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Biosynthetic potentials of metabolites and their hierarchical organization.

Matthäus F, Salazar C, Ebenhöh O - PLoS Comput. Biol. (2008)

Bottom Line: We observe that most of the resulting consensus scopes overlap or are fully contained in others, revealing a hierarchical ordering of metabolites according to their biosynthetic potential.A central result is that chemically very similar substances with different biological functions may differ significantly in their biosynthetic potentials.Our studies provide an important step towards understanding fundamental design principles of metabolic networks determined by the structural and functional complexity of metabolites.

View Article: PubMed Central - PubMed

Affiliation: Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.

ABSTRACT
A major challenge in systems biology is to understand how complex and highly connected metabolic networks are organized. The structure of these networks is investigated here by identifying sets of metabolites that have a similar biosynthetic potential. We measure the biosynthetic potential of a particular compound by determining all metabolites than can be produced from it and, following a terminology introduced previously, call this set the scope of the compound. To identify groups of compounds with similar scopes, we apply a hierarchical clustering method. We find that compounds within the same cluster often display similar chemical structures and appear in the same metabolic pathway. For each cluster we define a consensus scope by determining a set of metabolites that is most similar to all scopes within the cluster. This allows for a generalization from scopes of single compounds to scopes of a chemical family. We observe that most of the resulting consensus scopes overlap or are fully contained in others, revealing a hierarchical ordering of metabolites according to their biosynthetic potential. Our investigations show that this hierarchy is not only determined by the chemical complexity of the metabolites, but also strongly by their biological function. As a general tendency, metabolites which are necessary for essential cellular processes exhibit a larger biosynthetic potential than those involved in secondary metabolism. A central result is that chemically very similar substances with different biological functions may differ significantly in their biosynthetic potentials. Our studies provide an important step towards understanding fundamental design principles of metabolic networks determined by the structural and functional complexity of metabolites.

Show MeSH
Hierarchical clustering method: choice of clustering level.(A) Increasing distances at which clusters are merged at successive iterations of the nearest neighbors clustering. (B) Number of clusters of a given minimum size versus the joining distance at each iteration.
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pcbi-1000049-g005: Hierarchical clustering method: choice of clustering level.(A) Increasing distances at which clusters are merged at successive iterations of the nearest neighbors clustering. (B) Number of clusters of a given minimum size versus the joining distance at each iteration.

Mentions: The result obtained in this procedure is a clustering of the data on various scales. At the first iterations only very similar elements obtain the same cluster label and the clustering is very fine. Towards the end elements or clusters with large distances are joint, resulting in a coarse clustering with a smaller number of clusters. Figure 5A shows the increasing distances at which elements or clusters are merged at subsequent iterations of the nearest neighbors clustering. In the beginning elements are clustered at very small distances, in fact there is quite a large number of identical scopes. In the next region the distances increase linearly to the maximum value. The following iterations then join elements that do not have even a single common substance in their scopes. All the very small scopes of compounds with zero synthesizing capacity are assigned to clusters in this last phase.


Biosynthetic potentials of metabolites and their hierarchical organization.

Matthäus F, Salazar C, Ebenhöh O - PLoS Comput. Biol. (2008)

Hierarchical clustering method: choice of clustering level.(A) Increasing distances at which clusters are merged at successive iterations of the nearest neighbors clustering. (B) Number of clusters of a given minimum size versus the joining distance at each iteration.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2289774&req=5

pcbi-1000049-g005: Hierarchical clustering method: choice of clustering level.(A) Increasing distances at which clusters are merged at successive iterations of the nearest neighbors clustering. (B) Number of clusters of a given minimum size versus the joining distance at each iteration.
Mentions: The result obtained in this procedure is a clustering of the data on various scales. At the first iterations only very similar elements obtain the same cluster label and the clustering is very fine. Towards the end elements or clusters with large distances are joint, resulting in a coarse clustering with a smaller number of clusters. Figure 5A shows the increasing distances at which elements or clusters are merged at subsequent iterations of the nearest neighbors clustering. In the beginning elements are clustered at very small distances, in fact there is quite a large number of identical scopes. In the next region the distances increase linearly to the maximum value. The following iterations then join elements that do not have even a single common substance in their scopes. All the very small scopes of compounds with zero synthesizing capacity are assigned to clusters in this last phase.

Bottom Line: We observe that most of the resulting consensus scopes overlap or are fully contained in others, revealing a hierarchical ordering of metabolites according to their biosynthetic potential.A central result is that chemically very similar substances with different biological functions may differ significantly in their biosynthetic potentials.Our studies provide an important step towards understanding fundamental design principles of metabolic networks determined by the structural and functional complexity of metabolites.

View Article: PubMed Central - PubMed

Affiliation: Interdisciplinary Center for Scientific Computing, University of Heidelberg, Heidelberg, Germany.

ABSTRACT
A major challenge in systems biology is to understand how complex and highly connected metabolic networks are organized. The structure of these networks is investigated here by identifying sets of metabolites that have a similar biosynthetic potential. We measure the biosynthetic potential of a particular compound by determining all metabolites than can be produced from it and, following a terminology introduced previously, call this set the scope of the compound. To identify groups of compounds with similar scopes, we apply a hierarchical clustering method. We find that compounds within the same cluster often display similar chemical structures and appear in the same metabolic pathway. For each cluster we define a consensus scope by determining a set of metabolites that is most similar to all scopes within the cluster. This allows for a generalization from scopes of single compounds to scopes of a chemical family. We observe that most of the resulting consensus scopes overlap or are fully contained in others, revealing a hierarchical ordering of metabolites according to their biosynthetic potential. Our investigations show that this hierarchy is not only determined by the chemical complexity of the metabolites, but also strongly by their biological function. As a general tendency, metabolites which are necessary for essential cellular processes exhibit a larger biosynthetic potential than those involved in secondary metabolism. A central result is that chemically very similar substances with different biological functions may differ significantly in their biosynthetic potentials. Our studies provide an important step towards understanding fundamental design principles of metabolic networks determined by the structural and functional complexity of metabolites.

Show MeSH