New Elements To Consider When Modeling the Hazards Associated with Botulinum Neurotoxin in Food

Abstract

Botulinum neurotoxins (BoNTs) produced by the anaerobic bacterium Clostridium botulinum are the most potent biological substances known to mankind. BoNTs are the agents responsible for botulism, a rare condition affecting the neuromuscular junction and causing a spectrum of diseases ranging from mild cranial nerve palsies to acute respiratory failure and death. BoNTs are a potential biowarfare threat and a public health hazard, since outbreaks of foodborne botulism are caused by the ingestion of preformed BoNTs in food. Currently, mathematical models relating to the hazards associated with C. botulinum, which are largely empirical, make major contributions to botulinum risk assessment. Evaluated using statistical techniques, these models simulate the response of the bacterium to environmental conditions. Though empirical models have been successfully incorporated into risk assessments to support food safety decision making, this process includes significant uncertainties so that relevant decision making is frequently conservative and inflexible. Progression involves encoding into the models cellular processes at a molecular level, especially the details of the genetic and molecular machinery. This addition drives the connection between biological mechanisms and botulism risk assessment and hazard management strategies. This review brings together elements currently described in the literature that will be useful in building quantitative models of C. botulinum neurotoxin production. Subsequently, it outlines how the established form of modeling could be extended to include these new elements. Ultimately, this can offer further contributions to risk assessments to support food safety decision making.

An Integrative Approach to Computational Modelling of the Gene Regulatory Network Controlling Clostridium botulinum Type A1 Toxin Production

“…In turn this transcription is dependent on both positive and negative regulatory elements. This evidence supports the construction of a signal transduction and sensory transcription regulatory network to describe the kinetics of neurotoxin production [32]. …”

“…The model construction has integrated the available experimental knowledge on the factors that, at a molecular level, regulate toxigenesis in C . botulinum Group 1 type A1; previously reviewed in [32]. In addition it portrays the effects of nutrient availability and quorum-sensing molecules and their coupling with distinct sensing and response TCSs that are regulators that mediate the activation of the toxin coding genes.…”

“…Positively, through the participation of BotR [17], Agr quorum sensing system [28], CodY [29] and CLC_1094/CLC_1093 (equivalent to CBO_1042/CBO_1041), CLC_1913/ CLC_1914 (equivalent to CBO_1967/ CBO_1968) and CLC_0663/CLC_0661 (equivalent to CBO_0608/CBO_0607) two component signal transduction systems [30]. Negatively, through the participation of CBO0787/CBO0786 (equivalent to CLC_0843/CLC_0842) [31] which is also a two component signal transduction system [32]. …”

Impact of Clostridium botulinum genomic diversity on food safety

“…[72] has reported on a relationship between lineage (and toxin type) and spore heat resistance. A systems level approach, both data mining and systems biology modelling, can provide a framework to understand complexity and hence to discover genetic determinants of features such as minimum growth temperature, neurotoxin formation and spore heat resistance [73, 74]. When challenge tests are carried out, it is customary to use a mixture of strains to reflect intra-species variability.…”