IFI44L expression is regulated by IRF-1 and HIV-1

ACSL4 upregulates IFI44 and IFI44L expression and promotes the proliferation and invasiveness of head and neck squamous cell carcinoma cells

Reprogramming of cellular energy metabolism, including deregulated lipid metabolism, is a hallmark of head and neck squamous cell carcinoma (HNSCC). However, the underlying molecular mechanisms remain unclear. Long-chain acyl-CoA synthetase 4 (ACSL4), which catalyzes fatty acids to form fatty acyl-CoAs, is critical for synthesizing phospholipids or triglycerides. Despite the differing roles of ACSL4 in cancers, our data showed that ACSL4 was highly expressed in HNSCC tissues, positively correlating with poor survival rates in patients. Knockdown of ACSL4 in HNSCC cells led to reduced cell proliferation and invasiveness. RNA sequencing analyses identified interferon-induced protein 44 (IFI44) and interferon-induced protein 44-like (IFI44L), encoded by two interferon-stimulated genes, as potential effectors of ACSL4. Silencing IFI44 or IFI44L expression in HNSCC cells decreased cell proliferation and invasiveness. Manipulating ACSL4 expression or activity modulated the expression levels of JAK1, tyrosine kinase 2 (TYK2), signal transducer and activator of transcription 1 (STAT1), interferon α (IFNα), IFNβ, and interferon regulatory factor 1 (IRF1), which regulate IFI44 and IFI44L expression. Knockdown of IRF1 reduced the expression of JAK1, TYK2, IFNα, IFNβ, IFI44, or IFI44L and diminished cell proliferation and invasiveness. Our results suggest that ACSL4 upregulates interferon signaling, enhancing IFI44 and IFI44L expression and promoting HNSCC cell proliferation and invasiveness. Thus, ACSL4 could serve as a novel therapeutic target for HNSCC.

Discovering common pathogenetic processes between COVID-19 and tuberculosis by bioinformatics and system biology approach

Introduction

The coronavirus disease 2019 (COVID-19) pandemic, stemming from the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has persistently threatened the global health system. Meanwhile, tuberculosis (TB) caused by Mycobacterium tuberculosis (M. tuberculosis) still continues to be endemic in various regions of the world. There is a certain degree of similarity between the clinical features of COVID-19 and TB, but the underlying common pathogenetic processes between COVID-19 and TB are not well understood.

Methods

To elucidate the common pathogenetic processes between COVID-19 and TB, we implemented bioinformatics and systematic research to obtain shared pathways and molecular biomarkers. Here, the RNA-seq datasets (GSE196822 and GSE126614) are used to extract shared differentially expressed genes (DEGs) of COVID-19 and TB. The common DEGs were used to identify common pathways, hub genes, transcriptional regulatory networks, and potential drugs.

Results

A total of 96 common DEGs were selected for subsequent analyses. Functional enrichment analyses showed that viral genome replication and immune-related pathways collectively contributed to the development and progression of TB and COVID-19. Based on the protein-protein interaction (PPI) network analysis, we identified 10 hub genes, including IFI44L, ISG15, MX1, IFI44, OASL, RSAD2, GBP1, OAS1, IFI6, and HERC5. Subsequently, the transcription factor (TF)-gene interaction and microRNA (miRNA)-gene coregulatory network identified 61 TFs and 29 miRNAs. Notably, we identified 10 potential drugs to treat TB and COVID-19, namely suloctidil, prenylamine, acetohexamide, terfenadine, prochlorperazine, 3'-azido-3'-deoxythymidine, chlorophyllin, etoposide, clioquinol, and propofol.

Conclusion

This research provides novel strategies and valuable references for the treatment of tuberculosis and COVID-19.

