A novel parameter to predict the effects of antibiotic combinations on the development of Staphylococcus aureus resistance: in vitro model studies at subtherapeutic daptomycin and rifampicin exposures

Susceptibility evaluation and PK/PD integration of tulathromycin against Actinobacillus pleuropneumoniae during the mutant selection window

Introduction

Actinobacillus pleuropneumoniae (APP) is a serious pathogen that affects the development of livestock breeding. Due to excessive use of antimicrobial drugs, many multidrug-resistant bacteria have emerged and spread, which have threatened the livestock industry. Therefore, we established a peristaltic pump infection model (PPIM) to evaluate the susceptibility change and pharmacokinetic/pharmacodynamic (PK/PD) integration of tulathromycin against APP during the mutant selection window (MSW) for preventing the emergence of mutant-resistant bacteria.

Methods

The 99% minimum inhibitory concentration (MIC99) and mutant prevention concentration (MPC) of tulathromycin against APP were measured using the agar-plate method. After the model of dynamic infection had been established based on tulathromycin data in lungs, different dosages were administered to make the drug concentrations located in different parts of the MSW. The population and sensitivity of APP were monitored. Tulathromycin concentrations were measured by high-performance liquid chromatography-tandem mass spectrometry. Finally, a sigmoid Emax model was used to analyze the relationships between PK/PD parameters and antibacterial effects.

Results and discussion

The values of MIC, MIC99, and MPC of tulathromycin against APP were 2, 1.4, and 44.8 μg/mL, respectively. The PPIM was stable. An elimination effect without regrowth was observed at 5.6 to 44.8 μg/mL (-4.48 to -7.05 Log10 CFU/mL, respectively). The MIC of APP increased 32-fold at 8 MIC99. AUC168 h/MIC99 had the best fit with the antibacterial effect (R 2 = 0.9867). The AUC168 h/MIC99 required to achieve bacteriostatic, bactericidal, and clearance effects were 1.80, 87.42, and 198 h, respectively. Our results could provide guidance for the clinical application of tulathromycin to treat APP infection and avoid the generation of drug-resistant bacteria.

A review of current antibiotic resistance and promising antibiotics with novel modes of action to combat antibiotic resistance

The emergence and transmission of antibiotic resistance is a global public health crisis with significant burden on healthcare systems, resulting in high mortality and economic costs. In 2019, almost five million deaths were associated with drug-resistant infections, and if left unchecked, the global economy could lose $100 trillion by 2050. To effectively combat this crisis, it is essential for all countries to understand the current situation of antibiotic resistance. In this review, we examine the current driving factors leading to the crisis, impact of critical superbugs in three regions, and identify novel mechanisms of antibiotic resistance. It is crucial to monitor the phenotypic characteristics of drug-resistant pathogens and describe the mechanisms involved in preventing the emergence of cross-resistance to novel antimicrobials. Additionally, maintaining an active pipeline of new antibiotics is essential for fighting against diverse antibiotic-resistant pathogens. Developing antibacterial agents with novel mechanisms of action is a promising way to combat increasing antibiotic-resistant pathogens.

Daptomycin synergistic properties from in vitro and in vivo studies: a systematic review

INTRODUCTION

Daptomycin is a bactericidal lipopeptide antibiotic approved for the treatment of systemic infections (i.e. skin and soft tissue infections, bloodstream infections, infective endocarditis) caused by Gram-positive cocci. It is often prescribed in association with a partner drug to increase its bactericidal effect and to prevent the emergence of resistant strains during treatment; however, its synergistic properties are still under evaluation.

METHODS

We performed a systematic review to offer clinicians an updated overview of daptomycin synergistic properties from in vitro and in vivo studies. Moreover, we reported all in vitro and in vivo data evaluating daptomycin in combination with other antibiotic agents, subdivided by antibiotic classes, and a summary graph presenting the most favourable combinations at a glance.

