The yeast interactome (unit: g303204)

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1 The yeast interactome (unit: g303204) Peter Uetz 1 & Andrei Grigoriev 2 1 Institute of Genetics (ITG), Forschungszentrum Karlsruhe, Karlsruhe, Germany 2 GPC Biotech, Martinsried, Germany Addresses 1 Institute of Genetics (ITG), Forschungszentrum Karlsruhe, Box 3640, Karlsruhe, Germany peter.uetz@itg.fzk.de Phone: (office) Fax: GPC Biotech, Fraunhoferstrasse 20, Martinsried, Germany Tel +49 (0) Fax +49 (0) andrei.grigoriev@gpc-biotech.com 19 manuscript pages 9 illustrations 1 table ~6200 words (including references) ~4600 words (excluding references) Key Words: proteomics, network, two-hybrid system, mass spectrometry, interaction map, interactome, yeast, protein complex, synthetic lethality, genetic interaction This is a preprint from the Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics, to be published by John Wiley and Sons, and edited by Lynn B. Jorde, Peter Little, Michael Dunn, and Shankar Subramanian.

2 2 Table of contents ABSTRACT... 3 INTRODUCTION... 4 TYPES OF INTERACTION DATA: SOURCES AND CLASSIFICATION... 4 METHODS FOR INTERACTION ANALYSIS AND THEIR DATA... 4 TWO-HYBRID INTERACTIONS... 4 PROTEIN COMPLEX PURIFICATION AND ANALYSIS BY MASS SPECTROMETRY... 5 GENETIC INTERACTIONS AND SYNTHETIC LETHALITY... 6 OTHER PHYSICAL METHODS DATA QUALITY... 6 COMPARISON OF VARIOUS INTERACTION DATASETS... 7 TRANSIENT VS. STABLE INTERACTIONS... 7 INTEGRATING PROTEIN-PROTEIN INTERACTIONS WITH OTHER DATASETS... 8 THE YEAST INTERACTION NETWORK... 8 COMPUTATIONAL IDENTIFICATION OF PROTEIN COMPLEXES IN NETWORKS... 9 MODULARITY OF THE PROTEIN INTERACTION NETWORK IN YEAST... 9 WHICH PROTEINS DO INTERACT (OR NOT?)... 9 EVOLUTION AND CONSERVATION OF PROTEIN COMPLEXES AND INTERACTIONS HOW MANY PROTEIN INTERACTIONS ARE THERE IN YEAST? BIOLOGICAL RELEVANCE OF PROTEIN INTERACTIONS ACKNOWLEDGEMENTS RELATED ARTICLES REFERENCES FURTHER READING TABLES AND CAPTIONS FIGURE CAPTIONS

3 3 Abstract The yeast proteome and its interactome (that is, the sum of all protein interactions) are the best studied of all organisms. Currently there are about 3000 verified protein interactions and several thousand non-verified interactions known in yeast. Independent studies estimated that there may be more than 30,000 interactions in yeast although most estimates rather suggest 15,000 25,000. It remains unknown how many of these interactions are really essential. The average yeast protein appears to have about 5 interactions but this number may represent an overestimate because many proteins of yet unknown function exhibit fewer interactions. Nevertheless, most proteins can be connected in a huge network of interactions. The protein interaction network of yeast is highly dynamic although there are 1,500 or more proteins involved in several hundred stable complexes. The dynamics and regulation of protein interaction networks, e.g. by protein modifications, are only now being explored. There are no clear physical properties of a yeast protein that predics its interaction properties but several protein families (such as proteins involved in RNA splicing) seem to be much more highly connected than others (such as metabolic enzymes). 3

4 4 Introduction The genome of the budding yeast Saccharomyces cerevisiae was the first eukaryotic genome to be sequenced. Therefore yeast was also the first eukaryote whose complete set of proteins became known in 1996 (Goffeau et al., 1997). This lead to the first systematic attempts to study protein interactions (the interactome ) and function at the end of the 20 th century. As a consequence, the yeast proteome and interactome are probably the best known of all eukaryotes, including human. As a guide to understanding a cell, the knowledge of its its interactome is absolutely necessary as protein interactions are critical to all processes in biology. Here we summarize current knowledge of the yeast interactome and some of its implications for other model systems. Types of interaction data: sources and classification Historically, that is, until the yeast genome sequence became available, proteins and their interactions were studied one by one as they were identified in genetic screens or by other methods. However, the availability of the genome sequence allowed the study of all yeast proteins in a systematic way and as a consequence, the majority of our current knowledge of the yeast interactome stems mostly from a few large-scale studies. These studies included the yeast two-hybrid assay (Figure 1) and the purification of protein complexes and their analysis by mass spectrometry (see Figure 2, Section 1: core methodologies, and g303206). More recently, genetic screens also yielded a large number of interactions, but it remains unclear how many of those represent physical interactions (see below for details). Nevertheless, detailed small-scale studies remain extremely important as they still provide the only means for careful functional analysis and the placement of interaction data in a biological context. Methods for interaction analysis and their data Two-hybrid interactions. The two-hybrid system uses two hybrid proteins which reconstitute a transcription factor when they interact. This transcription factor can switch on a reporter gene (Figure 1). Two-hybrid interactions are usually binary although occasionally a third protein may mediate interactions between the two hybrids. For yeast there are about 7000 two-hybrid protein interactions available in databases derived from small and large-scale screens (Table 1). Figure 1 The first large-scale study (Uetz et al., 2000) included two independent screens: one tested 192 baits for interactions with all 6000 yeast proteins and found 281 reproducible interactions for 87 proteins. In the second screen all ~6000 activation domain constructs were pooled and tested against each DNA-binding domain fusion (Figure 1), resulting in 692 interactions involving 817 proteins. 4

