Influence of holding temperature on the growth and survival of Salmonella spp. and Staphylococcus aureus and the production of staphylococcal enterotoxin in egg products

Microbial Profile and Safety of Chicken Eggs from a Poultry Farm and Small-Scale Vendors in Hawassa, Southern Ethiopia

A freshly laid hen’s egg is devoid of microorganism, but soon after oviposition, it is contaminated by various spoilage and pathogenic microorganisms. The aim of this study was to assess the microbial profile and safety of chicken eggs in Hawassa City. A total of 60 egg samples were collected from Hawassa University Poultry Farm (HUPF) and small-scale vendors in Hawassa. The samples were analyzed for aerobic mesophilic bacterial count (AMBC), Staphylococcal count (SC), Enterobacteriaceae count (EC), total coliform count (TCC), fecal coliform count (FCC), and yeast and mold count (YMC). Moreover, the dominant mesophilic aerobic bacterial genera and common bacterial pathogens were identified by phenotypic methods. Accordingly, the mean aerobic mesophilic bacterial load of the shell surface rinsate of the egg samples ranged from 1.22 log10 CFU/ml to 9.7 log10 CFU/ml, while that of the internal contents ranged from 1.52 log CFU/ml to 9.36 log CFU/ml. The microbial load values of the egg contents were beyond the international recommended acceptable limits and suggested incipient spoilage. The mesophilic aerobic bacterial genera of the shell and internal contents of the egg samples were similarly dominated by Pseudomonas, Micrococcus, and Staphylococcus. The incidence of E. coli in shell rinsate and egg content was 10% (6 of 60) and 1.67% (1 of 60), respectively. Salmonellae were detected in shell rinsate of six egg samples (10%) and in the contents of eight samples (13.33%), all from small-scale vendors. These findings call for vigilant exercise of good agricultural and hygienic practices by primary producers and retailers.

Evaluation of Staphylococcus aureus growth and staphylococcal enterotoxin production in delicatessen and fine bakery products

Staphylococcal food poisoning is one of the most prevalent causes of foodborne intoxication worldwide. Sandwiches and desserts are susceptible to contamination by S. aureus due to the high proportion of manual work during their production. Our study aimed to evaluate the impact of storage conditions on staphylococcal enterotoxin production in sandwiches and buttercream puffs. Foods were inoculated with different S. aureus strains capable of producing type A, B, and C staphylococcal enterotoxins and incubated at 15, 25, and 30 °C. During the storage, samples were analysed for S. aureus counts and for staphylococcal enterotoxins. An enzyme-linked fluorescence assay was used to detect staphylococcal enterotoxins. The influence of inappropriate storage on S. aureus growth and staphylococcal enterotoxin production was evaluated. No staphylococcal enterotoxins were detected in sandwiches stored for 72 h at any of the tested temperatures. In buttercream puffs, enterotoxins type A, B, and C were detected within 24 h of storage at 25 °C.

[Staphylococcal Enterotoxin A Production and Inactivation in Bread during the Production Processes]

Staphylococcus aureus food poisoning is caused by the intoxication of staphylococcal enterotoxin (SE) produced in foods. Staphylococcal food poisoning is mostly due to staphylococcal enterotoxin type A (SEA) among SEs. There have been many studies on the growth and SEA production of S. aureus in various foods, but few studies in bread. Thus, the SEA production by S. aureus in dough during fermentation and the SEA inactivation in dough during baking were studied in the normal production processes of bread in this study. No growth of S. aureus or SEA production in dough, whose total weight was about 470 g, was observed during the fermentation at 25 and 35℃ for four hr, suggesting that the risk of SEA production in dough during fermentation under these conditions would be negligible. Any SEA injected at 6.0 and 0.56 ng/g in dough could not be detected after 20 and 10 min of baking at 200℃, respectively. These results showed that the baking process, which was completed in 25 min, was enough to inactivate SEA at those doses of SEA in the dough. The results on the production and inactivation of SEA in dough during the production processes in this study would be useful information on microbiological food safety of bread making.

