Endogenous retroviruses transcriptional modulation after severe infection, trauma and burn

Tabone, Olivier; Mommert, Marine; Jourdan, Camille; Cerrato, Elisabeth; Legrand, Matthieu; Lepape, Alain; Allaouchiche, Bernard; Rimmelé, Thomas; Pachot, Alexandre; Monneret, Guillaume; Venet, Fabienne; Mallet, François; Textoris, Julien

doi:10.1101/433029

Cited by 5 publications

(7 citation statements)

References 43 publications

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“…The LTRC/D of MER41 is a member of the PRIMA41 elements that have been identified as enhancers for adjacent IFN-induced genes and have been shown to be involved in the regulation of essential immune functions [21]. Overall, differential expression analysis between HV and septic shock patients confirmed that septic shock is associated with an early modulation of thousands of HERV/ MaLR loci, which is in agreement with (1) in vitro LTR retrotransposons being tightly regulated to endotoxininduced stress [13] and (2) in vivo preliminary observations in critically ill patients [12].…”

Section: Discussionsupporting

confidence: 67%

“…Long terminal repeat (LTR) retrotransposons, which represent 8.3% of the human genome [11] were recently hypothesized to be relevant in the pathophysiology of sepsis [12,13]. These retrovirus-like sequences consist of approximately 200,000 human endogenous retroviruses (HERVs) and 240,000 mammalian apparent long terminal repeat retrotransposons (MaLR).…”

Section: Introductionmentioning

confidence: 99%

“…We have recently shown that several HERVs are expressed and modulated after septic shock and other inflammatory injuries [12]. Using the HERV-V3 microarray, which allows the measurement of HERV/MaLR at the individual locus level [22], we have also shown that HERV/MaLR are tightly modulated in peripheral blood mononuclear cells (PBMCs).…”

Section: Introductionmentioning

confidence: 99%

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Dynamic LTR retrotransposon transcriptome landscape in septic shock patients

et al. 2020

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Background: Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. Numerous studies have explored the complex and dynamic transcriptome modulations observed in sepsis patients, but a large fraction of the transcriptome remains unexplored. This fraction could provide information to better understand sepsis pathophysiology. Multiple levels of interaction between human endogenous retroviruses (HERV) and the immune response have led us to hypothesize that sepsis is associated with HERV transcription and that HERVs may contribute to a signature among septic patients allowing stratification and personalized management. Methods: We used a high-density microarray and RT-qPCR to evaluate the HERV and Mammalian Apparent Long Terminal Repeat retrotransposons (MaLR) transcriptome in a pilot study that included 20 selected septic shock patients, stratified on mHLA-DR expression, with samples collected on day 1 and day 3 after inclusion. We validated the results in an unselected, independent cohort that included 100 septic shock patients on day 3 after inclusion. We compared septic shock patients, according to their immune status, to describe the transcriptional HERV/MaLR and conventional gene expression. For differential expression analyses, moderated t tests were performed and Wilcoxon signed-rank tests were used to analyze RT-qPCR results. Results: We showed that 6.9% of the HERV/MaLR repertoire was transcribed in the whole blood, and septic shock was associated with an early modulation of a few thousand of these loci, in comparison to healthy volunteers. We provided evidence that a subset of HERV/MaLR and conventional genes were differentially expressed in septic shock patients, according to their immune status, using monocyte HLA-DR (mHLA-DR) expression as a proxy. A group of 193 differentially expressed HERV/MaLR probesets, tested in an independent septic shock cohort, identified two groups of patients with different immune status and severity features. Conclusion: We demonstrated that a large, unexplored part of our genome, which codes for HERV/MaLR, may be linked to the host immune response. The identified set of HERV/MaLR probesets should be evaluated on a large scale to assess the relevance of these loci in the stratification of septic shock patients. This may help to address the heterogeneity of these patients.

