A comparison of multivariate analysis techniques and variable selection strategies in a laser-induced breakdown spectroscopy bacterial classification

Abstract

Laser-induced breakdown spectroscopy has been used to obtain spectral fingerprints from live bacterial specimens from thirteen distinct taxonomic bacterial classes representative of five bacterial genera. By taking sums, ratios, and complex ratios of measured atomic emission line intensities three unique sets of independent variables (models) were constructed to determine which choice of independent variables provided optimal genuslevel classification of unknown specimens utilizing a discriminant function analysis. A model composed of 80 independent variables constructed from simple and complex ratios of the measured emission line intensities was found to provide the greatest sensitivity and specificity. This model was then used in a partial least squares discriminant analysis to compare the performance of this multivariate technique with a discriminant function analysis. The partial least squares discriminant analysis possessed a higher true positive rate, possessed a higher false positive rate, and was more effective at distinguishing *Revised Manuscript Click here to view linked References 2 between highly similar spectra from closely related bacterial genera. This suggests it may be the preferred multivariate technique in future species-level or strain-level classifications.

Application of multivariate statistical techniques in microbial ecology

“…A model of class prediction can also be generated during discriminant analysis. Such model can be used to provide predictions for new (‘unknown’) object based on the values of measured variables in that object (Putnam et al , 2013). Examples of the use of different DFA variants in ecological studies are available in the reports by (Gilbert et al , 2012) and (Koenig et al , 2011).…”

A critical review of recent progress in analytical laser-induced breakdown spectroscopy

“…overall accuracy, robustness, or number of true and false-positive cases) should be described. Systematic studies comparing the performance of several classification methods on the same LIBS datasets are still rare [110][111][112][113], although these studies would be indispensable in assisting the selection of chemometric methods for wide use in LIBS.…”

“…In addition to this, little or no sample preparation is needed. Successful discrimination of pathogenic from non-pathogenic bacteria has been achieved, including some multi-drug-resistant strains of bacteria including Staphylococcus aureus and other strains causing hospital-acquired infections (HAI) [112,132]. Another advantage of LIBSbased identification of pathogens is that bacterial LIBS spectra have been revealed not to change with time as the culture ages, or on abiotic surfaces, or in killed or inactivated specimens [133].…”

Chemometrics in laser‐induced breakdown spectroscopy

“…Discriminant factor analysis is a multivariate statistical technique that serves to establish a model to predict group memberships, and its primary goal is to find the dimensions or directions along which the groups are best separated, and then to find discriminant functions to predict group membership. The 3 models based on sums, ratios, and complex ratios of measured atomic emission‐line intensities were constructed by down‐selected–independent variables, and PLS‐DA was effective at distinguishing between highly similar spectra from closely related bacterial genera . The PLS‐DA was used to investigate the possibility of discriminating healthy and carious tooth tissues based on atomic and ionic emission lines in the LIBS spectra of teeth; it showed excellent discrimination and prediction of unknown tooth tissues .…”