Rapid and quantitative detection of the microbial spoilage of muscle foods: current status and future trends

Combining metabolic fingerprinting and footprinting to understand the phenotypic response of HPV16 E6 expressing cervical carcinoma cells exposed to the HIV anti-viral drug lopinavir

Recently, it has been reported that the anti-viral drug, lopinavir, which is currently used as a human immunodeficiency virus (HIV) protease inhibitor, could also inhibit E6-mediated proteasomal degradation of mutant p53 in E6-transfected C33A cells. In this study, C33A parent control cells and HPV16 E6-transfected cells were exposed to lopinavir at concentrations ranging from 0 to 30 microM. The phenotypic response was assessed by Fourier transform infrared (FT-IR) spectroscopy directly on cells (the metabolic fingerprint) and on the cell growth medium (the metabolic footprint). Multivariate analysis of the data using both principal components analysis (PCA) and canonical variates analysis (PC-CVA) showed trends in scores plots that were related to the concentration of the drug. Inspection of the PC-CVA loadings vector revealed that the effect was not due to the drug alone and that several IR spectral regions including proteins, nucleotides and carbohydrates contributed to the separation in PC-CVA space. Finally, partial least squares regression (PLSR) could be used to predict the concentration of the drug accurately from the metabolic fingerprints and footprints, indicating a dose related phenotypic response. This study shows that the combination of metabolic fingerprinting and footprinting with appropriate chemometric analysis is a valuable approach for studying cellular responses to anti-viral drugs.

Development of a new method for the detection of lactic acid bacteria capable of protecting ham against Enterobacteriaceae

AIMS

Challenge trials seem to be the best assessment approach to evaluate the potency of food protective cultures. However, this method is time consuming and often difficult to implement. Here, we describe the development of the 'sequential culturing method', a new method for the screening of strains as protective cultures.

METHODS AND RESULTS

The sequential culturing method is based on the simulation, in a meat simulation medium (named BHI5L200), of the inhibition of Enterobacteriaceae by Lactobacillus, observed previously in situ. Results obtained with this sequential culturing method were in good agreement with those of the challenge test on sliced cooked ham and confirmed the antagonistic potency of Lactobacillus. The results obtained from the screening of 187 lactic acid bacteria (LAB) indicated that Lactobacillus sakei, Lactococcus lactis diacetylactis and Carnobacterium spp. were strong inhibitors of Enterobacteriaceae whereas Pediococcus spp., Leuconostoc spp., Weisselia spp. and other species of Lactobacillus and Lactococcus, did not possess the same inhibitory capacity.

CONCLUSIONS

Sequential culturing method appeared to be a useful tool to rapidly select LAB cultures which are good candidates for bioprotection of meat.

SIGNIFICANCE AND IMPACT OF THE STUDY

Sequential culturing method and simulating media could efficiently mimic challenge test experiments in the selection of potential protective culture for all types of food, on the condition to have the appropriate simulating media, corresponding to the food for which protective cultures were searched.

Supervised pattern recognition in food analysis

Data analysis has become a fundamental task in analytical chemistry due to the great quantity of analytical information provided by modern analytical instruments. Supervised pattern recognition aims to establish a classification model based on experimental data in order to assign unknown samples to a previously defined sample class based on its pattern of measured features. The basis of the supervised pattern recognition techniques mostly used in food analysis are reviewed, making special emphasis on the practical requirements of the measured data and discussing common misconceptions and errors that might arise. Applications of supervised pattern recognition in the field of food chemistry appearing in bibliography in the last two years are also reviewed.

