{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,8,13]],"date-time":"2022-08-13T04:06:06Z","timestamp":1660363566640},"reference-count":29,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T00:00:00Z","timestamp":1660262400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T00:00:00Z","timestamp":1660262400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Influenza A viruses (IAV) exhibit vast genetic mutability and have great zoonotic potential to infect avian and mammalian hosts and are known to be responsible for a number of pandemics. A key computational issue in influenza prevention and control is the identification of molecular signatures with cross-species transmission potential. We propose an adjusted entropy-based host-specific signature identification method that uses a similarity coefficient to incorporate the amino acid substitution information and improve the identification performance. Mutations in the polymerase genes (e.g., PB2) are known to play a major role in avian influenza virus adaptation to mammalian hosts. We thus focus on the analysis of PB2 protein sequences and identify host specific PB2 amino acid signatures.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>Validation with a set of H5N1 PB2 sequences from 1996 to 2006 results in adjusted entropy having a 40% false negative discovery rate compared to a 60% false negative rate using unadjusted entropy. Simulations across different levels of sequence divergence show a false negative rate of no higher than 10% while unadjusted entropy ranged from 9 to 100%. In addition, under all levels of divergence adjusted entropy never had a false positive rate higher than 9%. Adjusted entropy also identifies important mutations in H1N1pdm PB2 previously identified in the literature that explain changes in divergence between 2008 and 2009 which unadjusted entropy could not identify.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>Based on these results, adjusted entropy provides a reliable and widely applicable host signature identification approach useful for IAV monitoring and vaccine development.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-022-04885-7","type":"journal-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T08:08:56Z","timestamp":1660291736000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Identifying host-specific amino acid signatures for influenza A viruses using an adjusted entropy measure"],"prefix":"10.1186","volume":"23","author":[{"given":"Yixiang","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kent M.","family":"Eskridge","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunpu","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoqing","family":"Lu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,8,12]]},"reference":[{"key":"4885_CR1","unstructured":"Zhang Y. Novel protein functional analysis based on weighted & directed protein overlap network and adjusted entropy measurements. Diss. The University of Nebraska-Lincoln. 2016."},{"key":"4885_CR2","doi-asserted-by":"publisher","first-page":"1861","DOI":"10.1098\/rstb.2001.0999","volume":"356","author":"AJ Hay","year":"2001","unstructured":"Hay AJ, Gregory V, Douglas AR, Lin YP. The evolution of human influenza viruses. Philos Trans R Soc Lond Ser B. 2001;356:1861.","journal-title":"Philos Trans R Soc Lond Ser B"},{"key":"4885_CR3","doi-asserted-by":"publisher","first-page":"e84638","DOI":"10.1371\/journal.pone.0084638","volume":"9","author":"Y-J Hu","year":"2014","unstructured":"Hu Y-J, Tu P-C, Lin C-S, Guo S-T. Identification and chronological analysis of genomic signatures in influenza A viruses. PLoS ONE. 2014;9:e84638.","journal-title":"PLoS ONE"},{"key":"4885_CR4","doi-asserted-by":"publisher","first-page":"2060","DOI":"10.1016\/j.mcm.2010.06.008","volume":"52","author":"X Qiang","year":"2010","unstructured":"Qiang X, Kou Z. Prediction of interspecies transmission for avian influenza A virus based on a back-propagation neural network. Math Comput Model. 2010;52:2060\u20135.","journal-title":"Math Comput Model"},{"key":"4885_CR5","doi-asserted-by":"publisher","first-page":"S1","DOI":"10.1186\/1755-8794-7-S3-S1","volume":"7","author":"CLP Eng","year":"2014","unstructured":"Eng CLP, Tong JC, Tan TW. Predicting host tropism of influenza A virus proteins using random forest. BMC Med Genom. 