Intracellular life cycle kinetics of SARS-CoV-2 predicted using mathematical modelling

SARS-CoV-2 infection represents a global threat to human health. Various approaches were employed to reveal the pathogenetic mechanisms of COVID-19. Mathematical and computational modelling is a powerful tool to describe and analyze the infection dynamics in relation to a plethora of processes contributing to the observed disease phenotypes. In our study here, we formulate and calibrate a deterministic model of the SARS-CoV-2 life cycle. It provides a kinetic description of the major replication stages of SARS-CoV-2. Sensitivity analysis of the net viral progeny with respect to model parameters enables the identification of the life cycle stages that have the strongest impact on viral replication. These three most influential parameters are (i) degradation rate of positive sense vRNAs in cytoplasm (negative effect), (ii) threshold number of non-structural proteins enhancing vRNA transcription (negative effect), and (iii) translation rate of non-structural proteins (positive effect). The results of our analysis could be used for guiding the search for antiviral drug targets to combat SARS-CoV-2 infection.The reported study was funded by RFBR according to the research project numbers 20-04-60157 and 20-01-00352. AM is also supported by the Spanish Ministry of Science and Innovation grant no. PID2019-106323RB-I00(AEI/MINEICO/FEDER, UE), and “Unidad de Excelencia María de Maeztu”, funded by the AEI (CEX2018-000792-M). G.B. and D.G. were partly supported by Moscow Center for Fundamental and Applied Mathematics (agreement with the Ministry of Education and Science of the Russian Federation No. 075-15-2019-1624)

Predicting the kinetic coordination of immune response dynamics in SARS-CoV-2 infection: implications for disease pathogenesis

A calibrated mathematical model of antiviral immune response to SARS-CoV-2 infection is developed. The model considers the innate and antigen-specific responses to SARS-CoV-2 infection. Recently published data sets from human challenge studies with SARS-CoV-2 were used for parameter evaluation. The calibration of the mathematical model of SARS-CoV-2 infection is based on combining the parameter guesses from our earlier study of influenza A virus infection, some recent quantitative models of SARS-CoV-2 infection and clinical data-based parameter estimation of a subset of the model parameters. Hence, the calibrated mathematical model represents a theoretical exploration type of study, i.e., ‘in silico patient’ with mild-to-moderate severity phenotype, rather than a completely validated quantitative model of COVID-19 with respect to all its state-space variables. Understanding the regulation of multiple intertwined reaction components of the immune system is necessary for linking the kinetics of immune responses with the clinical phenotypes of COVID-19. Consideration of multiple immune reaction components in a single calibrated mathematical model allowed us to address some fundamental issues related to the pathogenesis of COVID-19, i.e., the sensitivity of the peak viral load to the parameters characterizing the antiviral specific response components, the kinetic coordination of the individual innate and adaptive immune responses, and the factors favoring a prolonged viral persistence. The model provides a tool for predicting the infectivity of patients, i.e., the amount of virus which is transmitted via droplets from the person infected with SARS-CoV-2, depending on the time of infection. The thresholds for variations of the innate and adaptive response parameters which lead to a prolonged persistence of SARS-CoV-2 due to the loss of a kinetic response synchrony/coordination between them were identified.The reported study was funded by RFBR according to the research projects number 20-04-60157 and 20-01-00352. AM is also supported by the Spanish Ministry of Science and Innovation grant no. PID2019-106323RB-I00 AEI//10.13039/501100011033 and the Unidad de Excelencia María de Maeztu (AEI CEX2018-000792-M)

