The evolutionary trajectory of mitochondrial carrier family during metazoan evolution
- Ming Gong†1,
- Jie Li†1,
- Meng Wang1,
- Jin Wang1Email author,
- Ke Zen1Email author and
- Chen-Yu Zhang1Email author
© Gong et al; licensee BioMed Central Ltd. 2010
Received: 18 May 2010
Accepted: 16 September 2010
Published: 16 September 2010
Exploring metabolic evolution is a way to understand metabolic complexity. The substrate transport of mitochondrial carrier family (MCF) influences direct metabolic activities, making it possible to understand indirectly metabolic evolution from the evolution of substrate transport of MCF. However, the evolutionary study of substrate transport of MCF does not mean that all the concrete structures of mitochondrial carriers (MCs) must first be gained.
Here we studied the alternation of MCF structure and potential correlated functions of MCF during metazoan evolution. The data analysis indicates that the types of substrates transported by MCF as a whole were maintained during metazoan evolution. However, the size of the substrates transported by members of MCs continuously diminished during the evolutionary process. We have found that the ratio of hydrophobic amino acids at specific helix-helix interfaces increases significantly during vertebrate evolution. Amino acid's spatial positioning and the calculating of packing values both indicate the increase in the number of hydrophobic amino acids would lead to a more "tight" structure of the TR domain, which is in agreement with the trend of diminishing size of substrates transported by MCs. In addition, there was a significant increase in the number of carriers of MCF during vertebrate evolution.
We propose that the more "tight" TR structure generated by the increase of the hydrophobic amino acids at specific helix-helix interfaces during vertebrate evolution enhances the substrate selectivity of MCF, reflecting the evolutionary trajectory of MCF during metazoan evolution.
Mitochondrial carriers (MCs), located at the inner membrane of mitochondria (IMM), are responsible for transporting a variety of metabolites between the cytosol and the mitochondria and influence the activities of the metabolic pathway direct [1, 2]. The substrates transported by MCs, such as nucleotides, amino acids, cofactors, and H+, are involved in oxidative phosphorylation, gluconeogenesis, the synthesis and degradations of amino and fatty acids, the macromolecular synthesis of proteins and nucleic acids, sterol metabolism, and thermogenesis . The mutations of the carriers are closely correlated with diseases, including Amish microcephaly, CAC deficiency, NICCD/CTLN2, neonatal myoclonic epilepsy, Sengers' syndrome, severe obesity, and type II diabetes [1, 3].
The substrates transported by MCs vary widely in their structure and size from the smallest, H+, to the largest and most highly charged species, such as ATP. By considering conservation of amino acids, distance and chemical constraints , and by modelling family members [5–12] on the known structure of the ADP/ATP carrier, recent research has identified a common substrate binding site located at approximately the midpoint of the membrane . However, the molecular mechanism of substrate selectivity of MCs remains incompletely understood. It is not possible to obtain the concrete structures of all mitochondrial carrier family (MCF) members through crystallization [1, 13], and thus uncovering the mechanism of substrate selectivity of MCF direct is impossible solely by linear superposition.
A powerful source of functional innovation is gene duplication and loss . Some reports have suggested that many of gene duplication events occur during the earlier period of vertebrate evolution [15, 16], indicating that if gene duplications exist in MCF [17, 18], the substrate selectivity changes may be a form of functional innovation closely associated with metabolic evolution. Here we investigate MCF, a gene family with common functional categories whose members do not have clearly defined functions, and subject it to The Big Experiment  to explore the evolutionary trajectory of MCF. We further investigate the synchronization between molecular evolution and macroevolution to search for evolutionary rules of sequences corresponding to structures of MCF in order to determine the characteristics of structural changes. The molecular mechanism of change of substrate selectivity was then analyzed to identify the transport functions of MCs.
Gene duplication of MCF is under strong purifying selection
According to the classification of the MCF secondary structure region (Additional file 1), TR has the most conservative sequence with an identity of 70.44%, while the average identities of LOOP135 (loop1, loop3, loop5) and NCLOOP24 (n, c, loop2, loop4) (Additional file 1) are only 42.24% and 19.25%, respectively. On the one hand, the high evolutionary conservation in TR reflects a stable structure maintaining the basic function of the transport channel. On the other hand, this evolutionary conservation indicates that the relatively small changes (29.56%) of TR sequences may have a large effect on the substrate transport of MCF.
