Literature DB >> 22085452

On the symmetry of siblings: automated single-cell tracking to quantify the behavior of hematopoietic stem cells in a biomimetic setup.

Nico Scherf1, Katja Franke, Ingmar Glauche, Ina Kurth, Martin Bornhäuser, Carsten Werner, Tilo Pompe, Ingo Roeder.   

Abstract

The interplay between hematopoietic stem and progenitor cells (HSPC) and their local microenvironment is a key mechanism for the organization of hematopoiesis. To quantitatively study this process, a time-resolved analysis of cellular dynamics at the single-cell level is an essential prerequisite. One way to generate sufficient amounts of appropriate data is automatic single-cell tracking using time-lapse video microscopy. We describe and apply newly developed computational algorithms that allow for an automated generation of high-content data of single-cell characteristics at high temporal and spatial resolution, together with the reconstruction and statistical evaluation of complete genealogical histories. This methodology has been applied to the particular example of purified primary human HSPCs in bioengineered culture conditions. The combination of genealogical information and dynamic profiles of cellular properties identified a marked symmetry between sibling HSPCs regarding cell cycle time, but also migration speed and growth kinetics. Furthermore, we demonstrate that this symmetry of HSPC siblings can be altered by exogenous cues of the local biomimetic microenvironment. Using the example of HSPC growth in biomimetic culture systems, we show that our approach provides a valuable tool for the quantitative analysis of dynamic single-cell features under defined in vitro conditions, allowing for integration of functional and genealogical data. The efficiency and accuracy of our approach pave the way for new and intriguing insights into the organizational principles of developmental patterns and the respective influence of exogenous cues not limited to the study of primary HSPCs.
Copyright © 2012 ISEH - Society for Hematology and Stem Cells. Published by Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22085452     DOI: 10.1016/j.exphem.2011.10.009

Source DB:  PubMed          Journal:  Exp Hematol        ISSN: 0301-472X            Impact factor:   3.084


  9 in total

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

Authors:  Maria Herberg; Ingmar Glauche; Thomas Zerjatke; Maria Winzi; Frank Buchholz; Ingo Roeder
Journal:  J R Soc Interface       Date:  2016-04       Impact factor: 4.118

Review 2.  Challenges in long-term imaging and quantification of single-cell dynamics.

Authors:  Stavroula Skylaki; Oliver Hilsenbeck; Timm Schroeder
Journal:  Nat Biotechnol       Date:  2016-11-08       Impact factor: 54.908

3.  Quantitative label-free single cell tracking in 3D biomimetic matrices.

Authors:  Jiranuwat Sapudom; Johannes Waschke; Katja Franke; Mario Hlawitschka; Tilo Pompe
Journal:  Sci Rep       Date:  2017-10-26       Impact factor: 4.379

4.  Heterogeneous structure of stem cells dynamics: statistical models and quantitative predictions.

Authors:  Paul Bogdan; Bridget M Deasy; Burhan Gharaibeh; Timo Roehrs; Radu Marculescu
Journal:  Sci Rep       Date:  2014-04-28       Impact factor: 4.379

5.  Labour-efficient in vitro lymphocyte population tracking and fate prediction using automation and manual review.

Authors:  Rajib Chakravorty; David Rawlinson; Alan Zhang; John Markham; Mark R Dowling; Cameron Wellard; Jie H S Zhou; Philip D Hodgkin
Journal:  PLoS One       Date:  2014-01-03       Impact factor: 3.240

6.  Distinguishing autocrine and paracrine signals in hematopoietic stem cell culture using a biofunctional microcavity platform.

Authors:  Eike Müller; Weijia Wang; Wenlian Qiao; Martin Bornhäuser; Peter W Zandstra; Carsten Werner; Tilo Pompe
Journal:  Sci Rep       Date:  2016-08-18       Impact factor: 4.379

7.  Ontology patterns for the representation of quality changes of cells in time.

Authors:  Patryk Burek; Nico Scherf; Heinrich Herre
Journal:  J Biomed Semantics       Date:  2019-10-16

8.  Quantitative characterization of cell behaviors through cell cycle progression via automated cell tracking.

Authors:  Yuliang Wang; Younkoo Jeong; Sissy M Jhiang; Lianbo Yu; Chia-Hsiang Menq
Journal:  PLoS One       Date:  2014-06-09       Impact factor: 3.240

9.  Quantifying intrinsic and extrinsic control of single-cell fates in cancer and stem/progenitor cell pedigrees with competing risks analysis.

Authors:  J A Cornwell; R M Hallett; S Auf der Mauer; A Motazedian; T Schroeder; J S Draper; R P Harvey; R E Nordon
Journal:  Sci Rep       Date:  2016-06-01       Impact factor: 4.379

  9 in total

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