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1.
NPJ Syst Biol Appl ; 8(1): 15, 2022 05 02.
Article in English | MEDLINE | ID: covidwho-1890186

ABSTRACT

Increasing evidence points towards the key role of the epithelium in the systemic and over-activated immune response to viral infection, including SARS-CoV-2 infection. Yet, how viral infection alters epithelial-immune cell interactions regulating inflammatory responses, is not well known. Available experimental approaches are insufficient to properly analyse this complex system, and computational predictions and targeted data integration are needed as an alternative approach. In this work, we propose an integrated computational biology framework that models how infection alters intracellular signalling of epithelial cells and how this change impacts the systemic immune response through modified interactions between epithelial cells and local immune cell populations. As a proof-of-concept, we focused on the role of intestinal and upper-airway epithelial infection. To characterise the modified epithelial-immune interactome, we integrated intra- and intercellular networks with single-cell RNA-seq data from SARS-CoV-2 infected human ileal and colonic organoids as well as from infected airway ciliated epithelial cells. This integrated methodology has proven useful to point out specific epithelial-immune interactions driving inflammation during disease response, and propose relevant molecular targets to guide focused experimental analysis.


Subject(s)
COVID-19 , Virus Diseases , Epithelial Cells , Humans , SARS-CoV-2 , Signal Transduction
2.
Mol Syst Biol ; 17(3): e9923, 2021 03.
Article in English | MEDLINE | ID: covidwho-1389839

ABSTRACT

Molecular knowledge of biological processes is a cornerstone in omics data analysis. Applied to single-cell data, such analyses provide mechanistic insights into individual cells and their interactions. However, knowledge of intercellular communication is scarce, scattered across resources, and not linked to intracellular processes. To address this gap, we combined over 100 resources covering interactions and roles of proteins in inter- and intracellular signaling, as well as transcriptional and post-transcriptional regulation. We added protein complex information and annotations on function, localization, and role in diseases for each protein. The resource is available for human, and via homology translation for mouse and rat. The data are accessible via OmniPath's web service (https://omnipathdb.org/), a Cytoscape plug-in, and packages in R/Bioconductor and Python, providing access options for computational and experimental scientists. We created workflows with tutorials to facilitate the analysis of cell-cell interactions and affected downstream intracellular signaling processes. OmniPath provides a single access point to knowledge spanning intra- and intercellular processes for data analysis, as we demonstrate in applications studying SARS-CoV-2 infection and ulcerative colitis.


Subject(s)
COVID-19/metabolism , Colitis, Ulcerative/metabolism , Computational Biology/methods , Proteins/metabolism , Signal Transduction , Animals , Cell Communication , Colitis, Ulcerative/pathology , Databases, Factual , Enzymes/metabolism , Humans , Mice , Protein Processing, Post-Translational , Proteins/genetics , Rats , Single-Cell Analysis , Software , Workflow
3.
Cells ; 10(9)2021 08 29.
Article in English | MEDLINE | ID: covidwho-1374308

ABSTRACT

Intercellular communication mediated by cytokines is critical to the development of immune responses, particularly in the context of infectious and inflammatory diseases. By releasing these small molecular weight peptides, the source cells can influence numerous intracellular processes in the target cells, including the secretion of other cytokines downstream. However, there are no readily available bioinformatic resources that can model cytokine-cytokine interactions. In this effort, we built a communication map between major tissues and blood cells that reveals how cytokine-mediated intercellular networks form during homeostatic conditions. We collated the most prevalent cytokines from the literature and assigned the proteins and their corresponding receptors to source tissue and blood cell types based on enriched consensus RNA-Seq data from the Human Protein Atlas database. To assign more confidence to the interactions, we integrated the literature information on cell-cytokine interactions from two systems of immunology databases, immuneXpresso and ImmunoGlobe. From the collated information, we defined two metanetworks: a cell-cell communication network connected by cytokines; and a cytokine-cytokine interaction network depicting the potential ways in which cytokines can affect the activity of each other. Using expression data from disease states, we then applied this resource to reveal perturbations in cytokine-mediated intercellular signalling in inflammatory and infectious diseases (ulcerative colitis and COVID-19, respectively). For ulcerative colitis, with CytokineLink, we demonstrated a significant rewiring of cytokine-mediated intercellular communication between non-inflamed and inflamed colonic tissues. For COVID-19, we were able to identify cell types and cytokine interactions following SARS-CoV-2 infection, highlighting important cytokine interactions that might contribute to severe illness in a subgroup of patients. Such findings have the potential to inform the development of novel, cytokine-targeted therapeutic strategies. CytokineLink is freely available for the scientific community through the NDEx platform and the project github repository.


