SFTSV Infection Induced Interleukin-1β Secretion Through NLRP3 Inflammasome Activation

Liu, Jianwei; Chu, Min; Jiao, Yongjun; Zhou, Chunkui; Qi, Rui; Yu, Xue-Jie

doi:10.3389/fimmu.2021.595140

Cited by 9 publications

(7 citation statements)

References 44 publications

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“…The adult wildtype mice have been used in researches on targeting of SFTSV infection, evaluation of safety and efficacy of candidate vaccines and therapeutics, and transmission modes of SFTSV ( Figure 2 ). For instance, by using the C57BL/6 mouse model, researchers found that SFTSV stimulated production and secretion of pro-inflammatory cytokine Interleukin (IL)-1β and further confirmed that the NLRP3 (NLR family, pyrin domain containing 3) inflammasome complex acted as an essential mediator in the process ( Liu et al, 2021 ). Several vaccine candidates based on viral vectors, expression plasmids, or the viral protein (NSs) have been evaluated in wildtype C57BL/6 or BALB/c mice ( Jung et al, 2017 ; Zhao et al, 2020 ; Tian et al, 2021 ).…”

Section: Animal Models For Severe Fever With Thrombocytopenia Syndrome Virusmentioning

confidence: 93%

Animal Model of Severe Fever With Thrombocytopenia Syndrome Virus Infection

Sun

Min

et al. 2022

Front. Microbiol.

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Severe fever with thrombocytopenia syndrome (SFTS), an emerging life-threatening infectious disease caused by SFTS bunyavirus (SFTSV; genus Bandavirus, family Phenuiviridae, order Bunyavirales), has been a significant medical problem. Currently, there are no licensed vaccines or specific therapeutic agents available and the viral pathogenesis remains largely unclear. Developing appropriate animal models capable of recapitulating SFTSV infection in humans is crucial for both the study of the viral pathogenic processes and the development of treatment and prevention strategies. Here, we review the current progress in animal models for SFTSV infection by summarizing susceptibility of various potential animal models to SFTSV challenge and the clinical manifestations and histopathological changes in these models. Together with exemplification of studies on SFTSV molecular mechanisms, vaccine candidates, and antiviral drugs, in which animal infection models are utilized, the strengths and limitations of the existing SFTSV animal models and some important directions for future research are also discussed. Further exploration and optimization of SFTSV animal models and the corresponding experimental methods will be undoubtedly valuable for elucidating the viral infection and pathogenesis and evaluating vaccines and antiviral therapies.

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Section: Animal Models For Severe Fever With Thrombocytopenia Syndrome Virusmentioning

confidence: 93%

Animal Model of Severe Fever With Thrombocytopenia Syndrome Virus Infection

Sun

Min

et al. 2022

Front. Microbiol.

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“…IL-1β recruits immune cells and causes the programmed death of cells by binding to IL-1R-expressing immune cells. Liu et al first reported that the secretion of IL-1β during SFTSV infection is mediated by the NOd-, LRR-and pyrin domain-containing protein 3 (NLRP3) inflammasome in a caspase-1-dependent manner (110). The use of short hairpin RNAs to knock down several NLRs in peripheral blood mononuclear cells revealed that the NLRP3 inflammasome is essential for the processing of pro-caspase-1 and pro-IL-1β (111).…”

Section: Innate Immunity In Sftsmentioning

confidence: 99%

Overview of the immunological mechanism underlying severe fever with thrombocytopenia syndrome (Review)

et al. 2022

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Severe fever with thrombocytopenia syndrome (SFTS) has been acknowledged as an emerging infectious disease that is caused by the SFTS virus (SFTSV). The main clinical features of SFTS on presentation include fever, thrombocytopenia, leukocytopenia and gastrointestinal symptoms. The mortality rate is estimated to range between 5-30% in East Asia. However, SFTSV infection is increasing on an annual basis globally and is becoming a public health problem. The transmission cycle of SFTSV remains poorly understood, which is compounded by the pathogenesis of SFTS not being fully elucidated. Since the mechanism underlying the host immune response towards SFTSV is also unclear, there are no effective vaccines or specific therapeutic agents against SFTS, with supportive care being the only realistic option. Therefore, it is now crucial to understand all aspects of the host-virus interaction following SFTSV infection, including the antiviral states and viral evasion mechanisms. In the present review, recent research progress into the possible host immune responses against SFTSV was summarized, which may be useful in designing novel therapeutics against SFTS.

