1
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Forouzani‐Moghaddam MJ, Habibi S, Hosseini‐Safa A, Khanaliha K, Mokarinejad R, Akhoundzadeh F, Oshaghi M. Rapid detection of major enterotoxin genes and antibiotic resistance of Staphylococcus aureus isolated from raw milk in the Yazd province, Iran. Vet Med Sci 2024; 10:e1407. [PMID: 38519836 PMCID: PMC10959825 DOI: 10.1002/vms3.1407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 01/22/2024] [Accepted: 02/19/2024] [Indexed: 03/25/2024] Open
Abstract
INTRODUCTION Raw milk is a nutrient-rich food, but it may harbour harmful bacteria, such as enterotoxigenic Staphylococcus aureus (S. aureus), which can cause staphylococcal food poisoning. Antibiotic resistance of S. aureus in raw milk can increase the risk of such infections, particularly among susceptible individuals. OBJECTIVE This study aimed to investigate the prevalence of enterotoxin genes a, d, g, i and j and the antibiotic resistance of S. aureus isolated from raw milk samples. METHODS During a 6-month sampling period, 60 raw milk specimens were obtained from diverse locations in Yazd province, Iran. Antibiogram profiling was conducted via the disc diffusion method. In addition, staphylococcal enterotoxin (SE) genes a, d, g, i, and j were detected through real-time PCR analysis. RESULTS Bacteriological assays confirmed the presence of S. aureus in 11 samples (18.3%). All isolates demonstrated 100% resistance to penicillin G but exhibited sensitivity to vancomycin, while resistance to other antibiotics ranged from 36.4% to 45.5%. The prevalence of enterotoxin genes in these strains showed variable distribution, with sea being the predominant SE (45.5%), followed by sed (36.4%), seg (18.2), sej and sei (9.1% each). CONCLUSIONS This study discovered the presence of multiple enterotoxins in S. aureus strains obtained from raw milk samples. These strains also demonstrated resistance to a variety of antibiotics. Since enterotoxigenic S. aureus is known to cause human food poisoning, monitoring food hygiene practices, especially during raw milk production, is critical.
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Affiliation(s)
| | - Sina Habibi
- Department of Medical Laboratory SciencesFaculty of Allied MedicineIran University of Medical SciencesTehranIran
- Department of Hematology and Blood Banking, Faculty of Allied MedicineIran University of Medical SciencesTehranIran
| | - Ahmad Hosseini‐Safa
- Department of Medical Laboratory SciencesFaculty of Allied MedicineIran University of Medical SciencesTehranIran
| | - Khadijeh Khanaliha
- Research Center of Pediatric Infectious DiseasesInstitute of Immunology and Infectious DiseasesIran University of Medical SciencesTehranIran
| | - Roya Mokarinejad
- Department of Medical Laboratory SciencesFaculty of Allied MedicineIran University of Medical SciencesTehranIran
| | - Fatemeh Akhoundzadeh
- Department of Medical Laboratory SciencesFaculty of Allied MedicineIran University of Medical SciencesTehranIran
| | - Mojgan Oshaghi
- Department of Medical Laboratory SciencesFaculty of Allied MedicineIran University of Medical SciencesTehranIran
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2
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Burkart SS, Schweinoch D, Frankish J, Sparn C, Wüst S, Urban C, Merlo M, Magalhães VG, Piras A, Pichlmair A, Willemsen J, Kaderali L, Binder M. High-resolution kinetic characterization of the RIG-I-signaling pathway and the antiviral response. Life Sci Alliance 2023; 6:e202302059. [PMID: 37558422 PMCID: PMC10412806 DOI: 10.26508/lsa.202302059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 07/24/2023] [Accepted: 07/27/2023] [Indexed: 08/11/2023] Open
Abstract
RIG-I recognizes viral dsRNA and activates a cell-autonomous antiviral response. Upon stimulation, it triggers a signaling cascade leading to the production of type I and III IFNs. IFNs are secreted and signal to elicit the expression of IFN-stimulated genes, establishing an antiviral state of the cell. The topology of this pathway has been studied intensively, however, its exact dynamics are less understood. Here, we employed electroporation to synchronously activate RIG-I, enabling us to characterize cell-intrinsic innate immune signaling at a high temporal resolution. Employing IFNAR1/IFNLR-deficient cells, we could differentiate primary RIG-I signaling from secondary signaling downstream of the IFN receptors. Based on these data, we developed a comprehensive mathematical model capable of simulating signaling downstream of dsRNA recognition by RIG-I and the feedback and signal amplification by IFN. We further investigated the impact of viral antagonists on signaling dynamics. Our work provides a comprehensive insight into the signaling events that occur early upon virus infection and opens new avenues to study and disentangle the complexity of the host-virus interface.
