Evidence map›Paper›PMID 36735673›Full record

ArticlePloS one2023

Transfer of knowledge from model organisms to evolutionarily distant non-model organisms: The coral Pocillopora damicornis membrane signaling receptome.

Lokender Kumar, Nathanael Brenner, Samuel Sledzieski, Monsurat Olaosebikan, Liza M Roger, Matthew Lynn-Goin, Roshan Klein-Seetharaman, Bonnie Berger, Hollie Putnam, Jinkyu Yang and 5 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.2field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Gobind's last graduate student.Biophysical reviews · 2023
    Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 7 institutions in 1 country.

Lokender KumarDepartment of Chemistry, Colorado School of Mines, Golden, CO, United States of America.
Nathanael BrennerDepartment of Chemistry, Colorado School of Mines, Golden, CO, United States of America.
Samuel SledzieskiMIT Computer Science & Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, United States of America.ORCID 0000-0002-0170-3029
Monsurat OlaosebikanDepartment of Computer Science, Tufts University, Medford, MA, United States of America.ORCID 0000-0002-1789-5336
Liza M RogerDepartment of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, United States of America.ORCID 0000-0003-2274-8311
Matthew Lynn-GoinDepartment of Chemistry, Colorado School of Mines, Golden, CO, United States of America.
Roshan Klein-SeetharamanYale University, New Haven, CT, United States of America.
Bonnie BergerMIT Computer Science & Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, United States of America.
Hollie PutnamDepartment of Biological Sciences, University of Rhode Island, South Kingstown, RI, United States of America.
Jinkyu YangDepartment of Department of Aeronautics & Astronautics, University of Washington, Seattle, WA, United States of America.
Nastassja A LewinskiDepartment of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA, United States of America.ORCID 0000-0002-9335-9949
Rohit SinghMIT Computer Science & Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, United States of America.
Noah M DanielsDepartment of Computer Science and Statistics, University of Rhode Island, South Kingstown, RI, United States of America.
Lenore CowenDepartment of Computer Science, Tufts University, Medford, MA, United States of America.
Judith Klein-SeetharamanDepartment of Chemistry, Colorado School of Mines, Golden, CO, United States of America.ORCID 0000-0002-4892-6828
Colorado School of Mines · USMassachusetts Institute of Technology · USTufts University · USUniversity of Rhode Island · USVirginia Commonwealth University · USUniversity of Washington · USYale University · US

Funding

Manifold representations and active learning for 21 st century biologyR35GM141861 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BERGER, BONNIE · 2021 to 2025
$1.9M
NIGMS NIH HHS R35 GM141861
6 · The paper itself

Abstract

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.

Indexed as

AnthozoaReceptors, G-Protein-CoupledSignal TransductionAnimalsGenomeHumansModels, AnimalReceptors, G-Protein-Coupled

Identifiers

PMID36735673
PMCPMC9897584
OpenAlexW4319058224

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.