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Many bivalve species have two types of mitochondrial DNA passed independently through the female line (F genome) and male line (M genome). Here we study the cytochrome oxidase I protein in such bivalve species and provide evidence for differences between the F and M proteins in amino acid property values, particularly relating to hydrophobicity and helicity. The magnitude of these differences varies between different regions of the protein and the change from the ancestor is most marked in the M protein. The observed changes occur in parallel and in the same direction in the different species studied. Two possible causes are considered, first relaxation of purifying selection with drift and second positive selection. These may operate in different ways in different regions of the protein. Many different amino acid substitutions contribute in a small way to the observed variation, but substitutions involving alanine and serine have a quantitatively large effect. Some of these substitutions are potential targets for phosphorylation and some are close to residues of functional importance in the catalytic mechanism. We propose that the observed changes in the F and M proteins might contribute to functional differences between them relating to ATP production and mitochondrial membrane potential with implications for sperm function.
Animal mitochondrial DNA (mtDNA) shows considerable diversity, including variation in size, structure, and gene content, which might have adaptive significance (Breton et al. 2014). Many species of bivalves have two types of mitochondria, one passed through the female line of descent (F type) and the other through the male line (M type) (Skibinski et al. 1994; Zouros et al. 1994). In this system (doubly uniparental inheritance [DUI]), females pass the F type to the progeny of both sexes, whereas males pass the M type to sons only. Females have F type mitochondria in both soma and germ line, whereas in males the germ line is homoplasmic for the M type with somatic tissues showing varying levels of heteroplasmy (Zouros 2013). There is ongoing research into the evolutionary and functional significance of the two genomes and their link with sex determination (Breton, Stewart, et al. 2011; Zouros 2013). Of potential relevance is that the F and M genomes show a variety of sequence differences. They can be highly diverged, exceeding 50% in some freshwater mussels and often show major structural differences and rearrangements (Ghiselli et al. 2013; Zouros 2013; Breton et al. 2014). Moreover, M and F type specific mtORFans of putative viral origin and with a proposed role in DUI have been discovered (Breton, Ghiselli, et al. 2011; Ghiselli et al. 2013; Milani et al. 2013). Sequence differences between M and F genomes located in the intergenic regions and in the RNA-coding genes can affect mtDNA transcription and translation, potentially resulting in sex-specific mitochondrial expression, especially in conditions where the two mtDNAs are in homoplasmy, namely, in gonads and gametes (Milani et al. 2014).
Although major structural differences between the F and M genomes may be biologically important, functional differences could also be sought in normal sequence variation in mitochondrial proteins. Amino acid substitution is influenced by a variety of structural and functional constraints (Chelliah et al. 2004). These relate to the physicochemical properties of amino acids and are consistent with evidence that substitutions within chemical groups (conservative) are more prevalent than those between groups (radical) (Hughes et al. 1990). The latter are more likely to have deleterious effects on structure and function and be removed by purifying selection (Zhang 2000). Information on protein structure and amino acid properties can augment DNA and protein sequence information in evolutionary studies in a variety of ways. Evolutionary trees built from atomic distances in superimposed known protein tertiary structures can be compared with those built from aligned sequences (Johnson et al. 1990; Balaji and Srinivasan 2007). Amino acid substitution tables can be built from different structural environments, for example, solvent accessible and inaccessible regions within proteins of known tertiary structure, and be used for constructing refined and better supported evolutionary trees (Overington et al. 1990; Thorne et al. 1996; Gong and Blundell 2008). In addition, if the tertiary structure is known for one of the sequences in an amino acid alignment it can be used to infer the structural environments for the other sequences (e.g., Mizuguchi et al. 1998; Melvin et al. 2008; Puslednik et al. 2012).
The chemical and physical properties of amino acids can also be used to improve evolutionary models for a variety of purposes (e.g., Koshi and Goldstein 1997; Xia and Li 1998; Liu and Wang 2006), for example, to define patches with functional regions on the surface of proteins (Pettit et al. 2007). Metrics, obtained by substituting amino acid physicochemical property values for the nominal amino acid symbols, can be summed up over the different amino acids within a region of a protein (McClellan and McCracken 2001; Atchley et al. 2005; McClellan 2013). This can aid the identification of causal components underlying the sequence variation in different regions of the protein by using approaches based on analysis of variance (ANOVA) to partition the variation (Atchley et al. 2005).
The aim of this study is to compare the structural features and differences in amino acid property values in the cytochrome oxidase I (COI) protein from the F and M mtDNA genomes. This protein is responsible for the transfer of electrons from cytochrome c to reduce molecular oxygen to water and is the final step in the electron transport chain. In the reaction, eight protons come from the mitochondrial matrix, four of which make water and four protons are released into the intermembrane space. This results in an electrochemical gradient across the membrane, which ATP synthase uses to make ATP (Chen 1988). COI is widely studied both in relation to the action of natural selection (Garvin et al. 2015) and in taxonomic studies (Hebert et al. 2003), and its mechanism of action is well understood (e.g., Tsukihara et al. 2003), though some details are not completely elucidated (Popovic 2013). We provide evidence that the F and M COI proteins show differences in the values of amino acid properties in relation to structural environment, which are concordant in four bivalve species with DUI. The differences include changes in hydrophobicity and helicity in the intermembrane space and mitochondrial matrix regions of the M protein. We suggest that these changes may affect ATP production and the mitochondrial membrane potential with consequent effects on sperm function and implications for DUI and discuss the evolutionary forces that might be responsible.
