Unveiling new features of the human pathogen through the reconstruction and exploitation of a dedicated genome-scale metabolic model.

is notorious for causing severe pulmonary and central nervous system infections, particularly in immunocompromised patients. High mortality rates, associated with its tropism and adaptation to the brain microenvironment and its drug resistance profile, make this pathogen a public health threat and a World Health Organization (WHO) priority. This study presents the first reconstructed genome-scale metabolic model (GSMM), iRV890, for , which comprises 890 genes, 2598 reactions, and 2047 metabolites across four compartments.

Reconstruction and exploitation of a dedicated Genome-Scale Metabolic Model of the human pathogen .

is notorious for causing severe pulmonary and central nervous system infections, particularly in immunocompromised patients. High mortality rates, associated with its tropism and adaptation to the brain microenvironment and its drug resistance profile, makes this pathogen a public health threat and a World Health Organization (WHO) priority. In this study, we reconstructed GSMM iRV890 for , providing a promising platform for the comprehensive understanding of the unique metabolic features of , and subsequently shedding light on its complex tropism for the brain microenvironment and potentially informing the discovery of new drug targets.

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.

In , ERMES Component 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 , 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.

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.

Insights into the Antimicrobial Activities and Metabolomes of (, ) 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.

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

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 -iDC1003-comprising 1003 genes, 1804 reactions, and 1278 metabolites across four compartments and an intercompartment.

Development of Polythiourethane/ZnO-Based Anti-Fouling Materials and Evaluation of the Adhesion of and 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.

Carrier-Mediated Drug Uptake in Fungal Pathogens.

, , and 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".

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

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 , iRV781, is presented.

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.

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

Infections by the pathogenic yeasts and 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. is especially resilient to azole antifungal treatment, while is best known for its wide array of virulence features.

Biofilms: Threats, Challenges, and Promising Strategies.

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 species pathogenicity is their ability to form biofilms, which protects them from external factors such as host immune system defenses and antifungal drugs.

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.

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.

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.

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.

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.

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.

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.

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).

Early transcriptional response of Saccharomyces cerevisiae to stress imposed by the herbicide 2,4-dichlorophenoxyacetic acid.

The global gene transcription pattern of the eukaryotic experimental model Saccharomyces cerevisiae in response to sudden aggression with the widely used herbicide 2,4-dichlorophenoxyacetic acid (2,4-D) was analysed. Under acute stress, 14% of the yeast transcripts suffered a greater than twofold change. The yeastract database was used to predict the transcription factors mediating the response registered in this microarray analysis.

Saccharomyces cerevisiae resistance to chlorinated phenoxyacetic acid herbicides involves Pdr1p-mediated transcriptional activation of TPO1 and PDR5 genes.

The transcription regulator Pdr1p is a determinant of Saccharomyces cerevisiae resistance to 2-methyl-4-chlorophenoxyacetic acid (MCPA) and 2,4-dichlorophenoxyacetic acid (2,4-D). The Pdr1p-regulated genes, TPO1 and PDR5, encoding putative multidrug transporters belonging to the major facilitator superfamily (MFS) and to the ATP-binding cassette (ABC) superfamily, respectively, are required for yeast resistance to sudden exposure to these herbicides. A rapid and transient activation of TPO1 (sixfold) and PDR5 (twofold) transcription takes place during the adaptation period preceding cell division under MCPA or 2,4-D moderate stress.