Membrane Proteins Are Dramatically Less Conserved thanWater-Soluble Proteins across the Tree of Life

Victor Sojo123 Christophe Dessimoz245 Andrew Pomiankowski12 and Nick Lane12

1CoMPLEX University College London London United Kingdom2Department of Genetics Evolution and Environment University College London London United Kingdom3Systems Biophysics Faculty of Physics Ludwig-Maximilian University of Munich Munich Germany4Department of Ecology and Evolution University of Lausanne Lausanne Switzerland5Center for Integrative Genomics University of Lausanne Lausanne Switzerland

Corresponding authors E-mails vsojo11uclacuk nicklaneuclacuk

Associate editor James McInerney

Abstract

Membrane proteins are crucial in transport signaling bioenergetics catalysis and as drug targets Here we show thatmembrane proteins have dramatically fewer detectable orthologs than water-soluble proteins less than half in mostspecies analyzed This sparse distribution could reflect rapid divergence or gene loss We find that both mechanismsoperate First membrane proteins evolve faster than water-soluble proteins particularly in their exterior-facing portionsSecond we demonstrate that predicted ancestral membrane proteins are preferentially lost compared with water-soluble proteins in closely related species of archaea and bacteria These patterns are consistent across the whole treeof life and in each of the three domains of archaea bacteria and eukaryotes Our findings point to a fundamentalevolutionary principle membrane proteins evolve faster due to stronger adaptive selection in changing environmentswhereas cytosolic proteins are under more stringent purifying selection in the homeostatic interior of the cell This effectshould be strongest in prokaryotes weaker in unicellular eukaryotes (with intracellular membranes) and weakest inmulticellular eukaryotes (with extracellular homeostasis) We demonstrate that this is indeed the case Similarly we showthat extracellular water-soluble proteins exhibit an even stronger pattern of low homology than membrane proteinsThese striking differences in conservation of membrane proteins versus water-soluble proteins have importantimplications for evolution and medicine

Key words membrane proteins orthologs homeostasis evolution adaptation

IntroductionBiological membranes form the boundary between the celland its surroundings and their embedded proteins constitutean active link to the environment with crucial roles in repro-duction bioenergetics transport signaling and catalysis(Mitchell 1957 1961 Singer and Nicolson 1972 Hedin et al2011) Over half of all known drug targets are membraneproteins (Overington et al 2006) Their study is thereforecentral to our understanding of the origins and evolutionof life as well as to physiology and medicine

Previous studies have shown that the subcellular localiza-tion of a protein is a strong predictor of its evolutionary rateExtracellular proteins secreted from the cell evolve faster thanintracellular proteins in both mammals and yeast as do theexternal parts of membrane proteins (Tourasse and Li 2000Julenius and Pedersen 2006 Liao et al 2010) but the reasonsare unclear Structural and packing constraints undoubtedlyplay a role with the exposure of amino-acid residues to thesolvent (Oberai et al 2009 Franzosa et al 2013) as well as thesub-cellular localization of the proteins and their portions(Julenius and Pedersen 2006 Liao et al 2010) being the stron-gest predictors of evolutionary rate Membrane proteins also

diverge faster than intracellular water-soluble proteins in par-asites where surface interactions evolve under pressure toavoid detection by the host (Volkman et al 2002 Plotkinet al 2004) This pattern may be specific to the ldquored-queenrdquodynamics of parasitic interactions that is the need for con-stant adaptation merely to maintain fitness Taken togetherhowever these disparate findings suggest that evolutionmight generally occur faster outside the cell and hint atthe operation of a wider evolutionary mechanism

Here we test the hypothesis that protein evolution is fasteroutside the cell as a result of adaptation to changing envi-ronments (fig 1 top) Over evolutionary time the interior ofthe cell remains stable compared with the exterior which isforced to change in response to shifting biogeochemical pro-cesses migration with colonization of new niches and otherbiotic interactions This leads to the faster evolution of se-creted water-soluble proteins and outside-facing sections ofmembrane proteins The utility of a protein will also dependon the specific environment potentially leading to greaterloss of membrane-bound proteins over time as environmentschange (fig 1 middle) We have analyzed large data sets oforthologs to evaluate the conservation of membrane proteins

Article

The Author 2016 Published by Oxford University Press on behalf of the Society for Molecular Biology and EvolutionThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (httpcreativecommonsorglicensesby40) which permits unrestricted reuse distribution and reproduction in any medium provided the original work isproperly cited Open Access2874 Mol Biol Evol 33(11)2874ndash2884 doi101093molbevmsw164 Advance Access publication August 8 2016

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relative to water-soluble proteins across the entire tree of lifeto test whether faster evolution outside the cell is driven byadaptation to new environments and functions

Results

Membrane Proteins Are Shared by Fewer Species in AllThree Domains of LifeTo study the evolution of membrane proteins across the treeof life we downloaded the 883176 pre-computed orthologgroups (OGs) for all 1706 species from the three domains oflife present in the OMA database (Altenhoff et al 2015) Weseparately obtained the full list of 66 species in the EMBL-EBIlist of reference proteomes (wwwebiacukreference_proteomes) and extracted the OMA OGs for each protein ofeach species where present (supplementary table S1Supplementary Material online) We classified each proteinsequence as either a membrane protein (MP) or a water-soluble protein (WS) using the predictions of the TMHMMalgorithm (Krogh et al 2001) We then determined the num-ber of orthologs found for each protein (ie the size of theortholog cluster or OG for each protein) independently foreach species We find that in all cases of all three domains oflife (archaea Gram-positive and Gram-negative bacteria aswell as unicellular and multicellular eukaryotes) the meannumber of orthologs is substantially smaller for MPs thanfor WSs (fig 2 and supplementary table S1 SupplementaryMaterial online) that is membrane proteins are shared byfewer species on average (paired t-test tfrac14 805 dffrac14 63

