Evidence map›Paper›PMID 42634449›Full record

ArticleBiotechnology journal2026

Expanding Transposase Technology to Regulatory Noncoding RNAs for Stable Expression in CHO Cells.

Sonja Lochmueller, Linus Weiss, Kerstin Otte

Abstract read
In one paragraph

Article in Biotechnology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Sonja LochmuellerUlm University, Ulm, Germany.ORCID https://orcid.org/0009-0000-0810-5913
Linus WeissUlm University, Ulm, Germany.ORCID https://orcid.org/0000-0002-6905-5283
Kerstin OtteInstitute for Applied Biotechnology, University of Applied Sciences Biberach, Biberach, Germany.

Funding

Federal Ministry of Education and Research 13FH036KB2
6 · The paper itself

Abstract

Stable expression of regulatory non-coding RNAs enables targeted cell engineering in Chinese hamster ovary (CHO) cells but commonly relies on random integration, resulting in variable expression. Here, we establish a transposase-mediated platform for stable microRNA (miRNA) expression in CHO cells and demonstrate the first application of a DNA transposon system for long-term miRNA genome integration. Using miR-3096b-5p, we compared piggyBac-mediated integration with conventional random integration in antibody-producing CHO cells. Transposase-mediated integration enabled rapid generation of stable cell pools with higher fractions of GFP-expressing cells. Both integration strategies supported comparable growth, viability, and antibody production in batch cultures, indicating that transposase-mediated miRNA integration does not compromise bioprocess performance. At the molecular level, transposase-mediated integration resulted in significantly higher transgene copy numbers and markedly increased miRNA expression, translating into stronger and more consistent regulation of the target genes Fuk and Gmds. By combining high integration efficiency and expression stability with the regulatory potential of miRNAs, this approach expands the applicability of transposase systems beyond protein-coding transgenes and provides a robust platform for precise and durable post-transcriptional gene regulation in CHO cell engineering.

Indexed as

Cell EngineeringMicroRNAsRNA, UntranslatedTransposasesAnimalsCHO CellsCricetinaeCricetulusDNA Transposable ElementsGene Expression RegulationTransgenesDNA Transposable ElementsMicroRNAsRNA, UntranslatedTransposasescell engineeringCHOmicroRNArandom integrationtransposase‐mediated integration

Identifiers

PMID42634449
PMCPMC13501212

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.