To select representative sequences for analysis, 44 bivalve F and M COI amino acid sequences were aligned and a maximum likelihood (ML) tree constructed (supplementary fig. S1, Supplementary Material online). Four species each with F and M genomes were chosen within each of the three orders, Mytiloida, Veneroida, and Unionoida. No part of the lineages separating the F and M COI sequences through their common ancestor within each of the chosen species overlaps with the corresponding lineages separating F and M genomes in the other species. In other words, the F and M genomes form monophyletic groups within each species (fig. 1A). This approach allows statistically independent comparisons of the F and M genomes in line with a proposal for the comparative method (Felsenstein 1985). Sequences from the Mytilus edulis group (M. edulis, M. trossulus, and M. galloprovincialis) were not chosen because of the complication of role reversals and rearrangements (Zouros 2013), Mytilus californianus was chosen instead. Musculista senhousia was added as a fourth species because it also satisfies the above criterion of nonoverlapping lineages, and the F and M COI sequences are sufficiently diverged to merit inclusion. The eight sequences used in analysis with NCBI accession numbers are M. californianus (Cal) (F: ACV65353 M: ACV65365), M. senhousia (Sen) (F: ACY00212 M: ACY00224), Pyganodon grandis (Gra) (F: ACQ91058 M: ACQ91071), and Ruditapes philippinarum (Phi) (F: BAB83795 M: BAB83782).
The eight bivalve sequences were aligned with a sequence from a known bovine structure (PDB ID: 1V54, Tsukihara et al. 2003) using T-coffee (Notredame et al. 2000). Terminal regions and a few internal sites with gaps were removed from the alignment. The terminal regions comprise on average 22 amino acids per sequence and are similar in length and amino acid sequence between genomes within species. The resulting alignment is 501 amino acid sites long, 13 sites less than the number of amino acids in 1V54 COI. To reconstruct predicted ancestral sequences of the F and M COI sequences within each species, the alignment without gaps was submitted to the FASTML server, which implements ML algorithms for this purpose (Ashkenazy et al. 2012).
Residue-specific and site-specific attributes are used for the comparative analysis of the F and M COI proteins. In the alignment of the eight bivalve sequences used, there are 8 × 501=4,008 individual amino acid residues to which residue-specific attributes can be assigned, and 501 alignment sites to which site-specific attributes can be assigned.
The residue-specific attributes are chemical and physical amino acid property values for the 20 amino acids, derived from several studies, which capture information about the amino acid in a metric value (Sneath 1966; Grantham 1974; Kidera et al. 1985; Haig and Hurst 1991; Xia and Li 1998; Atchley et al. 2005). We have given abbreviated names to these properties, which with brief description in brackets are cc (side chain composition), pp (polarity), vv (volume), arom (aromaticity), Atch1 (polarity), Atch2 (secondary structure), Atch3 (volume), Atch4 (amino acid composition), Atch5 (charge), Kid1 (bulk), Kid2, Kid3, Kid4 (hydrophobicity), Kid5, Kid6 (beta structure preference), Kid7 (alpha helix preference), Kid8, Kid9 (bend structure preference), HH1 (polarity), HH2 (hydropathy), and HH3 (isoelectric point). Further information on the properties is given in supplementary table S1, Supplementary Material online. A high value on the metric scale would indicate a tendency toward the specified description. Thus for vv (volume), tryptophan, a bulky amino acid has the highest value whereas glycine has the lowest value. Clustering of these 21 properties (fig. 1B) broadly reflects differences and similarities described in the cited studies. Many of the properties are derived by factor analysis and thus represent a combination of many individual physicochemical properties. Correlation and coefficient of determination values among the properties are given in supplementary table S2, Supplementary Material online. Most of the values of coefficient of determination are less than 0.5, suggesting some but not necessarily high redundancy between the properties.
To assign the site-specific attributes, the bivalve protein sequences are partitioned into different spatial regions called “structural environments,” which a priori are expected to reflect functional differences. Because the structures of the bivalve proteins are unknown, structural environment was estimated for COI using the known bovine structure 1V54. The program JOY (Mizuguchi et al. 1998) was used for this purpose, partitioning COI into categories for 11 structural environments. For illustration, consider an environment relating to main chain to main chain hydrogen bonding. Using a known or estimated protein structure, JOY would classify each amino residue as belonging to category “True” if it participated in such bonding and category “False” if it did not. We have given abbreviated names to these JOY environments, which with brief description in brackets are SecStrucPhi (secondary structure and phi angle), SolAcc (solvent accessibility), HmainCO (hydrogen bond from side chain to main chain CO group), HmainNH (hydrogen bond from side chain to main chain NH group), Hotherhet (hydrogen bond to nonstandard residue), Hhet (hydrogen bond to nonstandard residue), covhet (covalent bond to nonstandard residue), Hmamide (main chain to main chain hydrogen bond involving NH of specified residue), HmCO (main chain to main chain hydrogen bond involving CO of specified residue), DSSP (secondary structure using DSSP algorithm), and PosPhi (positive phi angle). The environment categories for SecStrucPhi and DSSP refer to participation in different types of secondary structure such as helix or coil. Further information on the environments is given in supplementary table S1, Supplementary Material online.
