Endogenous Retroviruses Transcriptional Modulation After Severe Infection, Trauma and Burn

Identification of 18β-glycyrrhetinic acid as an AGT inhibitor against LPS-induced myocardial dysfunction via high throughput screening

Sepsis induced myocardial dysfunction (SIMD) is a serious complication of sepsis. There is increasing evidence that the renin-angiotensin system (RAS) is activated in SIMD. Angiotensinogen (AGT) is a precursor of the RAS, and the inhibition of AGT may have significant cardiovascular benefits. But until now, there have been no reports of small molecule drugs targeting AGT. In this study, we designed a promoter-luciferase based system to screen for novel AGT inhibitors to alleviate SIMD. As a result of high-throughput screening, a total of 5 compounds from 351 medicinal herb-derived natural compounds were found inhibiting AGT. 18β-glycyrrhetinic acid (18βGA) was further identified as a potent suppressor of AGT. In vitro experiments, 18βGA could inhibit the secretion of AGT by HepG2 cells and alleviate the elevated level of mitochondrial oxidative stress in cardiomyocytes co-cultured with HepG2 supernatants. In vivo, 18βGA prolonged the survival rate of SIMD mice, enhanced cardiac function, and inhibited the damage of mitochondrial function and inflammation. In addition, the results showed that 18βGA may reduce AGT transcription by downregulating hepatocyte nuclear factor 4 (HNF4) and that further alleviated SIMD. In conclusion, we provided a more efficient screening strategy for AGT inhibitors and expanded the novel role of 18βGA as a promising lead compound in rescuing cardiovascular disease associated with RAS overactivation.

Targeting SLC22A5 fosters mitophagy inhibition-mediated macrophage immunity against septic acute kidney injury upon CD47-SIRPα axis blockade

Efferocytosis of apoptotic neutrophils (PMNs) by macrophages is helpful for inflammation resolution and injury repair, but the role of efferocytosis in intrinsic nature of macrophages during septic acute kidney injury (AKI) remains unknown. Here we report that CD47 and signal regulatory protein alpha (SIRPα)-the anti-efferocytotic 'don't eat me' signals-are highly expressed in peripheral blood mononuclear cells (PBMCs) from patients with septic AKI and kidney samples from mice with polymicrobial sepsis and endotoxin shock. Conditional knockout (CKO) of SIRPA in macrophages ameliorates AKI and systemic inflammation response in septic mice, accompanied by an escalation in mitophagy inhibition of macrophages. Ablation of SIRPA transcriptionally downregulates solute carrier family 22 member 5 (SLC22A5) in the lipopolysaccharide (LPS)-stimulated macrophages that efferocytose apoptotic neutrophils (PMNs). Targeting SLC22A5 renders mitophagy inhibition of macrophages in response to LPS stimuli, improves survival and deters development of septic AKI. Our study supports further clinical investigation of CD47-SIRPα signalling in sepsis and proposes that SLC22A5 might be a promising immunotherapeutic target for septic AKI.

Unlocking the potential of senescence-related gene signature as a diagnostic and prognostic biomarker in sepsis: insights from meta-analyses, single-cell RNA sequencing, and in vitro experiments

Cellular senescence is closely associated with the pathogenesis of sepsis. However, the diagnostic and prognostic value of senescence-related genes remain unclear. In this study, 866 senescence-related genes were collected from CellAge. The training cohort, GSE65682, which included 42 control and 760 sepsis samples, was obtained from the Gene Expression Omnibus (GEO). Feature selection was performed using gene expression difference detection, LASSO analysis, random forest, and Cox regression. TGFBI and MAD1L1 were ultimately selected for inclusion in the multivariate Cox regression model. Clustering based on the expressions of TGFBI and MAD1L1 was significantly associated with sepsis characteristics and prognoses (all P < 0.05). The risk signature served as a reliable prognostic predictor across the GSE65682, GSE95233, and GSE4607 cohorts (pooled hazard ratio = 4.27; 95% confidence interval [CI] = 1.63-11.17). Furthermore, it also served as a robust classifier to distinguish sepsis samples from control cases across 14 cohorts (pooled odds ratio = 5.88; 95% CI = 3.54-9.77). Single-cell RNA sequencing analyses from five healthy controls and four sepsis subjects indicated that the risk signature could reflect the senescence statuses of monocytes and B cells; this finding was then experimentally validated in THP-1 and IM-9 cells in vitro (both P < 0.05). In all, a senescence-related gene signature was developed as a prognostic and diagnostic biomarker for sepsis, providing cut-in points to uncover underlying mechanisms and a promising clinical tool to support precision medicine.