RESULTS

A total of 92 studies and 1087 isolates (723 Staphylococcus aureus, 68 Staphylococcus epidermidis, 179 Enterococcus faecium, 105 Enterococcus faecalis, 12 Enterococcus durans) were included. Synergism accounted for 30.9% of total interactions, while indifferent effect was the most frequently observed interaction (41.9%). Antagonistic effect accounted for 0.7% of total interactions. The highest synergistic rates against S. aureus were observed with daptomycin in combination with fosfomycin (55.6%). For S. epidermidis and Enterococcus spp., the most effective combinations were daptomycin plus ceftobiprole (50%) and daptomycin plus fosfomycin (63.6%) or rifampicin (62.8%), respectively.

FUTURE PERSPECTIVES

We believe this systematic review could be useful for the future updates of guidelines on systemic infections where daptomycin plays a key role.

Drug Combinations to Prevent Antimicrobial Resistance: Various Correlations and Laws, and Their Verifications, Thus Proposing Some Principles and a Preliminary Scheme

Antimicrobial resistance (AMR) has been a serious threat to human health, and combination therapy is proved to be an economic and effective strategy for fighting the resistance. However, the abuse of drug combinations conversely accelerates the spread of AMR. In our previous work, we concluded that the mutant selection indexes (SIs) of one agent against a specific bacterial strain are closely related to the proportions of two agents in a drug combination. To discover probable correlations, predictors and laws for further proposing feasible principles and schemes guiding the AMR-preventing practice, here, three aspects were further explored. First, the power function (y = axb, a > 0) correlation between the SI (y) of one agent and the ratio (x) of two agents in a drug combination was further established based on the mathematical and statistical analyses for those experimental data, and two rules a1 × MIC1 = a2 × MIC2 and b1 + b2 = −1 were discovered from both equations of y = a1xb1 and y = a2xb2 respectively for two agents in drug combinations. Simultaneously, it was found that one agent with larger MPC alone for drug combinations showed greater potency for narrowing itself MSW and preventing the resistance. Second, a new concept, mutation-preventing selection index (MPSI) was proposed and used for evaluating the mutation-preventing potency difference of two agents in drug combination; a positive correlation between the MPSI and the mutant prevention concentration (MPC) or minimal inhibitory concentration (MIC) was subsequently established. Inspired by this, the significantly positive correlation, contrary to previous reports, between the MIC and the corresponding MPC of antimicrobial agents against pathogenic bacteria was established using 181 data pairs reported. These results together for the above three aspects indicate that the MPCs in alone and combination are very important indexes for drug combinations to predict the mutation-preventing effects and the trajectories of collateral sensitivity, and while the MPC of an agent can be roughly calculated from its corresponding MIC. Subsequently, the former conclusion was further verified and improved via antibiotic exposure to 43 groups designed as different drug concentrations and various proportions. The results further proposed that the C/MPC for the agent with larger proportion in drug combinations can be considered as a predictor and is the key to judge whether the resistance and the collateral sensitivity occur to two agents. Based on these above correlations, laws, and their verification experiments, some principles were proposed, and a diagram of the mutation-preventing effects and the resistant trajectories for drug combinations with different concentrations and ratios of two agents was presented. Simultaneously, the reciprocal of MPC alone (1/MPC), proposed as the stress factors of two agents in drug combinations, together with their SI in combination, is the key to predict the mutation-preventing potency and control the trajectories of collateral sensitivity. Finally, a preliminary scheme for antimicrobial combinations preventing AMR was further proposed for subsequent improvement research and clinic popularization, based on the above analyses and discussion. Moreover, some similar conclusions were speculated for triple or multiple drug combinations.

