Biology subjects

Rodriguez-Manzano, J.

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

5 recordsLinked to original sources

bioRxiv2022

Electricity-free nucleic acid extraction method from dried blood spots on filter paper for point-of-care diagnostics

BackgroundNucleic acid extraction is a crucial step for molecular biology applications, being a determinant for any diagnostic test procedure. Dried blood spots (DBS) have been used for decades for serology, drug monitoring, environmental investigations, and molecular studies. Nevertheless, nucleic acid extraction from DBS remains one of the main challenges to translate them to the point-of-care (POC). MethodWe have developed a fast nucleic acid extraction (NAE) method from DBS which is electricity-free and relies on cellulose filter papers (DBSFP). The performance of NAE was assessed with loop-mediated isothermal amplification (LAMP), targeting the human reference gene beta-actin. The developed method was evaluated against FTA cards and magnetic bead-based purification, using time-to-positive (min) for comparative analysis. We optimised and validated the developed method for elution (eluted disk) and disk directly in the reaction (in-situ disk), RNA and DNA detection, and whole blood stored in anticoagulants (K2EDTA and lithium heparin). Furthermore, the compatibility of DBSFP with colourimetric detection was studied to show the transferability to the POC. ResultsThe proposed DBSFP is based on grade 3 filter paper pre-treated with 8% (v/v) igepal surfactant, 1 min washing step with PBS 1X and elution in TE 1X buffer after 5 min incubation at room temperature, enabling NAE under 7 min. Obtained results were comparable to gold standard methods across tested matrices, targets and experimental conditions, demonstrating the versatility of the methodology. Lastly, eluted disk colourimetric detection was achieved with a sample-to-result turnaround time under 35 min. ConclusionsThe developed method is a fast, electricity-free, and low-cost solution for NAE from DBSFP enabling molecular testing in virtually any POC setting.

molecular biology↗

bioRxiv2022

An adaptive filtering framework for non-specific and inefficient reactions in multiplex digital PCR based on sigmoidal trends

Real-time digital PCR (qdPCR) coupled with artificial intelligence has shown the potential of unlocking scientific breakthroughs, particularly in the field of molecular diagnostics for infectious diseases. One of the most promising applications is the use of machine learning (ML) methods to enable single fluorescent channel PCR multiplex by extracting target-specific kinetic and thermodynamic information contained in amplification curves. However, the robustness of such methods can be affected by the presence of undesired amplification events and nonideal reaction conditions. Therefore, here we proposed a novel framework to filter non-specific and low efficient reactions from qdPCR data using outlier detection algorithms purely based on sigmoidal trends of amplification curves. As a proof-of-concept, this framework is implemented to improve the classification performance of the recently reported ML-based Amplification Curve Analysis (ACA), using available data from a previous publication where the ACA method was used to screen carbapenemase-producing organisms in clinical isolates. Furthermore, we developed a novel strategy, named Adaptive Mapping Filter (AMF), to consider the variability of positive counts in digital PCR. Over 152,000 amplification events were analyzed. For the positive reactions, filtered and unfiltered amplification curves were evaluated by comparing against melting peak distribution, proving that abnormalities (filtered out data) are linked to shifted melting distribution or decreased PCR efficiency. The ACA was applied to compare classification accuracies before and after AMF, showing an improved sensitivity of 1.18% for inliers and 20% for outliers (p-value < 0.0001). This work explores the correlation between kinetics of amplification curves and thermodynamics of melting curves and it demonstrates that filtering out non-specific or low efficient reactions can significantly improve the classification accuracy for cutting edge multiplexing methodologies.

molecular biology↗

bioRxiv2019

Quantitative and rapid Plasmodium falciparum malaria diagnosis and artemisinin-resistance detection using a CMOS Lab-on-Chip platform

Early and accurate diagnosis of malaria and drug-resistance is essential to effective disease management. Available rapid malaria diagnostic tests present limitations in analytical sensitivity, drug-resistant testing and/or quantification. Conversely, diagnostic methods based on nucleic acid amplification stepped forwards owing to their high sensitivity, specificity and robustness. Nevertheless, these methods commonly rely on optical measurements and complex instrumentation which limit their applicability in resource-poor, point-of-care settings. This paper reports the specific, quantitative and fully-electronic detection of Plas-modium falciparum, the predominant malaria-causing parasite worldwide, using a Lab-on-Chip platform developed in-house. Furthermore, we demonstrate on-chip detection of C580Y, the most prevalent single-nucleotide polymorphism associated to artemisinin-resistant malaria. Real-time non-optical DNA sensing is facilitated using Ion-Sensitive Field-Effect Transistors, fabricated in unmodified complementary metal-oxide-semiconductor technology, coupled with loop-mediated isothermal amplification. This work holds significant potential for the development of a fully portable and quantitative malaria diagnostic that can be used as a rapid point-of-care test.

bioengineering↗

bioRxiv2018

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↗

bioRxiv2018

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↗