Hyperspectral Microscope Imaging Methods to Classify Gram-Positive and Gram-Negative Foodborne Pathogenic Bacteria

Abstract

<abstract><title><italic>Abstract.</italic></title> An acousto-optic tunable filter (AOTF)-based hyperspectral microscope imaging (HMI) method has potential for rapid identification of foodborne pathogenic bacteria from micro-colonies with a cell level. In this study, we successfully developed a method to acquire quality hyperspectral microscopic images from various gram-negative and gram-positive bacteria live cells. Among the contiguous spectral images from the visible/NIR region between 450 and 800 nm, the scattering intensity of spectral images was distinct at mostly visible wavelengths. Specifically, the scattering peak intensity was distinct at 458, 498, 522, 546, 574, 590, 646, 670, and 690 nm for Staphylococcus. Similarly, distinct peak spectra were observed at 462, 498, 522, 546, 574, 598, 642, 670, and 690 nm for Salmonella. For both cases, the scattering intensity of outer cell membranes was brighter than that of inner membranes except at 546 nm, which was possibly caused by excitation of the metal-halide lighting source. The scattering intensity from a single cell varied with the wavelength as well as the type of bacteria. The overall variability of intensity was 31.2% for gram-negative (Salmonella) and 42.7% for gram-positive (Staphylococcus) bacteria. With scattering intensity data from five serotypes of Salmonella (Kentucky, Enteritidis, Typhimurium, Infantis, and Heidelberg) and five species of Staphylococcus (aureus, haemolyticus, hyicus, simulans, and sciuri) bacterial cells, a classification accuracy of 99.9% with a kappa coefficient of 0.9998 was obtained from the support vector machine (SVM) classification algorithm.