The complement C1qA enhances retinoic acid-inducible gene-I-mediated immune signalling

Common ground on immune infiltration landscape and diagnostic biomarkers in diabetes-complicated atherosclerosis: an integrated bioinformatics analysis

Introduction

Type 2 diabetes mellitus (T2DM) is a major cause of atherosclerosis (AS). However, definitive evidence regarding the common molecular mechanisms underlying these two diseases are lacking. This study aimed to investigate the mechanisms underlying the association between T2DM and AS.

Methods

The gene expression profiles of T2DM (GSE159984) and AS (GSE100927) were obtained from the Gene Expression Omnibus, after which overlapping differentially expressed gene identification, bioinformatics enrichment analyses, protein-protein interaction network construction, and core genes identification were performed. We confirmed the discriminatory capacity of core genes using receiver operating curve analysis. We further identified transcription factors using TRRUST database to build a transcription factor-mRNA regulatory network. Finally, the immune infiltration and the correlation between core genes and differential infiltrating immune cells were analyzed.

Results

A total of 27 overlapping differentially expressed genes were identified under the two-stress conditions. Functional analyses revealed that immune responses and transcriptional regulation may be involved in the potential pathogenesis. After protein-protein interaction network deconstruction, external datasets, and qRT-PCR experimental validation, four core genes (IL1B, C1QA, CCR5, and MSR1) were identified. ROC analysis further showed the reliable value of these core genes. Four common differential infiltrating immune cells (B cells, CD4+ T cells, regulatory T cells, and M2 macrophages) between T2DM and AS datasets were selected based on immune cell infiltration. A significant correlation between core genes and common differential immune cells. Additionally, five transcription factors (RELA, NFκB1, JUN, YY1, and SPI1) regulating the transcription of core genes were mined using upstream gene regulator analysis.

Discussion

In this study, common target genes and co-immune infiltration landscapes were identified between T2DM and AS. The relationship among five transcription factors, four core genes, and four immune cells profiles may be crucial to understanding T2DM complicated with AS pathogenesis and therapeutic direction.

Canonical and non-canonical roles of complement in atherosclerosis

Cardiovascular diseases are the leading cause of death globally, and atherosclerosis is the major contributor to the development and progression of cardiovascular diseases. Immune responses have a central role in the pathogenesis of atherosclerosis, with the complement system being an acknowledged contributor. Chronic activation of liver-derived and serum-circulating canonical complement sustains endothelial inflammation and innate immune cell activation, and deposition of complement activation fragments on inflamed endothelial cells is a hallmark of atherosclerotic plaques. However, increasing evidence indicates that liver-independent, cell-autonomous and non-canonical complement activities are underappreciated contributors to atherosclerosis. Furthermore, complement activation can also have atheroprotective properties. These specific detrimental or beneficial contributions of the complement system to the pathogenesis of atherosclerosis are dictated by the location of complement activation and engagement of its canonical versus non-canonical functions in a temporal fashion during atherosclerosis progression. In this Review, we summarize the classical and the emerging non-classical roles of the complement system in the pathogenesis of atherosclerosis and discuss potential strategies for therapeutic modulation of complement for the prevention and treatment of atherosclerotic cardiovascular disease.

From complement to complosome in non-alcoholic fatty liver disease: When location matters

Non-alcoholic fatty liver disease (NAFLD) is a growing public health threat and becoming the leading cause of liver transplantation. Nevertheless, no approved specific treatment is currently available for NAFLD. The pathogenesis of NAFLD is multifaceted and not yet fully understood. Accumulating evidence suggests a significant role of the complement system in the development and progression of NAFLD. Here, we provide an overview of the complement system, incorporating the novel concept of complosome, and summarise the up-to-date evidence elucidating the association between complement dysregulation and the pathogenesis of NAFLD. In this process, the extracellular complement system is activated through various pathways, thereby directly contributing to, or working together with other immune cells in the disease development and progression. We also introduce the complosome and assess the evidence that implicates its potential influence in NAFLD through its direct impact on hepatocytes or non-parenchymal liver cells. Additionally, we expound upon how complement system and the complosome may exert their effects in relation with hepatic zonation in NAFLD. Furthermore, we discuss the potential therapeutic implications of targeting the complement system, extracellularly and intracellularly, for NAFLD treatment. Finally, we present future perspectives towards a better understanding of the complement system's contribution to NAFLD.

