TY - JOUR
T1 - Transfer of knowledge from model organisms to evolutionarily distant non-model organisms
T2 - The coral Pocillopora damicornis membrane signaling receptome
AU - Kumar, Lokender
AU - Brenner, Nathanael
AU - Sledzieski, Samuel
AU - Olaosebikan, Monsurat
AU - Roger, Liza M.
AU - Lynn-Goin, Matthew
AU - Klein-Seetharaman, Roshan
AU - Berger, Bonnie
AU - Putnam, Hollie
AU - Yang, Jinkyu
AU - Lewinski, Nastassja A.
AU - Singh, Rohit
AU - Daniels, Noah M.
AU - Cowen, Lenore
AU - Klein-Seetharaman, Judith
N1 - Funding Information:
This work was supported by NIH grant number R35GM141861, awarded to R.S., S.S., and B.B., the National Science Foundation Office of Advanced Cyberinfrastructure award numbers 1940169 to J.K.S., 1939263 to L.C., 1939699 to N. L., 1939795 to H.P., 1939249 to J.K.Y., National Science Foundation Division of Computing and Communication Foundations award number 2029543 to J.K.S., National Science Foundation Graduate Research Fellowship 1745302 to SS and the National Institute of Food and Agriculture award number 1017848 to H.P. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2023 Kumar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2023/2
Y1 - 2023/2
N2 - With the ease of gene sequencing and the technology available to study and manipulate non-model organisms, the extension of the methodological toolbox required to translate our understanding of model organisms to non-model organisms has become an urgent problem. For example, mining of large coral and their symbiont sequence data is a challenge, but also provides an opportunity for understanding functionality and evolution of these and other non-model organisms. Much more information than for any other eukaryotic species is available for humans, especially related to signal transduction and diseases. However, the coral cnidarian host and human have diverged over 700 million years ago and homologies between proteins in the two species are therefore often in the gray zone, or at least often undetectable with traditional BLAST searches. We introduce a two-stage approach to identifying putative coral homologues of human proteins. First, through remote homology detection using Hidden Markov Models, we identify candidate human homologues in the cnidarian genome. However, for many proteins, the human genome alone contains multiple family members with similar or even more divergence in sequence. In the second stage, therefore, we filter the remote homology results based on the functional and structural plausibility of each coral candidate, shortlisting the coral proteins likely to have conserved some of the functions of the human proteins. We demonstrate our approach with a pipeline for mapping membrane receptors in humans to membrane receptors in corals, with specific focus on the stony coral, P. damicornis. More than 1000 human membrane receptors mapped to 335 coral receptors, including 151 G protein coupled receptors (GPCRs). To validate specific sub-families, we chose opsin proteins, representative GPCRs that confer light sensitivity, and Toll-like receptors, representative non-GPCRs, which function in the immune response, and their ability to communicate with microorganisms. Through detailed structure-function analysis of their ligand-binding pockets and downstream signaling cascades, we selected those candidate remote homologues likely to carry out related functions in the corals. This pipeline may prove generally useful for other non-model organisms, such as to support the growing field of synthetic biology.
AB - With the ease of gene sequencing and the technology available to study and manipulate non-model organisms, the extension of the methodological toolbox required to translate our understanding of model organisms to non-model organisms has become an urgent problem. For example, mining of large coral and their symbiont sequence data is a challenge, but also provides an opportunity for understanding functionality and evolution of these and other non-model organisms. Much more information than for any other eukaryotic species is available for humans, especially related to signal transduction and diseases. However, the coral cnidarian host and human have diverged over 700 million years ago and homologies between proteins in the two species are therefore often in the gray zone, or at least often undetectable with traditional BLAST searches. We introduce a two-stage approach to identifying putative coral homologues of human proteins. First, through remote homology detection using Hidden Markov Models, we identify candidate human homologues in the cnidarian genome. However, for many proteins, the human genome alone contains multiple family members with similar or even more divergence in sequence. In the second stage, therefore, we filter the remote homology results based on the functional and structural plausibility of each coral candidate, shortlisting the coral proteins likely to have conserved some of the functions of the human proteins. We demonstrate our approach with a pipeline for mapping membrane receptors in humans to membrane receptors in corals, with specific focus on the stony coral, P. damicornis. More than 1000 human membrane receptors mapped to 335 coral receptors, including 151 G protein coupled receptors (GPCRs). To validate specific sub-families, we chose opsin proteins, representative GPCRs that confer light sensitivity, and Toll-like receptors, representative non-GPCRs, which function in the immune response, and their ability to communicate with microorganisms. Through detailed structure-function analysis of their ligand-binding pockets and downstream signaling cascades, we selected those candidate remote homologues likely to carry out related functions in the corals. This pipeline may prove generally useful for other non-model organisms, such as to support the growing field of synthetic biology.
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U2 - 10.1371/journal.pone.0270965
DO - 10.1371/journal.pone.0270965
M3 - Article
C2 - 36735673
AN - SCOPUS:85147457249
SN - 1932-6203
VL - 18
JO - PLoS One
JF - PLoS One
IS - 2 February
M1 - e0270965
ER -