A novel view on stem cell development: analysing the shape of cellular genealogies

Glauche, Ingmar; Lorenz, Ronny; Hasenclever, Dirk; Roeder, Ingo

doi:10.1111/j.1365-2184.2009.00586.x

Cited by 26 publications

(37 citation statements)

References 26 publications

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“…Here, we demonstrate that the agentbased model can be used to evaluate the outcome of different hypothesis on underlying mechanisms by providing in silico genealogies. In particular, we show how different model scenarios on the establishment of differential cell cycle times can be distinguished based on a sophisticated statistical analysis of cellular genealogies (Materials and methods; [34,37]). In fact, we considered two different scenarios on how Rex1-related cell cycle times can be established and propagated in simulated mESC populations.…”

Section: Analysis Of Cellular Genealogies Reveals Correlation Structumentioning

confidence: 99%

Dissecting mechanisms of mouse embryonic stem cells heterogeneity through a model-based analysis of transcription factor dynamics

Herberg

Glauche

Zerjatke

et al. 2016

J. R. Soc. Interface.

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Pluripotent mouse embryonic stem cells (mESCs) show heterogeneous expression levels of transcription factors (TFs) involved in pluripotency regulation, among them Nanog and Rex1. The expression of both TFs can change dynamically between states of high and low activity, correlating with the cells' capacity for self-renewal. Stochastic fluctuations as well as sustained oscillations in gene expression are possible mechanisms to explain this behaviour, but the lack of suitable data hampered their clear distinction. Here, we present a systems biology approach in which novel experimental data on TF heterogeneity is complemented by an agent-based model of mESC self-renewal. Because the model accounts for intracellular interactions, cell divisions and heredity structures, it allows for evaluating the consistency of the proposed mechanisms with data on population growth and on TF dynamics after cell sorting. Our model-based analysis revealed that a bistable, noise-driven network model fulfils the minimal requirements to consistently explain Nanog and Rex1 expression dynamics in heterogeneous and sorted mESC populations. Moreover, we studied the impact of TF-related proliferation capacities on the frequency of state transitions and demonstrate that cellular genealogies can provide insights into the heredity structures of mESCs.

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Section: Analysis Of Cellular Genealogies Reveals Correlation Structumentioning

confidence: 99%

Dissecting mechanisms of mouse embryonic stem cells heterogeneity through a model-based analysis of transcription factor dynamics

Herberg

Glauche

Zerjatke

et al. 2016

J. R. Soc. Interface.

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show abstract

“…Nordon et al [8] further introduced an analysis of genealogical trees based on the statistics of branching processes. Apart from that, only few works have addressed more sophisticated measures of cellular development obtained from genealogies [10,11]. In [10] we were among the first to propose a set of different measures to reliably detect asymmetries in cellular genealogies and potential correlations between apoptotic events of related cells.…”

Section: Related Workmentioning

confidence: 99%

“…Apart from that, only few works have addressed more sophisticated measures of cellular development obtained from genealogies [10,11]. In [10] we were among the first to propose a set of different measures to reliably detect asymmetries in cellular genealogies and potential correlations between apoptotic events of related cells. In particular, the latter analysis provided an important step to study regulation of differentiation in stem cell cultures.…”

Section: Related Workmentioning

confidence: 99%

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Beyond genealogies: Mutual information of causal paths to analyse single cell tracking data

Scherf

Zerjatke

Klemm

et al. 2013

2013 IEEE 10th International Symposium on Biomedical Imaging

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Single cell tracking, based on the computerised analysis of time-lapse movies, is a sophisticated experimental technique to quantify single cell dynamics in time and space. Although the resulting cellular genealogies comprehensively describe the divisional history of each cell, there are many open questions regarding the statistical analysis of this type of data. In particular, it is unclear, how tracking uncertainties or spatial information of cellular development can correctly be incorporated into the analysis. Here we propose a generalised description of single cell tracking data by spatiotemporal networks that accounts for ambiguities in cell assignment as well as for spatial relations between cells. We present a way to measure correlations among cell states by analysing the mutual information in state space considering causal (time-respecting) paths and illustrate our approach by a corresponding example. We conclude that a comprehensive spatiotemporal description of single cell tracking data is ultimately necessary to fully exploit the information obtained by time-lapse imaging.

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“…They are traditionally understood as dividing asymmetrically -generating a daughter stem cell and a second progenitor cell. This approach to repair has more recently been questioned [6] with in silico modelling of stem cell niches in the gut [7] and haemopoetic systems supporting a different 'niche approach' [8][9][10]. Faced with the challenge of repair or regeneration to achieve equilibrium within the tissue, local cytokines encourage 'stemness' within the neighbouring cells [11].…”

Section: Basic Scientific Researchmentioning

confidence: 99%

Current Issues and Regulations in Tendon Regeneration and Musculoskeletal Repair with Mesenchymal Stem Cells

Grange¹

2012

CSCR

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A novel view on stem cell development: analysing the shape of cellular genealogies

Cited by 26 publications

References 26 publications

Dissecting mechanisms of mouse embryonic stem cells heterogeneity through a model-based analysis of transcription factor dynamics

Dissecting mechanisms of mouse embryonic stem cells heterogeneity through a model-based analysis of transcription factor dynamics

Beyond genealogies: Mutual information of causal paths to analyse single cell tracking data

Current Issues and Regulations in Tendon Regeneration and Musculoskeletal Repair with Mesenchymal Stem Cells

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