The heptad repeat region is a major selection target in MERS-CoV and related coronaviruses
Identifieur interne : 000426 ( Pmc/Corpus ); précédent : 000425; suivant : 000427The heptad repeat region is a major selection target in MERS-CoV and related coronaviruses
Auteurs : Diego Forni ; Giulia Filippi ; Rachele Cagliani ; Luca De Gioia ; Uberto Pozzoli ; Nasser Al-Daghri ; Mario Clerici ; Manuela SironiSource :
- Scientific Reports [ 2045-2322 ] ; 2015.
Abstract
Middle East respiratory syndrome coronavirus (MERS-CoV) originated in bats and spread to humans via zoonotic transmission from camels. We analyzed the evolution of the
The online version of this article (doi:10.1038/srep14480) contains supplementary material, which is available to authorized users.
Url:
DOI: 10.1038/srep14480
PubMed: 26404138
PubMed Central: 4585914
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PMC:4585914Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">The heptad repeat region is a major selection target in MERS-CoV and related coronaviruses</title><author><name sortKey="Forni, Diego" sort="Forni, Diego" uniqKey="Forni D" first="Diego" last="Forni">Diego Forni</name><affiliation><nlm:aff id="Aff1">Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</nlm:aff></affiliation></author><author><name sortKey="Filippi, Giulia" sort="Filippi, Giulia" uniqKey="Filippi G" first="Giulia" last="Filippi">Giulia Filippi</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.7563.7</institution-id><institution-id institution-id-type="ISNI">0000 0001 2174 1754</institution-id><institution>Department of Biotechnology and Biosciences,</institution><institution>University of Milan-Bicocca,</institution></institution-wrap>Milan, 20126 Italy</nlm:aff></affiliation></author><author><name sortKey="Cagliani, Rachele" sort="Cagliani, Rachele" uniqKey="Cagliani R" first="Rachele" last="Cagliani">Rachele Cagliani</name><affiliation><nlm:aff id="Aff1">Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</nlm:aff></affiliation></author><author><name sortKey="De Gioia, Luca" sort="De Gioia, Luca" uniqKey="De Gioia L" first="Luca" last="De Gioia">Luca De Gioia</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.7563.7</institution-id><institution-id institution-id-type="ISNI">0000 0001 2174 1754</institution-id><institution>Department of Biotechnology and Biosciences,</institution><institution>University of Milan-Bicocca,</institution></institution-wrap>Milan, 20126 Italy</nlm:aff></affiliation></author><author><name sortKey="Pozzoli, Uberto" sort="Pozzoli, Uberto" uniqKey="Pozzoli U" first="Uberto" last="Pozzoli">Uberto Pozzoli</name><affiliation><nlm:aff id="Aff1">Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</nlm:aff></affiliation></author><author><name sortKey="Al Daghri, Nasser" sort="Al Daghri, Nasser" uniqKey="Al Daghri N" first="Nasser" last="Al-Daghri">Nasser Al-Daghri</name><affiliation><nlm:aff id="Aff3"><institution-wrap><institution-id institution-id-type="GRID">grid.56302.32</institution-id><institution-id institution-id-type="ISNI">0000 0004 1773 5396</institution-id><institution>Biomarkers research program, Biochemistry Department,</institution><institution>College of Science, King Saud University,</institution></institution-wrap>Riyadh, 11451 (KSA) Kingdom of Saudi Arabia</nlm:aff></affiliation><affiliation><nlm:aff id="Aff4"><institution-wrap><institution-id institution-id-type="GRID">grid.56302.32</institution-id><institution-id institution-id-type="ISNI">0000 0004 1773 5396</institution-id><institution>Prince Mutaib Chair for Biomarkers of Osteoporosis, Biochemistry Department,</institution><institution>College of science, King Saud University,</institution></institution-wrap>Riyadh, Kingdom of Saudi Arabia</nlm:aff></affiliation></author><author><name sortKey="Clerici, Mario" sort="Clerici, Mario" uniqKey="Clerici M" first="Mario" last="Clerici">Mario Clerici</name><affiliation><nlm:aff id="Aff5"><institution-wrap><institution-id institution-id-type="GRID">grid.4708.b</institution-id><institution-id institution-id-type="ISNI">0000 0004 1757 2822</institution-id><institution>Department of Physiopathology and Transplantation,</institution><institution>University of Milan,</institution></institution-wrap>Milan, 20090 Italy</nlm:aff></affiliation><affiliation><nlm:aff id="Aff6"><institution-wrap><institution-id institution-id-type="GRID">grid.414603.4</institution-id><institution>Don C. Gnocchi Foundation ONLUS, IRCCS,</institution></institution-wrap>Milan, 20148 Italy</nlm:aff></affiliation></author><author><name sortKey="Sironi, Manuela" sort="Sironi, Manuela" uniqKey="Sironi M" first="Manuela" last="Sironi">Manuela Sironi</name><affiliation><nlm:aff id="Aff1">Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">26404138</idno><idno type="pmc">4585914</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4585914</idno><idno type="RBID">PMC:4585914</idno><idno type="doi">10.1038/srep14480</idno><date when="2015">2015</date><idno type="wicri:Area/Pmc/Corpus">000426</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000426</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">The heptad repeat region is a major selection target in MERS-CoV and related coronaviruses</title><author><name sortKey="Forni, Diego" sort="Forni, Diego" uniqKey="Forni D" first="Diego" last="Forni">Diego Forni</name><affiliation><nlm:aff id="Aff1">Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</nlm:aff></affiliation></author><author><name sortKey="Filippi, Giulia" sort="Filippi, Giulia" uniqKey="Filippi G" first="Giulia" last="Filippi">Giulia Filippi</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.7563.7</institution-id><institution-id institution-id-type="ISNI">0000 0001 2174 1754</institution-id><institution>Department of Biotechnology and Biosciences,</institution><institution>University of Milan-Bicocca,</institution></institution-wrap>Milan, 20126 Italy</nlm:aff></affiliation></author><author><name sortKey="Cagliani, Rachele" sort="Cagliani, Rachele" uniqKey="Cagliani R" first="Rachele" last="Cagliani">Rachele Cagliani</name><affiliation><nlm:aff id="Aff1">Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</nlm:aff></affiliation></author><author><name sortKey="De Gioia, Luca" sort="De Gioia, Luca" uniqKey="De Gioia L" first="Luca" last="De Gioia">Luca De Gioia</name><affiliation><nlm:aff id="Aff2"><institution-wrap><institution-id institution-id-type="GRID">grid.7563.7</institution-id><institution-id institution-id-type="ISNI">0000 0001 2174 1754</institution-id><institution>Department of Biotechnology and Biosciences,</institution><institution>University of Milan-Bicocca,</institution></institution-wrap>Milan, 20126 Italy</nlm:aff></affiliation></author><author><name sortKey="Pozzoli, Uberto" sort="Pozzoli, Uberto" uniqKey="Pozzoli U" first="Uberto" last="Pozzoli">Uberto Pozzoli</name><affiliation><nlm:aff id="Aff1">Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</nlm:aff></affiliation></author><author><name sortKey="Al Daghri, Nasser" sort="Al Daghri, Nasser" uniqKey="Al Daghri N" first="Nasser" last="Al-Daghri">Nasser Al-Daghri</name><affiliation><nlm:aff id="Aff3"><institution-wrap><institution-id institution-id-type="GRID">grid.56302.32</institution-id><institution-id institution-id-type="ISNI">0000 0004 1773 5396</institution-id><institution>Biomarkers research program, Biochemistry Department,</institution><institution>College of Science, King Saud University,</institution></institution-wrap>Riyadh, 11451 (KSA) Kingdom of Saudi Arabia</nlm:aff></affiliation><affiliation><nlm:aff