Distinct Microbiotas Are Associated with Different Production Lines in the Cutting Room of a Swine Slaughterhouse

Fanie Shedleur-Bourguignon (1) , Tom Duchemin (2) , William P. Thériault (1) , Jessie Longpré (3) , Alexandre Thibodeau (1) , Mounia Hocine (2) , Philippe Fravalo (4, 5)

1 UdeM - Université de Montréal
2 MESuRS - Laboratoire Modélisation, épidémiologie et surveillance des risques sanitaires
3 Auteur indépendant
4 Metabiot - Metabiot
5 CNAM - Conservatoire National des Arts et Métiers [CNAM]

The microorganisms found on fresh, raw meat cuts at a slaughterhouse can influence the meat’s safety and spoilage patterns along further stages of processing. However, little is known about the general microbial ecology of the production environment of slaughterhouses. We used 16s rRNA sequencing and diversity analysis to characterize the microbiota heterogeneity on conveyor belt surfaces in the cutting room of a swine slaughterhouse from different production lines (each associated with a particular piece/cut of meat). Variation of the microbiota over a period of time (six visits) was also evaluated. Significant differences of alpha and beta diversity were found between the different visits and between the different production lines. Bacterial genera indicative of each visit and production line were also identified. We then created random forest models that, based on the microbiota of each sample, allowed us to predict with 94% accuracy to which visit a sample belonged and to predict with 88% accuracy from which production line it was taken. Our results suggest a possible influence of meat cut on processing surface microbiotas, which could lead to better prevention, surveillance, and control of microbial contamination of meat during processing.

Domaines: Sciences du Vivant [q-bio]

Fanie Shedleur-Bourguignon, Tom Duchemin, William P. Thériault, Jessie Longpré, Alexandre Thibodeau, et al.. Distinct Microbiotas Are Associated with Different Production Lines in the Cutting Room of a Swine Slaughterhouse. Microorganisms, 2023, 11 (1), pp.133. ⟨10.3390/microorganisms11010133⟩. ⟨hal-04161798⟩