Evidence map›Paper›PMID 31664102›Full record

ArticleScientific reports2019

Effects of codon optimization on coagulation factor IX translation and structure: Implications for protein and gene therapies.

Aikaterini Alexaki, Gaya K Hettiarachchi, John C Athey, Upendra K Katneni, Vijaya Simhadri, Nobuko Hamasaki-Katagiri, Puja Nanavaty, Brian Lin, Kazuyo Takeda, Darón Freedberg and 13 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
43citing papers in PubMed, 1 pooled it
3.1field-weighted citation impact, top 7% 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

43 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.

  1. Pooled it
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  4. Intra-CNS AAV9-Molecular therapy. Advances · 2026
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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

23 authors at 7 institutions in 1 country.

Aikaterini AlexakiCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Gaya K HettiarachchiCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
John C AtheyCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Upendra K KatneniCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Vijaya SimhadriCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Nobuko Hamasaki-KatagiriCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Puja NanavatyCenter for Gene Regulation in Health and Disease, Cleveland State University, Cleveland, OH, USA.
Brian LinCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Kazuyo TakedaCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Darón FreedbergCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.ORCID http://orcid.org/0000-0003-1991-5174
Dougald MonroeUniversity of North Carolina at Chapel hill, Chapel hill, NC, USA.ORCID http://orcid.org/0000-0002-0493-2943
Joseph R McGillCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.ORCID http://orcid.org/0000-0002-3369-3822
Robert PetersBioverativ, Cambridge, MA, USA.
Jacob M KamesCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
David D HolcombCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Ryan C HuntCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Zuben E SaunaCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.ORCID http://orcid.org/0000-0001-8202-5188
Amy GelinasSomaLogic, Inc, Boulder, CO, USA.
Nebojsa JanjicSomaLogic, Inc, Boulder, CO, USA.
Michael DiCuccioNational Center of Biotechnology Information, National Institutes of Health, Bethesda, MD, USA.
Haim BarDepartment of Statistics, University of Connecticut, Storrs, CT, USA.
Anton A KomarCenter for Gene Regulation in Health and Disease, Cleveland State University, Cleveland, OH, USA.ORCID http://orcid.org/0000-0003-4188-0633
Chava Kimchi-SarfatyCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA. Chava.kimchi-sarfaty@fda.hhs.gov.
Center for Biologics Evaluation and Research · USCleveland State University · USSomaLogic (United States) · USNational Institutes of Health · USNuvera Biosciences (United States) · USUniversity of Connecticut · USUniversity of North Carolina at Chapel Hill · US

Funding

Understanding the impact of disease causing mutations in FIXR15HL121779 · NHLBI · CLEVELAND STATE UNIVERSITY · PI KOMAR, ANTON A. · 2014 to 2014
$437k
NHLBI NIH HHS R15 HL121779U.S. Department of Health & Human Services | NIH | Office of Extramural Research, National Institutes of Health (OER) HL121779
6 · The paper itself

Abstract

Synonymous codons occur with different frequencies in different organisms, a phenomenon termed codon usage bias. Codon optimization, a common term for a variety of approaches used widely by the biopharmaceutical industry, involves synonymous substitutions to increase protein expression. It had long been presumed that synonymous variants, which, by definition, do not alter the primary amino acid sequence, have no effect on protein structure and function. However, a critical mass of reports suggests that synonymous codon variations may impact protein conformation. To investigate the impact of synonymous codons usage on protein expression and function, we designed an optimized coagulation factor IX (FIX) variant and used multiple methods to compare its properties to the wild-type FIX upon expression in HEK293T cells. We found that the two variants differ in their conformation, even when controlling for the difference in expression levels. Using ribosome profiling, we identified robust changes in the translational kinetics of the two variants and were able to identify a region in the gene that may have a role in altering the conformation of the protein. Our data have direct implications for codon optimization strategies, for production of recombinant proteins and gene therapies.

Indexed as

CodonGenetic TherapyProtein BiosynthesisFactor IXGenetic CodeHEK293 CellsHumansProtein ConformationCodonFactor IX

Identifiers

PMID31664102
PMCPMC6820528
OpenAlexW2982639824

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.