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Rodriguez-Manzano, J.

Publications and source records attributed to Rodriguez-Manzano, J..

2 recordsLinked to original sources

Simultaneous single-channel multiplex and quantification of carbapenem-resistant genes using multidimensional standard curves

Multiplexing and absolute quantification of nucleic acids, both have, in their own right, significant and extensive use in biomedical related fields, especially in point-of-care applications. Currently, the ability to detect several nucleic acid targets in a single-reaction scales linearly with the number of targets; an expensive and time-consuming feat. Here, we propose a new methodology based on multidimensional standard curves that extends the use of real-time PCR data obtained by common qPCR instruments. By applying this novel methodology, we achieve simultaneous single-channel multiplexing and enhanced quantification of multiple targets using only real-time amplification data. This is obtained without the need of fluorescent probes, agarose gels, melting curves or sequencing analysis. Given the importance and demand for tackling challenges in antimicrobial resistance, the proposed method is applied to the four most prominent carbapenem-resistant genes: blaOXA-48, blaNDM, blaVIM and blaKPC, which account for 97% of the UKs reported carbapenemase-producing Enterobacteriaceae.

microbiology

A framework for analysis of real-time nucleic acid amplification data using novel multidimensional standard curves

Research into improving methods for absolute quantification of nucleic acids using standard curves has plateaued despite its positive, far-reaching impact on biomedical applications and clinical diagnostics. Currently, the mathematics involved in this mature area is restricted by the simplicity of conventional standard curves such as the gold standard cycle-threshold (Ct) method. Here, we propose a novel framework that expands current methods into multidimensional space and opens the door for more complex mathematical techniques, signal processing and machine learning to be implemented. The heart of this work revolves around two new concepts: the multidimensional standard curve and its home - the feature space. This work has been validated using phage lambda DNA and standard qPCR instruments. We show that the capabilities of standard curves can be extended in order to simultaneously: enhance absolute quantification, detect outliers and provide insights into the intersection between molecular biology and amplification data. This work and its vision aims to maximise the information extracted from amplification data using current instruments without increasing the cost or complexity of existing diagnostic settings.

bioinformatics