5 5 Ito et al. (2001) presented the largest two-hybrid interaction screen to date, which detected 4549 interactions among 3,278 proteins. Of these, 841 were found 4 or more times and they represented a core subset of more reliable interactions. Protein complex purification and analysis by mass spectrometry (see also g and g303311) Often, proteins interact within stable protein complexes. These complexes can be purified and their components identified. In contrast to two-hybrid data this provides no or little information on which subunit interacts with which other subunit. Two-hybrid data on the other hand do not tell which interactions lead to a stable complex (Figure 2). Figure 2 Two large-scale studies identified protein complexes in yeast. Gavin et al. (2002) analyzed 1,739 genes, including 1,143 human orthologues, and identified 232 distinct multiprotein complexes using tandem affinity purification (TAP) (Figure 3). This set of proteins was not representative as it contained many highly conserved proteins and so we cannot conclusively extrapolate these numbers to the whole yeast proteome. However, these results suggest that there may be no more than 400 or 500 complexes in yeast, although many of them are not be precisely defined as some of their subunits may vary. A more conclusive number may become available through the analysis Emili et al. (pers. comm.), who have continued the analysis of Ho et al. and purified a total of 4455 TAPtagged baits of which more than 3400 resulted in successful purifications. However, an analysis of this dataset was not available at the time of this writing. Figure 3 Ho et al. (2002) chose an initial set of 725 bait proteins and identified the proteins associated with these baits using a Flag epitope tag in the high-throughput mass spectrometric protein complex identification (HMS-PCI). After removal of potential false positives this filtered data set contained 1,578 different interacting proteins. Two models are used to map complexes to pairwise interactions. The spoke model assumes that the bait protein interacts with all other proteins in the complex. The matrix model assumes that every protein in a complex interacts with every other protein, i.e. there are N(N-1)/2 interactions in a complex containing N proteins. These models represent theoretical minimum and maximum numbers of interactions and are both correct only if a complex is a heterodimer. The real topology of the interactions in a complex is most likely somewhere in between these extremes. When compared to a literature benchmark, one of the matrix model has turned out to be three times more incorrect than the spoke (Bader and Hogue, 2002), although other studies have not found any significant difference (Cornell et al., 2004). 5

6 6 A graphical representation of complexes yields a fairly intricate display of interconnections between individual bait-target groups (Fig. 4). Figure 4 Genetic interactions and synthetic lethality. Single mutations often do not affect the viability of a cell significantly. However, if two or more such mutations are combined this may have a much more severe affect than expected from the individual mutants or even may cause lethality. Genes that exhibit such a synthetic phenotype are said to interact genetically. In many cases the products of these genes are components of a complex, a pathway, or are otherwise functionally related (e.g., compensate each other s function). Therefore, such combined mutations often lead to an additive or even stronger effect. However, the proteins need not to interact physically in order to show such a synthetic phenotype. Tong et al. (2004) presented the largest analysis of synthetic lethal interactions so far. Their 132 SGA (i.e. synthetic genetic analysis ) screens focused on query genes involved in actin-based cell polarity, cell wall biosynthesis, microtubule-based chromosome segregation, and DNA synthesis and repair, detecting 4000 interactions amongst 1000 genes. It suggests that the yeast synthetic genetic network may contain up to 100,000 interactions although 24,000 appear more realistic based on the biased choice of genes studied. Approximately 20% of the query genes (not included in the 132 query genes mentioned above) showed no genetic interactions. The frequency of false negatives was estimated to be in the range of 20-40%. Other physical methods. Protein interactions have been identified using a number of differerent methods including co-immunoprecipitation, protein arrays (g302203), FRET (g304215) or structural biology (section 7). However, none of these methods has been used on a large scale to identify protein interactions although such projects are under way, especially in structural genomics (g307213) and using protein arrays (Zhu et al., 2001, see also g302203). Table 1 Data quality Many interactions from large-scale studies are not as rigorously quality-controlled as from small-scale experiments. This is true for both two-hybrid and mass spec analyses. Various studies estimated that two-hybrid data may have 50-90% false positives (Mrowka 2001, Sprinzak et al. 2003) while mass spec datasets may have >30% false positives (Gavin et al., 2002). The reason for two-hybrid false positives is not well understood but it must derive from unspecific activation of the reporter genes used. Mass spectrometry may result in false positives if the complexes are not highly purified. On the other hand, stringent purification may result in false negatives as subunits are lost. However, smaller scale screens also detect interactions, which are not in agreement with 6

7 7 structural data (Edwards et al. 2002), indicating a need in the integration of diverse types of data to confirm interactions by other means. Other approaches to assessment of interaction datasets have included analysis of orthologs (Deane et al., 2002, Pagel et al., 2004), gene expression (Kemmeren et al., 2002) and network topology (Saito et al., 2002; Goldberg and Roth, 2003). A comprehensive dataset of putative yeast interactions was collected by von Mering et al. (2003) from a large number of sources including two-hybrid and complex pull-down results, smaller-scale studies and in silico predictions (including conserved gene neighborhood, gene fusion events and co-occurrence of genes as well as correlated mrna expression). The gene pairs collected have been assigned confidence based on the number of sources of supporting evidence, with the high confidence set supported by at least two sources including about 2500 interactions between some 1000 proteins. Interestingly, homologous protein interactions found in 2 species appear to be more reliable than interactions found by 2 independent methods (Lehner & Fraser, 2004). Comparison of various interaction datasets Various high-throughput projects produced surprisingly different results. Biologists need to be aware of these differences as they indicate important limitations of different approaches (Cornell et al. 2004). Mass spectrometry data. In mass-spectrometry approaches, of 115 common baits used by TAP (Gavin) and HMS-PCI (Ho) only 47 retrieved complexes containing common proteins. In 33 other complexes with the same bait there was no other common member. As a result, there is considerable disparity between the size and content of complexes generated by TAP and HMS PCI. The TAP approach was also more successful at identifying reverse interactions than HMS PCI. In 39% of instances where B is used as a bait, it identified A, compared to 19% for HMS PCI. Two-hybrid data. There are 220 bait proteins in common between the two large-scale screens. For these baits, the Ito dataset contains 871 interactions, while that of Uetz contains 430; 164 interactions were common to both datasets. The Ito dataset contains many highly-connected proteins (HCPs), several of which interact with more than 100 preys. Of the 2161 HCP interactions, only 67 (3.1%) have been verified by multiple datasets. Most studies therefore agree that such interactions consist mostly of false positives. Uetz et al. (2000) filtered out such HCPs as false positives. In addition, in the vast majority of cases, unverified interactions were identified with the HCP as the bait protein. In only 221 of the 2161 interactions is the HCP the identified protein. Transient vs. stable interactions Aloy & Russell (2002) noticed that mass spectrometry studies appear to identify preferentially stable interactions while two-hybrid studies tend to prefer transient 7

