Quantitative analysis of protein interaction network dynamics in yeast

Abstract

Many cellular functions are mediated by protein–protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment‐dependent protein complex dynamics, we used a DNA‐barcode‐based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that “concerted” protein‐centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass‐action‐based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics.

An atlas of protein-protein interactions across mammalian tissues

“…This finding reinforces conclusions from targeted studies, which have revealed marked dissimilarities in PPIs across cell lines (Floyd et al, 2016;Jäger et al, 2011), between cellular compartments (Markmiller et al, 2018), in response to cellular stimulation (Kristensen et al, 2012;Scott et al, 2015), or in disease-relevant contexts (Pankow et al, 2015;Shirasaki et al, 2012). In yeast, widespread interaction rewiring has been observed in response to environmental perturbagens (Celaj et al, 2017). Our systematic screen builds on these findings, revealing interactome rewiring at a much larger scale and across healthy mammalian tissues.…”

A large accessory protein interactome is rewired across environments

“…Previous work has found that HXT5 expression increases during salt stress (Verwaal et al, 2002), suggesting the change in Hxt5 PPIs may be a direct consequence of its change in abundance. Taken together and consistent with mechanisms of core network regulation described above, these results suggest that the changes in the glucose transport subnetwork are mainly driven by changes in protein expression (Celaj et al, 2017).…”

The role of structural pleiotropy and regulatory evolution in the retention of heteromers of paralogs

“…To test for the effect of expression levels, we used integrated protein abundance for the yeast proteome (Wang et al, 2012) and measured mRNA abundance in cells growing in conditions that reflect the ones used in PCA experiments (Table S3 and Table S4). We found that in general, as previously observed (Celaj et al, 2017;Freschi et al, 2013), PCA signal correlates with mRNA and protein abundances (Spearman r = 0.32, p-value < 2.2e-16 and r = 0.45, p-value < 2.2e-16 respectively). This effect is also found when focusing only on HMs that were previously reported (Spearman r = 0.27, p-value = 2.248e-07 and r = 0.29, p-value < 2.2e-16 respectively).…”

“…To test for the effect of expression levels on PPI detection in the PCA assays, we measured mRNA abundance in cells growing in conditions that reflect the ones used in PCA experiments and used integrated protein abundance for the yeast proteome (Wang et al, 2012) (Tables S3 and S4). As previously observed (Celaj et al, 2017;Freschi et al, 2013), we found a correlation between PCA signal and expression level, both at the level of mRNA and protein abundance (Spearman r = 0.32, p-value < 2.2e-16 and r = 0.45, p-value < 2.2e-16 respectively). When focusing only on HMs previously reported, we also detected both correlations (Spearman r = 0.27, p-value = 2.248e-07 and r = 0.29, p-value < 2.2e-16 respectively).…”

“…To test for 163 the effect of expression levels on PPI detection in the PCA assays, we measured mRNA 164 abundance in cells grown in conditions that reflect the ones used in PCA experiments and 165 also used integrated protein abundance for the yeast proteome (Wang et al, 2012) 166 (Tables S3 and S4). As previously observed (Celaj et al, 2017;Freschi et al, 2013), we 167 found a correlation between PCA signal and expression level, both at the level of mRNA 168…”