Effects of storage and the presence of a beef microflora on the thermal resistance of Salmonella Typhimurium DT104 in beef and broth systems.

AIMS: To investigate the effects of storage and the presence of a beef microflora on the thermal resistance of Salmonella serotype Typhimurium DT104 on beef surfaces and in a broth system during subsequent heat treatments after extended low-temperature storage (4 degrees C for 14 days) or mild temperature abuse (10 degrees C for 7 days). METHODS AND RESULTS: Surviving Salm. Typhimurium DT104 cells were estimated after heating in a water bath (55 degrees C) by plating beef and broth samples on tryptone soya agar and overlaying with xylose-lysine-deoxycholate agar. In beef and broth systems, D(55) values for Salm. Typhimurium DT104 stored at 4 degrees C or 10 degrees C in the presence or absence of a beef microflora were significantly lower (P < 0.01) than the D values for this organism heat-treated immediately after inoculation. In beef systems, the D(55) values were significantly lower (P < 0.05) in the presence of a beef microflora than the D(55) values obtained in 'pure' culture under all temperature/storage combinations. However, in broth systems, there was no significant difference between the D(55) values obtained in 'pure' culture and the D(55) values obtained from systems containing beef microflora. CONCLUSIONS: Storage of Salm. Typhimurium DT104 significantly reduced the thermal resistance of the pathogen in beef and broth systems. In the presence of high numbers of a Gram-negative beef microflora, the heat sensitivity of the pathogen was further increased on beef surfaces but not in broth. SIGNIFICANCE AND IMPACT OF THE STUDY: Studies investigating the survival of Salm. Typhimurium DT104 in different food systems will help define safe food preservation processes and will aid in the elimination this pathogen from the food production environments.

Surface decontamination of beef inoculated with Salmonella Typhimurium DT104 or Escherichia coli O157:H7 using dry air in a novel heat treatment apparatus.

AIMS: To determine the effectiveness of a novel dry air decontamination apparatus in the deactivation of Salmonella serotype Typhimurium DT104 or Escherichia coli O157:H7 on beef surfaces. METHODS AND RESULTS: A laboratory scale dry air decontamination apparatus, capable of producing repeatable and known heating time-temperature cycles on food surfaces was used in decontamination trials. Beef samples were surface inoculated with 7-8 log10CFU cm(-2) of S. Typhimurium DT104 or E. coli O157:H7 and heated at 60, 75, 90 and 100 degrees C using fast and slow heating rates and subsequently held at these temperatures for up to 600 s. A substantial reduction in pathogen numbers was achieved at higher temperatures (90 and 100 degrees C, 4.18-6.06 log10CFU cm(-2)) using both heating rates, but cell survival at these temperatures was also observed. At the lower temperatures, deactivation was small at 60 degrees C in particular it was less than one log unit after 3 min heating. No significant differences were observed when total reductions in pathogen counts were compared for all the temperature/heat up time combinations tested. During slow heating at 90 degrees C, and both heating rates at 100 degrees C, the pattern of deactivation of S. Typhimurium DT104 or E. coli O157:H7 was triphasic. CONCLUSIONS: This study has shown that heating meat surfaces with dry air can achieve substantial reductions in S. Typhimurium DT104 or E. coli O157:H7. As surface decontamination of beef surfaces with dry air had a negative effect on beef colour and appearance, such a decontamination apparatus would be unsuitable for producing meat for retail sale but it could be used to produce safer meat for use in the catering trade. SIGNIFICANCE AND IMPACT OF THE STUDY: This study provides researchers and food processors with data on the dynamic changes in S. Typhimurium DT104 and E. coli O157:H7 counts on intact beef surfaces during heating with dry air under realistic (time-varying) temperature conditions.

Detection of the dipicolinic acid biomarker in Bacillus spores using Curie-point pyrolysis mass spectrometry and Fourier transform infrared spectroscopy.