id="Aff4"><institution-wrap><institution-id institution-id-type="GRID">grid.56302.32</institution-id><institution-id institution-id-type="ISNI">0000 0004 1773 5396</institution-id><institution>Prince Mutaib Chair for Biomarkers of Osteoporosis, Biochemistry Department,</institution><institution>College of science, King Saud University,</institution></institution-wrap>Riyadh, Kingdom of Saudi Arabia</nlm:aff></affiliation></author><author><name sortKey="Clerici, Mario" sort="Clerici, Mario" uniqKey="Clerici M" first="Mario" last="Clerici">Mario Clerici</name><affiliation><nlm:aff id="Aff5"><institution-wrap><institution-id institution-id-type="GRID">grid.4708.b</institution-id><institution-id institution-id-type="ISNI">0000 0004 1757 2822</institution-id><institution>Department of Physiopathology and Transplantation,</institution><institution>University of Milan,</institution></institution-wrap>Milan, 20090 Italy</nlm:aff></affiliation><affiliation><nlm:aff id="Aff6"><institution-wrap><institution-id institution-id-type="GRID">grid.414603.4</institution-id><institution>Don C. Gnocchi Foundation ONLUS, IRCCS,</institution></institution-wrap>Milan, 20148 Italy</nlm:aff></affiliation></author><author><name sortKey="Sironi, Manuela" sort="Sironi, Manuela" uniqKey="Sironi M" first="Manuela" last="Sironi">Manuela Sironi</name><affiliation><nlm:aff id="Aff1">Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</nlm:aff></affiliation></author></analytic><series><title level="j">Scientific Reports</title><idno type="eISSN">2045-2322</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p>Middle East respiratory syndrome coronavirus (MERS-CoV) originated in bats and spread to humans via zoonotic transmission from camels. We analyzed the evolution of the <italic>spike</italic> (<italic>S</italic>) gene in betacoronaviruses (betaCoVs) isolated from different mammals, in bat coronavirus populations, as well as in MERS-CoV strains from the current outbreak. Results indicated several positively selected sites located in the region comprising the two heptad repeats (HR1 and HR2) and their linker. Two sites (R652 and V1060) were positively selected in the betaCoVs phylogeny and correspond to mutations associated with expanded host range in other coronaviruses. During the most recent evolution of MERS-CoV, adaptive mutations in the HR1 (Q/R/H1020) arose in camels or in a previous host and spread to humans. We determined that different residues at position 1020 establish distinct inter- and intra-helical interactions and affect the stability of the six-helix bundle formed by the HRs. A similar effect on stability was observed for a nearby mutation (T1015N) that increases MERS-CoV infection efficiency <italic>in vitro</italic>. Data herein indicate that the heptad repeat region was a major target of adaptive evolution in MERS-CoV-related viruses; these results are relevant for the design of fusion inhibitor peptides with antiviral function.</p><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1038/srep14480) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Zaki, Am" uniqKey="Zaki A">AM Zaki</name></author><author><name sortKey="Van Boheemen, S" uniqKey="Van Boheemen S">S van Boheemen</name></author><author><name sortKey="Bestebroer, Tm" uniqKey="Bestebroer T">TM Bestebroer</name></author><author><name sortKey="Osterhaus, Ad" uniqKey="Osterhaus A">AD Osterhaus</name></author><author><name sortKey="Fouchier, Ra" uniqKey="Fouchier R">RA Fouchier</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="De 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<front><journal-meta><journal-id journal-id-type="nlm-ta">Sci Rep</journal-id><journal-id journal-id-type="iso-abbrev">Sci Rep</journal-id><journal-title-group><journal-title>Scientific Reports</journal-title></journal-title-group><issn pub-type="epub">2045-2322</issn><publisher><publisher-name>Nature Publishing Group UK</publisher-name><publisher-loc>London</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">26404138</article-id><article-id pub-id-type="pmc">4585914</article-id><article-id pub-id-type="publisher-id">BFsrep14480</article-id><article-id pub-id-type="doi">10.1038/srep14480</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>The heptad repeat region is a major selection target in MERS-CoV and related coronaviruses</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Forni</surname><given-names>Diego</given-names></name><address><email>diego.forni@bp.lnf.it</email></address><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Filippi</surname><given-names>Giulia</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Cagliani</surname><given-names>Rachele</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>De Gioia</surname><given-names>Luca</given-names></name><xref ref-type="aff" rid="Aff2">2</xref></contrib><contrib contrib-type="author"><name><surname>Pozzoli</surname><given-names>Uberto</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><contrib contrib-type="author"><name><surname>Al-Daghri</surname><given-names>Nasser</given-names></name><xref ref-type="aff" rid="Aff3">3</xref><xref ref-type="aff" rid="Aff4">4</xref></contrib><contrib contrib-type="author"><name><surname>Clerici</surname><given-names>Mario</given-names></name><xref ref-type="aff" rid="Aff5">5</xref><xref ref-type="aff" rid="Aff6">6</xref></contrib><contrib contrib-type="author"><name><surname>Sironi</surname><given-names>Manuela</given-names></name><xref ref-type="aff" rid="Aff1">1</xref></contrib><aff id="Aff1"><label>1</label>Scientific Institute IRCCS E. MEDEA, Bioinformatics, 23842 Bosisio Parini, Italy</aff><aff id="Aff2"><label>2</label><institution-wrap><institution-id institution-id-type="GRID">grid.7563.7</institution-id><institution-id institution-id-type="ISNI">0000 0001 2174 1754</institution-id><institution>Department of Biotechnology and Biosciences,</institution><institution>University of Milan-Bicocca,</institution></institution-wrap>Milan, 20126 Italy</aff><aff id="Aff3"><label>3</label><institution-wrap><institution-id institution-id-type="GRID">grid.56302.32</institution-id><institution-id institution-id-type="ISNI">0000 0004 1773 5396</institution-id><institution>Biomarkers research program, Biochemistry Department,</institution><institution>College of Science, King Saud University,</institution></institution-wrap>Riyadh, 11451 (KSA) Kingdom of Saudi Arabia</aff><aff id="Aff4"><label>4</label><institution-wrap><institution-id institution-id-type="GRID">grid.56302.32</institution-id><institution-id institution-id-type="ISNI">0000 0004 1773 5396</institution-id><institution>Prince Mutaib Chair for Biomarkers of Osteoporosis, Biochemistry Department,</institution><institution>College of science, King Saud University,</institution></institution-wrap>Riyadh, Kingdom of Saudi Arabia</aff><aff id="Aff5"><label>5</label><institution-wrap><institution-id institution-id-type="GRID">grid.4708.b</institution-id><institution-id institution-id-type="ISNI">0000 0004 1757 2822</institution-id><institution>Department of Physiopathology and Transplantation,</institution><institution>University of Milan,</institution></institution-wrap>Milan, 20090 Italy</aff><aff id="Aff6"><label>6</label><institution-wrap><institution-id institution-id-type="GRID">grid.414603.4</institution-id><institution>Don C. Gnocchi Foundation ONLUS, IRCCS,</institution></institution-wrap>Milan, 20148 Italy</aff></contrib-group><pub-date pub-type="epub"><day>25</day><month>9</month><year>2015</year></pub-date><pub-date