Dataset Information

RNA sequencing of CD4 T-cells reveals the relationships between lncRNA-mRNA co-expression in elite controller vs. HIV-positive infected patients.

ABSTRACT: 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.

SUBMITTER: Chen C

PROVIDER: S-EPMC7182024 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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RNA sequencing of CD4 T-cells reveals the relationships between lncRNA-mRNA co-expression in elite controller vs. HIV-positive infected patients.

Chen Chaoyu C Lu Xiangyun X Wu Nanping N

PeerJ 20200421

<h4>Background</h4>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.<h4>Methods</h4>We collected CD4 T-cell samples from two elite controllers (ECs), two HIV-positive infected patients ...[more]

PMID: 32341894

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Project description:HIV-1-infected elite controllers or suppressors (ES) maintain undetectable viral loads (< 50 copies/mL) without antiretroviral therapy. The mechanisms of suppression are incompletely understood. Modulation of HIV-1 replication by miRNAs has been reported, but the role of small RNAs in ES is unknown. Using samples from a well-characterized ES cohort, untreated viremic patients, and uninfected controls, we explored the PBMC miRNA profile and probed the relationships of miRNA expression, CD4+ T-cell counts, and viral load.miRNA profiles, obtained using multiple acquisition, data processing, and analysis methods, distinguished ES and uninfected controls from viremic HIV-1-infected patients. For several miRNAs, however, ES and viremic patients shared similar expression patterns. Differentially expressed miRNAs included those with reported roles in HIV-1 latency (miR-29 family members, miRs -125b and -150). Others, such as miR-31 and miR-31*, had no previously reported connection with HIV-1 infection but were found here to differ significantly with uncontrolled HIV-1 replication. Correlations of miRNA expression with CD4+ T-cell count and viral load were found, and we observed that ES with low CD4+ T-cell counts had miRNA profiles more closely related to viremic patients than controls. However, expression patterns indicate that miRNA variability cannot be explained solely by CD4+ T-cell variation.The intimate involvement of miRNAs in disease processes is underscored by connections of miRNA expression with the HIV disease clinical parameters of CD4 count and plasma viral load. However, miRNA profile changes are not explained completely by these variables. Significant declines of miRs-125b and -150, among others, in both ES and viremic patients indicate the persistence of host miRNA responses or ongoing effects of infection despite viral suppression by ES. We found no negative correlations with viral load in viremic patients, not even those that have been reported to silence HIV-1 in vitro, suggesting that the effects of these miRNAs are exerted in a focused, cell-type-specific manner. Finally, the observation that some ES with low CD4 counts were consistently related to viremic patients suggests that miRNAs may serve as biomarkers for risk of disease progression even in the presence of viral suppression.

Project description:Pediatric sepsis is a great threat to death worldwide. However, the pathogenesis has not been clearly understood until now in sepsis. This study identified differentially expressed mRNAs and lncRNAs based on Gene Expression Omnibus (GEO) database. And the weighted gene co-expression network analysis (WGCNA) was performed to explore co-expression modules associated with pediatric sepsis. Then, Gene Ontology (GO), KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway, mRNA‑lncRNA and mRNA‑lncRNA-pathway co-expression network analysis was conducted in selected significant module. A total of 1941 mRNAs and 225 lncRNAs were used to conduct WGCNA. And turquoise module was selected as a significant module that was associated with particular traits. The mRNAs functions associated with many vital processes were also shown by GO and KEGG pathway analysis in the turquoise module. Finally, 15 mRNAs (MAPK14, ITGAM, HK3, ALOX5, CR1, HCK, NCF4, PYGL, FLOT1, CARD6, NLRC4, SH3GLB1, PGS1, RAB31, LTB4R) and 4 lncRNAs (GSEC, NONHSAT160878.1, XR_926068.1 and RARA-AS1) were selected as hub genes in mRNA‑lncRNA-Pathway co-expression network. We identified 15 mRNAs and 4 lncRNAs as diagnostic markers, which have potential functions in pediatric sepsis. Our study provides more directions to study the molecular mechanism of pediatric sepsis.Abbreviations: mRNA: messenger RNA; lncRNA: long noncoding RNAs; GEO: Gene Expression Omnibus; WGCNA: weighted gene co-expression network analysis; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; SIRS: systemic inflammatory response syndrome; TOM: topological overlap measure; BP: biological process; MF: molecular function; CC: cellular component; ROC: receiver operating characteristic curve; AUC: area under curve; MAPK14: Mitogen-activated protein kinase 14; ALI: acute lung injury; ITGAM: Integrin subunit alpha M; HK3: Hexokinase 3; LPS: lipopolysaccharide; 5-LO: 5-lipoxygenase; LTs: leukotrienes; LTB4R: leukotriene B4 receptor.

Dataset Information

RNA sequencing of CD4 T-cells reveals the relationships between lncRNA-mRNA co-expression in elite controller vs. HIV-positive infected patients.

Publications

RNA sequencing of CD4 T-cells reveals the relationships between lncRNA-mRNA co-expression in elite controller vs. HIV-positive infected patients.

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