An optimized method for the detection and spatial distribution of aminoglycoside and vancomycin antibiotics in tissue
Ning Wang1, Véronique Dartois1,2, Claire L Carter1
1Center for Discovery and Innovation, Hackensack Meridian Health, Nutley, New Jersey, USA.
Abstract:
Suboptimal antibiotic dosing has been identified as one of the key drivers in the development of multidrug-resistant (MDR) bacteria that have become a global health concern. Aminoglycosides and vancomycin are broad-spectrum antibiotics used to treat critically ill patients infected by a variety of MDR bacterial species. Resistance to these antibiotics is becoming more prevalent. In order to design proper antibiotic regimens that maximize efficacy and minimize the development of resistance, it is pivotal to obtain the in situ pharmacokinetic-pharmacodynamic profiles at the sites of infection. Mass spectrometry imaging (MSI) is the ideal technique to achieve this. Aminoglycosides, due to their structure, suffer from poor ionization efficiency. Additionally, ion suppression effects by endogenous molecules greatly inhibit the detection of aminoglycosides and vancomycin at therapeutic levels. In the current study, an optimized method was developed that enabled the detection of these antibiotics by MSI. Tissue spotting experiments demonstrated a 5-, 15-, 35-, and 54-fold increase in detection sensitivity in the washed samples for kanamycin, amikacin, streptomycin, and vancomycin, respectively. Tissue mimetic models were utilized to optimize the washing time and matrix additive concentration. These studies determined the improved limit of detection was 40 to 5 μg/g of tissue for vancomycin and streptomycin, and 40 to 10 μg/g of tissue for kanamycin and amikacin. The optimized protocol was applied to lung sections from mice dosed with therapeutic levels of kanamycin and vancomycin. The washing protocol enabled the first drug distribution investigations of aminoglycosides and vancomycin by MSI, paving the way for site-of-disease antibiotic penetration studies.
Insights
Optimizing mass spectrometry imaging (MSI) allows sensitive detection of antibiotics like vancomycin and aminoglycosides in tissues. This breakthrough enables crucial studies on drug distribution at infection sites, aiding in the fight against multidrug-resistant bacteria.
Area of Science:
- Analytical Chemistry
- Pharmacology
- Microbiology
Background:
- Suboptimal antibiotic dosing drives multidrug-resistant (MDR) bacteria, a global health threat.
- Aminoglycosides and vancomycin are vital for treating MDR infections but face increasing resistance.
- Understanding in situ antibiotic pharmacokinetics is crucial for effective treatment and resistance mitigation.
Purpose of the Study:
- To develop an optimized mass spectrometry imaging (MSI) method for detecting aminoglycosides and vancomycin in tissues.
- To improve the sensitivity and limit of detection for these antibiotics using MSI.
- To enable the first drug distribution studies of these antibiotics at the site of infection using MSI.
Main Methods:
- Optimization of a washing protocol for tissue samples prior to MSI analysis.
- Utilized tissue spotting experiments to assess detection sensitivity.
- Employed tissue mimetic models to fine-tune washing parameters and matrix additive concentrations.
- Applied the optimized protocol to mouse lung sections.
Main Results:
- Achieved significant increases in detection sensitivity for kanamycin, amikacin, streptomycin, and vancomycin (5- to 54-fold).
- Established improved limits of detection: 5-10 μg/g for vancomycin and streptomycin, 10-40 μg/g for kanamycin and amikacin.
- Successfully applied the method to visualize drug distribution in mouse lung tissue.
Conclusions:
- The developed MSI method enhances the detection sensitivity of critical antibiotics in tissues.
- This optimized protocol facilitates the first in situ drug distribution studies for aminoglycosides and vancomycin.
- This research paves the way for essential antibiotic penetration studies at disease sites, crucial for combating MDR infections.
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