pub-type="pmc-release"><day>25</day><month>9</month><year>2015</year></pub-date><pub-date pub-type="collection"><year>2015</year></pub-date><volume>5</volume><elocation-id>14480</elocation-id><history><date date-type="received"><day>16</day><month>5</month><year>2015</year></date><date date-type="accepted"><day>1</day><month>9</month><year>2015</year></date></history><permissions><copyright-statement>© The Author(s) 2015</copyright-statement><license license-type="OpenAccess"><license-p>This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><abstract id="Abs1"><p>Middle East respiratory syndrome coronavirus (MERS-CoV) originated in bats and spread to humans via zoonotic transmission from camels. We analyzed the evolution of the <italic>spike</italic> (<italic>S</italic>) gene in betacoronaviruses (betaCoVs) isolated from different mammals, in bat coronavirus populations, as well as in MERS-CoV strains from the current outbreak. Results indicated several positively selected sites located in the region comprising the two heptad repeats (HR1 and HR2) and their linker. Two sites (R652 and V1060) were positively selected in the betaCoVs phylogeny and correspond to mutations associated with expanded host range in other coronaviruses. During the most recent evolution of MERS-CoV, adaptive mutations in the HR1 (Q/R/H1020) arose in camels or in a previous host and spread to humans. We determined that different residues at position 1020 establish distinct inter- and intra-helical interactions and affect the stability of the six-helix bundle formed by the HRs. A similar effect on stability was observed for a nearby mutation (T1015N) that increases MERS-CoV infection efficiency <italic>in vitro</italic>. Data herein indicate that the heptad repeat region was a major target of adaptive evolution in MERS-CoV-related viruses; these results are relevant for the design of fusion inhibitor peptides with antiviral function.</p><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1038/srep14480) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group kwd-group-type="npg-subject"><title>Subject terms</title><kwd>Computational biology and bioinformatics</kwd><kwd>Evolution</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© The Author(s) 2015</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="Sec1"><title>Introduction</title><p>Middle East respiratory syndrome coronavirus (MERS-CoV), a newly emerged virus that can cause severe lower respiratory tract infection in humans, was first identified in Saudi Arabia in 2012<sup><xref ref-type="bibr" rid="CR1">1</xref></sup>. Since then, 945 laboratory-confirmed cases of MERS-CoV infection, leading to at least 348 related deaths, have been reported to the WHO (as of January 5<sup>th</sup>, 2015) (<ext-link ext-link-type="uri" xlink:href="http://www.who.int/csr/don/05-january-2015-mers-jordan/en/">http://www.who.int/csr/don/05-january-2015-mers-jordan/en/</ext-link>).</p><p>MERS-CoV belongs to the clade c of betacoronaviruses (betaCoVs)<sup><xref ref-type="bibr" rid="CR2">2</xref></sup>, which also includes two bat sister species, namely Ty-BatCoV HKU4 and Pi-BatCoV HKU5, isolated from the lesser bamboo bats (<italic>Tylonycteris pachypus</italic>) and Japanese pipistrelles (<italic>Pipistrellus abramus</italic>), respectively<sup><xref ref-type="bibr" rid="CR3">3</xref></sup>. Additional viruses related to MERS-CoV have been described in bats (BtCoV/KW2E-F93, BtCoV/133) and hedgehogs (<italic>Erinaceus</italic> coronavirus, EriCoV)<sup><xref ref-type="bibr" rid="CR4">4</xref>,<xref ref-type="bibr" rid="CR5">5</xref></sup>. Recently, a virus belonging to the same species as MERS-CoV was isolated in <italic>Neoromicia</italic> bats (NeoCoV), supporting a bat-origin for MERS-CoV<sup><xref ref-type="bibr" rid="CR6">6</xref></sup>. This hypothesis received further confirmation by the identification of dipeptidyl-peptidase 4 (DPP4, also known as CD26) as the cellular receptor used by both Ty-BatCoV HKU4 and MERS-CoV<sup><xref ref-type="bibr" rid="CR7">7</xref>,<xref ref-type="bibr" rid="CR8">8</xref>,<xref ref-type="bibr" rid="CR9">9</xref></sup>.</p><p>Notably, high titers of MERS-CoV neutralizing antibodies have been detected in camels from various countries and MERS-CoV has been isolated from these animals in Saudi Arabia and Qatar<sup><xref ref-type="bibr" rid="CR10">10</xref></sup>. Genetic diversity is slightly higher for camel-derived viruses compared to human MERS-CoV isolates, suggesting camel to human transmission rather than vice versa<sup><xref ref-type="bibr" rid="CR10">10</xref></sup>. Therefore, the most likely scenario envisages that a bat-derived MERS-CoV spread to humans via the zoonotic transmission from dromedary camels.</p><p>Coronaviruses use their spike (S) protein to bind a host receptor and to promote membrane fusion. The spike protein assembles as a trimer on the viral surface and belongs to the class I fusion protein family<sup><xref ref-type="bibr" rid="CR11">11</xref></sup>. Class I fusion proteins are found in many other virus genera including retroviruses, orthomyxoviruses, paramyxoviruses and filoviruses and share similar domain organization, as well as common functional properties<sup><xref ref-type="bibr" rid="CR12">12</xref></sup>.</p><p>Host proteases cleave the CoV spike protein into two functionally distinct domains: the N-terminal region (usually referred to as the S1 subunit) contains the receptor binding domain (RBD), whereas the C-terminal portion (S2 subunit) includes the fusion peptide, two heptad repeats (HR1 and HR2) and the transmembrane (TM) domain<sup><xref ref-type="bibr" rid="CR12">12</xref></sup> (see <xref rid="Fig1" ref-type="fig">Fig. 1A</xref>). Following receptor binding, membrane fusion is mediated by a major conformational rearrangement that exposes the fusion peptide and results in the formation of a six-helix bundle (6HB)<sup><xref ref-type="bibr" rid="CR13">13</xref>,<xref ref-type="bibr" rid="CR14">14</xref></sup>. The core of the 6HB is a triple-stranded coiled coil formed by the HR1s of the three spike subunits forming the trimer; the HR2 elements pack within the grooves of the coiled coil in an antiparallel direction<sup><xref ref-type="bibr" rid="CR13">13</xref>,<xref ref-type="bibr" rid="CR14">14</xref></sup>.<fig id="Fig1"><label>Figure 1</label><caption><p>Positive selection at the <italic>spike</italic> gene of MERS-CoV-related coronaviruses.</p><p>(<bold>A</bold>) Cartoon representation of the MERS-CoV spike protein with distinct domains in different colors (SP, signal peptide; NTD, N-terminal domain; RBD, receptor binding domain; FP, fusion peptide, HR1 and HR2, heptad repeat 1 and 2; TM, transmembrane domain; CP, cytoplasmic domain). The location of positively selected sites detected in MERS-CoV related sequences is shown in red. A positively selected residue in MERS-CoV isolated from humans and camels is in orange. The positively selected site and recombination breakpoints in Pi-BatCoV HKU5 sequences are shown in blue and black, respectively. Furin cleavage sites are depicted as triangles<sup><xref ref-type="bibr" rid="CR56">56</xref></sup>. Two alignment portions are shown; positions that alter virus host range or tropism in SARS-CoV, MHV and Beaudette strain IBV (IBV Beau CK) are highlighted in green<sup><xref ref-type="bibr" rid="CR25">25</xref>,<xref ref-type="bibr" rid="CR26">26</xref>,<xref ref-type="bibr" rid="CR27">27</xref></sup>. A functional mutation which arose during tissue-culture adaptation of MERS-CoV (strain EMC2012) is highlighted in grey<sup><xref ref-type="bibr" rid="CR31">31</xref></sup>. (<bold>B</bold>) Bayesian phylogenies for the S1 (left) and S2 (right) sequences<sup><xref ref-type="bibr" rid="CR6">6</xref></sup>; branch length is proportional to dS. Branches in red were set as foreground lineages in independent branch-site tests. Thick branches yielded statistically significant evidence of positive selection. The bracket denotes a subset of sequences that were used for analysis of positive selection in the RBD. (<bold>C</bold>) OmegaMap results for Pi-BatCoV HKU5 <italic>spike</italic> genes. The hatched red line corresponds to a posterior probability of selection equal to 0.95.