1
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Wan Y, Myall AC, Boonyasiri A, Bolt F, Ledda A, Mookerjee S, Weiße AY, Getino M, Turton JF, Abbas H, Prakapaite R, Sabnis A, Abdolrasouli A, Malpartida-Cardenas K, Miglietta L, Donaldson H, Gilchrist M, Hopkins KL, Ellington MJ, Otter JA, Larrouy-Maumus G, Edwards AM, Rodriguez-Manzano J, Didelot X, Barahona M, Holmes AH, Jauneikaite E, Davies F. Integrated analysis of patient networks and plasmid genomes reveals a regional, multi-species outbreak of carbapenemase-producing Enterobacterales carrying both blaIMP and mcr-9 genes. J Infect Dis 2024:jiae019. [PMID: 38245822 DOI: 10.1093/infdis/jiae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 01/02/2024] [Accepted: 01/19/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Carbapenemase-producing Enterobacterales (CPE) are challenging in healthcare, with resistance to multiple classes of antibiotics. This study describes the emergence of IMP-encoding CPE amongst diverse Enterobacterales species between 2016 and 2019 across a London regional network. METHODS We performed a network analysis of patient pathways, using electronic health records, to identify contacts between IMP-encoding CPE positive patients. Genomes of IMP-encoding CPE isolates were overlayed with patient contacts to imply potential transmission events. RESULTS Genomic analysis of 84 Enterobacterales isolates revealed diverse species (predominantly Klebsiella spp, Enterobacter spp, E. coli); 86% (72/84) harboured an IncHI2 plasmid carrying blaIMP and colistin resistance gene mcr-9 (68/72). Phylogenetic analysis of IncHI2 plasmids identified three lineages showing significant association with patient contacts and movements between four hospital sites and across medical specialities, which was missed on initial investigations. CONCLUSIONS Combined, our patient network and plasmid analyses demonstrate an interspecies, plasmid-mediated outbreak of blaIMPCPE, which remained unidentified during standard investigations. With DNA sequencing and multi-modal data incorporation, the outbreak investigation approach proposed here provides a framework for real-time identification of key factors causing pathogen spread. Plasmid-level outbreak analysis reveals that resistance spread may be wider than suspected, allowing more interventions to stop transmission within hospital networks.
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Affiliation(s)
- Yu Wan
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Ashleigh C Myall
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Adhiratha Boonyasiri
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Frances Bolt
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
- Centre for Antimicrobial Optimisation, Hammersmith Hospital, Imperial College London, Du Cane Road, London, United Kingdom
| | - Alice Ledda
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
- HCAI, Fungal, AMR, AMU & Sepsis Division, UK Health Security Agency, London, United Kingdom
| | | | - Andrea Y Weiße
- School of Biological Sciences, University of Edinburgh, Scotland, United Kingdom
- School of Informatics, University of Edinburgh, Scotland, United Kingdom
| | - Maria Getino
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Jane F Turton
- HCAI, Fungal, AMR, AMU & Sepsis Division, UK Health Security Agency, London, United Kingdom
| | - Hala Abbas
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Department of Microbiology, North West London Pathology, London, United Kingdom
| | - Ruta Prakapaite
- MRC Centre for Molecular Bacteriology and Infection, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Akshay Sabnis
- MRC Centre for Molecular Bacteriology and Infection, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | | | - Kenny Malpartida-Cardenas
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, United Kingdom
| | - Luca Miglietta
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, United Kingdom
| | - Hugo Donaldson
- Department of Microbiology, North West London Pathology, London, United Kingdom
| | - Mark Gilchrist
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Katie L Hopkins
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- HCAI, Fungal, AMR, AMU & Sepsis Division, UK Health Security Agency, London, United Kingdom
| | - Matthew J Ellington
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Reference Services Division, UK Health Security Agency, London, United Kingdom
| | - Jonathan A Otter
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Gerald Larrouy-Maumus
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, United Kingdom
| | - Andrew M Edwards
- MRC Centre for Molecular Bacteriology and Infection, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Jesus Rodriguez-Manzano
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Centre for Antimicrobial Optimisation, Hammersmith Hospital, Imperial College London, Du Cane Road, London, United Kingdom
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, United Kingdom
| | - Xavier Didelot
- School of Life Sciences and Department of Statistics, University of Warwick, United Kingdom
| | - Mauricio Barahona
- Department of Mathematics, Imperial College London, London, United Kingdom
| | - Alison H Holmes
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
- Centre for Antimicrobial Optimisation, Hammersmith Hospital, Imperial College London, Du Cane Road, London, United Kingdom
| | - Elita Jauneikaite
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Frances Davies
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London, United Kingdom
- Imperial College Healthcare NHS Trust, London, United Kingdom
- Department of Microbiology, North West London Pathology, London, United Kingdom
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Miglietta L, Chen Y, Luo Z, Xu K, Ding N, Peng T, Moniri A, Kreitmann L, Cacho-Soblechero M, Holmes A, Georgiou P, Rodriguez-Manzano J. Smart-Plexer: a breakthrough workflow for hybrid development of multiplex PCR assays. Commun Biol 2023; 6:922. [PMID: 37689821 PMCID: PMC10492832 DOI: 10.1038/s42003-023-05235-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 08/10/2023] [Indexed: 09/11/2023] Open
Abstract
Developing multiplex PCR assays requires extensive experimental testing, the number of which exponentially increases by the number of multiplexed targets. Dedicated efforts must be devoted to the design of optimal multiplex assays ensuring specific and sensitive identification of multiple analytes in a single well reaction. Inspired by data-driven approaches, we reinvent the process of developing and designing multiplex assays using a hybrid, simple workflow, named Smart-Plexer, which couples empirical testing of singleplex assays and computer simulation to develop optimised multiplex combinations. The Smart-Plexer analyses kinetic inter-target distances between amplification curves to generate optimal multiplex PCR primer sets for accurate multi-pathogen identification. In this study, the Smart-Plexer method is applied and evaluated for seven respiratory infection target detection using an optimised multiplexed PCR assay. Single-channel multiplex assays, together with the recently published data-driven methodology, Amplification Curve Analysis (ACA), were demonstrated to be capable of classifying the presence of desired targets in a single test for seven common respiratory infection pathogens.
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Affiliation(s)
- Luca Miglietta
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Yuwen Chen
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Zhi Luo
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Ke Xu
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Ning Ding
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Tianyi Peng
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Ahmad Moniri
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Louis Kreitmann
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Miguel Cacho-Soblechero
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Alison Holmes
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
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3
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Arkell P, Mairiang D, Songjaeng A, Malpartida-Cardenas K, Hill-Cawthorne K, Avirutnan P, Georgiou P, Holmes A, Rodriguez-Manzano J. Analytical and diagnostic performance characteristics of reverse-transcriptase loop-mediated isothermal amplification assays for dengue virus serotypes 1-4: A scoping review to inform potential use in portable molecular diagnostic devices. PLOS Glob Public Health 2023; 3:e0002169. [PMID: 37552632 PMCID: PMC10409275 DOI: 10.1371/journal.pgph.0002169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 06/20/2023] [Indexed: 08/10/2023]
Abstract
Dengue is a mosquito-borne disease caused by dengue virus (DENV) serotypes 1-4 which affects 100-400 million adults and children each year. Reverse-transcriptase (RT) quantitative polymerase chain reaction (qPCR) assays are the current gold-standard in diagnosis and serotyping of infections, but their use in low-middle income countries (LMICs) has been limited by laboratory infrastructure requirements. Loop-mediated isothermal amplification (LAMP) assays do not require thermocycling equipment and therefore could potentially be deployed outside laboratories and/or miniaturised. This scoping literature review aimed to describe the analytical and diagnostic performance characteristics of previously developed serotype-specific dengue RT-LAMP assays and evaluate potential for use in portable molecular diagnostic devices. A literature search in Medline was conducted. Studies were included if they were listed before 4th May 2022 (no prior time limit set) and described the development of any serotype-specific DENV RT-LAMP assay ('original assays') or described the further evaluation, adaption or implementation of these assays. Technical features, analytical and diagnostic performance characteristics were collected for each assay. Eight original assays were identified. These were heterogenous in design and reporting. Assays' lower limit of detection (LLOD) and linear range of quantification were comparable to RT-qPCR (with lowest reported values 2.2x101 and 1.98x102 copies/ml, respectively, for studies which quantified target RNA copies) and analytical specificity was high. When evaluated, diagnostic performance was also high, though reference diagnostic criteria varied widely, prohibiting comparison between assays. Fourteen studies using previously described assays were identified, including those where reagents were lyophilised or 'printed' into microfluidic channels and where several novel detection methods were used. Serotype-specific DENV RT-LAMP assays are high-performing and have potential to be used in portable molecular diagnostic devices if they can be integrated with sample extraction and detection methods. Standardised reporting of assay validation and diagnostic accuracy studies would be beneficial.
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Affiliation(s)
- Paul Arkell
- Centre for Antimicrobial Optimisation, Department of Infectious Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom
| | - Dumrong Mairiang
- Siriraj Center of Research Excellence in Dengue and Emerging Pathogens (SiCORE-Dengue), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Molecular Biology of Dengue and Flaviviruses Research Team, Medical Molecular Biotechnology Research Group, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Bangkok, Thailand
| | - Adisak Songjaeng
- Siriraj Center of Research Excellence in Dengue and Emerging Pathogens (SiCORE-Dengue), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Division of Dengue Hemorrhagic Fever Research, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Kenny Malpartida-Cardenas
- Centre for Antimicrobial Optimisation, Department of Infectious Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom
| | - Kerri Hill-Cawthorne
- Centre for Antimicrobial Optimisation, Department of Infectious Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom
| | - Panisadee Avirutnan
- Siriraj Center of Research Excellence in Dengue and Emerging Pathogens (SiCORE-Dengue), Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
- Molecular Biology of Dengue and Flaviviruses Research Team, Medical Molecular Biotechnology Research Group, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency (NSTDA), Bangkok, Thailand
- Division of Dengue Hemorrhagic Fever Research, Department of Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Pantelis Georgiou
- Centre for Antimicrobial Optimisation, Department of Infectious Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom
- Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
| | - Alison Holmes
- Centre for Antimicrobial Optimisation, Department of Infectious Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom
- David Price Evans Global Health and Infectious Disease Research Group, University of Liverpool, Liverpool, United Kingdom
| | - Jesus Rodriguez-Manzano
- Centre for Antimicrobial Optimisation, Department of Infectious Disease, Imperial College London, Hammersmith Hospital, London, United Kingdom
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4
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Jackson HR, Miglietta L, Habgood-Coote D, D’Souza G, Shah P, Nichols S, Vito O, Powell O, Davidson MS, Shimizu C, Agyeman PKA, Beudeker CR, Brengel-Pesce K, Carrol ED, Carter MJ, De T, Eleftheriou I, Emonts M, Epalza C, Georgiou P, De Groot R, Fidler K, Fink C, van Keulen D, Kuijpers T, Moll H, Papatheodorou I, Paulus S, Pokorn M, Pollard AJ, Rivero-Calle I, Rojo P, Secka F, Schlapbach LJ, Tremoulet AH, Tsolia M, Usuf E, Van Der Flier M, Von Both U, Vermont C, Yeung S, Zavadska D, Zenz W, Coin LJM, Cunnington A, Burns JC, Wright V, Martinon-Torres F, Herberg JA, Rodriguez-Manzano J, Kaforou M, Levin M. Diagnosis of Multisystem Inflammatory Syndrome in Children by a Whole-Blood Transcriptional Signature. J Pediatric Infect Dis Soc 2023; 12:322-331. [PMID: 37255317 PMCID: PMC10312302 DOI: 10.1093/jpids/piad035] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 05/30/2023] [Indexed: 06/01/2023]
Abstract
BACKGROUND To identify a diagnostic blood transcriptomic signature that distinguishes multisystem inflammatory syndrome in children (MIS-C) from Kawasaki disease (KD), bacterial infections, and viral infections. METHODS Children presenting with MIS-C to participating hospitals in the United Kingdom and the European Union between April 2020 and April 2021 were prospectively recruited. Whole-blood RNA Sequencing was performed, contrasting the transcriptomes of children with MIS-C (n = 38) to those from children with KD (n = 136), definite bacterial (DB; n = 188) and viral infections (DV; n = 138). Genes significantly differentially expressed (SDE) between MIS-C and comparator groups were identified. Feature selection was used to identify genes that optimally distinguish MIS-C from other diseases, which were subsequently translated into RT-qPCR assays and evaluated in an independent validation set comprising MIS-C (n = 37), KD (n = 19), DB (n = 56), DV (n = 43), and COVID-19 (n = 39). RESULTS In the discovery set, 5696 genes were SDE between MIS-C and combined comparator disease groups. Five genes were identified as potential MIS-C diagnostic biomarkers (HSPBAP1, VPS37C, TGFB1, MX2, and TRBV11-2), achieving an AUC of 96.8% (95% CI: 94.6%-98.9%) in the discovery set, and were translated into RT-qPCR assays. The RT-qPCR 5-gene signature achieved an AUC of 93.2% (95% CI: 88.3%-97.7%) in the independent validation set when distinguishing MIS-C from KD, DB, and DV. CONCLUSIONS MIS-C can be distinguished from KD, DB, and DV groups using a 5-gene blood RNA expression signature. The small number of genes in the signature and good performance in both discovery and validation sets should enable the development of a diagnostic test for MIS-C.