8 8 interactions. Transient interactions also occur more frequently in HMS PCI data than in TAP data which may be due to a more rigorous washing regime than in the HMS-PCI procedure. Integrating protein-protein interactions with other datasets The first attempt of integrating the yeast proteome data was the study of a relationship between gene expression and protein interactions (Grigoriev, 2001). Protein pairs encoded by co-expressed genes were found to interact with each other more frequently than random protein pairs. This approach allows one to evaluate interaction datasets using large-scale gene expression profiling as benchmark. For example, the MIPS collection, with interactions collected from literature and often supported by additional evidence, has shown by far the best agreement with gene expression profiles than largescale interaction screens. Similarly, the "core" subset from Ito et al. (2001) has shown a better agreement than the rest of their interactions. These findings were supported by a number of follow-up papers (Ge et al., 2001; Jansen et al., 2002; Kemmeren et al., 2002; Deane et al., 2002). Cornell et al. (2004) compared protein pairs co-occuring in multiple TAP/HMS-PCI complexes with the pairs detected only once and found the former to display a much stronger correlation with gene expression data. Note that correlation of mrna expression is not necessary for protein interaction, i.e. proteins whose expression is not correlated strongly may still be bona fide interactors, as long as they co-exist in sufficient proximity within a cell. Integration of various datasets remains a tremendous challenge for bioinformatics, especially when interactions have to be displayed graphically together with expression data, homology, structures, or localization in a cell (Uetz et al. 2002). The yeast interaction network See also g global analysis of protein interaction networks When the results of large and small-scale two-hybrid screens were put together, the resulting network surprisingly connected almost all yeast proteins (Fig. 5); only a few proteins resulted in smaller networks that were not linked to the large component (Schwikowski et al., 2000). Such interaction networks have led to a flurry of bioinformatic studies, exploring the topology and biological significance of its properties. Here we summarize only a few interesting results and refer the reader to the literature for more detailed analysis (Barabasi & Oltvai, 2004). Figure 5 8

9 9 Computational identification of protein complexes in networks Several studies have demonstrated that complexes can be found in networks by searching for local clusters of interacting proteins (Bader & Hogue 2003, Krause et al. 2003, Spirin & Mirny, 2003, Bu et al., 2003). Given that many proteins are shared by several complexes these findings blur the distinction between defined complexes and whole proteome interaction networks and emphasize the dynamics of protein interactions within a cell. Modularity of the protein interaction network in yeast Early topological analyses of metabolic networks indicated that they can be considered as modular. The same seems to be true for protein interaction networks (Figure 6). Han et al. (2004) analyzed highly connected proteins (hubs) for correlated gene expression and separated them into party hubs (that interact mostly within a protein complex) and date hubs (interacting with other hubs, mainly transiently but not in stable complexes). Averaging Pearson correlation coefficients (PCCs) of mrna expression between hubs and their interaction partners produced a bimodal distribution for expression data related to various biological functions including stress response and the cell cycle (Fig. 6b). Other expression groups did not show such a bimodal distribution clearly. After excluding ribosomal hub proteins these two peaks of the distribution contained 91 date (lower PCCs) and 108 party hubs (higher PCCs) in high-confidence interaction dataset of von Mering et al. (2003). Figure 6 The distinction between date and party hubs obtained from gene expression is recapitulated by protein localization data. Interestingly, removal of party hubs from the interaction network does not affect connectivity (and thus resembles failures), whereas attacks directed against date hubs account for a vast majority of the effect observed when attacking all hubs. In single-gene knockout experiments similar proportions of party and date hubs score as essential. Date and party hubs are both threefold more likely to be essential than nonhubs, but their single knockout affects cellular viability to the same extent. Genetic interactions involving date hubs are twice as prevalent as those involving party hubs or only non-hub proteins. Which proteins do interact (or not?) As expected, most proteins interact with functionally related and co-localized proteins. In the interaction network (Fig. 5) proteins of the same function and cellular location tend to cluster together, with 60-75% of the interactions occurring between proteins with a 9

10 10 common functional assignment/same subcellular compartment. When proteins are grouped by functional role or subcellular compartment, interesting patterns of crosstalk between groups can be seen (Fig. 7). Figure 7 However, the tendency to interact at all is different among different functional classes. Signaling proteins or proteins within protein complexes need to interact with multiple proteins while enzymes tend to interact only with few proteins if at all (they rather interact with low-molecular weight substrates). With respect to function, proteins involved in the yeast cell envelope appear as the least connected, followed by proteins involved in transport and binding and metabolism. At the other extreme, proteins involved in transcription, replication, cellular processes, and regulatory functions have, on average, almost twice as many binding partners. Interestingly, proteins of unknown function ( Unknown functional class) are close to the lower end of connectivity, a trend that has been observed already in some of the initial high-throughput interaction screens (Uetz et al. 2000). Figure 8 summarizes the average connectivity of proteins of various functional classes. Figure 8 Evolution and conservation of protein complexes and interactions Gavin et al. (2002) showed that many protein complexes are conserved between yeast and human, even if the proteins have only limited sequence homology. Teichmann (2002) showed that homologous proteins involved in such complexes share 46% sequence identity between S. cerevisiae and S. pombe, while proteins not known to be involved in complexes share 38% identical amino acids. This is not a huge difference and falsepositive interactions have been used to explain why highly connected proteins are not subject to more evolutionary constraints (Wagner, 2001; Hahn et al., 2004). Pagel et al. (2004) detected a correlation between the number of interaction partnes of a yeast protein and its likelihood of having an ortholog in other ascomycota species. Surprisingly, the proteins of oldest origin (i.e. proteins that are conserved across most species) do not display the highest connectivity (Kunin et al. 2004). This in is contrast with the prediction of the preferential attachment model that oldest proteins are expected to display the highest levels of connectivity (Albert and Barabasi 2000). The majority of the most highly connected proteins are rather found to have emerged during the eukaryotic radiation. Although Kunin et al. (2004) observed that the most recent proteins tend to be of lower connectivity, they failed to detect the steady increase of connectivity 10

