Comparative Minimal Inhibitory and Mutant Prevention Concentration of Eight Antimicrobial Agents Against Klebsiella pneumoniae

Purpose: With the emergence of multidrug-resistant and pan-resistant strains, Klebsiella pneumoniae (K. pneumoniae) shows higher treatment failure rates and mortality in clinics. It is more important to develop an effective method for treating K. pneumonia infections. The main objectives of this study were to determine the minimal inhibitory concentration (MIC) and the mutant prevention concentration (MPC) for eight antimicrobial agents against K. pneumoniae isolated from different hosts and compare the emergence of resistant mutants between animal strains and human strains. Materials and Methods: A total of 72 nonduplicate K. pneumoniae isolates and 8 antimicrobial agents (amikacin, azithromycin, levofloxacin, doxycycline, nitrofurantoin, colistin, tigecycline, and imipenem) were used. The MIC and MPC values were determined using agar plate assays. The values of the selection index (SI) were calculated with MPC₉₀/MIC₉₀. Pharmacodynamic parameters were calculated using published plasma pharmacokinetic variables. Results: For human isolate strains, the MPC_50/90 (μg/mL) values were as follows: amikacin, 32/128; azithromycin, 64/128; levofloxacin, 4/16; doxycycline, 32/32; nitrofurantoin, 128/512; colistin, 4/8; tigecycline, 8/16; and imipenem, 4/8. The value of SI was 8 for azithromycin, doxycycline, and tigecycline; 16 for amikacin, levofloxacin, and nitrofurantoin; 4 for imipenem; and 2 for colistin. For animal isolate strains, the MPC₉₀ values were 128 μg/mL for azithromycin and doxycycline, 64 μg/mL for amikacin, 32 μg/mL for levofloxacin, 512 μg/mL for nitrofurantoin, 8 μg/mL for colistin and tigecycline, 4 μg/mL for imipenem. The value of SI was 2 for colistin and imipenem, 8 for tigecycline, 16 for amikacin, and 32 for the other four agents. In combination with pharmacokinetic parameters, these findings indicated that the plasma concentrations of the seven antibiotics except imipenem were below the MPC for the entire dosing interval. Conclusion: The ability of eight antibiotics to prevent resistant mutants of K. pneumoniae was different between animal strains and human strains. Higher doses than those currently approved should be required to prevent the enrichment of mutants of drug-resistant bacteria in the clinics.

Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells

The emergence of antibiotic resistance poses a critical threat to the efficacy of antibiotic treatments. A resistant bacterial population must originally arise from a single cell that mutates or acquires a resistance gene. This single cell may, by chance, fail to successfully reproduce before it dies, leading to loss of the nascent resistant lineage. Here, we show that antibiotic concentrations that selectively favor resistance are nonetheless sufficient to reduce the chance of outgrowth from a single cell to a very low probability. Our findings suggest that lower antibiotic concentrations than those required to clear a large resistant population may be sufficient to prevent, with high probability, outgrowth of initially rare resistant mutants.

A better understanding of how antibiotic exposure impacts the evolution of resistance in bacterial populations is crucial for designing more sustainable treatment strategies. The conventional approach to this question is to measure the range of concentrations over which resistant strain(s) are selectively favored over a sensitive strain. Here, we instead investigate how antibiotic concentration impacts the initial establishment of resistance from single cells, mimicking the clonal expansion of a resistant lineage following mutation or horizontal gene transfer. Using two Pseudomonas aeruginosa strains carrying resistance plasmids, we show that single resistant cells have <5% probability of detectable outgrowth at antibiotic concentrations as low as one-eighth of the resistant strain’s minimum inhibitory concentration (MIC). This low probability of establishment is due to detrimental effects of antibiotics on resistant cells, coupled with the inherently stochastic nature of cell division and death on the single-cell level, which leads to loss of many nascent resistant lineages. Our findings suggest that moderate doses of antibiotics, well below the MIC of resistant strains, may effectively restrict de novo emergence of resistance even though they cannot clear already-large resistant populations.

