Open AccessThe Impact of Individual Human Immunodeficiency Virus Type 1 Protease Mutations on Drug Susceptibility Is Highly Influenced by Complex Interactions with the Background Protease Sequence
Author(s) -
Herwig Van Marck,
Inge Dierynck,
Guenter Kraus,
Sabine Hallenberger,
Theresa Pattery,
Gaëtan Muyldermans,
Luc Geeraert,
L. Borozdina,
Rachelle Bonesteel,
Colin Aston,
Elliott Shaw,
Q. Chen,
Concepción Martínez,
V. Koka,
J. Lee,
Ellen Chi,
M.-P. De Béthune,
Kurt Hertogs
Publication year - 2009
Publication title -
journal of virology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.617
H-Index - 292
eISSN - 1070-6321
pISSN - 0022-538X
DOI - 10.1128/jvi.00291-09
Subject(s) - biology , protease , mutation , genetics , darunavir , virus , virology , drug resistance , mutant , wild type , resistance mutation , viral evolution , gene , viral load , reverse transcriptase , enzyme , polymerase chain reaction , genome , antiretroviral therapy , biochemistry
The requirement for multiple mutations for protease inhibitor (PI) resistance necessitates a better understanding of the molecular basis of resistance development. The novel bioinformatics resistance determination approach presented here elaborates on genetic profiles observed in clinical human immunodeficiency virus type 1 (HIV-1) isolates. Synthetic protease sequences were cloned in a wild-type HIV-1 background to generate a large number of close variants, covering 69 mutation clusters between multi-PI-resistant viruses and their corresponding genetically closely related, but PI-susceptible, counterparts. The vast number of mutants generated facilitates a profound and broad analysis of the influence of the background on the effect of individual PI resistance-associated mutations (PI-RAMs) on PI susceptibility. Within a set of viruses, all PI-RAMs that differed between susceptible and resistant viruses were varied while maintaining the background sequence from the resistant virus. The PI darunavir was used to evaluate PI susceptibility. Single sets allowed delineation of the impact of individual mutations on PI susceptibility, as well as the influence of PI-RAMs on one another. Comparing across sets, it could be inferred how the background influenced the interaction between two mutations, in some cases even changing antagonistic relationships into synergistic ones or vice versa. The approach elaborates on patient data and demonstrates how the specific mutational background greatly influences the impact of individual mutations on PI susceptibility in clinical patterns.