The COI protein was additionally partitioned into categories based on four environments, which potentially relate to selective constraint and purifying selection. The first of these is total amino acid diversity per site in the sample of eight sequences. The second and third relate to evolutionary conservation values derived using the programs ConSurf (Celniker et al. 2013) and FuncPatch (Huang and Golding 2015). As an exploratory approach, root mean square distance values for atomic distances within superimposed COI structures including 1V54 were also calculated as the fourth constraint environment (see supplementary methods S1, Supplementary Material online), on the basis that higher constraint may be related to lower molecular distances in the superimposed structures. Contrasting categories based on these environments did not reveal the significant differences that are reported below for the JOY structural environments and are not considered further. A dendrogram showing clustering of the JOY structural environments, based on the category assignments for all sites over the 501 sites of 1V54 that align with the bivalve sequences, is given in figure 1C, with correlation values between environments in supplementary table S3, Supplementary Material online. Some clustering is expected, for example, of SecStrucPhi and DSSP, which reflect secondary structure. The application of JOY revealed that 7 of the 11 structural environments gave only small numbers of sites differing between F and M COI proteins in one of the contrasting categories, and preliminary analysis was not informative and so these structural environments were excluded from further analysis. The remaining four structural environments, SecStrucPhi, SolAcc, Hmamide, and HmCO, are the focus of further investigation. As illustration of the spatial location of category regions, these are shown marked on an image of COI for three of these environments, Hmamide and HmCO in figure 2A and SolAcc in figure 2B. Hmamide and HmCO are combined as they have some overlapping sites with significant but not high correlation (supplementary table S3, Supplementary Material online). These three environments feature most prominently in the later analysis. The Hmamide and HmCO True category residues are located in a hydrophobic region within the membrane. The False category residues are located toward the aqueous intermembrane space and mitochondrial matrix. These hydrophilic regions have a greater number of side-chain oxygen and nitrogen atoms available for hydrogen bonding with other molecules as compared with the True category (fig. 2C). The SolAcc True residues are on the external parts of the protein, the False residues are buried. Confirmation that JOY is effective in generating categories having differences potentially reflecting structure and function was obtained by comparing the amino acid distributions between categories for the pooled data set of eight bivalve sequences (supplementary table S4, Supplementary Material online). Chi-square contingency analysis reveals highly significant differences in amino acid distribution between categories for the four environments tested.
Much of the analysis is based on the comparison of mean property values between the contrasting categories of the different structural environments. To facilitate this approach, the difference in property values between F and M COI proteins (F−M) was calculated for each species for each alignment site. Use of F−M corrects for variation between sites analogous to the approach in a paired t-test. A simple example of the calculation of F−M is given in figure 1D for a small made-up data set for aligned F and M sequences. The figure also shows the computation of the quantity False–True, the difference between categories, which is used in further calculations as described below. A diagrammatic representation of F−M for two categories for an environment is illustrated in figure 1E. In the example shown, F−M is positive for category False (F>M) and negative for category True (F<M). The values of F−M are also broken down into the deviations from the ancestors derived from FASTML. In different subsequent analyses, the averaging of F−M over sites is done in two ways, first over the 281 sites that differ between the F and M proteins, and second over all the 2,004 sites in the alignment for which the F and M proteins can be compared (4 species × 501 sites=2,004). The first method gives a mean value for only those sites that are variable, which may be more pertinent if many of the sites within a category region are invariant, the second for the entire physical region of a category.
The alignment of the eight sequences used for analysis is 501 sites long. Around 291 sites show variation, that is having at least two different amino acids in the alignment of eight sequences. The numbers of sites in which COI sequences differ between F and M genomes within species for 1, 2, 3, or all 4 species are respectively 135, 56, 10, and 1. Multiplying these vectors and summing gives 281 sites differing between genomes within species out of 291 × 4=1,164, a proportion of 0.24. Because each amino acid residue can be substituted by property values, a three-way ANOVA can be used to gauge the relative overall effect of the factors, genome, species, and environment. Mean partial eta squared values, the percentage of the total variation in the dependent variable attributable to a specified independent variable, over all properties and environments are given in table 1. The error is large because it reflects amino acid differences between sites. All factors have small effect as judged by the value of partial eta squared (%), and that for genome is smaller than that for species and environment. More optimistically, the genome effect is about 6% of the species value, and the interaction of genome and species is also higher, suggesting that the genome effect may in part be species dependent.
The difference in property values between the F and M COI proteins was first examined over the entire protein alignment. Confidence intervals (CIs) of F−M were computed for the 281 site and 2,004 site data sets. For all 21 properties, the CIs overlap zero for both data sets (supplementary table S5, Supplementary Material online), and the means over properties are −0.181 (95% CI −0.549, 0.188) and −0.025 (95% CI −0.078, 0.027), respectively. The second data set has lower absolute mean values because it includes many sites where F−M=0 and has narrower CIs because the sample size is greater. These results suggest no difference between the F and M COI proteins in property values over the whole COI protein. However, this averaging may hide differences in the value of F−M between the categories of structural environments.
Further analysis thus focused on comparing the value of F−M between different regions of the protein, that is, between the True and False categories for the different structural environments (see fig. 1D for illustration of computation of F−M, and fig. 1E for further clarification). For each property for each environment, the value of F−M was compared between categories averaging over all the alignment sites within categories and using either ANOVA or the nonparametric Kruskal–Wallis test. The resulting P-values for each amino acid property were then combined over environments using Fisher’s combining probabilities test (table 2 with further details in supplementary table S6, Supplementary Material online). The properties that have significant P-values in table 2 are retained for further analysis. Some of these are combined into groups that reflect the closeness of their clustering (fig. 1B). The groups are named Group A (comprising Kid8, Kid9, Atch2, and cc), Group B (Kid3, Kid4, Kid5, and HH2), and Group C (pp, Atch1, and HH1). In subsequent analyses, mean values for Groups A, B, and C are obtained by averaging over properties within groups. Properties with nonsignificant P-values in table 2 are not considered further.
