Identification of miRNA-mRNA crosstalk in CD4+ T cells during HIV-1 infection by integrating transcriptome analyses

Abstract

BackgroundHIV-1-infected long-term nonprogressors (LTNPs) are characterized by infection with HIV-1 more than 7–10 years, but keeping high CD4+ T cell counts and low viral load in the absence of antiretroviral treatment, while loss of CD4+ T cells and high viral load were observed in the most of HIV-1-infected individuals with chronic progressors (CPs) However, the mechanisms of different clinical outcomes in HIV-1 infection needs to be further resolved.MethodsTo identify microRNAs (miRNAs) and their target genes related to distinct clinical outcomes in HIV-1 infection, we performed the integrative transcriptome analyses in two series GSE24022 and GSE6740 by GEO2R, R, TargetScan, miRDB, and Cytoscape softwares. The functional pathways of these differentially expressed miRNAs (DEMs) targeting genes were further analyzed with DAVID.ResultsWe identified that 7 and 19 DEMs in CD4+ T cells of LTNPs and CPs, respectively, compared with uninfected controls (UCs), but only miR-630 was higher in CPs than that in LTNPs. Further, 478 and 799 differentially expressed genes (DEGs) were identified in the group of LTNPs and CPs, respectively, compared with UCs. Compared to CPs, four hundred and twenty-four DEGs were identified in LTNPs. Functional pathway analyses revealed that a close connection with miRNA-mRNA in HIV-1 infection that DEGs were involved in response to virus and immune system process, and RIG-I-like receptor signaling pathway, whose DEMs or DEGs will be novel biomarkers for prediction of clinical outcomes and therapeutic targets for HIV-1.ConclusionsIntegrative transcriptome analyses showed that distinct transcriptional profiles in CD4+ T cells are associated with different clinical outcomes during HIV-1 infection, and we identified a circulating miR-630 with potential to predict disease progression, which is necessary to further confirm our findings in the future.Electronic supplementary materialThe online version of this article (doi:10.1186/s12967-017-1130-y) contains supplementary material, which is available to authorized users.

Expression profiling of human milk derived exosomal microRNAs and their targets in HIV-1 infected mothers

“…Furthermore, the majority of women who participated in the study were carrying HIV-1 for greater than 5 years (Table 1), thus it is suggested these two miRNAs could be used to monitor AIDS progression in HIV-1 infected women. Indeed, our finding is in agreement with a previous study in which miR-630 was reported as a biomarker in chronic progressors of HIV-1 63 . Interestingly, our HM exosomal miRNA data from the South Africa cohort where HIV-1 infected women were carrying HIV-1 load < 1 year (data not shown) showed downregulation of these miRNAs identified in the current study and correlated with a recent report where it was shown that acute HIV-1 leads www.nature.com/scientificreports/ to downregulation of miRNAs 57 .…”

“…miRNAs are thought to be involved in mediating immune suppression, establishment of viral latency 59,64 or suppressing HIV-1 replication via decreasing HIV-1 dependency factors 65 . Some of the miRNAs we have identified have previously been implicated in HIV-1 infection including miR-630, miR-4516, miR-16-5p, miR-378, miR-93, miR-23, miR-30a 57,63,[66][67][68][69] thus strongly suggesting the reliability of the NanoString data obtained in the current study. Further, it has been described that NanoString can perform miRNA profiling with digital precision and the results do not require further validation by another method 70 .…”

Circular RNA Expression Profiling Identifies Prostate Cancer- Specific circRNAs in Prostate Cancer

“…To understand the role of differentially expressed circRNAs, Gene Ontology (GO) analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) were performed to construct meaningful annotation of genes as a whole network [23]. At the same time, we also constructed a circRNA-miRNA-mRNA network in transcripts.…”

Molecular analyses of prostate tumors for diagnosis of malignancy on fine-needle aspiration biopsies

“…These data showed a significant fold-change value in the gene expression of at least one gene. Figure 1B lists the common genes of the two databases from the GEO [ 21 ], combined with our microarray results. These 174 common genes are shown by the Venn diagrams, using the false discovery rate (0.05), p -values less than 0.05, and two-fold changes, which may be potentially involved in PCa progression from all three microarrays.…”

“…The GO category was classified by Fisher's exact test, and the p-value was corrected by the false discovery rate (FDR) calculation include molecular function (MF), and biological process (BP). Criteria used for the GO and IPA analyses have been described previously [ 21 , 36 , 37 ].…”