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Protein-protein interfaces from cytochrome c oxidase I evolve faster than nonbinding surfaces, yet negative selection is the driving force.

Aledo JC, Valverde H, Ruíz-Camacho M, Morilla I, López FD - Genome Biol Evol (2014)

Bottom Line: Herein, using evolutionary data in combination with structural information of COX, we show that failing to discern the effects of interaction from other structural and functional effects can lead to deceptive conclusions such as the "optimizing hypothesis." Once spurious factors have been accounted for, data analysis shows that mtDNA-encoded residues engaged in contacts are, in general, more constrained than their noncontact counterparts.This differential behavior cannot be explained on the basis of predicted thermodynamic stability, as interactions between mtDNA-encoded subunits contribute more weakly to the complex stability than those interactions between subunits encoded by different genomes.Therefore, the higher conservation observed among mtDNA-encoded residues involved in intragenome interactions is likely due to factors other than structural stability.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Biología Molecular y Bioquímica, Facultad de Ciencias, Universidad de Málaga, Spain caledo@uma.es.

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Flowchart for the main methodological procedure adopted. Once sequence and structural data were collected, aligned codons were sorted into different subsets according to the criteria sketched in the figure. Afterwards, the indicated variables were assessed and diverse evolutionary tests were carried out using the package of programs PAML (details given in the text). ASA stands for accessible surface area. For each amino acid from a given subunit, the ASA was assessed in two different ways: 1) In the single subunit, isolated from the rest of the complex, and 2) when the subunit forms part of the complex. Thus, ΔASA = ASA1 − ASA2 ≥ 0 for any residue. Raw data and a script in R to analyze them are provided as supplementary material S3, Supplementary Material online.
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evu240-F1: Flowchart for the main methodological procedure adopted. Once sequence and structural data were collected, aligned codons were sorted into different subsets according to the criteria sketched in the figure. Afterwards, the indicated variables were assessed and diverse evolutionary tests were carried out using the package of programs PAML (details given in the text). ASA stands for accessible surface area. For each amino acid from a given subunit, the ASA was assessed in two different ways: 1) In the single subunit, isolated from the rest of the complex, and 2) when the subunit forms part of the complex. Thus, ΔASA = ASA1 − ASA2 ≥ 0 for any residue. Raw data and a script in R to analyze them are provided as supplementary material S3, Supplementary Material online.

Mentions: Using the sequence from Bos taurus as reference and the crystal structure of bovine COX (Protein Data Bank, PDB, 2OCC), each codon position from the above described alignments was sorted into different subsets according to the algorithm sketched in figure 1. Briefly, the data set corresponding to all the codons from the alignment of a given COX subunit (for instance, chain A, corresponding to COX I, which is a mtDNA-encoded subunit) was initially divided into two subsets: “Contact” and “Noncontact,” depending on whether the encoded amino acid from chain A is or not closer than 4 Å to a residue from any polypeptide other than chain A, respectively. The distance between two amino acids is given by the minimal distance between all pairs of heavy atoms from the two residues. Interacting positions were defined as being less than 4 Å apart because this is the upper limit for weak interactions (Martin et al. 1997). Afterwards, the Contact set was, in turn, split into two subsets: Intergenomic Contact (“Mt–nu Contact,” in the example) and Intragenomic Contact (“Mt–mt Contact,” in the example). The criterion to assign a given codon into the former subset was that the interacting residues should have been encoded by different genomes, otherwise the codon was allocated into the latter subset. On the other hand, the Noncontact set was split up into two subsets: “Exposed Noncontact” and “Buried Noncontact,” on the basis of solvent accessible surface areas of the considered residue (Aledo et al. 2012).Fig. 1.—


Protein-protein interfaces from cytochrome c oxidase I evolve faster than nonbinding surfaces, yet negative selection is the driving force.

Aledo JC, Valverde H, Ruíz-Camacho M, Morilla I, López FD - Genome Biol Evol (2014)

Flowchart for the main methodological procedure adopted. Once sequence and structural data were collected, aligned codons were sorted into different subsets according to the criteria sketched in the figure. Afterwards, the indicated variables were assessed and diverse evolutionary tests were carried out using the package of programs PAML (details given in the text). ASA stands for accessible surface area. For each amino acid from a given subunit, the ASA was assessed in two different ways: 1) In the single subunit, isolated from the rest of the complex, and 2) when the subunit forms part of the complex. Thus, ΔASA = ASA1 − ASA2 ≥ 0 for any residue. Raw data and a script in R to analyze them are provided as supplementary material S3, Supplementary Material online.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4255772&req=5

evu240-F1: Flowchart for the main methodological procedure adopted. Once sequence and structural data were collected, aligned codons were sorted into different subsets according to the criteria sketched in the figure. Afterwards, the indicated variables were assessed and diverse evolutionary tests were carried out using the package of programs PAML (details given in the text). ASA stands for accessible surface area. For each amino acid from a given subunit, the ASA was assessed in two different ways: 1) In the single subunit, isolated from the rest of the complex, and 2) when the subunit forms part of the complex. Thus, ΔASA = ASA1 − ASA2 ≥ 0 for any residue. Raw data and a script in R to analyze them are provided as supplementary material S3, Supplementary Material online.
Mentions: Using the sequence from Bos taurus as reference and the crystal structure of bovine COX (Protein Data Bank, PDB, 2OCC), each codon position from the above described alignments was sorted into different subsets according to the algorithm sketched in figure 1. Briefly, the data set corresponding to all the codons from the alignment of a given COX subunit (for instance, chain A, corresponding to COX I, which is a mtDNA-encoded subunit) was initially divided into two subsets: “Contact” and “Noncontact,” depending on whether the encoded amino acid from chain A is or not closer than 4 Å to a residue from any polypeptide other than chain A, respectively. The distance between two amino acids is given by the minimal distance between all pairs of heavy atoms from the two residues. Interacting positions were defined as being less than 4 Å apart because this is the upper limit for weak interactions (Martin et al. 1997). Afterwards, the Contact set was, in turn, split into two subsets: Intergenomic Contact (“Mt–nu Contact,” in the example) and Intragenomic Contact (“Mt–mt Contact,” in the example). The criterion to assign a given codon into the former subset was that the interacting residues should have been encoded by different genomes, otherwise the codon was allocated into the latter subset. On the other hand, the Noncontact set was split up into two subsets: “Exposed Noncontact” and “Buried Noncontact,” on the basis of solvent accessible surface areas of the considered residue (Aledo et al. 2012).Fig. 1.—

Bottom Line: Herein, using evolutionary data in combination with structural information of COX, we show that failing to discern the effects of interaction from other structural and functional effects can lead to deceptive conclusions such as the "optimizing hypothesis." Once spurious factors have been accounted for, data analysis shows that mtDNA-encoded residues engaged in contacts are, in general, more constrained than their noncontact counterparts.This differential behavior cannot be explained on the basis of predicted thermodynamic stability, as interactions between mtDNA-encoded subunits contribute more weakly to the complex stability than those interactions between subunits encoded by different genomes.Therefore, the higher conservation observed among mtDNA-encoded residues involved in intragenome interactions is likely due to factors other than structural stability.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Biología Molecular y Bioquímica, Facultad de Ciencias, Universidad de Málaga, Spain caledo@uma.es.

Show MeSH