Complosome - the intracellular complement system

The complement system is a recognized pillar of host defence against infection and noxious self-derived antigens. Complement is traditionally known as a serum-effective system, whereby the liver expresses and secretes most complement components, which participate in the detection of bloodborne pathogens and drive an inflammatory reaction to safely remove the microbial or antigenic threat. However, perturbations in normal complement function can cause severe disease and, for reasons that are currently not fully understood, the kidney is particularly vulnerable to dysregulated complement activity. Novel insights into complement biology have identified cell-autonomous and intracellularly active complement - the complosome - as an unexpected central orchestrator of normal cell physiology. For example, the complosome controls mitochondrial activity, glycolysis, oxidative phosphorylation, cell survival and gene regulation in innate and adaptive immune cells, and in non-immune cells, such as fibroblasts and endothelial and epithelial cells. These unanticipated complosome contributions to basic cell physiological pathways make it a novel and central player in the control of cell homeostasis and effector responses. This discovery, together with the realization that an increasing number of human diseases involve complement perturbations, has renewed interest in the complement system and its therapeutic targeting. Here, we summarize the current knowledge about the complosome across healthy cells and tissues, highlight contributions from dysregulated complosome activities to human disease and discuss potential therapeutic implications.

F8 gene inversion and duplication cause no obvious hemophilia A phenotype

Hemophilia A (HA, OMIM#306700) is an X-linked recessive bleeding disorder caused by the defects in the F8 gene, which encodes coagulation factor VIII (FVIII). Intron 22 inversion (Inv22) is found in about 45% of patients with severe hemophilia A. Here, we reported a male without obvious hemophilia A phenotype but bearing an inherited segmental variant duplication encompassing F8 as well as Inv22. The duplication was approximately 0.16 Mb and involved from exon 1 to intron 22 of F8. This partial duplication and Inv22 in F8 was first found in the abortion tissue of his older sister with recurrent miscarriage. The genetic testing of his family revealed that his phenotypically normal older sister and mother also had this heterozygous Inv22 and a 0.16 Mb partial duplication of F8, while his father was genotypically normal. The integrity of the F8 gene transcript was verified by sequencing of the adjacent exons at the inversion breakpoint, which explained why this male had no phenotype for hemophilia A. Interestingly, although he had no significant hemophilia A phenotype, the expression of C1QA in his mother, sister, and the male subject was only about half of that in his father and normal population. Our report broadens the mutation spectrum of F8 inversion and duplication and its pathogenicity in hemophilia A.

Identification of crucial genes for predicting the risk of atherosclerosis with system lupus erythematosus based on comprehensive bioinformatics analysis and machine learning

BACKGROUND

Systemic lupus erythematosus (SLE) has become a major public health problem over the years, and atherosclerosis (AS) is one of the main complications of SLE associated with serious cardiovascular consequences in this patient population. The present study aimed to identify potential biomarkers for SLE patients with AS.

METHODS

Five microarray datasets (GSE50772, GSE81622, GSE100927, GSE28829, GSE37356) were downloaded from the NCBI Gene Expression Omnibus database. The Limma package was used to identify differentially expressed genes (DEGs) in AS. Weighted gene coexpression network analysis (WGCNA) was used to identify significant module genes associated with SLE. Functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning algorithms (least absolute shrinkage and selection operator (Lasso, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and random forest) were applied to identify hub genes. Subsequently, we generated a nomogram and receiver operating characteristic curve (ROC) for predicting the risk of AS in SLE patients. Finally, immune cell infiltrations were analyzed, and Consensus Cluster Analysis was conducted based on Single Sample Gene Set Enrichment Analysis (ssGSEA) scores.

RESULTS

Five hub genes (SPI1, MMP9, C1QA, CX3CR1, and MNDA) were identified and used to establish a nomogram that yielded a high predictive performance (area under the curve 0.900-0.981). Dysregulated immune cell infiltrations were found in AS, with positive correlations with the five hub genes. Consensus clustering showed that the optimal number of subtypes was 3. Compared to subtypes A and B, subtype C presented higher expression of the five hub genes, immune cell infiltration levels and immune checkpoint expression.

