ArticleJournal of visualized experiments : JoVE2012
High-throughput detection method for influenza virus.
Article in Journal of visualized experiments : JoVE, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Functional evaluation for adequacy of MDCK-lineage cells in influenza research.BMC research notes · 2019Article
- Systemic and mucosal humoral immune responses induced by the JY-adjuvanted nasal spray H7N9 vaccine in mice.Emerging microbes & infections · 2018Article
- A Novel Method to Titrate Herpes Simplex Virus-1 (HSV-1) Using Laser-Based Scanning of Near-Infrared Fluorophores Conjugated Antibodies.Frontiers in microbiology · 2017Article
- Quantitative imaging of tissue sections using infrared scanning technology.Journal of anatomy · 2016Article
- IL-22 from conventional NK cells is epithelial regenerative and inflammation protective during influenza infection.Mucosal immunology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
Influenza virus is a respiratory pathogen that causes a high degree of morbidity and mortality every year in multiple parts of the world. Therefore, precise diagnosis of the infecting strain and rapid high-throughput screening of vast numbers of clinical samples is paramount to control the spread of pandemic infections. Current clinical diagnoses of influenza infections are based on serologic testing, polymerase chain reaction, direct specimen immunofluorescence and cell culture (1,2). Here, we report the development of a novel diagnostic technique used to detect live influenza viruses. We used the mouse-adapted human A/PR/8/34 (PR8, H1N1) virus (3) to test the efficacy of this technique using MDCK cells (4). MDCK cells (10(4) or 5 x 10(3) per well) were cultured in 96- or 384-well plates, infected with PR8 and viral proteins were detected using anti-M2 followed by an IR dye-conjugated secondary antibody. M2 (5) and hemagglutinin (1) are two major marker proteins used in many different diagnostic assays. Employing IR-dye-conjugated secondary antibodies minimized the autofluorescence associated with other fluorescent dyes. The use of anti-M2 antibody allowed us to use the antigen-specific fluorescence intensity as a direct metric of viral quantity. To enumerate the fluorescence intensity, we used the LI-COR Odyssey-based IR scanner. This system uses two channel laser-based IR detections to identify fluorophores and differentiate them from background noise. The first channel excites at 680 nm and emits at 700 nm to help quantify the background. The second channel detects fluorophores that excite at 780 nm and emit at 800 nm. Scanning of PR8-infected MDCK cells in the IR scanner indicated a viral titer-dependent bright fluorescence. A positive correlation of fluorescence intensity to virus titer starting from 10(2)-10(5) PFU could be consistently observed. Minimal but detectable positivity consistently seen with 10(2)-10(3) PFU PR8 viral titers demonstrated the high sensitivity of the near-IR dyes. The signal-to-noise ratio was determined by comparing the mock-infected or isotype antibody-treated MDCK cells. Using the fluorescence intensities from 96- or 384-well plate formats, we constructed standard titration curves. In these calculations, the first variable is the viral titer while the second variable is the fluorescence intensity. Therefore, we used the exponential distribution to generate a curve-fit to determine the polynomial relationship between the viral titers and fluorescence intensities. Collectively, we conclude that IR dye-based protein detection system can help diagnose infecting viral strains and precisely enumerate the titer of the infecting pathogens.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.