NMI Functions as Immuno-regulatory Molecule in Sepsis by Regulating Multiple Signaling Pathways

Sepsis-induced tissue and organ damage is caused by an overactive inflammatory response, immune dysfunction, and coagulation dysfunction. Danger-associated molecular pattern (DAMP) molecules play a critical role in the excessive inflammation observed in sepsis. In our previous research, we identified NMI as a new type of DAMP molecule that promotes inflammation in sepsis by binding to toll-like receptor 4 (TLR4) on macrophage surfaces, activating the NF-κB pathway, and releasing pro-inflammatory cytokines. However, it is still unknown whether NMI plays a significant role in other pathways. Our analysis of bulk and single-cell transcriptome data from the GEO database revealed a significant increase in NMI expression in neutrophils and monocytes in sepsis patients. It is likely that NMI functions through multiple receptors in sepsis, including IFNAR1, IFNAR2, TNFR1, TLR3, TLR1, IL9R, IL10RB, and TLR4. Furthermore, the correlation between NMI expression and the activation of NF-κB, MAPK, and JAK pathways, as well as the up-regulation of their downstream pro-inflammatory factors, demonstrates that NMI may exacerbate the inflammatory response through these signaling pathways. Finally, we demonstrated that STAT1 phosphorylation was enhanced in RAW cells upon stimulation with NMI, supporting the activation of JAK signaling pathway by NMI. Collectively, these findings shed new light on the functional mechanism of NMI in sepsis.

Screening of four lysosome-related genes in sepsis based on RNA sequencing technology

PURPOSE

Screening of lysosome-related genes in sepsis patients to provide direction for lysosome-targeted therapy.

METHODS

Peripheral blood samples were obtained from 22 patients diagnosed with sepsis and 10 normal controls for the purpose of RNA sequencing and subsequent analysis of differential gene expression. Concurrently, lysosome-related genes were acquired from the Gene Ontology database. The intersecting genes between the differential genes and lysosome-related genes were then subjected to PPI, GO and KEGG analyses. Core genes were identified through survival analysis, and their expression trends in different groups were determined using meta-analysis. Single-cell RNA sequencing was used to clarify the cellular localization of core genes.

RESULTS

The intersection of 1328 sepsis-differential genes with 878 lysosome-related genes yielded 76 genes. PPI analysis showed that intersecting genes were mainly involved in Cellular process, Response to stimulus, Immune system process, Signal transduction, Lysosome. GO and KEGG analysis showed that intersecting genes were mainly involved in leukocyte mediated immunity, cell activation involved in immune response, lytic vacuole, lysosome. Survival analysis screened four genes positively correlated with sepsis prognosis, namely GNLY, GZMB, PRF1 and RASGRP1. The meta-analysis revealed that the expression levels of these four genes were significantly higher in the normal control group compared to the sepsis group, which aligns with the findings from RNA sequencing data. Furthermore, single-cell RNA sequencing demonstrated that T cells and NK cells exhibited high expression levels of GNLY, GZMB, PRF1, and RASGRP1.

CONCLUSION

GNLY, GZMB, PRF1, and RASGRP1, which are lysosome-related genes, are closely linked to the prognosis of sepsis and could potentially serve as novel research targets for sepsis, offering valuable insights for the development of lysosome-targeted therapy. The clinical trial registration number is ChiCTR1900021261, and the registration date is February 4, 2019.

Bioinformatics-Led Identification of Potential Biomarkers and Inflammatory Infiltrates in Burn Injury

Burn injury is a life-threatening disease with a poor prognosis. The immune change and underlying mechanisms remain largely unknown. Thus, this study aims to find potential biomarkers and analyze the immune infiltrates after burn injury. Gene expression data of burn patients were obtained from the Gene Expression Omnibus database. Key immune-related genes (IRGs) were screened by differential and least absolute shrinkage and selection operator (LASSO) regression analysis. Based on key IRGs, patients were divided into two clusters by consensus cluster analysis. Immune infiltration was analyzed by the single sample gene set enrichment analysis (GSEA) method and the immune score was calculated by the principal component analysis method. A nomogram model was constructed based on the calculated immune score and clinical features. Finally, the expression of screened key genes was validated by an external cohort and quantitative polymerase chain reaction experiment. Fifty-nine IRGs were differently expressed in burn patients. After LASSO regression analysis, 12 key genes remained, namely AZU1, OLR1, RNASE2, FGF13, NR1D2, NR2E1, TLR5, CAMP, DEFA4, PGLYRP1, CTSG, and CCR3. Then, patients were divided into two clusters. Immune infiltration analysis revealed that more immune cells were infiltrated and more pathways were activated in cluster A, in which patients showed high immune scores. Finally, a nomogram model was constructed and showed high accuracy and reliability. The expression pattern of 12 key genes in an external cohort and clinical samples was in accordance with the theoretical analysis results. In conclusion, this research elucidated the key role of immune response in burns and could be used as a guide for burn treatment.

