It More than Adds Up: Interaction of Antibiotic Mixing and Temperature

Use of antibiotics for the treatment and prevention of bacterial infections in humans, agri- and aquaculture as well as livestock rearing leads to antibiotic pollution of fresh water and these antibiotics have an impact on free-living bacteria. While we know which antibiotics are most common in natural environments such as rivers and streams, there is considerable uncertainty regarding antibiotics’ interactions with one another and the effect of abiotic factors such as temperature. Here, we used an experimental approach to explore the effects of antibiotic identity, concentration, mixing and water temperature on the growth of Pseudomonas fluorescens, a common, ubiquitous bacterium. We exposed P. fluorescens to the four antibiotics most commonly found in surface waters (ciprofloxacin, ofloxacin, sulfamethoxazole and sulfapyridine) and investigated antibiotic interactions for single and mixed treatments at different, field-realistic temperatures. We observed an overall dependence of antibiotic potency on temperature, as temperature increased efficacy of ciprofloxacin and ofloxacin with their EC50 lowered by >75% with a 10 °C temperature increase. Further, we show that mixtures of ciprofloxacin and ofloxacin, despite both belonging to the fluoroquinolone class, exhibit low-temperature-dependent synergistic effects in inhibiting bacterial growth. These findings highlight the context dependency of antibiotic efficacy. They further suggest antibiotic-specific off-target effects that only affect the bacteria once they enter a certain temperature range. This has important implications as freshwater systems already contain multi-drug antibiotic cocktails and are changing temperature due to environmental warming. These factors will interact and affect aquatic food webs, and hence this creates an urgent need to adapt and improve laboratory testing conditions to closer reflect natural environments.

A Case of In Situ Phage Therapy against Staphylococcus aureus in a Bone Allograft Polymicrobial Biofilm Infection: Outcomes and Phage-Antibiotic Interactions

Phage therapy (PT) shows promising potential in managing biofilm infections, which include refractory orthopedic infections. We report the case of a 13-year-old girl who developed chronic polymicrobial biofilm infection of a pelvic bone allograft after Ewing’s sarcoma resection surgery. Chronic infection by Clostridium hathewayi, Proteus mirabilis and Finegoldia magna was worsened by methicillin-susceptible Staphylococcus aureus exhibiting an inducible Macrolides-Lincosamides-Streptogramin B resistance phenotype (iMLSB). After failure of conventional conservative treatment, combination of in situ anti-S. aureus PT with surgical debridement and intravenous antibiotic therapy led to marked clinical and microbiological improvement, yet failed to prevent a recurrence of infection on the midterm. This eventually led to surgical graft replacement. Multiple factors can explain this midterm failure, among which incomplete coverage of the polymicrobial infection by PT. Indeed, no phage therapy against C. hathewayi, P. mirabilis or F. magna could be administered. Phage-antibiotic interactions were investigated using OmniLog® technology. Our results suggest that phage-antibiotic interactions should not be considered “unconditionally synergistic”, and should be assessed on a case-by-case basis. Specific pharmacodynamics of phages and antibiotics might explain these differences. More than two years after final graft replacement, the patient remains cured of her sarcoma and no further infections occurred.

Modulatory Effects of Caffeine and Pentoxifylline on Aromatic Antibiotics: A Role for Hetero-Complex Formation

Antimicrobial resistance is a major healthcare threat globally. Xanthines, including caffeine and pentoxifylline, are attractive candidates for drug repurposing, given their well-established safety and pharmacological profiles. This study aimed to analyze potential interactions between xanthines and aromatic antibiotics (i.e., tetracycline and ciprofloxacin), and their impact on antibiotic antibacterial activity. UV-vis spectroscopy, statistical-thermodynamical modeling, and isothermal titration calorimetry were used to quantitatively evaluate xanthine-antibiotic interactions. The antibacterial profiles of xanthines, and xanthine-antibiotic mixtures, towards important human pathogens Staphylococcus aureus, Enterococcus faecium, Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, and Enterobacter cloacae were examined. Caffeine and pentoxifylline directly interact with ciprofloxacin and tetracycline, with neighborhood association constant values of 15.8–45.6 M−1 and enthalpy change values up to −4 kJ·M−1. Caffeine, used in mixtures with tested antibiotics, enhanced their antibacterial activity in most pathogens tested. However, antagonistic effects of caffeine were also observed, but only with ciprofloxacin toward Gram-positive pathogens. Xanthines interact with aromatic antibiotics at the molecular and in vitro antibacterial activity level. Given considerable exposure to caffeine and pentoxifylline, these interactions might be relevant for the effectiveness of antibacterial pharmacotherapy, and may help to identify optimal treatment regimens in the era of multidrug resistance.

