| Literature DB >> 32568322 |
Martin Schulz1, Silvia Calabrese, Florian Hausladen, Holger Wurm, Dominik Drossart, Karl Stock, Anna M Sobieraj, Fritz Eichenseher, Martin J Loessner, Mathias Schmelcher, Anja Gerhardts, Ulrike Goetz, Marina Handel, Annerose Serr, Georg Haecker, Jia Li, Mara Specht, Philip Koch, Martin Meyer, Philipp Tepper, Raimund Rother, Michael Jehle, Simon Wadle, Roland Zengerle, Felix von Stetten, Nils Paust, Nadine Borst.
Abstract
We present an automated point-of-care testing (POCT) system for rapid detection of species- and resistance markers in methicillin-resistant Staphylococcus aureus (MRSA) at the level of single cells, directly from nasal swab samples. Our novel system allows clear differentiation between MRSA, methicillin-sensitive S. aureus (MSSA) and methicillin-resistant coagulase-negative staphylococci (MR-CoNS), which is not the case for currently used real-time quantitative PCR based systems. On top, the novel approach outcompetes the culture-based methods in terms of its short time-to-result (1 h vs. up to 60 h) and reduces manual labor. The walk-away test is fully automated on the centrifugal microfluidic LabDisk platform. The LabDisk cartridge comprises the unit operations swab-uptake, reagent pre-storage, distribution of the sample into 20 000 droplets, specific enzymatic lysis of Staphylococcus spp. and recombinase polymerase amplification (RPA) of species (vicK) - and resistance (mecA) -markers. LabDisk actuation, incubation and multi-channel fluorescence detection is demonstrated with a clinical isolate and spiked nasal swab samples down to a limit of detection (LOD) of 3 ± 0.3 CFU μl-1 for MRSA. The novel approach of the digital single cell detection is suggested to improve hospital admission screening, timely decision making, and goal-oriented antibiotic therapy. The implementation of a higher degree of multiplexing is required to translate the results into clinical practice.Entities:
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Year: 2020 PMID: 32568322 DOI: 10.1039/d0lc00294a
Source DB: PubMed Journal: Lab Chip ISSN: 1473-0189 Impact factor: 6.799