Evidence map›Paper›PMID 35228567›Full record

ArticleScientific reports2022

Comparative systeomics to elucidate physiological differences between CHO and SP2/0 cell lines.

Deniz Demirhan, Amit Kumar, Jie Zhu, Pi Camilla Poulsen, Natalia I Majewska, Yinong Sebastian, Raghothama Chaerkady, Wen Yu, Wei Zhu, Li Zhuang and 6 more

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

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 37% 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, 8 citations in OpenAlex.

  1. Review
  2. Review
  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

16 authors at 7 institutions in 2 countries.

Deniz DemirhanDepartment of Natural Sciences, Acibadem Mehmet Ali Aydınlar University, Istanbul, Turkey. Deniz.Demirhan@acibadem.edu.tr.
Amit KumarDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.
Jie ZhuCell Culture and Fermentation Sciences, BioPharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, MD, USA.
Pi Camilla PoulsenProtein Science, Antibody Discovery and Protein Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA.
Natalia I MajewskaDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.
Yinong SebastianTranslational Science, AstraZeneca, Gaithersburg, MD, USA.
Raghothama ChaerkadyProtein Science, Antibody Discovery and Protein Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA.
Wen YuInformatics, Data Science and Artificial Intelligence, R&D, AstraZeneca, Gaithersburg, MD, USA.
Wei ZhuTranslational Science, AstraZeneca, Gaithersburg, MD, USA.
Li ZhuangProtein Science, Antibody Discovery and Protein Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA.
Punit ShahBERG, Framingham, MA, 01701, USA.
Kristen LekstromProtein Science, Antibody Discovery and Protein Engineering, R&D, AstraZeneca, Gaithersburg, MD, USA.
Robert N ColeMass Spectrometry and Proteomics Facility, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Hui ZhangDepartment of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Michael J BetenbaughDepartment of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA.
Michael A BowenAllogene Therapeutics, South San Francisco, CA, USA.
AstraZeneca (United States) · USJohns Hopkins University · USProtein Express (United States) · USAllogene Therapeutics (United States) · USFramingham State University · USJohns Hopkins Medicine · USKent Hastanesi · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Omics-based tools were coupled with bioinformatics for a systeomics analysis of two biopharma cell types: Chinese hamster ovary (M-CHO and CHO-K1) and SP2/0. Exponential and stationary phase samples revealed more than 10,000 transcripts and 6000 proteins across these two manufacturing cell lines. A statistical comparison of transcriptomics and proteomics data identified downregulated genes involved in protein folding, protein synthesis and protein metabolism, including PPIA-cyclophilin A, HSPD1, and EIF3K, in M-CHO compared to SP2/0 while cell cycle and actin cytoskeleton genes were reduced in SP2/0. KEGG pathway comparisons revealed glycerolipids, glycosphingolipids, ABC transporters, calcium signaling, cell adhesion, and secretion pathways depleted in M-CHO while retinol metabolism was upregulated. KEGG and IPA also indicated apoptosis, RNA degradation, and proteosomes enriched in CHO stationary phase. Alternatively, gene ontology analysis revealed an underrepresentation in ion and potassium channel activities, membrane proteins, and secretory granules including Stxbpt2, Syt1, Syt9, and Cma1 proteins in M-CHO. Additional enrichment strategies involving ultracentrifugation, biotinylation, and hydrazide chemistry identified over 4000 potential CHO membrane and secretory proteins, yet many secretory and membrane proteins were still depleted. This systeomics pipeline has revealed bottlenecks and potential opportunities for cell line engineering in CHO and SP2/0 to improve their production capabilities.

Indexed as

ProteomicsSecretory PathwayAnimalsCHO CellsCricetinaeCricetulusMembrane ProteinsMembrane Proteins

Identifiers

PMID35228567
PMCPMC8885639
OpenAlexW4214841430

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Registered trials

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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.