Concordant and parallel changes between the F and M proteins across species would provide evidence of a general rather than species-specific evolutionary effect. To test for this, the mean values of F−M for the retained properties were calculated for the categories for each environment, separately for each of the four species. These F−M values were then compared between categories across the four species using a paired t-test. An example to illustrate the concordant differences between False and True across species is given in table 3 for the environment HmCO and the Group A and Group B properties. For the Group A property values, the mean F−M is higher for category False than True. A similar pattern occurs for Group B with True higher than False, though one of the species (Sen) is different for Kid4 and Kid5. The corresponding values for all properties and environment categories are given in supplementary table S7, Supplementary Material online, and the P-values from all the paired t-tests in supplementary table S8, Supplementary Material online. The structural environment SecStrucPhi does not show as good concordance or as many low P-values as SolAcc, Hmamide, and HmCO and is excluded from further consideration. The values of False–True are plotted for SolAcc, Hmamide, and HmCO in figure 3A from which the concordance between the four species is clearly evident.
Summary mean values of F−M for the False and True categories are given in table 4A with a further statistical interpretation in table 5. Of the 15 mean values for False in table 4A, 9 are significantly different from zero (bold and underlined in table 4A). None of the True values are significant. For eight of these significant values, all four species are concordant with the same sign for the difference between F−M for False and for True (indicated by a “4” in the concordance rows). For Hmamide and HmCO that show a similar pattern of variation, for all 10 paired False and True mean values, the absolute value of False is >True (row b, table 5). SolAcc does not show this effect so clearly (row a). In 12 of the 15 paired False and True mean values, the sign of the mean is different (row c). This suggests that a change in evolution that makes F>M in one category is accompanied by an opposite change making M>F in the other category consistent with the absence of a difference between F and M over the protein as a whole (see above and supplementary table S5, Supplementary Material online).
The value of F−M has also been broken down into deviation from the ancestor (shown as D=F−A and D=M−A in fig. 1E). In this illustration, the ancestor is positioned between F and M though it is also possible in evolution for the ancestor to have the most extreme value. The values of D are given in table 4A with statistical interpretation in table 5. The absolute value of M−A is more often greater than F−A particularly for category False (rows d and f, table 5). The signs of F−A and M−A are more often different within categories (rows e and g). For Hmamide and HmCO the absolute value of F−A (or M−A) is more often greater for False than True (rows i and l, table 5). SolAcc does not show this effect so clearly (rows h and k). There is more often a difference in sign for F−A between False and True (row j) and also for M−A (row m) consistent with the absence of a difference between F and M over the protein as a whole (supplementary table S5, Supplementary Material online). Finally, the table 5 data can be broken down into 15 2 × 2 tables for each property and environment combination. The cell with the highest absolute value is recorded and summed over tables (row n). The False and (M−A) cell has highest value in 11 of the 15 tables.
The (F−A) and (M−A) values in table 4A are the means over four species. A multiway ANOVA with sources of variation Property (5 classes), Environment (3), Category (2), Genome (2), and Species (4) on the absolute values was carried out. Genome and Category are both highly significant (P=0.000) as is Genome × Category (P=0.007) consistent with the analysis from table 5. No significant result is obtained in the corresponding ANOVA of the real values, again consistent with observations of different signs (table 5). Values of deviation from the ancestor for F and M proteins and for False and True categories are illustrated in figure 3B and confirm that the observed trends are consistent across species.
For a physicochemical interpretation of the values of F−M, it is necessary to establish the meaning of high and low values on the amino acid property scales. This has been done using the interpretation of the scales made by the authors who devised them (supplementary table S1, Supplementary Material online), supplemented by two other classification systems (from Taylor 1986 and Malkov et al. 2008) and also taking into consideration the amino acid chemical groups. The amino acids are sorted according to the property values from high to low values and lined up with these classification systems (supplementary table S9, Supplementary Material online). This allows a summary headline classification to be assigned to high or low property values. Whichever of the F or M COI proteins has the higher property value as judged by the F−M mean value in table 4A is assigned as best match to the headline classification as shown in table 4B. The entries in table 4B give a consistent picture showing greater helicity and hydrophobicity (or nonpolarity) for the M protein in external residues or those in the matrix or intermembrane space (Hmamide and HmCO False, and SolAcc True). By contrast the F protein shows greater helicity for buried residues (SolAcc False). To get an overall picture of hydrophobicity and helicity in the categories prior to divergence of F and M proteins, the mean property values over all residues were calculated for the ancestral sequences at the sites, which differ between F and M (table 4C). The buried residues (SolAcc False, and Hmamide and HmCO True) have greater helicity and hydrophobicity as expected, compared with the alternative categories representing external residues or those in the matrix or intermembrane space.
A summary of the more marked changes in the F and M proteins from table 4 are mapped onto a diagram of COI (fig. 4). Of general significance is that the changes in the M protein, which tend to be larger (see also fig. 3BI), are in a direction to minimize the difference between the categories. Thus, for Hmamide and HmCO, the M protein has a higher hydrophobicity change in the False category (fig. 4B), which is the more hydrophilic part of the protein. The F protein shows a smaller change in the opposite direction. All the five directional changes in the M protein and the four directional changes in the F protein in figure 4 show this same tendency, which is that M changes toward the mean of the two categories, whereas F changes to increase the difference between the two categories.