The evolution of MCF keeps pace with metazoan evolution
The significant rise of hydrophobic residues at helix-helix interfaces
Interestingly, TRUP246 showed a similar distribution (Figure 4D) with TRDOWN135, indicating that the number of hydrophobic residues was increased in TRUP246 during vertebrate evolution too. Although TRDOWN135 and TRUP246 faced opposite directions (Additional file 1 and Figure 4E), the spatial distributions in the structure of ADP/ATP carrier clearly showed that they were close to each other and formed three helix-helix interfaces (Figure 4E). The conserved P and G (Figure 4F) in TR246 could serve as the hinges between TRUP246 and TRDOWN246 (Figure 4E) and made the helices in TRUP246 tilt to the TRDOWN135 sides (Figure 4E). TRDOWN246 participated in the formation of helix-helix interfaces with TRDOWN135 as well as TRUP246 (Additional file 5A). However, TRUP135 had no similar properties according to its space distribution (Additional file 5B). So, TRDOWN135 served as links between TRUP246 and TRDOWN246 and played a vital role in the formation of helix-helix interfaces, indicating the potential functional significance of the increased hydrophobic residues in TRDOWN135.
The "tight" structure of TR during vertebrate evolution
Furthermore, the logo  analysis based on all the sequences in the TRDOWN of MCF showed not only the enrichment of the hydrophobic residues at the same site or contiguous site in TRDOWN, but also the transformation of hydrophilic residues to hydrophobic residues in TRDOWN135 at sites 2, 3, 4, 6 and 7 during metazoan evolution (Figure 5C and 5E). The hydrophobic effect was lost once the helices were inserted into hydrophobic bilayers as a driving force for the helix association of integral membrane proteins  such as the mitochondrial inner membrane protein, MCF. The helix association then occurs through a combination of hydrogen-bonding, electrostatic, and van der Waals interactions . Due to the enrichment of the hydrophobic residues in position 3, 4, 6, 8 of TRDOWN246 (Figure 5D and 5F) and the enrichment of the hydrophobic residues in position 4, 5, 7, 8 of TRUP246 (Additional file 6), we postulated that the methyl groups of the side chain of the hydrophobic residues might interact with the methyl groups of the hydrophobic residues from the neighboring residues in TRDOWN135 by van der Waals interactions to maintain the helix-helix interactions. The experimental evidence showed that A134 of bovine mitochondrial oxoglutarate carrier potentially engaged in inter-helical interactions as well as other key residues in the odd-numbered transmembrane α-helices . Further, we found that A134 was located rightly at the TRDOWN135 and evolved from S at the same site of invertebrate (Additional file 7), which indirectly supported our hypothesis that the increase of hydrophobic residues would bring in more methyl groups, further strengthening the accumulated effect of the van der Waals interaction among them and generating a more "tight" TR structure.
According to the calculation of packing values of the residues in membrane proteins , TRDOWN135 in vertebrates had a significantly higher packing value (0.396) than that of invertebrates (0.383). This result thus further indicates that vertebrates have a more "tight" TR structure of MCF than invertebrates.
Enhancement of substrate selectivity
A phylogenetic tree was constructed using MEGA4.0  based on TR sequences from 44 carriers in SLC25 and their orthologous sequences in nine species (44 Χ 9) (Figure 6B). As can be seen, its branches were labelled according to previous reports related to substrates transported by MCs [1, 2]. The tree clearly showed three clusters that correspond to three categories of substrates, namely ADP/ATP, amino acid and cofactor, and H+. According to the E-value of each carrier obtained by BLAST in all the fungal genomes database, we calculated the average E-values of representative carriers for each cluster, showing that the ADP/ATP cluster was 10-50.56, the amino acid and cofactor cluster was 10-43, and the H+ cluster was 10-38.35. The results showed that the ADP/ATP cluster was an older cluster, while the H+ cluster was relatively younger cluster. Combined with the size of substrates transported by MCs , we found that the size of substrates transported by members of MCs continuously diminished throughout the evolution (Figure 6B).
