In the past two decades, in addition to the expected annual viral infections, several emerging respiratory viruses have had a global impact including the SARS coronavirus, the 2009 swine flu, and currently the emerging 2019 coronavirus (2019-nCoV). The ability to screen for potential emerging viral pathogens would enable better preparation for such events. Current diagnostic tests for respiratory viruses readily detect known viruses, but do not detect unexpected viruses. However, prior work shows that many respiratory viruses induce a common pattern of gene and protein expression in the nasopharynx. This project will measure this host antiviral response in samples from symptomatic patients which have tested negative for common respiratory viruses. The central hypothesis of this project is that unexpected or emerging viruses will be found in patient samples in which a nasal antiviral response is evident, but no known viruses have been detected. The long- term objective of this work is to define an efficient strategy to identify unexpected or emerging viral respiratory pathogens, in order to aid in efforts to anticipate and prepare for the spread of illnesses caused by these viruses. In the proposed project, we will investigate our central hypothesis by screening samples from symptomatic patients to look for samples testing negative for known viruses, but positive for a biomarker of the antiviral response that we defined in previous work.
In Aim 1, we will perform a detailed evaluation of these ?screen- positive? samples to look for unexpected or novel viruses using a range of techniques which include next generation sequencing and advanced bioinformatics analysis, and classic virus discovery techniques such as viral culture and isolation and electron microscopy.
In Aim 2, we will generate reference nasopharyngeal transcriptomes from patients with known viral infections including coronaviruses, a group which includes several high-impact emerging viruses but which has not yet been studied in this way. These reference transcriptomes will serve as a resource for evaluating samples with suspected novel viral infections and will also inform further refinements of the screening strategy. Together, these aims will advance a promising new strategy for detecting unrecognized viruses able to cause illness in humans.
In the past two decades, in addition to the expected annual viral infections, several emerging respiratory viruses have had a global impact including the SARS coronavirus, the 2009 swine flu, and 2019 novel coronavirus. Early detection of potentially dangerous viruses in the human population would allow more lead time to develop diagnostic tests, treatments, and vaccines. In this project, we will develop a new screening method to enable detection of unexpected viruses, in which we will use the body's response to infection to pinpoint which patient samples are most likely to contain an unrecognized but potentially dangerous virus.
