Respiratory Mucosal Proteome Quantification in Human Influenza Infections

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Abstract

Respiratory influenza virus infections represent a serious threat to human health. Underlying medical conditions and genetic make-up predispose some influenza patients to more severe forms of disease. To date, only a few studies have been performed in patients to correlate a selected group of cytokines and chemokines with influenza infection. Therefore, we evaluated the potential of a novel multiplex micro-proteomics technology, SOMAscan, to quantify proteins in the respiratory mucosa of influenza A and B infected individuals. The analysis included but was not limited to quantification of cytokines and chemokines detected in previous studies. SOMAscan quantified more than 1,000 secreted proteins in small nasal wash volumes from infected and healthy individuals. Our results illustrate the utility of micro-proteomic technology for analysis of proteins in small volumes of respiratory mucosal samples. Furthermore, when we compared nasal wash samples from influenzainfected patients with viral load ≥ 28 and increased IL-6 and CXCL10 to healthy controls, we identified 162 differentially-expressed proteins between the two groups. This number greatly exceeds the number of DEPs identified in previous studies in human influenza patients. Most of the identified proteins were associated with the host immune response to infection, and changes in protein levels of 151 of the DEPs were significantly correlated with viral load. Most important, SOMAscan identified differentially expressed proteins heretofore not associated with respiratory influenza infection in humans. Our study is the first report for the use of SOMAscan to screen nasal secretions. It establishes a precedent for micro-proteomic quantification of proteins that reflect ongoing response to respiratory infection.

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Marion, T., Elbahesh, H., Thomas, P. G., DeVincenzo, J. P., Webby, R., & Schughart, K. (2016). Respiratory Mucosal Proteome Quantification in Human Influenza Infections. PLoS ONE, 11(4). https://doi.org/10.1371/journal.pone.0153674

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