CytokineLink: a cytokine communication map to analyse immune responses in inflammatory and infectious diseases
Olbei, M. L.; Thomas, J.; Hautefort, I.; Treveil, A.; Bohar, B.; Madgwick, M.; Potari-Gul, L.; Csabai, L.; Modos, D.; Korcsmaros, T.
Show 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 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 literature information on cell - cytokine interactions from two systems 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 inactive cell types and cytokine interactions that may be important following SARS-CoV-2 infection when comparing the cytokine response with other viruses capable of initiating a cytokine storm. Such findings have 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 (https://github.com/korcsmarosgroup/CytokineLink).
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Plasma gradient of soluble urokinase-type plasminogen activator receptor is linked to pathogenic plasma proteome and immune transcriptome and stratifies outcomes in severe COVID-19 93%
- A neutrophil-driven inflammatory signature characterizes the blood cell transcriptome fingerprints of Psoriasis and Kawasaki Disease 92%
- Transcriptional Regulatory Logic Orchestrating Lymphoid and Myeloid Cell Fate Decisions 92%
Similar papers in this journal
- Estimating the effect of tissue- and blood-derived cell reference matrices on deconvolving bulk transcriptomic datasets 92%
- TCR_Explore: a novel webtool for T cell receptor repertoire analysis 92%
- Blood biomarkers representing maternal-fetal interface tissues used to predict early-and late-onset preeclampsia but not COVID-19 infection 91%
Similar papers in this journal
- Leveraging Dynamic Stability to Infer Regulation in Protein-Protein Interaction Networks: A Study of Infectious Vulnerability in COPD. 93%
- Combining explainable machine learning, demographic and multi-omic data to identify precision medicine strategies for inflammatory bowel disease 92%
- Bioinformatic characterization of angiotensin-converting enzyme 2, the entry receptor for SARS-CoV-2 92%
Similar papers in this journal
- Hypothesizing mechanistic links between microbes and disease using knowledge graphs 94%
- Naturally occurring combinations of receptors from single cell transcriptomics in endothelial cells 93%
- Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method 92%
Similar papers in this journal
- GeneCOCOA: Detecting context-specific functions of individual genes using co-expression data 92%
- Ranking of cell clusters in a single-cell RNA-sequencing analysis framework using prior knowledge 92%
- HELP: A computational framework for labelling and predicting human common and context-specific essential genes 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.