Abstract
Positive (adaptive) selection has recently been implied in human superoxide dismutase 1 (SOD1), a highly abundant antioxidant protein with energy signaling and antiaging functions, one of very few examples of direct selection on a human protein product (exon); the molecular drivers of this selection are unknown. We mapped 30 extant SOD1 sequences to the recently established mammalian species tree and inferred ancestors, key substitutions, and signatures of selection during the protein’s evolution. We detected elevated substitution rates leading to great apes (Hominidae) at ~1 per 2 million years, significantly higher than in other primates and rodents, although these paradoxically generally evolve much faster. The high evolutionary rate was partly due to relaxation of some selection pressures and partly to distinct positive selection of SOD1 in great apes. We then show that higher stability and net charge and changes at the dimer interface were selectively introduced upon separation from old world monkeys and lesser apes (gibbons). Consequently, human, chimpanzee and gorilla SOD1s have a net charge of −6 at physiological pH, whereas the closely related gibbons and macaques have −3. These features consistently point towards selection against the malicious aggregation effects of elevated SOD1 levels in long-living great apes. The findings mirror the impact of human SOD1 mutations that reduce net charge and/or stability and cause ALS, a motor neuron disease characterized by oxidative stress and SOD1 aggregates and triggered by aging. Our study thus marks an example of direct selection for a particular chemical phenotype (high net charge and stability) in a single human protein with possible implications for the evolution of aging.
Similar content being viewed by others
References
Presgraves DC (2010) The molecular evolutionary basis of species formation. Nat Rev Genet 11:175–180. doi:10.1038/nrg2718
Hurst LD (2009) Fundamental concepts in genetics: genetics and the understanding of selection. Nat Rev Genet 10:83–93. doi:10.1038/nrg2506
Gillespie JH (1991) The Causes of Molecular Evolution. Oxford Ser Ecol Evol. doi:0195092716
King MC, Wilson AC (1975) Evolution at two levels in humans and chimpanzees. Science 188:107–116
Rogers J, Gibbs RA (2014) Comparative primate genomics: emerging patterns of genome content and dynamics. Nat Rev Genet 15:347–359
Wolfe KH, Li W-H (2003) Molecular evolution meets the genomics revolution. Nat Genet 33(Suppl):255–265. doi:10.1038/ng1088
Enard W, Pääbo S (2004) Comparative primate genomics. Annu Rev Genomics Hum Genet 5:351–378
Goodman M, Grossman LI, Wildman DE (2005) Moving primate genomics beyond the chimpanzee genome. Trends Genet 21:511–517
Corbetta M, Patel G, Shulman GL (2008) The reorienting system of the human brain: from environment to theory of mind. Neuron 58:306–324
Jolly CJ (2001) A proper study for mankind: analogies from the Papionin monkeys and their implications for human evolution. Am J Phys Anthropol 116:177–204. doi:10.1002/ajpa.10021
Locke DP, Hillier LW, Warren WC et al (2011) Comparative and demographic analysis of orang-utan genomes. Nature 469:529–533
Boffelli D, McAuliffe J, Ovcharenko D et al (2003) Phylogenetic shadowing of primate sequences to find functional regions of the human genome. Science 299:1391–1394. doi:10.1126/science.1081331
Blekhman R, Oshlack A, Chabot AE et al (2008) Gene regulation in primates evolves under tissue-specific selection pressures. PLoS Genet 4:e1000271
Perry GH, Melsted P, Marioni JC et al (2012) Comparative RNA sequencing reveals substantial genetic variation in endangered primates. Genome Res 22:602–610. doi:10.1101/gr.130468.111