Translating antibiotic prescribing into antibiotic resistance in the environment: A hazard characterisation case study

The environment receives antibiotics through a combination of direct application (e.g., aquaculture and fruit production), as well as indirect release through pharmaceutical manufacturing, sewage and animal manure. Antibiotic concentrations in many sewage-impacted rivers are thought to be sufficient to select for antibiotic resistance genes. Yet, because antibiotics are nearly always found associated with antibiotic-resistant faecal bacteria in wastewater, it is difficult to distinguish the selective role of effluent antibiotics within a 'sea' of gut-derived resistance genes. Here we examine the potential for macrolide and fluoroquinolone prescribing in England to select for resistance in the River Thames catchment, England. We show that 64% and 74% of the length of the modelled catchment is chronically exposed to putative resistance-selecting concentrations (PNEC) of macrolides and fluoroquinolones, respectively. Under current macrolide usage, 115 km of the modelled River Thames catchment (8% of total length) exceeds the PNEC by 5-fold. Similarly, under current fluoroquinolone usage, 223 km of the modelled River Thames catchment (16% of total length) exceeds the PNEC by 5-fold. Our results reveal that if reduced prescribing was the sole mitigating measure, that macrolide and fluoroquinolone prescribing would need to decline by 77% and 85%, respectively, to limit resistance selection in the catchment. Significant reductions in antibiotic prescribing are feasible, but innovation in sewage-treatment will be necessary for achieving substantially-reduced antibiotic loads and inactivation of DNA-pollution from resistant bacteria. Greater confidence is needed in current risk-based targets for antibiotics, particularly in mixtures, to better inform environmental risk assessments and mitigation.

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

The search for optimal predictors of anti-mutant effects remains a pressing problem in studies of antibiotic-associated bacterial resistance. To relate the emergence of bacterial resistance with the antibiotic mutant prevention concentration (MPC), a novel integral parameter - the area around the resistance threshold, i.e. MPC level (AAMPC) is proposed. The AAMPC is the algebraic sum of the area under the antibiotic concentration-time curve that is above the MPC (positive area) and the area above the concentration-time curve that is under the MPC (negative area). To assess the predictive performance of AAMPC, the enrichment of resistant Staphylococcus aureus was studied by simulating treatment with daptomycin and rifampicin alone and in combination in an in vitro dynamic model. The enhanced anti-mutant effects of the antibiotic combinations were due to lowering the negative 24-h AAMPCs. These findings suggest that a novel MPC-related parameter is a reliable predictor of mutant enrichment.

Concentration-dependent enrichment of resistant Enterococcus faecium exposed to linezolid in an in vitro dynamic model

To explore the relationship between pharmacokinetic variables and enterococcal resistance to linezolid, a vancomycin-resistant strain whose mutant prevention concentration (MPC) exceeded the MIC by two fold was selected among six clinical isolates of Enterococcus faecium. The selected strain was exposed to simulated pharmacokinetics of twice-daily linezolid for five days. Mutants resistant to 2 × MIC of the antibiotic were enriched at ratios of the 24-h area under the concentration-time curve (AUC₂₄) to the MIC of 15 and 30 h but not at 60 and 120 h. These observations could be explained by the different times when antibiotic concentrations exceed the MPC (T_>MPC): 0 to 14, 63 and 100% of the dosing interval. Using the area under the bacterial mutant concentration-time curve (AUBC_M) determined in this study and in previous work with other E. faecium strains (MPC/MIC 4), a strain-independent T_>MPC relationship with mutant enrichment was established.

Evolutionary epidemiology models to predict the dynamics of antibiotic resistance

The evolution of resistance to antibiotics is a major public health problem and an example of rapid adaptation under natural selection by antibiotics. The dynamics of antibiotic resistance within and between hosts can be understood in the light of mathematical models that describe the epidemiology and evolution of the bacterial population. "Between-host" models describe the spread of resistance in the host community, and in more specific settings such as hospitalized hosts (treated by antibiotics at a high rate), or farm animals. These models make predictions on the best strategies to limit the spread of resistance, such as reducing transmission or adapting the prescription of several antibiotics. Models can be fitted to epidemiological data in the context of intensive care units or hospitals to predict the impact of interventions on resistance. It has proven harder to explain the dynamics of resistance in the community at large, in particular because models often do not reproduce the observed coexistence of drug-sensitive and drug-resistant strains. "Within-host" models describe the evolution of resistance within the treated host. They show that the risk of resistance emergence is maximal at an intermediate antibiotic dose, and some models successfully explain experimental data. New models that include the complex host population structure, the interaction between resistance-determining loci and other loci, or integrating the within- and between-host levels will allow better interpretation of epidemiological and genomic data from common pathogens and better prediction of the evolution of resistance.

