| Abstrakt: |
Background Respiratory virus infections are important causes of morbidity and mortality among pediatric and adult patients. These viruses infect respiratory epithelial cells, where they may induce specific metabolite alterations. As a proof-of-concept, we investigate the novel use of liquid chromatography (LC) combined with quadrupole time-of-flight mass spectrometry (Q-TOF) for the study of host cell metabolite alterations to diagnose and differentiate respiratory viruses. Methods We studied nasopharyngeal swab samples positive for respiratory viruses by the eSensor Respiratory Viral Panel (GenMark Diagnostics, Carlsbad, CA). Banked, frozen samples (−80°C) stored in viral transport media were retrieved and thawed. Aliquots of 100 μL were centrifuged at 13.3 × g for 15 minutes, and the filtrate was analyzed by Agilent 6545 Quadrupole LC/Q-TOF (Agilent Technologies, Santa Clara, CA). Compounds were separated using a novel column arrangement based on hydrophobicity and charge using a quaternary solvent manager, followed by accurate mass analysis by LC/Q-TOF. Agilent Mass Profiler 3D principal component analysis was performed, and compound identification was completed using the METLIN metabolite database. Results A total of 235 specimens were tested by LC/Q-TOF, including 195 positive specimens [including adenovirus, coronavirus, influenza A H1N1 and H3N2, influenza B, human metapneumovirus, parainfluenza viruses 1, 2, 3, and 4, respiratory syncytial virus (RSV), and rhinovirus] as well as 40 negative clinical specimens. LC/Q-TOF primary component analysis (PCA) allowed preliminary identification of key metabolites that distinguished all virus-positive specimens compared with the negative group, and differentiated respiratory viruses from one another including between influenza A 2009 H1N1 and H3N2 subtypes (Figure 1). Conclusion Preliminary data from our LC/Q-TOF analysis show that respiratory viruses exhibit different host cell metabolomic profiles that allow viral differentiation to the species level, and for influenza A virus, the subtype level. This metabolomic approach has substantial potential for diagnostic applications in infectious diseases directly from patient samples, and may be eventually adapted for point-of-care testing. Disclosures All authors: No reported disclosures. [ABSTRACT FROM AUTHOR] |
