Journal Highlight: Exploring bacterial phenotypic diversity using factorial design and FTIR multivariate fingerprinting

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  • Published: Sep 15, 2014
  • Author: spectroscopyNOW
  • Channels: Infrared Spectroscopy / Chemometrics & Informatics
thumbnail image: Journal Highlight: Exploring bacterial phenotypic diversity using factorial design and FTIR multivariate fingerprinting
Bacterial phenotypic diversity of cultures of Staphylococcus aureus grown under variable sets of environmental conditions was characterized by FTIR spectroscopy, using different spectral preprocessing methods in combination with scaling methods in principal component analysis.


Exploring bacterial phenotypic diversity using factorial design and FTIR multivariate fingerprinting

Journal of Chemometrics, 2014, 28, 681-686
Patrick M. Wehrli, Erika Lindberg, Olof Svensson, Anders Sparén, Mats Josefson, R. Hugh Dunstan, Agnes E. Wold and Johan Gottfries

Abstract: Transmission Fourier transform infrared (FTIR) spectra were obtained from cultures of Staphylococcus aureus that were grown under sets of various environmental conditions enclosing ranges of potential conditions in wound sites. The primary aim of this study was to determine whether bacterial phenotypic diversity could be characterized by FTIR spectroscopy analyses of cultures of S. aureus grown under variable sets of environmental conditions. Designing experiments with full factorial design has shown to be a powerful way to explore an expectedly large array of phenotypic diversity of S. aureus. Various combinations of environmental conditions caused the bacteria to adapt their phenotype, which was assessed via FTIR spectral fingerprinting. Transmission FTIR spectroscopy was found to be superior to other vibrational spectroscopy techniques for this purpose because of its high sensitivity, reproducibility, and rapidity of analysis. The sample preparation presented was fundamental for reproducible results. Different spectral preprocessing methods were compared in combination with scaling methods to obtain distinguishable phenotypes in principal component analysis (PCA) models. Spectral preprocessing with combined filters, including standard normal variate transformation, Savitzky–Golay smoothing, and use of the first derivative in a PCA model with unit variance scaling, gave the most optimal clustering for the data in this study. Spectra obtained from each treatment group were found to have a unique FTIR profile with good reproducibility, and thus PCA resulted in full separation between all groups on three principal components. In conclusion, transmission FTIR spectroscopy in conjunction with design of experiment, and multivariate analysis are powerful tools to investigate phenotypic diversity of S. aureus.

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