Rapid Phenotypic Antibiotic Susceptibility Testing of Uropathogens Using Optical Signal Analysis on the Nanowell Slide

Abstract

Achieving fast antimicrobial susceptibility results is a primary goal in the fight against antimicrobial resistance. Standard antibiotic susceptibility testing (AST) takes, however, at least a day from patient sample to susceptibility profile. Here, we developed and clinically validated a rapid phenotypic AST based on a miniaturized nanotiter plate, the nanowell slide, that holds 672 wells in a 500 nl format for bacterial cultivation. The multitude of nanowells allows multiplexing with a panel of six antibiotics relevant for urinary tract infections. Inclusion of seven concentrations per antibiotic plus technical replicates enabled us to determine a precise minimum inhibitory concentration for 70 clinical uropathogenic Escherichia coli isolates. By combining optical recordings of bacterial growth with an algorithm for optical signal analysis, we calculated Tlag, the point of transition from lag to exponential phase, in each nanoculture. Algorithm-assisted analysis determined antibiotic susceptibility as early as 3 h 40 min. In comparison to standard disk diffusion assays, the nanowell AST showed a total categorical agreement of 97.9% with 2.6% major errors and 0% very major errors for all isolate-antibiotic combination tested. Taking advantage of the optical compatibility of the nanowell slide, we performed microscopy to illustrate its potential in defining susceptibility profiles based on bacterial morphotyping. The excellent clinical performance of the nanowell AST, combined with a short detection time, morphotyping, and the very low consumption of reagents clearly show the advantage of this phenotypic AST as a diagnostic tool in a clinical setting.

Nitrate Metabolism Modulates Biosynthesis of Biofilm Components in Uropathogenic Escherichia coli and Acts as a Fitness Factor During Experimental Urinary Tract Infection

“…Bacterial strains used in this study are listed in Supplementary Table S1. Clinical UPEC strains used in biofilm tests have been published (Veses-Garcia et al, 2018). Mutants were prepared in E. coli CFT073 using the λ-red recombination system (Datsenko and Wanner, 2000;Yu et al, 2000).…”

“…To study whether the observed changes in colony biofilm in response to nitrate was common among UPEC strains, we evaluated the colony biofilm morphotypes in a collection of 40 clinical UPEC isolates (Veses-Garcia et al, 2018). A palette of strain dependent phenotypes was seen when grown on CR LBNS agar in the absence or presence of 20 mM nitrate, with 22 of 40 demonstrating a decrease in CR binding and/ or colony roughness (Supplementary Figure S1).…”

Three-dimensional label-free observation of individual bacteria upon antibiotic treatment using optical diffraction tomography

“…A basic approach to understanding the mechanism of antibiotics is to observe the phenotypic or physical response of bacteria to antibiotics. Phenotypic imaging has been one of the most popular diagnostic methods to achieve rapid antimicrobial susceptibility testing [5][6][7][8][9][10], as it provides an easy, low cost, real-time single-cell level examination. Furthermore, phenotypic analysis of bacteria has been exploited to extract useful information in various fields such as epidemiology and systems biology [11].…”

Modern Tools for Rapid Diagnostics of Antimicrobial Resistance

“…In nanowell AST, morphotyping with a phase contrast microscopy and optical signal analysis is performed for 0.5 μl cultures. Antibiotic susceptibility data can be obtained for uropathogens in <4 h. The system showed a total categorical agreement of 97.9% with standard disk diffusion assays, but a careful standardization of cell densities prior to cultivation was found necessary (Veses-Garcia et al, 2018 ).…”

“…They were able to define a precise minimum inhibitory concentration for 70 clinical E. coli isolates. Algorithm-assisted optical analysis determined antibiotic susceptibility in 3 h 40 min, showing a total categorical agreement of 97.9% (Veses-Garcia et al, 2018 ).…”