Proline served as the hinge between TRDOWN135  and the label sequences of Px(D/E)xx(K/R) [24, 27] (Additional file 8). The conserved P and G (Figure 4F) in TR246 (Figure 4E and Figure 4F) could also serve as the hinges between TRUP246 and TRDOWN246. Furthermore, these conserved P and G in the transmembrane α-helices (Figure 4F) constituted the P-G level 1 located at approximately the midpoint of transmembrane region and the P-G level 2 located at approximately the bottom of transmembrane region . The two P-G levels  made the TRDOWN relatively independent and less affected by the structural changes due to helix tilt during the substrate transport process. So, the increased hydrophobic residues at the specific helix-helix interfaces could enhance the compactness degree in TRDOWN and strengthened the interaction between substrates and substrates contacting sites  of the MCF, thus allowing the passing of the substrates with the given size, in agreement with the trend of continuously diminishing size of substrates (Figure 6B).
MCF acts as the molecular fossil of metazoan
The rise of oxygen concentration appears to have precipitated a massive increase in metabolic complexity, culminating in the rise of metazoans around 600 million years ago . Feedback in the rise of oxygen concentrations has led to increasing metabolic complexity  and shows the existence of the intrinsic molecular mechanism of continuously adapting to the rise of oxygen concentration. We found that many gene duplication events of MCF occurred during the early period of vertebrate evolution, especially during the Ediacarian and Cambrian periods (Additional file 2). Further, the molecular evolution of MCF keeps pace with macroevolution (Figure 3). MCF located in mitochondria has a direct effect on metabolic activity [1, 2], and thus this feedback mechanism may be embodied in the functional evolution of MCF. These data make the MCF act as the molecular fossil for exploring metabolic complexity in metazoan.
Enhancement of substrates selectivity correlates to the rise of oxygen concentration
The enhancement of the substrate selectivity of MCF could partially explain the feedback mechanism evolved in metabolic evolution from the viewpoint of providing energy and reducing damage. From the view of providing energy, if mitochondria can be regarded as an energy-producing factory, its core department is the electron-transport chain. The enhancement of substrate selectivity of MCF allowed for more frequent communication between the mitochondrial matrix and the IMM. In addition, this increase of substrate selectivity provided more energy materials to the energy-producing factory by promoting the operation efficiency of this transport machine. Thus, the increase in the concentration of oxygen as the last electron receiver in the electron-transport chain [30, 31] would produce more abundant energy to satisfy physiological needs.
Oxygen participates in the provision of energy for the evolution of life but also brings by-products, such as superoxide and peroxides . The enhancement of substrate selectivity of MCF offers a possible way to reduce oxygen damage. It is the tendency towards strengthening of the substrate selectivity of MCF that makes the enhancement of selectivity of the H+ substrate. Uncoupling protein is generally considered as responsible for H+ conductance [32, 33]. No specific uncoupling protein is responsible for the proton conductance of yeast mitochondrion . The recent research represented that lamprey, generally considered as the most primitive vertebrate, had the uncoupling protein (UCP) transporting H+ , at least indicating the enhancement of selectivity of the H+ substrate. We also found the UCP subfamily was diverged approximately 637 million years ago (Additional file 2), in good agreement with around 600 million years ago when the rise of oxygen concentration culminates in the rise of metazoans. This good correlation further indicate that the rise of oxygen concentration may induces the enhancement of selectivity of the H+ substrate, which reduces oxygen damage by affecting the IMM potential, such as the role of the UCP located in the H+ cluster in reducing superoxide production and production of ROS [36–38].
In view of the important role of MCF as a molecular fossil in metabolism, we postulate that oxygen could be an environmental factor affecting the variation of substrate transport of MCF. Our studies explore the functional mechanism of oxygen on the evolution of MCF from the viewpoint of the enhancement of substrate selectivity of MCF.
The more "tight" TR structure generated by the increase of the hydrophobic amino acids at specific helix-helix interfaces enhances the substrate selectivity of MCF, which reflects the evolutionary trajectory of MCF. Because the goal of this study was to understand the variation in the structure of MCF from the level of sequence, our findings might provide the more specific mutation sites for laboratory experiments to improve experimental efficiency.
