Evidence map›Paper›PMID 35737825›Full record

ArticlemAbs

Engineering death resistance in CHO cells for improved perfusion culture.

Michael A MacDonald, Matthias Nöbel, Verónica S Martínez, Kym Baker, Evan Shave, Peter P Gray, Stephen Mahler, Trent Munro, Lars K Nielsen, Esteban Marcellin

Abstract read
In one paragraph

Article in mAbs. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Cell Engineering for Increasing Production of Recombinant Proteins in Mammalian Cells.BioDrugs : clinical immunotherapeutics, biopharmaceuticals and gene therapy · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
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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

10 authors.

Michael A MacDonaldARC Training Centre for Biopharmaceutical Innovation, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Australia.ORCID 0000-0002-2123-096X
Matthias NöbelARC Training Centre for Biopharmaceutical Innovation, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Australia.ORCID 0000-0001-6996-6776
Verónica S MartínezARC Training Centre for Biopharmaceutical Innovation, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Australia.
Kym BakerThermo Fisher Scientific, Woolloongabba, Brisbane, Australia.
Evan ShaveThermo Fisher Scientific, Woolloongabba, Brisbane, Australia.
Peter P GrayARC Training Centre for Biopharmaceutical Innovation, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Australia.
Stephen MahlerARC Training Centre for Biopharmaceutical Innovation, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Australia.ORCID 0000-0003-2403-1437
Trent MunroARC Training Centre for Biopharmaceutical Innovation, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Australia.ORCID 0000-0003-1987-2020
Lars K NielsenARC Training Centre for Biopharmaceutical Innovation, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Australia.
Esteban MarcellinARC Training Centre for Biopharmaceutical Innovation, Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, Australia.ORCID 0000-0003-3173-7956

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The reliable and cost-efficient manufacturing of monoclonal antibodies (mAbs) is essential to fulfil their ever-growing demand. Cell death in bioreactors reduces productivity and product quality, and is largely attributed to apoptosis. In perfusion bioreactors, this leads to the necessity of a bleed stream, which negatively affects the overall process economy. To combat this limitation, death-resistant Chinese hamster ovary cell lines were developed by simultaneously knocking out the apoptosis effector proteins Bak1, Bax, and Bok with CRISPR technology. These cell lines were cultured in fed-batch and perfusion bioreactors and compared to an unmodified control cell line. In fed-batch, the death-resistant cell lines showed higher cell densities and longer culture durations, lasting nearly a month under standard culture conditions. In perfusion, the death-resistant cell lines showed slower drops in viability and displayed an arrest in cell division after which cell size increased instead. Pertinently, the death-resistant cell lines demonstrated the ability to be cultured for several weeks without bleed, and achieved similar volumetric productivities at lower cell densities than that of the control cell line. Perfusion culture reduced fragmentation of the mAb produced, and the death-resistant cell lines showed increased glycosylation in the light chain in both bioreactor modes. These data demonstrate that rationally engineered death-resistant cell lines are ideal for mAb production in perfusion culture, negating the need to bleed the bioreactor whilst maintaining product quantity and quality.

Indexed as

Antibodies, MonoclonalBioreactorsAnimalsBatch Cell Culture TechniquesCHO CellsCricetinaeCricetulusPerfusionAntibodies, Monoclonalapoptosisbiopharmaceutical manufacturingbioprocessingcell line developmentgenetic engineeringmAb glycosylationmAb manufacturingmonoclonal antibody manufacturingperfusion

Identifiers

PMID35737825
PMCPMC9235890

What OpenQuestion holds

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LicenceCC BY-NC
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.