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Affiliation(s)
- Heather R Jackson
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Luca Miglietta
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Dominic Habgood-Coote
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Giselle D’Souza
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Priyen Shah
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Samuel Nichols
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Ortensia Vito
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Oliver Powell
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Maisey Salina Davidson
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Chisato Shimizu
- Department of Pediatrics, Rady Children’s Hospital and University of California San Diego, La Jolla, California, USA
| | - Philipp K A Agyeman
- Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Coco R Beudeker
- Department of Paediatric Infectious Diseases and Immunology, Wilhelmina Children’s Hospital, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Karen Brengel-Pesce
- Joint Research Unit Hospices Civils de Lyon-bioMérieux, Lyon Sud Hospital, Pierre-Bénite, France
| | - Enitan D Carrol
- Department of Clinical Infection Microbiology and Immunology, University of Liverpool Institute of Infection, Veterinary and Ecological Sciences, Liverpool, UK
| | - Michael J Carter
- Paediatric Intensive Care, Evelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- Department of Women and Children’s Health, School of Life Course Sciences, King’s College London, St Thomas’ Hospital, London, UK
| | - Tisham De
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Irini Eleftheriou
- Second Department of Paediatrics, National and Kapodistrian University of Athens (NKUA), School of Medicine, P. and A. Kyriakou Children’s Hospital, Athens, Greece
| | - Marieke Emonts
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
- Paediatric Infectious Diseases and Immunology Department, Newcastle upon Tyne Hospitals Foundation Trust, Great North Children’s Hospital, Newcastle upon Tyne, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Trust and Newcastle University, Newcastle upon Tyne, UK
| | - Cristina Epalza
- Pediatric Infectious Diseases Unit, Pediatric Department, Hospital Doce de Octubre, Madrid, Spain
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Ronald De Groot
- Department of Pediatrics, Division of Pediatric Infectious Diseases and Immunology and Laboratory of Infectious Diseases, Radboud Institute of Molecular Life Sciences, Radboudumc, Nijmegen, The Netherlands
| | - Katy Fidler
- Academic Department of Paediatrics, Royal Alexandra Children’s Hospital, University Hospitals Sussex, Brighton, UK
| | - Colin Fink
- Micropathology Ltd., University of Warwick, Warwick, UK
| | | | - Taco Kuijpers
- Department of Pediatric Immunology, Rheumatology, and Infectious Diseases, Emma Children’s Hospital, Amsterdam University Medical Centre, Amsterdam, The Netherlands
- Sanquin Research, Department of Blood Cell Research, and Landsteiner Laboratory, Amsterdam University Medical Centre, Amsterdam, The Netherlands
| | - Henriette Moll
- Department of Pediatrics, Erasmus MC Sophia Children’s Hospital, Rotterdam, The Netherlands
| | - Irene Papatheodorou
- Gene Expression Team, European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, UK
| | - Stephane Paulus
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford and the NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Marko Pokorn
- Division of Pediatrics, University Medical Centre Ljubljana and Medical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | - Andrew J Pollard
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford and the NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Irene Rivero-Calle
- Pediatrics Department, Translational Pediatrics and Infectious Diseases Section, Santiago de Compostela, Spain
- Genetics–Vaccines–Infectious Diseases and Pediatrics Research Group GENVIP, Instituto de Investigación Sanitaria de Santiago (IDIS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain
- Unidade de Xenética, Departamento de Anatomía Patolóxica e Ciencias Forenses, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, Galicia, Spain
- GenPoB Research Group, Instituto de Investigaciones Sanitarias (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain
| | - Pablo Rojo
- Pediatric Infectious Diseases Unit, Pediatric Department, Hospital Doce de Octubre, Madrid, Spain
| | - Fatou Secka
- Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine, Banjul, Gambia
| | - Luregn J Schlapbach
- Department of Intensive Care and Neonatology, and Children’s Research Center, University Children`s Hospital Zurich, Zurich, Switzerland
- Child Health Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Adriana H Tremoulet
- Department of Pediatrics, Rady Children’s Hospital and University of California San Diego, La Jolla, California, USA
| | - Maria Tsolia
- Second Department of Paediatrics, National and Kapodistrian University of Athens (NKUA), School of Medicine, P. and A. Kyriakou Children’s Hospital, Athens, Greece
| | - Effua Usuf
- Medical Research Council Unit, The Gambia at the London School of Hygiene and Tropical Medicine, Banjul, Gambia
| | - Michiel Van Der Flier
- Department of Paediatric Infectious Diseases and Immunology, Wilhelmina Children’s Hospital, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Ulrich Von Both
- Division of Pediatric Infectious Diseases, Department of Pediatrics, Dr von Hauner Children’s Hospital, University Hospital, LMU Munich, Munich, Germany
| | - Clementien Vermont
- Department of Paediatric Infectious Diseases and Immunology, Erasmus MC Sophia Children’s Hospital, Rotterdam, The Netherlands
| | - Shunmay Yeung
- Clinical Research Department, Faculty of Infectious and Tropical Disease, London School of Hygiene and Tropical Medicine, London, UK
| | - Dace Zavadska
- Department of Pediatrics, Children’s Clinical University Hospital, Rīga, Latvia
| | - Werner Zenz
- Department of General Paediatrics, University Clinic of Paediatrics and Adolescent Medicine, Medical University Graz, Austria
| | - Lachlan J M Coin
- Department of Microbiology and Immunology, University of Melbourne at The Peter Doherty Institute for Infection and Immunity, Melbourne, Australia
| | - Aubrey Cunnington
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Jane C Burns
- Department of Pediatrics, Rady Children’s Hospital and University of California San Diego, La Jolla, California, USA
| | - Victoria Wright
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Federico Martinon-Torres
- Pediatrics Department, Translational Pediatrics and Infectious Diseases Section, Santiago de Compostela, Spain
- Genetics–Vaccines–Infectious Diseases and Pediatrics Research Group GENVIP, Instituto de Investigación Sanitaria de Santiago (IDIS), Universidade de Santiago de Compostela (USC), Santiago de Compostela, Spain
- Unidade de Xenética, Departamento de Anatomía Patolóxica e Ciencias Forenses, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, Galicia, Spain
- GenPoB Research Group, Instituto de Investigaciones Sanitarias (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Galicia, Spain
| | - Jethro A Herberg
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | | | - Myrsini Kaforou
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
| | - Michael Levin
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, SW7 2AZ, UK
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5
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Malpartida-Cardenas K, Moser N, Ansah F, Pennisi I, Ahu Prah D, Amoah LE, Awandare G, Hafalla JCR, Cunnington A, Baum J, Rodriguez-Manzano J, Georgiou P. Sensitive Detection of Asymptomatic and Symptomatic Malaria with Seven Novel Parasite-Specific LAMP Assays and Translation for Use at Point-of-Care. Microbiol Spectr 2023; 11:e0522222. [PMID: 37158750 PMCID: PMC10269850 DOI: 10.1128/spectrum.05222-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 04/18/2023] [Indexed: 05/10/2023] Open
Abstract
Human malaria is a life-threatening parasitic disease with high impact in the sub-Saharan Africa region, where 95% of global cases occurred in 2021. While most malaria diagnostic tools are focused on Plasmodium falciparum, there is a current lack of testing non-P. falciparum cases, which may be underreported and, if undiagnosed or untreated, may lead to severe consequences. In this work, seven species-specific loop-mediated isothermal amplification (LAMP) assays were designed and evaluated against TaqMan quantitative PCR (qPCR), microscopy, and enzyme-linked immunosorbent assays (ELISAs). Their clinical performance was assessed with a cohort of 164 samples of symptomatic and asymptomatic patients from Ghana. All asymptomatic samples with a parasite load above 80 genomic DNA (gDNA) copies per μL of extracted sample were detected with the Plasmodium falciparum LAMP assay, reporting 95.6% (95% confidence interval [95% CI] of 89.9 to 98.5) sensitivity and 100% (95% CI of 87.2 to 100) specificity. This assay showed higher sensitivity than microscopy and ELISA, which were 52.7% (95% CI of 39.7 to 67%) and 67.3% (95% CI of 53.3 to 79.3%), respectively. Nine samples were positive for P. malariae, indicating coinfections with P. falciparum, which represented 5.5% of the tested population. No samples were detected as positive for P. vivax, P. ovale, P. knowlesi, or P. cynomolgi by any method. Furthermore, translation to the point-of-care was demonstrated with a subcohort of 18 samples tested locally in Ghana using our handheld lab-on-chip platform, Lacewing, showing comparable results to a conventional fluorescence-based instrument. The developed molecular diagnostic test could detect asymptomatic malaria cases, including submicroscopic parasitemia, and it has the potential to be used for point-of-care applications. IMPORTANCE The spread of Plasmodium falciparum parasites with Pfhrp2/3 gene deletions presents a major threat to reliable point-of-care diagnosis with current rapid diagnostic tests (RDTs). Novel molecular diagnostics based on nucleic acid amplification are needed to address this liability. In this work, we overcome this challenge by developing sensitive tools for the detection of Plasmodium falciparum and non-P. falciparum species. Furthermore, we evaluate these tools with a cohort of symptomatic and asymptomatic malaria patients and test a subcohort locally in Ghana. The findings of this work could lead to the implementation of DNA-based diagnostics to fight against the spread of malaria and provide reliable, sensitive, and specific diagnostics at the point of care.
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Affiliation(s)
- Kenny Malpartida-Cardenas
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Nicolas Moser
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Felix Ansah
- West African Centre for Cell Biology of Infectious Pathogens, Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Ghana
| | - Ivana Pennisi
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Diana Ahu Prah
- West African Centre for Cell Biology of Infectious Pathogens, Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Ghana
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Linda Eva Amoah
- West African Centre for Cell Biology of Infectious Pathogens, Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Ghana
- Immunology Department, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Ghana
| | - Gordon Awandare
- West African Centre for Cell Biology of Infectious Pathogens, Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Legon, Ghana
| | - Julius Clemence R. Hafalla
- Department of Infection Biology, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Immunology Department, Noguchi Memorial Institute for Medical Research, University of Ghana, Legon, Ghana
| | - Aubrey Cunnington
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Jake Baum
- Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, United Kingdom
- School of Biomedical Sciences, University of New South Wales Sydney, Sydney, Australia
| | - Jesus Rodriguez-Manzano
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
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6
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Malpartida-Cardenas K, Baum J, Cunnington A, Georgiou P, Rodriguez-Manzano J. A dual paper-based nucleic acid extraction method from blood in under ten minutes for point-of-care diagnostics. Analyst 2023. [PMID: 37265396 DOI: 10.1039/d3an00296a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Nucleic acid extraction (NAE) plays a crucial role for diagnostic testing procedures. For decades, dried blood spots (DBS) have been used for serology, drug monitoring, and molecular studies. However, extracting nucleic acids from DBS remains a significant challenge, especially when attempting to implement these applications to the point-of-care (POC). To address this issue, we have developed a paper-based NAE method using cellulose filter papers (DBSFP) that operates without the need for electricity (at room temperature). Our method allows for NAE in less than 7 min, and it involves grade 3 filter paper pre-treated with 8% (v/v) igepal surfactant, 1 min washing step with 1× PBS, and 5 min incubation at room temperature in 1× TE buffer. The performance of the methodology was assessed with loop-mediated isothermal amplification (LAMP), targeting the human reference gene beta-actin and the kelch 13 gene from P. falciparum. The developed method was evaluated against FTA cards and magnetic bead-based purification, using time-to-positive (min) for comparative analysis. Furthermore, we optimised our approach to take advantage of the dual functionality of the paper-based extraction, allowing for elution (eluted disk) as well as direct placement of the disk in the LAMP reaction (in situ disk). This flexibility extends to eukaryotic cells, bacterial cells, and viral particles. We successfully validated the method for RNA/DNA detection and demonstrated its compatibility with whole blood stored in anticoagulants. Additionally, we studied the compatibility of DBSFP with colorimetric and lateral flow detection, showcasing its potential for POC applications. Across various tested matrices, targets, and experimental conditions, our results were comparable to those obtained using gold standard methods, highlighting the versatility of our methodology. In summary, this manuscript presents a cost-effective solution for NAE from DBS, enabling molecular testing in virtually any POC setting. When combined with LAMP, our approach provides sample-to-result detection in under 35 minutes.
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Affiliation(s)
- Kenny Malpartida-Cardenas
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, UK.
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, UK
| | - Jake Baum
- Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, UK
- School of Medical Sciences, University of New South Wales, Australia
| | - Aubrey Cunnington
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, UK.
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, UK
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7
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Mao Y, Xu K, Miglietta L, Kreitmann L, Moser N, Georgiou P, Holmes A, Rodriguez-Manzano J. Deep Domain Adaptation Enhances Amplification Curve Analysis for Single-Channel Multiplexing in Real-Time PCR. IEEE J Biomed Health Inform 2023; 27:3093-3103. [PMID: 37028376 DOI: 10.1109/jbhi.2023.3257727] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
Data-driven approaches for molecular diagnostics are emerging as an alternative to perform an accurate and inexpensive multi-pathogen detection. A novel technique called Amplification Curve Analysis (ACA) has been recently developed by coupling machine learning and real-time Polymerase Chain Reaction (qPCR) to enable the simultaneous detection of multiple targets in a single reaction well. However, target classification purely relying on the amplification curve shapes faces several challenges, such as distribution discrepancies between different data sources (i.e., training vs testing). Optimisation of computational models is required to achieve higher performance of ACA classification in multiplex qPCR through the reduction of those discrepancies. Here, we proposed a novel transformer-based conditional domain adversarial network (T-CDAN) to eliminate data distribution differences between the source domain (synthetic DNA data) and the target domain (clinical isolate data). The labelled training data from the source domain and unlabelled testing data from the target domain are fed into the T-CDAN, which learns both domains' information simultaneously. After mapping the inputs into a domain-irrelevant space, T-CDAN removes the feature distribution differences and provides a clearer decision boundary for the classifier, resulting in a more accurate pathogen identification. Evaluation of 198 clinical isolates containing three types of carbapenem-resistant genes (blaNDM, blaIMP and blaOXA-48) illustrates a curve-level accuracy of 93.1% and a sample-level accuracy of 97.0% using T-CDAN, showing an accuracy improvement of 20.9% and 4.9% respectively. This research emphasises the importance of deep domain adaptation to enable high-level multiplexing in a single qPCR reaction, providing a solid approach to extend qPCR instruments' capabilities in real-world clinical applications.
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8
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Kreitmann L, Miglietta L, Xu K, Malpartida-Cardenas K, D'Souza G, Kaforou M, Brengel-Pesce K, Drazek L, Holmes A, Rodriguez-Manzano J. Next-generation molecular diagnostics: Leveraging digital technologies to enhance multiplexing in real-time PCR. Trends Analyt Chem 2023; 160:116963. [PMID: 36968318 PMCID: PMC7614363 DOI: 10.1016/j.trac.2023.116963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Real-time polymerase chain reaction (qPCR) enables accurate detection and quantification of nucleic acids and has become a fundamental tool in biological sciences, bioengineering and medicine. By combining multiple primer sets in one reaction, it is possible to detect several DNA or RNA targets simultaneously, a process called multiplex PCR (mPCR) which is key to attaining optimal throughput, cost-effectiveness and efficiency in molecular diagnostics, particularly in infectious diseases. Multiple solutions have been devised to increase multiplexing in qPCR, including single-well techniques, using target-specific fluorescent oligonucleotide probes, and spatial multiplexing, where segregation of the sample enables parallel amplification of multiple targets. However, these solutions are mostly limited to three or four targets, or highly sophisticated and expensive instrumentation. There is a need for innovations that will push forward the multiplexing field in qPCR, enabling for a next generation of diagnostic tools which could accommodate high throughput in an affordable manner. To this end, the use of machine learning (ML) algorithms (data-driven solutions) has recently emerged to leverage information contained in amplification and melting curves (AC and MC, respectively) - two of the most standard bio-signals emitted during qPCR - for accurate classification of multiple nucleic acid targets in a single reaction. Therefore, this review aims to demonstrate and illustrate that data-driven solutions can be successfully coupled with state-of-the-art and common qPCR platforms using a variety of amplification chemistries to enhance multiplexing in qPCR. Further, because both ACs and MCs can be predicted from sequence data using thermodynamic databases, it has also become possible to use computer simulation to rationalize and optimize the design of mPCR assays where target detection is supported by data-driven technologies. Thus, this review also discusses recent work converging towards the development of an end-to-end framework where knowledge-based and data-driven software solutions are integrated to streamline assay design, and increase the accuracy of target detection and quantification in the multiplex setting. We envision that concerted efforts by academic and industry scientists will help advance these technologies, to a point where they become mature and robust enough to bring about major improvements in the detection of nucleic acids across many fields.
