Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae

Andrew Jarnuczak, CE Eyers, Jean-Marc Schwartz, Christopher Grant, Simon Hubbard

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Molecular chaperones play an important role in protein homeostasis and the cellular response
    to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding
    through transient associations with their substrates. This chaperone interaction network can
    be disturbed by various perturbations, such as environmental stress or a gene deletion. Here,
    we consider deletions of two major chaperone proteins,
    SSA1
    and
    SSB1,
    from the chaperone
    network in
    Sacchromyces cerevisiae.
    We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs.
    Original languageEnglish
    Pages (from-to)3126-3139
    Number of pages13
    JournalProteomics
    Volume15
    Issue number18
    DOIs
    Publication statusPublished - 10 Apr 2015

    Keywords

    • Betweenness centrality
    • Chaperones
    • Protein interaction networks
    • Quantitative proteomics
    • SILAC
    • Systems biology

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