Evidence map›Paper›PMID 35140557›Full record

ArticleEngineering in life sciences2022

Exploitation of the ribosomal protein L10 R98S mutation to enhance recombinant protein production in mammalian cells.

Benno Verbelen, Tiziana Girardi, Sergey O Sulima, Stijn Vereecke, Paulien Verstraete, Jelle Verbeeck, Jonathan Royaert, Sonia Cinque, Lorenzo Montanaro, Marianna Penzo and 7 more

Open access · goldAbstract read
In one paragraph

Article in Engineering in life sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 54% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 3 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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

17 authors at 7 institutions in 5 countries.

Benno VerbelenLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.
Tiziana GirardiLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.
Sergey O SulimaLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.
Stijn VereeckeLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.ORCID https://orcid.org/0000-0001-8414-8907
Paulien VerstraeteLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.
Jelle VerbeeckLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.
Jonathan RoyaertLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.
Sonia CinqueLaboratory for RNA Cancer Biology Department of Oncology KU Leuven Leuven Belgium.
Lorenzo MontanaroIRCCS Azienda Ospedaliero-Universitaria di Bologna Bologna Italy.
Marianna PenzoDepartment of Experimental Diagnostic and Specialty Medicine and Center for Applied Biomedical Research (CRBA) Alma Mater Studiorum-University of Bologna Bologna Italy.ORCID https://orcid.org/0000-0002-1738-9767
Maya ImbrechtsLaboratory for Therapeutic and Diagnostic Antibodies Department of Pharmaceutical and Pharmacological Sciences KU Leuven Leuven Belgium.
Nick GeukensLaboratory for Therapeutic and Diagnostic Antibodies Department of Pharmaceutical and Pharmacological Sciences KU Leuven Leuven Belgium.
Thomas GeuensSimabs Diepenbeek Belgium.
Koen DierckxSimabs Diepenbeek Belgium.
Daniele PepeLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.
Kim KampenLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.
Kim De KeersmaeckerLaboratory for Disease Mechanisms in Cancer Department of Oncology KU Leuven Leuven Belgium.ORCID https://orcid.org/0000-0002-7420-9531
VIB-KU Leuven Center for Cancer Biology · BEAndrome (Belgium) · BEResearch & Diagnostic Antibodies (United States) · USAzienda USL di Bologna · ITHelmholtz Zentrum München · DEMaastricht University · NLUniversity of Bologna · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mammalian cells are commonly used to produce recombinant protein therapeutics, but suffer from a high cost per mg of protein produced. There is therefore great interest in improving protein yields to reduce production cost. We present an entirely novel approach to reach this goal through direct engineering of the cellular translation machinery by introducing the R98S point mutation in the catalytically essential ribosomal protein L10 (RPL10-R98S). Our data support that RPL10-R98S enhances translation levels and fidelity and reduces proteasomal activity in lymphoid Ba/F3 and Jurkat cell models. In HEK293T cells cultured in chemically defined medium, knock-in of RPL10-R98S was associated with a 1.7- to 2.5-fold increased production of four transiently expressed recombinant proteins and 1.7-fold for one out of two stably expressed proteins. In CHO-S cells, eGFP reached a 2-fold increased expression under stable but not transient conditions, but there was no production benefit for monoclonal antibodies. The RPL10-R98S associated production gain thus depends on culture conditions, cell type, and the nature of the expressed protein. Our study demonstrates the potential for using a ribosomal protein mutation for pharmaceutical protein production gains, and further research on how various factors influence RPL10-R98S phenotypes can maximize its exploitability for the mammalian protein production industry.

Indexed as

genome engineeringrecombinant protein productionribosomal protein mutationRPL10

Identifiers

PMID35140557
PMCPMC8811726
OpenAlexW4205376585

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.