Targeting 7-Dehydrocholesterol Reductase Integrates Cholesterol Metabolism and IRF3 Activation to Eliminate Infection

Xiao, Jun; Li, Weiyun; Zheng, Xin; Qi, Linlin; Wang, Hui; Zhang, Chi; Wan, Xiaopeng; Zheng, Yuxiao; Zhong, Ruiyue; Zhou, Xin; Lu, Yao; Li, Zhiqi; Qiu, Ying; Liu, Chang; Zhang, Fang; Zhang, Yanbo; Xu, Xiaoyan; Yang, Zhongzhou; Chen, Hualan; Zhai, Qiwei; Wei, Bin; Wang, Hongyan

doi:10.1016/j.immuni.2019.11.015

Cited by 99 publications

(98 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DHCR7 is downregulated during RNA virus infection in macrophages to promote IRF3 signaling and IFN-1 production. Moreover, inhibition of DHCR7 aids in clearance of multiple RNA viruses 47 . These previous findings indicate that interactions with IDI1 and DHCR7 may provide means for coronaviruses to counteract anti-viral responses.…”

Section: Discussionmentioning

confidence: 99%

“…We observed shared interactors between OC43 and SARS-CoV-2, such as the Nglycosylation factor RFT1 39,40 and a sarcoplasmic/endoplasmic reticulum calcium ATPase (SERCA -ATP2A2) 41 . In addition, we identified shared interactors between OC43 and SARS-CoV-1, including a regulator of UPR-mediated apoptosis (WLS or GPR177) 42 , a member of the signal peptidase complex (SEC11A) 43 , and factors involved in cholesterol synthesis (IDI1, DHCR7) [44][45][46][47] . WLS, SEC11A, and DHRC7 exhibited higher enrichment for OC43, whereas IDI1 was more greatly enriched for SARS-CoV-1.…”

Section: Analysis Of Go-mentioning

confidence: 99%

See 1 more Smart Citation

Comparative multiplexed interactomics of SARS-CoV-2 and homologous coronavirus non-structural proteins identifies unique and shared host-cell dependencies

Davies

Almasy

McDonald

et al. 2020

Preprint

View full text Add to dashboard Cite

Human coronaviruses (hCoV) have become a threat to global health and society, as evident from the SARS outbreak in 2002 caused by SARS-CoV-1 and the most recent COVID-19 pandemic caused by SARS-CoV-2. Despite high sequence similarity between SARS-CoV-1 and -2, each strain has distinctive virulence. A better understanding of the basic molecular mechanisms mediating changes in virulence is needed. Here, we profile the virus-host protein-protein interactions of two hCoV non-structural proteins (nsps) that are critical for virus replication. We use tandem mass tag-multiplexed quantitative proteomics to sensitively compare and contrast the interactomes of nsp2 and nsp4 from three betacoronavirus strains: SARS-CoV-1, SARS-CoV-2, and hCoV-OC43 - an endemic strain associated with the common cold. This approach enables the identification of both unique and shared host cell protein binding partners and the ability to further compare the enrichment of common interactions across homologs from related strains. We identify common nsp2 interactors involved in endoplasmic reticulum (ER) Ca2+ signaling and mitochondria biogenesis. We also identifiy nsp4 interactors unique to each strain, such as E3 ubiquitin ligase complexes for SARS-CoV-1 and ER homeostasis factors for SARS-CoV-2. Common nsp4 interactors include N-linked glycosylation machinery, unfolded protein response (UPR) associated proteins, and anti-viral innate immune signaling factors. Both nsp2 and nsp4 interactors are strongly enriched in proteins localized at mitochondrial-associated ER membranes suggesting a new functional role for modulating host processes, such as calcium homeostasis, at these organelle contact sites. Our results shed light on the role these hCoV proteins play in the infection cycle, as well as host factors that may mediate the divergent pathogenesis of OC43 from SARS strains. Our mass spectrometry workflow enables rapid and robust comparisons of multiple bait proteins, which can be applied to additional viral proteins. Furthermore, the identified common interactions may present new targets for exploration by host-directed anti-viral therapeutics.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Analysis Of Go-mentioning

confidence: 99%

Comparative multiplexed interactomics of SARS-CoV-2 and homologous coronavirus non-structural proteins identifies unique and shared host-cell dependencies

Davies

Almasy

McDonald

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…7-DHC is the direct precursor of free cholesterol and the substrate of 7-dehydrocholesterol reductase (DHCR7). Xiao et al (2020) found significantly increased DHCR7 expression in livers of hepatocellular carcinoma (HCC) patients with HBV infection. 7-DHC was also a biosynthesis precursor to vitamin D, thus increased DHCR7 promoted cholesterol synthesis while inhibited Vitamin D production (Prabhu et al, 2016).…”

