Literature DB >> 21118549

Structure of HIV-1 quasi-species as early indicator for switches of co-receptor tropism.

J Nikolaj Dybowski1, Dominik Heider, Daniel Hoffmann.   

Abstract

Deep sequencing is able to generate a complete picture of the retroviral quasi-species in a patient. We demonstrate that the unprecedented power of deep sequencing in conjunction with computational data analysis has great potential for clinical diagnostics and basic research. Specifically, we analyzed longitudinal deep sequencing data from patients in a study with Vicriviroc, a drug that blocks the HIV-1 co-receptor CCR5. Sequences covered the V3-loop of gp120, known to be the main determinant of co-receptor tropism. First, we evaluated this data with a computational model for the interpretation of V3-sequences with respect to tropism, and we found complete agreement with results from phenotypic assays. Thus, the method could be applied in cases where phenotypic assays fail. Second, computational analysis led to the discovery of a characteristic pattern in the quasi-species that foreshadows switches of co-receptor tropism. This analysis could help to unravel the mechanism of tropism switches, and to predict these switches weeks to months before they can be detected by a phenotypic assay.

Entities:  

Year:  2010        PMID: 21118549      PMCID: PMC3009693          DOI: 10.1186/1742-6405-7-41

Source DB:  PubMed          Journal:  AIDS Res Ther        ISSN: 1742-6405            Impact factor:   2.250


  22 in total

1.  A new perspective on V3 phenotype prediction.

Authors:  Satish Pillai; Benjamin Good; Douglas Richman; Jacques Corbeil
Journal:  AIDS Res Hum Retroviruses       Date:  2003-02       Impact factor: 2.205

2.  Amino acid substitution matrices from protein blocks.

Authors:  S Henikoff; J G Henikoff
Journal:  Proc Natl Acad Sci U S A       Date:  1992-11-15       Impact factor: 11.205

3.  A simple method for displaying the hydropathic character of a protein.

Authors:  J Kyte; R F Doolittle
Journal:  J Mol Biol       Date:  1982-05-05       Impact factor: 5.469

4.  Determining human immunodeficiency virus coreceptor use in a clinical setting: degree of correlation between two phenotypic assays and a bioinformatic model.

Authors:  Katharina Skrabal; Andrew J Low; Winnie Dong; Tobias Sing; Peter K Cheung; Fabrizio Mammano; P Richard Harrigan
Journal:  J Clin Microbiol       Date:  2006-11-22       Impact factor: 5.948

5.  Prediction of co-receptor usage of HIV-1 from genotype.

Authors:  J Nikolaj Dybowski; Dominik Heider; Daniel Hoffmann
Journal:  PLoS Comput Biol       Date:  2010-04-15       Impact factor: 4.475

6.  HIV-1 V3 envelope deep sequencing for clinical plasma specimens failing in phenotypic tropism assays.

Authors:  Ina Vandenbroucke; Herwig Van Marck; Wendy Mostmans; Veerle Van Eygen; Evelien Rondelez; Kim Thys; Kurt Van Baelen; Katrien Fransen; Dolores Vaira; Kabamba Kabeya; Stephane De Wit; Eric Florence; Michel Moutschen; Linos Vandekerckhove; Chris Verhofstede; Lieven J Stuyver
Journal:  AIDS Res Ther       Date:  2010-02-15       Impact factor: 2.250

7.  Current V3 genotyping algorithms are inadequate for predicting X4 co-receptor usage in clinical isolates.

Authors:  Andrew J Low; Winnie Dong; Dennison Chan; Tobias Sing; Ronald Swanstrom; Mark Jensen; Satish Pillai; Benjamin Good; P Richard Harrigan
Journal:  AIDS       Date:  2007-09-12       Impact factor: 4.177

8.  Design and validation of new genotypic tools for easy and reliable estimation of HIV tropism before using CCR5 antagonists.

Authors:  Eva Poveda; Eduardo Seclén; María del Mar González; Federico García; Natalia Chueca; Antonio Aguilera; Jose Javier Rodríguez; Juan González-Lahoz; Vincent Soriano
Journal:  J Antimicrob Chemother       Date:  2009-03-03       Impact factor: 5.790

9.  Improved coreceptor usage prediction and genotypic monitoring of R5-to-X4 transition by motif analysis of human immunodeficiency virus type 1 env V3 loop sequences.

