://pathoyeastract.org) database, a tool for the analysis and prediction of transcription regulatory associations at the gene and genomic levels in the pathogenic yeasts Candida albicans and C. glabrata Upon data retrieval from hundreds of publications, followed by curation, the database currently includes 28 000 unique documented regulatory associations between transcription factors (TF) and target genes and 107 DNA binding sites, considering 134 TFs in both species. Following the structure used for the YEASTRACT database, PathoYeastract makes available bioinformatics tools that enable the user to exploit the existing information to predict the TFs involved in the regulation of a gene or genome-wide transcriptional response, while ranking those TFs in order of their relative importance. Each search can be filtered based on the selection of specific environmental conditions, experimental evidence or positive/negative regulatory effect. Promoter analysis tools and interactive visualization tools for the representation of TF regulatory networks are also provided. The PathoYeastract database further provides simple tools for the prediction of gene and genomic regulation based on orthologous regulatory associations described for other yeast species, a comparative genomics setup for the study of cross-species evolution of regulatory networks.

New Mechanisms of Flucytosine Resistance in C. glabrata Unveiled by a Chemogenomics Analysis in S. cerevisiae.

5-Flucytosine is currently used as an antifungal drug in combination therapy, but fungal pathogens are rapidly able to develop resistance against this drug, compromising its therapeutic action. The understanding of the underlying resistance mechanisms is crucial to deal with this problem. In this work, the S. cerevisiae deletion mutant collection was screened for increased resistance to flucytosine. Through this chemogenomics analysis, 183 genes were found to confer resistance to this antifungal agent. Consistent with its known effect in DNA, RNA and protein synthesis, the most significant Gene Ontology terms over-represented in the list of 5-flucytosine resistance determinants are related to DNA repair, RNA and protein metabolism. Additional functional classes include carbohydrate and nitrogen-particularly arginine-metabolism, lipid metabolism and cell wall remodeling. Based on the results obtained for S. cerevisiae as a model system, further studies were conducted in the pathogenic yeast Candida glabrata. Arginine supplementation was found to relieve the inhibitory effect exerted by 5-flucytosine in C. glabrata. Lyticase susceptibility was found to increase within the first 30min of 5-flucytosine exposure, suggesting this antifungal drug to act as a cell wall damaging agent. Upon exponential growth resumption in the presence of 5-flucytosine, the cell wall exhibited higher resistance to lyticase, suggesting that cell wall remodeling occurs in response to 5-flucytosine. Additionally, the aquaglyceroporin encoding genes CgFPS1 and CgFPS2, from C. glabrata, were identified as determinants of 5-flucytosine resistance. CgFPS1 and CgFPS2 were found to mediate 5-flucytosine resistance, by decreasing 5-flucytosine accumulation in C. glabrata cells.

The YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation in Saccharomyces cerevisiae.

The YEASTRACT (http://www.yeastract.com) information system is a tool for the analysis and prediction of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in June 2013, this database contains over 200,000 regulatory associations between transcription factors (TFs) and target genes, including 326 DNA binding sites for 113 TFs. All regulatory associations stored in YEASTRACT were revisited and new information was added on the experimental conditions in which those associations take place and on whether the TF is acting on its target genes as activator or repressor. Based on this information, new queries were developed allowing the selection of specific environmental conditions, experimental evidence or positive/negative regulatory effect. This release further offers tools to rank the TFs controlling a gene or genome-wide response by their relative importance, based on (i) the percentage of target genes in the data set; (ii) the enrichment of the TF regulon in the data set when compared with the genome; or (iii) the score computed using the TFRank system, which selects and prioritizes the relevant TFs by walking through the yeast regulatory network. We expect that with the new data and services made available, the system will continue to be instrumental for yeast biologists and systems biology researchers.

Yeast toxicogenomics: genome-wide responses to chemical stresses with impact in environmental health, pharmacology, and biotechnology.

The emerging transdisciplinary field of Toxicogenomics aims to study the cell response to a given toxicant at the genome, transcriptome, proteome, and metabolome levels. This approach is expected to provide earlier and more sensitive biomarkers of toxicological responses and help in the delineation of regulatory risk assessment. The use of model organisms to gather such genomic information, through the exploitation of Omics and Bioinformatics approaches and tools, together with more focused molecular and cellular biology studies are rapidly increasing our understanding and providing an integrative view on how cells interact with their environment. The use of the model eukaryote Saccharomyces cerevisiae in the field of Toxicogenomics is discussed in this review. Despite the limitations intrinsic to the use of such a simple single cell experimental model, S. cerevisiae appears to be very useful as a first screening tool, limiting the use of animal models. Moreover, it is also one of the most interesting systems to obtain a truly global understanding of the toxicological response and resistance mechanisms, being in the frontline of systems biology research and developments. The impact of the knowledge gathered in the yeast model, through the use of Toxicogenomics approaches, is highlighted here by its use in prediction of toxicological outcomes of exposure to pesticides and pharmaceutical drugs, but also by its impact in biotechnology, namely in the development of more robust crops and in the improvement of yeast strains as cell factories.

