SignaFish: A Zebrafish-Specific Signaling Pathway Resource

Understanding living systems requires an in-depth knowledge of the signaling networks that drive cellular homeostasis, regulate intercellular communication, and contribute to cell fates during development. Several resources exist to provide high-throughput data sets or manually curated interaction information from human or invertebrate model organisms. We previously developed SignaLink, a uniformly curated, multi-layered signaling resource containing information for human and for the model organisms nematode Caenorhabditis elegans and fruit fly Drosophila melanogaster. Until now, the use of the SignaLink database for zebrafish pathway analysis was limited. To overcome this limitation, we created SignaFish ( http://signafish.org ), a fish-specific signaling resource, built using the concept of SignaLink. SignaFish contains more than 200 curation-based signaling interactions, 132 further interactions listed in other resources, and it also lists potential miRNA-based regulatory connections for seven major signaling pathways. From the SignaFish website, users can reach other web resources, such as ZFIN. SignaFish provides signaling or signaling-related interactions that can be examined for each gene or downloaded for each signaling pathway. We believe that the SignaFish resource will serve as a novel navigating point for experimental design and evaluation for the zebrafish community and for researchers focusing on nonmodel fish species, such as cyclids

P020 Mapping the changing intercellular communication and its downstream effect in Ulcerative Colitis

Abstract Background Intercellular communication is essential for growing and differentiating in multicellular organisms by transducing the signal from cell to cell. Despite its importance, the molecular background is less discovered due to the lack of data. This gap has started to be addressed with the appearance of single-cell omics approaches providing an insight among others into the gene expression of individual cells. Methods We have developed a method to predict and compare cell-cell signalling interactions using single-cell RNAseq data from colon biopsies. Transcriptomic data alone is not capable of connecting the cells, a reliable network resource is needed to mediate the signal via protein-protein interactions between the source and target cells. Here we used OmniPath - a resource providing not only intra- and intercellular interactions but also annotations of proteins involved in the interplay of cells - to reconstruct signalling networks. We examined intercellular communication among five cell-types (regulatory T cell, macrophage, dendritic cell, goblet cell and myofibroblast) in healthy colon and during Ulcerative Colitis. Results Our analysis shows that there are significant differences in the type of cell-cell communication (ligand-receptor connections, adherens junctions, etc.) between the healthy and Ulcerative Colitis (UC) conditions, and these differences lead to altered downstream effects in the signal receiving cell. In both conditions, the ligand-receptor and adhesion connections were overrepresented, however cell junctions were less abundant in UC. Regarding the communication among the five cell-types, in healthy condition, cells are tightly connected to dendritic cells while in diseased condition to regulatory T cells. Focusing on ligand-receptor interactions between myofibroblasts and regulatory T cells, our pipeline identified the MAPK, Toll-like receptor (TLR) 2/6 and TLR 7/8 pathways enriched downstream in healthy conditions. In contrast, TLR3 and TLR4 pathways were affected by the myofibroblast in Ulcerative Colitis. Conclusion We found key intercellular mechanisms leading to well-defined differential pathway activation profiles. We showed that in uninflamed UC condition myofibroblasts disrupt the anti-inflammatory effect of regulatory T cells. Our pipeline is able to predict and analyse cell-cell interactions and their downstream effects and to highlight the differences in healthy and diseased states. </jats:sec

Discriminate the response of Acute Myeloid Leukemia patients to treatment by using proteomics data and Answer Set Programming

International audienc

The minimum information about a molecular interaction CAusal STatement (MI2CAST)

Motivation: A large variety of molecular interactions occurs between biomolecular components in cells. When a molecular interaction results in a regulatory effect, exerted by one component onto a downstream component, a so-called 'causal interaction' takes place. Causal interactions constitute the building blocks in our understanding of larger regulatory networks in cells. These causal interactions and the biological processes they enable (e.g. gene regulation) need to be described with a careful appreciation of the underlying molecular reactions. A proper description of this information enables archiving, sharing and reuse by humans and for automated computational processing. Various representations of causal relationships between biological components are currently used in a variety of resources. Results: Here, we propose a checklist that accommodates current representations, called the Minimum Information about a Molecular Interaction CAusal STatement (MI2CAST). This checklist defines both the required core information, as well as a comprehensive set of other contextual details valuable to the end user and relevant for reusing and reproducing causal molecular interaction information. The MI2CAST checklist can be used as reporting guidelines when annotating and curating causal statements, while fostering uniformity and interoperability of the data across resources. Availability and implementation: The checklist together with examples is accessible at https://github.com/MI2CAST/MI2CAST