Evidence map›Paper›PMID 27581878›Full record

ArticleProceedings. Biological sciences2016

Using viromes to predict novel immune proteins in non-model organisms.

Steven D Quistad, Yan Wei Lim, Genivaldo Gueiros Z Silva, Craig E Nelson, Andreas F Haas, Linda Wegley Kelly, Robert A Edwards, Forest L Rohwer

Open access · hybridAbstract read
In one paragraph

Article in Proceedings. Biological sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 27% 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

4 citing papers in PubMed, 8 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Steven D QuistadDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA steven.quistad@gmail.com.ORCID 0000-0003-4384-8100
Yan Wei LimDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA.
Genivaldo Gueiros Z SilvaComputational Science Research Center, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA.
Craig E NelsonCenter for Microbial Oceanography: Research and Education, Department of Oceanography and Sea Grant College Program, School of Ocean and Earth Science and Technology, University of Hawai'i at Mānoa, HI 96822, USA.
Andreas F HaasDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA.
Linda Wegley KellyDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA.
Robert A EdwardsDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA Computational Science Research Center, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA Department of Computer Science, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA.
Forest L RohwerDepartment of Biology, San Diego State University, 5500 Campanile Drive, San Diego 92182, USA.
San Diego State University · USUniversity of Hawaiʻi at Mānoa · US

Funding

Hydra as an Antiviral Innate Immunity Model SystemR21AI094534 · NIAID · SAN DIEGO STATE UNIVERSITY · PI ROHWER, FOREST L · 2011 to 2012
$411k
NIAID NIH HHS R21 AI094534
6 · The paper itself

Abstract

Immunity is mostly studied in a few model organisms, leaving the majority of immune systems on the planet unexplored. To characterize the immune systems of non-model organisms alternative approaches are required. Viruses manipulate host cell biology through the expression of proteins that modulate the immune response. We hypothesized that metagenomic sequencing of viral communities would be useful to identify both known and unknown host immune proteins. To test this hypothesis, a mock human virome was generated and compared to the human proteome using tBLASTn, resulting in 36 proteins known to be involved in immunity. This same pipeline was then applied to reef-building coral, a non-model organism that currently lacks traditional molecular tools like transgenic animals, gene-editing capabilities, and in vitro cell cultures. Viromes isolated from corals and compared with the predicted coral proteome resulted in 2503 coral proteins, including many proteins involved with pathogen sensing and apoptosis. There were also 159 coral proteins predicted to be involved with coral immunity but currently lacking any functional annotation. The pipeline described here provides a novel method to rapidly predict host immune components that can be applied to virtually any system with the potential to discover novel immune proteins.

Indexed as

MetagenomicsAnimalsAnthozoaHumansProteomeVirusesProteomecnidarianscomparative genomicscoralevolutionimmunityviruses

Identifiers

PMID27581878
PMCPMC5013795
OpenAlexW2509473586

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.