11 11 with the protein age. Structurally, Aloy et al. (2003) found that close homologues (30 40% or higher sequence identity) almost invariably interact the same way, that is, with the same interaction surfaces. This similarity cutoff correlates well with the conservation of function which appears to be almost complete above a threshold of about 40% amino acid identity. How many protein interactions are there in yeast? The fact that neither of the two studies by Uetz et al. and Ito et al. recapitulated more than 13% of the published interactions detected by the community of yeast biologists indicates that there are many more interactions remaining to be discovered. Using approaches ranging from an educated guess to probabilistic modeling of largescale two-hybrid screens, various authors estimated the lower and upper bounds for the number of protein interactions in yeast to be around 15,000 and 30,000 interactions (Figure 9). Figure 9 Biological Relevance of protein interactions Many protein interactions are absolutely essential. However, it remains unclear which fraction of interactions are really necessary on a global scale. Jeong et al. (2001) investigated a yeast interaction network with 1,870 proteins as nodes, connected by 2,240 direct physical interactions, and found that the scale-free nature of the network makes it relatively error-tolerant, at least when the diameter of the network is measured (i.e. the average distance between two random proteins). Single random mutations in the genome of S. cerevisiae, modelled by the removal of randomly selected yeast proteins, do not affect the overall topology of the network. By contrast, when the most connected proteins are computationally eliminated, the network diameter increases rapidly. The likelihood that removal of a protein will prove lethal correlates with the number of interactions the protein has. For example, although proteins with five or fewer links constitute about 93% of the total number of proteins, Jeong et al. found that only about 21% of them are essential. By contrast, only some 0.7% of the yeast proteins with known phenotypic profiles have more than 15 links, but single deletion of 62% or so of these proves lethal. Acknowledgements We thank Pierre Legrain, Nils Johnsson, and members of the Uetz lab for critical reading of the manuscript and Andrew Emili for providing unpublished information. P.U. has been supported by DFG grant UE 50/2-1/2. 11

12 12 Related Articles g g g g g g g g g g g g g g g g Protein complexes, protein interaction domains and supramolecular architectures Protein interactions in cell signalling Biochemistry of protein complexes C. elgans interactome Small molecule and protein interactions Mammalian based assays for protein-protein interaction Database for protein interactions Membrane-anchored protein complexes Investigating protein-protein interactions in multi-subunit proteins: the case of eukaryotic RNA polymerases Computational methods for the prediction of protein interaction partners Structural biology of protein complexes Functional classification of proteins based on protein interaction data Integrative approaches to biology in the 21st century Global analysis of protein interaction networks The Alliance for Cell Signalling Data collection and analysis in systems biology References Albert R and Barabasi AL (2000) Topology of evolving networks: local events and universality. Phys Rev Lett, 85, Aloy P and Russell RB (2002) The third dimension for protein interactions and complexes. Trends Biochem Sci, 27, Aloy P, Ceulemans H, Stark A and Russell RB (2003) The relationship between sequence and interaction divergence in proteins. J Mol Biol, 332, Bader GD and Hogue CW (2002) Analyzing yeast protein-protein interaction data obtained from different sources. Nat Biotechnol, 20, Bader GD and Hogue CW (2003) An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics, 4, 2. Barabasi AL and Oltvai ZN (2004) Network biology: understanding the cell's functional organization. Nat Rev Genet, 5, Bu D, Zhao Y, Cai L, Xue H, Zhu X, Lu H, Zhang J, Sun S, Ling L, Zhang N, Li G and Chen R (2003) Topological structure analysis of the protein-protein interaction network in budding yeast. Nucleic Acids Res, 31, Cornell M, Paton NW and Oliver SG (2004) A critical and integrated view of the yeast interactome. Comp Funct Genom, 5,

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16 16 Further Reading Barabasi AL and Bonabeau E (2003) Scale-free networks. Sci Am., 288, Dorogovtsev, SN, and Mendes, JFF (2003) Evolution of Networks. From Biological Nets to the Internet and WWW, Oxford University Press, Oxford. Golemis, EA (ed.) (2001) Protein-Protein Interactions: A Molecular Cloning Manual., Cold Spring Harbor Laboratory Press, Cold Spring Harbor. Fields, S and Bartel, PL (eds.)(1997) The Yeast Two-Hybrid System., Oxford University Press, Oxford. Kleanthous, C (ed.) (2001) Protein-Protein Recognition. Oxford University Press, Oxford. 16

17 17 Tables and captions Table 1: Large-scale and examples of smaller studies of protein-protein interactions in yeast. Method (proteins) Interactions Reference Y2H ~4500 Ito et al Y2H ~1000 Uetz et al Y2H (cell polarity) 191 Drees et al Y2H (RNA splicing) 170 Fromont-Racine et al essential unknown proteins 271 Hazbun et al Y2H + PD (SH3 domain) * Tong et al Y2H (PX domain) 75 Vollert & Uetz 2004 Purification + MS ~18000** Gavin et al Purification + MS ~33000** Ho et al Synthetic lethality ~4000 Tong et al Combined large and smallscale ~15700 from DIP database collections ~12700 from MINT database ~15500 From MIPS database * 59 interactions were common to both approaches and therefore considered as highly likely. PD = phage display. **Counting all-against-all possible interactions between complex members in filtered datasets (matrix model), actual numbers of protein-protein interactions cannot be determined from the data. 17

18 18 Figure captions Figure 1. The two-hybrid system is based on the expression of two fusion (i.e. two hybrid) proteins in a cell. One of the fusion proteins contains a DNA-binding domain (DBD), which can bind to the promoter of a reporter gene (here: His3), and a B protein ( bait ). The second fusion protein consists of a transcription activation domain and an open reading frame encoding the prey protein ( P, any protein). If B interacts with ORF, a transcription factor is formed, which can switch on the reporter gene. This enables the cell to grow on a histidine-free medium. Hence, a growing yeast colony indicates that the two expressed proteins interact. If they do not interact, no colony is formed. Figure 2: Two-hybrid versus protein complex data. Skp1 is a protein involved in ubiquitin-mediated protein degradation and has been used as bait for two-hybrid screens and epitope-tagged for mass spectrometry analysis. The purified complexes of Skp1 from three independent MS studies (MS1-3) and the binary interactions from two Y2H studies (solid and broken blue lines) are compared. Despite the differences in the data sets most of the found interactions seem to be plausible: All proteins colored red are known to be involved in protein degradation. Skp1 is directed to its target proteins via so-called F-box proteins, which contain a short peptide motif, the F-box (F). For details see Titz et al. (2004). Figure 3. Statistics of proteins and complexes. Numbers inside pie charts represent the percentages of total proteins (a) and complexes (b-f) based on the data published by Gavin et al. (2002). Outer labels show partitioning of the data according to the chart function. (b) indicates the coverage of protein complexes when compared to the known complexes as cataloged in the Yeast Protein Database (YPD). For example, 46% of the complexes contained all known (100%) components of these complexes. (f) shows the conservation of proteins in complexes as defined by the presence of orthologues. For example, 27% of the complexes contained 20-40% human orthologues. 10% of the complexes did not contain any human orthologues. From Gavin et al. (2002) Figure 4. The protein complex network, and grouping of connected complexes. Links were established between complexes sharing at least one protein. For clarity, proteins found in more than nine complexes were omitted. The graphs were generated automatically by a relaxation algorithm that finds a local minimum in the distribution of nodes by minimizing the distance of connected nodes and maximizing distance of unconnected nodes. In the upper panel, cellular roles of the individual complexes are colour coded: red, cell cycle; dark green, signalling; dark blue, transcription, DNA maintenance, chromatin structure; pink, protein and RNA transport; orange, RNA metabolism; light green, protein synthesis and turnover; brown, cell polarity and structure; violet, intermediate and energy metabolism; light blue, membrane biogenesis and traffic. The lower panel is an example of a complex (yeast TAP-C212) linked to two other complexes (yeast TAP-C77 and TAP-C110) by shared components. It illustrates the connection between the protein and complex levels of organization. Red lines indicate physical interactions as listed in YPD. From Gavin et al. (2002) 18

