ArticleBMC bioinformatics2020
Inferring time-dependent population growth rates in cell cultures undergoing adaptation.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
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- Fibronectin and vitronectin alleviate adipose-derived stem cells senescence during long-term culture through the AKT/MDM2/P53 pathway.Scientific reports · 2024Article
- Zebrafish-A Suitable Model for Rapid Translation of Effective Therapies for Pediatric Cancers.Cancers · 2024Review
- Glucose Metabolism as a Potential Therapeutic Target in Cytarabine-Resistant Acute Myeloid Leukemia.Pharmaceutics · 2024Article
- Novel cryopreservation medium for enhanced stability of T cells at -80°C.Frontiers in hematology · 2024Article
- Characterization of Razi Bovine Kidney (RBK) Cell Line as a Sensitive Cell to Bovine Herpesvirus-1 (BoHV-1).Archives of Razi Institute · 2023Article
- Muscle denervation promotes functional interactions between glial and mesenchymal cells through NGFR and NGF.iScience · 2023Article
- A village in a dish model system for population-scale hiPSC studies.Nature communications · 2023Article
- Pre-Treatment of Swine Oviductal Epithelial Cells with Progesterone Increases the Sperm Fertilizing Ability in an IVF Model.Animals : an open access journal from MDPI · 2022Article
- Rotating between ponatinib and imatinib temporarily increases the efficacy of imatinib as shown in a chronic myeloid leukaemia model.Scientific reports · 2022Article
- Combating drug resistance in acute myeloid leukaemia by drug rotations: the effects of quizartinib and pexidartinib.Cancer cell international · 2021Article
- Immunophenotypic characterization and clinical relevance of passage number in umbilical cord mesenchymal stromal cells: A review.Cell transplantationReview
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Authors and funding
2 authors.
Funding
Abstract
backgroundThe population growth rate is an important characteristic of any cell culture. During sustained experiments, the growth rate may vary due to competition or adaptation. For instance, in presence of a toxin or a drug, an increasing growth rate indicates that the cells adapt and become resistant. Consequently, time-dependent growth rates are fundamental to follow on the adaptation of cells to a changing evolutionary landscape. However, as there are no tools to calculate the time-dependent growth rate directly by cell counting, it is common to use only end point measurements of growth rather than tracking the growth rate continuously.
resultsWe present a computer program for inferring the growth rate over time in suspension cells using nothing but cell counts, which can be measured non-destructively. The program was tested on simulated and experimental data. Changes were observed in the initial and absolute growth rates, betraying resistance and adaptation.
conclusionsFor experiments where adaptation is expected to occur over a longer time, our method provides a means of tracking growth rates using data that is normally collected anyhow for monitoring purposes. The program and its documentation are freely available at https://github.com/Sandalmoth/ratrack under the permissive zlib license.
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