Integrated bioinformatic analyses investigate macrophage-M1-related biomarkers and tuberculosis therapeutic drugs

Tuberculosis (TB) is a common infectious disease linked to host genetics and the innate immune response. It is vital to investigate new molecular mechanisms and efficient biomarkers for Tuberculosis because the pathophysiology of the disease is still unclear, and there aren't any precise diagnostic tools. This study downloaded three blood datasets from the GEO database, two of which (GSE19435 and 83456) were used to build a weighted gene co-expression network for searching hub genes associated with macrophage M1 by the CIBERSORT and WGCNA algorithms. Furthermore, 994 differentially expressed genes (DEGs) were extracted from healthy and TB samples, four of which were associated with macrophage M1, naming RTP4, CXCL10, CD38, and IFI44. They were confirmed as upregulation in TB samples by external dataset validation (GSE34608) and quantitative real-time PCR analysis (qRT-PCR). CMap was used to predict potential therapeutic compounds for tuberculosis using 300 differentially expressed genes (150 downregulated and 150 upregulated genes), and six small molecules (RWJ-21757, phenamil, benzanthrone, TG-101348, metyrapone, and WT-161) with a higher confidence value were extracted. We used in-depth bioinformatics analysis to investigate significant macrophage M1-related genes and promising anti-Tuberculosis therapeutic compounds. However, more clinical trials were necessary to determine their effect on Tuberculosis.

The involvement of an interferon-induced protein 44-like (CgIFI44L) in the antiviral immune response of Crassostrea gigas

Interferon-stimulated genes (ISGs) encoding proteins are the essential executors of interferon (IFN) mediated antiviral defense. In the present study, an ISG member, interferon-induced protein 44-like (IFI44L) gene (designed as CgIFI44L-1) was identified from the Pacific oyster Crassostrea gigas. The ORF of CgIFI44L-1 cDNA was of 1437 bp encoding a polypeptide of 479 amino acids with a TLDc domain and an MMR_HSR1 domain. The mRNA transcripts of CgIFI44L-1 were detected in all the tested tissues with highest level in haemocytes, which was 15.78-fold of that in gonad (p < 0.001). Among the haemocytes, the CgIFI44L-1 protein was detected to be highly expressed in granulocytes with dominant distribution in cytoplasm. The mRNA expression level of CgIFI44L-1 in haemocytes was significantly induced by poly (I:C) stimulation, and the expression level peaked at 24 h, which was 24.24-fold (p < 0.0001) of that in control group. After the treatment with the recombinant protein of an oyster IFN-like protein (rCgIFNLP), the mRNA expression level of CgIFI44L-1 was significantly enhanced at 6 h, 12 h and 24 h, which was 2.67-fold (p < 0.001), 5.44-fold (p < 0.001) and 5.16-fold (p < 0.001) of that in control group, respectively. When the expressions of CgSTAT and CgIFNLP were knocked down by RNA interference (RNAi), the mRNA transcripts of CgIFI44L-1 were significantly down-regulated after poly (I:C) stimulation, which was 0.09-fold (p < 0.001) and 0.06-fold (p < 0.001) of those in EGFP group, respectively. These results suggested that CgIFI44L-1 was a conserved ISG in oyster, which was regulated by CgIFNLP and CgSTAT, and involved in the oyster antiviral immune response.

Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method

Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a tight relationship with the immune system. Human resistance to COVID-19 infection comprises two stages. The first stage is immune defense, while the second stage is extensive inflammation. This process is further divided into innate and adaptive immunity during the immune defense phase. These two stages involve various immune cells, including CD4⁺ T cells, CD8⁺ T cells, monocytes, dendritic cells, B cells, and natural killer cells. Various immune cells are involved and make up the complex and unique immune system response to COVID-19, providing characteristics that set it apart from other respiratory infectious diseases. In the present study, we identified cell markers for differentiating COVID-19 from common inflammatory responses, non-COVID-19 severe respiratory diseases, and healthy populations based on single-cell profiling of the gene expression of six immune cell types by using Boruta and mRMR feature selection methods. Some features such as IFI44L in B cells, S100A8 in monocytes, and NCR2 in natural killer cells are involved in the innate immune response of COVID-19. Other features such as ZFP36L2 in CD4⁺ T cells can regulate the inflammatory process of COVID-19. Subsequently, the IFS method was used to determine the best feature subsets and classifiers in the six immune cell types for two classification algorithms. Furthermore, we established the quantitative rules used to distinguish the disease status. The results of this study can provide theoretical support for a more in-depth investigation of COVID-19 pathogenesis and intervention strategies.

