Reliable cell retention of mammalian suspension cells in microfluidic cultivation chambers

Schmitz, Julian; Stute, Birgit; Taeuber, Sarah; Kohlheyer, Dietrich; Lieres, Eric von; Gruenberger, Alexander

doi:10.1101/2022.01.05.475060

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…Microfluidic devices under highly controllable environmental conditions is a well‐established operation in ongoing research [39]. However, optimal nutrient supply and sufficient cell retention, especially for the long‐term cultivation of slow‐growing cells as well as motile cells, still requires a reliable cell retention concept to prevent permanent cell loss, which otherwise compromises qualitative and quantitative cell studies [40].…”

Section: Introductionmentioning

confidence: 99%

Initial refinement of data from video‐based single‐cell tracking

Korsnes,

Korsnes

2023

Cancer Innovation

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BackgroundVideo recording of cells offers a straightforward way to gain valuable information from their response to treatments. An indispensable step in obtaining such information involves tracking individual cells from the recorded data. A subsequent step is reducing such data to represent essential biological information. This can help to compare various single‐cell tracking data yielding a novel source of information. The vast array of potential data sources highlights the significance of methodologies prioritizing simplicity, robustness, transparency, affordability, sensor independence, and freedom from reliance on specific software or online services.MethodsThe provided data presents single‐cell tracking of clonal (A549) cells as they grow in two‐dimensional (2D) monolayers over 94 hours, spanning several cell cycles. The cells are exposed to three different concentrations of yessotoxin (YTX). The data treatments showcase the parametrization of population growth curves, as well as other statistical descriptions. These include the temporal development of cell speed in family trees with and without cell death, correlations between sister cells, single‐cell average displacements, and the study of clustering tendencies.ResultsVarious statistics obtained from single‐cell tracking reveal patterns suitable for data compression and parametrization. These statistics encompass essential aspects such as cell division, movements, and mutual information between sister cells.ConclusionThis work presents practical examples that highlight the abundant potential information within large sets of single‐cell tracking data. Data reduction is crucial in the process of acquiring such information which can be relevant for phenotypic drug discovery and therapeutics, extending beyond standardized procedures. Conducting meaningful big data analysis typically necessitates a substantial amount of data, which can stem from standalone case studies as an initial foundation.

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Section: Introductionmentioning

confidence: 99%

Initial refinement of data from video‐based single‐cell tracking

Korsnes,

Korsnes

2023

Cancer Innovation

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“…Microfluidic devices under highly controllable environmental conditions is a well-established operation in ongoing research Schmitz et al (2021). However, optimal nutrient supply and sufficient cell retention, especially for the long-term cultivation of slow growing cells as well as motile cells still requires a reliable cell retention concept to prevent permanent cell loss, which otherwise compromises qualitative and quantitative cell studies Schmitz et al (2022).…”

Section: Introductionmentioning

confidence: 99%

Initial refinement of data from video-based single-cell tracking

Korsnes

Korsnes²

2022

Preprint

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This work proposes initial refinements of data from tracking single cells in video from many experiments and at a scale assumed large enough to be meaningful for big data analyses. The present examples of data processing are for illustration only, and caution must be exercised not to consider this contribution as a stand-alone laboratory study. The main intention is to illustrate prototypes of data refinement to help initiation of fault-tolerant big data analyses to search for causal relations in possible future large amounts of data of varying quality. The authors conjecture that computer assisted comparison between cellular behavior in many and diverse experiments can constitute a new source of information. Diversity of data sources is an argument to utilize methods employing simplicity, transparency, low-cost and sensor independence as well as independence of software or alternative online services. Indicating the potential value of simple cell positional observations (tracks), can pave the way towards contributions to already established biological databases. This will presumably help to accumulate experience from a variety of data sources and facilitate big data analyses to search for new phenotypic signatures. Data can be spin-off from special analyses. Simple perturbation of the raw data can help to check for robustness of parameters derived from it. The present example data are from tracking clonal (A549) cells during several cycles while they grow in two-dimensional (2D) monolayers. The results from its processing reflect heterogeneity among the cells as well as inheritance in their response to treatments. The present illustrations include parametrization of population growth curves, aimed to simplify computerized search for similarities in large sets of single-cell tracking data. Other types of statistics, which can promote synergy between experiments, are from temporal development of cell speed in family trees with and without cell death, correlations between sister cells, development of single cell average displacements and the tendency of clustering. These are examples of parameters for further development to utilize information in large collections of data from cell behavior.

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Genetically Encoded Ratiometric pH Sensors for the Measurement of Intra- and Extracellular pH and Internalization Rates

et al. 2022

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pH-sensitive fluorescent proteins as genetically encoded pH sensors are promising tools for monitoring intra- and extracellular pH. However, there is a lack of ratiometric pH sensors, which offer a good dynamic range and can be purified and applied extracellularly to investigate uptake. In our study, the bright fluorescent protein CoGFP_V0 was C-terminally fused to the ligand epidermal growth factor (EGF) and retained its dual-excitation and dual-emission properties as a purified protein. The tandem fluorescent variants EGF-CoGFP-mTagBFP2 (pK′ = 6.6) and EGF-CoGFP-mCRISPRed (pK′ = 6.1) revealed high dynamic ranges between pH 4.0 and 7.5. Using live-cell fluorescence microscopy, both pH sensor molecules permitted the conversion of fluorescence intensity ratios to detailed intracellular pH maps, which revealed pH gradients within endocytic vesicles. Additionally, extracellular binding of the pH sensors to cells expressing the EGF receptor (EGFR) enabled the tracking of pH shifts inside cultivation chambers of a microfluidic device. Furthermore, the dual-emission properties of EGF-CoGFP-mCRISPRed upon 488 nm excitation make this pH sensor a valuable tool for ratiometric flow cytometry. This high-throughput method allowed for the determination of internalization rates, which represents a promising kinetic parameter for the in vitro characterization of protein–drug conjugates in cancer therapy.

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Reliable cell retention of mammalian suspension cells in microfluidic cultivation chambers

Cited by 3 publications

References 26 publications

Initial refinement of data from video‐based single‐cell tracking

Initial refinement of data from video‐based single‐cell tracking

Initial refinement of data from video-based single-cell tracking

Genetically Encoded Ratiometric pH Sensors for the Measurement of Intra- and Extracellular pH and Internalization Rates

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