Screening and identification of the core immune-related genes and immune cell infiltration in severe burns and sepsis

Severe burns often have a high mortality rate due to sepsis, but the genetic and immune crosstalk between them remains unclear. In the present study, the GSE77791 and GSE95233 datasets were analysed to identify immune-related differentially expressed genes (DEGs) involved in disease progression in both burns and sepsis. Subsequently, weighted gene coexpression network analysis (WGCNA), gene enrichment analysis, protein-protein interaction (PPI) network construction, immune cell infiltration analysis, core gene identification, coexpression network analysis and clinical correlation analysis were performed. A total of 282 common DEGs associated with burns and sepsis were identified. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified the following enriched pathways in burns and sepsis: metabolic pathways; complement and coagulation cascades; legionellosis; starch and sucrose metabolism; and ferroptosis. Finally, six core DEGs were identified, namely, IL10, RETN, THBS1, FGF13, LCN2 and MMP9. Correlation analysis showed that some core DEGs were significantly associated with simultaneous dysregulation of immune cells. Of these, RETN upregulation was associated with a worse prognosis. The immune-related genes and dysregulated immune cells in severe burns and sepsis provide potential research directions for diagnosis and treatment.

Genetic and immune crosstalk between severe burns and blunt trauma: A study of transcriptomic data

Background: Severe burns and blunt trauma can lead to multiple organ dysfunction syndrome, the leading cause of death in intensive care units. In addition to infection, the degree of immune inflammatory response also affects prognosis. However, the characteristics and clinical relevance of the common mechanisms of these major diseases are still underexplored.

Methods: In the present study, we performed microarray data analysis to identify immune-related differentially expressed genes (DEGs) involved in both disease progression in burns and blunt trauma. Six analyses were subsequently performed, including gene enrichment analysis, protein‐protein interaction (PPI) network construction, immune cell infiltration analysis, core gene identification, co-expression network analysis, and clinical correlation analysis.

Results: A total of 117 common immune-related DEGs was selected for subsequent analyses. Functional analysis emphasizes the important role of Th17 cell differentiation, Th1 and Th2 cell differentiation, Cytokine-cytokine receptor interaction and T cell receptor signaling pathway in these two diseases. Finally, eight core DEGs were identified using cytoHubba, including CD8A, IL10, CCL5, CD28, LCK, CCL4, IL2RB, and STAT1. The correlation analysis showed that the identified core DEGs were more or less significantly associated with simultaneous dysregulation of immune cells in blunt trauma and sepsis patients. Of these, the downregulation of CD8A and CD28 had a worse prognosis.

Conclusion: Our analysis lays the groundwork for future studies to elucidate molecular mechanisms shared in burns and blunt trauma. The functional roles of identified core immune-related DEGs and dysregulated immune cell subsets warrant further in-depth study.

Mortality Prediction in Sepsis With an Immune-Related Transcriptomics Signature: A Multi-Cohort Analysis

Background

Novel biomarkers are needed to progress toward individualized patient care in sepsis. The immune profiling panel (IPP) prototype has been designed as a fully-automated multiplex tool measuring expression levels of 26 genes in sepsis patients to explore immune functions, determine sepsis endotypes and guide personalized clinical management. The performance of the IPP gene set to predict 30-day mortality has not been extensively characterized in heterogeneous cohorts of sepsis patients.

Methods

Publicly available microarray data of sepsis patients with widely variable demographics, clinical characteristics and ethnical background were co-normalized, and the performance of the IPP gene set to predict 30-day mortality was assessed using a combination of machine learning algorithms.

Results

We collected data from 1,801 arrays sampled on sepsis patients and 598 sampled on controls in 17 studies. When gene expression was assayed at day 1 following admission (1,437 arrays sampled on sepsis patients, of whom 1,161 were alive and 276 (19.2%) were dead at day 30), the IPP gene set showed good performance to predict 30-day mortality, with an area under the receiving operating characteristics curve (AUROC) of 0.710 (CI 0.652-0.768). Importantly, there was no statistically significant improvement in predictive performance when training the same models with all genes common to the 17 microarray studies (n = 7,122 genes), with an AUROC = 0.755 (CI 0.697-0.813, p = 0.286). In patients with gene expression data sampled at day 3 following admission or later, the IPP gene set had higher performance, with an AUROC = 0.804 (CI 0.643-0.964), while the total gene pool had an AUROC = 0.787 (CI 0.610-0.965, p = 0.811).

