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An atypical weakly haemolytic strain of Brachyspira hyodysenteriae is avirulent and can be used to protect pigs from developing swine dysentery.

Tom LaNyree Dale PhillipsFlaminia CoiacettoDavid John Hampson
Published in: Veterinary research (2019)
The anaerobic intestinal spirochaete Brachyspira hyodysenteriae colonises the large intestine of pigs and causes swine dysentery (SD), a severe mucohaemorrhagic colitis. SD occurs worldwide, and control is hampered by a lack of vaccines and increasing antimicrobial resistance. B. hyodysenteriae strains typically produce strong beta-haemolysis on blood agar, and the haemolytic activity is thought to contribute to the pathogenesis of SD. Recently, weakly haemolytic variants of B. hyodysenteriae have been identified in Europe and Australia, and weakly haemolytic strain D28 from Belgium failed to cause disease when used experimentally to infect pigs. Moreover, pigs colonised with D28 and then challenged with virulent strongly haemolytic strain B204 showed a delay of 2-4 days in developing SD compared to pigs not exposed to D28. The current study aimed to determine whether Australian weakly haemolytic B. hyodysenteriae strain MU1, which is genetically distinct from D28, could cause disease and whether exposure to it protected pigs from subsequent challenge with strongly haemolytic virulent strains. Three experimental infection studies were undertaken in which no diseases occurred in 34 pigs inoculated with MU1, although mild superficial lesions were found in the colon in 2 pigs in one experiment. In two experiments, significantly fewer pigs exposed to MU1 and then challenged with strongly haemolytic virulent strains of B. hyodysenteriae developed SD compared to control pigs not previously exposed to MU1 (p = 0.009 and p = 0.0006). These data indicate that MU1 lacks virulence and has potential to be used to help protect pigs from SD.
Keyphrases
  • antimicrobial resistance
  • escherichia coli
  • staphylococcus aureus
  • pseudomonas aeruginosa
  • risk assessment
  • artificial intelligence
  • climate change
  • wastewater treatment
  • deep learning