Problem/Proposed Solution: Ligand-receptor binding mediates cell-to cell communication across different cell types and tissues. There is a need for more information on interactions between ligand-receptor pairs. Current research by Ramilowski et al. elucidates ligand-receptor pairs across 144 human primary cell types forming a large-scale map of cell-cell communication . It is necessary to expand this work to get a better understanding of cell-cell communication as a whole.
I propose a similar framework to L1000 , a “connectivity map” that examines transcriptomic expression profile changes in various cell lines based on drug compounds applied.
Details of suggested approach:
The method involves starting the search from known ligand-receptor pairs, such as the aforementioned “Ramilowski” pairs, and examine homologous ligand and receptors to these established pairs. These “homologous” protein families are quite similar in three-dimensional structure and sequence which reflects common ancestry. It is also widely known that these homologous proteins frequently have the same function as well. Therefore, it is reasonable to expect that these similar pairings could be undiscovered ligand-receptor pairs that behave similarly to observed pairs. Then, signaling of the “Ramilowski” receptors in these cells are studied in-depth, similarly to the methodology presented in the L1000 connectivity map. Changes of intercellular signal would be studied by knocking it down via shRNA, by knockout via CRISPR-CAS9, or by overexpressing the gene via cDNA and then adding corresponding ligands. Change in cell activity after these perturbations would be compared to normal cell-cell signaling and then profiled. This framework could also be repeated in other species of interest such as Mouse since previous work has examined ligand-receptor pairs across different species [4,5].
How it could affect the broader field: We would be able to see how the same cellular signals differ across a variety of cell types and tissues and how these perturbations can affect cell signaling. This work can further be applied in a practical setting by furthering therapeutic research. The discovery of novel ligand-receptor pairs can be used to develop novel agonists/antagonists. This work can also aid drug repositioning efforts since there could be already-existing therapeutics that mimic/inhibit the effects of elucidated ligands when applied to receptors. This framework can not only find novel ligand-receptor pairs, but can also be used to validate known pairs. Most importantly, this widely available compendium would be an invaluable resource to the scientific community for furthering our understanding of cell-cell communication.
1. Ramilowski, J. A. et al. A draft network of ligand–receptor-mediated multicellular signalling in human. Nat. Commun.6, 7866 (2015).
2. Subramanian, A. et al. A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. Cell171, 1437-1452.e17 (2017).
3. Pearson, W. R. An introduction to sequence similarity (‘homology’) searching. Curr. Protoc. Bioinforma.Chapter 3, Unit3.1 (2013).
4. Hsueh, A. J. W. & Feng, Y. Discovery of polypeptide ligand‐receptor pairs based on their co‐evolution. FASEB J.34, 8824–8832 (2020).
5. Braasch, I., Volff, J.-N. & Schartl, M. The Endothelin System: Evolution of Vertebrate-Specific Ligand-Receptor Interactions by Three Rounds of Genome Duplication. Mol. Biol. Evol.26, 783–799 (2009).