Conclusion

Using pooled publicly-available gene expression data from multiple cohorts, we showed that the IPP gene set, an immune-related transcriptomics signature conveys relevant information to predict 30-day mortality when sampled at day 1 following admission. Our data also suggests that higher predictive performance could be obtained when assaying gene expression at later time points during the course of sepsis. Prospective studies are needed to confirm these findings using the IPP gene set on its dedicated measurement platform.

Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation

Ferroptosis is a new type of programmed cell death that is different from apoptosis, cell necrosis, and autophagy, which might be involved in development of sepsis. However, the potential role of ferroptosis-related genes (FRGs) in sepsis remained unclear. We identified 41 ferroptosis-related differential expression genes by weighted correlation network and differential expression analysis. The hub module of 41 ferroptosis-related differential expression genes in the protein-protein interaction network was identified. Next, we estimated diagnostic values of genes in hub modules. TLR4, WIPI1, and GABARAPL2 with high diagnostic value were selected for construction of risk prognostic model. The high risk-scored patients had significantly higher mortality than the patients with low risk scores in discovery dataset. Furthermore, the risk scores of nonsurvivor were higher than those of survivor in validation dataset. It suggested that risk score was significantly correlated to prognosis in sepsis. Then, we constructed a nomogram for improving the clinical applicability of risk signature. Moreover, the risk score was significantly associated with immune infiltration in sepsis. Our comprehensive analysis of FRGs in sepsis demonstrated the potential roles in diagnosis, prognosis, and immune infiltration. This work may benefit in understanding FRGs in sepsis and pave a new path for diagnosis and assessment of prognosis.

Methyltransferase like 7B is upregulated in sepsis and modulates lipopolysaccharide-induced inflammatory response and macrophage polarization

Macrophages play a critical role in the regulation of the inflammatory responses in sepsis. Methyltransferase like 7B (METTL7B) has been implicated in several pathophysiological conditions. Nevertheless, the potential engagement of METTL7B in sepsis remains to be elucidated. In this study, we retrieved transcriptomic profile data of septic patients and healthy donors and compared the expression level of METTL7B between septic patients and healthy controls. We also collected septic patient samples to analyze METTL7B expression via RT-qPCR. Murine bone marrow-derived macrophages (BMDMs) were isolated and treated with incremental doses of LPS as an in vitro cell model. METTL7B was overexpressed or knocked down in BMDMs, and lipopolysaccharide (LPS)-mediated inflammatory cytokines production and macrophage polarization were evaluated. We found that METTL7B was upregulated in the blood and peripheral blood mononuclear cells (PBMC) of septic patients, which also showed a significant diagnostic potential for sepsis. In BMDMs, METTL7B was induced in a time and dose-dependent manner by LPS. Modulating the expression level of METTL7B could regulate LPS-mediated inflammatory cytokines production and macrophage polarization. The functional role of METTL7B was also validated in a septic mouse model. Our findings indicate that METTL7B is implicated in the immunopathogenesis of sepsis through modulating macrophage-mediated inflammatory responses. METTL7B may serve as a potential diagnostic and therapeutic target for sepsis.

