- Mycoplasma hyorhinis can cause polyserositis and arthritis in post-weaning pigs.
- To study M.hyorhinis‘ prevalence based on age, nasal swabs were taken from pigs at 1, 7, 14, 21, 28, 35, 42, 49, 56, 63, 70 and 77 days as well as from sows, in 3 different Minnesotan herds (A, B, and C).
- 8.8% of the sows were positive for M.hyorhinis in herds A and B whereas 3.3% of the sows were positive in herd C.
- The percentage of positive piglets (<21 days of age) was low: between 0 and 10% depending on the herds.
- At 28 days of age, the prevalence of M.hyorhinis in pigs increased dramatically to around 50% in herd A and 100% in herd B. After 42 days of age, the prevalence in those herds stayed above 95%.
- The prevalence in herd C stayed close to 0% until the pigs reached the age of 77 days, time at which the prevalence increased to 100%.
Did you see our Science page on Mycoplasma hyorhinis and swine conjunctivitis?
Mycoplasma hyorhinis is one of the causative agents of polyserositis and arthritis in postweaning pigs. Knowledge regarding colonization frequency and age distribution in modern pig production is lacking. The objective of this study was to estimate the prevalence of M hyorhinis colonization in different age groups across three commercial pig populations. Nasal swabs were collected from sows, piglets and nursery pigs of different ages. Oral fluids were collected from nursery pigs. Necropsies were performed to assess the presence of M hyorhinis-associated disease. M hyorhinis was detected in 5/60 sows in herd A, 3/60 in herd B and none in herd C. In herd A and B, the prevalence was low in preweaning piglets (∼8 per cent) and high in postweaning pigs (∼98 per cent). A total of 7/8 oral fluids tested PCR positive in herds A and B, while 1/8 tested positive in herd C. In herd C, the preweaning and postweaning prevalence was low. In herds A and B, necropsied pigs had polyserositis lesions where M hyorhinis was detected by PCR. This study showed that prevalence of M hyorhinis colonization varies with pig age and across farms. Information generated will aid in the design and implementation of control and prevention strategies.