Nielsen R, Hellmann I, Hubisz M et al (2007) Recent and ongoing selection in the human genome. Nat Rev Genet 8:857–868. doi:10.1038/nrg2187
Sabeti PC, Schaffner SF, Fry B et al (2006) Positive natural selection in the human lineage. Science 312:1614–1620. doi:10.1126/science.1124309
O’Bleness M, Searles VB, Varki A et al (2012) Evolution of genetic and genomic features unique to the human lineage. Nat Rev Genet 13:853–866. doi:10.1038/nrg3336
Pardo CA, Xu Z, Borchelt DR et al (1995) Superoxide dismutase is an abundant component in cell bodies, dendrites, and axons of motor neurons and in a subset of other neurons. Proc Natl Acad Sci USA 92:954–958
Perry J, Shin D, Getzoff E, Tainer J (2010) The structural biochemistry of the superoxide dismutases. Biochim Biophys Acta 1804:245–262. doi:10.1016/j.bbapap.2009.11.004
Reddi AR, Culotta VC (2013) SOD1 integrates signals from oxygen and glucose to repress respiration. Cell 152:224–235. doi:10.1016/j.cell.2012.11.046
Getzoff ED, Tainer JA, Stempien MM et al (1989) Evolution of CuZn superoxide dismutase and the Greek key β-barrel structural motif. Proteins Struct Funct Bioinforma 5:322–336
Landis GN, Tower J (2005) Superoxide dismutase evolution and life span regulation. Mech Ageing Dev 126:365–379. doi:10.1016/j.mad.2004.08.012
Sun J, Tower J (1999) FLP recombinase-mediated induction of Cu/Zn-superoxide dismutase transgene expression can extend the life span of adult Drosophila melanogaster flies. Mol Cell Biol 19:216–228
Melov S, Ravenscroft J, Malik S et al (2000) Extension of life-span with superoxide dismutase/catalase mimetics. Science 289:1567–1569. doi:10.1126/science.289.5484.1567
Gonzalez de Aguilar J-L, Echaniz-Laguna A, Fergani A et al (2007) Amyotrophic lateral sclerosis: all roads lead to Rome. J Neurochem 101:1153–1160. doi:10.1111/j.1471-4159.2006.04408.x
Rosen DR, Siddique T, Patterson D et al (1993) Mutations in Cu/Zn superoxide dismutase gene are associated with familial amyotrophic lateral sclerosis. Nature 362:59–62. doi:10.1038/362059a0
Renton AE, Chiò A, Traynor BJ (2014) State of play in amyotrophic lateral sclerosis genetics. Nat Neurosci 17:17–23. doi:10.1038/nn.3584
Nordlund A, Oliveberg M (2006) Folding of Cu/Zn superoxide dismutase suggests structural hotspots for gain of neurotoxic function in ALS: parallels to precursors in amyloid disease. Proc Natl Acad Sci 103:10218–10223
Byström R, Andersen PM, Gröbner G, Oliveberg M (2010) SOD1 mutations targeting surface hydrogen bonds promote amyotrophic lateral sclerosis without reducing apo-state stability. J Biol Chem 285:19544–19552. doi:10.1074/jbc.M109.086074
Shi P, Gal J, Kwinter DM et al (2010) Mitochondrial dysfunction in amyotrophic lateral sclerosis. Biochim Biophys Acta 1802:45–51. doi:10.1016/j.bbadis.2009.08.012
Huang P, Feng L, Oldham EA et al (2000) Superoxide dismutase as a target for the selective killing of cancer cells. Nature 407:390–395
Lu T, Pan Y, Kao S-Y et al (2004) Gene regulation and DNA damage in the ageing human brain. Nature 429:883–891. doi:10.1038/nature02661
Martin GM, Austad SN, Johnson TE (1996) Genetic analysis of ageing: role of oxidative damage and environmental stresses. Nat Genet 13:25–34
Carrì M, Cozzolino M (2011) SOD1 and mitochondria in ALS: a dangerous liaison. J Bioenerg Biomembr 43:593–599. doi:10.1007/s10863-011-9394-z
Kepp KP (2015) Genotype-property patient-phenotype relations suggest that proteome exhaustion can cause amyotrophic lateral sclerosis. PLoS One 10:e0118649. doi:10.1371/journal.pone.0118649
Lee YM, Friedman DJ, Ayala FJ (1985) Superoxide dismutase: an evolutionary puzzle. Proc Natl Acad Sci 82:824–828