CONCLUSION

Our study systematically identified five candidate hub genes (SPI1, MMP9, C1QA, CX3CR1, MNDA) and established a nomogram that could predict the risk of AS with SLE using various bioinformatic analyses and machine learning algorithms. Our findings provide the foothold for future studies on potential crucial genes for AS in SLE patients. Additionally, the dysregulated immune cell proportions and immune checkpoint expressions in AS with SLE were identified.

Multi-omics profiling identifies C1QA/B+ macrophages with multiple immune checkpoints associated with esophageal squamous cell carcinoma (ESCC) liver metastasis

Background

Esophageal squamous cell carcinoma (ESCC) is a highly lethal malignant tumor lacking effective treatments; 20% of ESCC patients develop liver metastasis with an extremely short survival time of ≈5 months. The tumor microenvironment (TME) plays a crucial role in tumor homeostasis, but the relationship between the ESCC TME and liver metastasis is still unknown.

Methods

To identify potential cell populations contributing to ESCC liver metastasis, single-cell RNA (scRNA) sequencing data were analyzed to identify the major cell populations within the TME. Each of the major cell populations was re-clustered to define detailed cell subsets. Thereafter, the gene set variation analysis (GSVA) score was calculated for the bulk RNA-seq data based on the gene signatures of each cell subset. The relationship between the GSVA score of each cellular subset and clinical outcome was further analyzed to identify the cellular subset associated with ESCC liver metastasis, which was validated by multiplex immunohistochemistry.

Results

C1QA/B⁺ tumor-associated macrophages (TAMs) acted as the central regulator of the ESCC TME, closely associated with several key cell subsets. Several immune checkpoints, including CD40, CD47 and LGALS9, were all positively expressed in C1QA/B⁺ macrophages, which may exert central regulatory control of immune evasion by ESCC via these immune checkpoints expressions.

Conclusions

Our results comprehensively revealed the landscape of tumor-infiltrating immune cells associated with ESCC prognosis and metastasis, and suggest a novel strategy for developing immunotherapies for ESCC liver metastasis by targeting C1QA/B⁺ TAMs.

Linking nutrient sensing, mitochondrial function, and PRR immune cell signaling in liver disease

Caloric overconsumption in vertebrates promotes adipose and liver fat accumulation while perturbing the gut microbiome. This triad triggers pattern recognition receptor (PRR)-mediated immune cell signaling and sterile inflammation. Moreover, immune system activation perpetuates metabolic consequences, including the progression of nonalcoholic fatty liver disease (NAFLD) to nonalcoholic hepatic steatohepatitis (NASH). Recent findings show that sensing of nutrient overabundance disrupts the activity and homeostasis of the central cellular energy-generating organelle, the mitochondrion. In parallel, whether caloric excess-initiated PRR signaling and mitochondrial perturbations are coordinated to amplify this inflammatory process in NASH progression remains in question. We hypothesize that altered mitochondrial function, classic PRR signaling, and complement activation in response to nutrient overload together play an integrated role across the immune cell landscape, leading to liver inflammation and NASH progression.

Proteomic and Metabolomic Signatures Associated With the Immune Response in Healthy Individuals Immunized With an Inactivated SARS-CoV-2 Vaccine

CoronaVac (Sinovac), an inactivated vaccine for SARS-CoV-2, has been widely used for immunization. However, analysis of the underlying molecular mechanisms driving CoronaVac-induced immunity is still limited. Here, we applied a systems biology approach to understand the mechanisms behind the adaptive immune response to CoronaVac in a cohort of 50 volunteers immunized with 2 doses of CoronaVac. Vaccination with CoronaVac led to an integrated immune response that included several effector arms of the adaptive immune system including specific IgM/IgG, humoral response and other immune response, as well as the innate immune system as shown by complement activation. Metabolites associated with immunity were also identified implicating the role of metabolites in the humoral response, complement activation and other immune response. Networks associated with the TCA cycle and amino acids metabolic pathways, such as phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and glycine, serine and threonine metabolism were tightly coupled with immunity. Critically, we constructed a multifactorial response network (MRN) to analyze the underlying interactions and compared the signatures affected by CoronaVac immunization and SARS-CoV-2 infection to further identify immune signatures and related metabolic pathways altered by CoronaVac immunization. These results help us to understand the host response to vaccination of CoronaVac and highlight the utility of a systems biology approach in defining molecular correlates of protection to vaccination.

