Multistate outbreak of Salmonella Typhimurium linked to pet hedgehogs, United States, 2018-2019

Antimicrobial resistance in multistate outbreaks of nontyphoidal Salmonella infections linked to animal contact-United States, 2015-2018

Animal contact is an established risk factor for nontyphoidal Salmonella infections and outbreaks. During 2015-2018, the U.S. Centers for Disease Control and Prevention (CDC) and other U.S. public health laboratories began implementing whole-genome sequencing (WGS) of Salmonella isolates. WGS was used to supplement the traditional methods of pulsed-field gel electrophoresis for isolate subtyping, outbreak detection, and antimicrobial susceptibility testing (AST) for the detection of resistance. We characterized the epidemiology and antimicrobial resistance (AMR) of multistate salmonellosis outbreaks linked to animal contact during this time period. An isolate was considered resistant if AST yielded a resistant (or intermediate, for ciprofloxacin) interpretation to any antimicrobial tested by the CDC or if WGS showed a resistance determinant in its genome for one of these agents. We identified 31 outbreaks linked to contact with poultry (n = 23), reptiles (n = 6), dairy calves (n = 1), and guinea pigs (n = 1). Of the 26 outbreaks with resistance data available, we identified antimicrobial resistance in at least one isolate from 20 outbreaks (77%). Of 1,309 isolates with resistance information, 247 (19%) were resistant to ≥1 antimicrobial, and 134 (10%) were multidrug-resistant to antimicrobials from ≥3 antimicrobial classes. The use of resistance data predicted from WGS increased the number of isolates with resistance information available fivefold compared with AST, and 28 of 43 total resistance patterns were identified exclusively by WGS; concordance was high (>99%) for resistance determined by AST and WGS. The use of predicted resistance from WGS enhanced the characterization of the resistance profiles of outbreaks linked to animal contact by providing resistance information for more isolates.

Spatiotemporal Distribution of Salmonella enterica in European Hedgehogs in Northern Italy

Growing attention is being given to the European hedgehog (Erinaceus europaeus) because of its synanthropic behaviour and its potential role in harbouring parasites, viruses, fungi and bacteria and disseminating them to several animals and humans. Salmonella are the most frequently detected zoonotic bacteria that hedgehogs could transmit through contaminating water and food sources with faeces. This study aimed to determine the prevalence and distribution of Salmonella spp. in wild hedgehogs in the Emilia-Romagna region (northern Italy). From 2019 to 2022, 212 European hedgehogs that died naturally were tested for Salmonella spp. through culture isolation. Positive samples were subjected to serological typing. A total of 82 samples tested positive for Salmonella spp., with the overall Bayesian posterior estimated prevalence ranging from 35% (95% CI: 23-47%) to a maximum of 45% (95% CI: 31-59%) during the years considered and with an overall prevalence calculated at 39% (95% CI: 33-45%). Salmonella enterica Enteritidis and Veneziana were the most prevalent detected serovars in 65% and 17% of the positive samples, respectively. Since 2021, S. Typhimurium, S. Typhimurium Monofasica, S. Zaiman, S. Hessarek, S. Muenster, S. Isangi serovars, S. enterica subsp. Diarizonae and S. enterica subsp. Houtenae have been detected. These findings show a high prevalence of Salmonella spp. in tested hedgehogs, suggesting an important role of this animal species in the epidemiology of potentially zoonotic serovars circulating in the Emilia-Romagna region.

Through the Looking Glass: Genome, Phenome, and Interactome of Salmonella enterica

This review revisits previous concepts on biological phenomenon contributing to the success of the Salmonella enterica subspecies I as a pathogen and expands upon them to include progress in epidemiology based on whole genome sequencing (WGS). Discussion goes beyond epidemiological uses of WGS to consider how phenotype, which is the biological character of an organism, can be correlated with its genotype to develop a knowledge of the interactome. Deciphering genome interactions with proteins, the impact of metabolic flux, epigenetic modifications, and other complex biochemical processes will lead to new therapeutics, control measures, environmental remediations, and improved design of vaccines.