Transcriptome innovations in primates revealed by single-molecule long-read sequencing

Transcriptomic diversity greatly contributes to the fundamentals of disease, lineage-specific biology, and environmental adaptation. However, much of the actual isoform repertoire contributing to shaping primate evolution remains unknown. Here, we combined deep long- and short-read sequencing complemented with mass spectrometry proteomics in a panel of lymphoblastoid cell lines (LCLs) from human, three other great apes, and rhesus macaque, producing the largest full-length isoform catalog in primates to date. Around half of the captured isoforms are not annotated in their reference genomes, significantly expanding the gene models in primates. Furthermore, our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these evolutionary innovations with signals of positive selection and their limited impact in the proteome points to changes in alternative splicing in genes involved in immune response as an important target of recent regulatory divergence in primates.

Epigenetic Regulation of IFI44L Expression in Monocytes Affects the Functions of Monocyte-Derived Dendritic Cells in Systemic Lupus Erythematosus

Background

Interferon-inducible 44 like (IFI44L) is a newly discovered interferon-induced gene and has been reported to overexpress in systemic lupus erythematosus (SLE). However, little is known about the mechanism and function of IFI44L overexpression in SLE. In this study, we aimed to investigate the epigenetic mechanism of IFI44L overexpression in SLE monocyte and its potential functions contributing to the pathogenesis of SLE.

Methods

We collected peripheral blood from 20 SLE patients and 20 healthy controls. Expression of IFI44L in monocytes and effects of different signal transducers and activators of transcription (STAT) pathway inhibitors on IFI44L expression were detected. Recruitment of ten-eleven translocation protein (TET) by STAT and methylation of IFI44L promoter were evaluated. Effects of IFI44L overexpression on the expression of surface markers on monocyte-derived dendritic cells (Mo-DCs) were analyzed. T cell differentiation mediated by Mo-DCs and related cytokines production were also analyzed.

Results

Expression level of IFI44L was significantly increased in SLE monocyte. IFI44L expression was decreased most significantly in STAT3 inhibitor compared with other inhibitors. STAT3 regulated IFI44L expression and interacted with TET2 which induced DNA demethylation of IFI44L promoter. Overexpression of IFI44L in monocyte enhanced the maturation and functions of Mo-DC by upregulating costimulatory receptors and inducing Th1/Th17-related cytokines when cocultured with naïve CD4+ T cells.

Conclusion

TET2 recruited by STAT3 induces DNA demethylation of IFI44L promoter which promotes IFI44L overexpression in monocyte contributing to the pathogenesis of SLE by enhancing the maturation and functions of Mo-DC. IFI44L is expected to become a new target for treatment of SLE.

Pulmonary Mesenchymal Stem Cells in Mild Cases of COVID-19 Are Dedicated to Proliferation; In Severe Cases, They Control Inflammation, Make Cell Dispersion, and Tissue Regeneration

Mesenchymal stem cells (MSCs) are multipotent adult stem cells present in virtually all tissues; they have potent self-renewal capacity and differentiate into multiple cell types. For many reasons, these cells are a promising therapeutic alternative to treat patients with severe COVID-19 and pulmonary post-COVID sequelae. These cells are not only essential for tissue regeneration; they can also alter the pulmonary environment through the paracrine secretion of several mediators. They can control or promote inflammation, induce other stem cells differentiation, restrain the virus load, and much more. In this work, we performed single-cell RNA-seq data analysis of MSCs in bronchoalveolar lavage samples from control individuals and COVID-19 patients with mild and severe clinical conditions. When we compared samples from mild cases with control individuals, most genes transcriptionally upregulated in COVID-19 were involved in cell proliferation. However, a new set of genes with distinct biological functions was upregulated when we compared severely affected with mild COVID-19 patients. In this analysis, the cells upregulated genes related to cell dispersion/migration and induced the γ-activated sequence (GAS) genes, probably triggered by IFNGR1 and IFNGR2. Then, IRF-1 was upregulated, one of the GAS target genes, leading to the interferon-stimulated response (ISR) and the overexpression of many signature target genes. The MSCs also upregulated genes involved in the mesenchymal-epithelial transition, virus control, cell chemotaxis, and used the cytoplasmic RNA danger sensors RIG-1, MDA5, and PKR. In a non-comparative analysis, we observed that MSCs from severe cases do not express many NF-κB upstream receptors, such as Toll-like (TLRs) TLR-3, -7, and -8; tumor necrosis factor (TNFR1 or TNFR2), RANK, CD40, and IL-1R1. Indeed, many NF-κB inhibitors were upregulated, including PPP2CB, OPTN, NFKBIA, and FHL2, suggesting that MSCs do not play a role in the "cytokine storm" observed. Therefore, lung MSCs in COVID-19 sense immune danger and act protectively in concert with the pulmonary environment, confirming their therapeutic potential in cell-based therapy for COVID-19. The transcription of MSCs senescence markers is discussed.

