Unraveling Resistance and Thresholds in Phage Therapy Using Staphylococcus aureus In Vitro Models

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This study modeled phage-bacteria dynamics in vitro, showing that resistance emerges and regrowth occurs if phage doses don't exceed both susceptible and resistant bacterial inundation thresholds.

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The paper investigated phage therapy dynamics against multidrug-resistant Staphylococcus aureus by using in vitro time-kill assays and pharmacokinetic/pharmacodynamic modeling for three phages (V1SA019, V1SA020, V1SA022) against two bacterial strains (SH1000 and USA300). Differential-equation models captured co-dynamics of susceptible, resistant, infected bacteria, and free phages, with nonlinear mixed-effect modeling quantifying parameter variability; resistance emergence was characterized by phenotyping and whole-genome sequencing of resistant clones. The authors found predator–prey-like interactions with early phage amplification and bacterial collapse, but resistant subpopulations regrew in an MOI-dependent manner, and all resistant clones carried mutations in teichoic acid biosynthesis genes accompanied by growth defects. Resistance control required phage doses exceeding both proliferation and inundation thresholds for susceptible and resistant populations, though the study is limited to in vitro systems. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Background Phage therapy is a promising approach against multidrug-resistant Staphylococcus aureus , but its clinical development is limited by gaps in pharmacokinetic/pharmacodynamic (PK/PD) understanding, especially concerning phage self-replication and resistance dynamics. Methods We combined in vitro time-kill assays with PK/PD modeling to study three anti-staphylococcal phages (V1SA019, V1SA020, V1SA022) against two S. aureus strains (SH1000 and USA300). A system of differential equations captured the co-dynamics of susceptible, resistant and infected bacteria and free phages. Nonlinear mixed-effect modeling quantified parameter variability. Resistance emergence was monitored through phenotyping and whole-genome sequencing of resistant clones. Results Phage–bacteria interactions followed a predator–prey pattern, with early bacterial growth, rapid phage amplification, and subsequent bacterial collapse. However, resistant subpopulations emerged, regrew over time, in a multiplicity of infection (MOI) dependent way. The model accurately described bacterial and phage dynamics and estimated kinetic parameters including adsorption and burst size. Proliferation and inundation thresholds varied by strain and phage. All resistant clones harbored mutations in genes involved in teichoic acid biosynthesis, with associated growth defects. Simulations demonstrated that only phage doses exceeding both susceptible and resistant bacterial inundation thresholds fully suppressed regrowth. Conclusion This study provides a quantitative framework for understanding phage– S. aureus co-dynamics and resistance emergence. It emphasizes the importance of considering both proliferation and inundation thresholds when designing phage dosing regimens. These findings inform the rational development of phage therapy and support translation toward in vivo and clinical applications.
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Abstract

Background Phage therapy is a promising approach against multidrug-resistant Staphylococcus aureus, but its clinical development is limited by gaps in pharmacokinetic/pharmacodynamic (PK/PD) understanding, especially concerning phage self-replication and resistance dynamics.

Methods

We combined in vitro time-kill assays with PK/PD modeling to study three anti-staphylococcal phages (V1SA019, V1SA020, V1SA022) against two S. aureus strains (SH1000 and USA300). A system of differential equations captured the co-dynamics of susceptible, resistant and infected bacteria and free phages. Nonlinear mixed-effect modeling quantified parameter variability. Resistance emergence was monitored through phenotyping and whole-genome sequencing of resistant clones.

Results

Phage–bacteria interactions followed a predator–prey pattern, with early bacterial growth, rapid phage amplification, and subsequent bacterial collapse. However, resistant subpopulations emerged, regrew over time, in a multiplicity of infection (MOI) dependent way. The model accurately described bacterial and phage dynamics and estimated kinetic parameters including adsorption and burst size. Proliferation and inundation thresholds varied by strain and phage. All resistant clones harbored mutations in genes involved in teichoic acid biosynthesis, with associated growth defects. Simulations demonstrated that only phage doses exceeding both susceptible and resistant bacterial inundation thresholds fully suppressed regrowth.

Conclusion

This study provides a quantitative framework for understanding phage–S. aureus co-dynamics and resistance emergence. It emphasizes the importance of considering both proliferation and inundation thresholds when designing phage dosing regimens. These findings inform the rational development of phage therapy and support translation toward in vivo and clinical applications. Competing Interest Statement The authors have declared no competing interest. Footnotes Entire manuscript was revised for more instinctive and coherent reading

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