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Published May 18, 2022 | Submitted + Supplemental Material + Published
Journal Article Open

Ligand-receptor promiscuity enables cellular addressing


In multicellular organisms, secreted ligands selectively activate, or "address," specific target cell populations to control cell fate decision-making and other processes. Key cell-cell communication pathways use multiple promiscuously interacting ligands and receptors, provoking the question of how addressing specificity can emerge from molecular promiscuity. To investigate this issue, we developed a general mathematical modeling framework based on the bone morphogenetic protein (BMP) pathway architecture. We find that promiscuously interacting ligand-receptor systems allow a small number of ligands, acting in combinations, to address a larger number of individual cell types, defined by their receptor expression profiles. Promiscuous systems outperform seemingly more specific one-to-one signaling architectures in addressing capability. Combinatorial addressing extends to groups of cell types, is robust to receptor expression noise, grows more powerful with increases in the number of receptor variants, and is maximized by specific biochemical parameter relationships. Together, these results identify design principles governing cellular addressing by ligand combinations.

Additional Information

© 2022 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Received 29 December 2020, Revised 8 November 2021, Accepted 16 March 2022, Available online 13 April 2022. We thank Ke-Huan Chow, Alejandro Granados, Bo Gu, Rachael Kuintzle, Yitong Ma, Nagarajan Nandagopal, Leah Santat, Martin Tran, and other members of the Elowitz lab for scientific input and feedback. We thank Samantha Butler, Sarah Denny, Jordi Garcia-Ojalvo, Lea Goentoro, Elliot Hui, Jay Lieberman, Roy Kishony, Alan Moses, Xiling Shen, Matt Thomson, Ned Wingreen, and Vincent Zaballa for helpful discussions. This work was supported by the Allen Discovery Center Program (award UWSC10142), a Paul G. Allen Frontiers Group advised program of the Paul G. Allen Family Foundation; the Defense Advanced Research Projects Agency (contract HR0011-16-0138); the Gordon and Betty Moore Foundation (grant GBMF2809 to the Caltech Programmable Molecular Technology Initiative); the Human Frontiers Science Program (grant RGP0020); the Institute for Collaborative Biotechnologies (grant W911NF-09-0001 from the U.S. Army Research Office); and the National Institutes of Health (NIH) (grants R01 HD075335A and R01 MH116508). This work does not necessarily reflect the position or policy of the U.S. Government, and no official endorsement should be inferred. C.J.S. was supported by the NIH National Institute of General Medical Sciences (grant T32 GM008042) and a David Geffen Medical Scholarship. H.K. was supported by a National Science Foundation graduate research fellowship (grant DGE-1144469). Y.E.A. was supported by the Israel Science Foundation (grant 1105/20) and is the incumbent Sygnet Career Development Chair for Bioinformatics. M.B.E. is a Howard Hughes Medical Institute investigator. Author contributions: C.J.S., A.M., Y.E.A., and M.B.E. conceived and designed the research. J.M.L., H.K., M.A.L., and Y.E.A. performed experiments. C.J.S., A.M., A.Y., J.B., and Y.E.A. developed mathematical models and performed computational analysis. C.J.S., A.M., Y.E.A., and M.B.E. wrote the manuscript. Declaration of interests: C.J.S. is presently at the University of Illinois College of Medicine. H.K. is currently at the Department of Biomedical Engineering at Boston University. The authors have a patent related to this work (U.S. patent number 10,527,631). Data and code availability: All data have been deposited at the CaltechDATA research data repository (https://doi.org/10.22002/D1.1692) and are publicly available as of the date of publication. The DOI is listed in the key resources table. All original code has been deposited at GitHub (https://github.com/christinasu/PromiSys) as well as the CaltechDATA research data repository (https://doi.org/10.22002/D1.20047) and is publicly available as of the date of publication. The DOI is listed in the key resources table. Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Attached Files

Published - 1-s2.0-S2405471222001284-main.pdf

Submitted - 2020.12.08.412643v1.full.pdf

Supplemental Material - 1-s2.0-S2405471222001284-mmc1.pdf


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