UBE2D1 and COX7C as Potential Biomarkers of Diabetes-Related Sepsis

Patients with diabetes are physiologically frail and more likely to suffer from infections and even life-threatening sepsis. This study aimed to identify and verify potential biomarkers of diabetes-related sepsis (DRS). Datasets GSE7014, GSE57065, and GSE95233 from the Gene Expression Omnibus were used to explore diabetes- and sepsis-related differentially expressed genes (DEGs). Gene set enrichment analysis (GSEA) and functional analyses were performed to explore potential functions and pathways associated with sepsis and diabetes. Weighted gene co-expression network analysis (WGCNA) was performed to identify diabetes- and sepsis-related modules. Functional enrichment analysis was performed to determine the characteristics and pathways of key modules. Intersecting DEGs that were also present in key modules were considered as common DEGs. Protein-protein interaction (PPI) network and key genes were analyzed to screen hub genes involved in DRS development. A mouse C57 BL/6J-DRS model and a neural network prediction model were constructed to verify the relationship between hub genes and DRS. In total, 7457 diabetes-related DEGs and 2606 sepsis-related DEGs were identified. GSEA indicated that gene datasets associated with diabetes and sepsis were mainly enriched in metabolic processes linked to inflammatory responses and reactive oxygen species, respectively. WGCNA indicated that grey60 and brown modules were diabetes- and sepsis-related key modules, respectively. Functional analysis showed that grey60 module genes were mainly enriched in cell morphogenesis, heart development, and the PI3K-Akt signaling pathway, whereas genes from the brown module were mainly enriched in organelle inner membrane, mitochondrion organization, and oxidative phosphorylation. UBE2D1, IDH1, DLD, ATP5C1, COX6C, and COX7C were identified as hub genes in the PPI network. Animal DRS and neural network prediction models indicated that the expression levels of UBE2D1 and COX7C in DRS models and samples were higher than control mice. UBE2D1 and COX7C were identified as potential biomarkers of DRS. These findings may help develop treatment strategies for DRS.

Admixture Mapping of Sepsis in European Individuals With African Ancestries

Sepsis is a severe systemic inflammatory response to infections that is accompanied by organ dysfunction. Although the ancestral genetic background is a relevant factor for sepsis susceptibility, there is a lack of studies using the genetic singularities of a recently admixed population to identify loci involved in sepsis susceptibility. Here we aimed to discover new sepsis loci by completing the first admixture mapping study of sepsis in Canary Islanders, leveraging their distinctive genetic makeup as a mixture of Europeans and African ancestries. We used a case-control approach and inferred local ancestry blocks from genome-wide data from 113,414 polymorphisms genotyped in 343 patients with sepsis and 410 unrelated controls, all ascertained for grandparental origin in the Canary Islands (Spain). Deviations in local ancestries between cases and controls were tested using logistic regressions, followed by fine-mapping analyses based on imputed genotypes, in silico functional assessments, and gene expression analysis centered on the region of interest. The admixture mapping analysis detected that local European ancestry in a locus spanning 1.2 megabases of chromosome 8p23.1 was associated with sepsis (lowest p = 1.37 × 10⁻⁴; Odds Ratio [OR] = 0.51; 95%CI = 0.40–0.66). Fine-mapping studies prioritized the variant rs13249564 within intron 1 of MFHAS1 gene associated with sepsis (p = 9.94 × 10⁻⁴; OR = 0.65; 95%CI = 0.50–0.84). Functional and gene expression analyses focused on 8p23.1 allowed us to identify alternative genes with possible biological plausibility such as defensins, which are well-known effector molecules of innate immunity. By completing the first admixture mapping study of sepsis, our results revealed a new genetic locus (8p23.1) harboring a number of genes with plausible implications in sepsis susceptibility.

The Landscape of Featured Metabolism-Related Genes and Imbalanced Immune Cell Subsets in Sepsis

Sepsis is a heterogeneous disease state triggered by an uncontrolled inflammatory host response with high mortality and morbidity in severely ill patients. Unfortunately, the treatment effectiveness varies among sepsis patients and the underlying mechanisms have yet to be elucidated. The present aim is to explore featured metabolism-related genes that may become the biomarkers in patients with sepsis. In this study, differentially expressed genes (DEGs) between sepsis and non-sepsis in whole blood samples were identified using two previously published datasets (GSE95233 and GSE54514). A total of 66 common DEGs were determined, namely, 52 upregulated and 14 downregulated DEGs. The Gene Set Enrichment Analysis (GSEA) results indicated that these DEGs participated in several metabolic processes including carbohydrate derivative, lipid, organic acid synthesis oxidation reduction, and small-molecule biosynthesis in patients with sepsis. Subsequently, a total of 8 hub genes were screened in the module with the highest score from the Cytoscape plugin cytoHubba. Further study showed that these hub DEGs may be robust markers for sepsis with high area under receiver operating characteristic curve (AUROC). The diagnostic values of these hub genes were further validated in myocardial tissues of septic rats and normal controls by untargeted metabolomics analysis using liquid chromatography-mass spectrometry (LC-MS). Immune cell infiltration analysis revealed that different infiltration patterns were mainly characterized by B cells, T cells, NK cells, monocytes, macrophages, dendritics, eosinophils, and neutrophils between sepsis patients and normal controls. This study indicates that metabolic hub genes may be hopeful biomarkers for prognosis prediction and precise treatment in sepsis patients.

