Relationship between Salmonella infection, shedding and serology in fattening pigs in low–moderate prevalence areas

Salmonella is a major foodborne pathogen causing important zoonosis worldwide. Pigs asymptomatically infected in mesenteric lymph nodes (MLN) can be intermittent shedders of the pathogen through faeces, being considered a major source of human infections. European baseline studies of fattening pig salmonellosis are based on Salmonella detection in MLN. This work studies the relationship between Salmonella infection in MLN and intestinal content (IC) shedding at slaughter and the relationship between the presence of the pathogen and the serologic status at farm level. Mean Salmonella prevalence in the selected pigs (vertically integrated production system of Navarra, Spain) was 7.2% in MLN, 8.4% in IC and 9.6% in serum samples. In this low–moderate prevalence context, poor concordance was found between MLN infection and shedding at slaughter and between bacteriology and serology. In fact, most of shedders were found uninfected in MLN (83%) or carrying different Salmonella strains in MLN and in IC (90%). The most prevalent Salmonellae were Typhimurium resistant to ACSSuT ± Nx or ASSuT antibiotic families, more frequently found invading the MLN (70%) than in IC (33.9%). Multivariable analysis revealed that risk factors associated with the presence of Salmonella in MLN or in IC were different, mainly related either to good hygiene practices or to water and feed control, respectively. Overall, in this prevalence context, detection of Salmonella in MLN is an unreliable predictor of faecal shedding at abattoir, indicating that subclinical infections in fattening pigs MLN could have limited relevance in the IC shedding.This work and VG post‐doctoral contract were supported by Gobierno de Navarra (ref. IIQ14064.RI1) and Fundación Caja Navarra (ref. 2014‐0411). BSR, SS and LMG contracts were supported by European Social Fund‐CSIC (Subprogram JAE‐Doc), Erasmus‐Mundus‐18 and European Social Fund‐INIA, respectively.Peer reviewe