Pfrac14 2881011 rfrac14 0712) A simple proteinndashprotein BLAST(BLASTp) search (Altschul et al 1990) against the full nonre-dundant (nr) NCBI protein database confirms these findings(supplementary fig S1 Supplementary Material online)

This dramatic reduction in the conservation of membraneproteins is widespread across the entire tree of life but theeffect decreases as cellular or organismal complexity increasesWater-soluble proteins have on average 27 times moreorthologs than membrane proteins in prokaryotes The factordecreases to 24 in unicellular eukaryotes and to 17 in multi-cellular eukaryotes (fig 3A one-way analysis of varianceF(261)frac14 2107 Pfrac14 11107 x2frac140149) Filtering for pro-teins shared by eukaryotes and at least one of the prokaryoticdomains produces the results in figure 3B While prokaryotesare largely unaltered and the difference between unicellularand multicellular eukaryotes remains the effect becomeslarger overall for eukaryotes That is potentially ancestral pro-teins in eukaryotes (namely with orthologs in either archaeaor bacteria) are more likely to be lost if they are membrane-bound

We performed a logistic regression on the entire pre-computed OMA ortholog data set to estimate the probabilitythat any given protein is membrane-bound as the number ofclades sharing it increases We find that the more universalthe protein the less likely it is to be membrane-bound (fig 4)

Since ortholog discovery depends on the successful detec-tion of homologs using tools such as BLAST the lower ho-mology of membrane proteins we report could have twomain causes (fig 1) First it is possible that membrane pro-teins evolve faster and hence their more divergent sequencesare picked up less frequently by homology-identification al-gorithms Second some of the absences may be true genelosses such that the orthologs are not found because they aregenuinely no longer there We show that both mechanismsare at play

Faster Evolution of Membrane Proteins and TheirOutside-Facing SectionsTo investigate whether the patterns above are due to mem-brane proteins having a higher divergence rate overall wecalculated Neirsquos sequence-diversity measure (p Nei and Li1979) for the 228148 OMA OGs shared by any three ormore species The results confirm previous reports on datasets with more limited phylogenetic ranges (Volkman et al2002 Julenius and Pedersen 2006) that membrane proteinsdiverge more quickly than water-soluble proteins (Welchrsquost-test tfrac14 1408 dffrac14 1426109 Pfrac14 2591045 rfrac14 012 fig5A) this result is consistent across the three domains of life(fig 5BndashD)

While the TMHMM algorithm has been shown to infertrans-membrane helical (TMH) regions with very high accu-racy (Krogh et al 2001) discerning the inside- versus outside-facing aqueous regions of TMH proteins is substantially morechallenging We downloaded the full nonredundant set ofsequences and annotations from the trans-membrane pro-tein data bank (PDBTM pdbtmenzimhu) (Tusnady et al2004) to assess the evolution of the three main regions oftrans-membrane proteins inside-facing aqueous membrane-

FIG 1 Two-fold effect of adaptation causes faster evolution of exter-nal sections and loss of homology in membrane proteins Adaptationto new functions and niches causes faster evolution for outside-facingsections (top) potentially contributing to divergence beyond recog-nition Other proteins may provide no advantage in the new envi-ronment and could be lost entirely over time (center) For simplicitythe species on the left is assumed to remain functionally identical tothe common ancestor (bottom)

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spanning and outside-facing aqueous Briefly this databasehas annotations where available for the sub-cellular localiza-tion of each amino acid in all membrane-protein structuresdeposited in the Protein Data Bank (PDB wwwrcsborg)(Berman et al 2000 Rose et al 2015) We performed aBLASTp search of the sequence of each PDB structure againstour subset of the OMA database aligned the sequences ofthe best-matching orthologous groups and sliced the align-ments vertically to obtain the inside-facing membrane-span-ning and outside-facing regions plus an ldquoaqueousrdquo

assemblage constructed by concatenating the inside and out-side portions (see Materials and Methods section for details)We next calculated Neirsquos sequence-diversity measure (p) foreach section of the protein alignments (fig 5E) The resultsconfirm that aqueous regions evolve faster than membrane-spanning regions (paired t-test tfrac14 887 dffrac14 309 Pfrac14 5951017 rfrac14 0450) Amongst the aqueous regions both ofwhich have faster rates than the membrane-spanning regionsoverall the outside-facing portions evolve faster than theirinside-facing counterparts (fig 5E paired t-test tfrac14 376

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FIG 2 Membrane proteins have fewer orthologs in all three domains of life The mean size of OMA Ortholog Groups (OGs) is substantially smallerfor membrane proteins in all 64 species in the EMBL-EBIrsquos list of reference proteomes studied (2 of the 66 species were not found in OMA at thetime of this analysis) Five-letter codes are OMA species identifiers details in supplementary table S1 Supplementary Material online Dark shadewater-soluble (WS) light shade membrane proteins (MP) Data represented as the mean number of orthologs that WSs and MPs of each genomehave in OMA62SEM (standard error of the mean)

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dffrac14 296 Pfrac14 207104 rfrac14 0213) These results are con-firmed using an additional estimate computed by buildingtrees for the sliced alignment portions and averaging thebranch lengths of all nodes within each tree (supplementaryfig S2 Supplementary Material online see Materials andMethods section for details) As before aqueous regions areshown to evolve faster than membrane-spanning regions(paired t-test tfrac14 102109 dffrac14 371 Pfrac14 1401016 rfrac14 0411) whereas specifically the outside-facing sections oncemore have faster rates than their corresponding inside-facing sections (paired t-test tfrac14 463 dffrac14 359 Pfrac14 522106 rfrac14 0237)