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9
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Kuiper R, Wright VJ, Habgood-Coote D, Shimizu C, Huigh D, Tremoulet AH, van Keulen D, Hoggart CJ, Rodriguez-Manzano J, Herberg JA, Kaforou M, Tempel D, Burns JC, Levin M. Bridging a diagnostic Kawasaki disease classifier from a microarray platform to a qRT-PCR assay. Pediatr Res 2023; 93:559-569. [PMID: 35732822 PMCID: PMC9988687 DOI: 10.1038/s41390-022-02148-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 05/18/2022] [Accepted: 05/25/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Kawasaki disease (KD) is a systemic vasculitis that mainly affects children under 5 years of age. Up to 30% of patients develop coronary artery abnormalities, which are reduced with early treatment. Timely diagnosis of KD is challenging but may become more straightforward with the recent discovery of a whole-blood host response classifier that discriminates KD patients from patients with other febrile conditions. Here, we bridged this microarray-based classifier to a clinically applicable quantitative reverse transcription-polymerase chain reaction (qRT-PCR) assay: the Kawasaki Disease Gene Expression Profiling (KiDs-GEP) classifier. METHODS We designed and optimized a qRT-PCR assay and applied it to a subset of samples previously used for the classifier discovery to reweight the original classifier. RESULTS The performance of the KiDs-GEP classifier was comparable to the original classifier with a cross-validated area under the ROC curve of 0.964 [95% CI: 0.924-1.00] vs 0.992 [95% CI: 0.978-1.00], respectively. Both classifiers demonstrated similar trends over various disease conditions, with the clearest distinction between individuals diagnosed with KD vs viral infections. CONCLUSION We successfully bridged the microarray-based classifier into the KiDs-GEP classifier, a more rapid and more cost-efficient qRT-PCR assay, bringing a diagnostic test for KD closer to the hospital clinical laboratory. IMPACT A diagnostic test is needed for Kawasaki disease and is currently not available. We describe the development of a One-Step multiplex qRT-PCR assay and the subsequent modification (i.e., bridging) of the microarray-based host response classifier previously described by Wright et al. The bridged KiDs-GEP classifier performs well in discriminating Kawasaki disease patients from febrile controls. This host response clinical test for Kawasaki disease can be adapted to the hospital clinical laboratory.
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Affiliation(s)
| | - Victoria J Wright
- Department of Infectious Disease, Imperial College London, London, UK
| | | | - Chisato Shimizu
- Department of Pediatrics, Rady Children's Hospital and University of California San Diego, La Jolla, CA, USA
| | | | - Adriana H Tremoulet
- Department of Pediatrics, Rady Children's Hospital and University of California San Diego, La Jolla, CA, USA
| | | | - Clive J Hoggart
- Department of Infectious Disease, Imperial College London, London, UK.,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | | | - Jethro A Herberg
- Department of Infectious Disease, Imperial College London, London, UK
| | - Myrsini Kaforou
- Department of Infectious Disease, Imperial College London, London, UK
| | | | - Jane C Burns
- Department of Pediatrics, Rady Children's Hospital and University of California San Diego, La Jolla, CA, USA
| | - Michael Levin
- Department of Infectious Disease, Imperial College London, London, UK
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10
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Pennisi I, Moniri A, Miscourides N, Miglietta L, Moser N, Habgood-Coote D, Herberg JA, Levin M, Kaforou M, Rodriguez-Manzano J, Georgiou P. Discrimination of bacterial and viral infection using host-RNA signatures integrated in a lab-on-chip platform. Biosens Bioelectron 2022; 216:114633. [PMID: 36081245 DOI: 10.1016/j.bios.2022.114633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 07/13/2022] [Accepted: 08/09/2022] [Indexed: 11/02/2022]
Abstract
The unmet clinical need for accurate point-of-care (POC) diagnostic tests able to discriminate bacterial from viral infection demands a solution that can be used both within healthcare settings and in the field, and that can also stem the tide of antimicrobial resistance. Our approach to solve this problem combine the use of host gene signatures with our Lab-on-a-Chip (LoC) technology enabling low-cost POC expression analysis to detect Infectious Disease. Transcriptomics have been extensively investigated as a potential tool to be implemented in the diagnosis of infectious disease. On the other hand, LoC technologies using ion-sensitive field-effect transistor (ISFET), in conjunction with isothermal chemistries, are offering a promising alternative to conventional amplification instruments, owing to their portable and affordable nature. Currently, the data analysis of ISFET arrays are restricted to established methods by averaging the output of every sensor to give a single time-series. This simple approach makes unrealistic assumptions, leading to insufficient performance for applications that require accurate quantification such as Host-Transcriptomics. In order to reliably quantify transcripts on our LoC platform enabling the classification of infectious disease on-chip, we propose a novel data-driven algorithm for extracting time-to-positive values from ISFET arrays. The algorithm proposed correctly outputs a time-to-positive for all the reactions, with a high correlation to RT-qLAMP (0.85, R2 = 0.98, p < 0.01), resulting in a classification accuracy of 100% (CI, 95-100%). This work aims to bridge the gap between translating assays from microarray analysis to ISFET arrays providing benefits on tackling infectious disease and diagnostic testing in hard-to-reach areas of the world.
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Affiliation(s)
- Ivana Pennisi
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, UK; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Ahmad Moniri
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, UK
| | - Nicholas Miscourides
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, UK
| | - Luca Miglietta
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, UK; Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Nicolas Moser
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, UK
| | - Dominic Habgood-Coote
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Jethro A Herberg
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Michael Levin
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | - Myrsini Kaforou
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK
| | | | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, UK
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11
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Miglietta L, Xu K, Chhaya P, Kreitmann L, Hill-Cawthorne K, Bolt F, Holmes A, Georgiou P, Rodriguez-Manzano J. Adaptive Filtering Framework to Remove Nonspecific and Low-Efficiency Reactions in Multiplex Digital PCR Based on Sigmoidal Trends. Anal Chem 2022; 94:14159-14168. [PMID: 36190816 PMCID: PMC9583074 DOI: 10.1021/acs.analchem.2c01883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Real-time digital polymerase chain reaction (qdPCR) coupled with machine learning (ML) methods has shown the potential to unlock scientific breakthroughs, particularly in the field of molecular diagnostics for infectious diseases. One promising application of this emerging field explores single fluorescent channel PCR multiplex by extracting target-specific kinetic and thermodynamic information contained in amplification curves, also known as data-driven multiplexing. However, accurate target classification is compromised by the presence of undesired amplification events and not ideal reaction conditions. Therefore, here, we proposed a novel framework to identify and filter out nonspecific 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 data-driven multiplexing method called amplification curve analysis (ACA), using available published data where the ACA is demonstrated to screen carbapenemase-producing organisms in clinical isolates. Furthermore, we developed a novel strategy, named adaptive mapping filter (AMF), to adjust the percentage of outliers removed according to the number of positive counts in qdPCR. From an overall total of 152,000 amplification events, 116,222 positive amplification reactions were evaluated before and after filtering by comparing against melting peak distribution, proving that abnormal amplification curves (outliers) are linked to shifted melting distribution or decreased PCR efficiency. The ACA was applied to assess classification performance before and after AMF, showing an improved sensitivity of 1.2% when using inliers compared to a decrement of 19.6% when using outliers (p-value < 0.0001), removing 53.5% of all wrong melting curves based only on the amplification shape. This work explores the correlation between the kinetics of amplification curves and the thermodynamics of melting curves, and it demonstrates that filtering out nonspecific or low-efficient reactions can significantly improve the classification accuracy for cutting-edge multiplexing methodologies.
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Affiliation(s)
- Luca Miglietta
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, LondonW12 0NN, U.K.,Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, LondonSW7 2AZ, U.K
| | - Ke Xu
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, LondonW12 0NN, U.K.,Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, LondonSW7 2AZ, U.K
| | - Priya Chhaya
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, LondonSW7 2AZ, U.K
| | - Louis Kreitmann
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, LondonW12 0NN, U.K
| | - Kerri Hill-Cawthorne
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, LondonW12 0NN, U.K
| | - Frances Bolt
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, LondonW12 0NN, U.K
| | - Alison Holmes
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, LondonW12 0NN, U.K
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, LondonSW7 2AZ, U.K
| | - Jesus Rodriguez-Manzano
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, LondonW12 0NN, U.K
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12
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Wormald BW, Moser N, deSouza NM, Mantikas KT, Malpartida-Cardenas K, Pennisi I, Ind TEJ, Vroobel K, Kalofonou M, Rodriguez-Manzano J, Georgiou P. Lab-on-chip assay of tumour markers and human papilloma virus for cervical cancer detection at the point-of-care. Sci Rep 2022; 12:8750. [PMID: 35610285 PMCID: PMC9128326 DOI: 10.1038/s41598-022-12557-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 04/22/2022] [Indexed: 01/17/2023] Open
Abstract
Cervical cancer affects over half a million people worldwide each year, the majority of whom are in resource-limited settings where cytology screening is not available. As persistent human papilloma virus (HPV) infections are a key causative factor, detection of HPV strains now complements cytology where screening services exist. This work demonstrates the efficacy of a handheld Lab-on-Chip (LoC) device, with an external sample extraction process, in detecting cervical cancer from biopsy samples. The device is based on Ion-Sensitive Field-Effect Transistor (ISFET) sensors used in combination with loop-mediated isothermal amplification (LAMP) assays, to amplify HPV DNA and human telomerase reverse transcriptase (hTERT) mRNA. These markers were selected because of their high levels of expression in cervical cancer cells, but low to nil expression in normal cervical tissue. The achieved analytical sensitivity for the molecular targets resolved down to a single copy per reaction for the mRNA markers, achieving a limit of detection of 102 for hTERT. In the tissue samples, HPV-16 DNA was present in 4/5 malignant and 2/5 benign tissues, with HPV-18 DNA being present in 1/5 malignant and 1/5 benign tissues. hTERT mRNA was detected in all malignant and no benign tissues, with the demonstrated pilot data to indicate the potential for using the LoC in cervical cancer screening in resource-limited settings on a large scale.
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Affiliation(s)
- Benjamin W Wormald
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, Institute of Cancer Research, London, SW7 3RP, UK
| | - Nicolas Moser
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2BT, UK
| | - Nandita M deSouza
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, Institute of Cancer Research, London, SW7 3RP, UK
| | - Katerina-Theresa Mantikas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2BT, UK
| | - Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2BT, UK
| | - Ivana Pennisi
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, London, W2 1NY, UK
| | - Thomas E J Ind
- Department of Surgical Oncology, Royal Marsden NHS Foundation Trust, London, SW3 6JJ, UK
| | - Katherine Vroobel
- Department of Pathology, Royal Marsden NHS Foundation Trust, London, SW3 6JJ, UK
| | - Melpomeni Kalofonou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2BT, UK
| | - Jesus Rodriguez-Manzano
- Department of Infectious Disease, Imperial College London, School of Medicine, St Mary's Hospital, London, W2 1NY, UK
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2BT, UK.
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13
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Stringer OW, Li Y, Bossé JT, Forrest MS, Hernandez-Garcia J, Tucker AW, Nunes T, Costa F, Mortensen P, Velazquez E, Penny P, Rodriguez-Manzano J, Georgiou P, Langford PR. Rapid Detection of Actinobacillus pleuropneumoniae From Clinical Samples Using Recombinase Polymerase Amplification. Front Vet Sci 2022; 9:805382. [PMID: 35400111 PMCID: PMC8990124 DOI: 10.3389/fvets.2022.805382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Accepted: 02/25/2022] [Indexed: 11/30/2022] Open
Abstract
Actinobacillus pleuropneumoniae (APP) is the causative agent of porcine pleuropneumonia, resulting in high economic impact worldwide. There are currently 19 known serovars of APP, with different ones being predominant in specific geographic regions. Outbreaks of pleuropneumonia, characterized by sudden respiratory difficulties and high mortality, can occur when infected pigs are brought into naïve herds, or by those carrying different serovars. Good biosecurity measures include regular diagnostic testing for surveillance purposes. Current gold standard diagnostic techniques lack sensitivity (bacterial culture), require expensive thermocycling machinery (PCR) and are time consuming (culture and PCR). Here we describe the development of an isothermal point-of-care diagnostic test - utilizing recombinase polymerase amplification (RPA) for the detection of APP, targeting the species-specific apxIVA gene. Our APP-RPA diagnostic test achieved a sensitivity of 10 copies/μL using a strain of APP serovar 8, which is the most prevalent serovar in the UK. Additionally, our APP-RPA assay achieved a clinical sensitivity and specificity of 84.3 and 100%, respectively, across 61 extracted clinical samples obtained from farms located in England and Portugal. Using a small subset (n = 14) of the lung tissue samples, we achieved a clinical sensitivity and specificity of 76.9 and 100%, respectively) using lung imprints made on FTA cards tested directly in the APP-RPA reaction. Our results demonstrate that our APP-RPA assay enables a suitable rapid and sensitive screening tool for this important veterinary pathogen.
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Affiliation(s)
- Oliver W. Stringer
- Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Yanwen Li
- Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Janine T. Bossé
- Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom
| | | | - Juan Hernandez-Garcia
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Alexander W. Tucker
- Department of Veterinary Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Tiago Nunes
- Ceva Animal Health Ltd., Saúde Animal, Algés, Portugal
| | | | | | | | - Paul Penny
- Ceva Animal Health Ltd., Amersham, United Kingdom
| | - Jesus Rodriguez-Manzano
- Section of Adult Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
| | - Paul R. Langford
- Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom
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14
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Fernandez-Cassi X, Timoneda N, Martínez-Puchol S, Rusiñol M, Rodriguez-Manzano J, Figuerola N, Bofill-Mas S, Abril JF, Girones R. Corrigendum to "Metagenomics for the study of viruses in urban sewage as a tool for public health surveillance" [Sci. Total Environ. 618 (2016) 870-880 10.1016/j.scitotenv.2017.08.249]. Sci Total Environ 2022; 814:152530. [PMID: 34995880 DOI: 10.1016/j.scitotenv.2021.152530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Affiliation(s)
- X Fernandez-Cassi
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain.
| | - N Timoneda
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain; Computational Genomics Lab and Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, Catalonia, Spain
| | - S Martínez-Puchol
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
| | - M Rusiñol
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
| | - J Rodriguez-Manzano
- Centre for Bio - Inspired Technology, Department of Electrica land Electronic Engineering, Imperial College London, London, United Kingdom
| | - N Figuerola
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
| | - S Bofill-Mas
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
| | - J F Abril
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain; Computational Genomics Lab and Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, Catalonia, Spain
| | - R Girones
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain.
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15
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Malpartida-Cardenas K, Miglietta L, Peng T, Moniri A, Holmes A, Georgiou P, Rodriguez-Manzano J. Single-channel digital LAMP multiplexing using amplification curve analysis. Sens Diagn 2022; 1:465-468. [PMID: 37034965 PMCID: PMC7614402 DOI: 10.1039/d2sd00038e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We demonstrate LAMP multiplexing (5-plex) in a single reaction with a single fluorescent channel using the machine learning-based method amplification curve analysis, showing a classification accuracy of 91.33% for detection of respiratory pathogens.
