The Impact of Mass Spectrometry-Based Proteomics on Fundamental Discoveries in Virology

Abstract

In recent years, mass spectrometry has emerged as a core component of fundamental discoveries in virology. As a consequence of their coevolution, viruses and host cells have established complex, dynamic interactions that function either in promoting virus replication and dissemination or in host defense against invading pathogens. Thus, viral infection triggers an impressive range of proteome changes. Alterations in protein abundances, interactions, posttranslational modifications, subcellular localizations, and secretion are temporally regulated during the progression of an infection. Consequently, understanding viral infection at the molecular level requires versatile approaches that afford both breadth and depth of analysis. Mass spectrometry is uniquely positioned to bridge this experimental dichotomy. Its application to both unbiased systems analyses and targeted, hypothesis-driven studies has accelerated discoveries in viral pathogenesis and host defense. Here, we review the contributions of mass spectrometry-based proteomic approaches to understanding viral morphogenesis, replication, and assembly and to characterizing host responses to infection.

Keywords: AP-MS; posttranslational modifications; secretome; viral proteomics; virus-host interactions.

Figure 1

Contribution of mass spectrometry (MS)-based proteomics to understanding viral infection. The productive infection cycle of the prototypic human virus herpes simplex virus 1 (HSV-1) is depicted within a susceptible host cell. Key aspects of the virus life cycle that can be studied using MS-based proteomics are designated by numbers. Briefly, the composition and structure of mature virions can be characterized by tandem MS and native MS, respectively (①). Affinity purification (AP)-MS can detail interactions between viral and host constituents at the cell surface mediating entry (①); in the nucleus regulating transcription, genome replication, and capsid assembly (②); and in the cytosol aiding egress and assembly (③). Quantitative MS can measure virus-induced, organelle-specific changes in protein expression and posttranslational modifications (③) and the secretion of antiviral mediators that initiate the innate and adaptive immune response (④). Viral proteins are shaded red and yellow; host proteins are shaded blue and purple.

Figure 2

(a) Multifaceted mass spectrometry (MS)-based analyses of viral structures, interactions, and pathogenesis. Orthogonal workflows illustrate biochemical and MS-based approaches that can be used to study recombinant viral proteins expressed in bacteria or mammalian cells, extracellular virions, or virus-infected mammalian cells. Masses of intact viral assemblies can be determined by electrospray ionization (ESI)–native MS (also called top-down MS), with an orthogonal ion mobility separation to assess molecular compactness (top). Peptide-based MS (also called bottom-up MS) analysis requires denatured protein extracts obtained from extracellular virions, infected cells, organelles, or virus-host complexes. Protein extracts can be directly digested to MS-amenable peptides, or they can first be separated by SDS-PAGE and then in-gel digested into peptides. Following nano–liquid chromatography and ESI (nLC-ESI), peptide sequencing is performed by successive rounds of intact and fragment peptide mass measurements (tandem MS) in the mass spectrometer. Peptide quantification strategies use MS or tandem MS spectra as the basis for protein-level quantification. Global quantitative techniques can use either isotope labeling—within the cell, for simultaneous comparison of usually up to three samples (SILAC), or at the peptide level, for comparison of currently up to ten samples (isobaric tags)—or label-free quantification (peak area or spectral counts). Selected reaction monitoring (SRM) is used for targeted analyses in isotopic or label-free workflows. (b,c) Supplemental Tutorials 1 and 2 provide hands-on experience in the computational analysis of AP-MS data sets. (b) In Supplemental Tutorial 1, a data set of high-confidence protein identifications from HDAC1-EGFP immunoisolations is provided as an example for construction and analysis of functional protein networks using the STRING database of known and predicted protein-protein interactions. (c) In Supplemental Tutorial 2, protein identifications from HDAC1-EGFP immunoisolations that have not been filtered for specificity are provided. The tutorial demonstrates how to use spectral counting to classify specific versus nonspecific associations. Abbreviations: H, heavy; hpi, hours postinfection; I, infected; L, light; M, mock; M⁹⁺, molecular ion with a charge state of 9; SC diff, spectral count difference.