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ODU CS 791 - Physical and functional modularity of the protein network in yeast

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Physical and functional modularity of theprotein network in yeastThomas Wilhelm§∗, Heinz-Peter Nasheuer†& Sui Huang‡§Institute of Molecular Biotechnology,Beutenbergstr. 11, D-07745 Jena, Germany†Department of Biochemistry, National University of Ireland,University Road, Galway, Ireland‡Department of Surgery, Children’s Hospital,Harvard Medical School, Boston, MA 02115, USA∗corresponding author; e-mail: [email protected], phone: +49 3641 656208, fax:+49 3641 6561911Running title: Modularity of the protein network in yeastAbbreviations:TAP - Tandem affinity purificationHMS-PCI - High-throughput mass-spectrometric protein complex identifica-tionPN - Protein-protein interaction networkCN - Protein complex interaction network2AbstractWhile protein-protein interactions have been studied largely as a net-work graph without physicality, here we analyze two protein complexdata sets of Saccharomyces cerevisiae to relate physical and functionalmodularity to the network topology. We study for the first time thenumber of different protein complexes as a function of the proteincomplex size and find that it follows an exponential decay with acharacteristic number of about 7. This reflects the dynamics of com-plex formation and dissociation in the cell. The analysis of the proteinusage by complexes shows an extensive sharing of subunits that is dueto the particular organization of the proteome into physical complexesand functional modules. This promiscuity accounts for the high clus-tering in the protein network graph. Our results underscore the needto include the information contained in observed protein complexesinto protein network analyses.Metabolic and signaling functions as well as global cell behavior arise fromthe collective action of proteins which engage in physical interactions. Thus,a first step in the functional characterization of the proteome is the iden-tification of protein-protein interactions. This has most exhaustively beenachieved for the budding yeast (S. cerevisiae) proteome, resulting in largelists of interaction pairs (1,2). This information has allowed the reconstruc-tion of a crude map of the protein interaction network (Fig.1A). Althoughsuch network maps are still devoid of any information on dynamics that wouldallow the simulation of cell behavior (3,4), they have paved the way to thestudy of global topological properties of molecular networks which have shedlight on basic evolutionary and organizational principles (5-7). For instance,3using yeast two-hybrid data it has been suggested that the connectivity dis-tribution P (k), i.e. the probability that a protein interacts with k otherproteins, follows a power law and therefore belong to the topology class ofscale-free networks (5).These topology studies relied on the abstract network graphs that wereconstructed with individual pairs of interactions identified separately, and assuch do not represent a physical entity. They do not consider the fact thatmany protein-protein interactions in the cell take place in dynamic, multi-protein complexes (Fig.1B). Thus, when placing the topology of the proteininteraction graph into a physical context, questions automatically arise, as towhether a highly connected protein (a hub in the scale-free network model),would simultaneously interact with all of its partners as denoted in the net-work graph and, in doing so, form one stable, observable protein complex.Further, one would also like to know how the protein complexes (physicalmodules) relate to the clusters of highly connected nodes in the networkgraphs (topological modules). The recent systematic survey of stable proteincomplexes using high-throughput mass spectrometry of purified tagged yeastproteins now allows us to examine generic aspects of the large-scale propertiesof complex mediated networks and to address this type of questions (8,9).The data sets are denoted according to the authors as (i) the TAP (tan-dem affinity purification) (8), and (ii) the HMS-PCI (high-throughput mass-spectrometric protein complex identification) (9) data sets. Their accuracyhas been compared with that of other methods of protein-protein interactiondetection (1). They have also been used to validate and complement exist-ing yeast interaction datasets and to infer the function of individual proteins4(10). Thus, while the protein complex data has been used to improve func-tional annotation of individual proteins, the additional, generic informationin these datasets, notably the complex size distribution and the pattern ofusage of subunits in various complexes has not been studied explicitly. Herewe investigate these two generic aspects of the population of yeast proteincomplexes, identify some characteristic features and propose models to ex-plain them.EXPERIMENTAL PROCEDURESStability and concentration of protein complexesThe number Nsof possible dissociations for a complex consisting of s proteins isNs=Ps/2i=1si−ss/2/2 if s is even, and Ns=P(s−1)/2i=1siif s is odd. It follows thesimple exact result Ns= 2Ns−1+1 = 2s−1−1. If all possible dissociations of a givencomplex occur on average with equal probability it follows the exponential decay ofthe average lifetime hτsi of a complex with s proteins: hτsi ∝ N−1s. If the numberSsof all complexes of size s, Ss=Pnsixs,i(ns= n0exp(−as) is the number ofdifferent complexes of size s (Fig.2), and xs,iis the number of complexes of speciesi (consists of exactly the same type of s proteins)), is proportional to τsit followsby using the above equations for Nsand hτsi: Ss/Ss−1∼=0.5. If for each complexsize xs,iis normally distributed around hxs,ii it follows by using the equations forSsand ns: hxs,ii exp(−as)/(hxs−1,ii exp(−a(s − 1)))∼=0.5 and therefore with theexperimentally determined characteristic number of different protein complexesa = acompl.size(Fig.2): hxs,ii ≈ 0.6hxs−1,ii. This finding suggests that the meannumber of one type of protein complexes of a given size decreases by 40% if the5size is increased by one.Construction of protein-protein interaction networks (PN):Three definitions of protein interactions (Fig.1)A “small P N” variant counts only the interactions A-B where protein A astagged bait catches protein B and protein B as bait catches protein A in the massspectroscopy protein complex analysis. In doing so one obtains P Ns with only193 proteins and 191 interactions for TAP, and 99 proteins and 67 interactionsfor


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ODU CS 791 - Physical and functional modularity of the protein network in yeast

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