Screening of Key Auto-Induction Medium Components Affecting Recombinant Endolysin Production Against Antibiotic-Resistant Acinetobacter baumannii Using a Plackett–Burman Design

Introduction: The global rise in antibiotic resistance has made infections caused by drug-resistant bacteria, such as Acinetobacter baumannii, a major public health concern. Consequently, the development of novel and efficient treatment strategies is urgently required. This study employed a Plackett–Burman design (PB) to identify the key autoinduction medium components affecting recombinant endolysin production in Escherichia coli BL۲۱ (DE۳) and its lytic activity against antibiotic-resistant A. baumannii strains. Methods: Five parameters were screened using a ۱۲-run PB design: the concentrations of glucose, glycerol, MgSO۴ .۷H۲ O, lactose, as well as lactose addition time. Recombinant endolysin was extracted from the E. coli cells obtained in each run, and its activity was determined using a turbidity reduction assay against an antibiotic-resistant A. baumannii strain. Results: Analysis of Variance (ANOVA) revealed that glucose, glycerol, and lactose significantly influenced recombinant endolysin production and lytic activity (P<۰.۰۵), whereas MgSO۴ .۷H۲ O and lactose addition time showed no significant effects. The results reflected screening-level functional activity rather than quantitative protein expression. The Plackett–Burman screening identified glucose, glycerol, and lactose as significant factors influencing endolysin activity. A positive linear correlation was observed between increasing glycerol and lactose concentrations and higher endolysin activity, whereas the effect of glucose was observed within a relatively narrow concentration range. The condition corresponding to the highest activity within the tested PB matrix was observed at low glucose (۰.۰۲۴۷% w/v), high glycerol (۵.۹۲% w/v), and high lactose (۴.۸۸۰% w/v). Conclusion: These findings highlight the key factors influencing endolysin production and provide a basis for subsequent detailed optimization studies.