Journal of Molecular Evolution

, Volume 68, Issue 3, pp 248–255 | Cite as

Low Contents of Carbon and Nitrogen in Highly Abundant Proteins: Evidence of Selection for the Economy of Atomic Composition

  • Ning Li
  • Jie Lv
  • Deng-Ke NiuEmail author


Proteins that assimilate particular elements were found to avoid using amino acids containing the element, which indicates that the metabolic constraints of amino acids may influence the evolution of proteins. We suspected that low contents of carbon, nitrogen, and sulfur may also be selected for economy in highly abundant proteins that consume large amounts of the resources of cells. By analyzing recently available proteomic data in Escherichia coli, Saccharomyces cerevisiae, and Schizosaccharomyces pombe, we found that at least the carbon and nitrogen contents in amino acid side chains are negatively correlated with protein abundance. An amino acid with a high number of carbon atoms in its side chain generally requires relatively more energy for its synthesis. Thus, it may be selected against in highly abundant proteins either because of economy in building blocks or because of economy in energy. Previous studies showed that highly abundant proteins preferentially use cheap (in terms of energy) amino acids. We found that the carbon content is still negatively correlated with protein abundance after controlling for the energetic cost of the amino acids. However, the negative correlation between protein abundance and energetic cost disappeared after controlling for carbon content. Building blocks seem to be more restricted than energy. It seems that the amino acid sequences of highly abundant proteins have to compromise between optimization for their biological functions and reducing the consumption of limiting resources. By contrast, the amino acid sequences of weakly expressed proteins are more likely to be optimized for their biological functions.


Atomic content Energetic cost Amino acid usage Resource availability Protein abundance Protein turnover rate 



We thank anonymous reviewers for very valuable comments on the manuscript and Xiaomei Wu, Jie Guo, and Yi-Fei Huang for their help. This study was supported by Program NCET-07-0094 and Beijing Normal University.

Supplementary material

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(DOC 243 kb)


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© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.MOE Key Laboratory for Biodiversity Science and Ecological Engineering, College of Life SciencesBeijing Normal UniversityBeijingChina

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