</p></caption><graphic xlink:href="41598_2015_Article_BFsrep14480_Fig1_HTML" id="d29e486"></graphic></fig></p><p>Because of its central role in membrane fusion, a number of antiviral peptides that interfere with the 6HB formation have been developed as potential therapeutic compounds against HIV<sup><xref ref-type="bibr" rid="CR15">15</xref></sup>, Ebola virus<sup><xref ref-type="bibr" rid="CR16">16</xref></sup>, SARS-CoV<sup><xref ref-type="bibr" rid="CR17">17</xref>,<xref ref-type="bibr" rid="CR18">18</xref></sup> and MERS-CoV<sup><xref ref-type="bibr" rid="CR14">14</xref></sup>.</p><p>Although the RBD of spike proteins is generally considered the major determinant of host range, several reports have suggested that variation in the C-terminal portion of spike proteins, particularly in the HR1 and HR2, determine host range expansion<sup><xref ref-type="bibr" rid="CR12">12</xref></sup>. Moreover, recent works indicated that MERS-CoV and Ty-BatCoV HKU4 bind DPP4 both of human and of bat origin<sup><xref ref-type="bibr" rid="CR7">7</xref>,<xref ref-type="bibr" rid="CR8">8</xref>,<xref ref-type="bibr" rid="CR9">9</xref></sup>. In particular, although MERS-CoV binds human DPP4 with higher affinity than Ty-BatCoV HKU4, which shows a preference for the bat receptor, the RBDs of the two viruses engage human DPP4 via a similar binding mode<sup><xref ref-type="bibr" rid="CR9">9</xref></sup>. These observations suggest that MERS-CoV and related viruses have the potential to shift host range with little adaptation of the RBD.</p><p>Motivated by the notion that evolutionary analyses can provide information on the molecular events that underlie host shifts and, more generally, host-pathogen interactions<sup><xref ref-type="bibr" rid="CR19">19</xref></sup>, we investigated the evolutionary history of S proteins in MERS-CoV and related betaCoVs. Specifically, we aimed to determine whether natural selection drove the evolution of specific regions and sites that may contribute to variation in host range or replication efficiency. Thus, using different strategies, we analyzed MERS-CoV strains isolated from human and camels, as well as MERS-CoV-related viruses from other mammals. Data indicate the HR1 to HR2 region as a major target of adaptive evolution in these viruses.</p></sec><sec id="Sec2"><title>Results</title><sec id="Sec3"><title>Positive selection shaped the evolution of clade c betaCoV spike protein</title><p>We first investigated whether positive selection drove the evolution of MERS-CoV-related coronavirus spike proteins. Previous phylogenetic analyses of <italic>S</italic> genes of viruses isolated from humans/camels (MERS-CoV), bats and hedgehogs (<xref rid="MOESM1" ref-type="media">Supplementary Table. S1</xref>) indicated that the S1 and S2 regions display different tree topologies (<xref rid="Fig1" ref-type="fig">Fig. 1B</xref>), possibly as a result of recombination<sup><xref ref-type="bibr" rid="CR6">6</xref></sup>. Because recombination can inflate estimates of positive selection<sup><xref ref-type="bibr" rid="CR20">20</xref></sup>, we separately analyzed the two regions.</p><p>We pruned the S1 and S2 multiple sequence alignments (MSAs) from unreliably aligned codons and we screened them for evidence of additional recombination events using GARD (Genetic Algorithm Recombination Detection)<sup><xref ref-type="bibr" rid="CR21">21</xref></sup>, which detected no breakpoint.</p><p>The saturation of substitution rates represents a major problem in the detection of positive selection among distantly related sequences. Computation of the nonsynonymous (dN) and synonymous (dS) substitution rates over whole phylogenies allows breaking of long branches, resulting in improved rate estimation. Thus, evidence of episodic positive selection was searched for by using the <italic>codeml</italic> branch-site test<sup><xref ref-type="bibr" rid="CR22">22</xref></sup>, which is relatively insensitive to the saturation of substitution rates<sup><xref ref-type="bibr" rid="CR23">23</xref></sup>. In the S1 and S2 regions, 3 and 4 branches yielded statistically significant evidence of positive selection under different codon frequency models (<xref rid="Fig1" ref-type="fig">Fig. 1B</xref>, <xref rid="Tab1" ref-type="table">Table 1</xref> and <xref rid="MOESM1" ref-type="media">Supplementary Table S3</xref>). Positively selected sites along these branches were detected using the BEB (Bayes empirical Bayes) procedure and validated using the Mixed Effects Model of Evolution (MEME)<sup><xref ref-type="bibr" rid="CR24">24</xref></sup>. <table-wrap id="Tab1"><label>Table 1</label><caption><p>Likelihood ratio test statistics for branch-site tests (clade c betaCoV).</p></caption><table frame="hsides" rules="groups"><thead><tr><th><bold><italic>Spike</italic></bold><bold>region</bold></th><th align="center"><bold>Foreground branch (MA vs MA1)</bold><sup><bold>1</bold></sup></th><th align="center"><bold>−2ΔlnL</bold><sup><bold>2</bold></sup></th><th align="center"><bold><italic>p</italic></bold><bold>value (FDR corrected</bold><bold><italic>p</italic></bold><bold>value)</bold><sup><bold>3</bold></sup></th><th align="center"><bold>Sites</bold><sup><bold>4</bold></sup><bold>identified by BEB and MEME</bold></th></tr></thead><tbody><tr><td align="left" colspan="5">S1 subunit</td></tr><tr><td rowspan="5"></td><td>Node 18</td><td>30.92</td><td>2.69 × 10<sup>−8</sup> (1.35 × 10<sup>−7</sup>)</td><td>R652</td></tr><tr><td>Node 19</td><td>16.18</td><td>5.74 × 10<sup>−5</sup> (1.43 × 10<sup>−4</sup>)</td><td>—</td></tr><tr><td>Node 20</td><td>1.51</td><td>0.218 (0.272)</td><td>—</td></tr><tr><td>Node 24</td><td>14.86</td><td>1.15 × 10<sup>−4</sup> (1.92 × 10<sup>−4</sup>)</td><td>—</td></tr><tr><td>Node 25</td><td>0.71</td><td>0.399 (0.399)</td><td>—</td></tr><tr><td align="left" colspan="5">S2 subunit</td></tr><tr><td rowspan="5"></td><td>Node 15</td><td>14.45</td><td>1.44 × 10<sup>−4</sup> (7.20 × 10<sup>−4</sup>)</td><td>K854, I1180</td></tr><tr><td align="center">Node 16</td><td>12.86</td><td>3.37 × 10<sup>−4</sup> (8.43 × 10<sup>−4</sup>)</td><td>V1060</td></tr><tr><td align="center">Node 17</td><td>5.66</td><td>0.0173 (0.0216)</td><td>M939, S1114, S1148</td></tr><tr><td align="center">Node 18</td><td align="center">0</td><td>1 (1)</td><td></td></tr><tr><td align="center">Node 23</td><td>7.20</td><td>7.30 × 10<sup>−3</sup> (0.0121)</td><td>A1275</td></tr></tbody></table><table-wrap-foot><p><sup>1</sup>MA and MA1 are branch-site models: MA allows a proportion of codons with dN/dS ≥ 1 on the foreground branches, whereas the MA1 model does not. The F61 codon frequency model was used.</p><p><sup>2</sup>2ΔlnL is twice the difference of the natural logs of the maximum likelihood of the models being compared.</p><p><sup>3</sup>Degrees of freedom = 1.</p><p><sup>4</sup>Positions are relative to the MERS-CoV sequence (EMC/2012).