Thirty-six strains of aerobic endospore-forming bacteria confirmed by polyphasic taxonomic methods to belong to Bacillus amyloliquefaciens, Bacillus cereus, Bacillus licheniformis, Bacillus megaterium, Bacillus subtilis (including Bacillus niger and Bacillus globigii), Bacillus sphaericus, and Brevi laterosporus were grown axenically on nutrient agar, and vegetative and sporulated biomasses were analyzed by Curie-point pyrolysis mass spectrometry (PyMS) and diffuse reflectance-absorbance Fourier-transform infrared spectroscopy (FT-IR). Chemometric methods based on rule induction and genetic programming were used to determine the physiological state (vegetative cells or spores) correctly, and these methods produced mathematical rules which could be simply interpreted in biochemical terms. For PyMS it was found that m/z 105 was characteristic and is a pyridine ketonium ion (C6H3ON+) obtained from the pyrolysis of dipicolinic acid (pyridine-2,6-dicarboxylic acid; DPA), a substance found in spores but not in vegetative cells; this was confirmed using pyrolysis-gas chromatography/mass spectrometry. In addition, a pyridine ring vibration at 1447-1439 cm-1 from DPA was found to be highly characteristic of spores in FT-IR analysis. Thus, although the original data sets recorded hundreds of spectral variables from whole cells simultaneously, a simple biomarker can be used for the rapid and unequivocal detection of spores of these organisms.

Rapid analysis of high-dimensional bioprocesses using multivariate spectroscopies and advanced chemometrics.

There are an increasing number of instrumental methods for obtaining data from biochemical processes, many of which now provide information on many (indeed many hundreds) of variables simultaneously. The wealth of data that these methods provide, however, is useless without the means to extract the required information. As instruments advance, and the quantity of data produced increases, the fields of bioinformatics and chemometrics have consequently grown greatly in importance. The chemometric methods nowadays available are both powerful and dangerous, and there are many issues to be considered when using statistical analyses on data for which there are numerous measurements (which often exceed the number of samples). It is not difficult to carry out statistical analysis on multivariate data in such a way that the results appear much more impressive than they really are. The authors present some of the methods that we have developed and exploited in Aberystwyth for gathering highly multivariate data from bioprocesses, and some techniques of sound multivariate statistical analyses (and of related methods based on neural and evolutionary computing) which can ensure that the results will stand up to the most rigorous scrutiny.

Rapid analysis of the expression of heterologous proteins in Escherichia coli using pyrolysis mass spectrometry and Fourier transform infrared spectroscopy with chemometrics: application to alpha 2-interferon production.

Cell pastes and supernatant Escherichia coli samples, taken from an industrial bioprocess overproducing recombinant alpha 2 IFN were analysed using pyrolysis mass spectrometry (PyMS) and diffuse reflectance-absorbance Fourier transform infrared spectroscopy (FT-IR). PyMS and FT-IR are physico-chemical methods which measure predominantly the bond strengths of molecules and the vibrations of bonds within functional groups, respectively. They therefore give quantitative information about the total biochemical composition of the bioprocess sample. The interpretation of these hyperspectral data, in terms of the quantity of alpha 2 IFN in the cell pastes and supernatant samples was possible only after the application of the 'supervised learning' methods of artificial neural networks (ANNs) and partial least squares (PLS) regression. Both PyMS and FT-IR are novel, rapid and economical methods for the screening and the quantitative analysis of complex biological bioprocess over producing recombinant proteins. Models established using either spectral data set had a similarly satisfactory predictive ability. This shows that whole-reaction mixture spectral methods, which measure all molecules simultaneously, do contain enough information to allow their quantification when the entire spectra are used as the inputs to methods based on supervised learning. Moreover, this is the first study where FT-IR in the mid-IR range has been used to quantify the expression of a heterologous protein directly from fermentation broths and the first study to compare the abilities of PyMS and FT-IR for the quantitative analyses of an industrial bioprocess.