Fukuhara R, Tezuka T, Kageyama T (2002) Structure, molecular evolution, and gene expression of primate superoxide dismutases. Gene 296:99–109
Hancock AM, Witonsky DB, Gordon AS et al (2008) Adaptations to climate in candidate genes for common metabolic disorders. PLoS Genet 4:e32
Meredith RW, Janečka JE, Gatesy J et al (2011) Impacts of the cretaceous terrestrial revolution and kpg extinction on mammal diversification. Science 334:521–524
Shaw BF, Moustakas DT, Whitelegge JP, Faull KF (2010) Taking charge of proteins: from neurodegeneration to industrial biotechnology. In: Biology AMBT-A in PC and S (ed) Adv. Protein Chem. Struct. Biol. Academic Press, New York, pp 127–164
Strange RW, Antonyuk SV, Hough MA et al (2006) Variable metallation of human superoxide dismutase: atomic resolution crystal structures of Cu–Zn, Zn–Zn and as-isolated wild-type enzymes. J Mol Biol 356:1152–1162. doi:10.1016/j.jmb.2005.11.081
Consortium TU (2008) The Universal Protein Resource (UniProt). Nucleic Acids Res 36:D190–D195. doi:10.1093/nar/gkm895
Dasmeh P, Serohijos AWR, Kepp KP, Shakhnovich EI (2013) Positively selected sites in cetacean myoglobins contribute to protein stability. PLoS Comput Biol 9:e1002929
Holm J, Dasmeh P, Kepp KP (2016) Tracking evolution of myoglobin stability in cetaceans using experimentally calibrated computational methods that account for generic protein relaxation. Biochim Biophys Acta Proteins Proteom 1864:825–834. doi:10.1016/j.bbapap.2016.04.004
Sievers F, Wilm A, Dineen D et al (2011) Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol 7:539
Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461–464
Whelan S, Goldman N (2001) A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach. Mol Biol Evol. doi:10.1093/oxfordjournals.molbev.a003851
Yang Z (1996) Among-site rate variation and its impact on phylogenetic analyses. Trends Ecol Evol 11:367–372
Williams PD, Pollock DD, Blackburne BP, Goldstein RA (2006) Assessing the accuracy of ancestral protein reconstruction methods. PLoS Comput Biol 2:e69. doi:10.1371/journal.pcbi.0020069
Yang Z, Nielsen R (2002) Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol Biol Evol 19:908–917
Neyman J, Pearson ES (1933) On the problem of the most efficient tests of statistical hypotheses. Philos Trans R Soc Lond A 231:289–337
Yang ZH, Nielsen R, Goldman N, Pedersen AMK (2000) Codon-substitution models for heterogeneous selection pressure at amino acid sites. Genetics 155:431–449
Yang Z (2007) PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 24:1586–1591. doi:10.1093/molbev/msm088
Pond SLK, Frost SDW (2005) Datamonkey: rapid detection of selective pressure on individual sites of codon alignments. Bioinformatics 21:2531–2533
Murrell B, Wertheim JO, Moola S et al (2012) Detecting individual sites subject to episodic diversifying selection. PLoS Genet 8:e1002764
Murrell B, Moola S, Mabona A et al (2013) FUBAR: a fast, unconstrained bayesian approximation for inferring selection. Mol Biol Evol:mst030
Wertheim JO, Murrell B, Smith MD et al (2014) RELAX: detecting relaxed selection in a phylogenetic framework. Mol Biol Evol 32:1–13. doi:10.1093/molbev/msu400
Vassall KA, Stubbs HR, Primmer HA et al (2011) Decreased stability and increased formation of soluble aggregates by immature superoxide dismutase do not account for disease severity in ALS. Proc Natl Acad Sci USA 108:2210–2215. doi:10.1073/pnas.0913021108
Furukawa Y, O’Halloran TV (2005) Amyotrophic lateral sclerosis mutations have the greatest destabilizing effect on the apo- and reduced form of SOD1, leading to unfolding and oxidative aggregation. J Biol Chem 280:17266–17274. doi:10.1074/jbc.M500482200
