ArticlePloS one2017
More or less-On the influence of labelling strategies to infer cell population dynamics.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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0 citing papers in PubMed, 1 citations in OpenAlex.
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3 authors at 2 institutions in 2 countries.
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Abstract
The adoptive transfer of labelled cell populations has been an essential tool to determine and quantify cellular dynamics. The experimental methods to label and track cells over time range from fluorescent dyes over congenic markers towards single-cell labelling techniques, such as genetic barcodes. While these methods have been widely used to quantify cell differentiation and division dynamics, the extent to which the applied labelling strategy actually affects the quantification of the dynamics has not been determined so far. This is especially important in situations where measurements can only be obtained at a single time point, as e.g. due to organ harvest. To this end, we studied the appropriateness of various labelling strategies as characterised by the number of different labels and the initial number of cells per label to quantify cellular dynamics. We simulated adoptive transfer experiments in systems of various complexity that assumed either homoeostatic cellular turnover or cell expansion dynamics involving various steps of cell differentiation and proliferation. Re-sampling cells at a single time point, we determined the ability of different labelling strategies to recover the underlying kinetics. Our results indicate that cell transition and expansion rates are differently affected by experimental shortcomings, such as loss of cells during transfer or sampling, dependent on the labelling strategy used. Furthermore, uniformly distributed labels in the transferred population generally lead to more robust and less biased results than non-equal label sizes. In addition, our analysis indicates that certain labelling approaches incorporate a systematic bias for the identification of complex cell expansion dynamics.
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