Influence of oxygen exclusion and temperature on pathogenic bacteria levels and sensory characteristics of packed ostrich steaks throughout refrigerated storage

Ostrich steaks (290) were obtained from Iliofibularis muscles. For microbiological and pH determinations, samples were inoculated with Listeria monocytogenes NCTC 11994 (80 steaks) or Escherichia coli ATCC 12806 (80), then air- or vacuum-packed and stored at either 4±1°C or 10±1°C. Analyses were carried out on days 0, 3, 6 and 9 of storage. For sensory evaluation, samples (130) were air- or vacuum-packed and stored at 4±1°C or at 10±1°C. Sensory attributes (odour, colour, drip loss, texture and general acceptability) were scored by six untrained judges using an unstructured nine-point hedonic scale on eleven sampling days (0, 3, 6, 9, 12, 15, 18, 21, 24, 27 and 30). Increases in microbial counts (log(10)cfu/g) were observed throughout storage in all groups of samples for both L. monocytogenes (from 6.39±0.43-6.62±0.32 at day 0 to 8.87±0.19-9.64±0.43 at day 9) and E. coli (from 5.57±0.15-5.68-0.40 to 7.79±0.96-9.64±0.17). Gas atmosphere influenced microbial counts from day 3 of storage with lower (P<0.05) values observed in vacuum- than in air-packed samples at 10°C (L. monocytogenes) or at 4 and 10°C (E. coli). Storage temperature significantly influenced bacterial counts throughout storage, especially in air-packed samples. Lower pH values in vacuum- than in air-packed samples were observed from day 6. Both effects (gas atmosphere and temperature) influenced the hedonic scores, with higher values assigned to vacuum-packed samples for most attributes (with the exception of drip loss) and sampling days. A marked influence of storage temperature on sensorial scores was obtained in air-packaged ostrich steaks. The shelf-life (time until the average general acceptability score fell below 5) was 6 (air-packed samples), 9 (vacuum-packed, 10°C), or 12 days (vacuum-packed, 4°C). The results being reported here suggest the importance of both oxygen exclusion and storage at low temperatures to reduce microbiological risks and improve the acceptability of ostrich meat. However, the short shelf-life of this product highlights the need to keep the time between slaughter and sale to a minimum.

Influence of storage temperature on microbial spoilage characteristics of haddock fillets (Melanogrammus aeglefinus) evaluated by multivariate quality prediction

The proliferation of specific spoilage organisms (SSO) and quality changes were evaluated in haddock fillets stored in styrofoam boxes at 0, 7 and 15 degrees C and under temperature fluctuations. A rapid electronic nose technique was used to monitor different classes of compounds, representing microbial metabolites that were characteristic for the onset of spoilage odors. Photobacterium phosphoreum predominated among the spoilage bacteria and high levels of TVB-N were observed at sensory rejection. Pseudomonas spp. appeared to be responsible for the development of sweet, fruity spoilage odors in haddock fillets coinciding with increasing response of the electronic nose CO sensor. H(2)S-producing bacteria, most likely Shewanella putrefaciens, were associated with the H(2)S sensor's response at abusive temperature conditions. Partial Least Squares Regression (PLSR) was used as an explorative tool to provide a better understanding of the spoilage potential of SSOs, by evaluating models based on electronic nose responses and counts of specific spoilage organisms to predict sensory quality (Torry scores). The best prediction of the sensory quality was obtained by PLSR models based on five variables: the electronic nose sensors (CO, NH(3) and H(2)S), pseudomonads counts and a time-temperature variable. Good agreement between the predicted and experimental data indicates that these variables characterize the sensory quality of haddock fillets stored under different temperatures.

Changes in the spoilage-related microbiota of beef during refrigerated storage under different packaging conditions