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Affiliation(s)
- Sandy S Burkart
- Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response", Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Darius Schweinoch
- Institute of Bioinformatics & Center for Functional Genomics of Microbes, University Medicine Greifswald, Greifswald, Germany
| | - Jamie Frankish
- Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response", Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Carola Sparn
- Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response", Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Sandra Wüst
- Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response", Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center, Heidelberg, Germany
| | - Christian Urban
- Technical University of Munich, School of Medicine, Institute of Virology, Munich, Germany
| | - Marta Merlo
- Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response", Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center, Heidelberg, Germany
- Faculty of Biosciences, Heidelberg University, Heidelberg, Germany
| | - Vladimir G Magalhães
- Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response", Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center, Heidelberg, Germany
| | - Antonio Piras
- Technical University of Munich, School of Medicine, Institute of Virology, Munich, Germany
| | - Andreas Pichlmair
- Technical University of Munich, School of Medicine, Institute of Virology, Munich, Germany
- German Center for Infection Research (DZIF), Munich Partner Site, Munich, Germany
| | - Joschka Willemsen
- Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response", Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center, Heidelberg, Germany
| | - Lars Kaderali
- Institute of Bioinformatics & Center for Functional Genomics of Microbes, University Medicine Greifswald, Greifswald, Germany
| | - Marco Binder
- Research Group "Dynamics of Early Viral Infection and the Innate Antiviral Response", Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center, Heidelberg, Germany
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3
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Adam L, Stanifer M, Springer F, Mathony J, Brune M, Di Ponzio C, Eils R, Boulant S, Niopek D, Kallenberger SM. Transcriptomics-inferred dynamics of SARS-CoV-2 interactions with host epithelial cells. Sci Signal 2023; 16:eabl8266. [PMID: 37751479 DOI: 10.1126/scisignal.abl8266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2021] [Accepted: 09/06/2023] [Indexed: 09/28/2023]
Abstract
Virus-host interactions can reveal potentially effective and selective therapeutic targets for treating infection. Here, we performed an integrated analysis of the dynamics of virus replication and the host cell transcriptional response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection using human Caco-2 colon cancer cells as a model. Time-resolved RNA sequencing revealed that, upon infection, cells immediately transcriptionally activated genes associated with inflammatory pathways that mediate the antiviral response, which was followed by an increase in the expression of genes involved in ribosome and mitochondria function, thus suggesting rapid alterations in protein production and cellular energy supply. At later stages, between 24 and 48 hours after infection, the expression of genes involved in metabolic processes-in particular, those related to xenobiotic metabolism-was decreased. Mathematical modeling incorporating SARS-CoV-2 replication suggested that SARS-CoV-2 proteins inhibited the host antiviral response and that virus transcripts exceeded the translation capacity of the host cells. Targeting kinase-dependent pathways that exhibited increases in transcription in host cells was as effective as a virus-targeted inhibitor at repressing viral replication. Our findings in this model system delineate a sequence of SARS-CoV-2 virus-host interactions that may facilitate the identification of druggable host pathways to suppress infection.
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Affiliation(s)
- Lukas Adam
- Health Data Science Unit, University Hospital Heidelberg and Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg 69120, Germany
| | - Megan Stanifer
- Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg 69120, Germany
- Department of Molecular Genetics & Microbiology, College of Medicine, University of Florida, Gainesville, FL 32603, USA
| | - Fabian Springer
- Health Data Science Unit, University Hospital Heidelberg and Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg 69120, Germany
| | - Jan Mathony
- Department of Biology, Technical University of Darmstadt, Darmstadt 64287, Germany
- Center for Synthetic Biology, Technical University of Darmstadt, Darmstadt 64287, Germany
- BZH Graduate School, Heidelberg University, Heidelberg 69120, Germany
- Institute of Pharmacy and Molecular Biotechnology (IPMB), Faculty of Engineering Sciences, Heidelberg University, Heidelberg 69120, Germany
| | - Maik Brune
- Clinic of Endocrinology, Diabetology, Metabolism, and Clinical Chemistry, Central Laboratory, Heidelberg University Hospital, Heidelberg 69120, Germany
| | - Chiara Di Ponzio
- Health Data Science Unit, University Hospital Heidelberg and Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg 69120, Germany
- Digital Health Center, Berlin Institute of Health (BIH) and Charité, Berlin 10178, Germany
| | - Roland Eils
- Health Data Science Unit, University Hospital Heidelberg and Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg 69120, Germany
- Digital Health Center, Berlin Institute of Health (BIH) and Charité, Berlin 10178, Germany
| | - Steeve Boulant
- Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg 69120, Germany
- Department of Molecular Genetics & Microbiology, College of Medicine, University of Florida, Gainesville, FL 32603, USA
- Research Group "Cellular polarity and viral infection" (F140), German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
| | - Dominik Niopek
- Department of Biology, Technical University of Darmstadt, Darmstadt 64287, Germany
- Center for Synthetic Biology, Technical University of Darmstadt, Darmstadt 64287, Germany
- Institute of Pharmacy and Molecular Biotechnology (IPMB), Faculty of Engineering Sciences, Heidelberg University, Heidelberg 69120, Germany
| | - Stefan M Kallenberger
- Health Data Science Unit, University Hospital Heidelberg and Center for Quantitative Analysis of Molecular and Cellular Biosystems (BioQuant), University of Heidelberg, Heidelberg 69120, Germany
- Division of Applied Bioinformatics (G200), German Cancer Research Center (DKFZ), Heidelberg 69120, Germany
- National Center for Tumor Diseases, Department of Medical Oncology, Heidelberg University Hospital, Heidelberg 69120, Germany
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4
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Hauber AL, Rosenblatt M, Timmer J. Uncovering specific mechanisms across cell types in dynamical models. PLoS Comput Biol 2023; 19:e1010867. [PMID: 37703301 PMCID: PMC10519600 DOI: 10.1371/journal.pcbi.1010867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 09/25/2023] [Accepted: 08/14/2023] [Indexed: 09/15/2023] Open
Abstract
Ordinary differential equations are frequently employed for mathematical modeling of biological systems. The identification of mechanisms that are specific to certain cell types is crucial for building useful models and to gain insights into the underlying biological processes. Regularization techniques have been proposed and applied to identify mechanisms specific to two cell types, e.g., healthy and cancer cells, including the LASSO (least absolute shrinkage and selection operator). However, when analyzing more than two cell types, these approaches are not consistent, and require the selection of a reference cell type, which can affect the results. To make the regularization approach applicable to identifying cell-type specific mechanisms in any number of cell types, we propose to incorporate the clustered LASSO into the framework of ordinary differential equation modeling by penalizing the pairwise differences of the logarithmized fold-change parameters encoding a specific mechanism in different cell types. The symmetry introduced by this approach renders the results independent of the reference cell type. We discuss the necessary adaptations of state-of-the-art numerical optimization techniques and the process of model selection for this method. We assess the performance with realistic biological models and synthetic data, and demonstrate that it outperforms existing approaches. Finally, we also exemplify its application to published biological models including experimental data, and link the results to independent biological measurements.