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Affiliation(s)
- Kenny Malpartida-Cardenas
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
- Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK
| | - Luca Miglietta
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
- Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK
| | - Tianyi Peng
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
| | - Ahmad Moniri
- Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK
| | - Alison Holmes
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK
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16
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Miglietta L, Moniri A, Pennisi I, Malpartida-Cardenas K, Abbas H, Hill-Cawthorne K, Bolt F, Jauneikaite E, Davies F, Holmes A, Georgiou P, Rodriguez-Manzano J. Coupling Machine Learning and High Throughput Multiplex Digital PCR Enables Accurate Detection of Carbapenem-Resistant Genes in Clinical Isolates. Front Mol Biosci 2021; 8:775299. [PMID: 34888355 PMCID: PMC8650054 DOI: 10.3389/fmolb.2021.775299] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
Rapid and accurate identification of patients colonised with carbapenemase-producing organisms (CPOs) is essential to adopt prompt prevention measures to reduce the risk of transmission. Recent studies have demonstrated the ability to combine machine learning (ML) algorithms with real-time digital PCR (dPCR) instruments to increase classification accuracy of multiplex PCR assays when using synthetic DNA templates. We sought to determine if this novel methodology could be applied to improve identification of the five major carbapenem-resistant genes in clinical CPO-isolates, which would represent a leap forward in the use of PCR-based data-driven diagnostics for clinical applications. We collected 253 clinical isolates (including 221 CPO-positive samples) and developed a novel 5-plex PCR assay for detection of blaIMP, blaKPC, blaNDM, blaOXA-48, and blaVIM. Combining the recently reported ML method “Amplification and Melting Curve Analysis” (AMCA) with the abovementioned multiplex assay, we assessed the performance of the AMCA methodology in detecting these genes. The improved classification accuracy of AMCA relies on the usage of real-time data from a single-fluorescent channel and benefits from the kinetic/thermodynamic information encoded in the thousands of amplification events produced by high throughput real-time dPCR. The 5-plex showed a lower limit of detection of 10 DNA copies per reaction for each primer set and no cross-reactivity with other carbapenemase genes. The AMCA classifier demonstrated excellent predictive performance with 99.6% (CI 97.8–99.9%) accuracy (only one misclassified sample out of the 253, with a total of 160,041 positive amplification events), which represents a 7.9% increase (p-value <0.05) compared to conventional melting curve analysis. This work demonstrates the use of the AMCA method to increase the throughput and performance of state-of-the-art molecular diagnostic platforms, without hardware modifications and additional costs, thus potentially providing substantial clinical utility on screening patients for CPO carriage.
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Affiliation(s)
- Luca Miglietta
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.,Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Ahmad Moniri
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Ivana Pennisi
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Kenny Malpartida-Cardenas
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Hala Abbas
- Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Kerri Hill-Cawthorne
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Frances Bolt
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Elita Jauneikaite
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.,Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Frances Davies
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.,Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Alison Holmes
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.,Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Jesus Rodriguez-Manzano
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
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17
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Wormald B, Rodriguez-Manzano J, Moser N, Pennisi I, Ind TEJ, Vroobel K, Attygalle A, Georgiou P, deSouza NM. Loop-Mediated Isothermal Amplification Assay for Detecting Tumor Markers and Human Papillomavirus: Accuracy and Supplemental Diagnostic Value to Endovaginal MRI in Cervical Cancer. Front Oncol 2021; 11:747614. [PMID: 34790573 PMCID: PMC8591099 DOI: 10.3389/fonc.2021.747614] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 10/13/2021] [Indexed: 11/18/2022] Open
Abstract
OBJECTIVE To establish the sensitivity and specificity of a human papillomavirus (HPV) and tumor marker DNA/mRNA assay for detecting cervical cancer that is transferrable to a Lab-on-a-chip platform and determine its diagnostic benefit in early stage disease when used in conjunction with high-resolution endovaginal magnetic resonance imaging (MRI). METHODS Forty-one patients (27 with Stage1 cervical cancer [Group1] and 14 non-cancer HPV negative controls [Group2]) had DNA and RNA extracted from cervical cytology swab samples. HPV16, HPV18, hTERT, TERC/GAPDH and MYC/GAPDH concentration was established using a loop mediated isothermal amplification (LAMP) assay. Thresholds for tumor marker detection for Group1 were set from Group2 analysis (any hTERT, TERC/GAPDH 3.12, MYC/GAPDH 0.155). Group 1 participants underwent endovaginal MRI. Sensitivity and specificity for cancer detection by LAMP and MRI individually and combined was documented by comparison to pathology. RESULTS Sensitivity and specificity for cancer detection was 68.8% and 77.8% if any tumor marker was positive regardless of HPV status (scenario1), and 93.8% and 55.8% if tumor marker or HPV were positive (scenario 2). Adding endovaginal MRI improved specificity to 88.9% in scenario 1 (sensitivity 68.8%) and to 77.8%% in scenario2 (sensitivity 93.8%). CONCLUSION Specificity for cervical cancer detection using a LAMP assay is superior with tumor markers; low sensitivity is improved by HPV detection. Accuracy for early stage cervical cancer detection is optimal using a spatially multiplexed tumor marker/HPV LAMP assay together with endovaginal MRI.
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Affiliation(s)
- Benjamin Wormald
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
| | - Jesus Rodriguez-Manzano
- Department of Infectious Disease, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Nicolas Moser
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Ivana Pennisi
- Department of Infectious Disease, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Thomas E. J. Ind
- Departmentof Surgical Oncology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Katherine Vroobel
- Department of Histopathology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Ayoma Attygalle
- Department of Histopathology, Royal Marsden NHS Foundation Trust, London, United Kingdom
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Nandita M. deSouza
- Cancer Research UK Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
- MRI Unit, Royal Marsden NHS Foundation Trust, Sutton, United Kingdom
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18
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Li HK, Kaforou M, Rodriguez-Manzano J, Channon-Wells S, Moniri A, Habgood-Coote D, Gupta RK, Mills EA, Arancon D, Lin J, Chiu YH, Pennisi I, Miglietta L, Mehta R, Obaray N, Herberg JA, Wright VJ, Georgiou P, Shallcross LJ, Mentzer AJ, Levin M, Cooke GS, Noursadeghi M, Sriskandan S. Discovery and validation of a three-gene signature to distinguish COVID-19 and other viral infections in emergency infectious disease presentations: a case-control and observational cohort study. Lancet Microbe 2021; 2:e594-e603. [PMID: 34423323 PMCID: PMC8367196 DOI: 10.1016/s2666-5247(21)00145-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Background Emergency admissions for infection often lack initial diagnostic certainty. COVID-19 has highlighted a need for novel diagnostic approaches to indicate likelihood of viral infection in a pandemic setting. We aimed to derive and validate a blood transcriptional signature to detect viral infections, including COVID-19, among adults with suspected infection who presented to the emergency department. Methods Individuals (aged ≥18 years) presenting with suspected infection to an emergency department at a major teaching hospital in the UK were prospectively recruited as part of the Bioresource in Adult Infectious Diseases (BioAID) discovery cohort. Whole-blood RNA sequencing was done on samples from participants with subsequently confirmed viral, bacterial, or no infection diagnoses. Differentially expressed host genes that met additional filtering criteria were subjected to feature selection to derive the most parsimonious discriminating signature. We validated the signature via RT-qPCR in a prospective validation cohort of participants who presented to an emergency department with undifferentiated fever, and a second case-control validation cohort of emergency department participants with PCR-positive COVID-19 or bacterial infection. We assessed signature performance by calculating the area under receiver operating characteristic curves (AUROCs), sensitivities, and specificities. Findings A three-gene transcript signature, comprising HERC6, IGF1R, and NAGK, was derived from the discovery cohort of 56 participants with bacterial infections and 27 with viral infections. In the validation cohort of 200 participants, the signature differentiated bacterial from viral infections with an AUROC of 0·976 (95% CI 0·919−1·000), sensitivity of 97·3% (85·8−99·9), and specificity of 100% (63·1−100). The AUROC for C-reactive protein (CRP) was 0·833 (0·694−0·944) and for leukocyte count was 0·938 (0·840−0·986). The signature achieved higher net benefit in decision curve analysis than either CRP or leukocyte count for discriminating viral infections from all other infections. In the second validation analysis, which included SARS-CoV-2-positive participants, the signature discriminated 35 bacterial infections from 34 SARS-CoV-2-positive COVID-19 infections with AUROC of 0·953 (0·893−0·992), sensitivity 88·6%, and specificity of 94·1%. Interpretation This novel three-gene signature discriminates viral infections, including COVID-19, from other emergency infection presentations in adults, outperforming both leukocyte count and CRP, thus potentially providing substantial clinical utility in managing acute presentations with infection. Funding National Institute for Health Research, Medical Research Council, Wellcome Trust, and EU-FP7.
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Affiliation(s)
- Ho Kwong Li
- Department of Infectious Disease, Imperial College London, London, UK
- Medical Research Council Centre for Molecular Bacteriology & Infection, Imperial College London, London, UK
| | - Myrsini Kaforou
- Department of Infectious Disease, Imperial College London, London, UK
| | - Jesus Rodriguez-Manzano
- Department of Infectious Disease, Imperial College London, London, UK
- National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infection & Antimicrobial Resistance, Imperial College London, London, UK
| | | | - Ahmad Moniri
- Department of Electrical & Electronic Engineering, Imperial College London, London, UK
| | | | - Rishi K Gupta
- Institute of Global Health, University College London, London, UK
| | - Ewurabena A Mills
- Department of Infectious Disease, Imperial College London, London, UK
| | | | - Jessica Lin
- Department of Infectious Disease, Imperial College London, London, UK
| | - Yueh-Ho Chiu
- Department of Infectious Disease, Imperial College London, London, UK
| | - Ivana Pennisi
- Department of Infectious Disease, Imperial College London, London, UK
| | - Luca Miglietta
- Department of Infectious Disease, Imperial College London, London, UK
- Department of Electrical & Electronic Engineering, Imperial College London, London, UK
| | - Ravi Mehta
- Department of Infectious Disease, Imperial College London, London, UK
| | - Nelofar Obaray
- Department of Infectious Disease, Imperial College London, London, UK
| | - Jethro A Herberg
- Department of Infectious Disease, Imperial College London, London, UK
| | - Victoria J Wright
- Department of Infectious Disease, Imperial College London, London, UK
| | - Pantelis Georgiou
- Department of Electrical & Electronic Engineering, Imperial College London, London, UK
- Centre for Bio-Inspired Technology, Imperial College London, London, UK
| | | | | | - Michael Levin
- Department of Infectious Disease, Imperial College London, London, UK
| | - Graham S Cooke
- Department of Infectious Disease, Imperial College London, London, UK
| | - Mahdad Noursadeghi
- Division of Infection and Immunity, University College London, London, UK
| | - Shiranee Sriskandan
- Department of Infectious Disease, Imperial College London, London, UK
- Medical Research Council Centre for Molecular Bacteriology & Infection, Imperial College London, London, UK
- National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infection & Antimicrobial Resistance, Imperial College London, London, UK
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Charani E, McKee M, Ahmad R, Balasegaram M, Bonaconsa C, Merrett GB, Busse R, Carter V, Castro-Sanchez E, Franklin BD, Georgiou P, Hill-Cawthorne K, Hope W, Imanaka Y, Kambugu A, Leather AJM, Mbamalu O, McLeod M, Mendelson M, Mpundu M, Rawson TM, Ricciardi W, Rodriguez-Manzano J, Singh S, Tsioutis C, Uchea C, Zhu N, Holmes AH. Optimising antimicrobial use in humans - review of current evidence and an interdisciplinary consensus on key priorities for research. Lancet Reg Health Eur 2021; 7:100161. [PMID: 34557847 PMCID: PMC8454847 DOI: 10.1016/j.lanepe.2021.100161] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Addressing the silent pandemic of antimicrobial resistance (AMR) is a focus of the 2021 G7 meeting. A major driver of AMR and poor clinical outcomes is suboptimal antimicrobial use. Current research in AMR is inequitably focused on new drug development. To achieve antimicrobial security we need to balance AMR research efforts between development of new agents and strategies to preserve the efficacy and maximise effectiveness of existing agents. Combining a review of current evidence and multistage engagement with diverse international stakeholders (including those in healthcare, public health, research, patient advocacy and policy) we identified research priorities for optimising antimicrobial use in humans across four broad themes: policy and strategic planning; medicines management and prescribing systems; technology to optimise prescribing; and context, culture and behaviours. Sustainable progress depends on: developing economic and contextually appropriate interventions; facilitating better use of data and prescribing systems across healthcare settings; supporting appropriate and scalable technological innovation. Implementing this strategy for AMR research on the optimisation of antimicrobial use in humans could contribute to equitable global health security.
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Affiliation(s)
- Esmita Charani
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
- Division of Infectious Diseases & HIV Medicine, Department of Medicine, University of Cape Town, South Africa
| | - Martin McKee
- London School of Hygiene and Tropical Medicine, London, UK
| | - Raheelah Ahmad
- School of Health Sciences City, University of London, UK
| | - Manica Balasegaram
- The Global Antibiotic Research and Development Partnership, Geneva, Switzerland
| | - Candice Bonaconsa
- Division of Infectious Diseases & HIV Medicine, Department of Medicine, University of Cape Town, South Africa
| | | | | | - Vanessa Carter
- Stanford University Medicine X e-Patient Scholars Program 2017, Health Communication and Social Media South Africa, Africa CDC Civil Society Champion for AMR
| | - Enrique Castro-Sanchez
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
| | - Bryony D Franklin
- University College London School of Pharmacy, London, UK
- Imperial College Healthcare NHS Trust, Centre for Medication Safety and Service Quality, Pharmacy Department, London, UK
| | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
| | - Kerri Hill-Cawthorne
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
| | - William Hope
- Department of Molecular and Clinical Pharmacology, University of Liverpool, UK
| | - Yuichi Imanaka
- Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Andrew Kambugu
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Andrew JM Leather
- King's Centre for Global Health and Health Partnerships, School of Population Health and Environmental Sciences, King's College London, London, UK
| | - Oluchi Mbamalu
- Division of Infectious Diseases & HIV Medicine, Department of Medicine, University of Cape Town, South Africa
| | - M McLeod
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
- Imperial College Healthcare NHS Trust, Centre for Medication Safety and Service Quality, Pharmacy Department, London, UK
| | - Marc Mendelson
- Division of Infectious Diseases & HIV Medicine, Department of Medicine, University of Cape Town, South Africa
| | | | - Timothy M Rawson
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
- Department of Bioengineering, Imperial College London, London, UK
| | | | - Jesus Rodriguez-Manzano
- Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK
- Department of Infectious Diseases, Faculty of Medicine, Imperial College London, London
| | - Sanjeev Singh
- Department of Infection Control and Epidemiology, Amrita Institute of Medical Science, Amrita Vishwa Vidyapeetham, Kochi (Kerala), India
| | - Constantinos Tsioutis
- Department of Internal Medicine and Infection Prevention and Control, School of Medicine, European University Cyprus, Nicosia, Cyprus
| | - Chibuzor Uchea
- Drug-Resistant Infections Priority Programme,Wellcome Trust, London, UK
| | - Nina Zhu
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
| | - Alison H Holmes
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Imperial College London, UK
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20
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Alexandrou G, Moser N, Mantikas KT, Rodriguez-Manzano J, Ali S, Coombes RC, Shaw J, Georgiou P, Toumazou C, Kalofonou M. Detection of Multiple Breast Cancer ESR1 Mutations on an ISFET Based Lab-on-Chip Platform. IEEE Trans Biomed Circuits Syst 2021; 15:380-389. [PMID: 34214044 DOI: 10.1109/tbcas.2021.3094464] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
ESR1 mutations are important biomarkers in metastatic breast cancer. Specifically, p.E380Q and p.Y537S mutations arise in response to hormonal therapies given to patients with hormone receptor positive (HR+) breast cancer (BC). This paper demonstrates the efficacy of an ISFET based CMOS integrated Lab-on-Chip (LoC) system, coupled with variant-specific isothermal amplification chemistries, for detection and discrimination of wild type (WT) from mutant (MT) copies of the ESR1 gene. Hormonal resistant cancers often lead to increased chances of metastatic disease which leads to high mortality rates, especially in low-income regions and areas with low healthcare coverage. Design and optimization of bespoke primers was carried out and tested on a qPCR instrument and then benchmarked versus the LoC platform. Assays for detection of p.Y537S and p.E380Q were developed and tested on the LoC platform, achieving amplification in under 25 minutes and sensitivity of down to 1000 copies of DNA per reaction for both target assays. The LoC system hereby presented, is cheaper and smaller than other standard industry equivalent technologies such as qPCR and sequencing. The LoC platform proposed, has the potential to be used at a breast cancer point-of-care testing setting, offering mutational tracking of circulating tumour DNA in liquid biopsies to assist patient stratification and metastatic monitoring.