Microbiota Analysis of Eggshells in Different Areas and During Different Storage Time by Non-cultural Methods

This study is to investigate and characterize the microbiota composition on eggshells from 3 different areas of Shaanxi province (Yulin, Hanzhong and Xi'an). The eggs were stored at 25 °C for 56 days and bacterial samples were collected from eggshells on day 0, 14, 28, 42 and 56. Denaturing gradient gel electrophoresis and high-throughput sequencing of 16S rRNA hypervariable region V3-V4 were performed. Alpha diversity was applied for analyzing the diversity of samples through 6 indices, including Observed-species, Chao1, Shannon, Simpson, ACE and Good's-coverage. Beta diversity was used to study the similarities or differences in the community composition of the samples. Totally, 36 phyla and 595 genera were classified by 16S rRNA gene sequencing. The composition of the microbial communities of different regions was quite different. Firmicutes (33-38% of total phyla) and Actinobacteria (36-61% of total phyla) were the most abundant phyla in all three regions. Proteobacteria were relatively more abundant (about 18% of total phyla) on eggs from Hanzhong. During storage time, the microbial communities mainly changed from Firmicutes to Actinobacteria on eggs from Yulin and Xi'an. Lactobacillus, Kocuria and Streptomyces were much higher at the genus level. Spoilage bacteria Staphylococcus, Streptococcus, Pseudomonas and Enterococcus were detected at the genus level. Campylobacter jejuni (< 1% of total bacteria), which might be related to human illness, was also detected. In conclusion, the structure, abundance, and composition of microbiota on eggshells differ among areas. The microbiota changed regularly during storage time. The current study may offer a new insight into bacterial species on eggshells.

Growth and Modeling of Staphylococcus aureus in Flour Products under Isothermal and Nonisothermal Conditions

This study was conducted to investigate the growth of Staphylococcus aureus in traditional Chinese flour products under isothermal (10, 15, 20, 25, 30, and 37°C) and nonisothermal (10 to 20, 20 to 30, and 25 to 37°C) conditions. Then, models for the growth of S. aureus in flour products as a function of storage temperature, pH, and water activity (a_w) were developed, and the goodness of fit of models was evaluated using the determination coefficient (R²), root mean square error (RMSE), bias factor (B_f), and accuracy factor (A_f). Based on the above information, S. aureus growth in steamed bread under nonisothermal conditions was predicted from experiments performed under isothermal conditions. It was shown that different combinations of temperature and a_w in flour products have a strong influence on the growth of S. aureus . The modified Gompertz model was found to be more suitable for describing the growth data of S. aureus in flour products, with an R² of >0.99 and an RMSE of <0.37. The newly developed secondary models were validated, and for the specific growth rate and the lag time, the R² values were 0.96 and 0.97, A_f was 1.12 and 1.06, and B_f was 1.13 and 1.05, respectively. The predicted nonisothermal growth curves of S. aureus were in agreement with the reported experimental ones, with RMSE <0.29, A_f value 1.02 to 1.09, and B_f value 0.92 to 0.99. These results indicated that the predictive models provided useful information for the establishment of safety standards and a risk assessment for S. aureus in flour products.

Predictive model for the growth kinetics of Staphylococcus aureus in raw pork developed using Integrated Pathogen Modeling Program (IPMP) 2013

A predictive model was performed to describe the growth of Staphylococcus aureus in raw pork by using Integrated Pathogen Modeling Program 2013 and a polynomial model as a secondary predictive model. S. aureus requires approximately 180 h to reach 5-6 log CFU/g at 10 °C. At 15 °C and 25 °C, approximately 48 and 20 h, respectively, are required to cause food poisoning. Predicted data using the Gompertz model was the most accurate in this study. For lag time (LT) model, bias factor (Bf) and accuracy factor (Af) values were both 1.014, showing that the predictions were within a reliable range. For specific growth rate (SGR) model, Bf and Af were 1.188 and 1.190, respectively. Additionally, both Bf and Af values of the LT and SGR models were close to 1, indicating that IPMP Gompertz model is more adequate for predicting the growth of S. aureus on raw pork than other models.

