Evidence map›Paper›PMID 39068333›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Simultaneous Plate-Reader Characterization of Promoter Activity and Cell Growth in Engineered Mammalian Cells.

Alice Grob, Chiara Enrico Bena, Chileab Redwood-Sawyerr, Karen Polizzi, Carla Bosia, Mark Isalan, Francesca Ceroni

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Article in Methods in molecular biology (Clifton, N.J.), 2024. 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
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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

7 authors.

Alice GrobDepartment of Chemical Engineering, Imperial College London, London, UK.
Chiara Enrico BenaItalian Institute for Genomic Medicine, Torino, Italy.
Chileab Redwood-SawyerrDepartment of Chemical Engineering, Imperial College London, London, UK.
Karen PolizziDepartment of Chemical Engineering, Imperial College London, London, UK.
Carla BosiaItalian Institute for Genomic Medicine, Torino, Italy.
Mark IsalanImperial College Centre for Synthetic Biology, Imperial College London, London, UK.
Francesca CeroniDepartment of Chemical Engineering, Imperial College London, London, UK. f.ceroni@imperial.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council BB/V00882X/1
6 · The paper itself

Abstract

Automated high-throughput methods that support tracking of mammalian cell growth are currently needed to advance cell line characterization and identification of desired genetic components required for cell engineering. Here, we describe a high-throughput noninvasive assay based on plate reader measurements. The assay relies on the change in absorbance of the pH indicator phenol red. We show that its basic and acidic absorbance profiles can be converted into a cell growth index consistent with cell count profiles, and that, by adopting a computational pipeline and calibration measurements, it is possible to identify a conversion that enables prediction of cell numbers from plate measurements alone. The assay is suitable for growth characterization of both suspension and adherent cell lines when these are grown under different environmental conditions and treated with chemotherapeutic drugs. The method also supports characterization of stably engineered cell lines and identification of desired promoters based on fluorescence output.

Indexed as

Cell ProliferationPromoter Regions, GeneticAnimalsCell Culture TechniquesCell EngineeringCell LineHigh-Throughput Screening AssaysHumansHydrogen-Ion ConcentrationPhenolsulfonphthaleinPhenolsulfonphthaleinComputational data processingHigh throughput assayMammalian cell engineeringMammalian cell growth trackingPlate reader measurements

Identifiers

PMID39068333

What OpenQuestion holds

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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.