To control for potential errors in the automatic annota-tions of PDBTM we repeated our analysis by manually an-notating the 3 main regions (inside outside and membrane-spanning) of 12 membrane proteins that are highly shared inOMA including 1 outer-membrane beta-barrel porin and 11trans-membrane helical proteins The closest-matching struc-tural file was found by BLASTp search against the PDB subseton the NCBI server The subcellular location of each amino-acid residue was then assigned by inspecting the PDB struc-tures against the information in the corresponding primaryliterature (supplementary table S2 Supplementary Materialonline) Orthologs were assigned from the corresponding

OMA OG (except in the case of OmpF whose homologswere obtained from a BLASTp search against the nr database)The homologous sequences were aligned to the PDB se-quence alignments sliced and evolutionary rates estimatedusing Neirsquos p In 10 of the 12 proteins hand-annotated in thisway evolution occurs faster for outside-facing than for inside-facing aqueous regions (supplementary fig S3 SupplementaryMaterial online paired t-test tfrac14 497 dffrac14 11 Pfrac14 425104rfrac14 0832) Using the mean branch lengths of trees as an al-ternative estimate of evolutionary rates all 12 proteins showfaster rates in the outside-facing regions than in their inside-facing counterparts (supplementary fig S4 SupplementaryMaterial online paired t-test tfrac14 471 dffrac14 11 Pfrac14 637104 rfrac14 0818)

These findings are again widespread across the tree of lifeand apply to multiple types of proteins We note that thesepatterns hold true despite the fact that some aqueous pro-teins are exported from the cell and predictably evolve faster(Julenius and Pedersen 2006) whereas some membrane pro-teins especially in eukaryotes sit on organellar membranes(hence presumably evolve slower)

Extracellular Water-Soluble Proteins Have FewerOrthologs than Membrane ProteinsTo estimate the effect of extracellularity we used the predic-tions of the SignalP package (Petersen et al 2011) Briefly thissoftware detects fragments of amino-acid sequences likely totarget proteins to the secretory pathway SignalP detectsthese signal peptides in most Gram-positive and Gram-negative bacteria as well as eukaryotes (note that the soft-ware is presently unable to reliably predict signal peptides inarchaea) We re-classified all water-soluble OMA OGs as ei-ther intracellular (ie cytosolic) or extracellular (ie contain-ing a signal peptide and not being a membrane protein)based on SignalP predictions Extracellular proteins are sharedon average by notably fewer clades than intracellular (mostsimply cytosolic) proteins (fig 6A mean OG size of intracel-lular WS proteins 860 versus 655 for extracellular Welchrsquos t-test tfrac14 2762 dffrac14 296020 Pfrac14 74010166 rfrac14 016)Membrane proteins are intermediate less widespread thanintracellular proteins but more so than extracellular onesSimilarly grouping proteins by the proportion of their resi-dues that are exposed to the environment produces a patternof falling phylogenetic spread as extracellular exposure in-creases (fig 6B linear regression on data binned as describedin Materials and Methods F(18)frac142545 Pfrac14 000147rfrac14 0859) The evolutionary rates measured by Neirsquos p arefaster for extracellular than for intracellular water-soluble pro-teins (fig 6C mean for intracellular WS proteins 0592 versus0610 for extracellular Welchrsquos t-test tfrac142267 dffrac14 1716309Pfrac14 37010112 rfrac14 0171) whereas membrane proteinsshow a slightly higher rate

Membrane Proteins Have Been Lost More Oftenwithin Closely Related SpeciesThe results in figure 5 suggest that the higher evolutionaryrates of membrane proteins could through divergence be-yond recognition lead to the loss of homology reported

FIG 3 Water-soluble orthologous groups are substantially larger onaverage than membrane-protein groups but the effect decreases asorganismal complexity increases Dividing the average size of water-soluble orthologous groups (OGs) of each species over the corre-sponding average size of membrane-protein OGs gives an indicationof the magnitude of the effect in figure 2 for the different groups ofspecies (A) The ratio of the mean sizes of water-soluble over mem-brane protein OGs isgt 1 for all species studied (ie each WS bar isalways larger than its corresponding MP bar in figure 2) but the effectdecreases as cellular and organismal complexity increase from pro-karyotes to unicellular eukaryotes to multicellular eukaryotes (B)Filtering for orthologous groups composed of both eukaryotes andprokaryotes keeps the relationship between unicellular and multi-cellular eukaryotes and indeed increases the effect whereas prokary-otes remain largely unaltered This suggests that membrane proteinsancestral to eukaryotes (ie with ancestors in archaea or bacteria)have been lost more often than their water-soluble counterpartsBold black lines represent the median white lines the mean andboxes and whiskers are standard in R at a 6 15IQR (inter-quartilerange) threshold Numbers below the boxes indicate sample sizes

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earlier (fig 2 and supplementary fig S1 SupplementaryMaterial online) To determine whether true gene loss hasoccurred as well we repeated the presencendashabsence analysis(fig 2) on sets of proteins predicted to be ancestral to closelyrelated species and strains We selected all prokaryotic cladeswith 10 or more closely related species in OMA and assumedthat proteins shared by more than half of the members of theclade were ancestral (see Materials and Methods section) Weconsidered that any clades that do not share such ancestralproteins represent true gene losses on the assumption that inclosely related strains and species orthologs are unlikely tohave diverged beyond recognition

The results show that the mean numbers of species sharingeach of these ancestral OGs are lower for membrane-boundthan for water-soluble proteins across 31 of the 35 cladesstudied (fig 7 paired t-test tfrac14 731 dffrac14 34 Pfrac14 181108rfrac14 0782) That is membrane proteins have been lost moreoften than water-soluble proteins between closely relatedtaxa confirming that true gene loss can also account inpart for the lower homology of membrane proteins reportedhere