The formation of Staphylococcus aureus enterotoxin in food environments and advances in risk assessment

The recent finding that the formation of staphylococcal enterotoxins in food is very different from that in cultures of pure Staphylococcus aureus sheds new light on, and brings into question, traditional microbial risk assessment methods based on planktonic liquid cultures. In fact, most bacteria in food appear to be associated with surfaces or tissues in various ways, and interaction with other bacteria through molecular signaling is prevalent. Nowadays it is well established that there are significant differences in the behavior of bacteria in the planktonic state and immobilized bacteria found in multicellular communities. Thus, in order to improve the production of high-quality, microbiologically safe food for human consumption, in situ data on enterotoxin formation in food environments are required to complement existing knowledge on the growth and survivability of S. aureus. This review focuses on enterotoxigenic S. aureus and describes recent findings related to enterotoxin formation in food environments, and ways in which risk assessment can take into account virulence behavior. An improved understanding of how environmental factors affect the expression of enterotoxins in foods will enable us to formulate new strategies for improved food safety.

Application of extended single-reaction multiplex polymerase chain reaction for toxin typing of Staphylococcus aureus isolates in South Korea

The extended single-reaction multiplex PCR (esr-mPCR) developed in this study to detect staphylococcal enterotoxins (SEs), including SEA, SEB, SEC, SED, SEE, SEH, SEI, and SEJ, requires fewer sets of primers than other conventional multiplex PCRs and can be used to detect newly identified staphylococcal enterotoxins SEs more readily. Esr-mPCR analysis of 141 isolates of Staphylococcus aureus obtained from abattoir and livestock product samples revealed that 27 of the S. aureus isolates were toxigenic, and two were 2 multitoxigenic isolates. The most prevalent SE type was SEI followed by SEA and SEH. In addition, we investigated the clonal relatedness of toxigenic S. aureus isolates by arbitrarily primed PCR (AP-PCR). AP-PCR analysis of toxigenic S. aureus isolates revealed that the discriminatory power of AP-PCR was 9 (D=0.81), 8 (D=0.77), and 10 types (D=0.83) with primers AP1, ERIC2, and AP7, respectively. The combination of three each AP-PCR result could rearrange toxigenic S. aureus isolates into 10 types and five subtypes, with the D-value of 0.92. Interestingly, our data showed that toxigenic S. aureus isolates from different sources had different fingerprinting patterns although some of them carried the same types of SE genes. These data suggest that combinations of esr-mPCR and AP-PCR can provide a powerful approach for epidemiological investigation of toxigenic S. aureus isolates.

Assessment of mathematical models for predicting Staphylococcus aureus growth in cooked meat products

The growth of Staphylococcus aureus in commercially available vacuum-packaged cooked ham, turkey breast meat, and chicken breast meat stored at 2.3, 6.5, 10, 13.5, and 17.7 degrees C was studied. Growth rates observed in these food products were compared with those predicted on the basis of various growth models found in the literature and with those generated by the Pathogen Modeling Program and the Food MicroModel software using graphical and mathematical analysis for performance evaluation. In general, the models studied overestimated the growth of S. aureus. The Dengremont and Membré model most closely matched the observed behavior of S. aureus in ham and chicken breast meat, with bias factors of 1.56 and 1.09, respectively. The Eifert et al. model accurately described the growth of S. aureus in turkey breast meat, with a bias factor of 1.51. The remaining models provided safe predictions of the growth rate of S. aureus, but with poor accuracy. Predictive microbiology models have an immediate practical application in improving microbial food safety and quality and are very useful decision support tools, but they should not be used as the sole determinant of product safety.