YEASTRACT: providing a programmatic access to curated transcriptional regulatory associations in Saccharomyces cerevisiae through a web services interface.

The YEAst Search for Transcriptional Regulators And Consensus Tracking (YEASTRACT) information system (http://www.yeastract.com) was developed to support the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in June 2010, this database contains over 48,200 regulatory associations between transcription factors (TFs) and target genes, including 298 specific DNA-binding sites for 110 characterized TFs. All regulatory associations stored in the database were revisited and detailed information on the experimental evidences that sustain those associations was added and classified as direct or indirect evidences. The inclusion of this new data, gathered in response to the requests of YEASTRACT users, allows the user to restrict its queries to subsets of the data based on the existence or not of experimental evidences for the direct action of the TFs in the promoter region of their target genes. Another new feature of this release is the availability of all data through a machine readable web-service interface. Users are no longer restricted to the set of available queries made available through the existing web interface, and can use the web service interface to query, retrieve and exploit the YEASTRACT data using their own implementation of additional functionalities. The YEASTRACT information system is further complemented with several computational tools that facilitate the use of the curated data when answering a number of important biological questions. Since its first release in 2006, YEASTRACT has been extensively used by hundreds of researchers from all over the world. We expect that by making the new data and services available, the system will continue to be instrumental for yeast biologists and systems biology researchers.

Adaptive response and tolerance to weak acids in Saccharomyces cerevisiae: a genome-wide view.

Weak acids are widely used as food preservatives (e.g., acetic, propionic, benzoic, and sorbic acids), herbicides (e.g., 2,4-dichlorophenoxyacetic acid), and as antimalarial (e.g., artesunic and artemisinic acids), anticancer (e.g., artesunic acid), and immunosuppressive (e.g., mycophenolic acid) drugs, among other possible applications. The understanding of the mechanisms underlying the adaptive response and resistance to these weak acids is a prerequisite to develop more effective strategies to control spoilage yeasts, and the emergence of resistant weeds, drug resistant parasites or cancer cells. Furthermore, the identification of toxicity mechanisms and resistance determinants to weak acid-based pharmaceuticals increases current knowledge on their cytotoxic effects and may lead to the identification of new drug targets. This review integrates current knowledge on the mechanisms of toxicity and tolerance to weak acid stress obtained in the model eukaryote Saccharomyces cerevisiae using genome-wide approaches and more detailed gene-by-gene analysis. The major features of the yeast response to weak acids in general, and the more specific responses and resistance mechanisms towards a specific weak acid or a group of weak acids, depending on the chemical nature of the side chain R group (R-COOH), are highlighted. The involvement of several transcriptional regulatory networks in the genomic response to different weak acids is discussed, focusing on the regulatory pathways controlled by the transcription factors Msn2p/Msn4p, War1p, Haa1p, Rim101p, and Pdr1p/Pdr3p, which are known to orchestrate weak acid stress response in yeast. The extrapolation of the knowledge gathered in yeast to other eukaryotes is also attempted.

Yeast adaptation to mancozeb involves the up-regulation of FLR1 under the coordinate control of Yap1, Rpn4, Pdr3, and Yrr1.

FLR1 gene, encoding a multidrug resistance (MDR) transporter of the major facilitator superfamily (MFS) was found to confer resistance to the fungicide mancozeb in Saccharomyces cerevisiae. This agrochemical has been linked to the development of Parkinson disease and cancer. Yeast response to mancozeb was proved to involve the strong activation of FLR1 transcription (20-fold) during the fungicide-induced growth latency. This activation of FLR1 transcription is fully dependent on Yap1p and is reduced (by 50%) in the absence of Rpn4p, Yrr1p or Pdr3p. A model for the coordinate action over FLR1 transcription activation, in response to mancozeb, of these transcription factors that mediate oxidative stress response (Yap1p), proteasome gene expression (Rpn4p), and pleiotropic drug resistance (Pdr3p and Yrr1p), is proposed.

Environmental genomics: mechanistic insights into toxicity of and resistance to the herbicide 2,4-D.

Genomic information and tools are beginning to be used to increase our understanding of how organisms of all types interact with their environment. The study of the expression of all genes, at the genome, transcriptome, proteome and metabolome level, in response to exposure to a toxicant, is known as toxicogenomics. Here, we show how this new field of environmental genomics has enhanced the development of fundamental knowledge on the mechanisms behind the toxicity of and resistance to the herbicide 2,4-dichlorophenoxyacetic acid (2,4-D). Although 2,4-D is one of the most successfully and widely used herbicides, its intensive use has led to the emergence of resistant weeds and might give rise to several toxicological problems when present in concentrations above those recommended. This review summarizes recent mechanistic insights into 2,4-D toxicity and the corresponding adaptive responses based on studies carried out using Saccharomyces cerevisiae and Arabidopsis thaliana as model organisms.