Probing pluripotency gene regulatory networks with quantitative live cell imaging

Abstract

Live cell imaging uniquely enables the measurement of dynamic events in single cells, but it has not been used often in the study of gene regulatory networks. Network components can be examined in relation to one another by quantitative live cell imaging of fluorescent protein reporter cell lines that simultaneously report on more than one network component. A series of dual-reporter cell lines would allow different combinations of network components to be examined in individual cells. Dynamical information about interacting network components in individual cells is critical to predictive modeling of gene regulatory networks, and such information is not accessible through omics and other end point techniques. Achieving this requires that gene-edited cell lines are appropriately designed and adequately characterized to assure the validity of the biological conclusions derived from the expression of the reporters. In this brief review we discuss what is known about the importance of dynamics to network modeling and review some recent advances in optical microscopy methods and image analysis approaches that are making the use of quantitative live cell imaging for network analysis possible. We also discuss how strategies for genetic engineering of reporter cell lines can influence the biological relevance of the data.

High-volume, label-free imaging for quantifying single-cell dynamics in induced pluripotent stem cell colonies

“…It will be possible to query a very large number of individual cells to study the heterogeneity in temporal responses of cellular features within a population, and the correlations in fluctuations of different features in individual cells. This approach may, for example, provide insight into gene regulatory networks (31). In addition, access to spatial information of individual cells permits the assessment of the effects of changes in culture conditions on cell-cell interactions, the relationship of location within the colony to cell division and motion, and the similarity of timing and location of cell divisions to subsequent divisions of daughter cells.…”

Mathematical modeling of regulatory networks of intracellular processes – Aims and selected methods

“…In particular, properly constructed mathematical models and their analysis may yield the following benefits (though they may be farfetched, as conclusions are based on the assumption that the model structure is correct and only feasible simplifications have been made when building it): answering a question if the current state-of-the-art knowledge can explain observed experimental results or if something is missing (e.g., when regardless of parameter changes, the model cannot reflect the system dynamics) – initial math model hypothesis suggests new experiments [116] ; saving resources that otherwise would be spent on experiments should not be planned (because the hypothesis to be tested will prove to false as suggested by the mathematical model) [115] supporting experiment planning through the number of cells that should be quantified at particular times to learn as much as possible about the model parameters and reduce the measurement error [41] , or indicating, in the case of limited time-point measurements, what should be the most informative time instants to gain a proper insight into true system dynamics ( Fig. 2 ; see also [114] ; despite recent progress in live microscopy [49] , [93] , such measurements constitute most of laboratory experiments;

Fig. 2 Actual time response of a signaling pathway (grey dashed line) and misleading results of experiments with several time-point measurements (black crosses).

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“…supporting experiment planning through the number of cells that should be quantified at particular times to learn as much as possible about the model parameters and reduce the measurement error [41] , or indicating, in the case of limited time-point measurements, what should be the most informative time instants to gain a proper insight into true system dynamics ( Fig. 2 ; see also [114] ; despite recent progress in live microscopy [49] , [93] , such measurements constitute most of laboratory experiments;

Fig. 2 Actual time response of a signaling pathway (grey dashed line) and misleading results of experiments with several time-point measurements (black crosses).

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