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21
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Pennisi I, Rodriguez-Manzano J, Moniri A, Kaforou M, Herberg JA, Levin M, Georgiou P. Translation of a Host Blood RNA Signature Distinguishing Bacterial From Viral Infection Into a Platform Suitable for Development as a Point-of-Care Test. JAMA Pediatr 2021; 175:417-419. [PMID: 33393977 PMCID: PMC7783591 DOI: 10.1001/jamapediatrics.2020.5227] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Accepted: 06/23/2020] [Indexed: 01/24/2023]
Affiliation(s)
- Ivana Pennisi
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Jesus Rodriguez-Manzano
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Ahmad Moniri
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
| | - Myrsini Kaforou
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Jethro A. Herberg
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Michael Levin
- Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
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22
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Cavallo FR, Mirza KB, de Mateo S, Nikolic K, Rodriguez-Manzano J, Toumazou C. Aptasensor for Quantification of Leptin Through PCR Amplification of Short DNA-Aptamers. ACS Sens 2021; 6:709-715. [PMID: 33650854 DOI: 10.1021/acssensors.0c02605] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Protein quantification is traditionally performed through enzyme-linked immunosorbent assay (ELISA), which involves long preparation times. To overcome this, new approaches use aptamers as an alternative to antibodies. In this paper, we present a new approach to quantify proteins with short DNA aptamers through polymerase chain reaction (PCR) resulting in shorter protocol times with comparatively improved limits of detection. The proposed method includes a novel way to quantify both the target protein and the corresponding short DNA-aptamers simultaneously, which also allows us to fully characterize the performance of aptasensors. Human leptin is used as a target protein to validate this technique, because it is considered an important biomarker for obesity-related studies. In our experiments, we achieved the lowest limit of detection of 100 pg/mL within less than 2 h, a limit affected by the dissociation constant of the leptin aptamer, which could be improved by selecting a more specific aptamer. Because of the simple and inexpensive approach, this technique can be employed for Lab-On-Chip implementations and for rapid "on-site" quantification of proteins.
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Affiliation(s)
| | - Khalid B. Mirza
- Centre for Bio-Inspired Technology, Imperial College London, London SW7 2AZ, United Kingdom
- Department of Biotechnology and Medical Engineering, National Institute of Technology, Rourkela, Odisha 769008, India
| | - Sara de Mateo
- Centre for Bio-Inspired Technology, Imperial College London, London SW7 2AZ, United Kingdom
| | - Konstantin Nikolic
- Centre for Bio-Inspired Technology, Imperial College London, London SW7 2AZ, United Kingdom
- School of Computing and Engineering, University of West London, London W5 5RF, United Kingdom
| | - Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Imperial College London, London SW7 2AZ, United Kingdom
- Department of Infectious Disease, Imperial College London, London SW7 2AZ, United Kingdom
| | - Christofer Toumazou
- Centre for Bio-Inspired Technology, Imperial College London, London SW7 2AZ, United Kingdom
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23
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Rodriguez-Manzano J, Malpartida-Cardenas K, Moser N, Pennisi I, Cavuto M, Miglietta L, Moniri A, Penn R, Satta G, Randell P, Davies F, Bolt F, Barclay W, Holmes A, Georgiou P. Handheld Point-of-Care System for Rapid Detection of SARS-CoV-2 Extracted RNA in under 20 min. ACS Cent Sci 2021; 7:307-317. [PMID: 33649735 PMCID: PMC7839415 DOI: 10.1021/acscentsci.0c01288] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Indexed: 05/02/2023]
Abstract
The COVID-19 pandemic is a global health emergency characterized by the high rate of transmission and ongoing increase of cases globally. Rapid point-of-care (PoC) diagnostics to detect the causative virus, SARS-CoV-2, are urgently needed to identify and isolate patients, contain its spread and guide clinical management. In this work, we report the development of a rapid PoC diagnostic test (<20 min) based on reverse transcriptase loop-mediated isothermal amplification (RT-LAMP) and semiconductor technology for the detection of SARS-CoV-2 from extracted RNA samples. The developed LAMP assay was tested on a real-time benchtop instrument (RT-qLAMP) showing a lower limit of detection of 10 RNA copies per reaction. It was validated against extracted RNA from 183 clinical samples including 127 positive samples (screened by the CDC RT-qPCR assay). Results showed 91% sensitivity and 100% specificity when compared to RT-qPCR and average positive detection times of 15.45 ± 4.43 min. For validating the incorporation of the RT-LAMP assay onto our PoC platform (RT-eLAMP), a subset of samples was tested (n = 52), showing average detection times of 12.68 ± 2.56 min for positive samples (n = 34), demonstrating a comparable performance to a benchtop commercial instrument. Paired with a smartphone for results visualization and geolocalization, this portable diagnostic platform with secure cloud connectivity will enable real-time case identification and epidemiological surveillance.
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Affiliation(s)
- Jesus Rodriguez-Manzano
- Department
of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
- Department
of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Kenny Malpartida-Cardenas
- Department
of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Nicolas Moser
- Department
of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Ivana Pennisi
- Department
of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
- Department
of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Matthew Cavuto
- Department
of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Luca Miglietta
- Department
of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Ahmad Moniri
- Department
of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
| | - Rebecca Penn
- Department
of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Giovanni Satta
- Imperial
College Healthcare NHS Trust, Hammersmith Hospital, London W12 0HS, United Kingdom
| | - Paul Randell
- Imperial
College Healthcare NHS Trust, Hammersmith Hospital, London W12 0HS, United Kingdom
| | - Frances Davies
- Department
of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Frances Bolt
- Department
of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Wendy Barclay
- Department
of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Alison Holmes
- Department
of Infectious Disease, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
- Imperial
College Healthcare NHS Trust, Hammersmith Hospital, London W12 0HS, United Kingdom
| | - Pantelis Georgiou
- Department
of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London SW7 2AZ, United Kingdom
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Moniri A, Miglietta L, Holmes A, Georgiou P, Rodriguez-Manzano J. High-Level Multiplexing in Digital PCR with Intercalating Dyes by Coupling Real-Time Kinetics and Melting Curve Analysis. Anal Chem 2020; 92:14181-14188. [PMID: 32954724 DOI: 10.1021/acs.analchem.0c03298] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Digital polymerase chain reaction (dPCR) is a mature technique that has enabled scientific breakthroughs in several fields. However, this technology is primarily used in research environments with high-level multiplexing, representing a major challenge. Here, we propose a novel method for multiplexing, referred to as amplification and melting curve analysis (AMCA), which leverages the kinetic information in real-time amplification data and the thermodynamic melting profile using an affordable intercalating dye (EvaGreen). The method trains a system composed of supervised machine learning models for accurate classification, by virtue of the large volume of data from dPCR platforms. As a case study, we develop a new 9-plex assay to detect mobilized colistin resistant genes as clinically relevant targets for antimicrobial resistance. Over 100,000 amplification events have been analyzed, and for the positive reactions, the AMCA approach reports a classification accuracy of 99.33 ± 0.13%, an increase of 10.0% over using melting curve analysis. This work provides an affordable method of high-level multiplexing without fluorescent probes, extending the benefits of dPCR in research and clinical settings.
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Affiliation(s)
- Ahmad Moniri
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Luca Miglietta
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Alison Holmes
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London W12 0NN, U.K
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K.,NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London W12 0NN, U.K
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Moniri A, Miglietta L, Malpartida-Cardenas K, Pennisi I, Cacho-Soblechero M, Moser N, Holmes A, Georgiou P, Rodriguez-Manzano J. Amplification Curve Analysis: Data-Driven Multiplexing Using Real-Time Digital PCR. Anal Chem 2020; 92:13134-13143. [PMID: 32946688 DOI: 10.1021/acs.analchem.0c02253] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Information about the kinetics of PCR reactions is encoded in the amplification curve. However, in digital PCR (dPCR), this information is typically neglected by collapsing each amplification curve into a binary output (positive/negative). Here, we demonstrate that the large volume of raw data obtained from real-time dPCR instruments can be exploited to perform data-driven multiplexing in a single fluorescent channel using machine learning methods, by virtue of the information in the amplification curve. This new approach, referred to as amplification curve analysis (ACA), was shown using an intercalating dye (EvaGreen), reducing the cost and complexity of the assay and enabling the use of melting curve analysis for validation. As a case study, we multiplexed 3 carbapenem-resistant genes to show the impact of this approach on global challenges such as antimicrobial resistance. In the presence of single targets, we report a classification accuracy of 99.1% (N = 16188), which represents a 19.7% increase compared to multiplexing based on the final fluorescent intensity. Considering all combinations of amplification events (including coamplifications), the accuracy was shown to be 92.9% (N = 10383). To support the analysis, we derived a formula to estimate the occurrence of coamplification in dPCR based on multivariate Poisson statistics and suggest reducing the digital occupancy in the case of multiple targets in the same digital panel. The ACA approach takes a step toward maximizing the capabilities of existing real-time dPCR instruments and chemistries, by extracting more information from data to enable data-driven multiplexing with high accuracy. Furthermore, we expect that combining this method with existing probe-based assays will increase multiplexing capabilities significantly. We envision that once emerging point-of-care technologies can reliably capture real-time data from isothermal chemistries, the ACA method will facilitate the implementation of dPCR outside of the lab.
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Affiliation(s)
- Ahmad Moniri
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Luca Miglietta
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Ivana Pennisi
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K.,Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London W2 1NY, U.K
| | - Miguel Cacho-Soblechero
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Nicolas Moser
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Alison Holmes
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London W12 0NN, U.K
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K
| | - Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, U.K.,NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Imperial College London, London W12 0NN, U.K
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Moniri A, Terracina D, Rodriguez-Manzano J, Strutton PH, Georgiou P. Real-Time Forecasting of sEMG Features for Trunk Muscle Fatigue Using Machine Learning. IEEE Trans Biomed Eng 2020; 68:718-727. [PMID: 32746076 DOI: 10.1109/tbme.2020.3012783] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Several features of the surface electromyography (sEMG) signal are related to muscle activity and fatigue. However, the time-evolution of these features are non-stationary and vary between subjects. The aim of this study is to investigate the use of adaptive algorithms to forecast sEMG feature of the trunk muscles. METHODS Shallow models and a deep convolutional neural network (CNN) were used to simultaneously learn and forecast 5 common sEMG features in real-time to provide tailored predictions. This was investigated for: up to a 25 second horizon; for 14 different muscles in the trunk; across 13 healthy subjects; while they were performing various exercises. RESULTS The CNN was able to forecast 25 seconds ahead of time, with 6.88% mean absolute percentage error and 3.72% standard deviation of absolute percentage error, across all the features. Moreover, the CNN outperforms the best shallow model in terms of a figure of merit combining accuracy and precision by at least 30% for all the 5 features. CONCLUSION Even though the sEMG features are non-stationary and vary between subjects, adaptive learning and forecasting, especially using CNNs, can provide accurate and precise forecasts across a range of physical activities. SIGNIFICANCE The proposed models provide the groundwork for a wearable device which can forecast muscle fatigue in the trunk, so as to potentially prevent low back pain. Additionally, the explicit real-time forecasting of sEMG features provides a general model which can be applied to many applications of muscle activity monitoring, which helps practitioners and physiotherapists improve therapy.
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Cacho-Soblechero M, Malpartida-Cardenas K, Cicatiello C, Rodriguez-Manzano J, Georgiou P. A Dual-Sensing Thermo-Chemical ISFET Array for DNA-Based Diagnostics. IEEE Trans Biomed Circuits Syst 2020; 14:477-489. [PMID: 32149696 DOI: 10.1109/tbcas.2020.2978000] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
This paper presents a 32 × 32 ISFET array with in-pixel dual-sensing and programmability targeted for on-chip DNA amplification detection. The pixel architecture provides thermal and chemical sensing by encoding temperature and ion activity in a single output PWM, modulating its frequency and its duty cycle respectively. Each pixel is composed of an ISFET-based differential linear OTA and a 2-stage sawtooth oscillator. The operating point and characteristic response of the pixel can be programmed, enabling trapped charge compensation and enhancing the versatility and adaptability of the architecture. Fabricated in 0.18 μm standard CMOS process, the system demonstrates a quadratic thermal response and a highly linear pH sensitivity, with a trapped charge compensation scheme able to calibrate 99.5% of the pixels in the target range, achieving a homogeneous response across the array. Furthermore, the sensing scheme is robust against process variations and can operate under various supply conditions. Finally, the architecture suitability for on-chip DNA amplification detection is proven by performing Loop-mediated Isothermal Amplification (LAMP) of phage lambda DNA, obtaining a time-to-positive of 7.71 minutes with results comparable to commercial qPCR instruments. This architecture represents the first in-pixel dual thermo-chemical sensing in ISFET arrays for Lab-on-a-Chip diagnostics.
