Infections by Gram-negative pathogens represent a major health care issue of growing concern due to a striking lack of novel antibacterial agents over the course of the last decades. The main scientific problem behind the rational optimization of novel antibiotics is our limited understanding of small molecule translocation into, and their export from, the target compartments of Gram-negative species. To address this issue, a versatile, label-free assay to determine the intracellular localization and concentration of a given compound has been developed for Escherichia coli and its efflux-impaired ΔTolC mutant. The assay applies a fractionation procedure to antibiotic-treated bacterial cells to obtain periplasm, cytoplasm, and membrane fractions of high purity, as demonstrated by Western Blots of compartment-specific marker proteins. This is followed by an LC-MS/MS-based quantification of antibiotic content in each compartment. Antibiotic amounts could be converted to antibiotic concentrations by assuming that an E. coli cell is a cylinder flanked by two half spheres and calculating the volumes of bacterial compartments. The quantification of antibiotics from different classes, namely ciprofloxacin, tetracycline, trimethoprim, and erythromycin, demonstrated pronounced differences in uptake quantities and distribution patterns across the compartments. For example, in the case of ciprofloxacin, a higher amount of compound was located in the cytoplasm than in the periplasm (592 ± 50 pg vs 277 ± 13 pg per 3.9 × 109 cells), but owing to the smaller volume of the periplasmic compartment, its concentration in the cytoplasm was much lower (37 ± 3 vs 221 ± 10 pg/μL for the periplasm). For erythromycin and tetracycline, differences in MICs between WT and ΔTolC mutant strains were not reflected by equal differences in uptake, illustrating that additional experimental data are needed to predict antibiotic efficacy. We believe that our assay, providing the antibiotic concentration at the compartment in which the drug target is expressed, constitutes an essential piece of information for a more rational optimization of novel antibiotics against Gram-negative infections.