Teresa Gil‐Gil

SPARK quantifies phage-antibiotic interactions using growth curves and shows synergy, antagonism, and dynamic changes across bacterial isolates and time.

The paper investigates phage resistance in E. coli due to O-antigen expression and finds that most E. coli in the gut are resistant, limiting phage impact on bacterial composition.

The paper investigates phage therapy failure in UTIs by showing that heteroresistance, not traditional resistance, causes rapid treatment failure despite initial susceptibility.

This study shows that combining bacteriophage and antibiotics improves clearance of Staphylococcus aureus infections in Galleria mellonella, even when antibiotics are resistant, but treatment timing and pharmacodynamics are critical.

This study shows that the innate immune system, not antibiotic type or bacterial resistance, determines treatment success in infections using Galleria mellonella and Staphylococcus aureus.

This study uses a mathematical-computer simulation model to evaluate the effectiveness of combining antibiotics and bacteriophage in treating prosthetic joint infections, finding that bacteriophage may not be an effective addition.

This study uses Galleria mellonella larvae to test hypotheses about innate immunity's role in bacterial infections and shows bacteriostatic drugs and phages are as effective as bactericidal antibiotics.

This study develops mathematical models to analyze how antibiotics, bacteriophage, and the innate immune system interact in treating bacterial infections, showing that host immunity significantly affects treatment outcomes and resistance development.

The paper tests if bactericidal antibiotics can kill bacteria previously treated with bacteriostatic drugs, finding that sequential treatment can be as effective as bactericidal drugs alone.

This study examines how sub-inhibitory antibiotic concentrations affect mutation rates and persistence in Staphylococcus aureus, showing increased mutation rates and reduced persistence.

This study shows that long-term exposure to bacteriostatic antibiotics in E. coli leads to the emergence of small colony variants (SCVs) that confer heteroresistance, which reverts upon antibiotic removal.

This paper develops two mathematical models of heteroresistance to explore how resistance ascends and reverts during antibiotic treatment, showing that current identification methods are insufficient.