Centre Hospitalier de Fougères

Listeria monocytogenes is an ubiquitous foodborne pathogen transmissible to humans through the consumption of contaminated products, including pork. In this study, we characterised the Listeria monocytogenes population circulating from the primary reservoir, pigs, to consumers in France. In 2008 and 2010, 147 strains from on-farm pig feces and 154 strains from retail pork meat were respectively isolated. Serogroups and clonal complexes (CC) were determined (n = 301), and 123 representative strains were further assessed for virulence, biofilm-forming ability, and resistance to Benzalkonium chloride (BC). Serogroup IIb, and CCs such as CC11, CC21, CC20, CC26, CC31, CC59, CC37, CC1 and CC77 strains predominated on farms, whereas serogroup IIc and IIa (respectively CC9 and CC121) were mainly recovered from retail meat. All 123 strains harbored the virulence-associated genes inlA, inlC, inlJ, plcA, prfA, actA, hlyA and iap. Overall virulence did not differ significantly between farm- and retail-derived strains; however, serogroup IVb strains were significantly more virulent, while serogroup IIc strains exhibited lower virulence. In our study, CC1 (mainly present in feces) and CC121 (present only on meat) showed the highest virulence level. Biofilm-forming ability was significantly higher in strains isolated from farm feces than in those from retail meat. Most meat strains, including CC121, CC9, CC14 and CC7, were more resistant to benzalkonium chloride than fecal strains. Our findings highlight the genetic and phenotypic evolution of the Listeria monocytogenes population along the pig-to-pork continuum. They suggest that strains persisting to the retail stage are more strongly associated with resistance to biocides than with robust biofilm formation in the food-processing environment. Contrary to expectations, our CC121 strains exhibited the highest level of virulence, even though this CC is reported hypovirulent.

Quantifying the fate of lipophilic contaminants in lactating cows is the cornerstone for ensuring the chemical safety of dairy products and beef meat. Exploring the effects of cow feeding and physiology on the toxicokinetics of several lipophilic contaminants requires an integrative approach. This study developed and evaluated a mechanistic model (RuMoPOP) of the absorption, distribution, metabolism, and excretion (ADME) of lipophilic contaminant in lactating cows. The model's rationale relies on the coupling of ADME with physiological sub-models. The ADME sub-model merges the concepts and advantages of former fugacity and physiologically based toxicokinetic models. The physiological sub-model is based on a model that finely describes the dynamics of lipids in the digestive contents, body, and milk, depending on the milk production level (from a low-yielding suckler cow to a high-yielding dairy cow). The model was fitted to toxicokinetic data from two dairy cow experiments for polychlorinated biphenyls, dibenzo-p-dioxins, and dibenzofurans. Model performances for predicting milk accumulation and depuration kinetics were judged satisfactory, with an average root mean square error relative to the observed mean of 27%. The model makes it possible to predict the variability in accumulation and depuration kinetics, depending on contaminant lipophilicity, hepatic clearance rate, and diet lipid content and digestibility, over the whole lifespan of low- and high-yielding cows. The RuMoPOP model is a valuable tool for exploring the complex interplay between lipophilic contaminant properties and cow physiology and ultimately contributes to the chemical safety of diverse dairy and beef production systems towards legacy and emerging lipophilic contaminants.

Unveiling the strategies of bacterial adaptation to stress constitute a challenging area of research. The understanding of mechanisms governing emergence of resistance to antimicrobials is of particular importance regarding the increasing threat of antibiotic resistance on public health worldwide. In the last decades, the fast democratization of sequencing technologies along with the development of dedicated bioinformatical tools to process data offered new opportunities to characterize genomic variations underlying bacterial adaptation. Thereby, research teams have now the possibility to dive deeper in the deciphering of bacterial adaptive mechanisms through the identification of specific genetic targets mediating survival to stress. In this chapter, we proposed a step-by-step bioinformatical pipeline enabling the identification of mutational events underlying biocidal stress adaptation associated with antimicrobial resistance development using Escherichia marmotae as an illustrative model.

Antimicrobials used in chicken farming for therapeutic and/or prophylactic purposes may result in unacceptable levels of edible residues, if withdrawal periods are not respected. To evaluate the risk in Vietnam, we validated an analytical method to detect antimicrobial residues from chicken meat samples and carried out a pilot cross-sectional study to identify optimal sampling strategies. A total of 45 raw meat samples were collected from 4 markets, 1 slaughterhouse and 4 farms (5 per site) in Northern Vietnam, between March and April 2021. Farmers were asked about antimicrobials used during sampled production cycles (5 chickens sampled per batch). Samples were analysed using liquid chromatography-tandem mass spectrometry for the presence of 68 antimicrobials at a pre-defined validation concentration. 7 compounds were identified from 4 classes (tetracyclines, sulphonamides, macrolides, and fluoroquinolones). In markets, where the source of sampled chickens was unknown, a diverse pool of residual antimicrobials was detected in 20% (4/20) of the meat samples. No residues were detected in samples from the slaughterhouse. No residues were detected in chickens from the one farm that reported using antimicrobials, whereas sulfadimethoxine, doxycycline and tilmicosin residues were identified from the other 3 farms reporting no antimicrobial use. The probability of detecting antimicrobial residues present in a flock based on sampling a single chicken was estimated at 0.93 (highest density interval 0.735–0.997). The preliminary results suggest a disparity between farmers’ reports on antimicrobial drug use and actual usage, and that the analysis of a single sample per farm has a high probability of detecting antimicrobial residues, if present.

International audience