Revealing static and dynamic modular architecture of the eukaryotic protein interaction network

Kakajan Komurov¹ & Michael White¹

Article highlights

Synopsis

In order to test the specific organizational layout of transcriptionally regulated (dynamic) versus nonregulated (static) proteins in the protein interaction network, we integrated high-confidence protein interaction data from yeast with high-throughput microarray gene expression data. The extent of transcriptional regulation of a gene (i.e. expression variance, EV) was simply scored by taking the statistical variance of its expression profile across 272 microarray experiments from various conditions.

By constructing a global interaction preference matrix of proteins with various EVs, we find that the network is enriched for clusters of static and dynamic proteins (static and dynamic neighborhoods, respectively) (Figure 1B). These neighborhoods are specialized functional modules dedicated to specific cellular processes like mRNA synthesis, protein degradation or vesicle trafficking. Interestingly, some cellular functions seem to be mainly performed by static modules, whereas others are mainly carried out by dynamically expressed modules, pointing to functional distinction between the two types of modules.

Figure 1

Interaction pattern of proteins according to their EV. (A) Boxplot of proteins in each of 50 bins with the given EV versus their neighborhood EV. (B) Interaction preference matrix of the yeast network. Each square represents the number of interactions between corresponding bins. Left panel: Interaction preference matrix of the actual network, right panel: Interaction preference matrix of randomized network achieved by randomly shuffling the positions of proteins in the network (right panel). (C) Interaction preference matrix of proteins with different node degrees corresponding to the four quartiles of the node degree distribution. Proteins were binned according to their EVs and node degrees. Each square represents the normalized number of interactions between proteins with given node degree (k) and EV. Normalization of a square (i, j) in the matrix was carried out by calculating the number of interactions between proteins in the bins i and j, and dividing that number with the total number of interactions that proteins in bins i and j have. Color key shows the normalized number of interactions between bins.

Full figure and legend (118K)Figures & Tables index

Our study shows that expression criteria for a protein to be located within a module are that either it has to be highly coexpressed with its neighbors in the network or it must be located within a static neighborhood. An earlier study named hubs (highly connected proteins) that are highly coexpressed with their neighbors and that are therefore in modules as 'party' hubs, and those that are not coexpressed with their neighbors and located outside modules as 'date' hubs (Han et al, 2004). Here, we named hubs located in static neighborhoods as 'family' hubs (they interact with their neighbors constitutively), as these hubs do not belong to party or date hubs because they are located within modules but are not highly coexpressed with their neighbors owing to their static expression pattern. Therefore, family and party hubs constitute the static and dynamic modules in the cell, respectively, whereas date hubs organize them into a network.

Based on the classification of hubs by Han et al (2004), date hubs have been found to evolve at a faster rate than party hubs, thereby suggesting that modularity imposes a constraint on the evolvability of proteins and that the protein interaction network mainly evolves by 're-wiring' the connections between modules in the network (Fraser, 2005). We also find that party hubs evolve much slower than other hubs (Figure 5A). However, family hubs are the ones that evolve the fastest rather than date hubs (Figure 5A), suggesting that modularity per se does not impose a constraint on the evolvability of proteins, as family hubs are also modular. Consistent with their evolutionary plasticity, deletions of family hubs in yeast are tolerated significantly more than deletions of party hubs, indicating specific robustness of the cell to dysfunctions in static modules. Moreover, family hubs are significantly 'noisier' in their expression (Figure 5C), meaning that their expression levels vary from cell-to-cell considerably more when compared to party or date hubs. These observations argue that family hubs are the most variable components of the cell both genetically during evolution and expressionally between cells in a population. Family hubs, and hence static modules, could therefore serve as buffers of genetic variations as well as of expression noise within the cell that contribute to the robustness of the cell.

Figure 5

Evolutionary rate and expression noise of the static and dynamic modules. Evolutionary rates of yeast proteins derived by Hirsh et al (2005) were used. (A) Boxplot of evolutionary rates of family, party and date hubs. Family hubs are static hubs with neighborhood EVs of <0.3, party hubs are hubs with avPCC>0.45 and date hubs are those with neighborhood EV>0.3 and avPCC<0.45. (B) Fractions of proteins in the static and dynamic networks whose gene deletion is lethal to yeast. (C) Boxplot of protein expression noise in the different hub classes.

Full figure and legend (28K)Figures & Tables index

MORE ARTICLES LIKE THIS

These links to content published by NPG are automatically generated.