Improving bulk RNA-seq classification by transferring gene signature from single cells in acute myeloid leukemia

The advances in single-cell RNA sequencing (scRNA-seq) technologies enable the characterization of transcriptomic profiles at the cellular level and demonstrate great promise in bulk sample analysis thereby offering opportunities to transfer gene signature from scRNA-seq to bulk data. However, the gene expression signatures identified from single cells are typically inapplicable to bulk RNA-seq data due to the profiling differences of distinct sequencing technologies. Here, we propose single-cell pair-wise gene expression (scPAGE), a novel method to develop single-cell gene pair signatures (scGPSs) that were beneficial to bulk RNA-seq classification to transfer knowledge across platforms. PAGE was adopted to tackle the challenge of profiling differences. We applied the method to acute myeloid leukemia (AML) and identified the scGPS from mouse scRNA-seq that allowed discriminating between AML and control cells. The scGPS was validated in bulk RNA-seq datasets and demonstrated better performance (average area under the curve [AUC] = 0.96) than the conventional gene expression strategies (average AUC$\le$ 0.88) suggesting its potential in disclosing the molecular mechanism of AML. The scGPS also outperformed its bulk counterpart, which highlighted the benefit of gene signature transfer. Furthermore, we confirmed the utility of scPAGE in sepsis as an example of other disease scenarios. scPAGE leveraged the advantages of single-cell profiles to enhance the analysis of bulk samples revealing great potential of transferring knowledge from single-cell to bulk transcriptome studies.

Herpes DNAemia and TTV Viraemia in Intensive Care Unit Critically Ill Patients: A Single-Centre Prospective Longitudinal Study

Introduction

We analysed blood DNAemia of TTV and four herpesviruses (CMV, EBV, HHV6, and HSV-1) in the REAnimation Low Immune Status Marker (REALISM) cohort of critically ill patients who had presented with either sepsis, burns, severe trauma, or major surgery. The aim was to identify common features related to virus and injury-associated pathologies and specific features linking one or several viruses to a particular pathological context.

Methods

Overall and individual viral DNAemia were measured over a month using quantitative PCR assays from the 377 patients in the REALISM cohort. These patients were characterised by clinical outcomes [severity scores, mortality, Intensive Care Unit (ICU)-acquired infection (IAI)] and 48 parameters defining their host response after injury (cell populations, immune functional assays, and biomarkers). Association between viraemic event and clinical outcomes or immune markers was assessed using χ²-test or exact Fisher’s test for qualitative variables and Wilcoxon test for continuous variables.

Results

The cumulative incidence of viral DNAemia increased from below 4% at ICU admission to 35% for each herpesvirus during the first month. EBV, HSV1, HHV6, and CMV were detected in 18%, 12%, 10%, and 9% of patients, respectively. The incidence of high TTV viraemia (>10,000 copies/ml) increased from 11% to 15% during the same period. Herpesvirus viraemia was associated with severity at admission; CMV and HHV6 viraemia correlated with mortality during the first week and over the month. The presence of individual herpesvirus during the first month was significantly associated (p < 0.001) with the occurrence of IAI, whilst herpesvirus DNAemia coupled with high TTV viraemia during the very first week was associated with IAI. Herpesvirus viraemia was associated with a lasting exacerbated host immune response, with concurrent profound immune suppression and hyper inflammation, and delayed return to immune homeostasis. The percentage of patients presenting with herpesvirus DNAemia was significantly higher in sepsis than in all other groups. Primary infection in the hospital and high IL10 levels might favour EBV and CMV reactivation.

Conclusion

In this cohort of ICU patients, phenotypic differences were observed between TTV and herpesviruses DNAemia. The higher prevalence of herpesvirus DNAemia in sepsis hints at further studies that may enable a better in vivo understanding of host determinants of herpesvirus viral reactivation. Furthermore, our data suggest that EBV and TTV may be useful as additional markers to predict clinical deterioration in ICU patients.

FYN and CD247: key Genes for Septic Shock Based on Bioinformatics and Meta-Analysis

BACKGROUND

Septic shock is sepsis accompanied by hemodynamic instability and high clinical mortality.

MATERIAL AND METHODS

GSE95233, GSE57065, GSE131761 gene-expression profiles of healthy control subjects and septic shock patients were downloaded from the Gene-Expression Omnibus (GEO) database, and differences of expression profiles and their intersection were analysed using GEO2R. Function and pathway enrichment analysis was performed on common differentially expressed genes (DEG), and key genes for septic shock were screened using a protein-protein interaction network created with STRING. Also, data from the GEO database were used for survival analysis for key genes, and a meta-analysis was used to explore expression trends of core genes. Finally, high-throughput sequencing using the blood of a murine sepsis model was performed to analyse the expression of CD247 and FYN in mice.

