Molecular mechanisms and cellular functions of liquid-liquid phase separation during antiviral immune responses.

Spatiotemporal separation of cellular components is vital to ensure biochemical processes. Membrane-bound organelles such as mitochondria and nuclei play a major role in isolating intracellular components, while membraneless organelles (MLOs) are accumulatively uncovered via liquid-liquid phase separation (LLPS) to mediate cellular spatiotemporal organization. MLOs orchestrate various key cellular processes, including protein localization, supramolecular assembly, gene expression, and signal transduction. During viral infection, LLPS not only participates in viral replication but also contributes to host antiviral immune responses. Therefore, a more comprehensive understanding of the roles of LLPS in virus infection may open up new avenues for treating viral infectious diseases. In this review, we focus on the antiviral defense mechanisms of LLPS in innate immunity and discuss the involvement of LLPS during viral replication and immune evasion escape, as well as the strategy of targeting LLPS to treat viral infectious diseases.

Phase-separated nucleocapsid protein of SARS-CoV-2 suppresses cGAS-DNA recognition by disrupting cGAS-G3BP1 complex.

Currently, the incidence and fatality rate of SARS-CoV-2 remain continually high worldwide. COVID-19 patients infected with SARS-CoV-2 exhibited decreased type I interferon (IFN-I) signal, along with limited activation of antiviral immune responses as well as enhanced viral infectivity. Dramatic progresses have been made in revealing the multiple strategies employed by SARS-CoV-2 in impairing canonical RNA sensing pathways. However, it remains to be determined about the SARS-CoV-2 antagonism of cGAS-mediated activation of IFN responses during infection. In the current study, we figure out that SARS-CoV-2 infection leads to the accumulation of released mitochondria DNA (mtDNA), which in turn triggers cGAS to activate IFN-I signaling. As countermeasures, SARS-CoV-2 nucleocapsid (N) protein restricts the DNA recognition capacity of cGAS to impair cGAS-induced IFN-I signaling. Mechanically, N protein disrupts the assembly of cGAS with its co-factor G3BP1 by undergoing DNA-induced liquid-liquid phase separation (LLPS), subsequently impairs the double-strand DNA (dsDNA) detection ability of cGAS. Taken together, our findings unravel a novel antagonistic strategy by which SARS-CoV-2 reduces DNA-triggered IFN-I pathway through interfering with cGAS-DNA phase separation.

Targeting Selective Autophagy as a Therapeutic Strategy for Viral Infectious Diseases.

Autophagy is an evolutionarily conserved lysosomal degradation system which can recycle multiple cytoplasmic components under both physiological and stressful conditions. Autophagy could be highly selective to deliver different cargoes or substrates, including protein aggregates, pathogenic proteins or superfluous organelles to lysosome using a series of cargo receptor proteins. During viral invasion, cargo receptors selectively target pathogenic components to autolysosome to defense against infection. However, viruses not only evolve different strategies to counteract and escape selective autophagy, but also utilize selective autophagy to restrict antiviral responses to expedite viral replication. Furthermore, several viruses could activate certain forms of selective autophagy, including mitophagy, lipophagy, aggrephagy, and ferritinophagy, for more effective infection and replication. The complicated relationship between selective autophagy and viral infection indicates that selective autophagy may provide potential therapeutic targets for human infectious diseases. In this review, we will summarize the recent progress on the interplay between selective autophagy and host antiviral defense, aiming to arouse the importance of modulating selective autophagy as future therapies toward viral infectious diseases.

Identification of serum metabolites enhancing inflammatory responses in COVID-19.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is characterized by a strong production of inflammatory cytokines such as TNF and IL-6, which underlie the severity of the disease. However, the molecular mechanisms responsible for such a strong immune response remains unclear. Here, utilizing targeted tandem mass spectrometry to analyze serum metabolome and lipidome in COVID-19 patients at different temporal stages, we identified that 611 metabolites (of 1,039) were significantly altered in COVID-19 patients. Among them, two metabolites, agmatine and putrescine, were prominently elevated in the serum of patients; and 2-quinolinecarboxylate was changed in a biphasic manner, elevated during early COVID-19 infection but levelled off. When tested in mouse embryonic fibroblasts (MEFs) and macrophages, these 3 metabolites were found to activate the NF-κB pathway that plays a pivotal role in governing cytokine production. Importantly, these metabolites were each able to cause strong increase of TNF and IL-6 levels when administered to wildtype mice, but not in the mice lacking NF-κB. Intriguingly, these metabolites have little effects on the activation of interferon regulatory factors (IRFs) for the production of type I interferons (IFNs) for antiviral defenses. These data suggest that circulating metabolites resulting from COVID-19 infection may act as effectors to elicit the peculiar systemic inflammatory responses, exhibiting severely strong proinflammatory cytokine production with limited induction of the interferons. Our study may provide a rationale for development of drugs to alleviate inflammation in COVID-19 patients.

Monitoring SARS-CoV-2 in air and on surfaces and estimating infection risk in buildings and buses on a university campus.

