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Zhang Z, Ma P, Ahmed R, Wang J, Akin D, Soto F, Liu BF, Li P, Demirci U. Advanced Point-of-Care Testing Technologies for Human Acute Respiratory Virus Detection. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2103646. [PMID: 34623709 DOI: 10.1002/adma.202103646] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 08/25/2021] [Indexed: 04/14/2023]
Abstract
The ever-growing global threats to human life caused by the human acute respiratory virus (RV) infections have cost billions of lives, created a significant economic burden, and shaped society for centuries. The timely response to emerging RVs could save human lives and reduce the medical care burden. The development of RV detection technologies is essential for potentially preventing RV pandemic and epidemics. However, commonly used detection technologies lack sensitivity, specificity, and speed, thus often failing to provide the rapid turnaround times. To address this problem, new technologies are devised to address the performance inadequacies of the traditional methods. These emerging technologies offer improvements in convenience, speed, flexibility, and portability of point-of-care test (POCT). Herein, recent developments in POCT are comprehensively reviewed for eight typical acute respiratory viruses. This review discusses the challenges and opportunities of various recognition and detection strategies and discusses these according to their detection principles, including nucleic acid amplification, optical POCT, electrochemistry, lateral flow assays, microfluidics, enzyme-linked immunosorbent assays, and microarrays. The importance of limits of detection, throughput, portability, and specificity when testing clinical samples in resource-limited settings is emphasized. Finally, the evaluation of commercial POCT kits for both essential RV diagnosis and clinical-oriented practices is included.
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Affiliation(s)
- Zhaowei Zhang
- Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, National Reference Laboratory for Agricultural Testing (Biotoxin), Key Laboratory of Biology and Genetic Improvement of Oil Crops, Key Laboratory of Detection for Mycotoxins, Ministry of Agriculture and Rural Affairs, Wuhan, 430062, P. R. China
- Bio-Acoustic MEMS in Medicine (BAMM) Laboratory, Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford School of Medicine, Palo Alto, CA, 94304, USA
| | - Peng Ma
- Bio-Acoustic MEMS in Medicine (BAMM) Laboratory, Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford School of Medicine, Palo Alto, CA, 94304, USA
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China
| | - Rajib Ahmed
- Bio-Acoustic MEMS in Medicine (BAMM) Laboratory, Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford School of Medicine, Palo Alto, CA, 94304, USA
| | - Jie Wang
- Bio-Acoustic MEMS in Medicine (BAMM) Laboratory, Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford School of Medicine, Palo Alto, CA, 94304, USA
| | - Demir Akin
- Bio-Acoustic MEMS in Medicine (BAMM) Laboratory, Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford School of Medicine, Palo Alto, CA, 94304, USA
| | - Fernando Soto
- Bio-Acoustic MEMS in Medicine (BAMM) Laboratory, Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford School of Medicine, Palo Alto, CA, 94304, USA
| | - Bi-Feng Liu
- The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics - Hubei Bioinformatics & Molecular Imaging Key Laboratory Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China
| | - Peiwu Li
- Oil Crops Research Institute of Chinese Academy of Agricultural Sciences, National Reference Laboratory for Agricultural Testing (Biotoxin), Key Laboratory of Biology and Genetic Improvement of Oil Crops, Key Laboratory of Detection for Mycotoxins, Ministry of Agriculture and Rural Affairs, Wuhan, 430062, P. R. China
| | - Utkan Demirci
- Bio-Acoustic MEMS in Medicine (BAMM) Laboratory, Canary Center at Stanford for Cancer Early Detection, Department of Radiology, Stanford School of Medicine, Palo Alto, CA, 94304, USA
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Sederdahl BK, Williams JV. Epidemiology and Clinical Characteristics of Influenza C Virus. Viruses 2020; 12:E89. [PMID: 31941041 PMCID: PMC7019359 DOI: 10.3390/v12010089] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 01/06/2020] [Accepted: 01/07/2020] [Indexed: 12/14/2022] Open
Abstract
Influenza C virus (ICV) is a common yet under-recognized cause of acute respiratory illness. ICV seropositivity has been found to be as high as 90% by 7-10 years of age, suggesting that most people are exposed to ICV at least once during childhood. Due to difficulty detecting ICV by cell culture, epidemiologic studies of ICV likely have underestimated the burden of ICV infection and disease. Recent development of highly sensitive RT-PCR has facilitated epidemiologic studies that provide further insights into the prevalence, seasonality, and course of ICV infection. In this review, we summarize the epidemiology and clinical characteristics of ICV.