Proteomic profiling and correlations with clinical features reveal biomarkers indicative of diabetic retinopathy with diabetic kidney disease

Diabetic retinopathy (DR) and diabetic kidney disease (DKD) are complications of diabetes and place serious health and economic burdens on society. However, the identification and characterization of early biomarkers for DKD, especially for nonproliferative DR (NPDR) patients with DKD, are still needed. This study aimed to demonstrate the plasma proteomic profiles of NPDR+DKD and NPDR patients and identify potential biomarkers for early diagnosis of DKD. Fifteen plasma samples from the NPDR group and nine from the NPDR+DKD group were analyzed by LC-MS/MS to identify the differentially expressed proteins between the two groups. Functional enrichment, protein-protein interaction and clinical feature correlation analyses revealed the target protein candidates, which were verified using ELISA and receiver operating characteristic (ROC) analysis. In total, 410 proteins were detected in plasma; 15 were significantly upregulated and 7 were downregulated in the NPDR+DKD group. Bioinformatics analysis suggested that DKD is closely related to cell adhesion and immunity pathways. β-2-Microglobulin (B2M) and vimentin (VIM) were upregulated in NPDR+DKD, enriched as hub proteins and strongly correlated with clinical features. ELISA showed that B2M (p<0.001) and VIM (p<0.0001) were significantly upregulated in NPDR+DKD compared with NPDR. In ROC analysis, B2M and VIM could distinguish DKD from NPDR with area under the curve values of 0.9000 (p < 0.0001) and 0.9950. Our proteomic study revealed alterations in the proteomic profile and identified VIM and B2M as early biomarkers of DKD, laying the foundation for the prevention, diagnosis and treatment of DKD.

The Novel Tumor Microenvironment-Related Prognostic Gene AIF1 May Influence Immune Infiltrates and is Correlated with TIGIT in Esophageal Cancer

BACKGROUND

Esophageal carcinoma (EC) is the sixth most common cause of cancer-related mortality worldwide. Studying the associations of the tumor microenvironment (TME) with pathology and prognosis would illustrate the underlying mechanism of prognostic prediction and provide novel targets for immunotherapy in the treatment of EC.

METHODS

Transcriptomic profiles of 159 EC patients were obtained from The Cancer Genome Atlas (TCGA) database. Stromal and immune scores were calculated using the ESTIMATE algorithm. Differentially expressed genes (DEGs) were identified by the optimal score cutoff. Functional enrichments were analyzed by DAVID, while prognostic genes were explored using the Kaplan-Meier method. Validation analysis was performed using immunohistochemistry in tissue microarrays containing samples from 145 EC patients. Multiplex immunofluorescence staining was performed to detect a panel of 6 immune markers, including T-cell immunoreceptor with Ig and ITIM domains (TIGIT), in 90 EC patients.

RESULTS

Immune scores significantly increased with increasing age, while stromal scores were dramatically elevated with increasing tumor stage. Fifteen TME-related DEGs including allograft inflammatory factor 1 (AIF1) were identified as prognostic factors of EC. Furthermore, the validation cohort indicated that AIF1 was negatively associated with the prognosis of esophageal squamous cell carcinoma patients. Subsequent analyses suggested that AIF1 may affect immune infiltrates, including T cells and natural-killer cells. Moreover, a correlation between AIF1 and TIGIT was identified.

CONCLUSIONS

These results indicate that the TME-related gene AIF1 is a promising predictor of prognosis and is related to immune infiltrates and TIGIT expression in EC. However, further mechanistic studies are needed.

A Novel Diagnostic Predictive Model for Idiopathic Short Stature in Children

OBJECTIVE

Idiopathic short stature (ISS), an endocrine-related disease, is difficult to diagnose. Previous studies have shown that many children with some inflammation-related diseases often have short stature, but whether inflammation is the underlying mechanism of ISS has not been studied. Here, we attempt to explore the role of inflammation in the occurrence and development of ISS and to demonstrate an available clinical diagnostic model of ISS.

METHODS

Frozen serum samples were collected from ISS patients (n = 4) and control individuals (n = 4). Isobaric tags for relative and absolute quantitation (iTRAQ) combined with LC-MS/MS analysis were applied to quantitative proteomics analysis. To assess clusters of potentially interacting proteins, functional enrichment (GO and KEGG) and protein-protein interaction network analyses were performed, and the crucial proteins were detected by Molecular Complex Detection (MCODE). Furthermore, serum levels of two selected proteins were measured by ELISA between ISS patients (n = 80) and controls (n = 80). In addition, experiments in vitro were used to further explore the effects of crucial proteins on endochondral ossification.

