Evaluation of eight different bioinformatics tools to predict viral tropism in different human immunodeficiency virus type 1 subtypes.
Human immunodeficiency virus type 1 (HIV-1) tropism can be assessed using phenotypic assays, but this is quite laborious, expensive, and time-consuming and can be made only in sophisticated laboratories. More accessible albeit reliable tools for testing of HIV-1 tropism are needed in view of the prompt introduction of CCR5 antagonists in clinical practice. Bioinformatics tools based on V3 sequences might help to predict HIV-1 tropism; however, most of these methods have been designed by taking only genetic information derived from HIV-1 subtype B into consideration. The aim of this study was to evaluate the performances of several genotypic tools to predict HIV-1 tropism in non-B subtypes, as data on this issue are scarce. Plasma samples were tested using a new phenotypic tropism assay (Phenoscript-tropism; Eurofins), and results were compared with estimates of coreceptor usage using eight different genotypic predictor softwares (Support Vector Machine [SVM], C4.5, C4.5 with positions 8 to 12 only, PART, Charge Rule, geno2pheno coreceptor, Position-Specific Scoring Matrix X4R5 [PSSM(X4R5)], and PSSM(sinsi)). A total of 150 samples were tested, with 115 belonging to patients infected with non-B subtypes and 35 drawn from subtype B-infected patients, which were taken as controls. When non-B subtypes were tested, the concordances between the results obtained using the phenotypic assay and distinct genotypic tools were as follows: 78.8% for SVM, 77.5% for C4.5, 82.5% for C4.5 with positions 8 to 12 only, 82.5% for PART, 82.5% for Charge Rule, 82.5% for PSSM(X4R5), 83.8% for PSSM(sinsi), and 71.3% for geno2pheno. When clade B viruses were tested, the best concordances were seen for PSSM(X4R5) (91.4%), PSSM(sinsi) (88.6%), and geno2pheno (88.6%). The sensitivity for detecting X4 variants was lower for non-B than for B viruses, especially in the case of PSSM(sinsi) (38.4% versus 100%, respectively), SVM(wetcat) (46% versus 100%, respectively), and PART (30% versus 90%, respectively). In summary, while inferences of HIV-1 coreceptor usage using genotypic tools seem to be reliable for clade B viruses, their performances are poor for non-B subtypes, in which they particularly fail to detect X4 variants.
Garrido
Carolina
C
Hospital Carlos III, Sinesio Delgado 10, 28029 Madrid, Spain.
Roulet
Vanessa
V
Chueca
Natalia
N
Poveda
Eva
E
Aguilera
Antonio
A
Skrabal
Katharina
K
Zahonero
Natalia
N
Carlos
Silvia
S
García
Federico
F
Faudon
Jean Louis
JL
Soriano
Vincent
V
de Mendoza
Carmen
C
D000328:Adult; D015704:CD4 Antigens / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D005260:Female; D005838:Genotype; D015699:HIV Envelope Protein gp120 / Q000235:genetics* / Q000378:metabolism; D015658:HIV Infections / Q000821:virology*; D015497:HIV-1 / Q000145:classification* / Q000235:genetics / Q000378:metabolism / Q000472:pathogenicity*; D006801:Humans; D008297:Male; D008875:Middle Aged; D010446:Peptide Fragments / Q000235:genetics* / Q000378:metabolism; D010641:Phenotype; D011933:Reagent Kits, Diagnostic; D019713:Receptors, CCR5 / Q000378:metabolism*; D019718:Receptors, CXCR4 / Q000378:metabolism*; D012680:Sensitivity and Specificity
D015704:CD4 Antigens; C527276:CXCR4 protein, human; D015699:HIV Envelope Protein gp120; C059762:HIV envelope protein gp120 (305-321); D010446:Peptide Fragments; D011933:Reagent Kits, Diagnostic; D019713:Receptors, CCR5; D019718:Receptors, CXCR4