Modulatory Effects of Caffeine and Pentoxifylline on Aromatic Antibiotics: A Role for Heterocomplex Formation

Antimicrobial resistance is a major healthcare threat globally. Xanthines, including caffeine and pentoxifylline, are attractive candidates for drug repurposing, given their well-established safety and pharmacological profiles. This study aimed to analyze potential interactions between xanthines and aromatic antibiotics (i.e., tetracycline and ciprofloxacin), and their impact on antibacterial activity. UV-vis spectroscopy, statistical-thermodynamical modeling, and isothermal titration calorimetry were used to quantitatively evaluate xanthine-antibiotic interactions. The antibacterial profiles of xanthines and xanthine-antibiotic mixtures towards important human pathogens Staphylococcus aureus, Enterococcus faecium, Escherichia coli, Acinetobacter baumannii, Klebsiella pneumoniae, and Enterobacter cloacae were examined. Caffeine and pentoxifylline directly interact with ciprofloxacin and tetracycline, with neighborhood association constant values of 15.8–45.6 M− 1 and enthalpy change values up to -4 kJ M− 1. Caffeine showed antibacterial activity (minimum inhibitory concentration, 4–8 mg/mL) toward Gram-negative bacteria. Caffeine enhanced the antibacterial activity of the tested antibiotics in most pathogens tested. Antagonistic effects of caffeine were observed only with ciprofloxacin toward Gram-positive pathogens. Xanthines interact with aromatic antibiotics at the molecular and in vitro antibacterial activity level. Given considerable exposure to caffeine and pentoxifylline, these interactions are relevant for the effectiveness of antibacterial pharmacotherapy, and may help to identify optimal treatment regimens in the era of multidrug resistance.

Weakest-Link Dynamics Predict Apparent Antibiotic Interactions in a Model Cross-Feeding Community

ABSTRACT With the growing global threat of antimicrobial resistance, novel strategies are required for combatting resistant pathogens. Combination therapy, in which multiple drugs are used to treat an infection, has proven highly successful in the treatment of cancer and HIV. However, this practice has proven challenging for the treatment of bacterial infections due to difficulties in selecting the correct combinations and dosages. An additional challenge in infection treatment is the polymicrobial nature of many infections, which may respond to antibiotics differently than a monoculture pathogen. This study tests whether patterns of antibiotic interactions (synergy, antagonism, or independence/additivity) in monoculture can be used to predict antibiotic interactions in an obligate cross-feeding coculture. Using our previously described weakest-link hypothesis, we hypothesized antibiotic interactions in coculture based on the interactions we observed in monoculture. We then compared our predictions to observed antibiotic interactions in coculture. We tested the interactions between 10 previously identified antibiotic combinations using checkerboard assays. Although our antibiotic combinations interacted differently than predicted in our monocultures, our monoculture results were generally sufficient to predict coculture patterns based solely on the weakest-link hypothesis. These results suggest that combination therapy for cross-feeding multispecies infections may be successfully designed based on antibiotic interaction patterns for their component species.

Weakest link dynamics predict apparent antibiotic interactions in a model cross-feeding community

With the growing global threat of antimicrobial resistance, novel strategies are required for combatting resistant pathogens. Combination therapy, wherein multiple drugs are used to treat an infection, has proven highly successful in the treatment of cancer and HIV. However, this practice has proven challenging for the treatment of bacterial infections due to difficulties in selecting the correct combinations and dosages. An additional challenge in infection treatment is the polymicrobial nature of many infections, which may respond to antibiotics differently than a monoculture pathogen. This study tests whether patterns of antibiotic interactions (synergy, antagonism, or independence/additivity) in monoculture can be used to predict antibiotic interactions in an obligate cross-feeding co-culture. Using our previously described weakest link hypothesis, we hypothesized antibiotic interactions in co-culture based on the interactions we observed in monoculture. We then compared our predictions to observed antibiotic interactions in co-culture. We tested the interactions between ten previously identified antibiotic combinations using checkerboard assays. Although our antibiotic combinations interacted differently than predicted in our monocultures, our monoculture results were generally sufficient to predict co-culture patterns based solely on the weakest link hypothesis. These results suggest that combination therapy for cross-feeding multispecies infections may be successfully designed based on antibiotic interaction patterns for their component species.