To gauge the influence of individual amino acids on variation in F−M, the mean category values have been partitioned into separate contributions from each amino acid. The F−M values associated with individual amino acids in the F and M sequences are summed for each amino acid over all sites in the F sequence and separately over all sites in the M sequence. The absolute values of the F−M are also summed over all amino acids. The individual amino acid contributions are then computed by dividing the sum for each amino acid by the overall sum of absolute values. A demonstration of the method is given in supplementary table S10A, Supplementary Material online, using the made-up data set of figure 1D. In the interpretation, focus is on those values which are large and have the same sign as the overall F−M value thus contributing to the excess of F over M or vice-versa. A summary of the results of this analysis is given in figure 5 where amino acids with high contributions are indicated, with the underlying data analysis in supplementary table S10B, Supplementary Material online. A high contribution in absolute terms will be favored when the amino acid has a high value on the amino acid property scale and when it has a high frequency, and will also be a function of the specific pairings of amino acids at sites in the alignment.
Amino acids showing the most marked contributions are the aliphatic amino acids (G, A, V, L, I) and the aliphatic hydroxyl amino acid serine (S). Contingency tests for association were carried out to compare the amino acid frequency distributions of F and M given in figure 5 (further details in supplementary table S10B, Supplementary Material online). Some significant results were obtained for individual amino acids: SolAcc False (alanine A, P=0.031), Hmamide True (A, P=0.028), HmCO True (A, P=0.023, serine S, P=0.042), and for the entire contingency table for True (P=0.029). The analysis of figure 5 was extended by calculating the contributions for precise F with M amino acid pairings in the alignment, of which there are 96 (supplementary table S10C, Supplementary Material online). Contributions of more than 10% are flagged in supplementary table S10C, Supplementary Material online, and these are AS (i.e., A in F protein and S in M protein), for SolAcc False Groups A, B, and Kid7 and for Hmamide and HmCO True Group A and Kid7, and AG for SolAcc False Group A. Thus, all these analyses support the conclusion that alanine (A) and serine (S) make a relatively large contribution to the difference between F and M proteins compared with other amino acids, particularly when S is in the M protein. However, in quantitative terms other amino acids make a larger contribution when summed overall.
The number of sequences available is unlikely to provide sufficient power for assessment of individual sites considered in isolation. Nevertheless, the four species-specific F−M values at each site were tested against the null hypothesis that F−M=0 using a paired t-test. Only one site generated an a priori P-value≤0.05. This underlines that combining data from different sites into a single metric, as in this study, provides greater power to detect differences between the F and M genomes. An analysis of the underlying DNA alignment gave nonsynonymous/synonymous ratios (Ka/Ks) between F and M within species ranging between 0.03 and 0.22, generally consistent with selective constraint and purifying selection acting on COI in the underlying DNA alignment. This may hide regions with positive selection, though the power to detect these will be limited given the number of sequences. A site by site analysis using HyPhy (Pond and Frost 2005) found no evidence of positive selection acting at individual sites. A further DNA analysis was carried out to test the hypothesis that the parallel changes in amino acid property values are caused by parallel changes in DNA base composition arising from mutational bias. For example, studies using mutation accumulation lines provided evidence for mtDNA mutational bias from G/C to A/T in Caenorhabditis elegans (Konrad et al. 2017) and an excess of nonsynonymous G to A mutations in Drosophila melanogaster (Haag-Liautard et al. 2008). The DNA base composition was analyzed in the codons for the 281 amino acid sites, which have an amino acid difference between F and M. The counts for A, C, G, T were compared in 4 × 2 tables between F and M within each species and between F and M within each environment category for SolAcc, Hmamide, and HmCO within each species. The count distributions appear similar for the F and M genomes and not a single a priori significant result at P≤0.05 was obtained out of 28 separate tests.
The numbers of radical amino acid changes between the F and M proteins were summed over the four species and over the nine properties of Taylor (1986). A total of 191 of the 501 sites show such radical differences between F and M in one or more species. These are mapped onto a view of the 1V54 structure in figure 2D. Sites showing radical amino acid differences are scattered throughout the protein, consistent with the evidence (previous section) that many amino acids contribute to the category differences.
In a study of Drosophila cytochrome oxidase, which also took advantage of the known bovine structure, Melvin et al. (2008) used alteration of physical and chemical properties or change in a contact site with another subunit as evidence of a likely change in cytochrome oxidase activity. Six of nine observed amino acid mutations were concluded to have potentially changed activity. By this approach, some of the many radical amino acid differences observed here between the F and M COI proteins may be of functional significance. A classification of the residues in 1V54 was made using information derived from its NCBI entry taking account of the study of Tsukihara et al. (2003). This identifies residues functionally important in the catalytic mechanism, as well as mtDNA-encoded subunit interface residues (i.e., COI with COII and COIII) and COI with nuclear DNA–encoded subunit interfaces.
