Journal of Molecular Evolution

, Volume 74, Issue 3–4, pp 206–216 | Cite as

Metabolic and Translational Efficiency in Microbial Organisms

  • Douglas W. Raiford
  • Esley M. HeizerJr.
  • Robert V. Miller
  • Travis E. Doom
  • Michael L. Raymer
  • Dan E. Krane


Metabolic efficiency, as a selective force shaping proteomes, has been shown to exist in Escherichia coli and Bacillus subtilis and in a small number of organisms with photoautotrophic and thermophilic lifestyles. Earlier attempts at larger-scale analyses have utilized proxies (such as molecular weight) for biosynthetic cost, and did not consider lifestyle or auxotrophy. This study extends the analysis to all currently sequenced microbial organisms that are amenable to these analyses while utilizing lifestyle specific amino acid biosynthesis pathways (where possible) to determine protein production costs and compensating for auxotrophy. The tendency for highly expressed proteins (with adherence to codon usage bias as a proxy for expressivity) to utilize less biosynthetically expensive amino acids is taken as evidence of cost selection. A comprehensive analysis of sequenced genomes to identify those that exhibit strong translational efficiency bias (389 out of 1,700 sequenced organisms) is also presented.


Metabolic efficiency Codon usage bias Biosynthesis pathways Auxotrophy Translational efficiency 

Supplementary material

239_2012_9500_MOESM1_ESM.csv (1 kb)
aerHetSlopeVsCst (CSV 1 kb)
239_2012_9500_MOESM2_ESM.csv (1 kb)
aerPhotSlopeVsCst (CSV 1 kb)
239_2012_9500_MOESM3_ESM.csv (1 kb)
aGlucoseSlopeVsCst (CSV 1 kb)
239_2012_9500_MOESM4_ESM.tsv (279 kb)
allOrgs (TSV 279 kb)
239_2012_9500_MOESM5_ESM.csv (1 kb)
anaerHetSlopeVsCst (CSV 1 kb)
239_2012_9500_MOESM6_ESM.csv (11 kb)
auxAAquintileDifferentialUsage (CSV 12 kb)
239_2012_9500_MOESM7_ESM.csv (227 kb)
phylo (CSV 227 kb)
239_2012_9500_MOESM8_ESM.csv (201 kb)
slopesAAusage (CSV 201 kb)
239_2012_9500_MOESM9_ESM.csv (20 kb)
strongTE (CSV 21 kb)
239_2012_9500_MOESM10_ESM.csv (1 kb)
weightSlopeVsCst (CSV 1 kb)


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Douglas W. Raiford
    • 1
  • Esley M. HeizerJr.
    • 2
  • Robert V. Miller
    • 3
  • Travis E. Doom
    • 4
  • Michael L. Raymer
    • 4
  • Dan E. Krane
    • 5
  1. 1.Department of Computer ScienceUniversity of MontanaMissoulaUSA
  2. 2.The Genome InstituteWashington UniversitySt LouisUSA
  3. 3.Department of Microbiology and Molecular GeneticsOklahoma State UniversityStillwaterUSA
  4. 4.Department of Computer ScienceWright State UniversityStillwaterUSA
  5. 5.Department of Biological SciencesWright State UniversityDaytonUSA

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