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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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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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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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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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5
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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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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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7
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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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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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9
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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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10
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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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11
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Dortet L, Bonnin RA, Pennisi I, Gauthier L, Jousset AB, Dabos L, Furniss RCD, Mavridou DAI, Bogaerts P, Glupczynski Y, Potron A, Plesiat P, Beyrouthy R, Robin F, Bonnet R, Naas T, Filloux A, Larrouy-Maumus G. Rapid detection and discrimination of chromosome- and MCR-plasmid-mediated resistance to polymyxins by MALDI-TOF MS in Escherichia coli: the MALDIxin test. J Antimicrob Chemother 2018; 73:3359-3367. [PMID: 30184212 DOI: 10.1093/jac/dky330] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 07/26/2018] [Indexed: 12/21/2022] Open
Abstract
Background Polymyxins are currently considered a last-resort treatment for infections caused by MDR Gram-negative bacteria. Recently, the emergence of carbapenemase-producing Enterobacteriaceae has accelerated the use of polymyxins in the clinic, resulting in an increase in polymyxin-resistant bacteria. Polymyxin resistance arises through modification of lipid A, such as the addition of phosphoethanolamine (pETN). The underlying mechanisms involve numerous chromosome-encoded genes or, more worryingly, a plasmid-encoded pETN transferase named MCR. Currently, detection of polymyxin resistance is difficult and time consuming. Objectives To develop a rapid diagnostic test that can identify polymyxin resistance and at the same time differentiate between chromosome- and plasmid-encoded resistances. Methods We developed a MALDI-TOF MS-based method, named the MALDIxin test, which allows the detection of polymyxin resistance-related modifications to lipid A (i.e. pETN addition), on intact bacteria, in <15 min. Results Using a characterized collection of polymyxin-susceptible and -resistant Escherichia coli, we demonstrated that our method is able to identify polymyxin-resistant isolates in 15 min whilst simultaneously discriminating between chromosome- and plasmid-encoded resistance. We validated the MALDIxin test on different media, using fresh and aged colonies and show that it successfully detects all MCR-1 producers in a blindly analysed set of carbapenemase-producing E. coli strains. Conclusions The MALDIxin test is an accurate, rapid, cost-effective and scalable method that represents a major advance in the diagnosis of polymyxin resistance by directly assessing lipid A modifications in intact bacteria.
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Affiliation(s)
- Laurent Dortet
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, UK.,Department of Bacteriology-Hygiene, Bicêtre Hospital, Assistance Publique - Hôpitaux de Paris, Le Kremlin-Bicêtre, France.,EA7361 'Structure, dynamic, function and expression of broad spectrum β-lactamases', Paris-Sud University, Paris Saclay University, LabEx Lermit, Faculty of Medicine, Le Kremlin-Bicêtre, France.,French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France
| | - Remy A Bonnin
- EA7361 'Structure, dynamic, function and expression of broad spectrum β-lactamases', Paris-Sud University, Paris Saclay University, LabEx Lermit, Faculty of Medicine, Le Kremlin-Bicêtre, France.,French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France
| | - Ivana Pennisi
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, UK
| | - Lauraine Gauthier
- Department of Bacteriology-Hygiene, Bicêtre Hospital, Assistance Publique - Hôpitaux de Paris, Le Kremlin-Bicêtre, France.,EA7361 'Structure, dynamic, function and expression of broad spectrum β-lactamases', Paris-Sud University, Paris Saclay University, LabEx Lermit, Faculty of Medicine, Le Kremlin-Bicêtre, France.,French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France
| | - Agnès B Jousset
- Department of Bacteriology-Hygiene, Bicêtre Hospital, Assistance Publique - Hôpitaux de Paris, Le Kremlin-Bicêtre, France.,EA7361 'Structure, dynamic, function and expression of broad spectrum β-lactamases', Paris-Sud University, Paris Saclay University, LabEx Lermit, Faculty of Medicine, Le Kremlin-Bicêtre, France.,French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France
| | - Laura Dabos
- EA7361 'Structure, dynamic, function and expression of broad spectrum ß-lactamases', Paris-Sud University, Paris Saclay University, LabEx Lermit, Faculty of Medicine, Le Kremlin-Bicêtre, France