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Affiliation(s)
- Adrian L. Hauber
- Institute of Physics, University of Freiburg, Freiburg, Germany
- Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany
- Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany
| | - Marcus Rosenblatt
- Institute of Physics, University of Freiburg, Freiburg, Germany
- Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany
| | - Jens Timmer
- Institute of Physics, University of Freiburg, Freiburg, Germany
- Freiburg Center for Data Analysis and Modeling, University of Freiburg, Freiburg, Germany
- Centre for Integrative Biological Signalling Studies, University of Freiburg, Freiburg, Germany
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5
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Muthu P, Modak B. Within-host models of dengue virus transmission with immune response. COMPUTATIONAL AND MATHEMATICAL BIOPHYSICS 2023; 11. [DOI: 10.1515/cmb-2022-0150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023] Open
Abstract
Abstract
Dengue fever is an infectious viral fever. The complex behavior of the virus within the body can be explained through mathematical models to understand the virus’s dynamics. We propose two different with-in host models of dengue virus transmission with humoral immune response. The proposed models differ from one another because one of the models assumes that newly formed viruses infect healthy cells again. To understand the dynamics of the proposed models, we perform a comparative study of stability analysis, numerical simulation, and sensitivity analysis. The basic reproduction number (BRN) of the two models is computed using next-generation matrix method. The local stability (l.s) analysis is discussed using the linearization method. The Lyapunov’s direct method is used to check the global stability (g.s) of the models. It has been found that both the equilibrium states for both the models, namely, virus-free equilibrium state and endemic equilibrium state, are globally stable, based on the value of BRN. Results show the influence of immune response on the cell dynamics and virus particles. The virus neutralization rate by antibodies and rate that affects the antibody growth are highly sensitive for the two models. Optimal control is applied to explore the possible control strategies to prevent virus spread in the host system. It is evident from the results that the strategy to administrate antibiotic drugs and home remedies slow down the virus spread in the host.
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Affiliation(s)
- Poosan Muthu
- Department of Mathematics, National Institute of Technology, Warangal - 506004 , Telangana , India
| | - Bikash Modak
- Department of Mathematics, National Institute of Technology, Warangal - 506004 , Telangana , India
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6
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Amoddeo A. A mathematical model and numerical simulation for SARS-CoV-2 dynamics. Sci Rep 2023; 13:4575. [PMID: 36941368 PMCID: PMC10027279 DOI: 10.1038/s41598-023-31733-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 03/16/2023] [Indexed: 03/23/2023] Open
Abstract
Since its outbreak the corona virus-19 disease has been particularly aggressive for the lower respiratory tract, and lungs in particular. The dynamics of the abnormal immune response leading to lung damage with fatal outcomes is not yet fully understood. We present a mathematical model describing the dynamics of corona virus disease-19 starting from virus seeding inside the human respiratory tract, taking into account its interaction with the components of the innate immune system as classically and alternatively activated macrophages, interleukin-6 and -10. The numerical simulations have been performed for two different parameter values related to the pro-inflammatory interleukin, searching for a correlation among components dynamics during the early stage of infection, in particular pro- and anti-inflammatory polarizations of the immune response. We found that in the initial stage of infection the immune machinery is unable to stop or weaken the virus progression. Also an abnormal anti-inflammatory interleukin response is predicted, induced by the disease progression and clinically associated to tissue damages. The numerical results well reproduce experimental results found in literature.
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Affiliation(s)
- Antonino Amoddeo
- Department of Civil, Energy, Environment and Materials Engineering, Università 'Mediterranea' di Reggio Calabria, Via Graziella 1, Feo di Vito, 89122, Reggio Calabria, Italy.
