Classification of Chemical and Biological Warfare Agent Simulants by Surface-Enhanced Raman Spectroscopy and Multivariate Statistical Techniques

Abstract

Initial results demonstrating the ability to classify surface-enhanced Raman (SERS) spectra of chemical and biological warfare agent simulants are presented. The spectra of two endospores (B. subtilis and B. atrophaeus), two chemical agent simulants (dimethyl methylphosphonate (DMMP) and diethyl methylphosphonate (DEMP)), and two toxin simulants (ovalbumin and horseradish peroxidase) were studied on multiple substrates fabricated from colloidal gold adsorbed onto a silanized quartz surface. The use of principal component analysis (PCA) and hierarchical clustering were used to evaluate the efficacy of identifying potential threat agents from their spectra collected on a single substrate. The use of partial least squares-discriminate analysis (PLS-DA) and soft independent modeling of class analogies (SIMCA) on a compilation of data from separate substrates, fabricated under identical conditions, demonstrates both the feasibility and the limitations of this technique for the identification of known but previously unclassified spectra.

Application of Mid-infrared and Raman Spectroscopy to the Study of Bacteria

“…Detection limits can be improved by an order of magnitude if cells can be collected on a matrix such as a membrane filter under controlled cultivation conditions and in a relatively pure state, particularly if the cells can be partially dehydrated prior to analysis (Burgula et al 2007). It is critical to concentrate bacteria and remove as much water from the sample as practical (Pearman and Fountain 2006) for qualitative as well as quantitative analysis. Recent developments in infrared spectroscopic characterization of bacteria have attempted to overcome some of these disadvantages by: (1) applying surface-enhanced infrared absorbance techniques to amplify the intensity of spectra derived from bacteria (Holman et al 1998); and (2) using magnetic nanoparticles to bind to targeted microorganisms, isolate, and concentrate them, and then distinguish spectral features in the infrared region (Ravindranath et al 2009).…”

Rapid and Sensitive Detection of Rotavirus Molecular Signatures Using Surface Enhanced Raman Spectroscopy

“…The enhancement effect is system dependent, e.g., substrate and analyte, with typical enhancements of 10 4 to 10 14 with respect to normal Raman intensities. Importantly, SERS retains all of the benefits of normal Raman spectroscopy while providing a markedly improved sensitivity, and as a result, SERS has advanced as the spectroscopic tool of choice for whole-organism fingerprinting [8], [9], [10], [11], [23], [24], [25], [26], [27], [28], [29], [30].…”

Functionalized paper SERS (P-SERS) substrates for selective targeting of analytes in complex samples

“…Alternatively, multivariate statistical techniques such as principal component analysis (PCA), partial least squares regression (PLS), independent component analysis (ICA), and hierarchical cluster analysis (HCA) can be helpful for complex spectra. [17][18][19] These methods have proven to be effective in controlled conditions where the components within the sample are well known, but it can be difficult to achieve good results for real-world samples, where interfering components are not necessarily known beforehand.…”