Multiplex detection of the big five carbapenemase genes using solid-phase recombinase polymerase amplification

Johnson, Christopher L. and Setterfield, Matthew A. and Hassanain, Waleed A. and Wipat, Anil and Pocock, Matthew and Faulds, Karen and Graham, Duncan and Keegan, Neil (2024) Multiplex detection of the big five carbapenemase genes using solid-phase recombinase polymerase amplification. Analyst, 149 (5). pp. 1527-1536. ISSN 0003-2654 (https://doi.org/10.1039/d3an01747h)

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Abstract

Five carbapenemase enzymes, coined the ‘big five’, have been identified as the biggest threat to worldwide antibiotic resistance based on their broad substrate affinity and global prevalence. Here we show the development of a molecular detection method for the gene sequences from the five carbapenemases utilising the isothermal amplification method of recombinase polymerase amplification (RPA). We demonstrate the successful detection of each of the big five carbapenemase genes with femtomolar detection limits using a spatially separated multiplex amplification strategy. The approach uses tailed oligonucleotides for hybridisation, reducing the complexity and cost of the assay compared to classical RPA detection strategies. The reporter probe, horseradish peroxidase, generates the measureable output on a benchtop microplate reader, but more notably, our study leverages the power of a portable Raman spectrometer, enabling up to a 19-fold enhancement in the limit of detection. Significantly, the development approach employed a solid-phase RPA format, wherein the forward primers targeting each of the five carbapenemase genes are immobilised to a streptavidin-coated microplate. The adoption of this solid-phase methodology is pivotal for achieving a successful developmental pathway when employing this streamlined approach. The assay takes 2 hours until result, including a 40 minutes RPA amplification step at 37 °C. This is the first example of using solid-phase RPA for the detection of the big five and represents a milestone towards the developments of an automated point-of-care diagnostic for the big five using RPA.

ORCID iDs

Johnson, Christopher L., Setterfield, Matthew A., Hassanain, Waleed A. ORCID logoORCID: https://orcid.org/0000-0002-1533-4818, Wipat, Anil, Pocock, Matthew, Faulds, Karen ORCID logoORCID: https://orcid.org/0000-0002-5567-7399, Graham, Duncan ORCID logoORCID: https://orcid.org/0000-0002-6079-2105 and Keegan, Neil;