</p></table-wrap-foot></table-wrap></p><p>One positively selected site was found in the S1 region, 7 sites in the S2 subunit (<xref rid="Fig1" ref-type="fig">Fig. 1A</xref>, <xref rid="Tab1" ref-type="table">Table 1</xref>). The R652 selected site (in S1) almost corresponds to two mutations that independently arose in the SARS-CoV <italic>spike</italic> gene as a result of <italic>in vitro</italic> adaptation of zoonotic strains to primate cells<sup><xref ref-type="bibr" rid="CR25">25</xref></sup> (<xref rid="Fig1" ref-type="fig">Fig. 1A</xref>). In S2, most selected sites are located in the HR1, HR2 and in the intervening linker. Remarkably, position 1060 is the almost exact counterpart of aminoacid changes that expand the host range or cell-type tropism of infectious bronchiolitis virus (IBV, L857F) and murine hepatitis virus (MHV, E1035D) (<xref rid="Fig1" ref-type="fig">Fig. 1A</xref>)<sup><xref ref-type="bibr" rid="CR26">26</xref>,<xref ref-type="bibr" rid="CR27">27</xref></sup>.</p><p>No positively selected site was found to be located in the RBD (<xref rid="Fig1" ref-type="fig">Fig. 1A</xref>). Nevertheless, the pruning of unreliably aligned codons operated on the MSA left a minority of RBD sites available for analysis. We thus repeated the branch-site test on a subset of more closely related sequences (<xref rid="Fig1" ref-type="fig">Fig. 1B</xref>). This procedure decreased divergence and pruning in the RBD and allowed analysis of most codons; even with this procedure, no positively selected site was detected (not shown).</p></sec><sec id="Sec4"><title>Minor effect of positive selection for the <italic>S</italic> genes of Ty-BatCoV HKU4 and Pi-BatCoV HKU5</title><p>Previous analysis of Ty-BatCoV HKU4 and Pi-BatCoV HKU5 viruses isolated in Hong Kong indicated that positive selection targeted the spike protein and particularly its S1 region<sup><xref ref-type="bibr" rid="CR28">28</xref></sup>. Nevertheless, recombination was not accounted for in that analysis. We thus analyzed the sequence alignments of the Hong Kong isolates for the presence of recombination breakpoints using GARD. The algorithm detected 9 recombination breakpoints for the Pi-BatCoV HKU5 alignment (<xref rid="Fig1" ref-type="fig">Fig. 1A</xref>) and none for Ty-BatCoV HKU4. The Ty-BatCoV HKU4 <italic>spike</italic> gene was therefore analyzed using the codeml site models, which test the hypothesis that a subset of codons evolve with dN/dS > 1. No evidence of positive selection was found, even using the relatively non-conservative model M7/model M8 comparison (<xref rid="MOESM1" ref-type="media">Supplementary Table S4</xref>). As for the Pi-BatCoV HKU5 <italic>spike</italic> gene, rampant recombination prevents application of a similar approach. We thus resorted to the simultaneous estimation of selection and recombination using omegaMap<sup><xref ref-type="bibr" rid="CR29">29</xref></sup>. This analysis confirmed high recombination along the whole gene (<xref rid="MOESM1" ref-type="media">Supplementary Fig. S1</xref>) and detected a single positively selected site in the S1 region (<xref rid="Fig1" ref-type="fig">Fig. 1C</xref>). The same site (codon 198, position relative to the MERS-CoV spike sequence) was also detected by MEME, which was run by incorporating the alternative phylogenies detected by GARD. Most of the previously reported selected sites<sup><xref ref-type="bibr" rid="CR28">28</xref></sup> were not detected using other methods that account for recombination (<xref rid="MOESM1" ref-type="media">Supplementary Table S5</xref>). We thus consider that robust inference of positive selection in Pi-BatCoV HKU5 <italic>spike</italic> genes can only be made for position 198, which lies outside the RBD (<xref rid="Fig1" ref-type="fig">Fig. 1A</xref>).</p></sec><sec id="Sec5"><title>Positive selection in the MERS-CoV heptad repeat 1</title><p>We next wished to determine whether positive selection occurred at the <italic>spike</italic> gene of MERS-CoV viruses circulating in the recent outbreak. A previous study suggested that positive selection drove the evolution of two codons in the MERS-CoV <italic>spike</italic> gene (positions 509 and 1020)<sup><xref ref-type="bibr" rid="CR30">30</xref></sup>. Nevertheless, in that study only one method was used to infer selection and sequences isolated from camels were not included.</p><p>We thus retrieved 54 fully or almost fully <italic>spike</italic> sequences of MERS-CoV isolated from camels or humans (<xref rid="MOESM1" ref-type="media">Supplementary Table S1</xref>). Alignments for the S1 and S2 regions were separately analyzed and screened for the presence of recombination. No breakpoint was detected and the <italic>codeml</italic> site models were applied. For the S2 region, two models of gene evolution that allow a class of codons to evolve with dN/dS > 1 (NSsite models M2a and M8) showed better fit to the data than the null models (NSsite models M1a and M7), strongly supporting the action of positive selection (<xref rid="Tab2" ref-type="table">Table 2</xref>, <xref rid="MOESM1" ref-type="media">Supplementary Table S6</xref>). No evidence of selection was detected for the S1 portion (<xref rid="Tab2" ref-type="table">Table 2</xref>, <xref rid="MOESM1" ref-type="media">Supplementary Table S6</xref>). In S2, both BEB and MEME detected one selected site: position 1020 in the HR1 (<xref rid="Fig1" ref-type="fig">Fig. 1A</xref>). Interestingly, three different residues are observed at this site in both camel- and human-derived viruses (<xref rid="Fig1" ref-type="fig">Fig. 1A</xref>). MERS-CoV is thought to have spread from camels to humans; the presence of the three alternative residues in viruses isolated from camels suggests that adaptive evolution at this site occurred prior to the infection of humans.<table-wrap id="Tab2"><label>Table 2</label><caption><p>Likelihood ratio test statistics for models of variable selective pressure among sites in MERS-CoV isolates.</p></caption><table frame="hsides" rules="groups"><thead><tr><th><bold><italic>Spike</italic></bold><bold>region</bold></th><th align="center"><bold>LRT model</bold></th><th align="center"><bold>Codon Frequency model</bold></th><th align="center"><bold>Degrees of freedom</bold></th><th align="center"><bold>−2ΔlnL</bold><sup><bold>3</bold></sup></th><th align="center"><bold><italic>p</italic></bold><bold>value</bold></th><th align="center"><bold>% of sites (average dN/dS)</bold></th><th align="center"><bold>Positively selected sites</bold><sup><bold>4</bold></sup><bold>(BEB and MEME)</bold></th></tr></thead><tbody><tr><td align="left" colspan="8">S1 subunit</td></tr><tr><td rowspan="2"></td><td>M1a vs M2a<sup>1</sup></td><td>F61</td><td>2</td><td>0.84</td><td>0.657</td><td>—</td><td></td></tr><tr><td>M7 vs M8<sup>2</sup></td><td>F61</td><td>2</td><td>4.21</td><td>0.121</td><td>—</td><td></td></tr><tr><td align="left" colspan="8">S2 subunit</td></tr><tr><td rowspan="2"></td><td>M1a vs M2a<sup>1</sup></td><td>F61</td><td>2</td><td>7.38</td><td>0.0250</td><td>0.2 (15.83)</td><td>1020Q</td></tr><tr><td align="center">M7 vs M8<sup>2</sup></td><td>F61</td><td>2</td><td>9.41</td><td>0.0091</td><td>0.2 (16.32)</td><td>1020Q</td></tr></tbody></table><table-wrap-foot><p><sup>1</sup>M1a is a nearly neutral model that assumes one dN/dS (ω) class between 0 and 1 and one class with ω = 1; M2a (positive selection model) is the same as M1a plus an extra class of ω > 1.</p><p><sup>2</sup>M7 is a null model that assumes that 0 < ω < 1 is beta distributed among sites; M8 (positive selection model) is the same as M7 but also includes an extra category of sites with ω > 1.