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Section: Discussionsupporting

confidence: 67%

Section: Introductionmentioning

confidence: 99%

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Dynamic LTR retrotransposon transcriptome landscape in septic shock patients

et al. 2020

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“…The three gene expression datasets analyzed in this study were downloaded from the Gene Expression Omnibus (GEO) database ( https://www.ncbi.nlm.nih.gov/geo/ ) and used to identify DEGs. GSE95233 [ 7 ], GSE57065 [ 8 ], and GSE28750 [ 9 ] were taken as representative datasets of patients with sepsis. For each dataset, data from day 1 of sample collection were used to analyze the gene expression based on the GPL570 platform (HG-U133_Plus_2).…”

Section: Methodsmentioning

confidence: 99%

Identification of Potential Biomarkers and Immune Features of Sepsis Using Bioinformatics Analysis

Gong

Wang

et al. 2020

Mediators of Inflammation

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Sepsis remains a major global concern and is associated with high mortality and morbidity despite improvements in its management. Markers currently in use have shortcomings such as a lack of specificity and failures in the early detection of sepsis. In this study, we aimed to identify key genes involved in the molecular mechanisms of sepsis and search for potential new biomarkers and treatment targets for sepsis using bioinformatics analyses. Three datasets (GSE95233, GSE57065, and GSE28750) associated with sepsis were downloaded from the public functional genomics data repository Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified using R packages (Affy and limma). Functional enrichment of the DEGs was analyzed with the DAVID database. Protein-protein interaction networks were derived using the STRING database and visualized using Cytoscape software. Potential biomarker genes were analyzed using receiver operating characteristic (ROC) curves in the R package (pROC). The three datasets included 156 whole blood RNA samples from 89 sepsis patients and 67 healthy controls. Between the two groups, 568 DEGs were identified, among which 315 were upregulated and 253 were downregulated in the septic group. These genes were enriched for pathways mainly involved in the innate immune response, T-cell biology, antigen presentation, and natural killer cell function. ROC analyses identified nine genes—LRG1, ELANE, TP53, LCK, TBX21, ZAP70, CD247, ITK, and FYN—as potential new biomarkers for sepsis. Real-time PCR confirmed that the expression of seven of these genes was in accordance with the microarray results. This study revealed imbalanced immune responses at the transcriptomic level during early sepsis and identified nine genes as potential biomarkers for sepsis.

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“…GSE95233 [47] Whole blood 22 51 Affymetrix Human Genome U133 Plus 2.0 Array GSE57065 [48] Whole blood 25 28 Affymetrix Human Genome U133 Plus 2.0 Array GSE28750 [49] Whole blood 20 10 Affymetrix Human Genome U133 Plus 2.0 Array Series GSE65682 was analyzed using the Affymetrix HG-U129 platform, including 42 healthy samples and 760 patients admitted to the ICU with sepsis. 522 patients with sepsis among them were picked up for futher analysis.…”

Section: Materials and Methods 1 Gene Expression Datasets And Data Pmentioning

confidence: 99%

Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis

Cheng

Nan

Kang

et al. 2020

Preprint

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Background: Sepsis is a fatal disease referring to the presence of a known or strongly suspected infection coupled with systemic and uncontrolled immune activation causing multiple organ failure. However, neither pathogenic long non-coding RNAs (lncRNAs) nor biological network analysis in sepsis draws enough attention to the society of sepsis studies. Methods: We performed an in-silico investigation of the gene coexpression pattern for the patients response to all-cause sepsis in consecutive intensive care unit (ICU) admissions. Sepsis coexpression gene modules were identified using WGCNA and enrichment analysis. lncRNAs were determined as sepsis biomarkers based on the interactions among lncRNAs and the identified modules. Results: Twenty-three sepsis modules, including both differentially expressed modules and prognostic modules, were identified from the whole blood RNA expression profilings of sepsis patients. Five lncRNAs, FENDRR, MALAT1, TUG1, CRNDE, and ANCR, were detected as sepsis regulators based on the interactions among lncRNAs and the identified coexpression modules. Furthermore, we found that CRNDE and MALAT1 may act as miRNA sponges of sepsis related miRNAs to regulate the expression of sepsis modules. Ultimately, FENDRR, MALAT1, TUG1, and CRNDE were reannotated using three independent lncRNA expression datasets and validated as differentially expressed lncRNAs. Conclusion: The procedure facilitates the identification of prognostic biomarkers and novel therapeutic strategies of sepsis. Our findings highlight the importance of transcriptome modularity and regulatory lncRNAs in the progress of sepsis.

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Endogenous retroviruses transcriptional modulation after severe infection, trauma and burn

Cited by 5 publications

References 43 publications

Dynamic LTR retrotransposon transcriptome landscape in septic shock patients

Dynamic LTR retrotransposon transcriptome landscape in septic shock patients

Identification of Potential Biomarkers and Immune Features of Sepsis Using Bioinformatics Analysis

Whole blood transcriptomic investigation identifies long non-coding RNAs as regulators in sepsis

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