Time-lapse microscopy and image processing for stem cell research: modeling cell migration

Author(s):  
Tomas Gustavsson ◽  
Karin Althoff ◽  
Johan Degerman ◽  
Torsten Olsson ◽  
Ann-Catrin Thoreson ◽  
...  
2000 ◽  
Author(s):  
Lisa Choi ◽  
John G. Georgiadis ◽  
Alan R. Horwitz

Abstract The application of optical flow image processing methods in the quantification of cell migration on substrates is reported here. By extracting pixel-based displacement vectors from time-lapse microscopy, this technique allows the accurate and objective analysis of the cell motility process.


2009 ◽  
Vol 15 (4) ◽  
pp. 531-540 ◽  
Author(s):  
Jed Johnson ◽  
M. Oskar Nowicki ◽  
Carol H. Lee ◽  
E. Antonio Chiocca ◽  
Mariano S. Viapiano ◽  
...  

2006 ◽  
Vol 51 (1) ◽  
pp. 7-19 ◽  
Author(s):  
Joseph S. Fotos ◽  
Vivek P. Patel ◽  
Norman J. Karin ◽  
Murali K. Temburni ◽  
John T. Koh ◽  
...  

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1188-1188
Author(s):  
Susanne Wingert ◽  
Frederic B Thalheimer ◽  
Nadine Haetscher ◽  
Maike Rehage ◽  
Hubert Serve ◽  
...  

Abstract The growth arrest and DNA-damage-inducible 45 (Gadd45) protein family is encoded by three genes, Gadd45a, b and g. All members of the family are early responders of cellular stress with tumor-suppressive function. In leukemia, the Gadd45 genes are often epigenetically silenced. Lately, we identified the GADD45 Gamma as the molecular link of differentiation-promoting cytokines to induce differentiation in HSCs (1). Here, we unraveled the function of the genotoxic stress-induced family member GADD45 Alpha (GADD45A) in hematopoiesis. GADD45A has been implicated in cell cycle control, cell death and senescence, as well as in DNA damage repair. In general, GADD45A provides cellular stability by either arresting the cell cycle progression until DNA damage is repaired or, in cases of fatal damage, by inducing apoptosis. However, the function of GADD45A in hematopoiesis remains highly controversial. We revealed the changes in murine HSC fate control orchestrated by the expression of GADD45A at single cell resolution using time-lapse microscopy-based HSC tracking. In contrast to other cellular systems, GADD45A expression neither caused a cell cycle arrest nor an alteration in the decision between cell survival and apoptosis in HSCs. Strikingly, GADD45A strongly induced and accelerated the differentiation program in HSCs. Continuous tracking of individual HSCs and their progeny via time-lapse microscopy elucidated that once GADD45A was expressed, HSCs differentiate into committed progenitors within 29 h. GADD45A-expressing HSCs failed to long-term reconstitute the blood of recipients by inducing multi-lineage differentiation in vivo. The differentiation induction by GADD45A was transmitted by activating p38 MAPK signaling, and allowed the generation of megakaryocytic-erythroid, myeloid and lymphoid lineages. These data indicate that genotoxic stress-induced GADD45A expression in HSCs prevents their fatal transformation by directing them into differentiation and thereby clearing them from the system. As the differentiation induction is conserved throughout the GADD45 family our study establishes this cell fate as an HSC-specific DNA-damage escape mechanism. Comparative analyses of the three proteins will further dissect the induced mechanisms at the molecular level. (1) Thalheimer, F.B., Wingert, S., De Giacomo, P., Haetscher, N., Rehage, M., Brill, B., Theis, F.J., Hennighausen, L., Schroeder, T., Rieger, M.A. Cytokine-Regulated GADD45G Induces Differentiation and Lineage Selection in Hematopoietic Stem Cells. Stem Cell Reports 3(1):34-43. (2014) Disclosures No relevant conflicts of interest to declare.


Author(s):  
Chengzhe Tian ◽  
Chen Yang ◽  
Sabrina L. Spencer

SummaryTime-lapse microscopy provides an unprecedented opportunity to monitor single-cell dynamics. However, tracking cells for long periods of time remains a technical challenge, especially for multi-day, large-scale movies with rapid cell migration, high cell density, and drug treatments that alter cell morphology/behavior. Here, we present EllipTrack, a global-local cell-tracking pipeline optimized for tracking such movies. EllipTrack first implements a global track-linking algorithm to construct tracks that maximize the probability of cell lineages, and then corrects tracking mistakes with a local track-correction module where tracks generated by the global algorithm are systematically examined and amended if a more probable alternative can be found. Through benchmarking, we show that EllipTrack outperforms state-of-the-art cell trackers and generates nearly error-free cell lineages for multiple large-scale movies. In addition, EllipTrack can adapt to time- and cell density-dependent changes in cell migration speeds, requires minimal training datasets, and provides a user-friendly interface. EllipTrack is available at github.com/tianchengzhe/EllipTrack.


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