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

• Tipo: Artigo em Revista Científica Internacional
• Data: 2022

Autores

Mendes, RJ (Autor) Outra; Amaro, C (Autor) Outra; Luz, JP (Autor) Outra; Fernando Tavares (Autor) FCUP; Santos, C (Autor) FCUP

Revista

Título: PeerJ

Vol. 10

ISSN: 2167-8359

Editora: PeerJ

Indexação

ISI Web of Knowledge - 0 Citações

Scopus

Outras Informações

ID Authenticus: P-00W-ZV5

DOI: 10.7717/peerj.13695

Abstract (EN): 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.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 20