Co-receptor usage and prediction of V3 genotyping algorithms in HIV-1 subtype B' from paid blood donors experienced anti-retroviral therapy in Chinese central province.
BACKGROUND
This study explored co-receptor usage and prediction of V3 genotyping algorithms in HIV-1 subtype B' from paid blood donors experienced anti-retroviral therapy in Chinese central province in order to design effectively therapeutic regimen.


METHODS
HIV-1 strains were isolated in treatment HIV-1 infections and treatment-naïve HIV-1 infections, then co-receptor usage of HIV-1 strains was identified based on Ghost cell lines using flow cytometry. HIV-1 V3 region was amplified and submitted into web-server (WebPSSM and geno2pheno) to predict HIV-1 co-receptor usage. The feasibility of prediction HIV-1 usage with Web-server assay was analyzed by comparing prediction of V3 genotyping algorithms with HIV phenotype assay based on Ghost cell line.


RESULTS
45 HIV-1 strains and 114 HIV-1 strains were isolated from HIV-1 infections exposed anti-retroviral therapy and treatment-naïve, respectively. 41% clinical viruses from ART patients and 18% from treatment-naïve patients used CXCR4 as co-receptor. The net charge in the V3 loop was significantly difference in both groups. The sensitivity and specificity for predicting co-receptor capacity is 54.6% and 90.0% on 11/25 rule, 50.0% and 90% on Web-PSSM(x4r5), 68.2% and 40.0% on Geno2pheno[co-receptor].


CONCLUSIONS
Dual/mixed/X4 co-receptor utilization was higher in ART patients than treatment-naïve patients. It is should paid attention to predicting HIV-1 co-receptor usage based on V3 genotyping algorithms in HIV-1 subtype B' from paid blood donors experienced anti-retroviral therapy in Chinese central province.
State Key Laboratory for Infectious Disease Control and Prevention, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Shuiling
S
Qu
Liying
L
Ma
Lin
L
Yuan
Wesi
W
Xu
Kunxue
K
Hong
Hui
H
Xing
Yang
Y
Huang
Xiaoling
X
Yu
Yiming
Y
Shao
D000328:Adult; D000465:Algorithms; D001782:Blood Donors; D002460:Cell Line; D002681:China; D016000:Cluster Analysis; D005260:Female; D005838:Genotype; D015699:HIV Envelope Protein gp120 / Q000235:genetics* / Q000378:metabolism; D015658:HIV Infections / Q000188:drug therapy* / Q000821:virology*; D015497:HIV-1 / Q000235:genetics* / Q000302:isolation & purification / Q000502:physiology; D006801:Humans; D020407:Internet; D008297:Male; D008875:Middle Aged; D010802:Phylogeny; D015728:Receptors, HIV / Q000378:metabolism*; D014773:Virology / Q000379:methods; D053585:Virus Attachment
D015699:HIV Envelope Protein gp120; D015728:Receptors, HIV; C514793:gp120 protein, Human immunodeficiency virus 1