19 19 Figure 5. An interaction map of the yeast proteome assembled from published interactions. The map contains 1,548 proteins and 2,358 interactions. Proteins are colored according to their functional role as defined by the Yeast Protein Database (YPD); proteins involved in membrane fusion (blue), chromatin structure (gray), cell structure (green), lipid metabolism (yellow), and cytokinesis (red). After Schwikowski et al. (2000). Figure 6. Date and party hubs (a). Probability densities of the average Pearson correlation coefficients (PCCs) were calculated from a global expression profiling compendium (b). The number n in each panel refers to the number of data points for each gene for each condition. No bimodal distribution is observed with the average PCCs of non-hub proteins (cyan curve) or for hubs in randomized networks (black curve). From Han et al. (2004). Figure 7. Interactions between functional groups. Numbers in parentheses indicate, first, the number of interactions within a group, and second, the number of proteins in a group. Numbers near connecting lines indicate the number of interactions between proteins of the two connected groups. For example, there are 77 interactions between the 21 proteins involved in membrane fusion and the 141 proteins involved in vesicular transport (upper left corner); 23 protein interactions connect the 21 proteins involved in membrane fusion. Only connections with 15 or more interactions are included here. Note that only proteins with known function are shown (many of these have several functions). The sum of all interactions in this diagram is therefore smaller than the number of all interactions. After Schwikowski et al. (2000). Figure 8. Average connectivity levels k of functional classes. Error was estimated from 100 random samplings of each functional class with 50 proteins each (after Kunin et al. 2004). Figure 9. Estimates of the size of the yeast interaction network, excluding homotypic interactions. Numbers and ranges are as in the original publications [von Mering 2002, Bader & Hogue 2003, Grigoriev 2003, Legrain et al. 2001, Sprinzak et al. 2003], not taking into account the changes in the estimated number of the yeast genes (for details see Grigoriev 2004). 19

20 Figure 1 Figure 2 MS3 MS1 Cep3 Rav1 YNL311C (F) B DBD P AD HIS3 YBR280 (F) YMR258C (F) Eft1 Rav2 YJL149 (F) Rcy1 (F) Cdc53 Hrt1 YLR097C (F) Skp1 Grr1 (F) MS2 Prb1 Ufo1 (F) Bop2 Ydr131C (F) Sgt1 Cdc4 Bdf1 Ctf13 (F) Rub1 Met30 (F) YLR368W (F) YLR352W (F) YLR224W (F) Figure 3 a Membrane Mitochondria 1 8 E R /G olgi/vesicles Nucleus % 32 C ytoplasm S ubcellular localization of identified proteins b 50% <75% <50% 0% % 16 75% <100% % C overage of described complexes c New complexes 58 % 9 C omplexes without new components 33 Novelties in complexes C omplexes with new components d > % e Transcription/DNA maintenance/ chromatin structure S ignalling R NA metabolism 9 24 C ell cycle 6 3 % P rotein/r NA transport 19 9 C ell polarity and structure Intermediate and energy metabolism Membrane biogenesis/ turnover P rotein synthesis/ turnover f 100% 0% >80% <100% >0% 20% 1 6 >60% 80% 14 % 27 >20% 40% 30 >40% 60% Number of proteins per complex Distribution of complexes according to function Distribution of orthologues in complexes

21 Figure RNR2 RAD53 MAM33 RPO31 RRP43 DIS3 SKI6 SRP1 RRP42 MTR3 77 MYO2 CMD1 CSL4 RRP6 RRP40 SHE4 RRP46 YJL109C SKI7 NMD5 SAM1 GCN1 ECM16 MLC1 CTR9 RFA1 RPC34 ISW2 ISW1 RRP4 RRP45 IOC3 ASF1 STO1 REB1 RVB2 HHF2 RNR4 HIR3 ADE5,7 TFC7 NHP6B VPS1 RPC40 MOT1 RFX1 ITC1 TAF145 TOP1 SFH1 RSC3 NPL6 STH1 RSC8 RSC2

