Optimization of the large-scale production for Erwinia amylovora bacteriophages

Abstract

Background: Fire blight, caused by Erwinia amylovora, poses a significant threat to global agriculture, with antibiotic-resistant strains necessitating alternative solutions such as phage therapy. Scaling phage therapy to an industrial level requires efficient mass-production methods, particularly in optimizing the seed culture process. In this study, we investigated large-scale E. amylovora phage production by optimizing media supplementation and fermenter conditions, focusing on minimizing seed phages and pathogenic strains to reduce risks and improve the seed culture process.

Results: We optimized the phage inoculum concentrations and media supplements to achieve higher phage yields comparable to or exceeding conventional methods. Laboratory-scale validation and refinement for fermenter-scale production allowed us to reduce bacterial and phage inoculum levels to 10⁵ CFU/mL and 10³ PFU/mL, respectively. Using fructose and sucrose supplements, the yields were comparable to conventional methods that use 10⁸ CFU/mL host bacteria and 10⁷ PFU/mL phages. Further pH adjustments in the fermenter increased yields by 16-303% across all phages tested.

Conclusions: We demonstrated the successful optimization and scale-up of E. amylovora phage production, emphasizing the potential for industrial bioprocessing with the reduced use of host cells and phage seeds. Overall, by refining key production parameters, we established a robust and scalable method for enhancing phage production efficiency.

Keywords: Erwinia amylovora; Fire blight; Large-scale; Optimization; Phage production.

Fig. 1

Phage production yields for Erwinia amylovora phages at different inoculum concentrations. Yields for the following E. amylovora phages were measured: pEa_SNUABM_8 (a), pEa_SNUABM_27 (b), and pEa_SNUABM_31 (c). Experiments were performed in triplicate. Statistical significance was determined using the Holm–Sidak test, with different letters above the bars indicating statistically significant differences between groups (p < 0.05)

Fig. 2

Screening of media supplements to maximize the production of Erwinia amylovora phages. Various carbon sources (a, b, c) and cations (d, e, f) were used, and the following E. amylovora phages were tested: pEa_SNUABM_8 (a, d), pEa_SNUABM_27 (b, e), and pEa_SNUABM_31 (c, f). Statistical significance was assessed using the Holm–Sidak test, with different letters above the bars representing statistically significant differences between groups (p < 0.05)

Fig. 3

Response surface 2D contour plots showing the effects of sugars on Erwinia amylovora phage production. The effect of fructose and sucrose on the production of pEa_SNUABM_8 (a), pEa_SNUABM_27 (b), and pEa_SNUABM_31 (c) phages were assessed. (d) Overlapping coded ranges of media supplements optimized for the three model phages using response surface methodology

Fig. 4

Validation of optimized phage production conditions at the flask scale using additional Erwinia amylovora phages. Yields for the additional E. amylovora phages, pEa_SNUABM_27, pEa_SNUABM_47, Fifi318, and Fifi451, were compared under conventional methods, optimized inoculum concentrations (IO), and optimized conditions (ISO), including both phage inoculation and media supplementation. Statistical analysis was performed using the Holm–Sidak test, and statistically significant differences between groups are indicated by different letters above the bars (p < 0.05)

Fig. 5

Further optimization of phage production conditions at the fermenter scale. The pH (a) and dissolved oxygen levels (b) were assessed. Significance testing was conducted using the Holm–Sidak test, with different letters above the bars indicating statistically significant differences between groups (p < 0.05)

Fig. 6

Validation of large-scale fermenter production conditions using various Erwinia amylovora phages. The E. amylovora phages, pEa_SNUABM_27 (a), pEa_SNUABM_47 (b), Fifi318 (c), and Fifi451 (d), were tested. The optimized phage production conditions were applied with additional parameters to maximize yields at the fermenter scale. Statistical significance was evaluated using the Holm–Sidak test, with different letters above the bars indicating significant differences between groups (p < 0.05)