dorsal/arxiv
View SchemaLow Degree Metabolites Explain Essential Reactions and Enhance Modularity in Biological Networks
| Authors | Areejit Samal, Shalini Singh, Varun Giri, Sandeep Krishna, N. Raghuram, Sanjay Jain |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0504026 |
| URL | https://arxiv.org/abs/q-bio/0504026 |
| Journal | BMC Bioinformatics 7:118 (2006) |
Abstract
Recently there has been a lot of interest in identifying modules at the level of genetic and metabolic networks of organisms, as well as in identifying single genes and reactions that are essential for the organism. A goal of computational and systems biology is to go beyond identification towards an explanation of specific modules and essential genes and reactions in terms of specific structural or evolutionary constraints. In the metabolic networks of E. coli, S. cerevisiae and S. aureus, we identified metabolites with a low degree of connectivity, particularly those that are produced and/or consumed in just a single reaction. Using FBA we also determined reactions essential for growth in these metabolic networks. We find that most reactions identified as essential in these networks turn out to be those involving the production or consumption of low degree metabolites. Applying graph theoretic methods to these metabolic networks, we identified connected clusters of these low degree metabolites. The genes involved in several operons in E. coli are correctly predicted as those of enzymes catalyzing the reactions of these clusters. We independently identified clusters of reactions whose fluxes are perfectly correlated. We find that the composition of the latter `functional clusters' is also largely explained in terms of clusters of low degree metabolites in each of these organisms. Our findings mean that most metabolic reactions that are essential can be tagged by one or more low degree metabolites. Those reactions are essential because they are the only ways of producing or consuming their respective tagged metabolites. Furthermore, reactions whose fluxes are strongly correlated can be thought of as `glued together' by these low degree metabolites.
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"abstract": "Recently there has been a lot of interest in identifying modules at the level\nof genetic and metabolic networks of organisms, as well as in identifying\nsingle genes and reactions that are essential for the organism. A goal of\ncomputational and systems biology is to go beyond identification towards an\nexplanation of specific modules and essential genes and reactions in terms of\nspecific structural or evolutionary constraints. In the metabolic networks of\nE. coli, S. cerevisiae and S. aureus, we identified metabolites with a low\ndegree of connectivity, particularly those that are produced and/or consumed in\njust a single reaction. Using FBA we also determined reactions essential for\ngrowth in these metabolic networks. We find that most reactions identified as\nessential in these networks turn out to be those involving the production or\nconsumption of low degree metabolites. Applying graph theoretic methods to\nthese metabolic networks, we identified connected clusters of these low degree\nmetabolites. The genes involved in several operons in E. coli are correctly\npredicted as those of enzymes catalyzing the reactions of these clusters. We\nindependently identified clusters of reactions whose fluxes are perfectly\ncorrelated. We find that the composition of the latter `functional clusters\u0027 is\nalso largely explained in terms of clusters of low degree metabolites in each\nof these organisms. Our findings mean that most metabolic reactions that are\nessential can be tagged by one or more low degree metabolites. Those reactions\nare essential because they are the only ways of producing or consuming their\nrespective tagged metabolites. Furthermore, reactions whose fluxes are strongly\ncorrelated can be thought of as `glued together\u0027 by these low degree\nmetabolites.",
"arxiv_id": "q-bio/0504026",
"authors": [
"Areejit Samal",
"Shalini Singh",
"Varun Giri",
"Sandeep Krishna",
"N. Raghuram",
"Sanjay Jain"
],
"categories": [
"q-bio.MN"
],
"journal_ref": "BMC Bioinformatics 7:118 (2006)",
"title": "Low Degree Metabolites Explain Essential Reactions and Enhance Modularity in Biological Networks",
"url": "https://arxiv.org/abs/q-bio/0504026"
},
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