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7
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Canova CT, Inguva PK, Braatz RD. Mechanistic modeling of viral particle production. Biotechnol Bioeng 2023; 120:629-641. [PMID: 36461898 DOI: 10.1002/bit.28296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 11/29/2022] [Accepted: 11/30/2022] [Indexed: 12/05/2022]
Abstract
Viral systems such as wild-type viruses, viral vectors, and virus-like particles are essential components of modern biotechnology and medicine. Despite their importance, the commercial-scale production of viral systems remains highly inefficient for multiple reasons. Computational strategies are a promising avenue for improving process development, optimization, and control, but require a mathematical description of the system. This article reviews mechanistic modeling strategies for the production of viral particles, both at the cellular and bioreactor scales. In many cases, techniques and models from adjacent fields such as epidemiology and wild-type viral infection kinetics can be adapted to construct a suitable process model. These process models can then be employed for various purposes such as in-silico testing of novel process operating strategies and/or advanced process control.
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Affiliation(s)
- Christopher T Canova
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Pavan K Inguva
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Richard D Braatz
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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8
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Zerfu B, Kassa T, Legesse M. Epidemiology, biology, pathogenesis, clinical manifestations, and diagnosis of dengue virus infection, and its trend in Ethiopia: a comprehensive literature review. Trop Med Health 2023; 51:11. [PMID: 36829222 PMCID: PMC9950709 DOI: 10.1186/s41182-023-00504-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/15/2023] [Indexed: 02/26/2023] Open
Abstract
Dengue fever is a dengue virus infection, emerging rapidly and posing public health threat worldwide, primarily in tropical and subtropical countries. Nearly half of the world's population is now at risk of contracting the dengue virus, including new countries with no previous history-like Ethiopia. However, little is known about the epidemiology and impact of the disease in different countries. This is especially true in countries, where cases have recently begun to be reported. This review aims to summarize epidemiology, biology, pathogenesis, clinical manifestations, and diagnosis of dengue virus infection and its trend in Ethiopia. It may help countries, where dengue fever is not yet on the public health list-like Ethiopia to alert healthcare workers to consider the disease for diagnosis and treatment. The review retrieved and incorporated 139 published and organizational reports showing approximately 390 million new infections. About 100 million of these infections develop the clinical features of dengue, and thousands of people die annually from severe dengue fever in 129 countries. It is caused by being bitten by a dengue virus-infected female mosquito, primarily Aedes aegypti and, lesser, Ae. albopictus. Dengue virus is a member of the Flavivirus genus of the Flaviviridae family and has four independent but antigen-related single-stranded positive-sense RNA virus serotypes. The infection is usually asymptomatic but causes illnesses ranging from mild febrile illness to fatal dengue hemorrhagic fever or shock syndrome. Diagnosis can be by detecting the virus genome using nucleic acids amplification tests or testing NS1 antigen and/or anti-dengue antibodies from serum, plasma, circulating blood cells, or other tissues. Dengue cases and outbreaks have increased in recent decades, with a significant public health impact. Ethiopia has had nearly annual outbreaks since 2013, devastating an already fragmented health system and economy. Standardization of medication, population-level screening for early diagnosis and prompt treatment, and minimization of mosquito bites reduce overall infection and mortality rates.
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Affiliation(s)
- Biruk Zerfu
- Department of Medical Laboratory Science, College of Health Science, Addis Ababa University, Addis Ababa, Ethiopia. .,Aklilu Lema Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia.
| | - Tesfu Kassa
- grid.7123.70000 0001 1250 5688Aklilu Lema Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
| | - Mengistu Legesse
- grid.7123.70000 0001 1250 5688Aklilu Lema Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia
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9
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Sharma S, Sarkar R, Mitra K, Giri L. Computational framework to understand the clinical stages of COVID-19 and visualization of time course for various treatment strategies. Biotechnol Bioeng 2023; 120:1640-1656. [PMID: 36810760 DOI: 10.1002/bit.28358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2022] [Revised: 12/09/2022] [Accepted: 02/13/2023] [Indexed: 02/24/2023]
Abstract
Coronavirus disease 2019 is known to be regulated by multiple factors such as delayed immune response, impaired T cell activation, and elevated levels of proinflammatory cytokines. Clinical management of the disease remains challenging due to interplay of various factors as drug candidates may elicit different responses depending on the staging of the disease. In this context, we propose a computational framework which provides insights into the interaction between viral infection and immune response in lung epithelial cells, with an aim of predicting optimal treatment strategies based on infection severity. First, we formulate the model for visualizing the nonlinear dynamics during the disease progression considering the role of T cells, macrophages and proinflammatory cytokines. Here, we show that the model is capable of emulating the dynamic and static data trends of viral load, T cell, macrophage levels, interleukin (IL)-6 and TNF-α levels. Second, we demonstrate the ability of the framework to capture the dynamics corresponding to mild, moderate, severe, and critical condition. Our result shows that, at late phase (>15 days), severity of disease is directly proportional to pro-inflammatory cytokine IL6 and tumor necrosis factor (TNF)-α levels and inversely proportional to the number of T cells. Finally, the simulation framework was used to assess the effect of drug administration time as well as efficacy of single or multiple drugs on patients. The major contribution of the proposed framework is to utilize the infection progression model for clinical management and administration of drugs inhibiting virus replication and cytokine levels as well as immunosuppressant drugs at various stages of the disease.
