Antibodies provide a sensitive indicator of proteins displayed by bacteria during sepsis. Because signals produced by infection are naturally amplified during the antibody response, host immunity can be used to identify biomarkers for proteins that are present at levels currently below detectable limits. We developed a microarray comprising ϳ70% of the 4066 proteins contained within the Yersinia pestis proteome to identify antibody biomarkers distinguishing plague from infections caused by other bacterial pathogens that may initially present similar clinical symptoms. We first examined rabbit antibodies produced against proteomes extracted from Y. pestis, Burkholderia mallei, Burkholderia cepecia, Burkholderia pseudomallei, Pseudomonas aeruginosa, Salmonella typhimurium, Shigella flexneri, and Escherichia coli, all pathogenic Gram-negative bacteria. These antibodies enabled detection of shared cross-reactive proteins, fingerprint proteins common for two or more bacteria, and signature proteins specific to each pathogen. Recognition by rabbit and non-human primate antibodies involved less than 100 of the thousands of proteins present within the Y. pestis proteome. Further antigen binding patterns were revealed that could distinguish plague from anthrax, caused by the Gram-positive bacterium Bacillus anthracis, using sera from acutely infected or convalescent primates. Thus, our results demonstrate potential biomarkers that are either specific to one strain or common to several species of pathogenic bacteria. Molecular & Cellular Proteomics 8:924 -935, 2009.
A commercial plant extract (prepared from olive, garlic, onion and citrus extracts with sodium acetate (SA) as a carrier) was evaluated to extend the viability of yogurt starter and probiotic bacteria as a means to enhance the shelf life of live and active culture, probiotic nonfat yogurt. Yogurts prepared from three different formulas (0.5* plant extract, 0.25* SA, or no supplement) and cultures (yogurt starter plus Bifidobacterium animalis,Lactobacillus acidophilus, or both probiotics) were assessed weekly during 29 days of storage at 5°C. Supplemented yogurt mixes had greater buffering capacities than non-supplemented yogurt mixes. At the end of storage, Lactobacillus bulgaricus and L. acidophilus counts in supplemented yogurts were greater compared with non-supplemented yogurts. Supplementation did not affect Streptococcus thermophilus and B. animalis counts. Hence the greater buffering capacity of yogurt containing plant extract could enhance the longevity of the probiotics, L. bulgaricus and L. acidophilus, during storage.
This research investigates the potential risk of Salmonella in muffins when contamination is introduced via flour, the main ingredient. Flour was inoculated with a 3-strain cocktail of Salmonella serovars (Newport, Typhimurium, and Senftenberg) and re-dried to achieve a target concentration of ~8logCFU/g. The inoculated flour was then used to prepare muffin batter following a standard commercial recipe. The survival of Salmonella during and after baking at 190.6°C for 21min was analyzed by plating samples on selective and injury-recovery media at regular intervals. The thermal inactivation parameters (D and z values) of the 3-strain Salmonella cocktail were determined. A ≥5logCFU/g reduction in Salmonella population was demonstrated by 17min of baking, and a 6.1logCFU/g reduction in Salmonella population by 21min of baking. The D-values of Salmonella serovar cocktail in muffin batter were 62.2±3.0, 40.1±0.9 and 16.5±1.7min at 55, 58 and 61°C, respectively; and the z-value was 10.4±0.6°C. The water activity (a) of the muffin crumb (0.928) after baking and 30min of cooling was similar to that of pre-baked muffin batter, whereas the a of the muffin crust decreased to (0.700). This study validates a typical commercial muffin baking process utilizing an oven temperature of 190.6°C for at least 17min as an effective kill-step in reducing a Salmonella serovar population by ≥5logCFU/g.
Hyperspectral imaging (HSI) provides both spatial and spectral information of a sample by combining imaging with spectroscopy. The objective of this study was to generate hyperspectral graphs of common foodborne pathogens and to develop and validate prediction models for the classification of these pathogens. Four strains of Cronobacter sakazakii , five strains of Salmonella spp., eight strains of Escherichia coli , and one strain each of Listeria monocytogenes and Staphylococcus aureus were used in the study. Principal component analysis and k NN ( k ‐nearest neighbor) classifier model were used for the classification of hyperspectra of various bacterial cells, which were then validated using the cross‐validation technique. Classification accuracy of various strains within genera including C. sakazakii , Salmonella spp., and E. coli , respectively, was 100%; except within C. sakazakii , strain BAA‐894, and E. coli , strains O26, O45, and O121 had 66.67% accuracy. When all strains were studied together (irrespective of their genus) for the classification, only C. sakazakii P1, E. coli O104, O111, and O145, S . Montevideo, and L. monocytogenes had 100% classification accuracy, whereas E. coli O45 and S . Tennessee were not classified (classification accuracy of 0%). Lauric arginate treatment of C. sakazakii BAA‐894, E. coli O157, S . Senftenberg, L. monocytogenes , and S. aureus significantly affected their hyperspectral signatures, and treated cells could be differentiated from the healthy, nontreated cells.
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