Phage-antibiotic combinations against Klebsiella pneumoniae: impact of methodological approaches on effect evaluation

Roman B Gorodnichev1, Anastasiia O Krivulia1,2, Maria A Kornienko1

  • 1Department of Biomedicine and Genomics, Lopukhin Federal Research and Clinical Center of Physical-Chemical Medicine of Federal Medical Biological Agency, Moscow, Russia.

PubMed
Abstract

Insights

Phage-antibiotic combinations show promise against resistant bacteria. Statistical methods impact results, with t-test and Bliss methods identifying more effects for potential clinical use.

Area of Science:

  • Microbiology
  • Bacteriology
  • Antimicrobial Resistance

Background:

  • Combined phage and antibiotic therapy offers a strategy against multidrug-resistant pathogens.
  • Inconsistent findings exist due to varied assessment methods for phage-antibiotic interactions.
  • Standardizing methods is crucial for reliable evaluation of combination therapies.

Purpose of the Study:

  • To evaluate phage-antibiotic interaction effects on Klebsiella pneumoniae.
  • To compare various statistical approaches for formalizing combination effects.
  • To identify optimal methods for detecting synergistic or antagonistic interactions.

Main Methods:

  • Tested antibiotics (gentamicin, levofloxacin, meropenem, chloramphenicol) and phages (Dlv622, Seu621, FRZ284) against K. pneumoniae strains.
  • Utilized a depolymerase (Dep622) in combination assays.
  • Employed modified t-test, Bliss independence model, two-way ANOVA, and checkerboard assays for effect evaluation.

Main Results:

  • 33 of 48 combinations showed statistically significant effects (26 synergy, 7 antagonism).
  • t-test and Bliss methods detected more effects than ANOVA or checkerboard assays.
  • Levofloxacin with Seu621 or Dep622 demonstrated the strongest synergy across strains.

Conclusions:

  • Analytical method choice significantly influences the detection of phage-antibiotic effects.
  • Simpler, sensitive methods like t-test and Bliss may suit clinical applications.
  • Understanding interaction characteristics is vital for developing effective therapeutic strategies.

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