Viral Proteomics & Metabolomics Mass Spectrometry

The surface of the virus envelope is covered with proteins, specifically glycoproteins, which are involved in the process of binding to the host cells for viral entry. Glycan diversity on these proteins are used by the virus to evade immune system response. Surface glycans have conformational flexibility that provides conformational dynamics to the virus, which can help shield drug binding sites. In order to get more detail on the type of glycosylation and the sites where it occurs (site occupancy) on viral surface glycoproteins, a glycoproteomics strategy can be used. Glycoproteomics can provide information on the sites of glycosylation and glycan compositions. Glycopeptide workflows involve sample preparation and enrichment, mass spectrometry analysis, data analysis and interpretation. Below is a short list of recommended products, but we invite you to explore more product information and resources on glycopeptide analysis on our protein glycosylation workflow page.

Glycomics can expand on glycoproteomics to provide further details on the glycans. Glycomics can provide structural information on the glycans like branching and linkage and can help resolve structural isomers. Glycomics workflows involve deglycoslyation, isolation, mass spectrometry analysis and glycan identification using powerful software.

Native MS provides an unaveraged picture of the solution conditions, meaning that different proteoforms (such as differential glycosylations) can be detected simultaneously. Native MS is also a useful tool for examining virus capsids, quantifying cargo encapsulation and monitoring capsid assembly. Combining native MS with top-down MS allows the structural characterization of the capsid’s proteins.

A major focus of structural virology is to obtain an understanding of the construction and structural basis for stability of the protein capsids that encapsulate the viral genomic information. HDX-MS can be used to measure local conformational dynamics and to gain insight into the mechanisms of assembly and capsid maturation for viruses.

The focus of virus-host interaction studies is to discover protein interaction events critical for different stages of a viral infection. AP-MS workflows can be used to examine specific protein-protein interactions within protein complexes, or to look at protein complexes more globally at the interactome level. Incorporating quantitative MS (LFQ, TMT) with affinity purification enables researchers to examine protein-protein interactions under different conditions (across different stages of viral infection), thereby providing a much more dynamic view. AP-MS can also be used to examine posttranslational modifications (PTMs) and the role they play in facilitating protein-protein interactions.

Insights into virus-host cell protein complexes, like subunit stoichiometry, subunit identification, biomolecule binding, protein complex topology and protein dynamics can be obtained with native MS. The capabilities of native MS can be further expanded when combined with other techniques like limited proteolysis to infer protein interactions.

Virus-host cell protein interactions are intermolecular interactions occurring between virus proteins and host cell receptors. Unfortunately, these interactions tend to be transient, occurring for a brief period. Crosslinking MS (XL-MS) can monitor transient interactions to help distinguish between direct and indirect protein-protein interactions. XL-MS can help identify host cell surface proteins involved in interaction. It can be used to examine protein interaction topologies between a virus and host cell proteins, map interaction sites between the virus and host, as well as the precise residues involved in binding. XL-MS can help elucidate protein structures or complexes involved in host-cell interaction.

Virus-host cell interactions are not static but a dynamic process. Quantitative techniques like TMT can be used to observe this dynamic process. As part of AP-MS or XL-MS, TMT workflows can be used to examine the protein-protein interaction occurring during virus infection, measuring changes in levels of interactions or binding affinities. TMT quantitation workflows provide multiplexing capabilities for relative quantitative proteomics analysis, allowing concurrent MS analysis of multiple samples derived from cells, tissues or biological fluids.

Peptide antigens bind to molecules encoded by the major histocompatibility complex (MHC) and are presented on the cell surface form the targets of T lymphocytes. This critical arm of the adaptive immune system facilitates the eradication of virus-infected cells as well as the production of antibodies. Identifying these peptide antigens is critical to the development of new vaccines. Bottom-up proteomics workflows are the mainstay for proteomics and are used to identify as many protein components in a biological sample as possible.

Quantitative proteomics can help identify distinct immune response profiles induced by viral infection. This is done by characterizing immune response proteins and identifying immune system pathways involved in response to viral infection. Quantitative proteomics workflows allow system-wide identification and quantification of proteins from discovery to targeted applications, detecting and quantifying thousands of proteins in a single experiment across multiple conditions with dynamics and insights, which can lead to deeper levels of understanding about how biological processes behave.

These workflows provide multiplexing capabilities for relative quantitative proteomics analysis, allowing concurrent MS analysis of multiple samples derived from cells, tissues or biological fluids.

These workflows identify and quantify relative changes in complex protein samples with a technique that can handle both labeled and unlabeled samples while detecting changes for both low-abundance proteins and posttranslational modifications such as in phosphorylation or glycosylation.

These workflows allow relative quantitation of protein samples from any origin with unlimited sample comparisons and peptide identification with any fragmentation method.

These workflows can detect all target product ions in parallel using one, concerted high-resolution, accurate-mass (HRAM) analysis; it’s ideally suited for analyzing and quantifying large numbers of samples.

These workflows utilize a triple quadrupole mass spectrometer for more routine, targeted quantitation and analysis of large numbers of samples.

The SureQuant IS targeted quantitation workflow delivers a complete assay from sample preparation to monitoring and quantitation of hundreds of target peptides in complex matrices with easy setup, high selectivity, quantitative accuracy, precision and specificity.

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PTMs such as phosphorylation and polyubiquitination regulate innate inflammatory responses due to infection. Studies have also shown that PTMs such as methylation, acetylation, SUMOylation, and succinylation are involved in the regulation of innate immunity and inflammation. MS can be used to characterize these PTMs. Phosphoproteomics (Posttranslational modification-PTM) workflows enable large-scale study of protein phosphorylation and phosphopeptides, furthering scientific understanding of the influence this important PTM has on biological processes and human health.

Mass spectrometry characterization and quantitation of metabolites can yield important insights into how the immune system functions.

These workflows are designed for small-molecule identification and can solve the most complex metabolomic challenges.

These workflows enable researchers to detect metabolites of interest while simultaneously discovering unknowns.

Quantitative proteomics techniques can be used to distinguish and predict mild to severe types of disease progression, assisting with development of appropriate medical treatments and resources at earlier stages, which can have a big impact on mortality-survival rate.

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Mass spectrometry characterization and quantitation of metabolites can yield important insights into how the immune system functions.

These workflows are designed for small-molecule identification and can solve the most complex metabolomic challenges.

These workflows enable researchers to detect metabolites of interest while simultaneously discovering unknowns.