You will know by its tail: a method for quantification of heterogeneity of bacterial populations using single-cell MIC profiling

Abstract

Severe non-healing infections are often caused by multiple pathogens or by genetic variants of the same pathogen exhibiting different levels of antibiotic resistance. For example, polymicrobial diabetic foot infections double the risk of amputation compared to monomicrobial infections. Although these infections lead to increased morbidity and mortality, standard antimicrobial susceptibility methods are designed for homogenous samples and are impaired in quantifying heteroresistance. Here, we propose a droplet-based label-free method for quantifying the antibiotic response of the entire population at the single-cell level. We used Pseudomonas aeruginosa and Staphylococcus aureus samples to confirm that the shape of the profile informs about the coexistence of diverse bacterial subpopulations, their sizes, and antibiotic heteroresistance. These profiles could therefore indicate the outcome of antibiotic treatment in terms of the size of remaining subpopulations. Moreover, we studied phenotypic variants of a S. aureus strain to confirm that the profile can be used to identify tolerant subpopulations, such as small colony variants, associated with increased risks for the development of persisting infections. Therefore, the profile is a versatile instrument for quantifying the size of each bacterial subpopulation within a specimen as well as their individual and joined heteroresistance.