22 UPF3 CRM1 CIT2 MUS81 YMR317W RIM11 KAR9 YLR266C CCZ1 SAP185 ROM2 RPC40 TPD3 SNF4 KTR3 ECM21 AIP2 GCN5 ZDS2 YKL183W NIF3 SMD1 YDR493W HSL7 DED1 BUB3 RVS167 YMR068W PUP2 YIL001W DST1 CDC20 PCL9 YHL023C DBF20 RNA15 YOL101C SAC7 STI1 YNL122C YNR048W PEX18 SEC22 YMD8 SFT2 CIN5 VMA6 YLR269C FUR1 INO80 ASH1 YOR206W RVS161 YNL050C YAP1801 ARP1 CKS1 BET1 YPR040W TSM1 CKA2 YPR008W CYP2 PAC10 YOR062C YLR376C ESR1 PKC1 YDR200C TIF5 PTP2 FPR4 MED6 PXA2 SEC20 SRO77 HYR1 NPL4 YPR115W RPT6 HDR1 WSC3 NPI46 RAD2 SPC19 PEX14 SIR1 CAF17 SPC98 YGR290W YIL007C LYS5 YCR045C YOR315W TIF4632 YKU70 PRP8 YOR138C YIL112W YMR285C SEC66 AMI1 ISY1 YOL106W YNL127W YDR130C SMY2 YLR379W CDC23 YIL113W YKR030W YOL034W BNI4 KAP123 YDR131C YDR026C SAP4 INO4 MCK1 BUB1 YCL016C RAD7 SWI4 BET5 YDR132C NUP159 CLB2 DUN1 YJL200C YGR294W CDC55 REG1 HSH49 TFB1 LSM4 EBS1 PAC2 SRB8 RCK1 SWI1 RHO2 SIN4 STB1 YER113C TEF1 UME6 MED4 TAH18 YOL070C YNL164C YOR353C YKL002W YPR049C GLN3 YDR061W YCR082W MAD1 YNL091W DAL80 DNA43 PIB1 BOI2 MNN9 YJR056C PRP9 SFB3 DIB1 APC5 PIG2 IME4 RHO3 NTF2 YOL144W YNL092W CTF19 TUP1 BNI1 YPL019C PRP21 RRN7 YDR063W MET30 ARL3 NIP29 YLR015W IPK1 YER116C SYG1 TRA1 GDS1 SEC2 GRR1 SPC34 YIL152W GAC1 YBR284W GRF10 SSA3 YNL094W SEC7 JSN1 SPB1 RPC82 YDR421W YCR086W TOF1 MEU1 SIP1 YER045C SHO1 YMR102C YOR284W RUB1 YLR123C SPT20 VAC8 KAR4 ABF1 YGR003W SPI1 HSP42 PEX5 RPO21 SSO1 YCR087W YCL056C LAC1 SUA7 KRE6 SIS2 TBF1 FIP1 KIN28 NUP82 YIL082W SUP35 MNN10 MCM21 YDL214C MDS3 YLR124W ABP1 DCP1 AUT7 ARGR3 SAP1 BEM4 YOR359W IME1 YEL015W RAS2 CSE2 TRS23 MET17 GDH2 YGL198W YLR052W YLR125W ANC1 SPA2 SPC42 NUP170 PRP18 HMO1 HOF1 YDL216C SNF5 KRR1 GLG2 CDC14 STT4 YKU80 APC2 BDF2 CCT4 YPT7 YJL064W RRP45 YMR211W YDL071C YAR014C YDL144C YDR532C YJL065C EST1 SPT8 KSS1 DAM1 SBA1 BNR1 NGG1 UBC12 SUI3 YLR128W GRX5 SSA2 YER007CA YNL279W SEC9 YPL238C VMA8 YDL218W TFB3 CEF1 IMP2 TOP3 YGR115C VPH2 TIF35 NUF1 SCJ1 COQ5 NOG1 MYO5 YHR022C RFA3 CRC1 YDR357C YDR179C ACC1 REV3 RPN5 RPN10 HSP104 SPT6 XDJ1 KIN3 YGR117C UBA2 BUL2 RPL31A MYO1 STP1 PDR1 RAS1 FKS1 TIM23 YDL076C CSE4 LYS9 YMR322C YMR071C TSP1 YBR103W YAP1 TEF4 SPP41 YLR238W YKL155C SWI3 NUP57 NYV1 SEC10 CCR4 YGR046W ADP1 SPT3 YGL015C ARK1 YML114C MDH3 RSR1 RPA135 TFC4 POP2 PTC2 TIF34 RPO41 IST3 AME1 YLR345W RPS31 VAN1 PAN1 YPR011C YJL178C YNR053C PIG1 YLR095C TUB2 HDA1 CAT2 TWF1 YGR153W NAB2 UFD1 RPT3 YOR105W YPT1 YMR325W YLR419W RRN11 HTB2 CTL1 TLG1 SST2 KAP95 PHO80 LTE1 VMA22 CNB1 SKN7 IRA1 SCM4 PFD1 SXM1 VAM3 YNL201C ACT1 CDC46 FAP1 GIC1 AKR2 YMR181C RIF2 YLR097C YBR108W CYS4 STE4 YDR469W CMD1 SMD2 YCK1 GCD2 SMI1 YMR077C CHA4 CKB1 MSL1 GOS1 SFL1 GFD1 SSN8 PPH22 SDS22 CLB5 PDR3 YDR100W SSO2 YSH1 SIN3 PRP39 YHR209W SUP45 PEP12 YDR398W RPB11 RPL11B MTR3 YIL011W SCS3 LSM8 SLA1 YCR050C MIF2 SOH1 YLR456W TOP1 SEC14 GYP1 DSS4 YAL028W HIR2 IKI3 NBP1 APG12 PAP1 NMD3 CRZ1 MYO4 HIP1 PDR11 SBP1 RSE1 YKT6 HIR1 STE5 SEC15 APG7 YDR104C YGL161C YMR291W CKB2 HSC82 YCL020W CLP1 RSC6 RDH54 RFA2 SPC97 YDR032C CDC54 GCD10 FPR1 YOR324C YLR387C DUT1 MNS1 RAD54 YDL001W ECM13 YGR268C RRP4 GCD6 PRE1 ARP10 SRB6 NHP10 NMD5 SKI6 TRS20 JNM1 YDJ1 TUB1 DCI1 PRP22 RAD1 CBF1 XPT1 YGR269W SMK1 SMP1 MYO2 UFE1 YCL024W SEC63 SNC2 PCL7 SKI7 SIM1 NUP145 CSE1 SLA2 SRV2 LAS17 YDR036C YGL239C SUI1 MAD2 YDR214W YDL110C MED2 RPL34B PEX7 PAN2 YPL025C RPG1 PRC1 PRT1 SCD5 KGD1 BIM1 RRP42 PKA3 APC1 YML088W YDR070C STB5 CDC5 VPS45 YOR078W PRE10 TIF3 FUS1 PEX2 STH1 ADR1 YKE2 HRR25 YJL211C CCT5 YDR071C OYE2 SPC25 RAD9 CDC31 ARP3 RPL16B SNF2 PRP40 GSP2 YBL049W YDL113C YCL061C YGL096W YPL027W BIK1 ARC19 YNL247W POT1 YER124C PEP7 SPR28 YPL133C APC11 KAR2 RPT4 MET18 TAF61 CDC39 SRM1 IRA2 TOR1 HOM3 SWI5 RHO1 NTC20 YPR093C YOR292C RSP5 SNF11 SIR2 YGL098W YOL082W CDC27 YAK1 LPP1 HSP82 SED5 YCL063W PUT3 SNX4 PRP11 MPT1 YOL083W QCR6 YIL163C MET32 GIP2 YDR326C CDC25 KGD2 CIN2 NAP1 BOI1 SCC2 LCP5 YEL023C MTD1 HCS1 PHO4 YJL038C MED11 IQG1 YDL117W TIM17 NPL3 MSH4 RAD55 A1 ENT2 SPT2 YDR255C SKP1 RAD17 ADH1 RIP1 ALPHA1 MSB2 PDC5 SEC35 ALPHA2 RAD4 GIN4 PEX3 SPH1 YDR078C YCR099C YKR083C YJL218W CDC26 YDR183W YHR100C SEC13 YMR009W YKL052C CUS2 RSC8 ATC1 CDC3 HBS1 SEC4 YDL225W SPT5 SIT4 IDS2 ARGR1 GCS1 YNR022C YPL246C PCL6 MCM1 YLR315W PPT1 YNL288W CDC40 YFR039C NIP100 SPC24 MTW1 COQ1 MSH5 ERV25 NRK1 MBF1 YER092W PAB1 SNF12 YLR243W YMR044W SLT2 PCL1 IMP1 GAL4 CLB3 NET1 YSP3 YKL161C MYO3 PUP3 YNR025C YLR423C MRE11 PET309 NPR2 CDC4 YDL156W SSB1 LRS4 YDL157C SFT1 TAF40 PRP19 NUP116 BUD6 YBR006W YAR027W YHR032W YHR105W EMP24 MNN11 TRS31 TFC7 SSN6 RAD51 UFD2 YLR424W SLY1 PPZ1 YOR006C NAM7 YMR226C YNL100W SQT1 FLO5 YKL090W YGR232W TRR2 MCM6 YJL184W TOA2 YLR352W