2014;7:S1.","journal-title":"BMC Med Genom"},{"key":"4885_CR6","doi-asserted-by":"publisher","first-page":"166","DOI":"10.1504\/IJDMB.2013.053198","volume":"7","author":"J Wang","year":"2013","unstructured":"Wang J, Ma C, Kou Z, Zhou Y-H, Liu H-L. Predicting transmission of avian influenza A viruses from avian to human by using informative physicochemical properties. Int J Data Min Bioinform. 2013;7:166\u201379.","journal-title":"Int J Data Min Bioinform"},{"key":"4885_CR7","doi-asserted-by":"publisher","first-page":"1353","DOI":"10.3201\/eid1209.060276","volume":"12","author":"G-W Chen","year":"2006","unstructured":"Chen G-W, Chang S-C, Mok C-K, Lo Y-L, Kung Y-N, Huang J-H, Shih Y-H, Wang J-Y, Chiang C, Chen C-J, et al. Genomic signatures of human versus avian influenza A viruses. Emerg Infect Diseases. 2006;12:1353.","journal-title":"Emerg Infect Diseases"},{"key":"4885_CR8","doi-asserted-by":"publisher","first-page":"10292","DOI":"10.1128\/JVI.00921-07","volume":"81","author":"DB Finkelstein","year":"2007","unstructured":"Finkelstein DB, Mukatira S, Mehta PK, Obenauer JC, Su X, Webster RG, Naeve CW. Persistent host markers in pandemic and H5N1 influenza viruses. J Virol. 2007;81:10292\u20139.","journal-title":"J Virol"},{"key":"4885_CR9","doi-asserted-by":"publisher","first-page":"e9025","DOI":"10.1371\/journal.pone.0009025","volume":"5","author":"O Miotto","year":"2010","unstructured":"Miotto O, Heiny AT, Albrecht R, Garcia-Sastre A, Tan TW, Augusty JT, Brusic V. Complete-proteome mapping of human influenza A adaptive mutations: implications for human transmissibility of zoonotic strains. PLoS ONE. 2010;5:e9025.","journal-title":"PLoS ONE"},{"key":"4885_CR10","doi-asserted-by":"publisher","first-page":"1135","DOI":"10.3390\/ijms18061135","volume":"18","author":"C Eng","year":"2017","unstructured":"Eng C, Tong J, Tan T. Predicting zoonotic risk of influenza A viruses from host tropism protein signature using random forest. Int J Mol Sci. 2017;18:1135.","journal-title":"Int J Mol Sci"},{"key":"4885_CR11","doi-asserted-by":"publisher","first-page":"1584","DOI":"10.3390\/molecules23071584","volume":"23","author":"X Qiang","year":"2018","unstructured":"Qiang X, Kou Z, Fang G, Wang Y. Scoring amino acid mutations to predict avian-to-human transmission of avian influenza viruses. Molecules. 2018;23:1584.","journal-title":"Molecules"},{"key":"4885_CR12","doi-asserted-by":"publisher","first-page":"1840023","DOI":"10.1142\/S0219720018400231","volume":"16","author":"R Yin","year":"2018","unstructured":"Yin R, Zhou X, Zheng J, Kwoh CK. Computational identification of physicochemical signatures for host tropism of influenza A virus. J Bioinform Comput Biol. 2018;16:1840023\u20131840023.","journal-title":"J Bioinform Comput Biol"},{"key":"4885_CR13","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1186\/s12864-016-2919-4","volume":"17","author":"Z Khaliq","year":"2016","unstructured":"Khaliq Z, Leijon M, Bel\u00e1k S, Komorowski J. Identification of combinatorial host-specific signatures with a potential to affect host adaptation in influenza A H1N1 and H3N2 subtypes. BMC Genom. 2016;17:529.","journal-title":"BMC Genom"},{"key":"4885_CR14","doi-asserted-by":"publisher","first-page":"459","DOI":"10.1093\/protein\/14.7.459","volume":"14","author":"SI Rogov","year":"2001","unstructured":"Rogov SI, Nekrasov AN. A numerical measure of amino acid residues similarity based on the analysis of their surroundings in natural protein sequences. Protein Eng. 2001;14:459\u201363.","journal-title":"Protein Eng"},{"key":"4885_CR15","unstructured":"Schwartz RM. Matrices for detecting distant relationships. Atlas Protein Seq Struct 353\u2013359 (1978)"},{"key":"4885_CR16","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1093\/bioinformatics\/8.3.275","volume":"8","author":"DT Jones","year":"1992","unstructured":"Jones DT, Taylor WR, Thornton JM. The rapid generation of mutation data matrices from protein sequences. Bioinformatics. 1992;8:275\u201382.","journal-title":"Bioinformatics"},{"key":"4885_CR17","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1126\/science.1604319","volume":"256","author":"GH Gonnet","year":"1992","unstructured":"Gonnet GH, Cohen MA, Benner SA. Exhaustive matching of the entire protein sequence database. Science. 1992;256:1443\u20135.","journal-title":"Science"},{"key":"4885_CR18","doi-asserted-by":"publisher","first-page":"10915","DOI":"10.1073\/pnas.89.22.10915","volume":"89","author":"S Henikoff","year":"1992","unstructured":"Henikoff S, Henikoff JG. Amino acid substitution matrices from protein blocks. Proc Natl Acad Sci. 1992;89:10915\u20139.","journal-title":"Proc Natl Acad Sci"},{"key":"4885_CR19","first-page":"345","volume":"5","author":"MO Dayhoff","year":"1978","unstructured":"Dayhoff MO, Schwartz RM, Orcutt BC. 22 a model of evolutionary change in proteins. Atlas Protein Seq Struct. 