RESULTS

A total of 539 DEGs were obtained (p < 0.05). Gene ontology analysis showed that key genes were enriched in functions, such as immune response and T cell activity, and DEGs were enriched in signal pathways, such as T cell receptors. FYN and CD247 are in the centre of the protein-protein interaction network, and survival analysis found that they are positively correlated with survival from sepsis. Further, meta-analysis results showed that FYN could be useful for the prognosis of patients, and CD247 might distinguish between sepsis and systemic inflammatory response syndrome patients. Finally, RNA sequencing using a mouse septic shock model showed low expression of CD247 and FYN in this model.

CONCLUSION

FYN and CD247 are expected to become new biomarkers of septic shock.

Identification of inflammatory subgroups of schizophrenia and bipolar disorder patients with HERV-W ENV antigenemia by unsupervised cluster analysis

Human endogenous retroviruses (HERVs) are remnants of infections that took place several million years ago and represent around 8% of the human genome. Despite evidence implicating increased expression of HERV type W envelope (HERV-W ENV) in schizophrenia and bipolar disorder, it remains unknown whether such expression is associated with distinct clinical or biological characteristics and symptoms. Accordingly, we performed unsupervised two-step clustering of a multivariate data set that included HERV-W ENV protein antigenemia, serum cytokine levels, childhood trauma scores, and clinical data of cohorts of patients with schizophrenia (n = 29), bipolar disorder (n = 43) and healthy controls (n = 32). We found that subsets of patients with schizophrenia (~41%) and bipolar disorder (~28%) show positive antigenemia for HERV-W ENV protein, whereas the large majority (96%) of controls was found to be negative for ENV protein. Unsupervised cluster analysis identified the presence of two main clusters of patients, which were best predicted by the presence or absence of HERV-W ENV protein. HERV-W expression was associated with increased serum levels of inflammatory cytokines and higher childhood maltreatment scores. Furthermore, patients with schizophrenia who were positive for HERV-W ENV protein showed more manic symptoms and higher daily chlorpromazine (CPZ) equivalents, whereas HERV-W ENV positive patients with bipolar disorder were found to have an earlier disease onset than those who were negative for HERV-W ENV protein. Taken together, our study suggest that HERV-W ENV protein antigenemia and cytokines can be used to stratify patients with major mood and psychotic disorders into subgroups with differing inflammatory and clinical profiles.

Transcriptome Analyses Implicate Endogenous Retroviruses Involved in the Host Antiviral Immune System through the Interferon Pathway

Human endogenous retroviruses (HERVs) are the remains of ancient retroviruses that invaded our ancestors' germline cell and were integrated into the genome. The expression of HERVs has always been a cause for concern because of its association with various cancers and diseases. However, few previous studies have focused on specific activation of HERVs by viral infections. Our previous study has shown that dengue virus type 2 (DENV-2) infection induces the transcription of a large number of abnormal HERVs loci; therefore, the purpose of this study was to explore the relationship between exogenous viral infection and HERV activation further. In this study, we retrieved and reanalyzed published data on 21 transcriptomes of human cells infected with various viruses. We found that infection with different viruses could induce transcriptional activation of HERV loci. Through the comparative analysis of all viral datasets, we identified 43 key HERV loci that were up-regulated by DENV-2, influenza A virus, influenza B virus, Zika virus, measles virus, and West Nile virus infections. Furthermore, the neighboring genes of these HERVs were simultaneously up-regulated, and almost all such neighboring genes were interferon-stimulated genes (ISGs), which are enriched in the host's antiviral immune response pathways. Our data supported the hypothesis that activation of HERVs, probably via an interferon-mediated mechanism, plays an important role in innate immunity against viral infections.

Human Endogenous Retroviruses (HERVs) and Mammalian Apparent LTRs Retrotransposons (MaLRs) Are Dynamically Modulated in Different Stages of Immunity

Human Endogenous retroviruses (HERVs) and Mammalian Apparent LTRs Retrotransposons (MaLRs) are remnants of ancient retroviral infections that represent a large fraction of our genome. The HERV and MaLR transcriptional activity is regulated in developmental stages, adult tissues, and pathological conditions. In this work, we used a bioinformatics approach based on RNA-sequencing (RNA-seq) to study the expression and modulation of HERVs and MaLR in a scenario of activation of the immune response. We analyzed transcriptome data from subjects before and after the administration of an inactivated vaccine against the Hantaan orthohantavirus, the causative agent of Korean hemorrhagic fever, to investigate the HERV and MaLR expression and differential expression in response to the administration of the vaccine. Specifically, we described the HERV transcriptome in PBMCs and identified HERV and MaLR loci differentially expressed after the 2nd, 3rd, and 4th inactivated vaccine administrations. We found that the expression of 545 HERV and MaLR elements increased in response to the vaccine and that the activation of several individual HERV and MaLR loci is specific for each vaccine administration and correlated to different genes and immune-related pathways.

