Evidence map›Paper›PMID 37272445›Full record

ArticleBiotechnology and bioengineering2023

CHOmpact: A reduced metabolic model of Chinese hamster ovary cells with enhanced interpretability.

Ioscani Jiménez Del Val, Sarantos Kyriakopoulos, Simone Albrecht, Henning Stockmann, Pauline M Rudd, Karen M Polizzi, Cleo Kontoravdi

Open access · hybridAbstract read
In one paragraph

Article in Biotechnology and bioengineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Towards advanced bioprocess optimization: A multiscale modelling approach.Computational and structural biotechnology journal · 2023
    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

7 authors at 4 institutions in 2 countries.

Ioscani Jiménez Del ValSchool of Chemical & Bioprocess Engineering, University College Dublin, Dublin, Ireland.ORCID 0000-0001-9289-0191
Sarantos KyriakopoulosManufacturing Science and Technology, BioMarin Pharmaceutical, Cork, Ireland, Ireland.
Simone AlbrechtGlycoScience Group, National Institute for Bioprocessing Research and Training, Dublin, Ireland.
Henning StockmannGlycoScience Group, National Institute for Bioprocessing Research and Training, Dublin, Ireland.
Pauline M RuddGlycoScience Group, National Institute for Bioprocessing Research and Training, Dublin, Ireland.
Karen M PolizziDepartment of Chemical Engineering, Imperial College London, London, UK.ORCID 0000-0001-5435-2667
Cleo KontoravdiDepartment of Chemical Engineering, Imperial College London, London, UK.
National Institute for Bioprocessing Research and Training · IEImperial College London · GBBioMarin (Ireland) · IEUniversity College Dublin · IE

Funding

Biotechnology and Biological Sciences Research Council BB/I017011/1
6 · The paper itself

Abstract

Metabolic modeling has emerged as a key tool for the characterization of biopharmaceutical cell culture processes. Metabolic models have also been instrumental in identifying genetic engineering targets and developing feeding strategies that optimize the growth and productivity of Chinese hamster ovary (CHO) cells. Despite their success, metabolic models of CHO cells still present considerable challenges. Genome-scale metabolic models (GeMs) of CHO cells are very large (>6000 reactions) and are difficult to constrain to yield physiologically consistent flux distributions. The large scale of GeMs also makes the interpretation of their outputs difficult. To address these challenges, we have developed CHOmpact, a reduced metabolic network that encompasses 101 metabolites linked through 144 reactions. Our compact reaction network allows us to deploy robust, nonlinear optimization and ensure that the computed flux distributions are physiologically consistent. Furthermore, our CHOmpact model delivers enhanced interpretability of simulation results and has allowed us to identify the mechanisms governing shifts in the anaplerotic consumption of asparagine and glutamate as well as an important mechanism of ammonia detoxification within mitochondria. CHOmpact, thus, addresses key challenges of large-scale metabolic models and will serve as a platform to develop dynamic metabolic models for the control and optimization of biopharmaceutical cell culture processes.

Indexed as

GenomeMetabolic Networks and PathwaysAnimalsCHO CellsComputer SimulationCricetinaeCricetulusbiopharmaceuticalsChinese hamster ovary cellsflux balance analysisnonlinear optimization

Identifiers

PMID37272445
PMCPMC10952303
OpenAlexW4379377227

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.