A Human Interactome in Three Quantitative Dimensions Organized by Stoichiometries and Abundances

Abstract

The organization of a cell emerges from the interactions in protein networks. The interactome is critically dependent on the strengths of interactions and the cellular abundances of the connected proteins, both of which span orders of magnitude. However, these aspects have not yet been analyzed globally. Here, we have generated a library of HeLa cell lines expressing 1,125 GFP-tagged proteins under near-endogenous control, which we used as input for a next-generation interaction survey. Using quantitative proteomics, we detect specific interactions, estimate interaction stoichiometries, and measure cellular abundances of interacting proteins. These three quantitative dimensions reveal that the protein network is dominated by weak, substoichiometric interactions that play a pivotal role in defining network topology. The minority of stable complexes can be identified by their unique stoichiometry signature. This study provides a rich interaction dataset connecting thousands of proteins and introduces a framework for quantitative network analysis.

Quantitative analysis of human centrosome architecture by targeted proteomics and fluorescence imaging

“…These values are in good agreement with estimates reported in previous large‐scale proteomics studies (Nagaraj et al , 2011; Kulak et al , 2014; Hein et al , 2015), and this adds confidence to our use of γ‐tubulin data for calibration purposes. Also, we emphasize that although this calibration is critical for calculations of exact absolute copy numbers, any future correction of γ‐tubulin abundance would not affect relative numbers or any of the major conclusions.…”

“…Comprehensive studies on the proteomes of cells, tissues, or organisms have been reported (e.g. Addona et al , 2009; Nilsson et al , 2010; Beck et al , 2011; Nagaraj et al , 2011; for review, see Bensimon et al , 2012; Kulak et al , 2014; Wilhelm et al , 2014; Hein et al , 2015; Richards et al , 2015), but accurate quantitative information on proteins expressed at low levels remains scarce. As a consequence, published estimates for the abundance of specific proteins sometimes vary over several orders of magnitude.…”

Slide-and-exchange mechanism for rapid and selective transport through the nuclear pore complex

“…S5), and by the fact that increased surface hydrophobicity promotes fast transport even in non-TF proteins (68); (iii) the intrinsic flexibility of the FG spacer regions that further disfavors static binding due to the entropic penalty of restraining flexible molecules; and (iv) the entropic benefit of interacting dynamically rather than statically. It remains to be seen whether such a specific-yet-dynamic mechanism of interaction is prevalent in other classes of disordered proteins and globular proteins, in particular in transient-yet-specific interactions, which are underrepresented in databases of protein interactions due to their lower signal in experimental assays (69).…”

Mapping, modeling, and characterization of protein–protein interactions on a proteomic scale

“…The investigation of quantitative stoichiometry and protein abundance in the QUBIC dataset suggested that stable complexes are relatively rare, accounting for only 10% of human interactome. Weak, substoichiometric interactions were more critical for maintaining the connectivity of the overall PPI network [19].…”

“…An alternative study, QUBIC, utilized GFP-tagged baits that were incorporated into HeLa cell chromosomes and thus were expressed at near-endogenous expression levels and patterns to identify interactions. The QUBIC dataset includes $28 500 PPAs among $5500 proteins, resulting from the expression of $1100 bait proteins [19]. The investigation of quantitative stoichiometry and protein abundance in the QUBIC dataset suggested that stable complexes are relatively rare, accounting for only 10% of human interactome.…”