DiscussionWe report that membrane proteins have fewer orthologs thanwater-soluble proteins across the entire tree of life (figs 2 and4) In principle this finding could be due to a higher evolu-tionary rate which prevents sequence-searching algorithms

such as BLAST from detecting homologs beyond a giventhreshold or it could correspond to true gene loss Weshow that both mechanisms are at play First we demonstratethat evolutionary rates are faster for membrane proteins thanfor water-soluble proteins across the whole tree of life and ineach of the three domains of archaea bacteria and eukaryotesindependently (fig 5AndashD) Significantly the evolutionary ratesof membrane proteins are faster in the outside-facing aqueousregions than in their inside-facing counterparts (fig 5E andsupplementary figs S2ndashS4 Supplementary Material online)Second our analysis of closely related species shows that pre-dicted ancestral proteins have been lost more frequently ifthey were membrane bound (fig 7) This indicates that thelower homology of membrane proteins is not only due todivergence beyond sequence recognition but also that truegene loss has occurred

It has been reported that exported water-soluble proteinsevolve faster than cytosolic proteins and indeed faster thanthe external sections of membrane proteins in mammals(Julenius and Pedersen 2006) Our hypothesis predicts thata similar pattern of low homology and greater gene lossshould be observed for excreted water-soluble proteins Weconfirm that this is indeed the case (fig 6A and B) withuniversality decreasing the further out the cell from cytosolicto membrane-bound to extracellular proteins

Membrane-bound and extracellular proteins are in generalless central to metabolic networks and functions (Julenius

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FIG 4 The probability of a protein being membrane-bound falls with wider distribution (A) A logistic regression shows that the probability that agene is a membrane protein falls significantly with increasing number of clades sharing it for OGs shared by any 3 or more separate clades Thepattern remains when considering each of the three domains separately (BndashD) The points and vertical stripes correspond to the proportions ofMPs amongst genes shared by increasingly large numbers of clades divided in 10 bins No proteins retrieved were shared by over 90 of the 489taxa in (A) In all cases the final bins have proportion zero ie no highly shared proteins are membrane-bound Note that the points and bins areprovided for reference only logistic regressions were performed on the individual ortholog clusters (ie the probability curves were derivedindependently see Materials and Methods section)

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and Pedersen 2006) so the patterns we report could becaused by stronger selective constraints operating on cyto-solic proteins and a comparatively relaxed evolution of moreperipheral proteins However at least for mammals the fasterevolutionary rates of membrane-bound and extracellular pro-teins do not seem to depend on the essentiality of the pro-teins themselves (Liao et al 2010) suggesting thatmechanisms other than purifying selection on purportedlyless crucial membrane-bound and exported proteins are atplay

Our findings suggest the operation of a more general evo-lutionary principle membrane proteins evolve faster becausethey face stronger adaptive selection in changing environ-ments whereas cytosolic proteins are under more stringentpurifying selection in the homeostatic interior of the cell(fig 1) The outside-facing sections of membrane-spanningproteins are closely involved in adaptation to new environ-ments and functions and so are more likely to diverge overtime than the cytosolic portions As emerging species colo-nize novel environments or specialize in new tasks theoutside-facing sections are subject to stronger positive selec-tion whereas rate-limiting purifying selection prevails in themembrane-spanning and inside-facing portions (fig 5E and Fsupplementary figs S2ndashS4 Supplementary Material online)Novel or changing environments are also likely to reduce theutility of existing membrane proteins leading to loss overtime and accounting for the absences that we observe inclosely related species (fig 7) Our hypothesis immediatelysuggests that this effect should be strongest in prokaryotesweaker in unicellular eukaryotes (where intracellular organ-elles can provide an additional homeostatic environment formembrane proteins) and weakest in multicellular eukaryotes(where even extracellular proteins face a homeostatic envi-ronment provided by tissues and organs) That is indeed thecase (fig 3A) although the difference in size of orthologgroups between membrane proteins and water-soluble pro-teins remains substantial even in multicellular eukaryotesMoreover the difference between water-soluble andmembrane-bound proteins is greater for proteins most sim-ply assumed to be ancient to eukaryotes (fig 3B) This rein-forces the suggestion that ancient membrane-bound proteinsare more likely to either diverge beyond recognition or be lostentirely than their water-soluble counterparts

This broad evolutionary perspective provides a frameworkfor interpreting a number of earlier findings that have proveddifficult to generalize Previous results show that water-soluble proteins secreted from the cell evolve faster than cy-tosolic proteins in mammals and yeast and that the externalportions of membrane proteins evolve faster than the internaldomains (Julenius and Pedersen 2006) However given thecomplexity of mammalian species a focus on this taxonomicclass does not lend itself to generalizations about purifyingselection or adaptation to changing extracellular environ-ments Similarly the G-protein-coupled receptor superfamilyis known to evolve faster in its extracellular portions than inthe transmembrane and cytosolic regions but this has againbeen interpreted in terms of particular functional and struc-tural constraints (Tourasse and Li 2000 Lee et al 2003) InGram-negative bacteria degradation of xenobiotic toxic sub-stances occurs in the periplasmic space (Kawai 1999 Nagataet al 1999) making evolutionary pressure stronger on theexternal regions than in the homeostatic interior Signal pep-tides have been shown to evolve rapidly in both prokaryotesand eukaryotes pointing to positive selection on these secre-tory membrane-targeting fragments (Li et al 2009) Finallyparasitic interactions can promote the rapid evolution ofmembrane proteins especially the external loops involveddirectly in antigen interactions (Volkman et al 2002 Plotkin

FIG 5 Membrane proteins evolve faster especially in their externalsections (AndashD) Neirsquos sequence diversity measure (p) is higher formembrane proteins (MP) than for water-soluble proteins (WS) inthe full set of OMA OGs (A) as well as for each of the three domainsof life separately (BndashD) indicating that evolution occurs faster forMPs (E) For sections of membrane-protein OMA OGs annotatedfrom the structures in the PDBTM database Neirsquos p shows that aque-ous sections evolve faster overall than membrane-spanning sectionsSplitting the aqueous sequences into outside- and inside-facing sec-tions confirms that regions exposed to the environment evolve fasterthan those facing the cytosol Boxplot ranges as in figure 3 withnotches at the 95 confidence-interval around the median All com-parisons of WS to MP in (AndashD) as well as inside and outside portionsto each other or to membrane-spanning portions in (E) had Plt0001Digits below the boxes indicate the numbers of orthologous groups

