The Use of Interdisciplinary Approaches to Understand the Biology of Campylobacter jejuni

• Published in: Microorganisms (Basel) Vol. 10; no. 12; p. 2498
• Main Authors: Dzianach, Paulina A, Pérez-Reche, Francisco J, Strachan, Norval J C, Forbes, Ken J, Dykes, Gary A
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 16.12.2022; MDPI
• Subjects: Animal models; Antimicrobial agents; Bacterial infections; Biofilms; biological models; Campylobacter; Campylobacter jejuni; Campylobacteriosis; Disinfection; Extracellular matrix; Food contamination & poisoning; Food safety; Foodborne diseases; Foodborne pathogens; Genomes; infection control; Infections; Mathematical analysis; Mathematical models; Metabolic pathways; Metabolism; multiscale descriptions; Pathogens; Plant extracts; Review; statistical models; Virulence; multiscale descriptions; infection control; foodborne pathogens; biological models; mathematical models; statistical models
• ISSN: 2076-2607; 2076-2607
• DOI: 10.3390/microorganisms10122498

is a bacterial pathogen recognised as a major cause of foodborne illness worldwide. While generally does not grow outside its host, it can survive outside of the host long enough to pose a health concern. This review presents an up-to-date description and evaluation of biological, mathematical, and statistical approaches used to understand the behaviour of this foodborne pathogen and suggests future avenues which can be explored. Specifically, the incorporation of mathematical modelling may aid the understanding of biofilm formation both outside and inside the host. Predictive studies may be improved by the introduction of more standardised protocols for assessments of disinfection methods and by assessment of novel physical disinfection strategies as well as assessment of the efficiency of plant extracts on eradication. A full description of the metabolic pathways of , which is needed for the successful application of metabolic models, is yet to be achieved. Finally, a shift from animal models (except for those that are a source of human campylobacteriosis) to human-specific data may be made possible due to recent technological advancements, and this may lead to more accurate predictions of human infections.