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Background and aimEpidemiology of human non-typhoid salmonellosis is characterised by recurrent emergence of new clones of the pathogen over time. Some clonal lines of Salmonella have shaped epidemiology of the disease at global level, as happened for serotype Enteritidis or, more recently, for Salmonella 4,[5],12:i:-, a monophasic variant of serotype Typhimurium. The same clonal behaviour is recognisable at sub-serotype level where single outbreaks or more generalised epidemics are attributable to defined clones. The aim of this study was to understand the dynamics of a clone of Salmonella 4,[5],12:i:- over a 3-year period (2012-15) in a province of Northern Italy where the clone caused a large outbreak in 2013. Furthermore, the role of candidate outbreak sources was investigated and the accuracy of multilocus variable-number tandem repeat analysis (MLVA) was evaluated. Methods: we retrospectively investigated the outbreak through whole genome sequencing (WGS) and further monitored the outbreak clone for 2 years after its conclusion. Results: The study showed the transient nature of the clone in the population, possibly as a consequence of its occasional expansion in a food-processing facility. We demonstrated that important weaknesses characterise conventional typing methods applied to clonal pathogens such as Salmonella 4,[5],12:i:-, namely lack of accuracy for MLVA and inadequate resolution power for PFGE to be reliably used for clone tracking. Conclusions : The study provided evidence for the remarkable prevention potential of whole genome sequencing used as a routine tool in systems that integrate human, food and animal surveillance.

Infectious diseases in livestock can be transmitted through fomites: objects able to convey infectious agents. Between-farm spread of infections through fomites is mostly due to indirect contacts generated by on-farm visits of personnel that can carry pathogens on their clothes, equipment, or vehicles. However, data on farm visitors are often difficult to obtain because of the heterogeneity of their nature and privacy issues. Thus, models simulating disease spread between farms usually rely on strong assumptions about the contribution of indirect contacts on infection spread. By using data on veterinarian on-farm visits in a dairy farm system, we built a simple simulation model to assess the role of indirect contacts on epidemic dynamics compared to cattle movements (i.e. direct contacts). We showed that including in the simulation model only specific subsets of the information available on indirect contacts could lead to outputs widely different from those obtained with the full-information model. Then, we provided a simple preferential attachment algorithm based on the probability to observe consecutive on-farm visits from the same operator that allows overcoming the information gaps. Our results suggest the importance of detailed data and a deeper understanding of visit dynamics for the prevention and control of livestock diseases.

Animals' exchanges are considered the most effective route of between-farm infectious disease transmission. However, despite being often overlooked, the infection spread due to contaminated equipment, vehicles, or personnel proved to be important for several livestock epidemics. This study investigated the role of indirect contacts in a potential infection spread in the dairy farm network of the Province of Parma (Northern Italy). We built between-farm contact networks using data on cattle exchange (direct contacts), and on-farm visits by veterinarians (indirect contacts). We compared the features of the contact structures by using measures on static and temporal networks. We assessed the disease spreading potential of the direct and indirect network structures in the farm system by using data on the infection state of farms by paratuberculosis. Direct and indirect networks showed non-trivial differences with respect to connectivity, contact distribution, and super-spreaders identification. Furthermore, our analyses on paratuberculosis data suggested that the contributions of direct and indirect contacts on diseases spread are apparent at different spatial scales. Our results highlighted the potential role of indirect contacts in between-farm disease spread and underlined the need for a deeper understanding of these contacts to develop better strategies for prevention of livestock epidemics., Competing Interests: The authors have declared that no competing interests exist.

