The global gene expression and biomolecular composition in an Escherichia coli model strain exposed to 10 adverse conditions (sodium chloride, ethanol, glycerol, hydrochloric and acetic acid, sodium hydroxide, heat (46 degrees C), and cold (15 degrees C), as well as ethidium bromide and the disinfectant benzalkonium chloride) were determined using DNA microarrays and Fourier transform infrared (FT-IR) spectroscopy. In total, approximately 40% of all investigated genes (1682/4279 genes) significantly changed expression, compared with a nonstressed control. There were, however, only 3 genes (ygaW (unknown function), rmf (encoding a ribosomal modification factor), and ghrA (encoding a glyoxylate/hydroxypyruvate reductase)) that significantly changed expression under all conditions (not including benzalkonium chloride). The FT-IR analysis showed an increase in unsaturated fatty acids during ethanol and cold exposure, and a decrease during acid and heat exposure. Cold conditions induced changes in the carbohydrate composition of the cell, possibly related to the upregulation of outer membrane genes (glgAP and rcsA). Although some covariance was observed between the 2 data sets, principle component analysis and regression analyses revealed that the gene expression and the biomolecular responses are not well correlated in stressed populations of E. coli, underlining the importance of multiple strategies to begin to understand the effect on the whole cell.

This work presents a pilot study to investigate the potential of fourier transform infrared (FT-IR) microspectroscopy for rapid identification of Listeria at the species level. Using this technique, FT-IR spectra were acquired from 30 strains from five Listeria species. The FT-IR spectra were analysed using stepwise canonical discriminant analysis and partial least-squares regression in a stepwise identification scheme. The results showed that 93% of all the samples were assigned to the correct species, and that 80% of the Listeria monocytogenes strains were correctly identified. In comparison, 100% of the samples, including the L. monocytogenes samples, were correctly identified using spectra acquired by FT-IR macrospectroscopy. The results show that FT-IR microspectroscopy has potential as a rapid screening method for Listeria, which is especially valuable for the food industry.