Long-range memory of growth and cycle progression correlates cell cycles in lineage trees

Kuchen, Erika E; Becker, Nils B.; Claudino, Nina; Höfer, Thomas

doi:10.1101/373258

Cited by 9 publications

(9 citation statements)

References 28 publications

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“…Within a tumor population, drug treatment can dynamically shift the balance of variability present, and so dynamic information will likely be critical 8,42 . Automated cell tracking would enable drug-response quantification, with single-cell resolution, while preserving the lineage relationship of cells 43,44 . Finally, while we distinguish relatively more or less apoptotic cell death here, various cell death programs exist 45 .…”

Section: Discussionmentioning

confidence: 99%

Measurement and models accounting for cell death capture hidden variation in compound response

et al. 2020

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Cancer cell sensitivity or resistance is almost universally quantified through a direct or surrogate measure of cell number. However, compound responses can occur through many distinct phenotypic outcomes, including changes in cell growth, apoptosis, and non-apoptotic cell death. These outcomes have divergent effects on the tumor microenvironment, immune response, and resistance mechanisms. Here, we show that quantifying cell viability alone is insufficient to distinguish between these compound responses. Using an alternative assay and drug-response analysis amenable to high-throughput measurement, we find that compounds with identical viability outcomes can have very different effects on cell growth and death. Moreover, additive compound pairs with distinct growth/death effects can appear synergistic when only assessed by viability. Overall, these results demonstrate an approach to incorporating measurements of cell death when characterizing a pharmacologic response.

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Section: Discussionmentioning

confidence: 99%

Measurement and models accounting for cell death capture hidden variation in compound response

et al. 2020

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“…Within a tumor population, drug treatment can dynamically shift the balance of variability present, and so dynamic information will likely be critical [ 8,22]. Automated cell tracking would enable drug response quantification, with single-cell resolution, while preserving the lineage relationship of cells [23,24]. While we distinguish relatively more or less apoptotic cell death here, various cell death programs exist [25].…”

Section: Discussionmentioning

confidence: 99%

Measurement and models accounting for cell death capture hidden variation in compound response

Bae

Guan

Yan

et al. 2019

Preprint

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AbstractCancer cell sensitivity or resistance is almost universally quantified through a direct or surrogate measure of cell number. However, compound responses can occur through many distinct phenotypic outcomes including changes in cell growth, apoptosis, and non-apoptotic cell death. These outcomes have distinct effects on the tumor microenvironment, immune responses, and resistance mechanisms. Here, we show that quantifying cell viability alone is insufficient to distinguish between these compound responses. Using an alternative assay and drug response analysis amenable to high-throughput measurement, we find that compounds with identical viability outcomes can have very different effects on cell growth and death. Moreover, compound pairs with additive cell growth and death effects can appear synergistic when only assessed by viability. Overall, these results demonstrate an approach to incorporating measurements of cell death when characterizing a pharmacologic response.Summary PointsMeasurements of solely live cell numbers mask important differences in compound effects.Additive effects on growth and death rates can appear synergistic when analyzed solely via live cell number.Automated imaging can provide reasonable throughput to analyze cell response in terms of cell growth and death, and endpoint analysis is similarly informative.

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“…Lineage information was found to be an important contributor to patterning gene expression in bacterial microcolony formation 28,29 , where it can act as the dominant cause of spatial correlations 30 . While properties such as cell cycle duration have been shown to propagate in mammalian cell lineages 31,32 , the importance of genealogy for transcriptional activity in mammalian cells is still poorly studied. Here, we used live-cell imaging to measure and compare transcriptional activity of lineage-related mammalian cells over time.…”

Section: Discussionmentioning

confidence: 99%

Gene-specific transcriptional memory in mammalian cell lineages

Phillips

Mandic

Omidi

et al. 2018

Preprint

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Phenotypically identical mammalian cells often display considerable variability in transcript levels of individual genes. How transcriptional activity propagates in cell lineages, and how this varies across genes is poorly understood. Here we combined live-cell imaging of shortlived transcriptional reporters in mouse embryonic stem cells with mathematical modelling to quantify the propagation of transcriptional activity over time and across cell generations. In sister cells we found mean transcriptional activity to be strongly correlated and transcriptional dynamics tended to be synchronous; both features control how quickly sister cells diverge in a gene-specific manner. Mean transcriptional activity was also highly correlated between mother and daughter cells, leading to multi-generational transcriptional memory whose duration scaled with the spread of transcriptional activities in the population.The resulting family-specific transcriptional levels suggest a potential role of transcriptional memory in patterning tissue gene expression.

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Long-range memory of growth and cycle progression correlates cell cycles in lineage trees

Cited by 9 publications

References 28 publications

Measurement and models accounting for cell death capture hidden variation in compound response

Measurement and models accounting for cell death capture hidden variation in compound response

Measurement and models accounting for cell death capture hidden variation in compound response

Gene-specific transcriptional memory in mammalian cell lineages

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