Percorrer por autor "Petrovska, Liljana"
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- Attributable sources of the five most prevalent non-typhoidal Salmonella serovars across ten European countriesPublication . Teunis, Gijs; Dallman, Timothy J.; Zajac, Magdalena; Skarżyńska, Magdalena; Petrovska, Liljana; Pista, Ângela; Silveira, Leonor; Clemente, Lurdes; Thépault, Amandine; Bonifait, Laetitia; Kerouanton, Annaelle; Chemaly, Marianne; Alvarez, Julio; Soderlund, Robert; Nielsen, Eva Moller; Chattaway, Marie; Burgess, Kaye; Byrne, William; Zomer, Aldert L.; van den Beld, Maaike; Hendrickx, Antoni P.A.; Franz, Eelco; Pires, Sara; Hald, Tine; Mughini-Gras, LapoNon-typhoidal Salmonella is the second most frequently reported zoonotic pathogen in the European Union and European Economic Area. Most human infections are caused by serovars Enteritidis and Typhimurium. Genomic characterisation of Salmonella isolates from humans and animals has become a routine public health surveillance tool in many countries. In this study, the relative contributions of several potential sources of human infection of the five frequently reported Salmonella serovars were estimated using machine-learning methods based on a large, cross-sectional collection of genomes from human cases, and animal and environmental sources, across ten European countries. To define the population structure, core-genome Multilocus Sequence Typing was performed. A supervised machine-learning approach was applied for source attribution in the form of a Random Forest classifier. The source and country attribution models achieved moderate accuracy (F1=0.6–0.9), which is lower than in previous studies using machine-learning on Whole Genome Sequencing data. However, attributions of human clinical isolates to different sources were generally in line with previous findings for these five serovars. While the lack of clonality in some sources hindered their prediction, it is also likely that certain sources (e.g., pets) do not serve as major contributors to human infection. Therefore, in most cases attributing these sources to the livestock species they are typically associated with, is likely appropriate. Country attributions showed that substantial human cases are attributable to countries other than their own, indicating geographical interrelatedness of sources. This highlights the value of internationally harmonised Salmonella-control policies in the food production chain.
- Multi-country and intersectoral assessment of cluster congruence between pipelines for genomics surveillance of foodborne pathogensPublication . Mixão, Verónica; Pinto, Miguel; Brendebach, Holger; Sobral, Daniel; Santos, João Dourado; Radomski, Nicolas; Uldall, Anne Sophie Majgaard; Bomba, Arkadiusz; Pietsch, Michael; Bucciacchio, Andrea; de Ruvo, Andrea; Castelli, Pierluigi; Iwan, Ewelina; Simon, Sandra; Coipan, Claudia E.; Linde, Jörg; Petrovska, Liljana; Kaas, Rolf Sommer; Joensen, Katrine Grimstrup; Nielsen, Sofie Holtsmark; Kiil, Kristoffer; Lagesen, Karin; Di Pasquale, Adriano; Gomes, João Paulo; Deneke, Carlus; Tausch, Simon H.; Borges, VítorDifferent laboratories employ different Whole-Genome Sequencing (WGS) pipelines for Food and Waterborne disease (FWD) surveillance, casting doubt on the comparability of their results and hindering optimal communication at intersectoral and international levels. Through a collaborative effort involving eleven European institutes spanning the food, animal, and human health sectors, we aimed to assess the inter-pipeline clustering congruence across all resolution levels and perform an in-depth comparative analysis of cluster composition at outbreak level for four important foodborne pathogens: Listeria monocytogenes, Salmonella enterica, Escherichia coli, and Campylobacter jejuni. We found a general concordance between allele-based pipelines for all species, except for C. jejuni, where the different resolution power of allele-based schemas led to marked discrepancies. Still, we identified non-negligible differences in outbreak detection and demonstrated how a threshold flexibilization favors the detection of similar outbreak signals by different laboratories. These results, together with the observation that different traditional typing groups (e.g., serotypes) exhibit a remarkably different genetic diversity, represent valuable information for future outbreak case-definitions and WGS-based nomenclature design. This study reinforces the need, while demonstrating the feasibility, of conducting continuous pipeline comparability assessments, and opens good perspectives for a smoother international and intersectoral cooperation towards an efficient One Health FWD surveillance.