Identifying Candida albicans Gene Networks Involved in Pathogenicity

Acknowledgments This is a short text to acknowledge the contributions of specific colleagues, institutions, or agencies that aided the efforts of the authors. Funding RA was generously supported by a Wellcome Trust Institutional Strategic Support Award [WT105618MA], a Microbiology Research Visit Grant [RVG16/18], and a EPSRC/BBSRC Innovation Fellowship [EP/S001352/1]. AB was supported by a programme grant from the UK Medical Research Council [MR/M026663/1] and by the Medical Research Council Centre for Medical Mycology at the University of Aberdeen [MR/N006364/1]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Sfl1 is required for Candida albicans biofilm formation under acidic conditions

Candida albicans is a common Candida species, responsible for infections in various anatomical sites under different environmental conditions, aggravated in the presence of its biofilms. As such, this study aimed to reveal the regulation of C. albicans biofilms under acidic conditions by the transcription factor Sfl1, whose role on biofilm formation is unclear. For that, microbiologic and transcriptomic analyses were performed with the knock-out mutant C. albicans sfl1Δ/sfl1Δ and its parental strain SN76, grown in planktonic and biofilm lifestyles at pH 4 (vaginal pH). The results revealed that despite being a filamentation repressor Sf1 is required for maximal biofilm formation under acidic conditions. Additionally, Sfl1 was found to induce 275 and 126 genes in biofilm and planktonic cells, respectively, with an overlap of 19 genes. The functional distribution of Sfl1 targets was similar in planktonic and biofilm modes but an enrichment of carbohydrate metabolism function was found in biofilm cells, including some genes encoding proteins involved in the biofilm matrix production. Furthermore, this study shows that the regulatory network of Sfl1 in acidic biofilms is complex and include the positive and negative regulation of transcription factors involved in adhesion and biofilm formation, such as AHR1, BRG1, TYE7, TEC1, WOR1, and various of their targets. Overall, this study shows that Sfl1 is a relevant regulator of C. albicans biofilm formation in acidic environments and contributes to a better understanding of C. albicans virulence under acidic conditions.publishe

Caracterização genética de isolados de Candida albicans provenientes de amostras clínicas distintas e do ambiente clínico

Candida albicans is a commensal microorganism of the human normal microbiota, capable of turning pathogenic, and one of the leading causes of human fungal infections with mortality rates as high as 50%. Based on this problem, it is imperative to routinely characterize this pathogen, not only phenotypically but also genotypically, to identify the genomic traits responsible for disease, drug resistance, adaptability to ecological niches, and unravel the genetic diversity among distinct isolates. As so, in this study, a collection of 76 C. albicans strains collected from blood, vaginal and oral samples, and samples from medical devices was characterized by whole genome sequencing and bioinformatics analysis. Their genome sequence was explored to discriminate and epidemiologically contextualize strains globally, identify genes with single nucleotide polymorphisms (SNPs) and contribute to the knowledge on the C. albicans variome. The isolates genome analysis showed that one of the isolates had been misidentified as C. albicans, being C. glabrata. A higher number of SNPs than usual was identified, possibly due to the high number of homozygous SNPs. Genes with SNPs common to all isolates, with SNPs exclusive of isolates from each sample type, and with SNPs common to all isolates of each origin were identified. Often, the frequency of genes with missense SNPs involved in molecular functions and biological processes was significatively higher when compared to the reference strain frequency in those gene ontology sets.Candida albicans é um microrganismo comensal que pertence à microbiota normal humana, capaz de se tornar patogénico, e é uma das principais causas de infeções fúngicas em humanos, com taxas de mortalidade até 50%. Com base neste problema, é imperativo caracterizar este patógeno rotineiramente, não só fenotipicamente, mas também genotipicamente, identificar características genómicas responsáveis pela doença, resistência a fármacos, adaptabilidade a nichos ecológicos e desvendar a diversidade genética dos isolados causadores de infeções. Assim, neste estudo, uma coleção de 76 estirpes de C. albicans recolhidas de amostras de sangue, vaginais, orais e de dispositivos médicos foi caracterizada através da sequenciação do genoma total e análises de bioinformática. Explorou-se as sequências genómicas dos isolados para discriminar e contextualizar epidemiologicamente as estirpes, identificar genes com polimorfismos de nucleotídeo único (SNPs) e contribuir para o conhecimento do varioma de C. albicans. A análise do genoma dos isolados mostrou que um dos isolados foi anteriormente mal classificado como C. albicans, sendo C. glabrata. Foi identificado um número de SNPs maior do que o habitual, possivelmente devido ao número elevado de SNPs homozigóticos. Foram identificados genes com SNPs comuns a todos os isolados, com SNPs exclusivos de isolados de cada tipo de amostra, e com SNPs comuns a todos os isolados de cada origem. A frequência de genes com SNPs missense envolvidos em funções moleculares e processos biológicos foi muitas vezes significativamente superior à frequência na estirpe de referência para os mesmos conjuntos de ontologia genética.Mestrado em Microbiologi

