Evidence map›Paper›PMID 29745863›Full record

ArticleBMC bioinformatics2018

Generation and comparative genomics of synthetic dengue viruses.

Eli Goz, Yael Tsalenchuck, Rony Oren Benaroya, Zohar Zafrir, Shimshi Atar, Tahel Altman, Justin Julander, Tamir Tuller

Abstract read
In one paragraph

Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

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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

1 citing paper in PubMed.

  1. 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

8 authors.

Eli GozDepartment of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.
Yael TsalenchuckSynVaccineLtd. Ramat Hachayal, Tel Aviv, Israel.
Rony Oren BenaroyaSynVaccineLtd. Ramat Hachayal, Tel Aviv, Israel.
Zohar ZafrirDepartment of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.
Shimshi AtarDepartment of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel.
Tahel AltmanSynVaccineLtd. Ramat Hachayal, Tel Aviv, Israel.
Justin JulanderInstitute for Antiviral Research, Utah State University, Logan, UT, USA.
Tamir TullerDepartment of Biomedical Engineering, Tel Aviv University, Tel Aviv, Israel. tamirtul@post.tau.ac.il.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSynthetic virology is an important multidisciplinary scientific field, with emerging applications in biotechnology and medicine, aiming at developing methods to generate and engineer synthetic viruses. In particular, many of the RNA viruses, including among others the Dengue and Zika, are widespread pathogens of significant importance to human health. The ability to design and synthesize such viruses may contribute to exploring novel approaches for developing vaccines and virus based therapies.

resultsHere we develop a full multidisciplinary pipeline for generation and analysis of synthetic RNA viruses and specifically apply it to Dengue virus serotype 2 (DENV-2). The major steps of the pipeline include comparative genomics of endogenous and synthetic viral strains. Specifically, we show that although the synthetic DENV-2 viruses were found to have lower nucleotide variability, their phenotype, as reflected in the study of the AG129 mouse model morbidity, RNA levels, and neutralization antibodies, is similar or even more pathogenic in comparison to the wildtype master strain. Additionally, the highly variable positions, identified in the analyzed DENV-2 population, were found to overlap with less conserved homologous positions in Zika virus and other Dengue serotypes. These results may suggest that synthetic DENV-2 could enhance virulence if the correct sequence is selected.

conclusionsThe approach reported in this study can be used to generate and analyze synthetic RNA viruses both on genotypic and on phenotypic level. It could be applied for understanding the functionality and the fitness effects of any set of mutations in viral RNA and for editing RNA viruses for various target applications.

Indexed as

GenomicsAnimalsBase SequenceChlorocebus aethiopsDengueDengue VirusHigh-Throughput Nucleotide SequencingHumansMiceOligodeoxyribonucleotidesPolymorphism, Single NucleotideSerogroupVero CellsCPG-oligonucleotideOligodeoxyribonucleotidesFlavivirusRNA virusesSilent and non-synonymous mutationsSynthetic virologyViral comparative genomicsViral evolution

Identifiers

PMID29745863
PMCPMC5998877

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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.