{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,6]],"date-time":"2026-04-06T14:45:44Z","timestamp":1775486744840,"version":"3.50.1"},"reference-count":36,"publisher":"Microbiology Society","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2010,8,1]]},"abstract":"<jats:p>A better understanding of human immunodeficiency virus type 1 drug-resistance evolution under the selective pressure of combination treatment is important for the design of long-term effective treatment strategies. We applied Bayesian network learning to sequences from patients treated with the reverse transcriptase inhibitor combination of zidovudine (AZT) and lamivudine (3TC) to identify the role of many treatment-selected mutations in the development of resistance. Based on the Bayesian network structure, an<jats:italic>in vivo<\/jats:italic>fitness landscape was built, reflecting the necessary selective pressure under treatment, to evolve naive sequences to sequences obtained from patients treated with the combination. This landscape, combined with an evolutionary model, was used to predict resistance evolution in longitudinal sequence pairs. In our analysis, mutations 41L, 70R, 184V and 215F\/Y were identified as major resistance mutations to the combination of AZT and 3TC, as they were associated directly with treatment experience. The network also suggested a possible role in resistance development for a number of novel mutations. Estimated fitness, using the landscape, correlated significantly with<jats:italic>in vitro<\/jats:italic>resistance phenotype in genotype\u2013phenotype pairs (<jats:italic>R<\/jats:italic><jats:sup>2<\/jats:sup>=0.70). Variation in predicted evolution under selective pressure correlated significantly with observed<jats:italic>in vivo<\/jats:italic>evolution during AZT plus 3CT treatment. In conclusion, we confirmed current knowledge on resistance development to the combination of AZT and 3CT, but additional novel mutations were identified. Moreover, a model to predict resistance evolution during AZT and 3CT treatment has been built and validated.<\/jats:p>","DOI":"10.1099\/vir.0.022657-0","type":"journal-article","created":{"date-parts":[[2010,4,22]],"date-time":"2010-04-22T02:24:37Z","timestamp":1271903077000},"page":"1898-1908","source":"Crossref","is-referenced-by-count":15,"title":["Resistance pathways of human immunodeficiency virus type 1 against the combination of zidovudine and lamivudine"],"prefix":"10.1099","volume":"91","author":[{"given":"K.","family":"Theys","sequence":"first","affiliation":[{"name":"Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium"}]},{"given":"K.","family":"Deforche","sequence":"additional","affiliation":[{"name":"MyBioData, Rotselaar, Belgium"}]},{"given":"P.","family":"Libin","sequence":"additional","affiliation":[{"name":"MyBioData, Rotselaar, Belgium"}]},{"given":"R. J.","family":"Camacho","sequence":"additional","affiliation":[{"name":"Instituto de Higiene e Medicina Tropical, Universidade Nova de Lisboa, Lisbon, Portugal"}]},{"given":"K.","family":"Van Laethem","sequence":"additional","affiliation":[{"name":"Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium"}]},{"given":"A.-M.","family":"Vandamme","sequence":"additional","affiliation":[{"name":"Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium"}]}],"member":"345","reference":[{"key":"R1","doi-asserted-by":"crossref","first-page":"3943","DOI":"10.1093\/bioinformatics\/bti654","article-title":"Computational methods for the design of effective therapies against drug resistant HIV strains","volume":"21","author":"Beerenwinkel","year":"2005a","journal-title":"Bioinformatics"},{"key":"R2","doi-asserted-by":"crossref","first-page":"1953","DOI":"10.1086\/430005","article-title":"Estimating HIV evolutionary pathways and the genetic barrier to drug resistance","volume":"191","author":"Beerenwinkel","year":"2005b","journal-title":"J Infect Dis"},{"key":"R3","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1089\/cmb.2005.12.584","article-title":"Learning multiple evolutionary pathways from cross-sectional data","volume":"12","author":"Beerenwinkel","year":"2005c","journal-title":"J Comput Biol"},{"key":"R4","doi-asserted-by":"crossref","first-page":"e4724","DOI":"10.1371\/journal.pone.0004724","article-title":"Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update","volume":"4","author":"Bennett","year":"2009","journal-title":"PLoS One"},{"key":"R5","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1093\/infdis\/165.1.105","article-title":"Ordered appearance of zidovudine resistance mutations during treatment of 18 human immunodeficiency virus-positive subjects","volume":"165","author":"Boucher","year":"1992","journal-title":"J Infect Dis"},{"key":"R6","doi-asserted-by":"crossref","first-page":"2231","DOI":"10.1128\/AAC.37.10.2231","article-title":"High-level resistance to (\u2212) enantiomeric 2\u2032-deoxy-3\u2032-thiacytidine in vitro is due to one amino acid substitution in the catalytic site of human immunodeficiency virus type 1 reverse transcriptase","volume":"37","author":"Boucher","year":"1993","journal-title":"Antimicrob Agents Chemother"},{"key":"R7","doi-asserted-by":"crossref","first-page":"11507","DOI":"10.1128\/JVI.00303-07","article-title":"Characterization and structural analysis of novel mutations in human immunodeficiency virus type 1 reverse transcriptase involved in the regulation of resistance to nonnucleoside inhibitors","volume":"81","author":"Ceccherini-Silberstein","year":"2007","journal-title":"J Virol"},{"key":"R8","doi-asserted-by":"crossref","first-page":"791","DOI":"10.1177\/135965350501000705","article-title":"Thymidine analogue mutation profiles: factors associated with acquiring specific profiles and their impact on the virological response to therapy","volume":"10","author":"Cozzi-Lepri","year":"2005","journal-title":"Antivir Ther"},{"key":"R9","doi-asserted-by":"crossref","first-page":"2975","DOI":"10.1093\/bioinformatics\/btl508","article-title":"Analysis of HIV-1 pol sequences using Bayesian networks: implications for drug resistance","volume":"22","author":"Deforche","year":"2006","journal-title":"Bioinformatics"},{"key":"R10","doi-asserted-by":"crossref","first-page":"382","DOI":"10.1016\/j.meegid.2006.09.004","article-title":"Bayesian network analysis of resistance pathways against HIV-1 protease inhibitors","volume":"7","author":"Deforche","year":"2007a","journal-title":"Infect Genet Evol"},{"key":"R11","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1089\/cmb.2007.0073","article-title":"Estimating the relative contribution of dNTP pool imbalance and APOBEC3G\/3F editing to HIV evolution in vivo","volume":"14","author":"Deforche","year":"2007b","journal-title":"J Comput Biol"},{"key":"R12","doi-asserted-by":"crossref","first-page":"2107","DOI":"10.1097\/QAD.0b013e32830fe940","article-title":"Bayesian network analyses of resistance pathways against efavirenz and nevirapine","volume":"22","author":"Deforche","year":"2008a","journal-title":"AIDS"},{"key":"R13","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1093\/bioinformatics\/btm540","article-title":"Estimation of an in vivo fitness landscape experienced by HIV-1 under drug selective pressure useful for prediction of drug resistance evolution during treatment","volume":"24","author":"Deforche","year":"2008b","journal-title":"Bioinformatics"},{"key":"R14","first-page":"399","article-title":"& other authors (2008c). 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