Subunit interface residues are mapped onto 1V54 in figure 2E. Seventy-one out of 76 interface sites occur near the surface of the protein, and of these 30 showed radical amino acid differences. The three mitochondrial coded subunits play an important catalytic function in the complex. They are regulated by their own redox state (Allen 2015) as well as being regulated by the nuclear encoded subunits (Ludwig et al. 2001). Studies of Ka/Ks ratios may throw light on whether selection and constraint differ between different types of interfaces perhaps to optimize interactions between residues coded by the mtDNA and nuclear genomes, but a consistent picture has not yet emerged (Schmidt et al. 2001; Aledo et al. 2014). In this study, no consistent differences are found comparing F and M COI proteins in the value of Ka/Ks between mtDNA–mtDNA and mtDNA–nuclear DNA interfaces. Following the approach used for comparing between structural environment categories (table 4A), no significant differences were observed in F−M for property values for hydrophobicity or helicity between the two types of interface sites, or between interface and noninterface sites.
The functionally important residues are mapped onto 1V54 in figure 2F. For those F and M COI sites aligning with the residues functionally important in the catalytic mechanism of 1V54 (31 identified here), the Ka/Ks ratio between F and M is 0.004 indicating high conservation as expected of such sites. Twenty-three of these 31 are buried within the COI protein (SolAcc False), and of these only one showed an amino acid difference between F and M and then in only one species. The bivalve sequences as targets were also modelled on the 1V54 structure as template using Modeller (Sali and Blundell 1993; Webb and Sali 2014) and the models and 1V54 structure superimposed in Chimera (Pettersen et al. 2004; see supplementary methods S2, Supplementary Material online, for further information). This allows the calculation of the distances of specific residues in the bivalve models from functional residues in 1V54. Following the approach used for table 4A, no significant differences were observed in F−M for property values for hydrophobicity and helicity between bivalve model sites closer to and further away than either 2 or 4 Å from the 1V54 functionally important sites shown in figure 2F. Further focus was thus on the substitutions between alanine (A) and serine (S), which are found to play a relatively large quantitative role in the amino acid property differences between the F and M proteins (fig. 5). The 13 AS and 7 SA substitutions together with the functional important 1V54 residues alone are made visible in figure 2F. The substitutions are scattered throughout the protein but many are close to functional sites (e.g., within 5 Å). There is a preponderance of such substitutions within the more hydrophobic regions of the protein (SolAcc False, Hmamide/HmCO True). In silico analysis using the program NetPhos (Blom et al. 1999) suggested that 13 of the 20 substitutions had serine residues, which had potential to be phosphorylated with associated potential kinase binding sites.
The amino acid properties considered here differ significantly in value between the categories of structural environments representing different regions of the protein (table 2). For environments Hmamide and HmCO, the categories contrast the more hydrophilic regions associated with the matrix and intermembrane space (False) with the region within the membrane (True) (figs. 2A and 4). For SolAcc, the contrast is between external regions (True) and buried regions (False) (figs. 2B and 4). The calculated difference between F and M proteins (F−M) is frequently significantly different from zero in individual categories (table 4A), and the value of F−M itself differs between categories consistently across species (fig. 3A). When the property changes are broken down into deviations of F and M from the ancestor (M−A and F−A, fig. 1E), greater change in the absolute value is observed for the M protein and the category False (tables 4A and 5, fig. 3B). In addition, although some amino acids make a relatively large contribution to the variation (e.g., alanine and serine) many other amino acids have small individual effects but which sum to a large value overall (fig. 5 and supplementary table S10, Supplementary Material online).
Category differences are to a great extent concordant in the four species studied (fig. 3A, table 3, supplementary table S7, Supplementary Material online). The absolute values of False and True also differ concordantly (fig. 3BII–IV). The absolute value of deviation from the ancestor is also greater for the M than F COI protein in all four species (fig. 3BI). The concordant changes give confidence that there may be shared causes occurring in parallel in the four species. One possible shared parallel cause of faster evolution of the COI M protein could be a higher mutation rate in the M genome resulting from oxidative damage in sperm or a higher number of mitotic divisions in the male germ line (Zouros 2013). This is consistent with some evolutionary studies of F and M genome sequences in Mytilus (Quesada et al. 1998), though Stewart et al. (1996) found no evidence of faster synonymous substitution in the M genome.
The changes in hydrophobicity and helicity, particularly in the M protein (tables 4 and and5,5, fig. 4) can be considered from a functional viewpoint. In anthropoid primates, Schmidt et al. (2005) found relatively many charged to uncharged amino acid substitutions in COI at the cytochrome c binding site on the intermembrane side of the protein. It was proposed that these would increase hydrophobicity and affect electron transfer from cytochrome c to COI. It was further proposed that this might be an adaptive change to reduce and hinder OXPHOS activity and consequent free radical damage in the brain, which uses a relatively large amount of oxygen in the anthropoids. In a comparison of COI between marine and freshwater copepods, McClellan (2013) found 11 radical amino acid changes consistent with a decrease in hydrophobicity around the proton input channel and possibly a less energetically expensive route for proton transfer during adaptation to freshwater. By analogy to these studies, the changes in hydrophobicity and helicity in the M protein (fig. 4) might have functional consequences as a result of effects on the movement of protons, electrons, or water molecules or alteration of the mitochondrial membrane potential. This could in turn affect ATP production by ATP synthase. Sperm uses ATP for movement, the acrosome reaction, and a variety of metabolic functions (Visconti 2012). Thus, reduction in ATP output could have negative consequences for sperm carrying the M genome. In humans, there is evidence that mtDNA mutations reducing ATP production may cause reduced sperm motility (Ruiz-Pesini et al. 2000). Conversely higher ATP production might lead to increased swimming speed or endurance, which in turn may lead to higher chance of successful fertilization. Changes in helicity might also have impact on protein stability because of requirements associated with hydrogen bonding (Pace et al. 2014). Proteins can only tolerate small changes in conformation operating under conditions of marginal stability, which may be of advantage in evolution (Taverna and Goldstein 2002). However, because of the effects of stability loss in a structure that is already marginally stable, a large proportion of missense mutations in proteins are likely to affect function (Tokuriki and Tawfik 2009). Thus, the decrease in helicity in buried residues (fig. 4C, SolAcc False) may have consequences for M COI protein stability and thence function.