Multidrug-resistant (MDR) Klebsiella pneumoniae is one of the most important causes of nosocomial infections worldwide. After the spread of strains resistant to beta-lactams at the end of the previous century, the diffusion of isolates resistant to carbapenems and colistin is now reducing treatment options and the containment of infections. Carbapenem-resistant K. pneumoniae strains have spread rapidly among Italian hospitals, with four subclades of pandemic clonal group 258 (CG258). Here we show that a single Italian hospital has been invaded by three of these subclades within 27 months, thus replicating on a small scale the "Italian scenario." We identified a single clone responsible for an epidemic outbreak involving seven patients, and we reconstructed its star-like pattern of diffusion within the intensive care unit. This epidemiological picture was obtained through phylogenomic analysis of 16 carbapenem-resistant K. pneumoniae isolates collected in the hospital during a 27-month period, which were added to a database of 319 genomes representing the available global diversity of K. pneumoniae strains. Phenotypic and molecular assays did not reveal virulence or resistance determinants specific for the outbreak isolates. Other factors, rather than selective advantages, might have caused the outbreak. Finally, analyses allowed us to identify a major subclade of CG258 composed of strains bearing the yersiniabactin virulence factor. Our work demonstrates how the use of combined phenotypic, molecular, and whole-genome sequencing techniques can help to identify quickly and to characterize accurately the spread of MDR pathogens., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Acute rheumatic fever (ARF) is a postsuppurative sequela caused by Streptococcus pyogenes infections affecting school-age children. We describe here the occurrence of an ARF outbreak that occurred in Bologna province, northeastern Italy, between November 2012 and May 2013. Molecular analysis revealed that ARF-related group A Streptococcus (GAS) strains belonged to the M-18 serotype, including subtypes emm18.29 and emm18.32. All M-18 GAS strains shared the same antigenic profile, including SpeA, SpeB, SpeC, SpeL, SpeM, and SmeZ. Matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) analysis revealed that M-18 GAS strains grouped separately from other serotypes, suggesting a different S. pyogenes lineage. Single nucleotide polymorphisms and phylogenetic analysis based on whole-genome sequencing showed that emm18.29 and emm18.32 GAS strains clustered in two distinct groups, highlighting genetic variations between these subtypes. Comparative analysis revealed a similar genome architecture between emm18.29 and emm18.32 strains that differed from noninvasive emm18.0 strains. The major sources of differences between M-18 genomes were attributable to the prophage elements. Prophage regions contained several virulence factors that could have contributed to the pathogenic potential of emm18.29 and emm18.32 strains. Notably, phage ΦSPBO.1 carried erythrogenic toxin A gene (speA1) in six ARF-related M-18 GAS strains but not in emm18.0 strains. In addition, a phage-encoded hyaluronidase gene (hylP.2) presented different variants among M-18 GAS strains by showing internal deletions located in the α-helical and TSβH regions. In conclusion, our study yielded insights into the genome structure of M-18 GAS strains responsible for the ARF outbreak in Italy, thus expanding our knowledge of this serotype., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

We retrospectively analyzed a rare Salmonella enterica serovar Manhattan outbreak that occurred in Italy in 2009 to evaluate the potential of new genomic tools based on differential single nucleotide polymorphism (SNP) analysis in comparison with the gold standard genotyping method, pulsed-field gel electrophoresis. A total of 39 isolates were analyzed from patients (n=15) and food, feed, animal, and environmental sources (n=24), resulting in five different pulsed-field gel electrophoresis (PFGE) profiles. Isolates epidemiologically related to the outbreak clustered within the same pulsotype, SXB_BS.0003, without any further differentiation. Thirty-three isolates were considered for genomic analysis based on different sets of SNPs, core, synonymous, nonsynonymous, as well as SNPs in different codon positions, by Bayesian and maximum likelihood algorithms. Trees generated from core and nonsynonymous SNPs, as well as SNPs at the second and first plus second codon positions detailed four distinct groups of isolates within the outbreak pulsotype, discriminating outbreak-related isolates of human and food origins. Conversely, the trees derived from synonymous and third-codon-position SNPs clustered food and human isolates together, indicating that all outbreak-related isolates constituted a single clone, which was in line with the epidemiological evidence. Further experiments are in place to extend this approach within our regional enteropathogen surveillance system., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)