Past, presence, and future of allergen immunotherapy vaccines

Allergen-specific immunotherapy (AIT) is an allergen-specific form of treatment for patients suffering from immunoglobulin E (IgE)-associated allergy; the most common and important immunologically mediated hypersensitivity disease. AIT is based on the administration of the disease-causing allergen with the goal to induce a protective immunity consisting of allergen-specific blocking IgG antibodies and alterations of the cellular immune response so that the patient can tolerate allergen contact. Major advantages of AIT over all other existing treatments for allergy are that AIT induces a long-lasting protection and prevents the progression of disease to severe manifestations. AIT is cost effective because it uses the patient´s own immune system for protection and potentially can be used as a preventive treatment. However, broad application of AIT is limited by mainly technical issues such as the quality of allergen preparations and the risk of inducing side effects which results in extremely cumbersome treatment schedules reducing patient´s compliance. In this article we review progress in AIT made from its beginning and provide an overview of the state of the art, the needs for further development, and possible technical solutions available through molecular allergology. Finally, we consider visions for AIT development towards prophylactic application. © 2020 The Authors. Allergy published by European Academy of Allergy and Clinical Immunology and John Wiley & Sons Lt

Molecular Allergen-Specific IgE Recognition Profiles and Cumulative Specific IgE Levels Associated with Phenotypes of Cat Allergy

Cat allergy is a major trigger factor for respiratory reactions (asthma and rhinitis) in patients with immunoglobulin E (IgE) sensitization. In this study, we used a comprehensive panel of purified cat allergen molecules (rFel d 1, nFel d 2, rFel d 3, rFel d 4, rFel d 7, and rFel d 8) that were obtained by recombinant expression in Escherichia coli or by purification as natural proteins to study possible associations with different phenotypes of cat allergy (i.e., rhinitis, conjunctivitis, asthma, and dermatitis) by analyzing molecular IgE recognition profiles in a representative cohort of clinically well-characterized adult cat allergic subjects (n = 84). IgE levels specific to each of the allergen molecules and to natural cat allergen extract were quantified by ImmunoCAP measurements. Cumulative IgE levels specific to the cat allergen molecules correlated significantly with IgE levels specific to the cat allergen extract, indicating that the panel of allergen molecules resembled IgE epitopes of the natural allergen source. rFel d 1 represented the major cat allergen, which was recognized by 97.2% of cat allergic patients; however, rFel d 3, rFel d 4, and rFel d 7 each showed IgE reactivity in more than 50% of cat allergic patients, indicating the importance of additional allergens in cat allergy. Patients with cat-related skin symptoms showed a trend toward higher IgE levels and/or frequencies of sensitization to each of the tested allergen molecules compared with patients suffering only from rhinitis or asthma, while there were no such differences between patients with rhinitis and asthma. The IgE levels specific to allergen molecules, the IgE levels specific to cat allergen extract, and the IgE levels specific to rFel d 1 were significantly higher in patients with four different symptoms compared with patients with 1–2 symptoms. This difference was more pronounced for the sum of IgE levels specific to the allergen molecules and to cat extract than for IgE levels specific for rFel d 1 alone. Our study indicates that, in addition to rFel d 1, rFel d 3, rFel d 4, and rFel d 7 must be considered as important cat allergens. Furthermore, the cumulative sum of IgE levels specific to cat allergen molecules seems to be a biomarker for identifying patients with complex phenotypes of cat allergy. These findings are important for the diagnosis of IgE sensitization to cats and for the design of allergen-specific immunotherapies for the treatment and prevention of cat allergy

Toward personalization of asthma treatment according to trigger factors

Asthma is a severe and chronic disabling disease affecting more than 300 million people worldwide. Although in the past few drugs for the treatment of asthma were available, new treatment options are currently emerging, which appear to be highly effective in certain subgroups of patients. Accordingly, there is a need for biomarkers that allow selection of patients for refined and personalized treatment strategies. Recently, serological chip tests based on microarrayed allergen molecules and peptides derived from the most common rhinovirus strains have been developed, which may discriminate 2 of the most common forms of asthma, that is, allergen- and virus-triggered asthma. In this perspective, we argue that classification of patients with asthma according to these common trigger factors may open new possibilities for personalized management of asthma. © 2020 The Author