NUP53 YMR048W MUD13 PHO81 YHR034C CDC12 YJL185C XRS2 FIG1 YBR113W STE7 YGR160W HHF1 CBF5 UBI4 SNC1 YNR029C ARO8 RFX1 YGL024W RAD16 YBL010C YHR140W YIR014W YHR035W RSC1 SYF2 PGD1 MTF1 TUB3 ASM4 RPL42B YEF3 TPK3 LST7 SWE1 CEG1 HHF2 MET4 PRP45 GAL80 TIF4631 ATP20 PDB1 YCR022C YBR043C HHT2 YEL068C LEU4 TRS33 SNF3 YDL089W PHO12 YHL006C YGR058W SNF1 TCM62 TKL2 BFR2 CRN1 MET28 SGS1 YRB1 ECI1 SEC31 YHR216W YJU2 FIL1 STE20 CHC1 SPR3 GIP1 SCW11 YMR263W HTA3 RSC2 CYB2 KEL2 YHR039C YGL060W YLR358C APG16 TEF2 RRN6 PCL5 DBF2 DUO1 RPT5 ECM19 YHR145C PEX21 RAD57 PCL10 MUD1 YAL036C YAP3 TOF2 YMR087W RPB2 CCL1 FOB1 YLR392C DOC1 YMR088C SIP2 CLC1 SEC18 RSG1 FUS3 RPB3 STD1 YNR068C YHL042W MEC3 CPR7 PEX17 NCE103 CMP2 YGL242C SPT7 CMK2 YJR033C PPA2 TAF145 YHR075C YOR331C YGR169C CDC19 TIM44 YNR069C POP8 ENA1 YGL170C SEC17 CNS1 RAP1 PET191 YPT52 TLG2 YMR269W NMD2 VTI1 VPS33 GAL3 HRP1 TFC5 GCD1 YHL046C CPA2 YFL002WA NFI1 YIL130W NUP49 YCR063W YDL011C RAD50 GAL11 GZF3 MFA2 YNL218W NRG1 KEM1 FCY1 TEL2 PHO85 NRD1 WTM2 CIK1 STE50 IRE1 PUP1 CYR1 SRB4 YBR190W YLR100W YDL012C YNL146W GIM5 SSP1 YIL132C YGR278W YOR262W YPL105C CLN1 RAD10 ADY1 NIC96 YGL174W BDF1 LSM7 RPL16A SAE2 APC9 RHO5 ALF1 HEX3 SME1 YIL028W APC4 NIP7 RPL25 SNP1 CTH1 HTB1 RIS1 MED8 YOR264W CDC45 SED4 YJR072C VPS9 MRS6 GCD11 ZIP2 SPT23 ARC15 MKK2 RBL2 NSP1 YJL114W YDR152W HTA1 LEA1 YOL129W PMD1 YRB2 TAF19 GAL83 THI6 ARGR2 NDD1 TOA1 MHP1 VPS21 CLB4 MPT5 RAD5 MOG1 CDC16 YNL078W PGI1 SIP3 CDC7 SMT3 YBL059W YJL043W GLC7 SIR4 CLU1 CBP3 MNN4 HOC1 ARG1 YIL065C TPM2 PCF11 SMB1 NUD1 TUB4 CDC11 SAP155 YKL023W YFR008W YPL070W SPO21 ROX3 RHO4 VMA7 MET31 GPD2 REV7 CRR1 TAF90 YLA1 MIR1 GDH1 YPL144W SHE2 TOR2 YJL151C PAN3 YIL172C YDR084C ADE8 YBL101WA YFR042W MSN5 GDI1 CDC48 SAR1 AHP1 YNL187W RTT101 AFR1 YPL146C MCM3 YMR316CB YKL204W VTH1 YDR409W YKR090W PCL8 KAR1 AKR1 YJL048C ICL1 SFH1 CPR6 PCL2 LOS1 YAR030C DHH1 PXA1 YGR024C SRP1 NUP42 RRP1 VIK1 RGR1 SRP40 RAD3 TFA1 YLR322W GCR1 BRR2 YFR046C RNA12 YMR051C SLU7 YLR323C HHT1 YAR031W ENT1 MBP1 YGR203W YKL061W ANP1 YPD1 HFI1 SDH2 STB4 APG5 GPA1 APL2 YDR445C YFR047C SSK2 MDJ1 SIG1 FAR3 STO1 RAD23 YLR324W YJL084C FAR1 STB2 CLN2 SMD3 PHO13 YOR011W FRQ1 ECM11 REF2 PEP5 SEN1 PPG1 GNA1 RAD59 RPS22A CLA4 EXO70 FUS2 RPL10 PEP3 EFB1 BUB2 YLR076C CDC36 DIG2 ADA2 YMR233W YLR432W YDL239C SRB2 CNA1 ARC35 APM1 SSA1 YGL104C RTS1 BMH1 ARH1 SWI6 POM152 YAP1802 SPT4 RNP1 YDR482C PSE1 YMR057C BOS1 HRB1 YCR101C YGR136W ARG3 KAP104 BAS1 LSM6 NIP1 SNU114 CDC6 NUP100 REG2 TFC1 SIP4 DMC1 STE11 TAF17 SIC1 PFY1 NPL6 NMD4 MLC1 CLN3 SNT309 YCR030C PET127 RPL37A RPN6 GSY2 GIF1 RPL11A YDR485C RRN9 AIP1 GCD7 VAM7 HSP60 DBP2 TSA1 YLL049W MIG1 YBR052C PTC4 AAD6 DFG5 YIP1 CDC24 SEC72 RPC19 YIR025W SET1 PRE2 YMR093W BRF1 YGR068C GSP1 SCM2 APL1 SPO12 YGR173W WTM1 CPA1 DIS3 CTF13 MRPL4 YCR087CA STE3 YPR105C ZDS1 SNO1 YLR294C CEP3 CLG1 YCR033W MCM2 BOP3 SRO7 MKK1 PRP6 RPS22B RPL34A TEM1 CDC28 PBP2 SNZ3 YNL116W SUI2 MGE1 RRP43 ARC40 RGA1 SNZ1 YLR368W YTH1 YLSM3 BUL1 YHL018W YIP3 ORC1 MTR10 MGA1 APM2 MUM2 DCP2 RRN10 TIP20 AUT2 SPC72 YHR083W YDR016C ABD1 RPC31 KAR3 PBP1 LSM2 UBC6 HSF1 ALR1 STE12 YIL105C KCS1 YPL110C RPD3 SGT1 YKR022C CNM67 YNL047C KEL1 YGR179C KIN1 PRP5 NOP10 YAL049C SRA1 YML068W INO2 YBR270C RPA190 GIM3 YOR164C RPS8B APG1 MOB1 CAR1 SKT5 STE24 MAD3 CAP2 MED1 AMI3 YCK2 YNL227C SSC1 GLK1 VPH1 SSA4 FZF1 RPN4 HRT1 ILV6 YPT31 YMEL1 CKA1 DBF4 SSK22 YBR094W SNZ2 YNL155W NUP157 SEC24 NOT5 ASN1 MED7 SNO2 GCN3 URE2 KIP1 GAR1 YIL141W RPS28A FIR1 SSL1 CDC34 SSN3 SSK1 PFK27 END3 CHK1 YNL335W MAM33 SSL2 GLE2 NOT3 RIF1 REV1 YIF1 HSL1 YDR128W YKR060W SAP190 CMK1 AOS1 SAC6 PAT1 YLR008C GIM4 SEC23 YOR275C PUT4 YDR412W TID3 YDL203C YPL222W HOG1 UBP13 LAP4 YNL086W LSM1 YHR197W YER036C SRB7 YJR083C CDC33 RPP1B YHR198C YCL046W HOP1 NUP1 YJL019W TFA2 VPS16 GCD14 FMN1 SMX3 GIC2 PRP46 CAF20 YPR078C CCC1 TOP2 SLN1 CDC53 DDI1 MPS1 MSL5 RAD14 RAD53 PDC1 SYF3 YDL133W SYF1 PPH21 STE18 SOR1 PBS2 RPC34 APG13 IFH1 STU2 DIG1 GLE1 ARP2 STM1 RDI1 GCN4 DOA1 SRB5 YJR087W MOT1 YLR046C NHP2 YLL014W RPN12 LSM5 TAF25 YPL260W YMR025W YLR224W CET1 YJL162C IKS1 YNR005C RPO26 BET3 SDH3 GSC2 YDR273W RFA1 YPL229W BIR1 PTP3 YJL058C STB3 ACS2 GCR2 UBC9 SDC25 SPT15 PEX19 GLC8 PEA2 AUT1 YLR049C SMX2 RGT2 SEC16 TAP42 COF1 RPC25 RPL31B SRL2 GAL1 CBF2 SPO13 HPR5 CLB1 PTM1 RNA14 NUP188 KNS1 CLB6 HSP10 CUS1 MTH1 YLR261C YPL192C CDC42 STB6 RPT1 RPP2B YFR057W BMH2 YDL246C MDM1 AQY2 YSC84 YDR383C YLR440C QCR7 BEM1 NDC1 CDC10 CHS3 YER079W PRE5 NUP2 RAD52 MUD2 RLM1 TAF60 BCK1 SNO3 TOM1 CAF16 YLR190W RED1 DDC1 YKL075C SDH1 AHC1 SIR3 VRP1 CDC47 YCP4 PEX13 CAK1 KAR5 RPS28B CIN4 PLC1 ARC18 YFL061W Figure 5 Figure 6

