Comparison of Two Optical-Density-Based Methods and a Plate Count Method for Estimation of Growth Parameters of Bacillus cereus

Abstract

Quantitative microbiological models predicting proliferation of microorganisms relevant for food safety and/or food stability are useful tools to limit the need for generation of biological data through challenge testing and shelf-life testing. The use of these models requires quick and reliable methods for the generation of growth data and estimation of growth parameters. Growth parameter estimation can be achieved using methods based on plate counting and methods based on measuring the optical density. This research compares the plate count method with two optical density methods, namely, the 2-fold dilution (2FD) method and the relative rate to detection (RRD) method. For model organism Bacillus cereus F4810/72, the plate count method and both optical density methods gave comparable estimates for key growth parameters. Values for the maximum specific growth rate ( max ) derived by the 2FD method and by the RRD method were of the same order of magnitude, but some marked differences between the two approaches were apparent. Whereas the 2FD method allowed the derivation of values for lag time () from the data, this was not possible with the RRD method. However, the RRD method gave many more data points per experiment and also gave more data points close to the growth boundary. This research shows that all three proposed methods can be used for parameter estimation but that the choice of method depends on the objectives of the research.

Impact of microbial variability on food safety and quality

“…The culture was incubated for 16 h in a shaking incubator (Innova 4335, New Brunswick Scientific, Netherlands) at 200 rpm at 30C. To prepare a working culture, a similar procedure was followed as previously described (Biesta-Peters et al, 2010b). Briefly, the overnight culture was divided in two 50 ml centrifuge tubes and centrifuged for 2 min at 15,557 x g (Centrifuge 5804 R, Eppendorf).…”

“…The OD 600 data obtained from Bioscreen C were imported in Microsoft Excel for data processing to estimate the TTD. For practical reasons, which did not influence the results, the OD values in this study were not corrected for the background colour of BHI broth ( 0.1 at OD 600 ) (Biesta-Peters et al, 2010b). The  max was calculated as the negative reciprocal slope of the linear regression between TTD and the natural logarithm of the initial bacterial concentration of the five wells.…”

“…The  max was estimated by monitoring the OD 600 of four sequential 2-fold dilutions in five neighbouring wells using the Bioscreen C Biesta-Peters et al, 2010b). The TTD was defined as the time at which a certain well reaches a specific value of OD 600 0.2 (or 0.15 for the condition close to the growth boundary).…”

“…The  max was estimated using the 2-fold dilution method, which is based on time-todetection (TTD) measurement of serially diluted concentration as described earlier by Biesta-Peters et al (2010b). The TTD was defined as a time at which a well reaches a specific value of OD 600 0.2 (or 0.15 for the condition close to the growth boundary).…”

Improvement of methods for the detection of Gram-negative foodborne pathogens

“…These are for example Salmonella Typhimurium, Bacillus cereus, Staphylococcus aureus etc. (53). Bacteria regarded as "severe hazards" such as Clostridium botulinum, Salmonella Typhi etc.…”