</p><p><sup>3</sup>2ΔlnL: twice the difference of the natural logs of the maximum likelihood of the models being compared.</p><p><sup>4</sup>Positions are relative to the MERS-CoV sequence (EMC/2012).</p></table-wrap-foot></table-wrap></p><p>Interestingly, the 1020 variant is in proximity to a mutation (T1015N) (<xref rid="Fig1" ref-type="fig">Figs 1</xref>A and <xref rid="Fig2" ref-type="fig">2</xref>A) that arose during tissue-culture adaptation of MERS-CoV (strain EMC2012) and increases replication efficiency<sup><xref ref-type="bibr" rid="CR31">31</xref></sup>.<fig id="Fig2"><label>Figure 2</label><caption><p>Analysis of variation in the MERS-CoV HR1.</p><p>(<bold>A</bold>) Ribbon representation of MERS-CoV HR region. Positively selected sites in betaCoVs are shown in red; Q1020 (orange) and M1266 (yellow) are shown as sticks. T1015 is in blue. (<bold>B</bold>) Detail of inter- and intra-helical interactions for residue 1020. Interactions are shown for Q1020 (left), R1020 (middle) and H1020 (right). Hydrogen bonds are shown as hatched yellow lines; color codes: carbon, white; oxygen, red; nitrogen, blue; sulphur, yellow. Hydrogens have been omitted for clarity. (<bold>C</bold>) Stability analysis for HR1 positions 1020 (left) and 1015 (right). ΔΔG in kcal/mol for mutations of Q1020 and T1015 to all other 19 aminoacids are reported. Aminoacid residues observed in MERS-CoV sequences are circled. Results are shown for FoldX, PopMuSiC and I-Mutant.</p></caption><graphic xlink:href="41598_2015_Article_BFsrep14480_Fig2_HTML" id="d29e1226"></graphic></fig></p></sec><sec id="Sec6"><title>Analysis of MERS-CoV HR1 variation</title><p>The structure of the 6HB of MERS-CoV has been solved<sup><xref ref-type="bibr" rid="CR13">13</xref>,<xref ref-type="bibr" rid="CR14">14</xref></sup>; through its side chain, the Q1020 residue forms hydrogen bonds with D1024 and interacts with M1266 in HR2 (<xref rid="Fig2" ref-type="fig">Fig. 2A,B</xref>). Replacement of the glutamine residue with histidine or arginine (observed in the camel- and human-derived viruses) results in loss of side chain interactions with M1266 and variably affects hydrogen bonds with D1024 (<xref rid="Fig2" ref-type="fig">Fig. 2B</xref>).</p><p>To gain further insight into the effect of adaptive evolution at position 1020, we performed a stability computational analysis after in silico mutagenesis. Q1020 was replaced with all other possible aminoacids: even if changes of different magnitude in ΔG were obtained using three different methods<sup><xref ref-type="bibr" rid="CR32">32</xref>,<xref ref-type="bibr" rid="CR33">33</xref>,<xref ref-type="bibr" rid="CR34">34</xref></sup>, trends were very consistent (<xref rid="Fig2" ref-type="fig">Fig. 2C</xref>). In particular, replacement with histidine or arginine residues resulted in mild destabilization (<xref rid="Fig2" ref-type="fig">Fig. 2C</xref>). As a comparison, the same analysis was performed for position 1015. Replacement of the threonine residue with asparagine, which was previously associated with increased replication efficiency <italic>in vitro</italic><sup><xref ref-type="bibr" rid="CR31">31</xref></sup>, resulted in a similar level of destabilization as observed for Q1020H/R (<xref rid="Fig2" ref-type="fig">Fig. 2C</xref>).</p></sec></sec><sec id="Sec7"><title>Discussion</title><p>We analyzed the evolution of the S protein in betaCoVs, in bat Ty-BatCoV HKU4 and Pi-BatCoV HKU5 viral populations, as well as in MERS-CoV isolates from the current outbreak. Different strategies were applied, as appropriate depending on divergence and recombination.</p><p>Results indicated that several adaptive changes are located in the S2 region, with fewer in the S1 domain and none of these within the RBD. It should be noted, though, that in all analyses we applied quite conservative approaches and we intersected two different methods to declare a site as positively selected. Whereas this approach was meant to limit the false positive rate it may have yielded some false negative results. In particular, the branch-site test we used to analyze the S1 and S2 regions of betaCoVs is robust to saturation issues and has a minimal false positive rate, but lacks power<sup><xref ref-type="bibr" rid="CR23">23</xref></sup>. Moreover, due to the high divergence and the consequent need of alignment pruning, analysis of the RBD was performed on a shallower phylogeny compared to the other regions. This procedure is expected to reduce power, but is nonetheless necessary. In fact, alignment errors, together with unrecognized recombination, inflate estimates of positive selection and represent major sources of false positive results in evolutionary analyses<sup><xref ref-type="bibr" rid="CR20">20</xref>,<xref ref-type="bibr" rid="CR35">35</xref></sup>. Consistently, when we accounted for recombination in Pi-BatCoV HKU5 sequences most previously described selection signals disappeared, including those in the RBD<sup><xref ref-type="bibr" rid="CR28">28</xref></sup>. Thus, whereas we cannot exclude that adaptive variants in the RBD of betaCoVs were missed by our approach, we conclude that the more recent evolution of MERS-CoV, Ty-BatCoV HKU4 and Pi-BatCoV HKU5 was not driven by positive selection in this domain. Conversely, as previously shown for SARS-CoV<sup><xref ref-type="bibr" rid="CR25">25</xref></sup>, our data support a role for the S1 region separating the RBD and fusion peptide as a determinant of betaCoV host range expansion.</p><p>Analysis of both betaCoVs and MERS-CoV strains revealed evidence of positive selection in the S2 region. Most positively selected sites were found to be located either in the heptad repeats or in the intervening linker. Among these sites, position 1060 is particularly interesting, as it almost corresponds to substitutions that modify the host range and/or cell tropism in MHV and IBV<sup><xref ref-type="bibr" rid="CR26">26</xref>,<xref ref-type="bibr" rid="CR27">27</xref></sup>. Both viruses belong to the <italic>coronavirus</italic> genus. The Beaudette strain of IBV has been adapted to embryonated chicken eggs; following passages in culture, the strain was further adapted to infect Vero cells (from African Green monkey) and primary chicken kidney cells<sup><xref ref-type="bibr" rid="CR26">26</xref></sup>. The L857F mutation was shown to represent a major determinant of the fusogenic activity in these cell types<sup><xref ref-type="bibr" rid="CR26">26</xref></sup>. As far as MHV is concerned, the E1035D mutation was recovered after passages in mouse liver and was shown to contribute significantly to the hepatotropism and hepatic virulence of a previously attenuated strain (MHV-A59)<sup><xref ref-type="bibr" rid="CR27">27</xref></sup>. Additional variants in the HR1 and fusion peptide of MHV strains cooperate with changes in the S1 region, resulting in a broadening of receptor usage (to heparan sulfate) and, consequently, an extension of the host range<sup><xref ref-type="bibr" rid="CR36">36</xref></sup>. Finally, in the MHV-A51 strain the ability to bind human CAECAM receptors is strongly influenced by mutant residues located in the fusion peptide, HR1 and HR1/HR2 linker<sup><xref ref-type="bibr" rid="CR37">37</xref></sup>. Similar observations have been reported for viruses that do not belong to the <italic>coronavirus</italic> genus, but that use a class I fusion protein. For instance, one single mutation in the HR1 of a simian-human immunodeficiency virus (SHIV) strain (KB9) increases by two- to three-fold infection efficiency in cells expressing the marmoset cellular receptors<sup><xref ref-type="bibr" rid="CR38">38</xref></sup>, whereas a nearby HR1 change in SIV contributes to macrophage tropism<sup><xref ref-type="bibr" rid="CR39">39</xref></sup>. Overall, these findings pinpoint the relevance of changes in the HR1 and HR2 as modifiers of host range and cell-type tropism.