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Affiliation(s)
- Surbhi Sharma
- Department of Chemical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana, India
| | - Rahuldeb Sarkar
- Departments of Respiratory Medicine and Critical Care, Medway NHS Foundation Trust, Gillingham, Kent, UK.,Faculty of Life Sciences, King's College London, London, UK
| | - Kishalay Mitra
- Department of Chemical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana, India
| | - Lopamudra Giri
- Department of Chemical Engineering, Indian Institute of Technology Hyderabad, Kandi, Sangareddy, Telangana, India
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10
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Zitzmann C, Dächert C, Schmid B, van der Schaar H, van Hemert M, Perelson AS, van Kuppeveld FJ, Bartenschlager R, Binder M, Kaderali L. Mathematical modeling of plus-strand RNA virus replication to identify broad-spectrum antiviral treatment strategies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2022.07.25.501353. [PMID: 35923314 PMCID: PMC9347285 DOI: 10.1101/2022.07.25.501353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Plus-strand RNA viruses are the largest group of viruses. Many are human pathogens that inflict a socio-economic burden. Interestingly, plus-strand RNA viruses share remarkable similarities in their replication. A hallmark of plus-strand RNA viruses is the remodeling of intracellular membranes to establish replication organelles (so-called "replication factories"), which provide a protected environment for the replicase complex, consisting of the viral genome and proteins necessary for viral RNA synthesis. In the current study, we investigate pan-viral similarities and virus-specific differences in the life cycle of this highly relevant group of viruses. We first measured the kinetics of viral RNA, viral protein, and infectious virus particle production of hepatitis C virus (HCV), dengue virus (DENV), and coxsackievirus B3 (CVB3) in the immuno-compromised Huh7 cell line and thus without perturbations by an intrinsic immune response. Based on these measurements, we developed a detailed mathematical model of the replication of HCV, DENV, and CVB3 and show that only small virus-specific changes in the model were necessary to describe the in vitro dynamics of the different viruses. Our model correctly predicted virus-specific mechanisms such as host cell translation shut off and different kinetics of replication organelles. Further, our model suggests that the ability to suppress or shut down host cell mRNA translation may be a key factor for in vitro replication efficiency which may determine acute self-limited or chronic infection. We further analyzed potential broad-spectrum antiviral treatment options in silico and found that targeting viral RNA translation, especially polyprotein cleavage, and viral RNA synthesis may be the most promising drug targets for all plus-strand RNA viruses. Moreover, we found that targeting only the formation of replicase complexes did not stop the viral replication in vitro early in infection, while inhibiting intracellular trafficking processes may even lead to amplified viral growth. Author summary Plus-strand RNA viruses comprise a large group of related and medically relevant viruses. The current global pandemic of COVID-19 caused by the SARS-coronavirus-2 as well as the constant spread of diseases such as dengue and chikungunya fever show the necessity of a comprehensive and precise analysis of plus-strand RNA virus infections. Plus-strand RNA viruses share similarities in their life cycle. To understand their within-host replication strategies, we developed a mathematical model that studies pan-viral similarities and virus-specific differences of three plus-strand RNA viruses, namely hepatitis C, dengue, and coxsackievirus. By fitting our model to in vitro data, we found that only small virus-specific variations in the model were required to describe the dynamics of all three viruses. Furthermore, our model predicted that ribosomes involved in viral RNA translation seem to be a key player in plus-strand RNA replication efficiency, which may determine acute or chronic infection outcome. Furthermore, our in-silico drug treatment analysis suggests that targeting viral proteases involved in polyprotein cleavage, in combination with viral RNA replication, may represent promising drug targets with broad-spectrum antiviral activity.