BACKGROUND: Evidence is needed on the presence of SARS-CoV-2 in various types of environmental samples and on the estimated transmission risks in non-healthcare settings on campus. OBJECTIVES: The objective of this research was to collect data on SARS-CoV-2 viral load and to examine potential infection risks of people exposed to the virus in publicly accessible non-healthcare environments on a university campus. METHODS: Air and surface samples were collected using wetted wall cyclone bioaerosol samplers and swab kits, respectively, in a longitudinal environmental surveillance program from August 2020 until April 2021 on the University of Michigan Ann Arbor campus. Quantitative rRT-PCR with primers and probes targeting gene N1 were used for SARS-CoV-2 RNA quantification. The RNA concentrations were used to estimate the probability of infection by quantitative microbial risk assessment modeling and Monte-Carlo simulation. RESULTS: In total, 256 air samples and 517 surface samples were collected during the study period, among which positive rates were 1.6% and 1.4%, respectively. Point-biserial correlation showed that the total case number on campus was significantly higher in weeks with positive environmental samples than in non-positive weeks (p = 0.001). The estimated probability of infection was about 1 per 100 exposures to SARS-CoV-2-laden aerosols through inhalation and as high as 1 per 100,000 exposures from contacting contaminated surfaces in simulated scenarios. SIGNIFICANCE: Viral shedding was demonstrated by the detection of viral RNA in multiple air and surface samples on a university campus. The low overall positivity rate indicated that the risk of exposure to SARS-CoV-2 at monitored locations was low. Risk modeling results suggest that inhalation is the predominant route of exposure compared to surface contact, which emphasizes the importance of protecting individuals from airborne transmission of SARS-CoV-2 and potentially other respiratory infectious diseases. IMPACT: Given the reoccurring epidemics caused by highly infectious respiratory viruses in recent years, our manuscript reinforces the importance of monitoring environmental transmission by the simultaneous sampling and integration of multiple environmental surveillance matrices for modeling and risk assessment.

Systemic Corticosteroids and Mortality in Severe and Critical COVID-19 Patients in Wuhan, China.

BACKGROUND: Systemic corticosteroids are now recommended in many treatment guidelines, although supporting evidence is limited to 1 randomized controlled clinical trial (RECOVERY). OBJECTIVE: To identify whether corticosteroids were beneficial to COVID-19 patients. METHODS: A total of 1514 severe and 249 critical hospitalized COVID-19 patients from 2 medical centers in Wuhan, China. Multivariable Cox models, Cox model with time-varying exposure and propensity score analysis (inverse-probability-of-treatment-weighting [IPTW] and propensity score matching [PSM]) were used to estimate the association of corticosteroid use with risk of in-hospital mortality in severe and critical cases. RESULTS: Corticosteroids were administered in 531 (35.1%) severe and 159 (63.9%) critical patients. Compared to the non-corticosteroid group, systemic corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality in either severe cases (HR = 1.77; 95% CI, 1.08-2.89; P = 0.023), or critical cases (HR = 2.07; 95% CI, 1.08-3.98; P = 0.028). Findings were similar in time-varying Cox analysis. For patients with severe COVID-19 at admission, corticosteroid use was not associated with improved or harmful outcome in either PSM or IPTW analysis. For critical COVID-19 patients at admission, results were consistent with multivariable Cox model analysis. CONCLUSION: Corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality for severe or critical cases in Wuhan. Absence of the beneficial effect in our study in contrast to that observed in the RECOVERY clinical trial may be due to biases in observational data, in particular prescription by indication bias, differences in clinical characteristics of patients, choice of corticosteroid used, timing of initiation of treatment, and duration of treatment.

Elevation of blood glucose level predicts worse outcomes in hospitalized patients with COVID-19: a retrospective cohort study.

INTRODUCTION: With intense deficiency of medical resources during COVID-19 pandemic, risk stratification is of strategic importance. Blood glucose level is an important risk factor for the prognosis of infection and critically ill patients. We aimed to investigate the prognostic value of blood glucose level in patients with COVID-19. RESEARCH DESIGN AND METHODS: We collected clinical and survival information of 2041 consecutive hospitalized patients with COVID-19 from two medical centers in Wuhan. Patients without available blood glucose level were excluded. We performed multivariable Cox regression to calculate HRs of blood glucose-associated indexes for the risk of progression to critical cases/mortality among non-critical cases, as well as in-hospital mortality in critical cases. Sensitivity analysis were conducted in patient without diabetes. RESULTS: Elevation of admission blood glucose level was an independent risk factor for progression to critical cases/death among non-critical cases (HR=1.30, 95% CI 1.03 to 1.63, p=0.026). Elevation of initial blood glucose level of critical diagnosis was an independent risk factor for in-hospital mortality in critical cases (HR=1.84, 95% CI 1.14 to 2.98, p=0.013). Higher median glucose level during hospital stay or after critical diagnosis (≥6.1 mmol/L) was independently associated with increased risks of progression to critical cases/death among non-critical cases, as well as in-hospital mortality in critical cases. Above results were consistent in the sensitivity analysis in patients without diabetes. CONCLUSIONS: Elevation of blood glucose level predicted worse outcomes in hospitalized patients with COVID-19. Our findings may provide a simple and practical way to risk stratify COVID-19 inpatients for hierarchical management, particularly where medical resources are in severe shortage during the pandemic.