Queuing up for resistance testing

See allHide authors and affiliations

Science Translational Medicine  06 Sep 2017:
Vol. 9, Issue 406, eaao6118
DOI: 10.1126/scitranslmed.aao6118


Antibiotic resistance in Escherichia coli can be assessed by real-time imaging of bacterial replication in a microfluidics system.

In the past few years, there have been exciting advances to shorten turnaround time to identify disease-causing pathogens in clinical specimens. Antibiotic resistance testing is often a two-stage process, requiring the generation of a pure culture before resistance testing is performed. Automated antibiotic resistance testing platforms are an expanding field of interest. In a recent article in Proceedings of the National Academy of Sciences, Baltekin and colleagues outlined how bacterial replication can be observed and quantitated in real time to determine antibiotic resistance.

A microfluidic chip composed of silicon elastomer and glass was designed with parallel “cell traps” with size optimized to trap Escherichia coli. After loading, fluids flow through these cell traps, but the bacteria are trapped in a line by a constriction at the “out” end of the trap. Alternating cell traps receive one of two fluid streams, which in this study contained growth media with or without antibiotic. Two-dimensional phase contrast images were obtained at intervals to determine if the cell trap was being filled with additional Escherichia coli during the experiment, connoting resistance to the antibiotic present in the growth media. This could be determined within 30 min from sample loading into the cell traps, comparing the antibiotic treated and untreated traps. Ciprofloxacin resistance or sensitivity was determined from 49 Escherichia coli culture isolates derived from clinical samples, with 100% concordance with resistance results determined by disk diffusion testing in a clinical microbiology laboratory.

The diameter of the microfluidics chamber is critical for proper alignment of the bacteria for the imaging and analysis and was optimized for Escherichia coli. Although Escherichia coli is a very common cause of urinary tract infections, it is not the only cause. Growth curves of Klebsiella pneumoniae and Staphylococcus saprophyticus, other common causes of UTI, were generated but did not show the same performance as for Escherichia coli. The article detailed limited assessments for direct testing from urine specimens, which would be the sample material for a point-of-care assay. Chip design and imaging algorithm components are in development to address contaminating organisms, polymicrobial bacteriuria, and clogging during loading of bacteria from a cell-rich urine sample. This study is a good example of how tools developed for basic science studies—in this case, Escherichia coli cell cycle research—can be adapted to address clinical and diagnostic challenges.

Highlighted Article

View Abstract

Navigate This Article