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

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.

RNA-Seq Transcriptome Analysis Reveals Long Terminal Repeat Retrotransposon Modulation in Human Peripheral Blood Mononuclear Cells after In Vivo Lipopolysaccharide Injection

Human endogenous retroviruses (HERVs) and mammalian apparent long terminal repeat (LTR) retrotransposons (MaLRs) are retroviral sequences that integrated into germ line cells millions of years ago. Transcripts of these LTR retrotransposons are present in several tissues, and their expression is modulated in pathological conditions, although their function remains often far from being understood. Here, we focused on the HERV/MaLR expression and modulation in a scenario of immune system activation. We used a public data set of human peripheral blood mononuclear cells (PBMCs) RNA-Seq from 15 healthy participants to a clinical trial before and after exposure to lipopolysaccharide (LPS), for which we established an RNA-Seq workflow for the identification of expressed and modulated cellular genes and LTR retrotransposon elements.IMPORTANCE We described the HERV and MaLR transcriptome in PBMCs, finding that about 8.4% of the LTR retrotransposon loci were expressed and identifying the betaretrovirus-like HERVs as those with the highest percentage of expressed loci. We found 4,607 HERV and MaLR loci that were modulated as a result of in vivo stimulation with LPS. The HERV-H group showed the highest number of differentially expressed most intact proviruses. We characterized the HERV and MaLR loci as differentially expressed, checking their genomic context of insertion and observing a general colocalization with genes that are involved and modulated in the immune response, as a consequence of LPS stimulation. The analyses of HERV and MaLR expression and modulation show that these LTR retrotransposons are expressed in PBMCs and regulated in inflammatory settings. The similar regulation of HERVs/MaLRs and genes after LPS stimulation suggests possible interactions of LTR retrotransposons and the immune host response.

Two gene set variation indexes as potential diagnostic tool for sepsis

Accurate diagnosis of sepsis remains challenging, new markers or combinations of markers are urgently needed. In the present study, we screened differentially expressed genes (DEGs) between sepsis and non-sepsis blood samples across three previously published gene expression data sets. Common upregulated and downregulated DEGs were ranked according to their average functional similarity. The ten genes (OLFM4, ORM1, CEP55, S100A12, S100P, LRG1, CEACAM8, MS4A4A, PLSCR1, and IL1R2) with the largest average functional similarity among the common upregulated genes and another ten genes (THEMIS, IL2RB, CD2, IL7R, CD3E, KLRB1, PVRIG, CCRR3, TGFBR3, and PLEKHA1) with the largest average functional similarity among the common downregulated genes were separately identified as the upregulated crucial gene set and the downregulated crucial gene set. Gene set variation analysis (GSVA) was used to obtain the GSVA index of each sample against the two crucial gene sets. Both the two crucial GSVA indexes may be robust markers for sepsis with high area under ROC curve. The diagnostic utility of the upregulated GSVA index was validated in another independent data set. Functional analyses revealed several sepsis-related pathways. In conclusion, we proposed two sepsis-related gene sets across multiple data sets and created two GSVA indexes with promising diagnostic value.

High-Throughput Sequencing is a Crucial Tool to Investigate the Contribution of Human Endogenous Retroviruses (HERVs) to Human Biology and Development

Human Endogenous retroviruses (HERVs) are remnants of ancient retroviral infections that represent a large fraction of our genome. Their transcriptional activity is finely regulated in early developmental stages and their expression is modulated in different cell types and tissues. Such activity has an impact on human physiology and pathology that is only partially understood up to date. Novel high-throughput sequencing tools have recently allowed for a great advancement in elucidating the various HERV expression patterns in different tissues as well as the mechanisms controlling their transcription, and overall, have helped in gaining better insights in an all-inclusive understanding of the impact of HERVs in biology of the host.

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

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, current knowledge of the role of lncRNAs in sepsis is still extremely limited.

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 profiling 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.

Dynamic LTR retrotransposon transcriptome landscape in septic shock patients

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.