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Affiliation(s)
- Carolin Zitzmann
- Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Christopher Dächert
- Research Group “Dynamics of Early Viral Infection and the Innate Antiviral Response”, Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Bianca Schmid
- Dept of Infectious Diseases, Molecular Virology, Heidelberg University, Heidelberg, Germany
| | - Hilde van der Schaar
- Division of infectious Diseases and Immunology, Virology Section, Dept of Biomolecular Health Sciences, Utrecht University, Utrecht, The Netherlands
| | - Martijn van Hemert
- Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Alan S. Perelson
- Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America
| | - Frank J.M. van Kuppeveld
- Division of infectious Diseases and Immunology, Virology Section, Dept of Biomolecular Health Sciences, Utrecht University, Utrecht, The Netherlands
| | - Ralf Bartenschlager
- Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Dept of Infectious Diseases, Molecular Virology, Heidelberg University, Heidelberg, Germany
- German Center for Infection Research (DZIF), Heidelberg partner site, Heidelberg, Germany
| | - Marco Binder
- Research Group “Dynamics of Early Viral Infection and the Innate Antiviral Response”, Division Virus-Associated Carcinogenesis (F170), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Lars Kaderali
- Institute of Bioinformatics, University Medicine Greifswald, Greifswald, Germany
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11
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Liu X, Pappas EJ, Husby ML, Motsa BB, Stahelin RV, Pienaar E. Mechanisms of phosphatidylserine influence on viral production: A computational model of Ebola virus matrix protein assembly. J Biol Chem 2022; 298:102025. [PMID: 35568195 PMCID: PMC9218153 DOI: 10.1016/j.jbc.2022.102025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 05/02/2022] [Accepted: 05/04/2022] [Indexed: 11/30/2022] Open
Abstract
Ebola virus (EBOV) infections continue to pose a global public health threat, with high mortality rates and sporadic outbreaks in Central and Western Africa. A quantitative understanding of the key processes driving EBOV assembly and budding could provide valuable insights to inform drug development. Here, we use a computational model to evaluate EBOV matrix assembly. Our model focuses on the assembly kinetics of VP40, the matrix protein in EBOV, and its interaction with phosphatidylserine (PS) in the host cell membrane. It has been shown that mammalian cells transfected with VP40-expressing plasmids are capable of producing virus-like particles (VLPs) that closely resemble EBOV virions. Previous studies have also shown that PS levels in the host cell membrane affects VP40 association with the plasma membrane inner leaflet and that lower membrane PS levels result in lower VLP production. Our computational findings indicate that PS may also have a direct influence on VP40 VLP assembly and budding, where a higher PS level will result in a higher VLP budding rate and filament dissociation rate. Our results further suggest that the assembly of VP40 filaments follow the nucleation-elongation theory, where initialization and oligomerization of VP40 are two distinct steps in the assembly process. Our findings advance the current understanding of VP40 VLP formation by identifying new possible mechanisms of PS influence on VP40 assembly. We propose that these mechanisms could inform treatment strategies targeting PS alone or in combination with other VP40 assembly steps.
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Affiliation(s)
- Xiao Liu
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Ethan J Pappas
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Monica L Husby
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, Indiana, USA
| | - Balindile B Motsa
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, Indiana, USA
| | - Robert V Stahelin
- Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, Indiana, USA
| | - Elsje Pienaar
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA.
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12
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Lothert K, Eilts F, Wolff MW. Quantification methods for viruses and virus-like particles applied in biopharmaceutical production processes. Expert Rev Vaccines 2022; 21:1029-1044. [PMID: 35483057 DOI: 10.1080/14760584.2022.2072302] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Effective cell-based production processes of virus particles are the foundation for the global availability of classical vaccines, gene therapeutic vectors, and viral oncolytic treatments. Their production is subject to regulatory standards ensuring the safety and efficacy of the pharmaceutical product. Process analytics must be fast and reliable to provide an efficient process development and a robust process control during production. Additionally, for the product release, the drug compound and the contaminants must be quantified by assays specified by regulatory authorities. AREAS COVERED This review summarizes analytical methods suitable for the quantification of viruses or virus-like particles. The different techniques are grouped by the analytical question that may be addressed. Accordingly, methods focus on the infectivity of the drug component on the one hand, and on particle counting and the quantification of viral elements on the other hand. The different techniques are compared regarding their advantages, drawbacks, required assay time, and sample throughput. EXPERT OPINION Among the technologies summarized, a tendency toward fast methods, allowing a high throughput and a wide applicability, can be foreseen. Driving forces for this progress are miniaturization and automation, and the continuous enhancement of process-relevant databases for a successful future process control.
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Affiliation(s)
- Keven Lothert
- Department of Life Science Engineering, Institute of Bioprocess Engineering and Pharmaceutical Technology, University of Applied Sciences Mittelhessen (THM), Giessen, Germany
| | - Friederike Eilts
- Department of Life Science Engineering, Institute of Bioprocess Engineering and Pharmaceutical Technology, University of Applied Sciences Mittelhessen (THM), Giessen, Germany
| | - Michael W Wolff
- Department of Life Science Engineering, Institute of Bioprocess Engineering and Pharmaceutical Technology, University of Applied Sciences Mittelhessen (THM), Giessen, Germany.,Branch for Bioresources, Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), Giessen, Germany
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13
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Pasin F, Daròs JA, Tzanetakis IE. OUP accepted manuscript. FEMS Microbiol Rev 2022; 46:6534904. [PMID: 35195244 PMCID: PMC9249622 DOI: 10.1093/femsre/fuac011] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 02/02/2022] [Accepted: 02/08/2022] [Indexed: 11/17/2022] Open
Abstract
Potyviridae, the largest family of known RNA viruses (realm Riboviria), belongs to the picorna-like supergroup and has important agricultural and ecological impacts. Potyvirid genomes are translated into polyproteins, which are in turn hydrolyzed to release mature products. Recent sequencing efforts revealed an unprecedented number of potyvirids with a rich variability in gene content and genomic layouts. Here, we review the heterogeneity of non-core modules that expand the structural and functional diversity of the potyvirid proteomes. We provide a family-wide classification of P1 proteinases into the functional Types A and B, and discuss pretty interesting sweet potato potyviral ORF (PISPO), putative zinc fingers, and alkylation B (AlkB)—non-core modules found within P1 cistrons. The atypical inosine triphosphate pyrophosphatase (ITPase/HAM1), as well as the pseudo tobacco mosaic virus-like coat protein (TMV-like CP) are discussed alongside homologs of unrelated virus taxa. Family-wide abundance of the multitasking helper component proteinase (HC-pro) is revised. Functional connections between non-core modules are highlighted to support host niche adaptation and immune evasion as main drivers of the Potyviridae evolutionary radiation. Potential biotechnological and synthetic biology applications of potyvirid leader proteinases and non-core modules are finally explored.
