Detection and quantification of viable Bacillus cereus in food by RT–qPCR

Effect of Nisin and Storage Temperature on Outgrowth of Bacillus cereus Spores in Pasteurized Liquid Whole Eggs

Pasteurization is used to ensure the safety of liquid whole eggs (LWEs) before commercial distribution; however, it is insufficient to inactivate the spore-forming bacteria Bacillus cereus. This study investigated the effect of nisin on the growth kinetics of B. cereus in LWE. Samples supplemented with 0-6.25 ppm of nisin were inoculated with a four-strain cocktail of heat-shocked B. cereus spores and incubated at isothermal temperatures of 15-45 °C. The Baranyi model was fitted to all B. cereus isothermal growth profiles, generating maximum growth rate (µmax) and lag phase duration (LPD). The extended Ratkowsky square root model described the temperature dependency of µmax. A second-order polynomial model assessed the combined effects of temperature and nisin on the LPD of B. cereus in LWE. A tertiary model was developed and validated using three dynamic temperature profiles. Nisin significantly extended LPD at lower temperatures, while µmax remained unaffected. Samples with 6.25 ppm of nisin inhibited growth for 29 days (average) at 15 °C. Although the tertiary model accurately predicted growth rates, it underpredicted LPD. Adjusting h0 values for each experimental condition improved LPD prediction accuracy. The study's findings indicate that nisin is effective in inhibiting the growth of B. cereus spores in LWE, lowering the risk of illness.

PacBio sequencing revealed variation in the microbiota diversity, species richness and composition between milk collected from healthy and mastitis cows

Mastitis is the economically most important disease of dairy cows. This study used PacBio single-molecule real-time sequencing technology to sequence the full-length 16S rRNAs from 27 milk samples (18 from mastitis and nine from healthy cows; the cows were at different stages of lactation). We observed that healthy or late stage milk microbiota had significantly higher microbial diversity and richness. The community composition of the microbiota of different groups also varied greatly. The healthy cow milk microbiota was predominantly comprised of Lactococcus lactis, Acinetobacter johnsonii, and Bacteroides dorei, while the milk from mastitis cows was predominantly comprised of Bacillus cereus. The prevalence of L. lactis and B. cereus in the milk samples was confirmed by digital droplets PCR. Differences in the milk microbiota diversity and composition could suggest an important role for some these microbes in protecting the host from mastitis while others associated with mastitis. The results of our research serve as useful references for designing strategies to prevent and treat mastitis.

Analysis of RNA Interference (RNAi) Biopesticides: Double-Stranded RNA (dsRNA) Extraction from Agricultural Soils and Quantification by RT-qPCR

Double-stranded RNA (dsRNA) molecules are used as a novel class of biopesticides. To enable assessments of the ecological risk associated with their release to receiving environments, we developed an approach to quantify dsRNA in agricultural soils using quantitative reverse transcription-polymerase chain reaction (RT-qPCR). To allow quantification of dsRNA adsorbed to particles, we also developed a protocol to transfer dsRNA from particles to the extraction buffer by changing particle surface charge and adding constituents to compete with dsRNA for adsorption sites. Our approach could quantify dsRNA amounts as low as 0.003 ng_dsRNA/g_soil. This approach is the first available field-applicable approach able to quantify dsRNA biopesticides down to environmentally relevant concentrations. We applied this approach to investigate dsRNA dissipation (including dilution, degradation, and adsorption) in two agricultural soils. When we applied a low amount of dsRNA (1 ng_dsRNA/g_soil) to the soils, we observed that a greater fraction of dsRNA was adsorbed to and extractable from soil particles in a silty clay loam soil than in a fine sandy loam soil. In both soils, dsRNA dissipated on the timescale of hours. Overall, these results demonstrate that our approach can be applied to assess the environmental fate of dsRNA biopesticides at concentrations relevant to their release to soils.

DNA extract characterization process for microbial detection methods development and validation

Background

Quantitative polymerase chain reaction (qPCR) assays used in pathogen detection require rigorous methods development including characterizing DNA extraction products. A DNA extract characterization process is demonstrated using DNA extracted from five different cells types (two Gram-negatives: Escherichia coli, and Burkholderia thailandensis, spores and vegetative cells from the Gram-positive Bacillus cereus, and yeast Saccharomyces cerevisiae) with six different methods.

Results

DNA extract quantity (concentration and extraction efficiency) and quality (purity and intactness) varied by cell type and extraction method enabling the demonstration of different DNA characterization methods. DNA purity was measured using UV spectroscopy, where the A₂₆₀/A₂₈₀ and A₂₆₀/A₂₃₀ ratios are indicators of different contaminants. Reproducibility of UV spectroscopy measurements decreased for DNA concentrations less than 17.5 ng/μL. Forty-seven extracts had concentrations greater than 17.5 ng/μL, 25 had A₂₆₀/A₂₈₀ above 2.0, and 28 had A₂₆₀/A₂₃₀ ratios below 1.8 indicating RNA and polysaccharide contamination respectively. Based on a qPCR inhibition assay the contaminants did not inhibit PCR. Extract intactness was evaluated using microfluidic gel electrophoresis. Thirty-five samples had concentrations above the limit of quantification (LOQ, roughly 11 ng/ μL), 93.5% of the DNA was larger than 1kb and 1% was smaller than 300 bp. Extract concentrations ranged from 1502.2 ng/μL to below the LOQ when UV spectroscopy, fluorometry, and qPCR were used. LOQ for UV spectroscopic and fluorometric measurements were 3.5 ng/μL and 0.25 ng/μL respectively. The qPCR LOQ varied by cell type (5.72 × 10^-3 ng/μL for E. coli, 2.66 × 10^-3 ng/μL, for B. cereus, 3.78 × 10^-3 ng/μL for B. thailandensis, and 7.67 × 10^-4 ng/μL for S. cerevisiae). A number of samples were below the UV spectroscopy (n = 27), flurometry (n = 15), and qPCR (n = 3) LOQ.

Conclusion

The presented DNA extract characterization process provides measures of DNA quantity and quality applicable to microbial detection methods development and validation studies. Evaluating DNA quality and quantity results in a better understanding of process LOD and contributing factors to suboptimal assay performance. The samples used demonstrated the use of different DNA characterization methods presented but did not encompass the full range of DNA extract characteristics.