RESULTS

A total of 437 proteins were quantified, and 84 DEPs (60 upregulated and 24 downregulated) were identified between patients with ISS and controls. Functional enrichment analysis showed that the DEPs were primarily enriched in blood microparticle, acute inflammatory response, protein activation cascade, collagen-containing extracellular matrix, platelet degranulation, etc. According to the results of top 10 fold change DEPs and MCODE analysis, C1QA and C1QB were selected to further experiment. The expression levels of C1QA and C1QB were validated in serum samples. Based on the logistic regression analysis and ROC curve analysis, we constructed a novel diagnostic model by serum levels of C1QA and C1QB with a specificity of 91.2% and a sensitivity of 75% (AUC = 0.900, p <0.001). Finally, the western blotting analysis confirmed the expression levels of OCN, OPN, RUNX2, and Collagen X were downregulated in chondrocytes, and the outcome of Collagen II was upregulated.

CONCLUSION

Our study is the first to demonstrate the significant role of inflammation in the development of ISS. In addition, we identify C1QA and C1QB as novel serum biomarkers for the diagnosis of ISS.

The HMGB1-2 Ovarian Cancer Interactome. The Role of HMGB Proteins and Their Interacting Partners MIEN1 and NOP53 in Ovary Cancer and Drug-Response

High mobility group box B (HMGB) proteins are overexpressed in different types of cancers such as epithelial ovarian cancers (EOC). We have determined the first interactome of HMGB1 and HMGB2 in epithelial ovarian cancer (the EOC-HMGB interactome). Libraries from the SKOV-3 cell line and a primary transitional cell carcinoma (TCC) ovarian tumor were tested by the Yeast Two Hybrid (Y2H) approach. The interactome reveals proteins that are related to cancer hallmarks and their expression is altered in EOC. Moreover, some of these proteins have been associated to survival and prognosis of patients. The interaction of MIEN1 and NOP53 with HMGB2 has been validated by co-immunoprecipitation in SKOV-3 and PEO1 cell lines. SKOV-3 cells were treated with different anti-tumoral drugs to evaluate changes in HMGB1, HMGB2, MIEN1 and NOP53 gene expression. Results show that combined treatment of paclitaxel and carboplatin induces a stronger down-regulation of these genes in comparison to individual treatments. Individual treatment with paclitaxel or olaparib up-regulates NOP53, which is expressed at lower levels in EOC than in non-cancerous cells. On the other hand, bevacizumab diminishes the expression of HMGB2 and NOP53. This study also shows that silencing of these genes affects cell-viability after drug exposure. HMGB1 silencing causes loss of response to paclitaxel, whereas silencing of HMGB2 slightly increases sensitivity to olaparib. Silencing of either HMGB1 or HMGB2 increases sensitivity to carboplatin. Lastly, a moderate loss of response to bevacizumab is observed when NOP53 is silenced.

Complement-Mediated Regulation of Metabolism and Basic Cellular Processes

Complement is well appreciated as a critical arm of innate immunity. It is required for the removal of invading pathogens and works by directly destroying them through the activation of innate and adaptive immune cells. However, complement activation and function is not confined to the extracellular space but also occurs within cells. Recent work indicates that complement activation regulates key metabolic pathways and thus can impact fundamental cellular processes, such as survival, proliferation, and autophagy. Newly identified functions of complement include a key role in shaping metabolic reprogramming, which underlies T cell effector differentiation, and a role as a nexus for interactions with other effector systems, in particular the inflammasome and Notch transcription-factor networks. This review focuses on the contributions of complement to basic processes of the cell, in particular the integration of complement with cellular metabolism and the potential implications in infection and other disease settings.

