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Amino Acid metabolism conflicts with protein diversity.

Krick T, Verstraete N, Alonso LG, Shub DA, Ferreiro DU, Shub M, Sánchez IE - Mol. Biol. Evol. (2014)

Bottom Line: The 20 protein-coding amino acids are found in proteomes with different relative abundances.More than 100 organisms reach comparable solutions to the trade-off by different combinations of proteome cost and sequence diversity.Quantifying the interplay between proteome size and entropy shows that proteomes can get optimally large and diverse.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Matemática, Facultad de Ciencias Exactas y Naturales and IMAS-CONICET, Universidad de Buenos Aires, Buenos Aires, Argentina.

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Trade-off between amino acid metabolic cost and proteome sequence diversity. (A) Genomic GC content dependence of the average metabolic cost per amino acid. (B) Genomic GC content dependence of the proteome entropy. (C) Genomic GC content dependence of the target function f. (D) Trade-off between amino acid metabolic cost (x axis) and proteome sequence diversity measured as entropy (y axis). The contour lines indicate the value for the target function, and the triangles correspond to the trade-off model using the values of m for DS1 and DS2 from figure 1B and E. All panels display the 107 organisms in data set DS1 (white symbols), the 17 organisms in data set DS2 (black symbols), and the genetic code model (red symbols). (D) includes genomic GC contents between 0.15 (lower right corner) and 0.75 (lower left corner). The y axis legend to the right of (B) and (D) illustrates the number of probable peptide chains of length 100 given by , where h is the entropy (Shannon 1948; Shannon and Weaver 1949).
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msu228-F3: Trade-off between amino acid metabolic cost and proteome sequence diversity. (A) Genomic GC content dependence of the average metabolic cost per amino acid. (B) Genomic GC content dependence of the proteome entropy. (C) Genomic GC content dependence of the target function f. (D) Trade-off between amino acid metabolic cost (x axis) and proteome sequence diversity measured as entropy (y axis). The contour lines indicate the value for the target function, and the triangles correspond to the trade-off model using the values of m for DS1 and DS2 from figure 1B and E. All panels display the 107 organisms in data set DS1 (white symbols), the 17 organisms in data set DS2 (black symbols), and the genetic code model (red symbols). (D) includes genomic GC contents between 0.15 (lower right corner) and 0.75 (lower left corner). The y axis legend to the right of (B) and (D) illustrates the number of probable peptide chains of length 100 given by , where h is the entropy (Shannon 1948; Shannon and Weaver 1949).

Mentions: We postulate a model in which living organisms maximize a target function f that equals the entropy of the amino acid distribution in the proteome h minus the average metabolic cost of an amino acid . This gives rise to a trade-off between both terms. Figure 3 displays this trade-off for all organisms in DS1 (white symbols) and DS2 (black symbols). The figure also shows the expectation for the genetic code model (red symbols); figure 3A shows that most natural proteomes present lower metabolic costs than the genetic code model. Similarly, the entropies of natural proteomes are in the same order as the genetic code model or higher (fig. 3B). Finally, the target function f takes higher values in most natural proteomes than in the genetic code model (fig. 3C).Fig. 3.


Amino Acid metabolism conflicts with protein diversity.

Krick T, Verstraete N, Alonso LG, Shub DA, Ferreiro DU, Shub M, Sánchez IE - Mol. Biol. Evol. (2014)

Trade-off between amino acid metabolic cost and proteome sequence diversity. (A) Genomic GC content dependence of the average metabolic cost per amino acid. (B) Genomic GC content dependence of the proteome entropy. (C) Genomic GC content dependence of the target function f. (D) Trade-off between amino acid metabolic cost (x axis) and proteome sequence diversity measured as entropy (y axis). The contour lines indicate the value for the target function, and the triangles correspond to the trade-off model using the values of m for DS1 and DS2 from figure 1B and E. All panels display the 107 organisms in data set DS1 (white symbols), the 17 organisms in data set DS2 (black symbols), and the genetic code model (red symbols). (D) includes genomic GC contents between 0.15 (lower right corner) and 0.75 (lower left corner). The y axis legend to the right of (B) and (D) illustrates the number of probable peptide chains of length 100 given by , where h is the entropy (Shannon 1948; Shannon and Weaver 1949).
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msu228-F3: Trade-off between amino acid metabolic cost and proteome sequence diversity. (A) Genomic GC content dependence of the average metabolic cost per amino acid. (B) Genomic GC content dependence of the proteome entropy. (C) Genomic GC content dependence of the target function f. (D) Trade-off between amino acid metabolic cost (x axis) and proteome sequence diversity measured as entropy (y axis). The contour lines indicate the value for the target function, and the triangles correspond to the trade-off model using the values of m for DS1 and DS2 from figure 1B and E. All panels display the 107 organisms in data set DS1 (white symbols), the 17 organisms in data set DS2 (black symbols), and the genetic code model (red symbols). (D) includes genomic GC contents between 0.15 (lower right corner) and 0.75 (lower left corner). The y axis legend to the right of (B) and (D) illustrates the number of probable peptide chains of length 100 given by , where h is the entropy (Shannon 1948; Shannon and Weaver 1949).
Mentions: We postulate a model in which living organisms maximize a target function f that equals the entropy of the amino acid distribution in the proteome h minus the average metabolic cost of an amino acid . This gives rise to a trade-off between both terms. Figure 3 displays this trade-off for all organisms in DS1 (white symbols) and DS2 (black symbols). The figure also shows the expectation for the genetic code model (red symbols); figure 3A shows that most natural proteomes present lower metabolic costs than the genetic code model. Similarly, the entropies of natural proteomes are in the same order as the genetic code model or higher (fig. 3B). Finally, the target function f takes higher values in most natural proteomes than in the genetic code model (fig. 3C).Fig. 3.

Bottom Line: The 20 protein-coding amino acids are found in proteomes with different relative abundances.More than 100 organisms reach comparable solutions to the trade-off by different combinations of proteome cost and sequence diversity.Quantifying the interplay between proteome size and entropy shows that proteomes can get optimally large and diverse.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Matemática, Facultad de Ciencias Exactas y Naturales and IMAS-CONICET, Universidad de Buenos Aires, Buenos Aires, Argentina.

Show MeSH
Related in: MedlinePlus