Lindberg MJ, Byström R, Boknäs N et al (2005) Systematically perturbed folding patterns of amyotrophic lateral sclerosis (ALS)-associated SOD1 mutants. Proc Natl Acad Sci USA 102:9754–9759. doi:10.1073/pnas.0501957102
Wang Q, Johnson JL, Agar NYR, Agar JN (2008) Protein aggregation and protein instability govern familial amyotrophic lateral sclerosis patient survival. PLoS Biol 6:e170. doi:10.1371/journal.pbio.0060170
Capriotti E, Fariselli P, Casadio R (2005) I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res 33:W306–W310
Dehouck Y, Kwasigroch JM, Gilis D, Rooman M (2011) PoPMuSiC 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality. BMC Bioinform 12:151. doi:10.1186/1471-2105-12-151
Kepp KP (2014) Computing stability effects of mutations in human superoxide dismutase 1. J Phys Chem B 118:1799–1812
Christensen NJ, Kepp KP (2012) Accurate stabilities of laccase mutants predicted with a modified FoldX protocol. J Chem Inf Model 52:3028–3042. doi:10.1021/ci300398z
Kepp KP (2015) Towards a “Golden Standard” for computing globin stability: stability and structure sensitivity of myoglobin mutants. Biochim Biophys Acta Proteins Proteom 1854:1239–1248. doi:10.1016/j.bbapap.2015.06.002
Capriotti E, Fariselli P, Casadio R (2004) A neural-network-based method for predicting protein stability changes upon single point mutations. Bioinformatics 20(suppl 1):i63–i68. doi:10.1093/bioinformatics/bth928
Thiltgen G, Goldstein RA (2012) Assessing predictors of changes in protein stability upon mutation using self-consistency. PLoS One 7:e46084. doi:10.1371/journal.pone.0046084
Tokuriki N, Stricher F, Schymkowitz J et al (2007) The stability effects of protein mutations appear to be universally distributed. J Mol Biol. doi:10.1016/j.jmb.2007.03.069
Shi Y, Mowery RA, Shaw BF (2013) Effect of metal loading and subcellular pH on net charge of superoxide dismutase-1. J Mol Biol 425:4388–4404. doi:10.1016/j.jmb.2013.07.018
Gao J, Mammen M, Whitesides GM (1996) Evaluating electrostatic contributions to binding with the use of protein charge ladders. Science 272:535
Shi Y, Abdolvahabi A, Shaw BF (2014) Protein charge ladders reveal that the net charge of ALS-linked superoxide dismutase can be different in sign and magnitude from predicted values. Protein Sci 23:1417–1433
Shaw BF, Valentine JS (2007) How do ALS-associated mutations in superoxide dismutase 1 promote aggregation of the protein? Trends Biochem Sci 32:78–85. doi:10.1016/j.tibs.2006.12.005
Danielsson J, Mu X, Lang L et al (2015) Thermodynamics of protein destabilization in live cells. Proc Natl Acad Sci USA 112:12402–12407. doi:10.1073/pnas.1511308112
Mailund T, Halager AE, Westergaard M et al (2012) A new isolation with migration model along complete genomes infers very different divergence processes among closely related great ape species. PLoS Genet 8:e1003125. doi:10.1371/journal.pgen.1003125
Li WH, Ellsworth DL, Krushkal J et al (1996) Rates of nucleotide substitution in primates and rodents and the generation-time effect hypothesis. Mol Phylogenet Evol 5:182–187. doi:10.1006/mpev.1996.0012
Britten RJ (1986) Rates of DNA sequence evolution differ between taxonomic groups. Science 231:1393–1398
Seino S, Bell GI, Li WH (1992) Sequences of primate insulin genes support the hypothesis of a slower rate of molecular evolution in humans and apes than in monkeys. Mol Biol Evol 9:193–203
Yi S, Ellsworth DL, Li W-H (2002) Slow molecular clocks in Old World monkeys, apes, and humans. Mol Biol Evol 19:2191–2198
