Identification and Localization of Bacteria at Single - Cell Level in Cancer Cell using Raman Spectroscopy Combined with Multivariate Data Analysis
It has been recently observed that Peptostreptococcus anaerobius (P. anaerobius), a gram-positive bacterium, plays a very significant role in promoting colorectal carcinogenesis and tumorigenesis. The detection of bacteria is sophisticated in biological samples, and the detection of micro-organisms to prevent pathogenic infection is at a hype. The identification of biological systems has been challenging, but recently vibrational spectroscopy has been of great potential.
In this study, we investigated the Raman mapped spectral datasets of P. anaerobius in colorectal adenocarcinoma cells (Caco-2) combined with robust Principal component analysis to understand the "fingerprint" components. The multivariate statistical analyses generate false-color images, and the primary principal component gives a reference for cross-validation of the localization of the gram-positive bacteria in Caco-2 cells. The application of multivariate imaging analysis, such as cluster analysis and other image reconstruction models, can help in pattern recognition of bacteria, which can be a rapid approach to accurately understanding micro-organisms. Furthermore, Raman mapping, combined with Multivariate analyses, is an innovative technique. This method of identifying and localizing the potential fingerprint of bacteria can be used as a database for future identification in tracing of pathogenic bacteria in cancer cells.
Keywords: Raman mapping, Gram-positive bacteria, Colorectal Cancer Cell, Principal Component Analysis, Cluster Analysis.
File with abstract
Pooja Manik Badgujar
National Dong Hwa University
File with report