Morphological and Molecular Characterization of Erwinia sp. Causing Bacterial Blight of Eucalyptus in Western Kenya

Abstract

Bacterial blight is an emerging disease threatening eucalyptus production in Kenya; however, information on the identity and pathogenicity of the associated bacterial pathogens remains limited. This study aimed to characterise bacterial pathogens associated with bacterial blight of eucalyptus in Western Kenya using morphological, molecular and pathogenicity analyses. Symptomatic leaves and shoots of Eucalyptus grandis and Eucalyptus camaldulensis were collected from six commercial nurseries in Kisumu and Siaya counties, Kenya, between May 2025 and May 2026. Twenty-nine bacterial isolates were recovered and characterised based on Gram reaction, cell shape, motility, colony colour, colony shape, colony margin, colony surface and colony diameter. Morphological similarity was assessed using Gower's distance coefficient and Partitioning Around Medoids (PAM) clustering in R, with the optimal clustering solution (k = 3) selected using the highest average silhouette width (0.53). Representative isolates were subjected to 16S rRNA gene sequencing and phylogenetic analysis, while pathogenicity was evaluated on one-month-old eucalyptus seedlings of each species in a completely randomised design under glasshouse conditions. Twenty-nine bacterial isolates exhibiting significant morphological variation (P < .001) were recovered. BLASTn analysis identified isolates belonging to the genera Erwinia, Pantoea, Enterobacter, Burkholderia, Pseudomonas and Kosakonia, with sequence identities ranging from 98.15% to 100%. Phylogenetic analysis placed the most virulent isolate, ECKSN1_Ep11, within the Erwinia clade. Pathogenicity differed significantly among isolates (P < .001), with ECKSN1_Ep11 causing the highest disease severity on E. grandis (84%) and E. camaldulensis (80%). This study provides the first molecular characterisation of Erwinia-associated bacteria linked to bacterial blight of eucalyptus in western Kenya and identifies ECKSN1_Ep11 as the most virulent isolate recovered. These findings enhance understanding of the disease aetiology and provide a foundation for improved diagnosis, surveillance and management, while multilocus sequence analysis or whole-genome sequencing is recommended for definitive species identification.