Waging War on Resistance

Multi-drug-resistant infections are a problem everywhere, but nowhere so much as in close quarters like hospitals, prisons and military environments. They’re a particularly significant concern in combat-related injuries, where wounded soldiers often exhibit a range of pathogens that don’t respond to antibiotics. Although we do have a way of tackling this challenge – namely, culture-directed treatment – it requires the growth of a positive culture, which can take 48 hours or more. Delaying treatment by this long in a patient with injuries and related drug-resistant infections can have disastrous consequences. So what’s the alternative?

Connie Price, chief medical officer at Denver Health and a professor of medicine at the University of Colorado School of Medicine, has developed a new approach that may significantly speed up multi-drug-resistant disease diagnosis. The technique makes use of multiplexed automated digital microscopy (MADM), a type of imaging that can rapidly identify and even quantify pathogens. During their studies, Price and her colleagues have been able to spot a wide variety of treatment-resistant bacteria including Staphylococcus, Klebsiella, Enterobacter, E. coli and more – all within one hour, and with a sensitivity and specificity exceeding 97 percent (1). In fact, when applied to blood, respiratory and infected tissue samples from soldiers suffering multi-drug-resistant infections, MADM has shown an ability to analyze bacterial populations, differentiate between phenotypes, and characterize heterogeneous and inducible resistance mechanisms based on only four hours’ growth (2). With detailed results in such short amounts of time, Price hopes that their MADM-based method can save hours – and, more importantly, lives.

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References

1. IS Douglas et al., “Rapid automated microscopy for microbiological surveillance of ventilator-associated pneumonia”, Am J Respir Crit Care Med, 191, 566–573 (2015). PMID: 25585163. CS Price et al., “Rapid antibiotic susceptibility phenotypic characterization of Staphylococcus aureus using automated microscopy of small numbers of cells”, J Microbiol Methods, 98, 50–58 (2014). PMID: 24393790.

About the Author(s)

Michael Schubert

While obtaining degrees in biology from the University of Alberta and biochemistry from Penn State College of Medicine, I worked as a freelance science and medical writer. I was able to hone my skills in research, presentation and scientific writing by assembling grants and journal articles, speaking at international conferences, and consulting on topics ranging from medical education to comic book science. As much as I’ve enjoyed designing new bacteria and plausible superheroes, though, I’m more pleased than ever to be at Texere, using my writing and editing skills to create great content for a professional audience.

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