</p><p>The molecular mechanisms underlying the altered phenotype of HR1 and HR2 mutants remain to be determined in all these instances, although changes in conformational structure have been suggested as a possible explanation. Unfortunately, no coronavirus S protein fusion intermediate or pre-fusion state has been solved to date, hampering investigation of molecular interactions. We therefore analyzed the effect of variation at the 1020 position of MERS-CoV on the stability of the 6HB in the post-fusion conformation<sup><xref ref-type="bibr" rid="CR14">14</xref></sup>. The presence of a Q1020 had previously been suggested to confer higher stability to the MERS-CoV 6HB compared to SARS-CoV<sup><xref ref-type="bibr" rid="CR14">14</xref></sup>. Indeed, replacement of this residue results in loss of intra- and inter-helical interactions. In line with these observations, three different methods used for stability analysis were concordant in showing that the alternative arginine and histidine residues at position 1020 result in a moderate and similar level of destabilization. Although the observed ΔΔG is relatively small, it was calculated on the single monomer and is expected to be multiplied in the trimer. The observation whereby mildly destabilizing variants are favored by selection may seem counterintuitive. Nonetheless, we show that a similar level of destabilization is observed for a mutation in MERS-Cov HR1 (T1015N) that increases infection efficiency, at least <italic>in vitro</italic><sup><xref ref-type="bibr" rid="CR31">31</xref></sup>. Mutagenesis of HR1 in retroviral type I fusion proteins has indicated that, whereas strong destabilization of the 6HB (as measured by circular dichroism) almost inevitably results in reduced infectivity, a minor stability decrease is not necessarily associated with defects in cell fusion and infection efficiency<sup><xref ref-type="bibr" rid="CR40">40</xref>,<xref ref-type="bibr" rid="CR41">41</xref>,<xref ref-type="bibr" rid="CR42">42</xref></sup>. For instance, different aminoacid replacements at the same HR1 position in HIV-1 gp41 result in decreased stability, but unaffected or even increased infectivity<sup><xref ref-type="bibr" rid="CR40">40</xref></sup>. In the case of EIAV (equine infectious anemia virus), destabilized HR1 mutants were found to display different infection phenotypes depending on temperature<sup><xref ref-type="bibr" rid="CR42">42</xref></sup>. This observation may be extremely interesting in the context of MERS-CoV, as both bats and dromedary camels display adaptive heterothermy (i.e. sensible daily or season variation in body temperature).</p><p>Coronavirus spike proteins are highly exposed on the virus surface and represent major targets for antibody response<sup><xref ref-type="bibr" rid="CR43">43</xref></sup>, raising the possibility that adaptive evolution of the S protein is driven by the host immune system. This hypothesis is difficult to address due to the paucity of information concerning the specific MERS-CoV epitopes recognized by human antibodies. Recently, different studies identified human antibodies againts MERS-CoV from non-immune human antibody libraries: all of them were directed against the RBD, suggesting that this region represents a major target for the host immune system<sup><xref ref-type="bibr" rid="CR43">43</xref></sup>. Nevertheless, data on the humoral immune response to MERS-CoV in infected subjects are presently lacking, whereas such information is richer for SARS-CoV. Indeed, analysis of antibodies derived from a patient who recovered from SARS indicated that some of them recognize epitopes in the HR2 region<sup><xref ref-type="bibr" rid="CR44">44</xref></sup>. Their neutralizing effect was ascribed to interference of the interaction between HR2 and HR1. Whether antibodies against the S2 region also arise in human subjects (or other mammalian hosts) infected with MERS-CoV and related betaCoVs remains to be determined; if this were the case, some of the selected sites we identified may be under selective pressure to evade recognition.</p><p>Finally, it is worth noting that HRs have been studied in different viruses because synthetic peptides interfering with 6HB formation are promising antiviral molecules<sup><xref ref-type="bibr" rid="CR15">15</xref>,<xref ref-type="bibr" rid="CR16">16</xref>,<xref ref-type="bibr" rid="CR17">17</xref>,<xref ref-type="bibr" rid="CR18">18</xref></sup>. This is also the case for MERS-CoV and HR2-like peptides were recently shown to be effective <italic>in vitro</italic><sup><xref ref-type="bibr" rid="CR14">14</xref></sup>. These peptides were tested against a MERS-CoV strain carrying Q1020 and all include the interacting M1266 residue<sup><xref ref-type="bibr" rid="CR14">14</xref></sup>. These antivirals may display decreased activity depending on the MERS-CoV strain and its aminoacid status at the selected 1020 position.</p></sec><sec id="Sec8"><title>Materials and Methods</title><sec id="Sec9"><title>Sequences and alignments</title><p>Virus sequences were retrieved from the NCBI database and a list of accession numbers is provided as <xref rid="MOESM1" ref-type="media">Supplementary Table S1</xref>. Sequences of Ty-BatCoV HKU4 and Pi-BatCoV HKU5 isolated in Hong Kong were derived from a previous work<sup><xref ref-type="bibr" rid="CR28">28</xref></sup>.</p><p>Errors in the inferred multiple sequence alignment (MSA), which may be common when highly divergent sequences are analyzed, can inflate estimates of positive selection. We therefore used PRANK<sup><xref ref-type="bibr" rid="CR45">45</xref></sup> for building the MSA and GUIDANCE<sup><xref ref-type="bibr" rid="CR46">46</xref></sup> for filtering unreliably aligned codons (i.e. we masked codons with a score <0.90), as suggested<sup><xref ref-type="bibr" rid="CR35">35</xref></sup>.</p></sec><sec id="Sec10"><title>Detection of recombination and positive selection</title><p>To detect positive selection at the <italic>S</italic> gene of clade c betaCoVs we applied the branch-site test from the PAML suite<sup><xref ref-type="bibr" rid="CR22">22</xref></sup>. The test compares a model (MA) that allows positive selection on one or more lineages (foreground lineages) with a model (MA1) that does not allow such positive selection. Twice the difference of likelihood for the two models (ΔlnL) is then compared to a χ<sup>2</sup> distribution with one degree of freedom<sup><xref ref-type="bibr" rid="CR22">22</xref></sup>. Specifically, the internal branches of previously reconstructed<sup><xref ref-type="bibr" rid="CR6">6</xref></sup> Bayesian phylogenies of the S1 and S2 regions were set as the foreground lineages in independent tests. A false discovery rate (FDR) correction was applied to account for multiple hypothesis testing (i.e. we corrected for the number of tested branches), as suggested<sup><xref ref-type="bibr" rid="CR47">47</xref></sup>.</p><p>Positively selected sites were identified through the BEB analysis (with a p value cutoff of 0.90), which calculates the posterior probability that each site belongs to the site class of positive selection on the foreground branch(es). Sites were validated using MEME (with the default cutoff of 0.1), which allows the distribution of dN/dS (also referred to as ω) to vary from site to site and from branch to branch at a site, therefore allowing the detection of episodic positive selection<sup><xref ref-type="bibr" rid="CR24">24</xref></sup>.