Partitioning evolutional processes and obtaining orthologous sequences
The orthologous sequences of human MCF (SLC25) were obtained from Swiss-Prot/TrEMBL and GenBank using the BLAST network service [39, 40]. The complexity of metabolism was reflected by the evolutional process of metazoan, and thus the orthologous sequences from metazoan were studied exclusively. In view of the facts that sequence similarity is close to 30% between members of SLC25 , the shorter process of metazoan evolution has a lower sequence variation and the orthologous gene itself has the a higher sequence similarity, the E-value of BLAST was set to 10-50 to exclude the interference from many nonhomologous genes. For cases when there was more than one sequence with a high similarity to human members, the sequence with the highest similarity was selected as the orthologous gene.
The emergences of vertebrates and endotherms indicate the two great leaps in metazoan evolution, and thus metazoan evolution was divided into three consecutive phases named the Non-ver (invertebrate) phase, the Ver-eco (vertebrate ectotherm) phase and the Ver-endo (vertebrate endotherm) phase. As current databases do not provide sequence data of MCF for more than three ectotherm species, we only chose three fully annotated species from three partitioned phases to meet the statistical requirements of ANOVA. Caenorhabditis elegans, Drosophila melanogaster and Strongylocentrotus purpuratus were used to represent the Non-ver phase. Tetraodon nigroviridis, Danio rerio and Xenopus tropicalis were used to represent the Ver-eco phase. Bos Taurus, Mus musculus, and Homo sapiens were used to represent the Ver-endo phase. The number of carriers from the nine species are as follows: human (44), mouse (44), bovine (40), frog (43), zebrafish (44), fugu (41), sea urchin (22), fly (26), and worm (25). A list of sequence accessions could be found in Additional file 9.
Classification of the whole structural region
In accordance with the generally accepted secondary structure of MCF [1, 2, 13, 23, 27, 41], we defined amino-ends, carboxyl-ends and two hydrophilic regions (n, c, loop2, loop4) facing the cytosol space as NCLOOP24; transmembrane regions consisting of six α-helices as TR; and three hydrophilic regions facing matrix space as LOOP135 (loop1, loop3, loop5) (Additional file 1). Six transmembrane α-helices were defined according to the classification of TR  and the c-terminal definition of three odd α-helices . The example of TR classification could be found in the CLUSTAL alignment among the oxoglutarate/malate sequences in metazoan species (Additional file 7). TR135 represents three odd α-helices. TR246 represents three even α-helices. TR was separated into two parts along the vertical direction from cytosol to matrix (Additional file 1). TRUP indicates the upper part facing cytosol. TRUP was further divided into two parts: TRUP135 was made up of three odd α-helices, while TRUP246 consisted of three even α-helices. TRDOWN represents the lower part of TR which faces the mitochondria matrix. TRDOWN was further divided into two parts: TRDOWN135 was made up of three odd α-helices, while TRDOWN246 consisted of three even α-helices.
Gene duplication and natural selection detection
Gene duplication events were detected through the construction of phylogenetic trees of gene families . The acceptance criterion was that the orthologous subfamily emerging from a duplication event had at least two species. The topology of the phylogenetic tree of the candidate family was constructed by the neighbor-joining method  (bootstrap = 500, JTT matrix).
The nonsynonymous substitution (those causing amino acid-alterations) to synonymous substitution (silent) rate ratio (ω = d N /d S ) provides a sensitive measure of natural selection at the protein level, with ω values of 1, > 1, and < 1, indicating neutral evolution, positive selection and purifying selection, respectively . We used branch-site model A [44, 45] to detect the type of natural selection of TR. This model has been reported to be more sensitive to the detection of positive selection than previous models including branch models  and site models , which may be useful in detecting positive selection after gene duplication in gene family evolution . We used a branch-site test of positive selection  to construct a likelihood ratio test between Model A with ω2≧1(alternative model,) and Model A1 with ω2 = 1 fixed (null model). The test was done by comparing the difference of likelihood values 2λ to a χ2 distribution of 1 degree of freedom. The critical values of 2λ at the 5% and 1% level are 2.71 and 5.41, respectively . Sites that could be under positive selection were identified with a Bayes Empirical Bayes approach . In addition, synonymous (d S ) and nonsynonymous (d N ) substitution rates were estimated using the methods of Yang and Nielson  as implemented in yn00 using PAML software .