| | - R Christopher D Furniss
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, UK
| | - Despoina A I Mavridou
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, UK
| | - Pierre Bogaerts
- Laboratory of Clinical Microbiology, Belgian National Reference Center for Monitoring Antimicrobial Resistance in Gram-negative Bacteria, CHU UCL Namur, Yvoir, Belgium
| | - Youri Glupczynski
- Laboratory of Clinical Microbiology, Belgian National Reference Center for Monitoring Antimicrobial Resistance in Gram-negative Bacteria, CHU UCL Namur, Yvoir, Belgium
| | - Anais Potron
- French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France.,Bacteriology Unit, University Hospital of Besançon, Besançon, France
| | - Patrick Plesiat
- French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France.,Bacteriology Unit, University Hospital of Besançon, Besançon, France
| | - Racha Beyrouthy
- French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France.,Bacteriology Unit, University Hospital of Clermont-Ferrand, Clermont-Ferrand, France
| | - Frédéric Robin
- French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France.,Bacteriology Unit, University Hospital of Clermont-Ferrand, Clermont-Ferrand, France
| | - Richard Bonnet
- French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France.,Bacteriology Unit, University Hospital of Clermont-Ferrand, Clermont-Ferrand, France
| | - Thierry Naas
- Department of Bacteriology-Hygiene, Bicêtre Hospital, Assistance Publique - Hôpitaux de Paris, Le Kremlin-Bicêtre, France.,EA7361 'Structure, dynamic, function and expression of broad spectrum β-lactamases', Paris-Sud University, Paris Saclay University, LabEx Lermit, Faculty of Medicine, Le Kremlin-Bicêtre, France.,French National Reference Center for Antibiotic Resistance, Le Kremlin-Bicêtre, France
| | - Alain Filloux
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, UK
| | - Gerald Larrouy-Maumus
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences, Imperial College London, London, UK
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12
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Rebollo-Ramirez S, Krokowski S, Lobato-Márquez D, Thomson M, Pennisi I, Mostowy S, Larrouy-Maumus G. Intact Cell Lipidomics Reveal Changes to the Ratio of Cardiolipins to Phosphatidylinositols in Response to Kanamycin in HeLa and Primary Cells. Chem Res Toxicol 2018; 31:688-696. [PMID: 29947513 PMCID: PMC6103485 DOI: 10.1021/acs.chemrestox.8b00038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
![]()
Antimicrobial resistance is a major
threat the world is currently
facing. Development of new antibiotics and the assessment of their
toxicity represent important challenges. Current methods for addressing
antibiotic toxicity rely on measuring mitochondrial damage using ATP
and/or membrane potential as a readout. In this study, we propose
an alternative readout looking at changes in the lipidome on intact
and unprocessed cells by matrix-assisted laser desorption ionization
mass spectrometry. As a proof of principle, we evaluated the impact
of known antibiotics (levofloxacin, ethambutol, and kanamycin) on
the lipidome of HeLa cells and mouse bone marrow-derived macrophages.
Our methodology revealed that clinically relevant concentrations of
kanamycin alter the ratio of cardiolipins to phosphatidylinositols.
Unexpectedly, only kanamycin had this effect even though all antibiotics
used in this study led to a decrease in the maximal mitochondrial
respiratory capacity. Altogether, we report that intact cell-targeted
lipidomics can be used as a qualitative method to rapidly assess the
toxicity of aminoglycosides in HeLa and primary cells. Moreover, these
results demonstrate there is no direct correlation between the ratio
of cardiolipins to phosphatidylinositols and the maximal mitochondrial
respiratory capacity.
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Affiliation(s)
- Sonia Rebollo-Ramirez
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences , Imperial College London , London SW7 2AZ , U.K
| | - Sina Krokowski
- MRC Centre for Molecular Bacteriology and Infection, Department of Medicine, Section of Microbiology , Imperial College London , London W12 0NN , U.K.,Department of Immunology and Infection , London School of Hygiene and Tropical Medicine , Keppel Street , London WC1E 7HT , U.K
| | - Damian Lobato-Márquez
- MRC Centre for Molecular Bacteriology and Infection, Department of Medicine, Section of Microbiology , Imperial College London , London W12 0NN , U.K.,Department of Immunology and Infection , London School of Hygiene and Tropical Medicine , Keppel Street , London WC1E 7HT , U.K
| | - Michael Thomson
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences , Imperial College London , London SW7 2AZ , U.K
| | - Ivana Pennisi
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences , Imperial College London , London SW7 2AZ , U.K
| | - Serge Mostowy
- MRC Centre for Molecular Bacteriology and Infection, Department of Medicine, Section of Microbiology , Imperial College London , London W12 0NN , U.K.,Department of Immunology and Infection , London School of Hygiene and Tropical Medicine , Keppel Street , London WC1E 7HT , U.K
| | - Gerald Larrouy-Maumus
- MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Faculty of Natural Sciences , Imperial College London , London SW7 2AZ , U.K
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