Detection and identification of Escherichia coli and Staphylococcus aureus by Raman spectroscopy

Abstract

Food-borne infection is one of the main reasons affecting public health problem worldwide. Therefore, food safety is highly concerned for the food production system and the rapid-testing process is still required in order to prevent contamination before commercially distributed to consumers. Bacterial detection process is becoming one of the most critical steps in the food production chain. Raman spectroscopy is considered as an alternative technique to rapidly detect and identify the microorganism. In this study, Raman spectroscopy was applied to detect and identify the food-borne pathogens, including Gram-positive and Gram-negative bacteria. The multivariate statistical analysis of principal component analysis (PCA) was used to distinguish these microorganisms based on their Raman spectroscopic fingerprints. Our study demonstrated that the physiological state of microorganism species had an influence on the identification sensitivity. In addition, there were significant differences between Raman spectra of Gram-negative and Gram-positive bacteria. The resultant plots showed that the bacterial spectra displayed degree of discrimination and accuracy identification in calculating accounted for 73.39% of total variance of the first and second principal components (PC-1 and PC-2) of the analyzed data sets. In conclusion, the study suggested that Raman spectroscopy could be utilized for food quality control with reliable and rapid identification.