Comprehensive Analysis of Immune Implication and Prognostic Value of IFI44L in Non-Small Cell Lung Cancer

Interferon-induced protein 44-like (IFI44L), a type I interferon-stimulated gene (ISG), has been reported to be involved in innate immune processes and to act as a tumor suppressor in several cancers. However, its immune implication on lung cancer remains unclear. Here, we systemically analyzed the immune association of IFI44L with multiple tumor-infiltrating immune cells (TIICs) and immunomodulators through bioinformatics methods in The Cancer Genome Atlas (TCGA) lung cancer cohorts. Then, the IFI44L-related immunomodulators were selected to construct the prognostic signatures in the lung adenocarcinoma (LUAD) cohort and the lung squamous cell carcinoma (LUSC) cohort, respectively. Concordance index and time-dependent receiver operating characteristics (ROC) curves were applied to evaluate the prognostic signatures. GSE72094 and GSE50081 were used to validate the TCGA-LUAD signature and TCGA-LUSC signature, respectively. A nomogram was established by risk score and clinical features in the LUAD cohort. Finally, the prognostic value and biological function of IFI44L were verified in a real-world cohort and in vitro experiments. The results indicated that IFI44L showed significant correlation with TIICs in LUAD and LUSC samples. Functional enrichment analysis showed that IFI44L may participate in various cancer/immune-related pathways, including JAK/STAT signaling pathway and NF-κB signaling pathway. A total of 44 immunomodulators presented obvious association with IFI44L in the TCGA-LUAD cohort and a robust 10-immunomodulator signature was constructed. Patients in the higher-risk group presented worse prognosis than those in the lower-risk group. Notably, the risk signature was successfully validated in GSE72094. Multivariate Cox regression suggested that the risk signature could act as independent prognostic factors in both TCGA-LUAD and GSE72094 cohorts. Besides, a 17-immunomodulator signature was established in the TCGA-LUSC cohort and similar results were presented through analysis. The nomogram exhibited good accuracy in predicting overall survival (OS) outcome among TCGA-LUAD patients than the risk signature and other clinical features, with the area under curve values being 0.782 at 1 year, 0.825 at 3 years, and 0.792 at 5 years. Finally, tissue microarray analysis indicated that higher expression of IFI44L presented opposite relationship with pathological stage (p = 0.016) and a better outcome among lung cancer patients (p = 0.024). Functional experiments found that IFI44L overexpression significantly inhibited the proliferation, migration, and invasion in LUAD and LUSC cells; RT-qPCR experiments verified the correlation between the expression level of IFI44L with multiple immunomodulators in SPC-A-1 and NCI-H520 cells. In conclusion, our research highlighted that IFI44L is associated with tumor immune infiltration and provided information on IFI44L's immune implication, which indicates that IFI44L has potential clinical immunotherapeutic value and the proposed nomogram is a promising biomarker for non-small cell lung cancer patients.