1978;5:345\u201352.","journal-title":"Atlas Protein Seq Struct"},{"key":"4885_CR20","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1093\/oxfordjournals.molbev.a003985","volume":"19","author":"T M\u00fcller","year":"2002","unstructured":"M\u00fcller T, Spang R, Vingron M. Estimating amino acid substitution models: a comparison of Dayhoff\u2019s estimator, the resolvent approach and a maximum likelihood method. Mol Biol Evol. 2002;19:8\u201313.","journal-title":"Mol Biol Evol"},{"key":"4885_CR21","doi-asserted-by":"publisher","first-page":"1307","DOI":"10.1093\/molbev\/msn067","volume":"25","author":"SQ Le","year":"2008","unstructured":"Le SQ, Gascuel O. An improved general amino acid replacement matrix. Mol Biol Evol. 2008;25:1307\u201320.","journal-title":"Mol Biol Evol"},{"key":"4885_CR22","unstructured":"Dang CC, Quang LS, Vinh LS, et al. A fast and efficient method for estimating amino acid substitution models. In: 2011 third international conference on knowledge and systems engineering (KSE) (2011)"},{"key":"4885_CR23","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1186\/1471-2148-10-99","volume":"10","author":"CC Dang","year":"2010","unstructured":"Dang CC, Le QS, Gascuel O, Le VS. FLU, an amino acid substitution model for influenza proteins. BMC Evol Biol. 2010;10:99.","journal-title":"BMC Evol Biol"},{"key":"4885_CR24","doi-asserted-by":"publisher","first-page":"1897","DOI":"10.3201\/eid1512.090845","volume":"15","author":"G-W Chen","year":"2009","unstructured":"Chen G-W, Shih S-R. Genomic signatures of influenza A pandemic (H1N1) 2009 virus. Emerg Infect Dis. 2009;15:1897.","journal-title":"Emerg Infect Dis"},{"key":"4885_CR25","unstructured":"Centers for Disease Control. First global estimates of 2009 H1N1 pandemic mortality released by CDC-led collaboration. Centers for Disease Control, Atlanta, GA (2012)"},{"key":"4885_CR26","doi-asserted-by":"publisher","first-page":"3472","DOI":"10.1093\/gbe\/evv240","volume":"7","author":"SS Belanov","year":"2015","unstructured":"Belanov SS, Bychkov D, Benner C, Ripatti S, Ojala T, Kankainen M, Kai Lee H, Wei-Tze Tang J, Kainov DE. Genome-wide analysis of evolutionary markers of human influenza A (H1N1) pdm09 and A (H3N2) viruses may guide selection of vaccine strain candidates. Genome Biol Evol. 2015;7:3472\u201383.","journal-title":"Genome Biol Evol"},{"key":"4885_CR27","doi-asserted-by":"publisher","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","volume":"27","author":"CE Shannon","year":"1948","unstructured":"Shannon CE. A mathematical theory of communication. Bell Syst Tech J. 1948;27:379\u2013423.","journal-title":"Bell Syst Tech J"},{"key":"4885_CR28","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1002\/0471250953.bi0305s43","volume":"43","author":"WR Pearson","year":"2013","unstructured":"Pearson WR. Selecting the right similarity-scoring matrix. Curr Protoc Bioinform. 2013;43:3\u20135.","journal-title":"Curr Protoc Bioinform"},{"key":"4885_CR29","doi-asserted-by":"publisher","first-page":"1792","DOI":"10.1093\/nar\/gkh340","volume":"32","author":"RC Edgar","year":"2004","unstructured":"Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792\u20137.","journal-title":"Nucleic Acids Res"}],"container-title":["BMC Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04885-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12859-022-04885-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12859-022-04885-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T08:09:19Z","timestamp":1660291759000},"score":1,"resource":{"primary":{"URL":"https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-022-04885-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,12]]},"references-count":29,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["4885"],"URL":"https:\/\/doi.org\/10.1186\/s12859-022-04885-7","relation":{},"ISSN":["1471-2105"],"issn-type":[{"value":"1471-2105","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,8,12]]},"assertion":[{"value":"14 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 August 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 August 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}],"article-number":"333"}}