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et al 2004) Parasite membrane proteins face positive selectivepressure from recognition by the host but these red-queendynamics have not been extended beyond parasitendashhost in-teractions We show that each of these specific instances canbe generalized for membrane proteins as a class across thetree of life When interpreted in a more comprehensive con-text all these observations point to faster evolution outsidethe cell in response to changing environments or functions

We have not considered the effects of horizontal genetransfer (HGT) a major force in microbial evolution as theunequivocal detection and ecological significance of ancientHGT events is still a hotly debated topic (Philippe andDouady 2003 Dagan and Martin 2007 Koonin 2014 2015Puigbo et al 2014 Akanni et al 2015 Boothby et al 2015 Katz2015 Ravenhall et al 2015 Soucy et al 2015 Koutsovouloset al 2016) Horizontally transferred genes tend to be inte-grated at the periphery of metabolic networks whereas genesat the core tend to be more evolutionarily conserved (Palet al 2005) As noted earlier at the level of cellular genenetworks extracellular proteins could be considered periph-eral whereas intracellular proteins are more central and soshould be more conserved (Julenius and Pedersen 2006) Butour data suggest that membrane proteins are not more likelyto be lost (or horizontally transferred) simply because they areperipheral to gene networks The observation that theoutside-facing portions of membrane proteins evolve fasterthan their cytosolic counterparts (fig 5E and F) and that thegreater the extracellular content the less widely conserved theprotein (fig 6A and B) are more consistent with selectionoperating differently outside the cell

We conclude that adaptation to novel environments andfunctions underlies the lower homology of membrane pro-teins across the tree of life Life is defined by its cellular naturethe inside of a living cell is separated from its environment byan organic membrane Cells must constantly interact withvarying environments while maintaining tight internal ho-meostasis The interactions between the inside and outsideof the cell are largely mediated by membrane-bound and

exported proteins so elucidating their evolution is centralto understanding the origins and evolution of life For thesame reasons membrane proteins have great medical impor-tance Over half of all known drug targets are membraneproteins so our findings may help to explain why the pro-gression of new drugs from animal models into human trialsis so often unsuccessful (Holmes et al 2011 Denayer et al2014) Our results are also of practical importance in phylo-genetics if membrane proteins are less than half as likely to beconserved widely across the tree of life then homologysearches will often be confounded as could molecular clocksFaster evolution outside the cell makes simple intuitive sensebut the strength of this signal across the whole tree of lifeelevates what has been seen as an interesting sporadic patterninto a general principle of evolution

Materials and Methods

Acquisition of OrthologsThe full set of ortholog groups (OGs) from the OMA databasewas downloaded from the OMA server at wwwomabrowserorgexport September 2014 release

The species in the list of reference proteomes for figure 2were obtained from EMBL-EBI at wwwebiacukreference_proteomes (last accessed August 8 2016) Two of the 66species in the list were not found on OMA (supplementarytable S1 Supplementary Material online) For each species infigure 2 the downloaded OMA data set was scanned for anyOGs containing the species of interest and the size of the OGdetermined (ie the total number of orthologs in the groupor equivalently the number of species with an identifiableortholog) This implies that several OGs were counted mul-tiple times ie if they were shared by two or more of the 64species in the data set Removing these duplications had noeffect on our conclusions (data available upon request)

The set of 883176 OMA OGs includes multiple orthologsshared by multiple strains of the same species (eg Escherichiacoli) so as a strategy to avoid oversampling in the

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FIG 6 Extracellular proteins evolve faster and are shared by fewer species on average (A) The mean ortholog cluster size is smaller for extracellularwater-soluble than for membrane-bound proteins whereas intracellular (cytosolic) proteins are shared by more species on average (B) Binningproteins by the proportion of their amino-acid residues that are extracellular produces the mean OG sizes represented by the points whereas theline is a simple linear regression on these points See Materials and Methods section for details (C) The evolutionary rates estimated by Neirsquos p arehigher for exported water-soluble proteins than for their intracellular counterparts whereas membrane proteins show a slightly higher rate overallDigits below the boxes indicate the numbers of orthologous groups

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phylogenetic-distribution analysis of figure 4 one sequencewas chosen per clade at the sixth level of taxonomic differ-entiation according to the NCBI taxonomy browser As anexample the full NCBI taxonomic lineage for E coli is1Bacteriagt 2Proteobacteriagt 3Gammaproteobacteriagt4Enterobacterialesgt 5Enterobacteriaceaegt 6Escherichiagt7Escherichia coli from where the sixth taxonomic level isldquoEscherichiardquo similarly the equivalent for humans isldquoDeuterostomiardquo from 1Eukaryotagt 2Opisthokontagt

3Metazoagt 4Eumetazoagt 5Bilateriagt 6DeuterostomiaOnly OGs with 3 or more different such clades were kept Thisleft a total of 228148 OGs When multiple sequences werefound for the same clade as defined earlier a representativewas chosen from well-annotated species (eg Escherichia coliSaccharomyces cerevisiae Homo sapiens Methanosarcina ace-tivorans) where available or at random

Since each protein was classified in a binary fashion aseither WS or MP (except for the analyses in fig 6) the logistic