Urinary Tract Infection Antibiotic Resistance in the United States

Urinary tract infection (UTI) is one of the most common entities in medicine and affected patients present daily in a typical family medicine practice. The patients often present with the "classic symptoms" of dysuria and increased frequency, but sometimes they are asymptomatic or have a mixed picture. In most cases, an antibiotic is prescribed, and this practice is likely contributing to increasing worldwide antibiotic resistance. To help combat this problem, it is important that clinicians seek out their local bacterial resistance patterns and antibiograms, properly diagnose and treat UTI if indicated, and recognize their role in antibiotic stewardship.

Prevention of Surgical Site Infections and Biofilms: Pharmacokinetics of Subcutaneous Cefazolin and Metronidazole in a Tumescent Lidocaine Solution

BACKGROUND

Tumescent anesthesia antibiotic delivery (TAAD) consists of subcutaneous infiltration of antibiotic(s) dissolved tumescent lidocaine anesthesia. Tumescent lidocaine anesthesia contains lidocaine (≤ 1 g/L), epinephrine (≤ 1 mg/L), sodium bicarbonate (10 mEq/L) in 0.9% saline. Our aim was to measure cefazolin and metronidazole concentrations over time in subcutaneous tumescent interstitial fluid (TISF) after TAAD, in serum after TAAD and after intravenous antibiotic delivery (IVAD). We hypothesize that the pharmacokinetic/pharmacodynamic profiles of TAAD + IVAD are superior to IVAD alone for the prevention of surgical site infections and biofilms.

METHODS

Concentrations of cefazolin and metronidazole in TISF and serum following TAAD and in serum following IVAD were compared in 5 female volunteers. Subjects received cefazolin or cefazolin plus metronidazole by IVAD alone and by TAAD alone. One subject also received concomitant IVAD and TAAD of these 2 antibiotics. Sequential samples of serum or subcutaneous TISF were assayed for antibiotic concentration.

RESULTS

Cefazolin (1 g) by TAAD resulted in an area under the curve of the concentration-time profile and a maximum concentration (Cmax) in subcutaneous tissue that were 16.5 and 5.6 times greater than in serum following 1 g by IVAD. Metronidazole (500 mg) by TAAD resulted in an area under the curve and Cmax that were 8.1 and 24.7 times greater in TISF, than in serum after 500 mg by intravenous delivery. IVAD + TAAD resulted in superior antibiotic concentrations to IVAD alone.

CONCLUSIONS

TAAD + IVAD produced superior antibiotic bioavailability in both subcutaneous interstitial fluid and serum compared with IVAD alone. There was no evidence that TAAD of cefazolin and metronidazole poses a significant risk of harm to patients.

Predicting effects of antibiotic combinations using MICs determined at pharmacokinetically derived concentration ratios: in vitro model studies with linezolid- and rifampicin-exposed Staphylococcus aureus

To predict the effects of combined use of antibiotics on their pharmacodynamics, the susceptibility of Staphylococcus aureus to linezolid-rifampicin combinations was tested at concentration ratios equal to the ratios of 24-area under the concentration-time curve (AUC₂₄) simulated in an in vitro dynamic model. The linezolid MICs in combination with rifampicin decreased 8- to 67-fold. The rifampicin MICs were similar with or without linezolid. The enhanced activity of linezolid combined with rifampicin increased the AUC₂₄/MIC ratios and provided more pronounced antibacterial effects compared with single treatments. The areas between the control growth and time-kill curves (ABBCs) determined in combined and single treatments with linezolid were plotted against AUC₂₄/MIC on the same graph (r² 0.94). These findings suggest that the effects of linezolid-rifampicin combinations can be predicted by AUC₂₄/MICs of linezolid using its MIC determined at pharmacokinetically derived linezolid-to-rifampicin concentration ratios.