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Affiliation(s)
- Bethany K. Sederdahl
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA;
| | - John V. Williams
- Department of Pediatrics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA;
- Institute for Infection, Inflammation, and Immunity in Children (i4Kids), University of Pittsburgh, Pittsburgh, PA 15224, USA
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Zhang H, Wang Y, Porter E, Lu N, Li Y, Yuan F, Lohman M, Noll L, Zheng W, Stoy C, Lang Y, Huber VC, Ma W, Peddireddi L, Fang Y, Shi J, Anderson G, Liu X, Bai J. Development of a multiplex real-time RT-PCR assay for simultaneous detection and differentiation of influenza A, B, C, and D viruses. Diagn Microbiol Infect Dis 2019; 95:59-66. [PMID: 31130238 PMCID: PMC6697560 DOI: 10.1016/j.diagmicrobio.2019.04.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 04/08/2019] [Accepted: 04/23/2019] [Indexed: 01/18/2023]
Abstract
Influenza is a common and contagious respiratory disease caused by influenza A, B, C, and D viruses (IAV, IBV, ICV, and IDV). A multiplex real-time RT-PCR assay was developed for simultaneous detection of IAV, IBV, ICV, and IDV. The assay was designed to target unique sequences in the matrix gene of IBV and ICV, the RNA polymerase subunit PB1 of IDV, and combined with USDA and CDC IAV assays, both target the matrix gene. The host 18S rRNA gene was included as an internal control. In silico analyses indicated high strain coverages: 97.9% for IBV, 99.5% for ICV, and 100% for IDV. Transcribed RNA, viral isolates and clinical samples were used for validation. The assay specifically detected target viruses without cross-reactivity, nor detection of other common pathogens. The limit of detection was approximately 30 copies for each viral RNA template, which was equivalent to a threshold cycle value of ~37.
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Affiliation(s)
- Hewei Zhang
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA; College of Food and Drugs, Luoyang Polytechnic, Luo Yang, Henan, China
| | - Yin Wang
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Elizabeth Porter
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Nanyan Lu
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Yanhua Li
- Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Fangfeng Yuan
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Molly Lohman
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Lance Noll
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Wanglong Zheng
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Colin Stoy
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Yuekun Lang
- Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Victor C Huber
- Division of Basic Biomedical Sciences, Sanford School of Medicine, The University of South Dakota, Vermillion, SD, USA
| | - Wenjun Ma
- Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Lalitha Peddireddi
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA; Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Ying Fang
- Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Jishu Shi
- Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Gary Anderson
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA; Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Xuming Liu
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA; Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.
| | - Jianfa Bai
- Kansas State Veterinary Diagnostic Laboratory, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA; Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA.
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Fritsch A, Schweiger B, Biere B. Influenza C virus in pre-school children with respiratory infections: retrospective analysis of data from the national influenza surveillance system in Germany, 2012 to 2014. Euro Surveill 2019; 24:1800174. [PMID: 30862333 PMCID: PMC6415498 DOI: 10.2807/1560-7917.es.2019.24.10.1800174] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Accepted: 12/31/2018] [Indexed: 11/23/2022] Open
Abstract
IntroductionRecent data on influenza C virus indicate a possible higher clinical impact in specified patient populations than previously thought.AimWe aimed to investigate influenza C virus circulation in Germany.MethodsA total of 1,588 samples from 0 to 4 year-old children presenting as outpatients with influenza-like illness (ILI) or acute respiratory infection were analysed retrospectively. The samples represented a subset of all samples from the German national surveillance system for influenza in this age group in 2012-14. The presence of influenza C virus was investigated by real-time PCR. For positive samples, information on symptoms as well as other respiratory virus co-infections was considered. Retrieved influenza C viral sequences were phylogenetically characterised.ResultsInfluenza C viral RNA was detected in 20 (1.3% of) samples, including 16 during the 2012/13 season. The majority (18/20) of influenza C-positive patients had ILI according to the European Union definition, one patient had pneumonia. Viruses belonged to the C/Sao Paulo and C/Kanagawa lineages. Most (11/20) samples were co-infected with other respiratory viruses.ConclusionOur data are the first on influenza C virus circulation in Germany and notably from a European national surveillance system. The low detection frequency and the identified virus variants confirm earlier observations outside a surveillance system. More virus detections during the 2012/13 season indicate a variable circulation intensity in the different years studied. Influenza C virus can be considered for ILI patients. Future studies addressing its clinical impact, especially in patients with severe disease are needed.
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Affiliation(s)
- Annemarie Fritsch
- Robert Koch Institute, National Reference Center for Influenza, FG 17 Influenza and Other Respiratory Viruses, Berlin, Germany
| | - Brunhilde Schweiger
- Robert Koch Institute, National Reference Center for Influenza, FG 17 Influenza and Other Respiratory Viruses, Berlin, Germany
| | - Barbara Biere
- Robert Koch Institute, National Reference Center for Influenza, FG 17 Influenza and Other Respiratory Viruses, Berlin, Germany
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