Laszlo Irinyi , Michael Roper , Richard Malik , Wieland Meyer
{"title":"In silico environmental sampling of emerging fungal pathogens via big data analysis","authors":"Laszlo Irinyi , Michael Roper , Richard Malik , Wieland Meyer","doi":"10.1016/j.funeco.2022.101212","DOIUrl":null,"url":null,"abstract":"<div><p>Yeast species in the <em>Candida haemulonii</em> complex (<em>C. haemulonii</em>, <em>C. haemulonii</em> var. <em>vulnera</em>, <em>C. duobushaemulonii</em>, <em>C. pseudohaemulonii</em>, and <em>C. vulturna</em>) and closely related species (<em>C. auris</em>, <em>C. heveicola</em>, and <em>C. ruelliae</em>) are of significant public health concern worldwide. Little is known about their natural habitat. To understand the worldwide emergence of new fungal pathogens, it is important to identify key environmental habitats. Showing the effectiveness of the primary fungal DNA barcode and leveraging big data archived in the Sequence Read Archive (SRA) database enabled the identification of novel reservoirs over a wide range of geographical areas for those yeasts. We identified 1209 datasets corresponding to species in the <em>C. haemulonii</em> complex and three closely related species. Our results imply that climate change is not the main driver for the emergence of pathogenic multidrug-resistant yeast species. This approach opens the door for further big data analysis using the accessible resources of such databases.</p></div>","PeriodicalId":1,"journal":{"name":"Accounts of Chemical Research","volume":null,"pages":null},"PeriodicalIF":16.4000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Accounts of Chemical Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1754504822000733","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 4
Abstract
Yeast species in the Candida haemulonii complex (C. haemulonii, C. haemulonii var. vulnera, C. duobushaemulonii, C. pseudohaemulonii, and C. vulturna) and closely related species (C. auris, C. heveicola, and C. ruelliae) are of significant public health concern worldwide. Little is known about their natural habitat. To understand the worldwide emergence of new fungal pathogens, it is important to identify key environmental habitats. Showing the effectiveness of the primary fungal DNA barcode and leveraging big data archived in the Sequence Read Archive (SRA) database enabled the identification of novel reservoirs over a wide range of geographical areas for those yeasts. We identified 1209 datasets corresponding to species in the C. haemulonii complex and three closely related species. Our results imply that climate change is not the main driver for the emergence of pathogenic multidrug-resistant yeast species. This approach opens the door for further big data analysis using the accessible resources of such databases.
期刊介绍:
Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance.
Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.