Comparative transcriptome analysis of PBMC from HIV patients pre- and post-antiretroviral therapy

Abstract

This version available http://nora.nerc.ac.uk/516128/ NERC has developed NORA to enable users to access research outputs wholly or partially funded by NERC. Copyright and other rights for material on this site are retained by the rights owners. Users should read the terms and conditions of use of this material at http://nora.nerc.ac.uk/policies.html#access NOTICE: this is the author's version of a work that was accepted for publication in Meta Gene. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Meta Gene, 12. 50-61. 10.1016Gene, 12. 50-61. 10. /j.mgene.2017 www.elsevier.com/ Contact CEH NORA team at noraceh@ceh.ac.ukThe NERC and CEH trademarks and logos ('the Trademarks') are registered trademarks of NERC in the UK and other countries, and may not be used without the prior written consent of the Trademark owner. Sequencing strategy: paired-end sequencing) as described in previous article [28]. 2.4.Mapping reads to the human genome and transcriptome database 141The reference sequences used in this study were the human genome and transcriptome sequences 142 downloaded from the UCSC website (http://genome.ucsc.edu/index.html, version hg19). After the removal 143 of low quality reads, clean reads were aligned to the reference genome or transcriptome using SOAP2 [29]. 144No more than five mismatches were allowed in the alignment of each read. Reads that could be uniquely mapped to a reference gene were used to calculate the expression level. 148The gene expression level was measured based on the number of uniquely mapped reads per kilo-base of Table S1) and SYBR® Green (One Step SYBR PrimeScript RT-PCR Kit, TaKaRa). The signature distinct from those of the other patients at both pre-and post-HAART, whereas the transcriptomes 233 of P2, P3, H1 and H2 clustered together and displayed similar gene expression profiles (Fig. 1). Given that 234P1 developed TB-IRIS, it is tempting to speculate that the complication of TB-IRIS was accountable for the 235 reprogramming of the host's whole transcriptome Furthermore, the striking alteration in the transcriptome of 236P1 at pre-vs post-treatment (Fig 1) was likely to be a real demonstration of the effectiveness of HAART, in 237 light of the dramatic decline of viral load and the considerable recovery of CD4-cells (Table 1). Though Identification of HAART-induced differentially expressed genes (DEGs) 246Even though the total number of genes detected in each subject exceeded 15,000, the numbers of DEGs 247 in each individual varied greatly, ranging from >2000 (e.g.P3) to <50 (e.g.H1) ( Fig. 2A, Supplementary Fig. 248S1 and Supplementary Table S3 and S4). H1 control had the minimal DEGs in response to HAART (number 249 42), while P3 had the most DEGs induced by HAART (number 2,083) (Fig 2A). More DEGs were ...

Both anti-inflammatory and antiviral properties of novel drug candidate ABX464 are mediated by modulation of RNA splicing

“…To ensure that ABX464 acted specifically on HIV splicing and did not significantly or globally affect the splicing events of human genes, we used a high-throughput RNAseq approach. Many genome-wide expression studies of HIV infection are based on analyses of total peripheral blood mononuclear cells (PBMCs) 38,39 , which consist of over a dozen cell subsets, including T cells, B cells, NK cells and monocytes. To avoid the dilution of the specific gene expression signals of particular cell subsets by those from the other cells and thus a reduction of the specificity of this approach, we used purified CD4+ T cells from the PBMCs of 4 donors.…”

CD71 + Erythroid Cells Exacerbate HIV-1 Susceptibility, Mediate trans -Infection, and Harbor Infective Viral Particles

“…Another important upregulated gene was the AQP9 gene, expression of which in peripheral blood mononuclear cells (PBMCs) of HIV-infected individuals has already been reported (44). Although its role in HIV infection is unknown, we suggest AQP9 may act as an ROS scavenger to prevent T cells apoptosis (29).…”

CD71+erythroid cells exacerbate HIV-1 infection by reactive oxygen species and trans-infect HIV to CD4+T cells

“…Another important upregulated gene was AQP9, which its expression in PBMCs of HIVinfected individuals has already been reported (42). Although, its role in HIV infection is unknown, we suggest AQP9 may act as a ROS scavenger to prevent T cells apoptosis (27).…”