Integrated weighted gene co-expression network analysis uncovers STAT1(signal transducer and activator of transcription 1) and IFI44L (interferon-induced protein 44-like) as key genes in pulmonary arterial hypertension

Despite the multiple diagnostic and therapeutic strategies implemented in clinical practice, the mortality rate of patients with pulmonary arterial hypertension (PAH) remains high. Understanding the mechanisms and key genes involved could provide insight into the drivers of the pathogenesis of PAH. In this research, we aimed to examine the mechanisms underlying PAH and identify key genes with potential usefulness as clinical biomarkers of PAH and thereby establish therapeutic targets for PAH. The datasets GSE117261, GSE113439, and GSE53408 were downloaded from the Gene Expression Omnibus (GEOs) database. We used weighted gene coexpression network analysis (WGCNA) to identify networks and the most relevant modules in PAH. Functional enrichment analysis was performed for the selected clinically relevant modules. The least absolute shrinkage and selection operator (LASSO) was applied to identify key genes in lung samples from patients with PAH. The genes were validated in a monocrotaline-induced PAH rat model. Three clinically relevant modules were identified through average linkage hierarchical clustering. The genes in the clinically relevant modules were related to endothelial cell differentiation, inflammation, and autoimmunity. Seven genes were screened as key genes significantly associated with PAH. Interferon-induced protein 44-like (IFI44L) and signal transducer and activator of transcription 1 (STAT1) were expressed at higher levels in the lung tissues of the PAH rat model than in those of the controls. Our findings reveal the novel pathological mechanisms underlying PAH and indicate that STAT1 and IFI44L may represent potential therapeutic targets in PAH.

IFI44L as a Forward Regulator Enhancing Host Antituberculosis Responses

Interferon-induced protein 44-like (IFI44L) gene is a type I interferon-stimulated gene (ISG) that plays a critical role in antiviral activity and constitutes a promising diagnostic marker. However, its precise role and function in tuberculosis have not been unveiled. This study showed that IFI44L acts as an antimicrobial target and positive modulator in human macrophages. Knockdown of IFI44L led to increased Mycobacterium tuberculosis intracellular survival. Moreover, IFI44L was significantly upregulated, and it restricted the intracellular survival of M. tuberculosis H37Rv strains at 72 h after rifampicin treatment. Individuals with cutaneous tuberculosis (CTB) were found to have significantly higher IFI44L expression after 6 months of rifampicin therapy than after only 1 month. These results demonstrated that IFI44L induced positive regulation and clearance of M. tuberculosis from human macrophages. This antimicrobial activity of IFI44L makes it a possible target for therapeutic applications against M. tuberculosis.

Blood Transcriptomes of Anti-SARS-CoV-2 Antibody-Positive Healthy Individuals Who Experienced Asymptomatic Versus Clinical Infection

The reasons behind the clinical variability of SARS-CoV-2 infection, ranging from asymptomatic infection to lethal disease, are still unclear. We performed genome-wide transcriptional whole-blood RNA sequencing, bioinformatics analysis and PCR validation to test the hypothesis that immune response-related gene signatures reflecting baseline may differ between healthy individuals, with an equally robust antibody response, who experienced an entirely asymptomatic (n=17) versus clinical SARS-CoV-2 infection (n=15) in the past months (mean of 14 weeks). Among 12.789 protein-coding genes analysed, we identified six and nine genes with significantly decreased or increased expression, respectively, in those with prior asymptomatic infection relatively to those with clinical infection. All six genes with decreased expression (IFIT3, IFI44L, RSAD2, FOLR3, PI3, ALOX15), are involved in innate immune response while the first two are interferon-induced proteins. Among genes with increased expression six are involved in immune response (GZMH, CLEC1B, CLEC12A), viral mRNA translation (GCAT), energy metabolism (CACNA2D2) and oxidative stress response (ENC1). Notably, 8/15 differentially expressed genes are regulated by interferons. Our results suggest that subtle differences at baseline expression of innate immunity-related genes may be associated with an asymptomatic disease course in SARS-CoV-2 infection. Whether a certain gene signature predicts, or not, those who will develop a more efficient immune response upon exposure to SARS-CoV-2, with implications for prioritization for vaccination, warrant further study.