23 Amino-acid-metabolism (23/68) 20 Meiosis (17/55) Membrane-fusion (23/21) Mitosis (81/75) DNA-synthesis (41/50) 77 Protein-degradation (77/84) Vesicular-transport (141/141) Cell-cycle-control Recombination (9/28) Cell-structure (39/54) 20 (90/113) Cell-polarity (54/52) Mating-response 47 Protein Protein-folding (18/32) 27 (41/66) modification DNA-repair (37/65) 19 (28/65) Cytokinesis (18) Differentiation 21 Chromatin/chromosome Protein-synthesis (54/89) structure (72/102) Protein-translocation (51/54) (4/20) RNA-processing/modification (117/132) Nuclear-cytoplasmic-transport 32 (106/56) Signal-transduction (42/66) Lipid/fatty-acid and RNA-turnover sterol-metabolism (18/27) 29 (9/16) Pol-II-transcription (184/177) RNA-splicing (65/65) Cell-stress (27/75) Pol-I-transcription (9/17) 32 Carbohydrate-metabolism Pol-III-transcription (14/21) (30/78) Figure 7 Cell envelope Unknown Figure 8 Transport Metabolism Translation Regulation Cellular processes Replication Transcription connectivity <k> Figure 9 E von Mering et al D Bader and Hogue 2003 C Grigoriev 2003 B Legrain et al A Sprinzak et al Tucker et al Number of Interactions