FIG 7 Ancestral membrane proteins have been lost more frequently (A) Predicted ancestral proteins (defined as shared by at least half of themembers of a clade) are shared by a smaller proportion of members in the clade if they are membrane proteins for 31 of the 35 groups studied(exceptions are Neisseria Rickettsia Salmonella and Yersinia) Dark shade water-soluble light shade membrane proteins First six pairs (blue) arearchaeal clades the remainder (yellow) are bacterial Error bars 2SEM Digits below bars indicate the numbers of orthologous groups (B) Valuesas in (A) paired and without error bars Red-dashed results with higher mean proportion of sharing species for MP than WS Yellow-dotted resultswith MPltWS but P-value over a cutoff of 005 in a two-sample Welch t-test Green-solid results with Plt005

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regressions of figure 4 were produced by fitting a quasi-binomial model to the type of protein (0 for WS and 1 forMP) using as predictor the number of orthologs in the cluster(ie the size of the OMA OG or more simplistically the num-ber of taxa that have an identifiable ortholog of the protein inOMA) The points were produced entirely independently bybinning the data in 10 increments of how many taxa shareeach protein or size of the OG That is for figure 4A the totalnumber of taxa is 489 so proteins in the first bin are shared bybetween 3 and 49 clades The point represents the proportionof those proteins that are MPs

BLAST SearchesThe full proteomes of six representative species for supplementary fig S1 Supplementary Material online were pro-cured from the EMBL-EBI list of reference proteomes Thecomplete nonredundant (nr) protein database was down-loaded from NCBI The BLASTp algorithm and softwarewas also downloaded from NCBI and run locally for eachprotein in each of the six selected proteomes SignificantBLASTp matches were defined as having an e-value lt1010

and a query coverage of at least 70 when multiple hits werefound for the same species only one hit was counted

Separately a BLAST-able database was created from allsequences in the 228148 selected OMA ortholog groups us-ing the makeblastdb command in the NCBI BLAST suiteBLASTp was then used to detect hits of PDB sequencesagainst this local OMA OGs database for figure 5E the ortho-log group containing the best hit was found aligned andsliced into portions as described below in ldquoEstimation of evo-lutionary ratesrdquo Whenever two PDBs retrieved the same OGas their best hit the one with the best alignment (judged byNeirsquos sequence-diversity measure p) was kept

Identification of Membrane ProteinsMembrane proteins were annotated using the predictions ofthe TMHMM 20c algorithm (Krogh et al 2001) This algo-rithm predicts only trans-membrane alpha helical proteins soon preliminary tests undetected ortholog groups marked asporins or integral membrane proteins in their descriptions inOMA were further annotated as MPs Gene Ontology anno-tations where available were used in addition to identifyfurther MPs in these preliminary tests All other proteinswere assumed to be WS These additional classifications ofMPs produced only minor changes that did not alter ourconclusions (data available upon request) so to ensure repro-ducibility and avoid unpredictable effects of the sparse anno-tations for all results in the article MPs were annotated usingonly the predictions of the TMHMM algorithm

Identification and Analysis of Extracellular Proteinsand RegionsExtracellular (exported) proteins for analyses in figure 6 wereidentified using SignalP 41 (Petersen et al 2011) This soft-ware cannot presently provide reliable predictions of signalpeptides in archaea or bacterial Tenericutes so results forthese were ignored If the majority of orthologs within anortholog group were identified positively by SignalP the

OG was considered to contain a signal peptide These classi-fications were used to separate water-soluble proteins intocytosolic and exported for figure 6A and C For figure 6B theproportion of extracellular residues was computed for mem-brane proteins by parsing the predictions of TMHMM dis-cussed earlier For each orthologous group the lengths ofoutside-facing residues in proteins predicted as containingtrans-membrane helices were summed and divided overthe sum of the total sequence lengths of the same proteinsThis proportion was assigned to the corresponding orthologgroup and the data binned in 10 intervals as shown in figure6B In addition water-soluble proteins predicted by theSignalP analysis as cytosolic (negative results) were added tothe first bin (00ndash01) whereas predicted extracellular proteinswere added to the last bin (09ndash10) The points were thencomputed by averaging the ortholog-group sizes within eachbin The predictions of SignalP were only used for figure 6 andits related analyses In all other analyses in the article weconsidered only MPs versus WSs in general

Estimation of Evolutionary Rates and SelectiveConstraints Slicing of Membrane-Protein PortionsFor figure 5AndashD the protein sequences of each of the 228148OMA OGs shared by three or more clades were aligned usingMAFFT (Katoh and Standley 2013) Neirsquos sequence-diversitymeasure (p Nei and Li 1979) was calculated by averaging thenumber of differences per alignment position per pair of se-quences and then averaging these over the number of pairsfor each group of orthologs These values were used in figure5AndashD and in the re-classifications of water-soluble proteins asextracellular versus intracellular in figure 6C Neirsquos p was com-puted in the same manner for figure 5E and supplementaryfigure S3 Supplementary Material online

For results in figure 5E the entire nonredundant set of PDBamino-acid sequences and annotations was downloadedfrom pdbtmenzimhu (Tusnady et al 2004) This data set isconstantly updated to include all PDB structures for mem-brane proteins in the PDB database and the files parsed intoannotations for the subcellular localization of each amino acidin each of these structures where the information is available(often the crystal structures have unresolved portions notablyloops and in other cases the researchers do not reportwhether an aqueous section is inside- or outside-facing inwhich case the protein was ignored altogether) At the timeof this analysis there were 576 nonredundant integral mem-brane proteins in PDBTM (496 annotated as alpha helices and80 as beta barrels) 378 of which unambiguously specifiedinside- versus outside-facing aqueous regions Homologswere procured by BLASTp search against a local subset ofthe OMA database created as described earlier and align-ments produced with MAFFT To ldquoslicerdquo (ie split vertically)the multiple-sequence alignments (MSAs) used in figure 5Eand supplementary figures S2ndashS4 Supplementary Materialonline into the membrane-spanning inside outside andaqueous (which includes both inside- and outside-facing) sec-tions the PDBTM annotations (fig 5E and supplementary figS2 Supplementary Material online) or the hand-annotatedpositions (supplementary figs S3 and S4 Supplementary

