International journal of molecular sciences · 2022
Raman Metabolomics of Candida auris Clades: Profiling and Barcode Identification.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Pezzotti Giuseppe, Kobara Miyuki, Nakaya Tamaki, Imamura Hayata, Fujii Tomoya, Miyamoto Nao, Adachi Tetsuya, Yamamoto Toshiro, Kanamura Narisato, Ohgitani Eriko, Marin Elia, Zhu Wenliang, Kawai Toshihisa, Mazda Osam, Nakata Tetsuo, Makimura Koichi
Аннотация
This study targets on-site/real-time taxonomic identification and metabolic profiling of seven different Candida auris clades/subclades by means of Raman spectroscopy and imaging. Representative Raman spectra from different Candida auris samples were systematically deconvoluted by means of a customized machine-learning algorithm linked to a Raman database in order to decode structural differences at the molecular scale. Raman analyses of metabolites revealed clear differences in cell walls and membrane structure among clades/subclades. Such differences are key in maintaining the integrity and physical strength of the cell walls in the dynamic response to external stress and drugs. It was found that Candida cells use the glucan structure of the extracellular matrix, the degree of α-chitin crystallinity, and the concentration of hydrogen bonds between its antiparallel chains to tailor cell walls' flexibility. Besides being an effective ploy in survivorship by providing stiff shields in the α-1,3-glucan polymorph, the α-1,3-glycosidic linkages are also water-insoluble, thus forming a rigid and hydrophobic scaffold surrounded by a matrix of pliable and hydrated β-glucans. Raman analysis revealed a variety of strategies by different clades to balance stiffness, hydrophobicity, and impermeability in their cell walls. The selected strategies lead to differences in resistance toward specific environmental stresses of cationic/osmotic, oxidative, and nitrosative origins. A statistical validation based on principal component analysis was found only partially capable of distinguishing among Raman spectra of clades and subclades. Raman barcoding based on an algorithm converting spectrally deconvoluted Raman sub-bands into barcodes allowed for circumventing any speciation deficiency. Empowered by barcoding bioinformatics, Raman analyses, which are fast and require no sample preparation, allow on-site speciation and real-time selection of appropriate treatments.