Metabolic economics and bacterial proteome evolution
Natural selection is thought to act upon protein structures
to optimize biochemical properties (activity, stability, and specificity) related
to their specific cellular function. Selection pressures related to efficient
synthesis, rather than proper function, of proteins may act globally on the
amino acid composition of the proteome, but are less firmly established.
A substantial fraction of the energy
budget of bacteria is devoted to biosynthesis of amino acids, the building blocks
of proteins. The fueling reactions of central metabolism provide precursor metabolites
for synthesis of the 20 amino acids incorporated into proteins. Thus, synthesis
of an amino acid entails a dual cost; energy is lost by diverting chemical intermediates
from fueling reactions and additional energy is required to convert precursor
metabolites to amino acids. The range of costs of biosynthesis vary from 11
ATP equivalents per molecule of Glycine, Alanine, and Serine to over 70 ATP
per molecule of Tryptophan.
| Figure 1. Fueling reactions and amino acid biosynthetic pathways in E. coli | Fueling reactions and amino acid biosynthetic pathways are shown as black and blue arrows, respectively. The major anapleurotic pathway, which replenishes oaa in the TCA cycle, is shown in yellow. |
If energy is limiting to survival or
reproduction, then the amino acid composition of proteins encoded in the genome
should be biased toward less energetically costly molecules. The extent to which
amino acid composition is biased to reduce metabolic costs should be a positive
function of gene expression levels, or the numbers of proteins synthesized from
each gene. Figure 2 shows striking correlations between average costs of biosynthesis
and major codon usage (a proxy for gene expression levels) in the genomes of
E. coli and B. subtilis. Such correlations exist within functional categories
of proteins and within groups of exchangeable amino acids, suggesting that the
primary structures of proteins reflect natural selection for efficient biosynthesis
as well as proper function.
| Figure 2 Correlations between energetic costs and major codon usage in B. subtilis and E. coli genes |
| (A) and (B) plot the average cost per amino acid and average MCU for bins of genes from the B. subtilis and E. coli genomes, respectively. Genes were ranked by MCU and data were pooled from low to high MCU values until 50,000 codons was reached for each bin. 95% confidence intervals on the estimates of mean costs are shown. |
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