Weinreich DM (2001) The rates of molecular evolution in rodent and primate mitochondrial DNA. J Mol Evol 52:40–50
Martin AP, Palumbi SR (1993) Body size, metabolic rate, generation time, and the molecular clock. Proc Natl Acad Sci USA 90:4087–4091
Tolmasoff JM, Ono T, Cutler RG (1980) Superoxide dismutase: correlation with life-span and specific metabolic rate in primate species. Proc Natl Acad Sci 77:2777–2781
Anisimova M, Yang Z (2007) Multiple hypothesis testing to detect lineages under positive selection that affects only a few sites. Mol Biol Evol 24:1219–1228
Ding F, Dokholyan NV (2008) Dynamical roles of metal ions and the disulfide bond in Cu, Zn superoxide dismutase folding and aggregation. Proc Natl Acad Sci USA 105:19696–19701. doi:10.1073/pnas.0803266105
Khan S, Vihinen M (2010) Performance of protein stability predictors. Hum Mutat 31:675–684. doi:10.1002/humu.21242
Scott EE, Paster EV, Olson JS (2000) The stabilities of mammalian apomyoglobins vary over a 600-fold range and can be enhanced by comparative mutagenesis. J Biol Chem 275:27129–27136. doi:10.1074/jbc.M000452200
Hendgen-Cotta UB, Merx MW, Shiva S et al (2008) Nitrite reductase activity of myoglobin regulates respiration and cellular viability in myocardial ischemia-reperfusion injury. Proc Natl Acad Sci USA 105:10256–10261. doi:10.1073/pnas.0801336105
Davis RW, Polasek L, Watson R et al (2004) The diving paradox: new insights into the role of the dive response in air-breathing vertebrates. Comp Biochem Physiol Part A Mol Integr Physiol 138:263–268. doi:10.1016/j.cbpb.2004.05.003
Dasmeh P, Davis RW, Kepp KP (2013) Aerobic dive limits of seals with mutant myoglobin using combined thermochemical and physiological data. Comp Biochem Physiol Part A Mol Integr Physiol 164:119–128. doi:10.1016/j.cbpa.2012.10.010
Mirceta S, Signore AV, Burns JM et al (2013) Evolution of mammalian diving capacity traced by myoglobin net surface charge. Science 340:1234192. doi:10.1126/science.1234192
Kimura M (1962) On the probability of fixation of mutant genes in a population. Genetics 47:713
Phifer-Rixey M, Bonhomme F, Boursot P et al (2012) Adaptive evolution and effective population size in wild house mice. Mol Biol Evol 29:2949–2955. doi:10.1093/molbev/mss105
Piganeau G, Eyre-Walker A (2009) Evidence for variation in the effective population size of animal mitochondrial DNA. PLoS One 4:e4396
Demetrius L (2006) Aging in mouse and human systems: a comparative study. Ann N Y Acad Sci 1067:66–82. doi:10.1196/annals.1354.010
Perez SI, Tejedor MF, Novo NM, Aristide L (2013) Divergence times and the evolutionary radiation of new world monkeys (Platyrrhini, Primates): an analysis of fossil and molecular data. PLoS One 8:e68029
White CR, Seymour RS (2003) Mammalian basal metabolic rate is proportional to body mass2/3. Proc Natl Acad Sci 100:4046–4049. doi:10.1073/pnas.0436428100
Marquet PA (2002) Of predators, prey, and power laws. Science 295:2229–2230
Kumar S, Subramanian S (2002) Mutation rates in mammalian genomes. Proc Natl Acad Sci 99:803–808
Scandalios JG (1993) Oxygen stress and superoxide dismutases. Plant Physiol 101:7–12
Drummond DA, Wilke CO (2008) Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell 134:341–352. doi:10.1016/j.cell.2008.05.042
Kepp KP, Dasmeh P (2014) A model of proteostatic energy cost and its use in analysis of proteome trends and sequence evolution. PLoS One 9:e90504. doi:10.1371/journal.pone.0090504
Serohijos AWR, Rimas Z, Shakhnovich EI (2012) Protein biophysics explains why highly abundant proteins evolve slowly. Cell Rep 2:249–256. doi:10.1016/j.celrep.2012.06.022
