Current Approaches on Viral Infection: Proteomics and Functional Validations

Zheng, Jie; Tan, Boon Huan; Sugrue, Richard; Tang, Kai

Although the introduction of software is a significant advance to a variety of proteomic studies by performing statistical analysis and filtering out low confident protein candidates, the development of bioinformatics is still hampered by computational limitations. For tandem mass spectra, only a small number of most abundant precursors are generally selected for subsequent MS/MS analysis due to limited sampling rate of MS. It therefore results in missed identification of some lower abundant proteins could escape identification. The method may also identify some non-specific proteins or contaminants, for instance, HSC70 was identified associated with purified RSV by proteomic approach, yet validation by fluorescence microscopy showed that the proteomic observation of HSC70 in RSV was false-positive (Radhakrishnan et al., 2010) . Also, for large-scale quantitative proteomic analysis, such as 2D gel and 2D LC-MS/MS, it is hard to validate the functional activity of each protein due to the large quantity of protein IDs and shortages of antibodies. More importantly, mass spectrometric data may also contain proteins from indirect secondary cellular responses that are not directly related to virus infections. For instance, some indirect cellular processes during the late stages of HIV or RSV infection, such as syncytium formation that causes severe secondary host countermeasures could also be detected in proteomic analysis.