Background: Elite controller refers to a patient with human immunodeficiency virus infection with an undetected viral load in the absence of highly active antiretroviral therapy. Studies on gene expression and regulation in these individuals are limited but significant, and have helped researchers and clinicians to understand the interrelationships between HIV and its host.
Methods: We collected CD4 T-cell samples from two elite controllers (ECs), two HIV-positive infected patients (HPs), and two healthy controls (HCs) to perform second-generation transcriptome sequencing. Using the Cufflinks software, we calculated the Fragments Per Kilobase of transcript per Million fragments mapped (FPKM) and identified differentially expressed (DE) mRNAs and long non-coding RNAs (lncRNAs), with corrected P value < 0.05 (based on a false discovery rate (FDR) < 0.05). We then constructed a protein-protein interaction network using cytoHubba and a long non-coding RNA-mRNA co-expression network based on the Pearson correlation coefficient.
Results: In total, 1109 linear correlations of DE lncRNAs targeting DE mRNAs were found and several interesting interactions were identified as being associated with viral infections and immune responses within the networks based on these correlations. Among these lncRNA-mRNA relationships, hub mRNAs including HDAC6, MAPK8, MAPK9, ATM and their corresponding annotated co-expressed lncRNAs presented strong correlations with the MAPK-NF-kappa B pathway, which plays a role in the reactivation and replication of the virus.
Conclusions: Using RNA-sequencing, we systematically analyzed the expression profiles of lncRNAs and mRNAs from CD4+ T cells from ECs, HPs, and HCs, and constructed a co-expression network based on the relationships among DE transcripts and database annotations. This was the first study to examine gene transcription in elite controllers and to study their functional relationships. Our results provide a reference for subsequent functional verification at the molecular or cellular level.
Keywords: CD4 T-cell; Elite controller; HIV; Network; Transcriptome.
©2020 Chen et al.