Many patients with severe infections receive inappropriate empirical treatment, and rapid detection of bacterial antibiotic susceptibility can improve clinical outcome and reduce mortality. To this end, we have developed a multiplex fluidic chip for rapid phenotypic antibiotic susceptibility testing of bacteria. A total of 21 clinical isolates of Escherichia coli, Klebsiella pneumoniae, and Staphylococcus aureus were acquired from the EUCAST Development Laboratory and tested against amikacin, ceftazidime, and meropenem (Gram-negative bacteria) or gentamicin, ofloxacin, and tetracycline (Gram-positive bacteria). The bacterial samples were mixed with agarose and loaded in an array of growth chambers in the chip where bacterial microcolony growth was monitored over time using automated image analysis. MIC values were automatically obtained by tracking the growth rates of individual microcolonies in different regions of antibiotic gradients. Stable MIC values were obtained within 2 to 4 h, and the results showed categorical agreement with reference MIC values as determined by broth microdilution in 86% of the cases. IMPORTANCE Prompt and effective antimicrobial therapy is crucial for the management of patients with severe bacterial infections but is becoming increasingly difficult to provide due to emerging antibiotic resistance. The traditional methods for antibiotic susceptibility testing (AST) used in most clinical laboratories are reliable but slow with turnaround times of 2 to 3 days, which necessitates the use of empirical therapy with broad-spectrum antibiotics. There is a great need for fast and reliable AST methods that enable starting targeted treatment within a few hours to improve patient outcome and reduce the overuse of broad-spectrum antibiotics. The multiplex fluidic chip for phenotypic AST described in the present study may enable data on antimicrobial resistance within 2 to 4 h, allowing for an early initiation of appropriate antibiotic therapy.
Antibiotic combination therapies are important for the efficient treatment of many types of infections, including those caused by antibiotic-resistant pathogens. Combination treatment strategies are typically used under the assumption that synergies are conserved across species and strains, even though recent results show that the combined treatment effect is determined by specific drug-strain interactions that can vary extensively and unpredictably, both between and within bacterial species. To address this problem, we present a new method in which antibiotic synergy is rapidly quantified on a case-by-case basis, allowing for improved combination therapy. The novel CombiANT methodology consists of a 3D-printed agar plate insert that produces defined diffusion landscapes of 3 antibiotics, permitting synergy quantification between all 3 antibiotic pairs with a single test. Automated image analysis yields fractional inhibitory concentration indices (FICis) with high accuracy and precision. A technical validation with 3 major pathogens, Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus, showed equivalent performance to checkerboard methodology, with the advantage of strongly reduced assay complexity and costs for CombiANT. A synergy screening of 10 antibiotic combinations for 12 E. coli urinary tract infection (UTI) clinical isolates illustrates the need for refined combination treatment strategies. For example, combinations of trimethoprim (TMP) + nitrofurantoin (NIT) and TMP + mecillinam (MEC) showed synergy, but only for certain individual isolates, whereas MEC + NIT combinations showed antagonistic interactions across all tested strains. These data suggest that the CombiANT methodology could allow personalized clinical synergy testing and largescale screening. We anticipate that CombiANT will greatly facilitate clinical and basic research of antibiotic synergy.
Time-lapse imaging is a powerful tool for studying cellular dynamics and cell behavior over long periods of time to acquire detailed functional information. However, commercially available time-lapse imaging systems are expensive and this has limited a broader implementation of this technique in low-resource environments. Further, the availability of time-lapse imaging systems often present workflow bottlenecks in well-funded institutions. To address these limitations we have designed a modular and affordable time-lapse imaging and incubation system (ATLIS). The ATLIS enables the transformation of simple inverted microscopes into live cell imaging systems using custom-designed 3D-printed parts, a smartphone, and off-the-shelf electronic components. We demonstrate that the ATLIS provides stable environmental conditions to support normal cell behavior during live imaging experiments in both traditional and evaporation-sensitive microfluidic cell culture systems. Thus, the system presented here has the potential to increase the accessibility of time-lapse microscopy of living cells for the wider research community.
Generation of exact cell clusters in the CAGE chip allows for paracrine signaling studies in models of specific tissue niches.
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