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Affiliation(s)
- Fabio Pasin
- Corresponding author: Instituto de Biología Molecular y Celular de Plantas (IBMCP), Consejo Superior de Investigaciones Científicas-Universitat Politècnica de València (CSIC-UPV), UPV Building 8E, Ingeniero Fausto Elio, 46011 Valencia, Spain. E-mail:
| | - José-Antonio Daròs
- Instituto de Biología Molecular y Celular de Plantas (IBMCP), Consejo Superior de Investigaciones Científicas-Universitat Politècnica de València (CSIC-UPV), 46011 Valencia, Spain
| | - Ioannis E Tzanetakis
- Department of Entomology and Plant Pathology, Division of Agriculture, University of Arkansas System, 72701 Fayetteville, AR, USA
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14
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Bernhauerová V, Lisowski B, Rezelj VV, Vignuzzi M. Mathematical modelling of SARS-CoV-2 infection of human and animal host cells reveals differences in the infection rates and delays in viral particle production by infected cells. J Theor Biol 2021; 531:110895. [PMID: 34499915 PMCID: PMC8418984 DOI: 10.1016/j.jtbi.2021.110895] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 07/28/2021] [Accepted: 09/01/2021] [Indexed: 01/04/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV -2), a causative agent of COVID-19 disease, poses a significant threat to public health. Since its outbreak in December 2019, Wuhan, China, extensive collection of diverse data from cell culture and animal infections as well as population level data from an ongoing pandemic, has been vital in assessing strategies to battle its spread. Mathematical modelling plays a key role in quantifying determinants that drive virus infection dynamics, especially those relevant for epidemiological investigations and predictions as well as for proposing efficient mitigation strategies. We utilized a simple mathematical model to describe and explain experimental results on viral replication cycle kinetics during SARS-CoV-2 infection of animal and human derived cell lines, green monkey kidney cells, Vero-E6, and human lung epithelium cells, A549-ACE2, respectively. We conducted cell infections using two distinct initial viral concentrations and quantified viral loads over time. We then fitted the model to our experimental data and quantified the viral parameters. We showed that such cellular tropism generates significant differences in the infection rates and incubation times of SARS-CoV-2, that is, the times to the first release of newly synthesised viral progeny by SARS-CoV-2-infected cells. Specifically, the rate at which A549-ACE2 cells were infected by SARS-CoV-2 was 15 times lower than that in the case of Vero-E6 cell infection and the duration of latent phase of A549-ACE2 cells was 1.6 times longer than that of Vero-E6 cells. On the other hand, we found no statistically significant differences in other viral parameters, such as viral production rate or infected cell death rate. Since in vitro infection assays represent the first stage in the development of antiviral treatments against SARS-CoV-2, discrepancies in the viral parameter values across different cell hosts have to be identified and quantified to better target vaccine and antiviral research.
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Affiliation(s)
- Veronika Bernhauerová
- Department of Biophysics and Physical Chemistry, Faculty of Pharmacy, Charles University, Heyrovského 1203, Hradec Králové 500 05, Czech Republic.
| | - Bartek Lisowski
- Department of Biophysics, Chair of Physiology, Jagiellonian University Medical College, św. Łazarza 16, Kraków 31-530, Poland
| | - Veronica V Rezelj
- Institut Pasteur, Viral Populations and Pathogenesis Unit, Department of Virology, CNRS UMR 3569, Paris F-75015, France
| | - Marco Vignuzzi
- Institut Pasteur, Viral Populations and Pathogenesis Unit, Department of Virology, CNRS UMR 3569, Paris F-75015, France.
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15
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Chhajer H, Rizvi VA, Roy R. Life cycle process dependencies of positive-sense RNA viruses suggest strategies for inhibiting productive cellular infection. J R Soc Interface 2021; 18:20210401. [PMID: 34753308 PMCID: PMC8580453 DOI: 10.1098/rsif.2021.0401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Accepted: 10/18/2021] [Indexed: 12/25/2022] Open
Abstract
Life cycle processes of positive-strand (+)RNA viruses are broadly conserved across families, yet they employ different strategies to grow in the cell. Using a generalized dynamical model for intracellular (+)RNA virus growth, we decipher these life cycle determinants and their dependencies for several viruses and parse the effects of viral mutations, drugs and host cell permissivity. We show that poliovirus employs rapid replication and virus assembly, whereas the Japanese encephalitis virus leverages its higher rate of translation and efficient cellular reorganization compared to the hepatitis C virus. Stochastic simulations demonstrate infection extinction if all seeding (inoculating) viral RNA degrade before establishing robust replication critical for infection. The probability of this productive cellular infection, 'cellular infectivity', is affected by virus-host processes and defined by early life cycle events and viral seeding. An increase in cytoplasmic RNA degradation and delay in vesicular compartment formation reduces infectivity, more so when combined. Synergy among these parameters in limiting (+)RNA virus infection as predicted by our model suggests new avenues for inhibiting infections by targeting the early life cycle bottlenecks.