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28
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Rodriguez-Manzano J, Moser N, Malpartida-Cardenas K, Moniri A, Fisarova L, Pennisi I, Boonyasiri A, Jauneikaite E, Abdolrasouli A, Otter JA, Bolt F, Davies F, Didelot X, Holmes A, Georgiou P. Rapid Detection of Mobilized Colistin Resistance using a Nucleic Acid Based Lab-on-a-Chip Diagnostic System. Sci Rep 2020; 10:8448. [PMID: 32439986 PMCID: PMC7242339 DOI: 10.1038/s41598-020-64612-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 04/13/2020] [Indexed: 11/30/2022] Open
Abstract
The increasing prevalence of antimicrobial resistance is a serious threat to global public health. One of the most concerning trends is the rapid spread of Carbapenemase-Producing Organisms (CPO), where colistin has become the last-resort antibiotic treatment. The emergence of colistin resistance, including the spread of mobilized colistin resistance (mcr) genes, raises the possibility of untreatable bacterial infections and motivates the development of improved diagnostics for the detection of colistin-resistant organisms. This work demonstrates a rapid response for detecting the most recently reported mcr gene, mcr−9, using a portable and affordable lab-on-a-chip (LoC) platform, offering a promising alternative to conventional laboratory-based instruments such as real-time PCR (qPCR). The platform combines semiconductor technology, for non-optical real-time DNA sensing, with a smartphone application for data acquisition, visualization and cloud connectivity. This technology is enabled by using loop-mediated isothermal amplification (LAMP) as the chemistry for targeted DNA detection, by virtue of its high sensitivity, specificity, yield, and manageable temperature requirements. Here, we have developed the first LAMP assay for mcr−9 - showing high sensitivity (down to 100 genomic copies/reaction) and high specificity (no cross-reactivity with other mcr variants). This assay is demonstrated through supporting a hospital investigation where we analyzed nucleic acids extracted from 128 carbapenemase-producing bacteria isolated from clinical and screening samples and found that 41 carried mcr−9 (validated using whole genome sequencing). Average positive detection times were 6.58 ± 0.42 min when performing the experiments on a conventional qPCR instrument (n = 41). For validating the translation of the LAMP assay onto a LoC platform, a subset of the samples were tested (n = 20), showing average detection times of 6.83 ± 0.92 min for positive isolates (n = 14). All experiments detected mcr−9 in under 10 min, and both platforms showed no statistically significant difference (p-value > 0.05). When sample preparation and throughput capabilities are integrated within this LoC platform, the adoption of this technology for the rapid detection and surveillance of antimicrobial resistance genes will decrease the turnaround time for DNA detection and resistotyping, improving diagnostic capabilities, patient outcomes, and the management of infectious diseases.
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Affiliation(s)
- Jesus Rodriguez-Manzano
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom. .,Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom.
| | - Nicolas Moser
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Ahmad Moniri
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Lenka Fisarova
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Ivana Pennisi
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
| | - Adhiratha Boonyasiri
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Elita Jauneikaite
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.,Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom
| | - Alireza Abdolrasouli
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Jonathan A Otter
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom.,Imperial College Healthcare NHS Trust, St Mary's Hospital, London, United Kingdom
| | - Frances Bolt
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Frances Davies
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Xavier Didelot
- School of Life Sciences and Department of Statistics, University of Warwick, Coventry, United Kingdom
| | - Alison Holmes
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, United Kingdom
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Kalofonou M, Malpartida-Cardenas K, Alexandrou G, Rodriguez-Manzano J, Yu LS, Miscourides N, Allsopp R, Gleason KLT, Goddard K, Fernandez-Garcia D, Page K, Georgiou P, Ali S, Coombes RC, Shaw J, Toumazou C. A novel hotspot specific isothermal amplification method for detection of the common PIK3CA p.H1047R breast cancer mutation. Sci Rep 2020; 10:4553. [PMID: 32165708 PMCID: PMC7067842 DOI: 10.1038/s41598-020-60852-3] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2019] [Accepted: 02/13/2020] [Indexed: 01/07/2023] Open
Abstract
Breast cancer (BC) is a common cancer in women worldwide. Despite advances in treatment, up to 30% of women eventually relapse and die of metastatic breast cancer. Liquid biopsy analysis of circulating cell-free DNA fragments in the patients' blood can monitor clonality and evolving mutations as a surrogate for tumour biopsy. Next generation sequencing platforms and digital droplet PCR can be used to profile circulating tumour DNA from liquid biopsies; however, they are expensive and time consuming for clinical use. Here, we report a novel strategy with proof-of-concept data that supports the usage of loop-mediated isothermal amplification (LAMP) to detect PIK3CA c.3140 A > G (H1047R), a prevalent BC missense mutation that is attributed to BC tumour growth. Allele-specific primers were designed and optimized to detect the p.H1047R variant following the USS-sbLAMP method. The assay was developed with synthetic DNA templates and validated with DNA from two breast cancer cell-lines and two patient tumour tissue samples through a qPCR instrument and finally piloted on an ISFET enabled microchip. This work sets a foundation for BC mutational profiling on a Lab-on-Chip device, to help the early detection of patient relapse and to monitor efficacy of systemic therapies for personalised cancer patient management.
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Affiliation(s)
- Melpomeni Kalofonou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, England.
| | - Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, England
| | - George Alexandrou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, England
| | - Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, England
| | - Ling-Shan Yu
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, England
| | - Nicholas Miscourides
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, England
| | - Rebecca Allsopp
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Leicester, LE2 7LX, England
| | - Kelly L T Gleason
- Division of Cancer, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, England
| | - Katie Goddard
- Division of Cancer, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, England
| | - Daniel Fernandez-Garcia
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Leicester, LE2 7LX, England
| | - Karen Page
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Leicester, LE2 7LX, England
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, England
| | - Simak Ali
- Division of Cancer, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, England
| | - R Charles Coombes
- Division of Cancer, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, England
| | - Jacqueline Shaw
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Leicester, LE2 7LX, England
| | - Christofer Toumazou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, SW7 2AZ, England
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30
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Malpartida-Cardenas K, Miscourides N, Rodriguez-Manzano J, Yu LS, Moser N, Baum J, Georgiou P. Quantitative and rapid Plasmodium falciparum malaria diagnosis and artemisinin-resistance detection using a CMOS Lab-on-Chip platform. Biosens Bioelectron 2019; 145:111678. [PMID: 31541787 PMCID: PMC7224984 DOI: 10.1016/j.bios.2019.111678] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2019] [Revised: 08/01/2019] [Accepted: 09/04/2019] [Indexed: 12/16/2022]
Abstract
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-resistance 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 Plasmodium 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 (CMOS) 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.
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Affiliation(s)
- Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, UK
| | - Nicholas Miscourides
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, UK
| | - Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, UK.
| | - Ling-Shan Yu
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, UK
| | - Nicolas Moser
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, UK
| | - Jake Baum
- Department of Life Sciences, Imperial College London, UK
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, UK
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Moniri A, Rodriguez-Manzano J, Malpartida-Cardenas K, Yu LS, Didelot X, Holmes A, Georgiou P. Framework for DNA Quantification and Outlier Detection Using Multidimensional Standard Curves. Anal Chem 2019; 91:7426-7434. [PMID: 31056898 PMCID: PMC6551572 DOI: 10.1021/acs.analchem.9b01466] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
![]()
Real-time PCR is a highly sensitive
and powerful technology for
the quantification of DNA and has become the method of choice in microbiology,
bioengineering, and molecular biology. Currently, the analysis of
real-time PCR data is hampered by only considering a single feature
of the amplification profile to generate a standard curve. The current
“gold standard” is the cycle-threshold (Ct) method which is known to provide poor quantification
under inconsistent reaction efficiencies. Multiple single-feature
methods have been developed to overcome the limitations of the Ct method; however, there is an unexplored area
of combining multiple features in order to benefit from their joint
information. Here, we propose a novel framework that combines existing
standard curve methods into a multidimensional standard curve. This
is achieved by considering multiple features together such that each
amplification curve is viewed as a point in a multidimensional space.
Contrary to only considering a single-feature, in the multidimensional
space, data points do not fall exactly on the standard curve, which
enables a similarity measure between amplification curves based on
distances between data points. We show that this framework expands
the capabilities of standard curves in order to optimize quantification
performance, provide a measure of how suitable an amplification curve
is for a standard, and thus automatically detect outliers and increase
the reliability of quantification. Our aim is to provide an affordable
solution to enhance existing diagnostic settings through maximizing
the amount of information extracted from conventional instruments.
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Affiliation(s)
- Ahmad Moniri
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , U.K
| | - Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , U.K
| | - Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , U.K
| | - Ling-Shan Yu
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , U.K
| | - Xavier Didelot
- School of Life Sciences and Department of Statistics , University of Warwick , Coventry CV4 7AL , U.K
| | - Alison Holmes
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance , Imperial College London , Hammersmith Hospital Campus, London W12 0NN , U.K
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , U.K
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Ming D, Rawson T, Sangkaew S, Rodriguez-Manzano J, Georgiou P, Holmes A. Connectivity of rapid-testing diagnostics and surveillance of infectious diseases. Bull World Health Organ 2019; 97:242-244. [PMID: 30992638 PMCID: PMC6453318 DOI: 10.2471/blt.18.219691] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 11/30/2018] [Accepted: 12/25/2018] [Indexed: 11/27/2022] Open
Affiliation(s)
- Damien Ming
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Hammersmith Hospital Campus, London W12 0NN, England
| | - Timothy Rawson
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Hammersmith Hospital Campus, London W12 0NN, England
| | - Sorawat Sangkaew
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Hammersmith Hospital Campus, London W12 0NN, England
| | | | - Pantelis Georgiou
- Department of Electrical and Electronic Engineering, Imperial College, London, England
| | - Alison Holmes
- NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, Hammersmith Hospital Campus, London W12 0NN, England
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Rodriguez-Manzano J, Moniri A, Malpartida-Cardenas K, Dronavalli J, Davies F, Holmes A, Georgiou P. Simultaneous Single-Channel Multiplexing and Quantification of Carbapenem-Resistant Genes Using Multidimensional Standard Curves. Anal Chem 2019; 91:2013-2020. [PMID: 30624047 PMCID: PMC6389101 DOI: 10.1021/acs.analchem.8b04412] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Abstract
![]()
Multiplexing
and quantification of nucleic acids, both have, in
their own right, significant and extensive use in biomedical related
fields. 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 four of the most prominent
carbapenem-resistant genes: blaOXA-48, blaNDM, blaVIM, and blaKPC, which account for 97% of
the UK’s reported carbapenemase-producing Enterobacteriaceae.
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Affiliation(s)
- Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London , SW7 2AZ , United Kingdom
| | - Ahmad Moniri
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London , SW7 2AZ , United Kingdom
| | - Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London , SW7 2AZ , United Kingdom
| | - Jyothsna Dronavalli
- Imperial College Healthcare NHS Trust , St. Mary's Hospital , Praed Street , London , W2 1NY , United Kingdom
| | - Frances Davies
- Imperial College Healthcare NHS Trust , St. Mary's Hospital , Praed Street , London , W2 1NY , United Kingdom
| | - Alison Holmes
- National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance , Imperial College London , Hammersmith Campus, W12 0NN , London , United Kingdom
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London , SW7 2AZ , United Kingdom
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Yu LS, Rodriguez-Manzano J, Malpartida-Cardenas K, Sewell T, Bader O, Armstrong-James D, Fisher MC, Georgiou P. Rapid and Sensitive Detection of Azole-Resistant Aspergillus fumigatus by Tandem Repeat Loop-Mediated Isothermal Amplification. J Mol Diagn 2018; 21:286-295. [PMID: 30529128 DOI: 10.1016/j.jmoldx.2018.10.004] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 09/07/2018] [Accepted: 10/16/2018] [Indexed: 12/11/2022] Open
Abstract
Invasive fungal infections caused by multiazole-resistant Aspergillus fumigatus are associated with increasing rates of mortality in susceptible patients. Current methods of diagnosing infections caused by multiazole-resistant A. fumigatus are, however, not well suited for use in clinical point-of-care testing or in the field. Loop-mediated isothermal amplification (LAMP) is a widely used method of nucleic acid amplification with rapid and easy-to-use features, making it suitable for use in different resource settings. Here, we developed a LAMP assay to detect a 34 bp tandem repeat, named TR34-LAMP. TR34 is a high-prevalence allele that, in conjunction with the L98H single-nucleotide polymorphism, is associated with the occurrence of multiazole resistance in A. fumigatus in the environment and in patients. This process was validated with both synthetic double-stranded DNA and genomic DNA prepared from azole-resistant isolates of A. fumigatus. Use of our assay resulted in rapid and specific identification of the TR34 allele with high sensitivity, detecting down to 10 genomic copies per reaction within 25 minutes. Fluorescent and colorimetric detections were used for the analysis of 11 clinical isolates as cross validation. These results show that the TR34-LAMP assay has the potential to accelerate the screening of clinical and environmental A. fumigatus to provide a rapid and accurate diagnosis of azole resistance, which current methods struggle to achieve.
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Affiliation(s)
- Ling-Shan Yu
- Centre for Bio-Inspired Technology, Institute of Biomedical Engineering, Department of Electrical and Electronic Engineering.
| | - Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Institute of Biomedical Engineering, Department of Electrical and Electronic Engineering.
| | - Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Institute of Biomedical Engineering, Department of Electrical and Electronic Engineering
| | - Thomas Sewell
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Oliver Bader
- Institute for Medical Microbiology, University Medical Center Göttingen, Göttingen, Germany
| | | | - Matthew C Fisher
- MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, United Kingdom
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Institute of Biomedical Engineering, Department of Electrical and Electronic Engineering
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Malpartida-Cardenas K, Rodriguez-Manzano J, Yu LS, Delves MJ, Nguon C, Chotivanich K, Baum J, Georgiou P. Allele-Specific Isothermal Amplification Method Using Unmodified Self-Stabilizing Competitive Primers. Anal Chem 2018; 90:11972-11980. [PMID: 30226760 PMCID: PMC6195307 DOI: 10.1021/acs.analchem.8b02416] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Rapid and specific detection of single nucleotide polymorphisms (SNPs) related to drug resistance in infectious diseases is crucial for accurate prognostics, therapeutics and disease management at point-of-care. Here, we present a novel amplification method and provide universal guidelines for the detection of SNPs at isothermal conditions. This method, called USS-sbLAMP, consists of SNP-based loop-mediated isothermal amplification (sbLAMP) primers and unmodified self-stabilizing (USS) competitive primers that robustly delay or prevent unspecific amplification. Both sets of primers are incorporated into the same reaction mixture, but always targeting different alleles; one set specific to the wild type allele and the other to the mutant allele. The mechanism of action relies on thermodynamically favored hybridization of totally complementary primers, enabling allele-specific amplification. We successfully validate our method by detecting SNPs, C580Y and Y493H, in the Plasmodium falciparum kelch 13 gene that are responsible for resistance to artemisinin-based combination therapies currently used globally in the treatment of malaria. USS-sbLAMP primers can efficiently discriminate between SNPs with high sensitivity (limit of detection of 5 × 101 copies per reaction), efficiency, specificity and rapidness (<35 min) with the capability of quantitative measurements for point-of-care diagnosis, treatment guidance, and epidemiological reporting of drug-resistance.
