Variability within a clonal population of Erwinia amylovora disclosed by phenotypic analysis

• Autor(a) principal: Mendes, Rafael J.
• Data de Publicação: 2022
• Outros Autores: Silva, M.C.A., Luz, J.P., Tavares, Fernando, Santos, Conceição
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.11/8447

Background Fire blight is a destructive disease of pome trees, caused by Erwinia amylovora, leading to high losses of chain-of-values fruits. Major outbreaks were registered between 2010 and 2017 in Portugal, and the first molecular epidemiological characterization of those isolates disclosed a clonal population with different levels of virulence and susceptibility to antimicrobial peptides. Methods This work aimed to further disclose the genetic characterization and unveil the phenotypic diversity of this E. amylovora population, resorting to MLSA, growth kinetics, biochemical characterization, and antibiotic susceptibility. Results While MLSA further confirmed the genetic clonality of those isolates, several phenotypic differences were recorded regarding their growth, carbon sources preferences, and chemical susceptibility to several antibiotics, disclosing a heterogeneous population. Principal component analysis regarding the phenotypic traits allows to separate the strains Ea 630 and Ea 680 from the remaining. Discussion Regardless the genetic clonality of these E. amylovora strains isolated from fire blight outbreaks, the phenotypic characterization evidenced a population diversity beyond the genotype clonality inferred by MLSA and CRISPR, suggesting that distinct sources or environmental adaptations of this pathogen may have occurred. Conclusion Attending the characteristic clonality of E. amylovora species, the data gathered here emphasizes the importance of phenotypic assessment of E. amylovora isolates to better understand their epidemiological behavior, namely by improving source tracking, make risk assessment analysis, and determine strain-specific environmental adaptations, that might ultimately lead to prevent new outbreaks.