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Functional integrative levels in the human interactome recapitulate organ organization.

Souiai O, Becker E, Prieto C, Benkahla A, De las Rivas J, Brun C - PLoS ONE (2011)

Bottom Line: Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery.This gradient of functions recapitulates the organization of organs, from cells to organs.Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.

View Article: PubMed Central - PubMed

Affiliation: INSERM, U928, TAGC, Marseille, France.

ABSTRACT
Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This 'Largest Common Interactome Network' represents a 'functional interactome core'. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.

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Workflow.The human interactome network is analyzed with two classification processes. (Left side) Using ESTs as source of gene expression, 22 tissular interactomes are inferred. The Interaction Usage of each interaction is determined, i.e. the number of tissues in which the interaction is possible given the co-expression of the partners in tissues. For each IU bin containing interactions with respect to their interaction usage, enrichment or depletion of GO Biological Process (BP) are computed and represented as a heatmap, which is ultimately clusterized using a k-means algorithm. (Right side) Following a k-core decomposition of the graph, enrichment or depletion of GO Biological Process are computed for proteins of coreness 1 to 9 and represented as a heatmap. (Bottom) For each UI cluster, enrichment/depletion profiles according to UI and topology are compared.
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pone-0022051-g001: Workflow.The human interactome network is analyzed with two classification processes. (Left side) Using ESTs as source of gene expression, 22 tissular interactomes are inferred. The Interaction Usage of each interaction is determined, i.e. the number of tissues in which the interaction is possible given the co-expression of the partners in tissues. For each IU bin containing interactions with respect to their interaction usage, enrichment or depletion of GO Biological Process (BP) are computed and represented as a heatmap, which is ultimately clusterized using a k-means algorithm. (Right side) Following a k-core decomposition of the graph, enrichment or depletion of GO Biological Process are computed for proteins of coreness 1 to 9 and represented as a heatmap. (Bottom) For each UI cluster, enrichment/depletion profiles according to UI and topology are compared.

Mentions: In the work described here (Figure 1), we aim at understanding the influence of function on interactome topology and answering questions such as ‘Does interactome topology reflect functional issues? Does function ‘shape’ the interactome? Is there an organizational ‘functional logic’ in the interactome?'. For this, we classified the interactions according to gene expression and the proteins according to network topology. By interpreting the results functionally using GO annotations, we address tissue diversity from an interactome point of view. We first defined the Largest Common Interactome Network (LCIN) which consists of those interactions possible in all the tissues tested, and whose proteins are mainly involved in housekeeping functions. We show that this LCIN corresponds to a ‘functional interactome core’, lying at the topological center of the interactome, and that tissue-specific interactions by definition excluded from the LCIN, are interestingly (i) centrally located when involved in regulatory and developmental functions and (ii) located at the periphery when involved in organ physiological functions. Combining interactions, expression, interactome network topology with cellular function annotations, we show that the organization of the interactome follows a functional gradient recapitulating the organization of organs.


Functional integrative levels in the human interactome recapitulate organ organization.

Souiai O, Becker E, Prieto C, Benkahla A, De las Rivas J, Brun C - PLoS ONE (2011)

Workflow.The human interactome network is analyzed with two classification processes. (Left side) Using ESTs as source of gene expression, 22 tissular interactomes are inferred. The Interaction Usage of each interaction is determined, i.e. the number of tissues in which the interaction is possible given the co-expression of the partners in tissues. For each IU bin containing interactions with respect to their interaction usage, enrichment or depletion of GO Biological Process (BP) are computed and represented as a heatmap, which is ultimately clusterized using a k-means algorithm. (Right side) Following a k-core decomposition of the graph, enrichment or depletion of GO Biological Process are computed for proteins of coreness 1 to 9 and represented as a heatmap. (Bottom) For each UI cluster, enrichment/depletion profiles according to UI and topology are compared.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3140469&req=5

pone-0022051-g001: Workflow.The human interactome network is analyzed with two classification processes. (Left side) Using ESTs as source of gene expression, 22 tissular interactomes are inferred. The Interaction Usage of each interaction is determined, i.e. the number of tissues in which the interaction is possible given the co-expression of the partners in tissues. For each IU bin containing interactions with respect to their interaction usage, enrichment or depletion of GO Biological Process (BP) are computed and represented as a heatmap, which is ultimately clusterized using a k-means algorithm. (Right side) Following a k-core decomposition of the graph, enrichment or depletion of GO Biological Process are computed for proteins of coreness 1 to 9 and represented as a heatmap. (Bottom) For each UI cluster, enrichment/depletion profiles according to UI and topology are compared.
Mentions: In the work described here (Figure 1), we aim at understanding the influence of function on interactome topology and answering questions such as ‘Does interactome topology reflect functional issues? Does function ‘shape’ the interactome? Is there an organizational ‘functional logic’ in the interactome?'. For this, we classified the interactions according to gene expression and the proteins according to network topology. By interpreting the results functionally using GO annotations, we address tissue diversity from an interactome point of view. We first defined the Largest Common Interactome Network (LCIN) which consists of those interactions possible in all the tissues tested, and whose proteins are mainly involved in housekeeping functions. We show that this LCIN corresponds to a ‘functional interactome core’, lying at the topological center of the interactome, and that tissue-specific interactions by definition excluded from the LCIN, are interestingly (i) centrally located when involved in regulatory and developmental functions and (ii) located at the periphery when involved in organ physiological functions. Combining interactions, expression, interactome network topology with cellular function annotations, we show that the organization of the interactome follows a functional gradient recapitulating the organization of organs.

Bottom Line: Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery.This gradient of functions recapitulates the organization of organs, from cells to organs.Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.

View Article: PubMed Central - PubMed

Affiliation: INSERM, U928, TAGC, Marseille, France.

ABSTRACT
Interactome networks represent sets of possible physical interactions between proteins. They lack spatio-temporal information by construction. However, the specialized functions of the differentiated cell types which are assembled into tissues or organs depend on the combinatorial arrangements of proteins and their physical interactions. Is tissue-specificity, therefore, encoded within the interactome? In order to address this question, we combined protein-protein interactions, expression data, functional annotations and interactome topology. We first identified a subnetwork formed exclusively of proteins whose interactions were observed in all tested tissues. These are mainly involved in housekeeping functions and are located at the topological center of the interactome. This 'Largest Common Interactome Network' represents a 'functional interactome core'. Interestingly, two types of tissue-specific interactions are distinguished when considering function and network topology: tissue-specific interactions involved in regulatory and developmental functions are central whereas tissue-specific interactions involved in organ physiological functions are peripheral. Overall, the functional organization of the human interactome reflects several integrative levels of functions with housekeeping and regulatory tissue-specific functions at the center and physiological tissue-specific functions at the periphery. This gradient of functions recapitulates the organization of organs, from cells to organs. Given that several gradients have already been identified across interactomes, we propose that gradients may represent a general principle of protein-protein interaction network organization.

Show MeSH