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Affiliation(s)
- Kenny Malpartida-Cardenas
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London , SW7 2AZ , United Kingdom
| | - Jesus Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London , SW7 2AZ , United Kingdom
| | - Ling-Shan Yu
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London , SW7 2AZ , United Kingdom
| | - Michael J Delves
- Department of Life Sciences, Imperial College London , South Kensington Campus , SW7 2AZ , London , United Kingdom
| | - Chea Nguon
- National Centre for Parasitology , Entomology and Malaria Control , Phnom Penh 12302 , Cambodia
| | - Kesinee Chotivanich
- Department of Clinical Tropical Medicine, Faculty of Tropical Medicine , Mahidol University , Bangkok 10400 , Thailand
| | - Jake Baum
- Department of Life Sciences, Imperial College London , South Kensington Campus , SW7 2AZ , London , United Kingdom
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering , Imperial College London , London , SW7 2AZ , United Kingdom
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Miscourides N, Yu LS, Rodriguez-Manzano J, Georgiou P. A 12.8 k Current-Mode Velocity-Saturation ISFET Array for On-Chip Real-Time DNA Detection. IEEE Trans Biomed Circuits Syst 2018; 12:1202-1214. [PMID: 30010599 DOI: 10.1109/tbcas.2018.2851448] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
This paper presents a large-scale CMOS chemical-sensing array operating in current mode for real-time ion imaging and detection of DNA amplification. We show that the current-mode operation of ion-sensitive field-effect transistors in velocity saturation devices can be exploited to achieve an almost perfect linearity in their input-output characteristics (pH-current), which are aligned with the continuous scaling trend of transistors in CMOS. The array is implemented in a 0.35-m process and includes 12.8 k sensors configured in a 2T per pixel topology. We characterize the array by taking into account nonideal effects observed with floating gate devices, such as increased pixel mismatch due to trapped charge and attenuation of the input signal due to the passivation capacitance, and show that the selected biasing regime allows for a sufficiently large linear range that ensures a linear pH to current despite the increased mismatch. The proposed system achieves a sensitivity of 1.03 A/pH with a pH resolution of 0.101 pH and is suitable for the real-time detection of the NDM carbapenemase gene in E. Coli using a loop-mediated isothermal amplification.
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Ma D, Rodriguez-Manzano J, de Mateo Lopez S, Kalofonou M, Georgiou P, Toumazou C. Adapting ISFETs for Epigenetics: An Overview. IEEE Trans Biomed Circuits Syst 2018; 12:1186-1201. [PMID: 30010588 DOI: 10.1109/tbcas.2018.2838153] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
This paper gives an overview of how CMOS design methods can be applied to ion-sensitive field effect transistor (ISFETs) for pH-based DNA methylation and miRNA detection. Design specifications are fundamentally defined by the choice of analysis. As such, the focus for DNA methylation was on developing front-end analogue circuits to carry out Methylation-specific PCR (MSP) for Point-of-Care applications, and sequencing for detailed analysis. The use of MSP prompted the design of an ISFET weak inversion current mirror topology for differential sensing and reduction of drift and temperature sensitivities. The primary limitation in ion-semiconductor sequencing is base calling of repeated nucleotides known as homopolymers. Implementation of a switched current integrator can potentially increase both accuracy and window for detection, within the frequency region of DNA reactions. For quantifying miRNAs, digital back-end processing circuits were considered toward a fully portable platform that can carry out real-time monitoring of DNA amplification reactions. Two systems to evaluate threshold cycles were developed, based on the Derivative method and a new proposed 3-point exponential evaluation aim to reduce detection time simultaneously. Both implementations were tested with datasets from fluorescent qPCR reactions, as well as pH-LAMP experiments that have been optimized for on-chip amplifications. All designs were fabricated in unmodified CMOS with performance assessed based on functionality as well as pH-resolution required in practice.
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Rodriguez-Manzano J, Chia PY, Yeo TW, Holmes A, Georgiou P, Yacoub S. Correction to: Improving Dengue Diagnostics and Management Through Innovative Technology. Curr Infect Dis Rep 2018; 20:28. [PMID: 29951848 DOI: 10.1007/s11908-018-0646-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
In the original publication, the Table 2 contains an error. The original article has been corrected.
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Affiliation(s)
- Jesus Rodriguez-Manzano
- Centre for Bio-inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, UK
| | - Po Ying Chia
- Communicable Diseases Centre, Institute for Infectious Disease and Epidemiology, Tan Tock Seng Hospital, Singapore, Singapore
| | - Tsin Wen Yeo
- Communicable Diseases Centre, Institute for Infectious Disease and Epidemiology, Tan Tock Seng Hospital, Singapore, Singapore.,Lee Kong Chian School ofMedicine, Nanyang Technical University, Singapore, Singapore
| | - Alison Holmes
- Department of Medicine, Imperial College London, London, UK
| | - Pantelis Georgiou
- Centre for Bio-inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, UK
| | - Sophie Yacoub
- Department of Medicine, Imperial College London, London, UK. .,Singapore-MIT Alliance for Research and Technology, Singapore, Singapore. .,Oxford University Clinical Research Unit, Wellcome Trust Asia Programme, Ho Chi Minh City, Vietnam.
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Abstract
PURPOSE OF REVIEW Dengue continues to be a major global public health threat. Symptomatic infections can cause a spectrum of disease ranging from a mild febrile illness to severe and potentially life-threatening manifestations. Management relies on supportive treatment with careful fluid replacement. The purpose of this review is to define the unmet needs and challenges in current dengue diagnostics and patient monitoring and outline potential novel technologies to address these needs. RECENT FINDINGS There have been recent advances in molecular and point-of-care (POC) diagnostics as well as technologies including wireless communication, low-power microelectronics, and wearable sensors that have opened up new possibilities for management, clinical monitoring, and real-time surveillance of dengue. Novel platforms utilizing innovative technologies for POC dengue diagnostics and wearable patient monitors have the potential to revolutionize dengue surveillance, outbreak response, and management at population and individual levels. Validation studies of these technologies are urgently required in dengue-endemic areas.
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Affiliation(s)
- Jesus Rodriguez-Manzano
- Centre for Bio-inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, UK
| | - Po Ying Chia
- Communicable Diseases Centre, Institute for Infectious Disease and Epidemiology, Tan Tock Seng Hospital, Singapore, Singapore
| | - Tsin Wen Yeo
- Communicable Diseases Centre, Institute for Infectious Disease and Epidemiology, Tan Tock Seng Hospital, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technical University, Singapore, Singapore
| | - Alison Holmes
- Department of Medicine, Imperial College London, London, UK
| | - Pantelis Georgiou
- Centre for Bio-inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, UK
| | - Sophie Yacoub
- Department of Medicine, Imperial College London, London, UK.
- Singapore-MIT Alliance for Research and Technology, Singapore, Singapore.
- Oxford University Clinical Research Unit, Wellcome Trust Asia Programme, Ho Chi Minh City, Vietnam.
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Moser N, Rodriguez-Manzano J, Lande TS, Georgiou P. A Scalable ISFET Sensing and Memory Array With Sensor Auto-Calibration for On-Chip Real-Time DNA Detection. IEEE Trans Biomed Circuits Syst 2018; 12:390-401. [PMID: 29570065 DOI: 10.1109/tbcas.2017.2789161] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
This paper presents a novel CMOS-based system-on-chip with a 78 56 ion-sensitive field-effect transistor array using in-pixel quantization and compensation of sensor nonidealities. The pixel integrates sensing circuitry and memory cells to encode the ion concentration in time and store a calibration value per pixel. Temperature sensing pixels spread throughout the array allow temperature monitoring during the reaction. We describe the integration of the array as part of a lab-on-chip cartridge that plugs into a motherboard for power management, biasing, data acquisition, and temperature regulation. This forms a robust ion detection platform, which is demonstrated as a pH sensing system. We show that our calibration is able to perform readout with a linear spread of 0.3% and that the system exhibits a high pH sensitivity of 3.2 /pH. The complete system is shown to perform on-chip real-time DNA amplification and detection of lambda phage DNA by loop-mediated isothermal amplification.
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Fernandez-Cassi X, Timoneda N, Martínez-Puchol S, Rusiñol M, Rodriguez-Manzano J, Figuerola N, Bofill-Mas S, Abril JF, Girones R. Metagenomics for the study of viruses in urban sewage as a tool for public health surveillance. Sci Total Environ 2018; 618:870-880. [PMID: 29108696 DOI: 10.1016/j.scitotenv.2017.08.249] [Citation(s) in RCA: 85] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 08/23/2017] [Accepted: 08/24/2017] [Indexed: 04/14/2023]
Abstract
The application of next-generation sequencing (NGS) techniques for the identification of viruses present in urban sewage has not been fully explored. This is partially due to a lack of reliable and sensitive protocols for studying viral diversity and to the highly complex analysis required for NGS data processing. One important step towards this goal is finding methods that can efficiently concentrate viruses from sewage samples. Here the application of a virus concentration method based on skimmed milk organic flocculation (SMF) using 10L of sewage collected in different seasons enabled the detection of many viruses. However, some viruses, such as human adenoviruses, could not always be detected using metagenomics, even when quantitative PCR (qPCR) assessments were positive. A targeted metagenomic assay for adenoviruses was conducted and 59.41% of the obtained reads were assigned to murine adenoviruses. However, up to 20 different human adenoviruses (HAdV) were detected by this targeted assay being the most abundant HAdV-41 (29.24%) and HAdV-51 (1.63%). To improve metagenomics' sensitivity, two different protocols for virus concentration were comparatively analysed: an ultracentrifugation protocol and a lower-volume SMF protocol. The sewage virome contained 41 viral families, including pathogenic viral species from families Caliciviridae, Adenoviridae, Astroviridae, Picornaviridae, Polyomaviridae, Papillomaviridae and Hepeviridae. The contribution of urine to sewage metavirome seems to be restricted to a few specific DNA viral families, including the polyomavirus and papillomavirus species. In experimental infections with sewage in a rhesus macaque model, infective human hepatitis E and JC polyomavirus were identified. Urban raw sewage consists of the excreta of thousands of inhabitants; therefore, it is a representative sample for epidemiological surveillance purposes. The knowledge of the metavirome is of significance to public health, highlighting the presence of viral strains that are circulating within a population while acting as a complex matrix for viral discovery.
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Affiliation(s)
- X Fernandez-Cassi
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain.
| | - N Timoneda
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain; Computational Genomics Lab, University of Barcelona and Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, Catalonia, Spain
| | - S Martínez-Puchol
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
| | - M Rusiñol
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
| | - J Rodriguez-Manzano
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, United Kingdom
| | - N Figuerola
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
| | - S Bofill-Mas
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
| | - J F Abril
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain; Computational Genomics Lab, University of Barcelona and Institute of Biomedicine (IBUB), University of Barcelona, Barcelona, Catalonia, Spain
| | - R Girones
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Catalonia, Spain
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Rodriguez-Manzano J, Karymov MA, Begolo S, Selck DA, Zhukov D, Jue E, Ismagilov RF. Reading Out Single-Molecule Digital RNA and DNA Isothermal Amplification in Nanoliter Volumes with Unmodified Camera Phones. ACS Nano 2016; 10:3102-13. [PMID: 26900709 PMCID: PMC4819493 DOI: 10.1021/acsnano.5b07338] [Citation(s) in RCA: 92] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Digital single-molecule technologies are expanding diagnostic capabilities, enabling the ultrasensitive quantification of targets, such as viral load in HIV and hepatitis C infections, by directly counting single molecules. Replacing fluorescent readout with a robust visual readout that can be captured by any unmodified cell phone camera will facilitate the global distribution of diagnostic tests, including in limited-resource settings where the need is greatest. This paper describes a methodology for developing a visual readout system for digital single-molecule amplification of RNA and DNA by (i) selecting colorimetric amplification-indicator dyes that are compatible with the spectral sensitivity of standard mobile phones, and (ii) identifying an optimal ratiometric image-process for a selected dye to achieve a readout that is robust to lighting conditions and camera hardware and provides unambiguous quantitative results, even for colorblind users. We also include an analysis of the limitations of this methodology, and provide a microfluidic approach that can be applied to expand dynamic range and improve reaction performance, allowing ultrasensitive, quantitative measurements at volumes as low as 5 nL. We validate this methodology using SlipChip-based digital single-molecule isothermal amplification with λDNA as a model and hepatitis C viral RNA as a clinically relevant target. The innovative combination of isothermal amplification chemistry in the presence of a judiciously chosen indicator dye and ratiometric image processing with SlipChip technology allowed the sequence-specific visual readout of single nucleic acid molecules in nanoliter volumes with an unmodified cell phone camera. When paired with devices that integrate sample preparation and nucleic acid amplification, this hardware-agnostic approach will increase the affordability and the distribution of quantitative diagnostic and environmental tests.
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Abstract
This account examines developments in "digital" biology and chemistry within the context of microfluidics, from a personal perspective. Using microfluidics as a frame of reference, we identify two areas of research within digital biology and chemistry that are of special interest: (i) the study of systems that switch between discrete states in response to changes in chemical concentration of signals, and (ii) the study of single biological entities such as molecules or cells. In particular, microfluidics accelerates analysis of switching systems (i.e., those that exhibit a sharp change in output over a narrow range of input) by enabling monitoring of multiple reactions in parallel over a range of concentrations of signals. Conversely, such switching systems can be used to create new kinds of microfluidic detection systems that provide "analog-to-digital" signal conversion and logic. Microfluidic compartmentalization technologies for studying and isolating single entities can be used to reconstruct and understand cellular processes, study interactions between single biological entities, and examine the intrinsic heterogeneity of populations of molecules, cells, or organisms. Furthermore, compartmentalization of single cells or molecules in "digital" microfluidic experiments can induce switching in a range of reaction systems to enable sensitive detection of cells or biomolecules, such as with digital ELISA or digital PCR. This "digitizing" offers advantages in terms of robustness, assay design, and simplicity because quantitative information can be obtained with qualitative measurements. While digital formats have been shown to improve the robustness of existing chemistries, we anticipate that in the future they will enable new chemistries to be used for quantitative measurements, and that digital biology and chemistry will continue to provide further opportunities for measuring biomolecules, understanding natural systems more deeply, and advancing molecular and cellular analysis. Microfluidics will impact digital biology and chemistry and will also benefit from them if it becomes massively distributed.
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Affiliation(s)
- Daan Witters
- Division of Chemistry and Chemical Engineering, California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA.