Type I interferon related genes are common genes on the early stage after vaccination by meta-analysis of microarray data

The objective of this study was to find common immune mechanism across different kinds of vaccines. A meta-analysis of microarray datasets was performed using publicly available microarray Gene Expression Omnibus (GEO) and Array Express data sets of vaccination records. Seven studies (out of 35) were selected for this meta-analysis. A total of 447 chips (145 pre-vaccination and 302 post-vaccination) were included. Significance analysis of microarrays (SAM) program was used for screening differentially expressed genes (DEGs). Functional pathway enrichment for the DEGs was conducted in DAVID Gene Ontology (GO) database. Twenty DEGs were identified, of which 10 up-regulated genes involved immune response. Six of which were type I interferon (IFN) related genes, including LY6E, MX1, OAS3, IFI44L, IFI6 and IFITM3. Ten down-regulated genes mainly mediated negative regulation of cell proliferation and cell motion. Results of a subgroup analysis showed that although the kinds of genes varied widely between days 3 and 7 post vaccination, the pathways between them are basically the same, such as immune response and response to viruses, etc. For an independent verification of these 6 type I IFN related genes, peripheral blood mononuclear cells (PBMCs) were collected at baseline and day 3 after the vaccination from 8 Enterovirus 71(EV71) vaccinees and were assayed by RT-PCR. Results showed that the 6 DEGs were also upregulated in EV71 vaccinees. In summary, meta-analysis methods were used to explore the immune mechanism of vaccines and results indicated that the type I IFN related genes and corresponding pathways were common in early immune responses for different kinds of vaccines.

Complement--tapping into new sites and effector systems

Complement is traditionally known to be a system of serum proteins that provide protection against pathogens through direct cell lysis and the mobilization of innate and adaptive immunity. However, recent work indicates that the complement system has additional physiological roles beyond those in host defence. In this Opinion article, we describe the new modes and locations of complement activation that enable it to interact with other cell effector systems, such as growth factor receptors, inflammasomes and metabolic pathways. We propose that the location of complement activation dictates its function.

AMPylation of Rho GTPases subverts multiple host signaling processes

Rho GTPases are frequent targets of virulence factors as they are keystone signaling molecules. Herein, we demonstrate that AMPylation of Rho GTPases by VopS is a multifaceted virulence mechanism that counters several host immunity strategies. Activation of NFκB, Erk, and JNK kinase signaling pathways were inhibited in a VopS-dependent manner during infection with Vibrio parahaemolyticus. Phosphorylation and degradation of IKBα were inhibited in the presence of VopS as was nuclear translocation of the NFκB subunit p65. AMPylation also prevented the generation of superoxide by the phagocytic NADPH oxidase complex, potentially by inhibiting the interaction of Rac and p67. Furthermore, the interaction of GTPases with the E3 ubiquitin ligases cIAP1 and XIAP was hindered, leading to decreased degradation of Rac and RhoA during infection. Finally, we screened for novel Rac1 interactions using a nucleic acid programmable protein array and discovered that Rac1 binds to the protein C1QA, a protein known to promote immune signaling in the cytosol. Interestingly, this interaction was disrupted by AMPylation. We conclude that AMPylation of Rho Family GTPases by VopS results in diverse inhibitory consequences during infection beyond the most obvious phenotype, the collapse of the actin cytoskeleton.

Intracellular sensing of complement C3 activates cell autonomous immunity

Pathogens traverse multiple barriers during infection, including cell membranes. We found that during this transition, pathogens carried covalently attached complement C3 into the cell, triggering immediate signaling and effector responses. Sensing of C3 in the cytosol activated mitochondrial antiviral signaling (MAVS)-dependent signaling cascades and induced proinflammatory cytokine secretion. C3 also flagged viruses for rapid proteasomal degradation, preventing their replication. This system could detect both viral and bacterial pathogens but was antagonized by enteroviruses, such as rhinovirus and poliovirus, which cleave C3 using their 3C protease. The antiviral rupintrivir inhibited 3C protease and prevented C3 cleavage, rendering enteroviruses susceptible to intracellular complement sensing. Thus, complement C3 allows cells to detect and disable pathogens that have invaded the cytosol.

Systems biology unravels interferon responses to respiratory virus infections

Interferon production is an important defence against viral replication and its activation is an attractive therapeutic target. However, it has long been known that viruses perpetually evolve a multitude of strategies to evade these host immune responses. In recent years there has been an explosion of information on virus-induced alterations of the host immune response that have resulted from data-rich omics technologies. Unravelling how these systems interact and determining the overall outcome of the host response to viral infection will play an important role in future treatment and vaccine development. In this review we focus primarily on the interferon pathway and its regulation as well as mechanisms by which respiratory RNA viruses interfere with its signalling capacity.