MPC-Based Prediction of Anti-Mutant Effectiveness of Antibiotic Combinations: In Vitro Model Study with Daptomycin and Gentamicin against Staphylococcus aureus

To explore whether combined treatments with daptomycin and gentamicin can prevent the development of Staphylococcus aureus resistance, and whether the possible restriction is associated with changes in antibiotic mutant prevention concentrations (MPCs), the enrichment of daptomycin- and gentamicin-resistant mutants was studied by simulating 5-day single and combined treatments in an in vitro dynamic model. The MPCs of the antibiotics in the combination were determined at concentration ratios equal to the ratios of 24 h areas, under the concentration–time curve (AUCs) of the antibiotics, as simulated in pharmacodynamic experiments. The MPCs of both daptomycin and gentamicin decreased in the presence of each other; this led to an increase in the time when antibiotic concentrations were above the MPC (T_>MPC). The increases in T_>MPCs were concurrent with increases of the anti-mutant effects of the combined antibiotics. When anti-mutant effects of the antibiotics in single and combined treatments were plotted against the T_>MPCs, significant sigmoid relationships were obtained. These findings suggest that (1) daptomycin–gentamicin combinations prevent the development of S. aureus resistance to each antibiotic; (2) the anti-mutant effects of antibiotic combinations can be predicted using MPCs determined at pharmacokinetic-based antibiotic concentration ratios; (3) T_>MPC is a reliable predictor of the anti-mutant efficacy of antibiotic combinations.

Anti-mutant efficacy of antibiotic combinations: in vitro model studies with linezolid and daptomycin

OBJECTIVES

To explore whether linezolid/daptomycin combinations can restrict Staphylococcus aureus resistance and if this restriction is associated with changes in the mutant prevention concentrations (MPCs) of the antibiotics in combination, the enrichment of resistant mutants was studied in an in vitro dynamic model.

METHODS

Two MRSA strains, vancomycin-intermediate resistant ATCC 700699 and vancomycin-susceptible 2061 (both susceptible to linezolid and daptomycin), and their linezolid-resistant mutants selected by passaging on antibiotic-containing medium were used in the study. MPCs of antibiotics in combination were determined at a linezolid-to-daptomycin concentration ratio (1:2) that corresponds to the ratio of 24 h AUCs (AUC24s) actually used in the pharmacokinetic simulations. Each S. aureus strain was supplemented with respective linezolid-resistant mutants (mutation frequency 10-8) and treated with twice-daily linezolid and once-daily daptomycin, alone and in combination, simulated at therapeutic and sub-therapeutic AUC24s.

RESULTS

Numbers of linezolid-resistant mutants increased at therapeutic and sub-therapeutic AUC24s, whereas daptomycin-resistant mutants were enriched only at sub-therapeutic AUC24 in single drug treatments. Linezolid/daptomycin combinations prevented the enrichment of linezolid-resistant S. aureus and restricted the enrichment of daptomycin-resistant mutants. The pronounced anti-mutant effects of the combinations were attributed to lengthening the time above MPC of both linezolid and daptomycin as their MPCs were lowered.

CONCLUSIONS

The present study suggests that (i) the inhibition of S. aureus resistant mutants using linezolid/daptomycin combinations can be predicted by MPCs determined at pharmacokinetically derived antibiotic concentration ratios and (ii) T>MPC is a reliable predictor of the anti-mutant efficacy of antibiotic combinations as studied using in vitro dynamic models.

Predicting the antistaphylococcal effects of daptomycin-rifampicin combinations in an in vitro dynamic model

To predict the effects of combined use of antibiotics on their pharmacodynamics, the susceptibility of Staphylococcus aureus to daptomycin-rifampicin combinations was tested at concentration ratios equal to the ratios of daptomycin and rifampicin 24-h areas under the concentration-time curve (AUC₂₄s) simulated in an in vitro dynamic model. In combination with rifampicin, daptomycin MICs decreased 2- to 31-fold, whereas rifampicin MICs were similar with or without daptomycin. The enhanced susceptibility of S. aureus to daptomycin combined with rifampicin resulted in both an increase of the actual AUC₂₄/MIC ratios and also more pronounced antibacterial effects compared with single treatments. The areas between the control growth and time-kill curves (ABBCs) determined in combined and single daptomycin treatments were plotted against AUC₂₄/MIC on the same graph (r² 0.90). These findings suggest that the effects of daptomycin-rifampicin combinations can be predicted by AUC₂₄/MICs of daptomycin using its MIC determined at pharmacokinetically derived daptomycin-to-rifampicin concentration ratios.