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Material online) for the reference PDB protein sequence wereused to establish the sub-cellular location of each amino acidEach position was then sliced as described in the toy examplein figure 8 The ldquoaqueousrdquo portions were constructed by con-catenating the inside and outside alignments

As an additional measure to confirm our results we builttrees using FastTree 20 (Price et al 2010) with default options(JonesndashTaylorndashThornton model with CAT approximation)for the full alignment and for each of the three sliced portionsand computed the mean of the branch lengths of all nodeswithin each tree The branch lengths in a tree correspond tothe number of substitutions per site so we used their mean asa further estimate of evolutionary rate in supplementary figures S2 and S4 Supplementary Material online Branchlengths were extracted directly from the FastTree outputtrees computed on the whole and sliced MAFFT alignments

Analysis of Closely Related SpeciesDue to the difficulty of reliably inferring phylogenetic treesspanning all three domains of life as well as widespread hor-izontal gene transfer within and across the domains we useda coarse but robust approach to infer genes present in thecommon ancestor of closely related taxa clades with 10 ormore closely related species or strains of archaea and bacteriawere detected by exploring the NCBI taxonomy of speciesincluded in OMA (omabrowserorgomaexport lastaccessed August 8 2016) These clades of ldquoclosely relatedrdquospecies in figure 7 were defined as sharing members at thefifth or higher taxonomic level of differentiation according tothe NCBI lineages (as earlier) The pre-computed OMA dataset was then scanned for any OGs containing members ofeach of these clades OGs shared by more than half of themembers of the clade were considered ancestral and the restwere ignored These ancestral OGs were then classified aseither MPs or WSs using a majority census for the predictionsof the TMHMM algorithm on each sequence in the group

BioinformaticsBioPython (Cock et al 2009) ETE (Huerta-Cepas et al 2010)TMHMM (Krogh et al 2001) SignalP (Petersen et al 2011)and R (R Core Team 2014) were used widely in the calcula-tions and analyses in this article Data can be accessed atdxdoiorg105061dryad00731

Supplementary MaterialSupplementary tables S1 and S2 and figures S1ndashS4 are avail-able at Molecular Biology and Evolution online (httpwwwmbeoxfordjournalsorg)

AcknowledgmentsThe authors thank Adrian Altenhoff Tom Richards KevinGori Steven Muller and Konstantinos Angelis for their sup-port and suggestions This work was supported by theEngineering and Physical Sciences Research Council (EPSRCEPF5003511 to VS and AP EPI0179091 and EPK0386561 to AP) UCL-CoMPLEX (to VS) the European MolecularBiology Organization (to VS) the Biotechnology andBiological Sciences Research Council (BBSRC BBL0182411to CD) the Swiss National Science Foundation (150654 toCD) the Leverhulme Trust (to NL) and the UCL ResearchFrontiers Origins of Life Programme (to NL) The authorsdeclare no competing interests

ReferencesAkanni WA Siu-Ting K Creevey CJ McInerney JO Wilkinson M Foster

PG Pisani D 2015 Horizontal gene flow from Eubacteria toArchaebacteria and what it means for our understanding of eukar-yogenesis Philos Trans R Soc B Biol Sci 37020140337

Altenhoff AM Skunca N Glover N Train C-M Sueki A Pilizota I Gori KTomiczek B Muller S Redestig H et al 2015 The OMA orthologydatabase in 2015 function predictions better plant support syntenyview and other improvements Nucleic Acids Res 43D240ndashD249

Altschul SF Gish W Miller W Myers EW Lipman DJ 1990 Basic localalignment search tool J Mol Biol 215403ndash410

Berman HM Westbrook J Feng Z Gilliland G Bhat TN Weissig HShindyalov IN Bourne PE 2000 The Protein Data Bank NucleicAcids Res 28235ndash242

Boothby TC Tenlen JR Smith FW Wang JR Patanella KA Osborne ETintori SC Li Q Jones CD Yandell M et al 2015 Evidence for ex-tensive horizontal gene transfer from the draft genome of a tardi-grade Proc Natl Acad Sci USA 11215976ndash15981

Cock PJA Antao T Chang JT Chapman BA Cox CJ Dalke A Friedberg IHamelryck T Kauff F Wilczynski B et al 2009 Biopython freelyavailable Python tools for computational molecular biology andbioinformatics Bioinformatics 251422ndash1423

Dagan T Martin W 2007 Ancestral genome sizes specify the minimumrate of lateral gene transfer during prokaryote evolution Proc NatlAcad Sci USA 104870ndash875

Denayer T Stohr T Van Roy M 2014 Animal models in translationalmedicine validation and prediction New Horizons Transl Med25ndash11

Franzosa EA Xue R Xia Y 2013 Quantitative residue-level structure-evolution relationships in the yeast membrane proteome GenomeBiol Evol 5734ndash744

Hedin LE Illergard K Elofsson A 2011 An introduction to membraneproteins J Proteome Res 103324ndash3331

Holmes AM Solari R Holgate ST 2011 Animal models of asthma valuelimitations and opportunities for alternative approaches DrugDiscov Today 16659ndash670

Huerta-Cepas J Dopazo J Gabaldon T 2010 ETE a python environmentfor tree exploration BMC Bioinformatics 1124

Julenius K Pedersen AG 2006 Protein evolution is faster outside the cellMol Biol Evol 232039ndash2048

Katoh K Standley DM 2013 MAFFT multiple sequence alignment soft-ware version 7 improvements in performance and usability Mol BiolEvol 30772ndash780

Katz LA 2015 Recent events dominate interdomain lateral gene trans-fers between prokaryotes and eukaryotes and with the exception of