The microbial spoilage of beef was monitored during storage at 5 degrees C under three different conditions of modified-atmosphere packaging (MAP): (i) air (MAP1), (ii) 60% O2 and 40% CO2 (MAP2), and (iii) 20% O2 and 40% CO2 (MAP3). Pseudomonas, Enterobacteriaceae, Brochothrix thermosphacta, and lactic acid bacteria were monitored by viable counts and PCR-denaturing gradient gel electrophoresis (DGGE) analysis during 14 days of storage. Moreover, headspace gas composition, weight loss, and beef color change were also determined at each sampling time. Overall, MAP2 was shown to have the best protective effect, keeping the microbial loads and color change to acceptable levels in the first 7 days of refrigerated storage. The microbial colonies from the plate counts of each microbial group were identified by PCR-DGGE of the variable V6-V8 region of the 16S rRNA gene. Thirteen different genera and at least 17 different species were identified after sequencing of DGGE fragments that showed a wide diversity of spoilage-related bacteria taking turns during beef storage in the function of the packaging conditions. The countable species for each spoilage-related microbial group were different according to packaging conditions and times of storage. In fact, the DGGE profiles displayed significant changes during time and depending on the initial atmosphere used. The spoilage occurred between 7 and 14 days of storage, and the microbial species found in the spoiled meat varied according to the packaging conditions. Rahnella aquatilis, Rahnella spp., Pseudomonas spp., and Carnobacterium divergens were identified as acting during beef storage in air (MAP1). Pseudomonas spp. and Lactobacillus sakei were found in beef stored under MAP conditions with high oxygen content (MAP2), while Rahnella spp. and L. sakei were the main species found during storage using MAP3. The identification of the spoilage-related microbiota by molecular methods can help in the effective establishment of storage conditions for fresh meat.

Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy

The ability to diagnose the early onset of disease, rapidly, non-invasively and unequivocally has multiple benefits. These include the early intervention of therapeutic strategies leading to a reduction in morbidity and mortality, and the releasing of economic resources within overburdened health care systems. Some of the routine clinical tests currently in use are known to be unsuitable or unreliable. In addition, these often rely on single disease markers which are inappropriate when multiple factors are involved. Many diseases are a result of metabolic disorders, therefore it is logical to measure metabolism directly. One of the strategies employed by the emergent science of metabolomics is metabolic fingerprinting; which involves rapid, high-throughput global analysis to discriminate between samples of different biological status or origin. This review focuses on a selective number of recent studies where metabolic fingerprinting has been forwarded as a potential tool for disease diagnosis using infrared and Raman spectroscopies.

Sequential Injection Analysis System for the Sandwich Hybridization-Based Detection of Nucleic Acids

A sequential injection analysis lab-on-valve (SIA-LOV) system was developed for the specific detection of single-stranded nucleic acid sequences via sandwich hybridization of specific DNA probes to the target sequence. One DNA probe was tagged with fluorescein; the other was biotinylated and immobilized to streptavidin-coated porous beads. The system was optimized with respect to buffer composition, length of hybridization and wash steps, and volumes and concentrations of components used. On-bead oligonucleotide hybridization was studied using UV detection at 260 nm, while a final dose response curve was quantified using fluorescence detection. A dynamic range of 1-1000 pmol was obtained for a synthetic DNA sequence that was homologous to a segment in the B. anthracis atxA mRNA. A within-day variation of 7.2% and a day-to-day variation of 9.9% was observed. Each analysis was completed within 20 min. Subsequently, the system was applied to the detection of atxA mRNA expressed in a surrogate organism and amplified using NASBA. The SIA-LOV will find its application in routine laboratory-based analysis of specific single-stranded DNA/RNA sequences. Future improvements will include the integration of dye-encapsulating liposomes for signal enhancement used in lieu of the single fluorophore-labeled probe in order to lower the limit of detection.

Optical characterization of Pseudomonas fluorescens on meat surfaces using time-resolved fluorescence

A scanning optical system for the detection of bacteria on meat surfaces based on fluorescence lifetime and intensity measurements is described. The system detects autofluorescent light emitted by naturally occurring fluorophores in bacteria. The technique only requires minimal sample preparation and handling, thus the chemical properties of the specimen are preserved. This work presents the preliminary results obtained from a time-resolved fluorescence imaging system for the characterization of a nonpathogenic gram-negative bacteria, Pseudomonas fluorescens. Initial results indicate that the combination of fluorescence lifetime and intensity measurements provides a means for characterizing biological media and for detecting microorganisms on surfaces.