Authors:  Mark A Jensen; Fu-Sheng Li; Angélique B van 't Wout; David C Nickle; Daniel Shriner; Hong-Xia He; Sherry McLaughlin; Raj Shankarappa; Joseph B Margolick; James I Mullins
Journal:  J Virol       Date:  2003-12       Impact factor: 5.103

10.  Quantitative deep sequencing reveals dynamic HIV-1 escape and large population shifts during CCR5 antagonist therapy in vivo.

Authors:  Athe M N Tsibris; Bette Korber; Ramy Arnaout; Carsten Russ; Chien-Chi Lo; Thomas Leitner; Brian Gaschen; James Theiler; Roger Paredes; Zhaohui Su; Michael D Hughes; Roy M Gulick; Wayne Greaves; Eoin Coakley; Charles Flexner; Chad Nusbaum; Daniel R Kuritzkes
Journal:  PLoS One       Date:  2009-05-25       Impact factor: 3.240

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  12 in total

1.  Comprehensive human virus screening using high-throughput sequencing with a user-friendly representation of bioinformatics analysis: a pilot study.

Authors:  Tom J Petty; Samuel Cordey; Ismael Padioleau; Mylène Docquier; Lara Turin; Olivier Preynat-Seauve; Evgeny M Zdobnov; Laurent Kaiser
Journal:  J Clin Microbiol       Date:  2014-07-09       Impact factor: 5.948

2.  Deep Sequencing of the HIV-1 env Gene Reveals Discrete X4 Lineages and Linkage Disequilibrium between X4 and R5 Viruses in the V1/V2 and V3 Variable Regions.

Authors:  Shuntai Zhou; Maria M Bednar; Christa B Sturdevant; Blake M Hauser; Ronald Swanstrom
Journal:  J Virol       Date:  2016-07-27       Impact factor: 5.103

3.  A simple structure-based model for the prediction of HIV-1 co-receptor tropism.

Authors:  Dominik Heider; Jan Nikolaj Dybowski; Christoph Wilms; Daniel Hoffmann
Journal:  BioData Min       Date:  2014-08-01       Impact factor: 2.522

4.  Compartmentalization and Clonal Amplification of HIV-1 in the Male Genital Tract Characterized Using Next-Generation Sequencing.

Authors:  Samuel Mundia Kariuki; Philippe Selhorst; Colin Anthony; David Matten; Melissa-Rose Abrahams; Darren P Martin; Kevin K Ariën; Kevin Rebe; Carolyn Williamson; Jeffrey R Dorfman
Journal:  J Virol       Date:  2020-06-01       Impact factor: 5.103

5.  Position-specific automated processing of V3 env ultra-deep pyrosequencing data for predicting HIV-1 tropism.

Authors:  Nicolas Jeanne; Adrien Saliou; Romain Carcenac; Caroline Lefebvre; Martine Dubois; Michelle Cazabat; Florence Nicot; Claire Loiseau; Stéphanie Raymond; Jacques Izopet; Pierre Delobel
Journal:  Sci Rep       Date:  2015-11-20       Impact factor: 4.379

6.  Frequency and predictors of HIV-1 co-receptor switch in treatment naive patients.

Authors:  Virginie Mortier; Kenny Dauwe; Leen Vancoillie; Delfien Staelens; Filip Van Wanzeele; Dirk Vogelaers; Linos Vandekerckhove; Kristen Chalmet; Chris Verhofstede
Journal:  PLoS One       Date:  2013-11-07       Impact factor: 3.240

7.  Genotypic Prediction of Co-receptor Tropism of HIV-1 Subtypes A and C.

Authors:  Mona Riemenschneider; Kieran Y Cashin; Bettina Budeus; Saleta Sierra; Elham Shirvani-Dastgerdi; Saeed Bayanolhagh; Rolf Kaiser; Paul R Gorry; Dominik Heider
Journal:  Sci Rep       Date:  2016-04-29       Impact factor: 4.379

8.  Exploiting HIV-1 protease and reverse transcriptase cross-resistance information for improved drug resistance prediction by means of multi-label classification.

Authors:  Mona Riemenschneider; Robin Senge; Ursula Neumann; Eyke Hüllermeier; Dominik Heider
Journal:  BioData Min       Date:  2016-02-29       Impact factor: 2.522

9.  SHIVA - a web application for drug resistance and tropism testing in HIV.

Authors:  Mona Riemenschneider; Thomas Hummel; Dominik Heider
Journal:  BMC Bioinformatics       Date:  2016-08-22       Impact factor: 3.169

10.  EFS: an ensemble feature selection tool implemented as R-package and web-application.

Authors:  Ursula Neumann; Nikita Genze; Dominik Heider
Journal:  BioData Min       Date:  2017-06-27       Impact factor: 2.522

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