A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCR
This paper presents a fully automated point-of-care device for protein quantification using short-DNA aptamers, where no manual sample preparation is needed. The device is based on our novel aptamer-based methodology combined with real-time polymerase chain reaction (qPCR), which we employ for very...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-07-01
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| Series: | Biosensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-6374/12/7/537 |
| _version_ | 1797433780393213952 |
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| author | Francesca Romana Cavallo Khalid Baig Mirza Sara de Mateo Luca Miglietta Jesus Rodriguez-Manzano Konstantin Nikolic Christofer Toumazou |
| author_facet | Francesca Romana Cavallo Khalid Baig Mirza Sara de Mateo Luca Miglietta Jesus Rodriguez-Manzano Konstantin Nikolic Christofer Toumazou |
| author_sort | Francesca Romana Cavallo |
| collection | DOAJ |
| description | This paper presents a fully automated point-of-care device for protein quantification using short-DNA aptamers, where no manual sample preparation is needed. The device is based on our novel aptamer-based methodology combined with real-time polymerase chain reaction (qPCR), which we employ for very sensitive protein quantification. DNA amplification through qPCR, sensing and real-time data processing are seamlessly integrated into a point-of-care device equipped with a disposable cartridge for automated sample preparation. The system’s modular nature allows for easy assembly, adjustment and expansion towards a variety of biomarkers for applications in disease diagnostics and personalised medicine. Alongside the device description, we also present a new algorithm, which we named PeakFluo, to perform automated and real-time quantification of proteins. PeakFluo achieves better linearity than proprietary software from a commercially available qPCR machine, and it allows for early detection of the amplification signal. Additionally, we propose an alternative way to use the proposed device beyond the quantitative reading, which can provide clinically relevant advice. We demonstrate how a convolutional neural network algorithm trained on qPCR images can classify samples into high/low concentration classes. This method can help classify obese patients from their leptin values to optimise weight loss therapies in clinical settings. |
| first_indexed | 2024-03-09T10:21:58Z |
| format | Article |
| id | doaj.art-1dab9f0cdb274723afd5e441b4b61b0d |
| institution | Directory Open Access Journal |
| issn | 2079-6374 |
| language | English |
| last_indexed | 2024-03-09T10:21:58Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biosensors |
| spelling | doaj.art-1dab9f0cdb274723afd5e441b4b61b0d2023-12-01T21:57:15ZengMDPI AGBiosensors2079-63742022-07-0112753710.3390/bios12070537A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCRFrancesca Romana Cavallo0Khalid Baig Mirza1Sara de Mateo2Luca Miglietta3Jesus Rodriguez-Manzano 4Konstantin Nikolic5Christofer Toumazou6Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UKDepartment of Biotechnology and Medical Engineering, National Institute of Technology, Rourkela 769008, IndiaCentre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UKCentre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UKDepartment of Infectious Disease, Imperial College London, London SW7 2AZ, UKCentre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UKCentre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UKThis paper presents a fully automated point-of-care device for protein quantification using short-DNA aptamers, where no manual sample preparation is needed. The device is based on our novel aptamer-based methodology combined with real-time polymerase chain reaction (qPCR), which we employ for very sensitive protein quantification. DNA amplification through qPCR, sensing and real-time data processing are seamlessly integrated into a point-of-care device equipped with a disposable cartridge for automated sample preparation. The system’s modular nature allows for easy assembly, adjustment and expansion towards a variety of biomarkers for applications in disease diagnostics and personalised medicine. Alongside the device description, we also present a new algorithm, which we named PeakFluo, to perform automated and real-time quantification of proteins. PeakFluo achieves better linearity than proprietary software from a commercially available qPCR machine, and it allows for early detection of the amplification signal. Additionally, we propose an alternative way to use the proposed device beyond the quantitative reading, which can provide clinically relevant advice. We demonstrate how a convolutional neural network algorithm trained on qPCR images can classify samples into high/low concentration classes. This method can help classify obese patients from their leptin values to optimise weight loss therapies in clinical settings.https://www.mdpi.com/2079-6374/12/7/537point-of-carenoise minimisationqPCRalgorithmdiagnosticsprotein quantification |
| spellingShingle | Francesca Romana Cavallo Khalid Baig Mirza Sara de Mateo Luca Miglietta Jesus Rodriguez-Manzano Konstantin Nikolic Christofer Toumazou A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCR Biosensors point-of-care noise minimisation qPCR algorithm diagnostics protein quantification |
| title | A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCR |
| title_full | A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCR |
| title_fullStr | A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCR |
| title_full_unstemmed | A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCR |
| title_short | A Point-of-Care Device for Fully Automated, Fast and Sensitive Protein Quantification via qPCR |
| title_sort | point of care device for fully automated fast and sensitive protein quantification via qpcr |
| topic | point-of-care noise minimisation qPCR algorithm diagnostics protein quantification |
| url | https://www.mdpi.com/2079-6374/12/7/537 |
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