Relaxation of selective constraint and purifying selection with increased genetic drift and fixation of nearly neutral mutations (Ohta 1992) as the cause of the changes in amino acid property values in the M protein would be consistent with the observed directional changes in property values. The False and True categories (see fig. 2A and B) have ancestral physicochemical differences reflected in their overall property values (table 4C). The changes in the M protein tend to be such as to decrease these differences with a difference in sign of M−A for both the False and True categories (tables 4A and 5). For example, the regions of the M protein that are less hydrophobic in the ancestor evolve to become more hydrophobic, the less helical regions tend to become more helical, and the more helical regions tend to become less helical (fig. 4). Given that the maintenance of these differences is important for normal functioning, their erosion by fixation of nearly neutral mutations would be expected to affect function adversely, altering mitochondrial membrane potential and ATP production with consequent biological effects, for example, a reduction in sperm performance. Other studies also indicate faster evolution of the M genome as a result of lower functional constraint and less purifying selection (Stewart et al. 1996; Zouros 2013). A contributory factor may be a lower effective population size for the M than F genome, for example, due to a narrower bottleneck of mtDNA copy number in sperm (Stewart et al. 1996) compared with eggs. There is no evidence however that the M genome is nonfunctional. In sperm of R. philippinarum, one of the species used here, there is experimental evidence for the existence of membrane potential consistent with OXPHOS activity (Milani and Ghiselli 2015). The M genome is abundant in somatic tissues of R. philippinarum (Ghiselli et al. 2011) and transcriptionally active in male tissues (Milani et al. 2014). The M genome is also expressed in male but less so in female tissues of Mytilus species (Dalziel and Stewart 2002; Obata et al. 2011). It has been suggested that selective constraint may be lower in the M genome because it functions in fewer tissues (Stewart et al. 1996; Zouros 2013), but the relative influences of selective pressures in different tissues are unknown.
Given the importance of mitochondrial function in gonads and sperm of these broadcast spawning species (Ghiselli et al. 2013; Zouros 2013), parallel positive selection, for example, toward improved sperm performance through enhanced ATP production, can also be considered as a cause of the changes in amino acid property values. The associated high membrane potential could also be used as a signal for preferential partitioning of sperm-derived mitochondria into the primordial germ cells in males of DUI species (Milani 2015). However, in this study the Ka/Ks ratio is less than 1 for comparisons between F and M proteins and a site-specific analysis with HyPhy provides no evidence of positive selection. This is consistent with evidence of high conservation of the COI protein in general across eukaryotes (Pierron et al. 2012) and in bivalves specifically (Plazzi et al. 2016), though meta-analyses have revealed examples of positive selection in almost all mtDNA-encoded proteins (Garvin et al. 2015; James et al. 2016). Consideration could also be given to the possibility that the positive selection acts at linked regions in the mtDNA molecule (genetic draft or hitchhiking), which may be highly prevalent in mtDNA (Bazin et al. 2006). Such an explanation would require that positive selection in another mtDNA-encoded protein would cause the same parallel amino acid property changes between F and M COI proteins in all four of the studied species. In the F COI protein, the changes in property values away from the ancestral values tend to increase the difference between False and True categories. For example, for SolAcc the category False comprises buried residues in a highly helical region and the F protein shows an increase of helicity in this region (fig. 4C). The changes are small in magnitude, but are difficult to explain by relaxation of selection and drift, and are more in line with an adaptive change enhancing the function of the F protein. The difference in sign of F−M in the False and True categories (tables 4A and 5) is consistent with the absence of differences between the F and M protein overall (supplementary table S5, Supplementary Material online). This could reflect compensatory evolution (Ivankov et al. 2014) with stabilizing selection maintaining the overall F−M property value within a tolerable range and deleterious mutations in one category being balanced by advantageous mutations in the other category.
Individual amino acid substitutions may also have a context-dependent functional influence on the catalytic mechanism. Because the radical differences between F and M are scattered throughout the protein (fig. 2D), many fulfil a criterion for potential influence, being close to functionally important sites (Schmidt et al. 2005; Melvin et al. 2008). Many of these substitutions involve alanine and serine, which play a relatively large quantitative role in the amino acid property differences between the F and M COI proteins (fig. 5). Serine residues occur quite frequently in functional centers because the OH side chain group can form hydrogen bonds with other residues or substrates. In a study of different isolates of the nematode C. elegans, Dingley et al. (2014) discovered a single A to S substitution in COI, which had a significant effect on cytochrome oxidase activity with other phenotypic consequences. The serine was close to the binding site for a kinase known to affect mitochondrial membrane potential and ATP synthase. In this study, the in silico analysis also suggested potential for serine phosphorylation. Phosphorylation of enzymes involved in OXPHOS may play an important role in its regulation (Acin-Perez et al. 2009). Tyrosine phosphorylation by kinases is involved in sperm capacitation and the acrosome reaction (Naz and Rajesh 2004). Thus, this frequently occurring substitution may be a good potential candidate in the search for functional effects.
