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Brucella ceti Infection in Striped Dolphins from Italian Seas: Associated Lesions and Epidemiological Data.

Carla GrattarolaAntonio PetrellaGiuseppe LuciforaGabriella Di FrancescoFabio Di NoceraAntonio PintoreCristiano CocumelliGiuliana TerraccianoAntonio BattistiLudovica Di RenzoDonatella FarinaCristina Esmeralda Di FrancescoMaria Ines CrescioSimona ZoppiAlessandro DondoBarbara IuliniKatia VarelloWalter MignoneMaria GoriaVirginia MattiodaFederica GiordaGiovanni Di GuardoAnna JanowiczManuela TittarelliFabrizio De MassisCristina CasaloneGiuliano Garofolo
Published in: Pathogens (Basel, Switzerland) (2023)
Brucella ceti infections have been increasingly reported in cetaceans. In this study, we analyzed all cases of B. ceti infection detected in striped dolphins stranded along the Italian coastline between 2012 and 2021 ( N = 24). We focused on the pathogenic role of B. ceti through detailed pathological studies, and ad hoc microbiological, biomolecular, and serological investigations, coupled with a comparative genomic analysis of the strains. Neurobrucellosis was observed in 20 animals. The primary histopathologic features included non-suppurative meningoencephalitis ( N = 9), meningitis ( N = 6), and meningoencephalomyelitis ( N = 5), which was also associated with typical lesions in other tissues ( N = 8). Co-infections were detected in more than half of the cases, mostly involving Cetacean Morbillivirus (CeMV). The 24 B. ceti isolates were assigned primarily to sequence type 26 (ST26) ( N = 21) and, in a few cases, ST49 ( N = 3). The multilocus sequence typing (cgMLST) based on whole genome sequencing (WGS) data showed that strains from Italy clustered into four genetically distinct clades. Plotting these clades onto a geographic map suggests a link between their phylogeny and the topographical distribution. These results support the role of B. ceti as a primary neurotropic pathogen for striped dolphins and highlight the utility of WGS data in understanding the evolution of this emerging pathogen.
Keyphrases
  • electronic health record
  • big data
  • escherichia coli
  • candida albicans
  • gene expression
  • data analysis
  • cerebrospinal fluid
  • high density