Identification of an active RNAi pathway in Candida albicans

RNA interference (RNAi) is a fundamental regulatory pathway with a wide range of functions, including regulation of gene expression and maintenance of genome stability. Although RNAi is widespread in the fungal kingdom, well-known species, such as the model yeast , have lost the RNAi pathway. Until now evidence has been lacking for a fully functional RNAi pathway in , a human fungal pathogen considered critically important by the World Health Organization. Here, we demonstrated that the widely used reference strain (SC5314) contains an inactivating missense mutation in the gene encoding for the central RNAi component Argonaute. In contrast, most other isolates contain a canonical Argonaute protein predicted to be functional and RNAi-active. Indeed, using high-throughput small and long RNA sequencing combined with seamless CRISPR/Cas9-based gene editing, we demonstrate that an active RNAi machinery represses expression of subtelomeric gene families. Thus, an intact and functional RNAi pathway exists in , highlighting the importance of using multiple reference strains when studying this dangerous pathogen

What is new in FungiDB: a web-based bioinformatics platform for omics-scale data analysis for fungal and oomycete species

FungiDB (https://fungidb.org) serves as a valuable online resource that seamlessly integrates genomic and related large-scale data for a wide range of fungal and oomycete species. As an integral part of the VEuPathDB Bioinformatics Resource Center (https://veupathdb.org), FungiDB continually integrates both published and unpublished data addressing various aspects of fungal biology. Established in early 2011, the database has evolved to support 674 datasets. The datasets include over 300 genomes spanning various taxa (e.g. Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, as well as Albuginales, Peronosporales, Pythiales, and Saprolegniales). In addition to genomic assemblies and annotation, over 300 extra datasets encompassing diverse information, such as expression and variation data, are also available. The resource also provides an intuitive web-based interface, facilitating comprehensive approaches to data mining and visualization. Users can test their hypotheses and navigate through omics-scale datasets using a built-in search strategy system. Moreover, FungiDB offers capabilities for private data analysis via the integrated VEuPathDB Galaxy platform. FungiDB also permits genome improvements by capturing expert knowledge through the User Comments system and the Apollo genome annotation editor for structural and functional gene curation. FungiDB facilitates data exploration and analysis and contributes to advancing research efforts by capturing expert knowledge for fungal and oomycete species

Recent trends in molecular diagnostics of yeast infections : from PCR to NGS

The incidence of opportunistic yeast infections in humans has been increasing over recent years. These infections are difficult to treat and diagnose, in part due to the large number and broad diversity of species that can underlie the infection. In addition, resistance to one or several antifungal drugs in infecting strains is increasingly being reported, severely limiting therapeutic options and showcasing the need for rapid detection of the infecting agent and its drug susceptibility profile. Current methods for species and resistance identification lack satisfactory sensitivity and specificity, and often require prior culturing of the infecting agent, which delays diagnosis. Recently developed high-throughput technologies such as next generation sequencing or proteomics are opening completely new avenues for more sensitive, accurate and fast diagnosis of yeast pathogens. These approaches are the focus of intensive research, but translation into the clinics requires overcoming important challenges. In this review, we provide an overview of existing and recently emerged approaches that can be used in the identification of yeast pathogens and their drug resistance profiles. Throughout the text we highlight the advantages and disadvantages of each methodology and discuss the most promising developments in their path from bench to bedside

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project