Influenza annually infects 5-20% of the US population leading to 39,000 deaths and $87.1 billion lost in economic output. Current strategies for mitigating these effects include vaccination and antiviral therapies. Of the latter, the best available medications are oseltamivir and zanamivir, which can reduce the duration of influenza infections by 30%. These antivirals have relatively few side effects, and thereby their prescription is indicated in confirmed cases of influenza infection. Unfortunately, these medications are available in limited quantities, are costly, and are only effective against particular viral subtypes. Furthermore, they are most effective when administered early, preferably within the first 12 hours of symptoms. Thus, in order to guide clinical care with regards to antiviral usage, clinicians need accurate and rapid diagnostics for influenza. Currently available influenza diagnostic are either fast with low sensitivity or slow with high sensitivity, nd there is an unmet clinical need for fast, sensitive, and specific influenza diagnostics. We address this need by developing an integrated system for ultra-rapid and highly sensitive detection of influenza via oligonucleotide- based RNA fluorescent in situ hybridization (RNA FISH). In our preliminary experiments, we designed and tested RNA FISH probes targeting the influenza virus in a cell culture model of influenza infection, showing that our probes exhibit dramatic signal to background by brightly labeling infected cells and leaving uninfected cells undetected. We pushed the assay further by designing influenza subtype-specific probes to target influenza A H1N1, H3N2 and influenza B, finding that these probe sets are of distinguishing subtypes with virtually perfect discriminative ability in cell culture models system infected with the human strains. To enable diagnostic applications of this assay, we next developed a closed-format microfluidic device to automatically concentrate cells from a nasal swab, perform RNA FISH, and analyze the resulting images. This proposal outlines the next steps in translating RNA FISH from a research technique into a clinically viable diagnostic test for influenza. In the first aim, we reconfigure the geometry of our microfluidic device to perform multiple assays with one chip, thereby allowing us to use all of our subtype specific probes on one specimen. Next, we will optimize the multiplex chip and then test human nasal specimens on this platform.
In aim two, we will validate RNA FISH based influenza detection on clinical nasal specimens from patients infected with the virus. We will recruit subjects from the Children's Hospital of Philadelphia who previously had influenza RT-PCR tests performed as part of their routine clinical care. With a pool of positive and negative subjects, we will formalie a protocol for running the microfluidic chip and optimize the assay on clinical samples. Next, we will establish the sensitivity and specificity of the assay for influenza detection and subtype discrimination. Successful completion of these aims will prove that ultra-rapid RNA FISH is a viable and potentially paradigm shifting point-of-care diagnostic.

Public Health Relevance

Influenza viruses are a major source of respiratory illness, infecting 5-20% of the United States population annually. In order to administer anti-influenza medications, clinicians need fast and accurate diagnostics to confirm infection. We will develop a new molecular diagnostic to rapidly diagnose influenza at the point of care.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Individual Predoctoral NRSA for M.D./Ph.D. Fellowships (ADAMHA) (F30)
Project #
5F30AI114475-02
Application #
9045376
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Krafft, Amy
Project Start
2015-02-01
Project End
2018-01-31
Budget Start
2016-02-01
Budget End
2017-01-31
Support Year
2
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104
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Torre, Eduardo; Dueck, Hannah; Shaffer, Sydney et al. (2018) Rare Cell Detection by Single-Cell RNA Sequencing as Guided by Single-Molecule RNA FISH. Cell Syst 6:171-179.e5
Shaffer, Sydney M; Dunagin, Margaret C; Torborg, Stefan R et al. (2017) Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature 546:431-435
Dar, Roy D; Shaffer, Sydney M; Singh, Abhyudai et al. (2016) Transcriptional Bursting Explains the Noise-Versus-Mean Relationship in mRNA and Protein Levels. PLoS One 11:e0158298
Shaffer, Sydney M; Joshi, Rohan P; Chambers, Benjamin S et al. (2015) Multiplexed detection of viral infections using rapid in situ RNA analysis on a chip. Lab Chip 15:3170-82