Tracking bacteriome variation over time in Listeria monocytogenes-positive foci in food industry.

The variation in microbial composition over time was assessed in biofilms formed in situ on selected non-food and food contact surfaces of meat and fish industries, previously identified as Listeria monocytogenes-positive foci. First, all samples were analysed for the detection and quantification of L. monocytogenes using ISO 11290-1 and ISO 11290-2 norms, respectively. Although the pathogen was initially detected in all samples, direct quantification was not possible. Psychrotrophic bacteria counts were among resident microbiota in meat industry samples (Mean = 6.14 log CFU/cm) compared to those form fish industry (Mean = 5.85 log CFU/cm). Visual analysis of the biofilms using epifluorescence microscopy revealed a trend to form microcolonies in which damaged/dead cells would act as anchoring structures. 16S rRNA gene metagenetic analysis demonstrated that, although Proteobacteria (71.37%) initially dominated the bacterial communities at one meat industry location, there was a dramatic shift in composition as the biofilms matured, where Actinobacteria (79.72%) became the major phylum present in later samples. This change was largely due to an increase of Nocardiaceae, Micrococcaceae and Microbacteriaceae. Nevertheless, for the other sampling location, the relative abundance of the dominating phylum (Firmicutes) remained consistent over the entire sampling period (Mean = 63.02%). In fish industry samples, Proteobacteria also initially dominated early on (90.69%) but subsequent sampling showed a higher diversity in which Bacteroidetes and Proteobacteria were the most abundant phyla accounting for the 48.04 and 37.98%, respectively by the last sampling period. Regardless of the location, the community profiles of the endpoint samples were similar to those reported previously. This demonstrated that in a given industrial setting there is a trend to establish a determinate biofilm structure due to the environmental factors and the constant incoming microbiota. This information could be used to improve the existing sanitisation protocols or for the design of novel strategies.