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“…Cholesterol synthesis pathways regulated by site 1 protease (S1P) are required for efficient replications of SFTSV [ 24 ]. NLRP3 inflammasome activation in SFTSV infection may be stimulated by calcium influx or potassium efflux [ 25 ]. Our previous study also identified that patients with cough, wheezing dyspnea in encephalitis group are significantly higher at clinical manifestations, than those in nonencephalitis group [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

A Reservoir Computing with Boosted Topology Model to Predict Encephalitis and Mortality for Patients with Severe Fever with Thrombocytopenia Syndrome: A Retrospective Multicenter Study

Zheng

Geng

et al. 2023

Infect Dis Ther

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Introduction Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging tick-borne virus associated with a high rate of mortality, as well as encephalitis. We aim to develop and validate a machine learning model to early predict the potential life-threatening conditions of SFTS. Methods The clinical presentation, demographic information, and laboratory parameters from 327 patients with SFTS at admission in three large tertiary hospitals in Jiangsu, China between 2010 to 2022 are retrieved. We establish a reservoir computing with boosted topology (RC–BT) algorithm to obtain the models’ predictions of the encephalitis and mortality of patients with SFTS. The prediction performances of encephalitis and mortality are further tested and validated. Finally, we compare our RC–BT model with the other traditional machine learning algorithms including Lightgbm, support vector machine (SVM), Xgboost, Decision Tree, and Neural Network (NN). Results For the prediction of encephalitis among patients with SFTS, nine parameters are selected with equal weight, namely calcium, cholesterol, muscle soreness, dry cough, smoking history, temperature at admission, troponin T, potassium, and thermal peak. The accuracy for the validation cohort by the RC–BT model is 0.897 [95% confidence interval (CI) 0.873–0.921]. The sensitivity and negative predictive value (NPV) of the RC–BT model are 0.855 (95% CI 0.824–0.886) and 0.904 (95% CI 0.863–0.945), respectively. Area under curve of the RC–BT model for the validation cohort is 0.899 (95% CI 0.882–0.916). For the prediction of fatality among patients with SFTS, seven parameters are selected with equal weight, namely calcium, cholesterol, history of drinking, headache, field contact, potassium, and dyspnea. The accuracy of the RC–BT model is 0.903 (95% CI 0.881–0.925). The sensitivity and NPV of the RC–BT model are 0.913 (95% CI 0.902–0.924) and 0.946 (95% CI 0.917–0.975), respectively. The area under curve is 0.917 (95% CI 0.902–0.932). Importantly, the RC–BT models outperform the other artificial intelligence-based algorithms in both prediction tasks. Conclusions Our two RC–BT models of SFTS encephalitis and fatality demonstrate high area under curves, specificity, and NPV, with nine and seven routine clinical parameters, respectively. Our models can not only greatly improve the early prognosis accuracy of SFTS, but can also be widely applied in underdeveloped areas with limited medical resources. Supplementary Information The online version contains supplementary material available at 10.1007/s40121-023-00808-y.

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SFTSV Infection Induced Interleukin-1β Secretion Through NLRP3 Inflammasome Activation

Cited by 9 publications

References 44 publications

Animal Model of Severe Fever With Thrombocytopenia Syndrome Virus Infection

Animal Model of Severe Fever With Thrombocytopenia Syndrome Virus Infection

Overview of the immunological mechanism underlying severe fever with thrombocytopenia syndrome (Review)

A Reservoir Computing with Boosted Topology Model to Predict Encephalitis and Mortality for Patients with Severe Fever with Thrombocytopenia Syndrome: A Retrospective Multicenter Study

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