Hydrophobicity and charge shape cellular metabolite concentrations.
What governs the concentrations of metabolites within living cells? Beyond specific metabolic and enzymatic considerations, are there global trends that affect their values? We hypothesize that the physico-chemical properties of metabolites considerably affect their in-vivo concentrations. The recen...
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doaj-941bb9c37ca7422db84d3bd77987e2062021-04-21T15:28:38ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582011-10-01710e100216610.1371/journal.pcbi.1002166Hydrophobicity and charge shape cellular metabolite concentrations.Arren Bar-EvenElad NoorAvi FlamholzJoerg M BuescherRon MiloWhat governs the concentrations of metabolites within living cells? Beyond specific metabolic and enzymatic considerations, are there global trends that affect their values? We hypothesize that the physico-chemical properties of metabolites considerably affect their in-vivo concentrations. The recently achieved experimental capability to measure the concentrations of many metabolites simultaneously has made the testing of this hypothesis possible. Here, we analyze such recently available data sets of metabolite concentrations within E. coli, S. cerevisiae, B. subtilis and human. Overall, these data sets encompass more than twenty conditions, each containing dozens (28-108) of simultaneously measured metabolites. We test for correlations with various physico-chemical properties and find that the number of charged atoms, non-polar surface area, lipophilicity and solubility consistently correlate with concentration. In most data sets, a change in one of these properties elicits a ~100 fold increase in metabolite concentrations. We find that the non-polar surface area and number of charged atoms account for almost half of the variation in concentrations in the most reliable and comprehensive data set. Analyzing specific groups of metabolites, such as amino-acids or phosphorylated nucleotides, reveals even a higher dependence of concentration on hydrophobicity. We suggest that these findings can be explained by evolutionary constraints imposed on metabolite concentrations and discuss possible selective pressures that can account for them. These include the reduction of solute leakage through the lipid membrane, avoidance of deleterious aggregates and reduction of non-specific hydrophobic binding. By highlighting the global constraints imposed on metabolic pathways, future research could shed light onto aspects of biochemical evolution and the chemical constraints that bound metabolic engineering efforts.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21998563/pdf/?tool=EBI |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Arren Bar-Even Elad Noor Avi Flamholz Joerg M Buescher Ron Milo |
spellingShingle |
Arren Bar-Even Elad Noor Avi Flamholz Joerg M Buescher Ron Milo Hydrophobicity and charge shape cellular metabolite concentrations. PLoS Computational Biology |
author_facet |
Arren Bar-Even Elad Noor Avi Flamholz Joerg M Buescher Ron Milo |
author_sort |
Arren Bar-Even |
title |
Hydrophobicity and charge shape cellular metabolite concentrations. |
title_short |
Hydrophobicity and charge shape cellular metabolite concentrations. |
title_full |
Hydrophobicity and charge shape cellular metabolite concentrations. |
title_fullStr |
Hydrophobicity and charge shape cellular metabolite concentrations. |
title_full_unstemmed |
Hydrophobicity and charge shape cellular metabolite concentrations. |
title_sort |
hydrophobicity and charge shape cellular metabolite concentrations. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Computational Biology |
issn |
1553-734X 1553-7358 |
publishDate |
2011-10-01 |
description |
What governs the concentrations of metabolites within living cells? Beyond specific metabolic and enzymatic considerations, are there global trends that affect their values? We hypothesize that the physico-chemical properties of metabolites considerably affect their in-vivo concentrations. The recently achieved experimental capability to measure the concentrations of many metabolites simultaneously has made the testing of this hypothesis possible. Here, we analyze such recently available data sets of metabolite concentrations within E. coli, S. cerevisiae, B. subtilis and human. Overall, these data sets encompass more than twenty conditions, each containing dozens (28-108) of simultaneously measured metabolites. We test for correlations with various physico-chemical properties and find that the number of charged atoms, non-polar surface area, lipophilicity and solubility consistently correlate with concentration. In most data sets, a change in one of these properties elicits a ~100 fold increase in metabolite concentrations. We find that the non-polar surface area and number of charged atoms account for almost half of the variation in concentrations in the most reliable and comprehensive data set. Analyzing specific groups of metabolites, such as amino-acids or phosphorylated nucleotides, reveals even a higher dependence of concentration on hydrophobicity. We suggest that these findings can be explained by evolutionary constraints imposed on metabolite concentrations and discuss possible selective pressures that can account for them. These include the reduction of solute leakage through the lipid membrane, avoidance of deleterious aggregates and reduction of non-specific hydrophobic binding. By highlighting the global constraints imposed on metabolic pathways, future research could shed light onto aspects of biochemical evolution and the chemical constraints that bound metabolic engineering efforts. |
url |
https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21998563/pdf/?tool=EBI |
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