FIG 8 An example of the alignment slicing process Here i m and orepresent that the corresponding amino acid in the PDB structure isannotated as inside membrane-spanning or outside (respectively)either in the PDBTM database for figure 5E or in the 12 annotationscreated by directly inspecting the PDB structure against the primaryliterature for supplementary figures S3 and S4 Supplementary Materialonline In the example here positions 1ndash2 and 15ndash19 are inside 6ndash7 areoutside 3ndash5 8ndash9 25 and 12ndash14 are membrane-spanning and 10ndash1120 are not present in the reference sequence and are therefore ignored

Membrane Proteins Are Dramatically Less Conserved doi101093molbevmsw164 MBE

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endosymbiotic gene transfers few ancient transfer events persistPhilos Trans R Soc B Biol Sci 37020140324

Kawai F 1999 Sphingomonads involved in the biodegradation of xeno-biotic polymers J Ind Microbiol Biotechnol 23400ndash407

Koonin EV 2014 Horizontal transfer beyond genes Proc Natl Acad SciUSA 11115865ndash15866

Koonin EV 2015 The turbulent network dynamics of microbial evolu-tion and the statistical tree of life J Mol Evol 80244ndash250

Koutsovoulos G Kumar S Laetsch DR Stevens L Daub J Conlon CMaroon H Thomas F Aboobaker AA Blaxter M 2016 Noevidence for extensive horizontal gene transfer in the genomeof the tardigrade Hypsibius dujardini Proc Natl Acad Sci USA1135053ndash5058

Krogh A Larsson B von Heijne G Sonnhammer EL 2001 Predictingtransmembrane protein topology with a hidden Markov modelapplication to complete genomes J Mol Biol 305567ndash580

Lee A Rana BK Schiffer HH Schork NJ Brann MR Insel PA Weiner DM2003 Distribution analysis of nonsynonymous polymorphismswithin the G-protein-coupled receptor gene family Genomics81245ndash248

Li Y-D Xie Z-Y Du Y-L Zhou Z Mao XM Lv L-X Li Y-Q 2009 The rapidevolution of signal peptides is mainly caused by relaxed selection onnon-synonymous and synonymous sites Gene 4368ndash11

Liao BY Weng MP Zhang J 2010 Impact of extracellularity on theevolutionary rate of mammalian proteins Genome Biol Evol239ndash43

Mitchell P 1957 The origin of life and the formation and organisingfunctions of natural membranes In Oparin AI Pasynskii AGBraunshtein AE Pavlovskaya TE editors Proceedings of the FirstInternational Symposium on the Origin of Life on the EarthMoscow Academy of Sciences (USSR) p 229ndash234

Mitchell P 1961 Coupling of phosphorylation to electron and hydrogentransfer by a chemi-osmotic type of mechanism Nature191144ndash148

Nagata Y Futamura A Miyauchi K Takagi M 1999 Two differenttypes of dehalogenases LinA and LinB involved in c-hexachlorocy-clohexane degradation in Sphingomonas paucimobilis UT26 are lo-calized in the periplasmic space without molecular processing JBacteriol 1815409ndash5413

Nei M Li WH 1979 Mathematical model for studying genetic variationin terms of restriction endonucleases Proc Natl Acad Sci USA765269ndash5273

Oberai A Joh NH Pettit FK Bowie JU 2009 Structural imperativesimpose diverse evolutionary constraints on helical membrane pro-teins Proc Natl Acad Sci USA 10617747ndash17750

Overington J Al-Lazikani B Hopkins A 2006 How many drug targets arethere Nat Rev Drug Discov 5993ndash996

Pal C Papp B Lercher MJ 2005 Adaptive evolution of bacterial meta-bolic networks by horizontal gene transfer Nat Genet 371372ndash1375

Petersen TN Brunak S von Heijne G Nielsen H 2011 SignalP 40 dis-criminating signal peptides from transmembrane regions NatMethods 8785ndash786

Philippe H Douady CJ 2003 Horizontal gene transfer and phylogeneticsCurr Opin Microbiol 6498ndash505

Plotkin JB Dushoff J Fraser HB 2004 Detecting selection using a singlegenome sequence of M tuberculosis and P falciparum Nature428942ndash945

Price MN Dehal PS Arkin AP 2010 FastTree 2 ndash approximatelymaximum-likelihood trees for large alignments PLoS One 5e9490

Puigbo P Lobkovsky AE Kristensen DM Wolf YI Koonin EV 2014Genomes in turmoil quantification of genome dynamics in prokary-ote supergenomes BMC Biol 1266

R Core Team 2016 R A language and environment for statistical com-puting R Vienna (Austria) R Foundation for Statistical Computing[cited 8 Aug 2016] Available at httpswwwR-projectorg

Ravenhall M Skunca N Lassalle F Dessimoz C 2015 Inferring horizontalgene transfer PLoS Comput Biol 11e1004095

Rose PW Prlic A Bi C Bluhm WF Christie CH Dutta S Green RKGoodsell DS Westbrook JD Woo J et al 2015 The RCSB ProteinData Bank views of structural biology for basic and applied researchand education Nucleic Acids Res 43D345ndashD356

Singer SJ Nicolson GL 1972 The fluid mosaic model of the structure ofcell membranes Science 175720ndash731

Soucy SM Huang J Gogarten JP 2015 Horizontal gene transfer buildingthe web of life Nat Rev Genet 16472ndash482

Tourasse NJ Li WH 2000 Selective constraints amino acid compositionand the rate of protein evolution Mol Biol Evol 17656ndash664

Tusnady GE Dosztanyi Z Simon I 2004 Transmembrane proteins in theProtein Data Bank identification and classification Bioinformatics202964ndash2972

Volkman SK Hartl DL Wirth DF Nielsen KM Choi M Batalov S Zhou YPlouffe D Le Roch KG Abagyan R et al 2002 Excess polymorphismsin genes for membrane proteins in Plasmodium falciparum Science298216ndash218

Sojo et al doi101093molbevmsw164 MBE

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ownloaded from