Section: Hbv-induced Changes In Cholesterol Metabolismmentioning

confidence: 97%

Multifaceted Interaction Between Hepatitis B Virus Infection and Lipid Metabolism in Hepatocytes: A Potential Target of Antiviral Therapy for Chronic Hepatitis B

et al. 2021

View full text Add to dashboard Cite

Hepatitis B virus (HBV) is considered a “metabolic virus” and affects many hepatic metabolic pathways. However, how HBV affects lipid metabolism in hepatocytes remains uncertain yet. Accumulating clinical studies suggested that compared to non-HBV-infected controls, chronic HBV infection was associated with lower levels of serum total cholesterol and triglycerides and a lower prevalence of hepatic steatosis. In patients with chronic HBV infection, high ALT level, high body mass index, male gender, or old age was found to be positively correlated with hepatic steatosis. Furthermore, mechanisms of how HBV infection affected hepatic lipid metabolism had also been explored in a number of studies based on cell lines and mouse models. These results demonstrated that HBV replication or expression induced extensive and diverse changes in hepatic lipid metabolism, by not only activating expression of some critical lipogenesis and cholesterolgenesis-related proteins but also upregulating fatty acid oxidation and bile acid synthesis. Moreover, increasing studies found some potential targets to inhibit HBV replication or expression by decreasing or enhancing certain lipid metabolism-related proteins or metabolites. Therefore, in this article, we comprehensively reviewed these publications and revealed the connections between clinical observations and experimental findings to better understand the interaction between hepatic lipid metabolism and HBV infection. However, the available data are far from conclusive, and there is still a long way to go before clarifying the complex interaction between HBV infection and hepatic lipid metabolism.

show abstract

“…Furthermore, SC5D regulates the enzyme converting lathosterol to 7-Dehydrocholesterol. And the downstream gene DHCR7, which converts 7-Dehydrocholesterol to cholesterol, has been targeted by drugs inhibiting HBV infection (Xiao et al, 2020). Therefore, although the three genes are currently not targets of existing drugs, they are all related to the main-effect pathway cholesterol biosynthesis and important for tumorigenesis of HCC.…”

Section: Metabolic Genes In Cholesterol Biosynthesis Are Druggable Tamentioning

confidence: 99%

Mechanistic Modeling of Gene Regulation and Metabolism Identifies Potential Targets for Hepatocellular Carcinoma

et al. 2020

View full text Add to dashboard Cite

Hepatocellular carcinoma (HCC) is the predominant form of liver cancer and has long been among the top three cancers that cause the most deaths worldwide. Therapeutic options for HCC are limited due to the pronounced tumor heterogeneity. Thus, there is a critical need to study HCC from a systems point of view to discover effective therapeutic targets, such as through the systematic study of disease perturbation in both regulation and metabolism using a unified model. Such integration makes sense for cancers as it links one of the dominant physiological features of cancers (growth, which is driven by metabolic networks) with the primary available omics data source, transcriptomics (which is systematically integrated with metabolism through the regulatory-metabolic network model). Here, we developed an integrated transcriptional regulatory-metabolic model for HCC molecular stratification and the prediction of potential therapeutic targets. To predict transcription factors (TFs) and target genes affecting tumorigenesis, we used two algorithms to reconstruct the genome-scale transcriptional regulatory networks for HCC and normal liver tissue. which were then integrated with corresponding constraint-based metabolic models. Five key TFs affecting cancer cell growth were identified. They included the regulator CREB3L3, which has been associated with poor prognosis. Comprehensive personalized metabolic analysis based on models generated from data of liver HCC in The Cancer Genome Atlas revealed 18 genes essential for tumorigenesis in all three subtypes of patients stratified based on the non-negative matrix factorization method and two other genes (ACADSB and CMPK1) that have been strongly correlated with lower overall survival subtype. Among these 20 genes, 11 are targeted by approved drugs for cancers or cancer-related diseases, and six other genes have corresponding drugs being evaluated experimentally or investigationally. The remaining three genes represent potential targets. We also validated the stratification and prognosis results by an independent dataset of HCC cohort samples (LIRI-JP) from the International Cancer Genome Consortium database. In addition, microRNAs targeting key TFs and genes were also involved in established cancer-related pathways. Taken together, the multi-scale regulatory-metabolic model provided a new approach to assess key mechanisms of HCC cell proliferation in the context of systems and suggested potential targets.

show abstract

Targeting 7-Dehydrocholesterol Reductase Integrates Cholesterol Metabolism and IRF3 Activation to Eliminate Infection

Cited by 99 publications

References 51 publications

Comparative multiplexed interactomics of SARS-CoV-2 and homologous coronavirus non-structural proteins identifies unique and shared host-cell dependencies

Comparative multiplexed interactomics of SARS-CoV-2 and homologous coronavirus non-structural proteins identifies unique and shared host-cell dependencies

Multifaceted Interaction Between Hepatitis B Virus Infection and Lipid Metabolism in Hepatocytes: A Potential Target of Antiviral Therapy for Chronic Hepatitis B

Mechanistic Modeling of Gene Regulation and Metabolism Identifies Potential Targets for Hepatocellular Carcinoma

Contact Info

Product

Resources

About