Immunomagnetic Isolation of Enterohemorrhagic Escherichia coli O157:H7 from Ground Beef and Identification by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry and Database Searches

A rapid (25 min) and facile method was developed for the isolation and identification of the enterohemorrhagic Escherichia coli (serotype O157:H7) in ground beef. The isolation method employed microscopic magnetic beads coated with antibodies covalently bonded to the surface that were specific to antigens of serotype O157. This selective preconcentration step was necessary because direct matrix-assisted laser desorption/ionization (MALDI) MS analysis of bacteria was not amenable, serving to isolate the bacteria from meat components and other nontarget bacteria. The immunomagnetic separation increased the sensitivity of the method and permitted the detection of bacteria in meat. MALDI time-of-flight MS furnished bacterial mass spectra that were useful for organism identification. Molecular weight database searches using the Expert Protein Analysis System proved useful for confirmation of the organism's identity. Bacterial biomarkers from direct MALDI analysis of pure bacterial suspensions were consistently present in bacterial suspensions of buffer/tryptic soy broth (positive controls) and meat extract samples. The detection limits were 2 x 10(6) cells/mL for the experimental approach used herein. Cross-reactivity studies performed on three nontarget bacterial strains revealed that the immunomagnetic beads are specific only to E. coli strain serotype O157:H7, and there is no cross-reactivity with the other relatively innocuous strains studied.

Chemometric Studies for the Characterization and Differentiation of Microorganisms Using in Situ Derivatization and Thermal Desorption Ion Mobility Spectrometry

Whole-cell bacteria were characterized and differentiated by thermal desorption ion mobility spectrometry and chemometric modeling. Principal component analysis was used to evaluate the differences in the ion mobility spectra of whole-cell bacteria and the fatty acid methyl esters (FAMEs) generated in situ after derivatization of the bacterial lipids. Alternating least squares served to extract bacterial peaks from the complex ion mobility spectra of intact microorganisms and, therefore, facilitated the characterization of bacterial strains, species, and Gram type. In situ thermal hydrolysis/methylation with tetramethylammonium hydroxide was necessary for the differentiation of Escherichia coli strains, which otherwise could not be distinguished by spectra acquired with the ITEMISER ion mobility spectrometer. The addition of the methylating agent had no effect on Gram-positive bacteria, and therefore, they could not be differentiated by genera. The classification of E. coli strains was possible by analysis of the IMS spectra from the FAMEs generated in situ. By using the fuzzy multivariate rule-building expert system and cross-validation, a correct classification rate of 96% (22 out of 23 spectra) was obtained. Chemometric modeling on bacterial ion mobility spectra coupled to thermal hydrolysis/methylation proved a simple, rapid (2 min/sample), inexpensive, and sensitive technique to characterize and differentiate intact microorganisms. The ITEMISER ion mobility spectrometer could detect as few as 4 x 10(6) cells/sample.

Rapid identification of closely related muscle foods by vibrational spectroscopy and machine learning

Muscle foods are an integral part of the human diet and during the last few decades consumption of poultry products in particular has increased significantly. It is important for consumers, retailers and food regulatory bodies that these products are of a consistently high quality, authentic, and have not been subjected to adulteration by any lower-grade material either by accident or for economic gain. A variety of methods have been developed for the identification and authentication of muscle foods. However, none of these are rapid or non-invasive, all are time-consuming and difficulties have been encountered in discriminating between the commercially important avian species. Whilst previous attempts have been made to discriminate between muscle foods using infrared spectroscopy, these have had limited success, in particular regarding the closely related poultry species, chicken and turkey. Moreover, this study includes novel data since no attempts have been made to discriminate between both the species and the distinct muscle groups within these species, and this is the first application of Raman spectroscopy to the study of muscle foods. Samples of pre-packed meat and poultry were acquired and FT-IR and Raman measurements taken directly from the meat surface. Qualitative interpretation of FT-IR and Raman spectra at the species and muscle group levels were possible using discriminant function analysis. Genetic algorithms were used to elucidate meaningful interpretation of FT-IR results in (bio)chemical terms and we show that specific wavenumbers, and therefore chemical species, were discriminatory for each type (species and muscle) of poultry sample. We believe that this approach would aid food regulatory bodies in the rapid identification of meat and poultry products and shows particular potential for rapid assessment of food adulteration.