Lanfear R, Kokko H, Eyre-Walker A (2014) Population size and the rate of evolution. Trends Ecol Evol 29:33–41. doi:10.1016/j.tree.2013.09.009
Haldane JBS (1927) A mathematical theory of natural and artificial selection, part V: selection and mutation. Math Proc Cambridge Philos Soc 23:838–844
Prudencio M, Hart PJ, Borchelt DR, Andersen PM (2009) Variation in aggregation propensities among ALS-associated variants of SOD1: correlation to human disease. Hum Mol Genet 18:3217–3226. doi:10.1093/hmg/ddp260
Dobson CM (2003) Protein folding and misfolding. Nature 426:884–890. doi:10.1038/nature02261
Münch C, Bertolotti A (2010) Exposure of hydrophobic surfaces initiates aggregation of diverse ALS-causing superoxide dismutase-1 mutants. J Mol Biol 399:512–525. doi:10.1016/j.jmb.2010.04.019
Gagliardi S, Cova E, Davin A et al (2010) SOD1 mRNA expression in sporadic amyotrophic lateral sclerosis. Neurobiol Dis 39:198–203. doi:10.1016/j.nbd.2010.04.008
Kitamura A, Inada N, Kubota H et al (2014) Dysregulation of the proteasome increases the toxicity of ALS-linked mutant SOD1. Genes Cells 19:209–224. doi:10.1111/gtc.12125
Allen SP, Rajan S, Duffy L et al (2014) Superoxide dismutase 1 mutation in a cellular model of amyotrophic lateral sclerosis shifts energy generation from oxidative phosphorylation to glycolysis. Neurobiol Aging 35:1499–1509. doi:10.1016/j.neurobiolaging.2013.11.025
Richardson K, Allen SP, Mortiboys H et al (2013) The effect of SOD1 mutation on cellular bioenergetic profile and viability in response to oxidative stress and influence of mutation-type. PLoS One 8:e68256. doi:10.1371/journal.pone.0068256
Bouteloup C, Desport J-C, Clavelou P et al (2009) Hypermetabolism in ALS patients: an early and persistent phenomenon. J Neurol 256:1236–1242. doi:10.1007/s00415-009-5100-z
Wagner A (2005) Energy constraints on the evolution of gene expression. Mol Biol Evol 22:1365–1374. doi:10.1093/molbev/msi126
Heizer EM, Raiford DW, Raymer ML et al (2006) Amino acid cost and codon-usage biases in 6 prokaryotic genomes: a whole-genome analysis. Mol Biol Evol 23:1670–1680. doi:10.1093/molbev/msl029
Drummond DA, Bloom JD, Adami C et al (2005) Why highly expressed proteins evolve slowly. Proc Natl Acad Sci USA 102:14338–14343. doi:10.1073/pnas.0504070102
Kirkwood TB, Rose MR (1991) Evolution of senescence: late survival sacrificed for reproduction. Philos Trans R Soc Lond B Biol Sci 332:15–24. doi:10.1098/rstb.1991.0028
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
18_2017_2519_MOESM1_ESM.pdf
Supplementary information: The supporting information file contains the alignment of SOD1 sequences used in this work (Figures S1 and S2); the tree used for rate relaxation analysis as made from DataMonkey (Figure S3); codons detected to be under positive selection using various models (Table S1); branches detected to be under positive selection (Table S2); numerical data from relaxation analysis (Table S3); correlation of benchmarked experimental stability data vs. computed stability changes of SOD1 mutants (Figure S4); numerical data used for this correlation (Table S4); distribution of stability effects for all possible mutations in SOD1 as estimated using Popmusic (Figure S5); all inferred substitutions in the phylogeny from ancestral state reconstruction and computed ∆∆G values and solvent exposure for all sites (Table S5) (PDF 3065 kb)
Rights and permissions
About this article
Cite this article
Dasmeh, P., Kepp, K.P. Superoxide dismutase 1 is positively selected to minimize protein aggregation in great apes. Cell. Mol. Life Sci. 74, 3023–3037 (2017). https://doi.org/10.1007/s00018-017-2519-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00018-017-2519-8