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Sun B, Rodriguez-Manzano J, Selck DA, Khorosheva E, Karymov MA, Ismagilov RF. Measuring Fate and Rate of Single-Molecule Competition of Amplification and Restriction Digestion, and Its Use for Rapid Genotyping Tested with Hepatitis C Viral RNA. Angew Chem Int Ed Engl 2014. [DOI: 10.1002/ange.201403035] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
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Sun B, Rodriguez-Manzano J, Selck DA, Khorosheva E, Karymov MA, Ismagilov RF. Measuring fate and rate of single-molecule competition of amplification and restriction digestion, and its use for rapid genotyping tested with hepatitis C viral RNA. Angew Chem Int Ed Engl 2014; 53:8088-8092. [PMID: 24889060 DOI: 10.1002/anie.201403035] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2014] [Indexed: 01/16/2023]
Abstract
We experimentally monitored, at the single-molecule level, the competition among reverse transcription, exponential amplification (RT-LAMP), and linear degradation (restriction enzymes) starting with hepatitis C viral RNA molecules. We found significant heterogeneity in the rate of single-molecule amplification; introduction of the restriction enzymes affected both the rate and the "fate" (the binary outcome) of single-molecule amplification. While end-point digital measurements were primarily sensitive to changes in fate, the bulk real-time kinetic measurements were dominated by the rate of amplification of the earliest molecules, and were not sensitive to fate of the rest of the molecules. We show how this competition of reactions can be used for rapid HCV genotyping with either digital or bulk readout. This work advances our understanding of single-molecule dynamics in reaction networks and may help bring genotyping capabilities out of clinical labs and into limited-resource settings.
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Affiliation(s)
- Bing Sun
- Division of Chemistry and Chemical Engineering California Institute of Technology 1200 E. California Blvd. Pasadena, CA 91125 (USA)
| | - Jesus Rodriguez-Manzano
- Division of Chemistry and Chemical Engineering California Institute of Technology 1200 E. California Blvd. Pasadena, CA 91125 (USA)
| | - David A Selck
- Division of Chemistry and Chemical Engineering California Institute of Technology 1200 E. California Blvd. Pasadena, CA 91125 (USA)
| | - Eugenia Khorosheva
- Division of Chemistry and Chemical Engineering California Institute of Technology 1200 E. California Blvd. Pasadena, CA 91125 (USA)
| | - Mikhail A Karymov
- Division of Chemistry and Chemical Engineering California Institute of Technology 1200 E. California Blvd. Pasadena, CA 91125 (USA)
| | - Rustem F Ismagilov
- Division of Chemistry and Chemical Engineering California Institute of Technology 1200 E. California Blvd. Pasadena, CA 91125 (USA)
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Rodriguez-Manzano J, Hundesa A, Calgua B, Carratala A, Maluquer de Motes C, Rusiñol M, Moresco V, Ramos AP, Martínez-Marca F, Calvo M, Monte Barardi CR, Girones R, Bofill-Mas S. Adenovirus and Norovirus Contaminants in Commercially Distributed Shellfish. Food Environ Virol 2014; 6:31-41. [PMID: 24293153 DOI: 10.1007/s12560-013-9133-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2013] [Accepted: 11/12/2013] [Indexed: 05/22/2023]
Abstract
Shellfish complying with European Regulations based on quantification of fecal bacterial indicators (FIB) are introduced into markets; however, information on viruses, more stable than FIB, is not available in the literature. To assess the presence of noroviruses (NoVs) GI and GII and human adenoviruses (HAdV) in domestic and imported mussels and clams (n = 151) their presence was analyzed during winter seasons (2004-2008) in north-west Spanish markets through a routine surveillance system. All samples tested negative for NoV GI and 13 % were positive for NoV GII. The role of HAdV as viral indicator was evaluated in 20 negative and 10 positive NoV GII samples showing an estimated sensitivity and specificity of HAdV to predict the presence of NoV GII of 100 and 74 % (cut-off 0.5). The levels of HAdV and NoVs and the efficiency of decontamination in shellfish depuration plants (SDP) were evaluated analyzing pre- and post-depurated mussels collected in May-June 2010 from three different SDP. There were no statistically significant differences in the prevalence and quantification of HAdV between pre- and post-depurated shellfish and between seawater entering and leaving the depuration systems. Moreover, infectious HAdV were detected in depurated mussels. These results confirm previous studies showing that current controls and depuration treatments limiting the number of FIB do not guarantee the absence of viruses in shellfish.
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Affiliation(s)
- Jesus Rodriguez-Manzano
- Department of Microbiology, Faculty of Biology, University of Barcelona, Diagonal Ave., 643, 08028, Barcelona, Spain
| | - Ayalkibet Hundesa
- Department of Microbiology, Faculty of Biology, University of Barcelona, Diagonal Ave., 643, 08028, Barcelona, Spain
| | - Byron Calgua
- Department of Microbiology, Faculty of Biology, University of Barcelona, Diagonal Ave., 643, 08028, Barcelona, Spain
| | - Anna Carratala
- Department of Microbiology, Faculty of Biology, University of Barcelona, Diagonal Ave., 643, 08028, Barcelona, Spain
| | - Carlos Maluquer de Motes
- Department of Microbiology, Faculty of Biology, University of Barcelona, Diagonal Ave., 643, 08028, Barcelona, Spain
| | - Marta Rusiñol
- Department of Microbiology, Faculty of Biology, University of Barcelona, Diagonal Ave., 643, 08028, Barcelona, Spain
| | - Vanessa Moresco
- Laboratory of Applied Virology, Microbiology, Inmunology and Parasitology, CCB, Federal Santa Catarina University (UFSC), Florianópolis, Brazil
| | - Ana Paula Ramos
- Laboratory of Applied Virology, Microbiology, Inmunology and Parasitology, CCB, Federal Santa Catarina University (UFSC), Florianópolis, Brazil
| | | | - Miquel Calvo
- Department of Statistics, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | - Celia Regina Monte Barardi
- Laboratory of Applied Virology, Microbiology, Inmunology and Parasitology, CCB, Federal Santa Catarina University (UFSC), Florianópolis, Brazil
| | - Rosina Girones
- Department of Microbiology, Faculty of Biology, University of Barcelona, Diagonal Ave., 643, 08028, Barcelona, Spain.
| | - Sílvia Bofill-Mas
- Department of Microbiology, Faculty of Biology, University of Barcelona, Diagonal Ave., 643, 08028, Barcelona, Spain
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Calgua B, Fumian T, Rusiñol M, Rodriguez-Manzano J, Mbayed VA, Bofill-Mas S, Miagostovich M, Girones R. Detection and quantification of classic and emerging viruses by skimmed-milk flocculation and PCR in river water from two geographical areas. Water Res 2013; 47:2797-810. [PMID: 23535378 DOI: 10.1016/j.watres.2013.02.043] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2012] [Revised: 02/16/2013] [Accepted: 02/21/2013] [Indexed: 05/27/2023]
Abstract
Molecular techniques and virus concentration methods have shown that previously unknown viruses are shed by humans and animals, and may be transmitted by sewage-contaminated water. In the present study, 10-L river-water samples from urban areas in Barcelona, Spain and Rio Janeiro, Brazil, have been analyzed to evaluate the viral dissemination of human viruses, validating also a low-cost concentration method for virus quantification in fresh water. Three viral groups were analyzed: (i) recently reported viruses, klassevirus (KV), asfarvirus-like virus (ASFLV), and the polyomaviruses Merkel cell (MCPyV), KI (KIPyV) and WU (WUPyV); (ii) the gastroenteritis agents noroviruses (NoV) and rotaviruses (RV); and (iii) the human fecal viral indicators in water, human adenoviruses (HAdV) and JC polyomaviruses (JCPyV). Virus detection was based on nested and quantitative PCR assays. For KV and ASFLV, nested PCR assays were developed for the present study. The method applied for virus concentration in fresh water samples is a one-step procedure based on a skimmed-milk flocculation procedure described previously for seawater. Using spiked river water samples, inter- and intra-laboratory assays showed a viral recovery rate of about 50% (20-95%) for HAdV, JCPyV, NoV and RV with a coefficient of variation ≤ 50%. HAdV and JCPyV were detected in 100% (12/12) of the river samples from Barcelona and Rio de Janeiro. Moreover, NoV GGII was detected in 83% (5/6) and MCPyV in 50% (3/6) of the samples from Barcelona, whereas none of the other viruses tested were detected. NoV GGII was detected in 33% (2/6), KV in 33% (2/6), ASFLV in 17% (1/6) and MCPyV in 50% (3/6) of the samples from Rio de Janeiro, whereas KIPyV and WUPyV were not detected. RV were only analyzed in Rio de Janeiro and resulted positive in 67% (4/6) of the samples. The procedure applied here to river water represents a useful, straightforward and cost-effective method that could be applied in routine water quality testing. The results of the assays expand our understanding of the global distribution of the viral pathogens studied here and their persistence in the environment.
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Affiliation(s)
- Byron Calgua
- Department of Microbiology, Faculty of Biology, University of Barcelona, Av. Diagonal 643, Barcelona 08028, Spain
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48
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Calgua B, Rodriguez-Manzano J, Hundesa A, Suñen E, Calvo M, Bofill-Mas S, Girones R. New methods for the concentration of viruses from urban sewage using quantitative PCR. J Virol Methods 2012; 187:215-21. [PMID: 23164995 DOI: 10.1016/j.jviromet.2012.10.012] [Citation(s) in RCA: 73] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2012] [Revised: 10/18/2012] [Accepted: 10/24/2012] [Indexed: 11/24/2022]
Abstract
Viruses are among the most important pathogens present in water contaminated with feces or urine and represent a serious risk to human health. Four procedures for concentrating viruses from sewage have been compared in this work, three of which were developed in the present study. Viruses were quantified using PCR techniques. According to statistical analysis and the sensitivity to detect human adenoviruses (HAdV), JC polyomaviruses (JCPyV) and noroviruses genogroup II (NoV GGII): (i) a new procedure (elution and skimmed-milk flocculation procedure (ESMP)) based on the elution of the viruses with glycine-alkaline buffer followed by organic flocculation with skimmed-milk was found to be the most efficient method when compared to (ii) ultrafiltration and glycine-alkaline elution, (iii) a lyophilization-based method and (iv) ultracentrifugation and glycine-alkaline elution. Through the analysis of replicate sewage samples, ESMP showed reproducible results with a coefficient of variation (CV) of 16% for HAdV, 12% for JCPyV and 17% for NoV GGII. Using spiked samples, the viral recoveries were estimated at 30-95% for HAdV, 55-90% for JCPyV and 45-50% for NoV GGII. ESMP was validated in a field study using twelve 24-h composite sewage samples collected in an urban sewage treatment plant in the North of Spain that reported 100% positive samples with mean values of HAdV, JCPyV and NoV GGII similar to those observed in other studies. Although all of the methods compared in this work yield consistently high values of virus detection and recovery in urban sewage, some require expensive laboratory equipment. ESMP is an effective low-cost procedure which allows a large number of samples to be processed simultaneously and is easily standardizable for its performance in a routine laboratory working in water monitoring. Moreover, in the present study, a CV was applied and proposed as a parameter to evaluate and compare the methods for detecting viruses in sewage samples.
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Affiliation(s)
- Byron Calgua
- Department of Microbiology, Faculty of Biology, University of Barcelona, Av. Diagonal 643, Barcelona 08028, Spain
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Jardi R, Crespo M, Homs M, van den Eynde E, Girones R, Rodriguez-Manzano J, Caballero A, Buti M, Esteban R, Rodriguez-Frias F. HIV, HEV and cirrhosis: evidence of a possible link from eastern Spain. HIV Med 2012; 13:379-83. [PMID: 22257075 DOI: 10.1111/j.1468-1293.2011.00985.x] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/08/2011] [Indexed: 12/11/2022]
Abstract
OBJECTIVES The aim of the study was to assess the seroprevalence of hepatitis E virus (HEV) infection in an HIV-infected population, as determined by HEV immunoglobulin G (IgG) antibodies (anti-HEV). METHODS The design of the study was cross-sectional. Serum anti-HEV IgG was determined by enzyme immunoassay in 238 HIV-infected patients consecutively attending our out-patient clinic between April and May 2011. In HEV-seropositive patients, HEV RNA was analysed by nested reverse transcriptase-polymerase chain reaction (RT-PCR). Associations between anti-HEV and liver cirrhosis, route of HIV infection, hepatitis B virus (HBV) and hepatitis C virus (HCV) serological markers, age, sex and alanine aminotransferase (ALT) levels were examined by univariate and multivariate analysis. RESULTS One hundred and forty patients (59%) had chronic liver disease (99% were HBV- and/or HCV-coinfected). Liver cirrhosis was detected in 44 individuals (19%). Two hundred and twelve patients (89%) were on antiretroviral treatment; the median CD4 T-cell count was 483 cells/μL [interquartile range (IQR) 313-662 cells/μL] and the HIV viral load was <25 HIV-1 RNA copies/mL. Overall, 22 patients (9%) were anti-HEV positive. Liver cirrhosis was the only factor independently associated with the presence of anti-HEV, which was documented in 23% of patients with cirrhosis and 6% of patients without cirrhosis (P=0.002; odds ratio 5.77). HEV RNA was detected in three seropositive patients (14%), two of whom had liver cirrhosis. CONCLUSIONS Our findings show a high prevalence of anti-HEV in HIV-infected patients, strongly associated with liver cirrhosis. Chronic HEV infection was detected in a significant number of HEV-seropositive patients. Further research is needed to ascertain whether cirrhosis is a predisposing factor for HEV infection and to assess the role of chronic HEV infection in the pathogeneses of cirrhosis in this population.
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Affiliation(s)
- R Jardi
- Department of Biochemistry, Vall d'Hebron Hospital, University "Autonoma" of Barcelona, Barcelona, Spain
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50
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Rodriguez-Manzano J, Alonso JL, Ferrús MA, Moreno Y, Amorós I, Calgua B, Hundesa A, Guerrero-Latorre L, Carratala A, Rusiñol M, Girones R. Standard and new faecal indicators and pathogens in sewage treatment plants, microbiological parameters for improving the control of reclaimed water. Water Sci Technol 2012; 66:2517-23. [PMID: 23109565 DOI: 10.2166/wst.2012.233] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
This study involved collaboration between three centres with expertise in viruses, bacteria and protozoa. The focus of the research was the study of the dissemination and removal of pathogens and faecal indicators in two sewage treatment plants (STP1 and STP2) using tertiary treatments. Samples were collected over a period of five months through the sewage treatment processes. Analysis of the samples revealed that the plants were not efficient at removing the faecal indicators and pathogens tested during the study. From entry point (raw sewage) to effluent level (tertiary treatment effluent water), the experimental results showed that the reduction ratios of human adenoviruses were 1.2 log₁₀ in STP1 and 1.9 log₁₀ in STP2. Whereas for Giardia spp. and Cryptosporidium spp. the reduction ratios were 2.3 log₁₀ for both pathogens in STP1, and 3.0 and 1.7 log₁₀ in STP2, respectively. Furthermore, the presence of faecal indicators and pathogens at different sampling points was evaluated revealing that the tested pathogens were present in reclaimed water. Human adenovirus and Arcobacter spp. showed positive results in infectivity assays for most of the tertiary effluent water samples that comply with current legislation in Spain. The pathogens detected must be evaluated using a risk assessment model, which will be essential for the development of improved guidelines for the re-use of reclaimed water.
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Affiliation(s)
- J Rodriguez-Manzano
- Department of Microbiology, Faculty of Biology, University of Barcelona, Spain.
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