Chromatographic analysis of peptidoglycan samples with the aid of a chemometric technique: introducing a novel analytical procedure to classify bacterial cell wall collection

Abstract

The technical development of liquid chromatography has provided the necessary sensitivity to characterise peptidoglycan samples. However, the analysis of large numbers of complex chromatographic data sets without the aid of a proper chemometric technique is a laborious task, carrying a high risk of losing important biochemical information. The present work describes the development of a simple analytical procedure using self-organising map (SOM) analysis to analyse the large number of complex chromatographic data sets from bacterial peptidoglycan samples. SOM analysis essentially maps the samples to a hexagonal sheet based on their compositional similarity, and thus provides an approach to classify the bacterial cell wall collection in an unsupervised manner. The utility of the proposed approach was successfully validated by analysing peptidoglycan samples belonging to the Alphaproteobacterium class. The classification results achieved with SOM analysis were found to correlate well with their relative similarity in peptidoglycan compositions. In summary, the SOM analysis-based analytical procedure is shown to be useful towards automatising the analyses of chromatographic data sets of peptidoglycan samples from bacterial collections.