Chapman et al. (2008) evaluated physicochemical properties in a specific extension of the M genome COII protein in unionoidean bivalves, and although purifying selection was dominant, the properties helical contact area and partial specific amino acid volume showed evidence of positive selection. Similarly, relaxation of selection and drift and positive selection might together be combined in an integrated explanation of the change in the M COI protein. Residues in the external regions of proteins are generally less conserved than buried sites in the core or important functional residues (Toth-Petroczy and Tawfik 2011), and the distribution of selection coefficients for mtDNA shows a peak at near neutrality but with many values greater or less than zero (Tamuri et al. 2012). Thus, given a lower effective population size in males (Stewart et al. 1996), the many substitutions in the external regions of the protein associated with the category differences (table 4A and fig. 4) might have smaller selection coefficients, some decreasing and some increasing amino acid properties, and be nearly neutral. Their fixation by drift would degrade the variation in hydrophobicity between the different regions of the M protein and adversely affect function. A consequent strong selective pressure to maintain membrane potential and ATP production could result in compensating adaptive substitutions with larger selection coefficients in the slower evolving protein core, such as those involving alanine and serine, to enhance the catalytic mechanism. This could involve an additive effect on fitness of the spatially separated sites or involve epistatic interactions, which are generally assumed to be widespread in protein evolution (Starr and Thornton 2016). Examples of studies providing approaches to mechanistic understanding of such interactions are the analysis of compensatory interactions between mutations around a heme pocket in the protein CY51 affecting resistance to azoles (Mullins et al. 2011) or the analysis of the restoration of channel activity involving allosteric interaction between extra-membrane and transmembrane domains in viruses (To et al. 2017).
Apart from phylogenetic and molecular evolution approaches, a variety of experimental techniques are available for investigating the functional and biological effects of genetic variation in cytochrome oxidase, and some of these may be applicable in the analysis of F and M genome proteins in future. Mutations in COI are known to cause genetic conditions in humans (Zhen et al. 2015) or affect cytochrome oxidase activity in mouse cells (Acin-Perez et al. 2003). Performance of mtDNA genomes can be compared on the same or different nuclear backgrounds in cell cybrids (Kenyon and Moraes 1997) or in whole organisms obtained by backcrossing (Dingley et al. 2014). Such techniques are difficult at present in bivalves that are more difficult to breed in the laboratory. However measurements of swimming speed on sperm carrying different mtDNA genomes have been made in M. edulis (Everett et al. 2004; Jha et al. 2008) and this could be pursued in the species studied here, with the hypotheses of relaxed versus positive selection having different predictions on performance of F and M carrying sperm. Many spectrophotometric and cyto-histochemical methods are available for measuring cytochrome oxidase activity in isolated mitochondria, cells or tissue sections (Lanza and Nair 2009) and which can be extended with the use of cytochrome oxidase inhibitors (Pacelli et al. 2011). Techniques are also available for measuring ATP production directly or making accurate measurements of respiration in mitochondria or cells (Lanza and Nair 2009; TeSlaa and Teitell 2014). Such approaches seem more feasible for bivalves. Experimental techniques could be supplemented with molecular modelling to identify novel residue interactions or structural changes (Mullins et al. 2011; To et al. 2017) or with molecular dynamics simulations which have been used to study cytochrome oxidase function (Arnarez et al. 2013), and identify water exit pathways in bovine cytochrome oxidase (Sugitani and Stuchebrukhov 2009).
In future, mtDNA will be sequenced in many other species with DUI, and it could be possible to extend the use of metrics in the place of amino acid codes as in this study to test more refined hypotheses on regional variation in the protein combined with the diverse experimental and simulation techniques outlined above. If the F and M COI proteins are structurally and functionally different, it will be important to investigate how the different proteins maintain the same primary function (OXPHOS) while adapting to different cellular environments (e.g., spermatozoon and egg). In this study, the changes in amino acid property values in the F and M COI proteins are frequently different in sign and direction within categories (rows e and g, table 5 and fig. 4). This could suggest an interaction due to physical proximity of the two proteins and their genomes, so that evolution in one direction in the F protein favors compensatory adaptive evolution in the opposite direction in the M protein to conserve some as yet unidentified property or function. This proximity could occur most readily in males with DUI, perhaps in the fertilized egg, or in heteroplasmic mitochondria. The natural coexistence of two diverged mtDNAs in the same organism in DUI also opens new areas of investigation into mito-nuclear interactions and co-evolution, for example, of proteins involved in fertilization and sex determination and identified through genomics and proteomics (Ghiselli et al. 2012; Diz et al 2013). This could be through interactions with different alleles of the same nuclear genes in different tissues, in accordance with growing evidence of tissue- and environment-specific modulation of intraindividual mito-nuclear interactions in animals (Wolff et al. 2014).
Supplementary data are available at Genome Biology and Evolution online.
We thank Andrej Sali and Ben Webb for advice and discussion, Andrej Sali for suggesting the use of JOY, and Kenji Mizuguchi for advice on the implementation of JOY. We thank Dennis Lavrov, the Associate Editor of GBE and three anonymous reviewers for their suggestions and helpful comments. The work by F.G. was supported by the Italian Ministry of Education, University and Research, MIUR—FIR Programme no. RBFR13T97A; L.M. was supported by MIUR—SIR Programme no. RBSI14G0P5; A.P.D. was supported by the Spanish “Ministerio de Economía y Competitividad” (code AGL2014-52062-R), Fondos Feder and Xunta de Galicia (“Grupos de Referencia Competitiva” ED431C 2016-037).