Time scale and molecular clock estimation
The time scale estimation of gene duplication with multiple calibrations was implemented in the codeml program  of the PAML package (version 4) . We adopted several calibrations inferred from both fossil data and molecular data [52, 53], such as the primate-rodent (91 Myr ago), and vertebrate-fly (993 Myr ago) calibrations. The mtREV24 model  was applied as a model of amino acid substitution. We used both global clock and local clock methods to conduct the time scale estimation of gene duplication . Linear regression was applied to test the congruence between global clock and local clock.
We applied the above-mentioned method to the molecular clock estimation to infer whether the evolution of MCF keeps pace with macroevolution. Nine species could be found in the small number of orthologous sequences of human MCF, barely enough on behalf of MCF. Therefore, six species (worm, fruitfly, zebrafish, frog, mouse, and human) were selected to narrow the range of species. Then 33 orthologous sequences were found for each species. Further, the tandem concatenated sequence, which consisted of 33 orthologous TR sequences in each species, was applied in the molecular clock estimation.
Analysis of the feature of the sequence from the structure of MCF
The statistics of the amino acid component (AAC) were conducted according to the classification of the structure of MCF. Hydrophobic residues were based on the hydrophobicity table . Our compiled program using perl 5.8.7 was applied to the AAC statistic with two approaches of selecting and de-selecting species, respectively. Firstly, the statistics with selecting species were based on the above-mentioned nine species. A one-way ANOVA, followed by the Holm-Sidak test for multiple comparisons, was conducted using SigmaStat Windows Version 3.5 to evaluate differences in mean values among groups. The downloaded orthologous sequences according to 10-50 (not including sequence fragments and the sequences with obvious deletion in TR or conical pit region) were divided into the three sequences pools that were in the Non-ver pool (192), the Ver-eco pool (164), and the Ver-endo pool (208). A list of sequence accessions could be found in Additional file 10. The mean value of the percentage of the relative AAC was calculated from 132 (44 carriers × 3 species) sequences sampled randomly from three pools, respectively. This process was repeated for 132 times. The cumulative distribution function in the R language was applied to the analysis of the cumulative distribution of the mean values obtained.
Helix packing is important in the folding, stability, and association of membrane proteins [22, 57]. The packing value correlates positively with the degree of compactness of TR [22, 58]. Therefore, the quantitative statistics of packing values of the membrane protein can partially reflect the degree of compactness of TR. By studying the packing trait on the membrane protein helix from the obtained structure data of the membrane complex , it was able to obtain the packing values of the helix residues of TR. These data were applied to determine the average packing values of TR in MCF, indicating changes in the degree of compactness of TR during metazoan evolution.
The evolution of substrate transport of MCs
A phylogenetic tree was constructed using MEGA4.0  based on TR sequences from 44 carriers in SLC25 and their orthologous sequences in nine species (44 Χ 9). In view of the large number of sequences, the relatively low number of amino acids (the average length of the sequences used was 111 amino acids), and the relatively high divergence among the sequences, the neighbor-joining method was selected to generate the phylogenetic tree with the Poisson correction used to measure the pairwise sequence distances [59, 60]. Other tree-generating algorithms (minimal evolution, UPMGA and maximum likelihood) resulted in phylogenetic trees with a similar topology regarding the main branches generated by the neighbor-joining method. According to previous reports about the function of the members of MCF [1, 2], we could obtain the pattern of substrate transport of MCF.
As this family is exclusive to eukaryotes , we took all the fungal genomes in NCBI, the primitive species in eukaryotes, as a reference from which to estimate the ancient level of MCs. The sequences of SLC25 members were applied into the BLAST network service in all the fungal genomes in NCBI to obtain the corresponding list of E-values. The smallest 10 E-values on the list were used to determine the mean value statistics. The smaller the mean value, the higher the similarity between the sequences, and the older the carrier.
mitochondrial carrier family
solute carrier family 25
inner membrane of mitochondria
reactive oxygen species
amino acid component.
This work was supported by grants from the National Natural Science Foundation of China (no. 90813035, 30890044). We are very grateful to the three anonymous reviewers for valuable comments and suggestions.
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