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Affiliation(s)
- Harsh Chhajer
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
| | - Vaseef A. Rizvi
- Molecular Biophysics Unit, Indian Institute of Science, Bangalore 560012, Karnataka, India
| | - Rahul Roy
- Centre for Biosystems Science and Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
- Department of Chemical Engineering, Indian Institute of Science, Bangalore 560012, Karnataka, India
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16
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Nguyen HD, Chaudhury S, Waickman AT, Friberg H, Currier JR, Wallqvist A. Stochastic Model of the Adaptive Immune Response Predicts Disease Severity and Captures Enhanced Cross-Reactivity in Natural Dengue Infections. Front Immunol 2021; 12:696755. [PMID: 34484195 PMCID: PMC8416063 DOI: 10.3389/fimmu.2021.696755] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 07/26/2021] [Indexed: 11/13/2022] Open
Abstract
The dengue virus circulates as four distinct serotypes, where a single serotype infection is typically asymptomatic and leads to acquired immunity against that serotype. However, the developed immunity to one serotype is thought to underlie the severe manifestation of the disease observed in subsequent infections from a different serotype. We developed a stochastic model of the adaptive immune response to dengue infections. We first delineated the mechanisms initiating and sustaining adaptive immune responses during primary infections. We then contrasted these immune responses during secondary infections of either a homotypic or heterotypic serotype to understand the role of pre-existing and reactivated immune pathways on disease severity. Comparison of non-symptomatic and severe cases from heterotypic infections demonstrated that overproduction of specific antibodies during primary infection induces an enhanced population of cross-reactive antibodies during secondary infection, ultimately leading to severe disease manifestations. In addition, the level of disease severity was found to correlate with immune response kinetics, which was dependent on beginning lymphocyte levels. Our results detail the contribution of specific lymphocytes and antibodies to immunity and memory recall that lead to either protective or pathological outcomes, allowing for the understanding and determination of mechanisms of protective immunity.
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Affiliation(s)
- Hung D Nguyen
- Biotechnology High Performance Computing (HPC) Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, United States.,Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States
| | - Sidhartha Chaudhury
- Center for Enabling Capabilities, Walter Reed Army Institute of Research, Silver Spring, MD, United States
| | - Adam T Waickman
- Department of Microbiology and Immunology, State University of New York Upstate Medical University, Syracuse, NY, United States
| | - Heather Friberg
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MD, United States
| | - Jeffrey R Currier
- Viral Diseases Branch, Walter Reed Army Institute of Research, Silver Spring, MD, United States
| | - Anders Wallqvist
- Biotechnology High Performance Computing (HPC) Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick, MD, United States
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17
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Modeling the complete kinetics of coxsackievirus B3 reveals human determinants of host-cell feedback. Cell Syst 2021; 12:304-323.e13. [PMID: 33740397 DOI: 10.1016/j.cels.2021.02.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 01/13/2021] [Accepted: 02/19/2021] [Indexed: 12/13/2022]
Abstract
Complete kinetic models are pervasive in chemistry but lacking in biological systems. We encoded the complete kinetics of infection for coxsackievirus B3 (CVB3), a compact and fast-acting RNA virus. The model consists of separable, detailed modules describing viral binding-delivery, translation-replication, and encapsidation. Specific module activities are dampened by the type I interferon response to viral double-stranded RNAs (dsRNAs), which is itself disrupted by viral proteinases. The experimentally validated kinetics uncovered that cleavability of the dsRNA transducer mitochondrial antiviral signaling protein (MAVS) becomes a stronger determinant of viral outcomes when cells receive supplemental interferon after infection. Cleavability is naturally altered in humans by a common MAVS polymorphism, which removes a proteinase-targeted site but paradoxically elevates CVB3 infectivity. These observations are reconciled with a simple nonlinear model of MAVS regulation. Modeling complete kinetics is an attainable goal for small, rapidly infecting viruses and perhaps viral pathogens more broadly. A record of this paper's transparent peer review process is included in the Supplemental information.
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18
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Dobrovolny HM. Quantifying the effect of remdesivir in rhesus macaques infected with SARS-CoV-2. Virology 2020; 550:61-69. [PMID: 32882638 PMCID: PMC7443325 DOI: 10.1016/j.virol.2020.07.015] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Revised: 06/28/2020] [Accepted: 07/21/2020] [Indexed: 02/08/2023]
Abstract
The world is in the midst of a pandemic caused by a novel coronavirus and is desperately searching for possible treatments. The antiviral remdesivir has shown some effectiveness against SARS-CoV-2 in vitro and in a recent animal study. We use data from a study of remdesivir in rhesus macaques to fit a viral kinetics model in an effort to determine the most appropriate mathematical descripton of the effect of remdesivir. We find statistically significant differences in the viral decay rate and use this to inform a possible mathematical formulation of the effect of remdesivir. Unfortunately, this model formulation suggests that the application of remdesivir will lengthen SARS-CoV-2 infections, putting into question its potential clinical benefit.
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Affiliation(s)
- Hana M Dobrovolny
- Department of Physics and Astronomy, Texas Christian University, Fort Worth, TX, USA.
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