Subject(s)
COVID-19/immunology , Cytokines/metabolism , Immunity , Inflammatory Bowel Diseases/immunology , Cell Communication , Colitis, Ulcerative/immunology , Colitis, Ulcerative/pathology , Databases, Genetic , Humans , Inflammatory Bowel Diseases/pathology , Signal Transduction
4.
Front Immunol ; 12: 629193, 2021.
Article in English | MEDLINE | ID: covidwho-1140644

ABSTRACT

Hyper-induction of pro-inflammatory cytokines, also known as a cytokine storm or cytokine release syndrome (CRS), is one of the key aspects of the currently ongoing SARS-CoV-2 pandemic. This process occurs when a large number of innate and adaptive immune cells activate and start producing pro-inflammatory cytokines, establishing an exacerbated feedback loop of inflammation. It is one of the factors contributing to the mortality observed with coronavirus 2019 (COVID-19) for a subgroup of patients. CRS is not unique to the SARS-CoV-2 infection; it was prevalent in most of the major human coronavirus and influenza A subtype outbreaks of the past two decades (H5N1, SARS-CoV, MERS-CoV, and H7N9). With a comprehensive literature search, we collected changing the cytokine levels from patients upon infection with the viral pathogens mentioned above. We analyzed published patient data to highlight the conserved and unique cytokine responses caused by these viruses. Our curation indicates that the cytokine response induced by SARS-CoV-2 is different compared to other CRS-causing respiratory viruses, as SARS-CoV-2 does not always induce specific cytokines like other coronaviruses or influenza do, such as IL-2, IL-10, IL-4, or IL-5. Comparing the collated cytokine responses caused by the analyzed viruses highlights a SARS-CoV-2-specific dysregulation of the type-I interferon (IFN) response and its downstream cytokine signatures. The map of responses gathered in this study could help specialists identify interventions that alleviate CRS in different diseases and evaluate whether they could be used in the COVID-19 cases.


Subject(s)
COVID-19/immunology , Cytokine Release Syndrome/immunology , Influenza A virus/immunology , Influenza, Human/immunology , Middle East Respiratory Syndrome Coronavirus/immunology , SARS-CoV-2/immunology , Severe Acute Respiratory Syndrome/immunology , Severe acute respiratory syndrome-related coronavirus/immunology , Severity of Illness Index , COVID-19/blood , COVID-19/pathology , COVID-19/virology , Cytokine Release Syndrome/blood , Cytokine Release Syndrome/virology , Cytokines/blood , Humans , Inflammation/immunology , Influenza, Human/blood , Influenza, Human/virology , Severe Acute Respiratory Syndrome/blood , Severe Acute Respiratory Syndrome/virology
5.
PLoS Comput Biol ; 17(2): e1008685, 2021 02.
Article in English | MEDLINE | ID: covidwho-1061189

ABSTRACT

The SARS-CoV-2 pandemic of 2020 has mobilised scientists around the globe to research all aspects of the coronavirus virus and its infection. For fruitful and rapid investigation of viral pathomechanisms, a collaborative and interdisciplinary approach is required. Therefore, we have developed ViralLink: a systems biology workflow which reconstructs and analyses networks representing the effect of viruses on intracellular signalling. These networks trace the flow of signal from intracellular viral proteins through their human binding proteins and downstream signalling pathways, ending with transcription factors regulating genes differentially expressed upon viral exposure. In this way, the workflow provides a mechanistic insight from previously identified knowledge of virally infected cells. By default, the workflow is set up to analyse the intracellular effects of SARS-CoV-2, requiring only transcriptomics counts data as input from the user: thus, encouraging and enabling rapid multidisciplinary research. However, the wide-ranging applicability and modularity of the workflow facilitates customisation of viral context, a priori interactions and analysis methods. Through a case study of SARS-CoV-2 infected bronchial/tracheal epithelial cells, we evidence the functionality of the workflow and its ability to identify key pathways and proteins in the cellular response to infection. The application of ViralLink to different viral infections in a context specific manner using different available transcriptomics datasets will uncover key mechanisms in viral pathogenesis.


Subject(s)
COVID-19/metabolism , Computational Biology/methods , Gene Expression Regulation, Viral , SARS-CoV-2/pathogenicity , Signal Transduction , Algorithms , Bronchi/virology , Cluster Analysis , Gene Expression Profiling , Host-Pathogen Interactions , Humans , Interdisciplinary Research , Lung/virology , Models, Statistical , Systems Biology , Transcriptome , Workflow
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