</p><p>The site models implemented in PAML were applied -independently- for the analysis of HKU4 and MERS-CoV sequences, which display very limited divergence and do not suffer from saturation problems. To detect selection, site models that allow (M2a, M8) or disallow (M1a, M7) a class of sites to evolve with ω > 1 were fitted to the data<sup><xref ref-type="bibr" rid="CR48">48</xref></sup>. Trees were generated by maximum-likelihood using the PhyML program<sup><xref ref-type="bibr" rid="CR49">49</xref></sup> with a GTR model of nucleotide substitution and γ distributed rates. Positively selected sites were identified using the BEB analysis (from model M8)<sup><xref ref-type="bibr" rid="CR50">50</xref></sup>. Again, sites were validated using MEME.</p><p>To assure consistency, all models were run using the F3 × 4 and the F61 codon frequency models.</p><p>MSAs were screened for the presence of recombination using GARD. Recombination breakpoints were considered significant if the HK (Kishino-Hasegawa) p value was <0.01.</p><p>Simultaneous inference of selection and recombination for analysis of positive selection was performed using omegaMap<sup><xref ref-type="bibr" rid="CR29">29</xref></sup>, a program for detecting natural selection and recombination based on a model of population genetics and molecular evolution. The model uses a population genetic approximation to the coalescent with recombination. This latter is estimated from patterns of linkage disequilibrium assuming that recombination events occur only between codons and not within them. OmegaMap applies reversible-jump Markov Chain Monte Carlo (MCMC) to perform Bayesian inferences of both ω and the recombination parameter ρ, allowing both parameters to vary along the sequence. An average block length of 10 and 30 codons was used to estimate ω and ρ, respectively. To determine the influence of the choice of the priors on the posteriors, analyses were repeated with alternative sets of priors (<xref rid="MOESM1" ref-type="media">Supplementary Table S2</xref>). Three independent omegaMap runs, each with 500,000 iterations and a 50,000 burn-in iteration, were compared to assess convergence and merged to obtain the posterior probability estimate.</p><p>The REL (random effects likelihood) analysis models variation in both dN and dS across sites according to a predefined distribution with different rate classes; positively selected sites are identified through an empirical Bayes method<sup><xref ref-type="bibr" rid="CR51">51</xref></sup>. The default criterion of a Bayes Factor >50 was used to identify positively selected sites.</p><p>For GARD, MEME and REL the nucleotide substitution models were chosen using a Genetic Algorithm implemented in the dataMonkey suite<sup><xref ref-type="bibr" rid="CR52">52</xref></sup>. All analyses were performed through the DataMonkey server<sup><xref ref-type="bibr" rid="CR53">53</xref></sup> (<ext-link ext-link-type="uri" xlink:href="http://www.datamonkey.org">http://www.datamonkey.org</ext-link>).</p></sec><sec id="Sec11"><title>In silico analysis of HR1 variants</title><p>The crystal structure of MERS-CoV HR1 and HR2 region was obtained from PDB (PDB ID: 4MOD).</p><p>Histidine or arginine residues were introduced at positions 1020 and suitable rotamers were sampled through the rapid torsion scan utility in Maestro (Maestro. 9.1; Schrodinger). Intraprotein interactions were calculated with PIC (protein interaction calculator)<sup><xref ref-type="bibr" rid="CR54">54</xref></sup>.</p><p>Because programs that calculate stability changes achieve only moderate accuracy<sup><xref ref-type="bibr" rid="CR55">55</xref></sup>, we used three different methods to assure reliability. These approaches are based on different principles. Specifically, PoPMuSiC uses statistical potentials and takes into account amino acid volume variation upon mutation<sup><xref ref-type="bibr" rid="CR33">33</xref></sup>; FoldX uses an empirical force field and evaluates the energetic effect of point mutations and the interactions contributing to the stability of proteins<sup><xref ref-type="bibr" rid="CR32">32</xref></sup>. Finally, I-Mutant 2.0 is based on a neural network approach to evaluate the free energy change after a single point mutation with incorporation of information on the three-dimensional structure of the protein<sup><xref ref-type="bibr" rid="CR34">34</xref></sup>.</p><p>In FoldX and I-Mutant the ΔΔG values are calculated as follows: <italic>ΔΔG</italic> = <italic>ΔG</italic><sub><italic>mutant</italic></sub> − <italic>ΔG</italic><sub><italic>wild-type</italic></sub>. In FoldX and I-Mutant ΔΔG values > 0 kcal/mol indicate mutations that decrease protein stability, whereas in PoPMuSiC ΔΔG values > 0 kcal/mol are mark of mutations increasing protein stability. Therefore, PoPMuSiC ΔΔG values were multiplied by −1 to obtain homogeneous results.</p><p>In the analysis carried out with FoldX 3D, the three-dimensional structure of the protein was repaired using the command. Mutations were introduced using the command with set to 5 and set to 0. Temperature (298K), ionic strength (0.05 M) and pH (7) were set to default values and the force-field was used to predict the water molecules on the protein surface.</p> </sec></sec><sec id="Sec12"><title>Additional Information</title><p><bold>How to cite this article</bold>: Forni, D. <italic>et al.</italic> The heptad repeat region is a major selection target in MERS-CoV and related coronaviruses. <italic>Sci. Rep.</italic><bold>5</bold>, 14480; doi: 10.1038/srep14480 (2015).</p></sec><sec sec-type="supplementary-material"><title>Electronic supplementary material</title><sec id="Sec13"><p><supplementary-material content-type="local-data" id="MOESM1"><media xlink:href="41598_2015_BFsrep14480_MOESM1_ESM.pdf"><caption><p>Supplementary Information</p></caption></media></supplementary-material></p></sec></sec></body><back><ack><title>Acknowledgements</title><p>NAD is supported by the Deanship of Scientific Research, Prolific Research Group Program (PRG-1436-15), Vice Rectorate for Graduate Studies and Scientific Research in King Saud University (KSU), Riyadh, Saudi Arabia.</p></ack><notes notes-type="author-contribution"><title>Author Contributions</title><p>M.S. and D.F. conceived the study; M.S. and M.C. supervised the project; D.F., R.C., U.P. and N.A.D. performed the evolutionary analysis; L.D.G. and G.F. performed the <italic>in silico</italic> studies; D.F. and G.F. produced the figures, with input from all authors; U.P. provided support during the bioinformatic analyses; M.S. wrote the manuscript, with critical input from M.C. and from the remaining authors.</p></notes><notes notes-type="COI-statement"><title>Competing interests</title><p>The authors declare no competing financial interests.</p></notes><ref-list id="Bib1"><title>References</title><ref id="CR1"><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zaki</surname><given-names>AM</given-names></name><name><surname>van Boheemen</surname><given-names>S</given-names></name><name><surname>Bestebroer</surname><given-names>TM</given-names></name><name><surname>Osterhaus</surname><given-names>AD</given-names></name><name><surname>Fouchier</surname><given-names>RA</given-names></name></person-group><article-title>Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia</article-title><source>N. 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