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推断适应过程中细胞培养物中时变的种群增长率。

Inferring time-dependent population growth rates in cell cultures undergoing adaptation.

机构信息

Department of Chemistry and Biomedical Sciences, Linnaeus University, 391 82, Kalmar, Sweden.

出版信息

BMC Bioinformatics. 2020 Dec 17;21(1):583. doi: 10.1186/s12859-020-03887-7.

Abstract

BACKGROUND

The 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.

RESULTS

We 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.

CONCLUSIONS

For 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.

摘要

背景

人口增长率是任何细胞培养的重要特征。在持续的实验中,由于竞争或适应,增长率可能会发生变化。例如,在存在毒素或药物的情况下,增长率的增加表明细胞适应并变得具有抗性。因此,时间依赖性增长率是跟踪细胞对不断变化的进化环境的适应的基础。然而,由于没有工具可以通过细胞计数直接计算时间依赖性增长率,因此通常仅使用生长的终点测量值,而不是连续跟踪生长速率。

结果

我们提出了一种使用仅细胞计数即可推断悬浮细胞随时间变化的增长率的计算机程序,而这些细胞计数可以非破坏性地测量。该程序在模拟和实验数据上进行了测试。在初始和绝对增长率方面观察到了变化,这表明出现了抗性和适应性。

结论

对于预计在较长时间内发生适应的实验,我们的方法提供了一种使用通常为监控目的而收集的数据跟踪生长速率的方法。该程序及其文档可在 https://github.com/Sandalmoth/ratrack 上免费获得,采用宽松的 zlib 许可证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f17/7745411/e559c0957402/12859_2020_3887_Fig1_HTML.jpg

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