Rapid detection method for identifying and distinguishing Candida auris and its relatives by surface-enhanced Raman spectroscopy / 中华检验医学杂志

ABSTRACT

Objective:To develop an accurate, specific and rapid and non-destructive technique for the identification of Candida auris and its relatives without destroying the cell wall. Methods:The study was conducted in Beijing Institute of Radiation Medicine in 2021. Surface-enhanced Raman spectroscopy (SERS) substrates were prepared by sodium citrate reduction. Through SERS, the collected SERS fingerprint spectra were analyzed by orthogonal partial least-squares-discrimination analysis (OPLS-DA) using SIMCA 14.1 (Umetrics, Sweden). Four strains of Candida auris, 4 strains of Candida heamulonii, 3 strains of Candida pseudohaemulonii and 4 strains of Candida duobushaemulonii were effectively identified and distinguished. Results:Within the 95% confidence interval, the sample analysis results presented an oval. The four Candida species detected in this study could be well separated. R2X(cum)=0.629, R2Y(cum)=0.947, Q2(cum)=0.915. R2X, R2Y and Q2 all>0.5 and closed to 1, suggesting that the model in this study was well established, and had good prediction ability. The results of the 10-fold-cross validation showed that the accuracy of both the model training data and test data are 100%, indicating that the model established in this research had good classification capabilities. Conclusions:This research has developed a new technique that can identify Candida auris and its relatives in a highly accuracy, specific and rapid way without destroying the cell wall. Being cost-effective and easy to operate, this technique has great potential to be applied in clinical fungal testing.