Literature DB >> 31431185

Mathematical models incorporating a multi-stage cell cycle replicate normally-hidden inherent synchronization in cell proliferation.

Sean T Vittadello1, Scott W McCue1, Gency Gunasingh2, Nikolas K Haass2, Matthew J Simpson1.   

Abstract

We present a suite of experimental data showing that cell proliferation assays, prepared using standard methods thought to produce asynchronous cell populations, persistently exhibit inherent synchronization. Our experiments use fluorescent cell cycle indicators to reveal the normally hidden cell synchronization, by highlighting oscillatory subpopulations within the total cell population. These oscillatory subpopulations would never be observed without these cell cycle indicators. On the other hand, our experimental data show that the total cell population appears to grow exponentially, as in an asynchronous population. We reconcile these seemingly inconsistent observations by employing a multi-stage mathematical model of cell proliferation that can replicate the oscillatory subpopulations. Our study has important implications for understanding and improving experimental reproducibility. In particular, inherent synchronization may affect the experimental reproducibility of studies aiming to investigate cell cycle-dependent mechanisms, including changes in migration and drug response.

Keywords:  cell cycle; cell proliferation; fluorescent ubiquitination-based cell cycle indicator; mathematical model; reproducibility; synchronization

Mesh:

Year:  2019        PMID: 31431185      PMCID: PMC6731503          DOI: 10.1098/rsif.2019.0382

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  19 in total

Review 1.  Biological methods for cell-cycle synchronization of mammalian cells.

Authors:  P K Davis; A Ho; S F Dowdy
Journal:  Biotechniques       Date:  2001-06       Impact factor: 1.993

2.  Analysis of logistic growth models.

Authors:  A Tsoularis; J Wallace
Journal:  Math Biosci       Date:  2002 Jul-Aug       Impact factor: 2.144

3.  Traveling wave model to interpret a wound-healing cell migration assay for human peritoneal mesothelial cells.

Authors:  Philip K Maini; D L Sean McElwain; David I Leavesley
Journal:  Tissue Eng       Date:  2004 Mar-Apr

4.  Models of epidermal wound healing.

Authors:  J A Sherratt; J D Murray
Journal:  Proc Biol Sci       Date:  1990-07-23       Impact factor: 5.349

5.  Are in vitro estimates of cell diffusivity and cell proliferation rate sensitive to assay geometry?

Authors:  Katrina K Treloar; Matthew J Simpson; D L Sean McElwain; Ruth E Baker
Journal:  J Theor Biol       Date:  2014-04-28       Impact factor: 2.691

6.  A mathematical model of tumour self-seeding reveals secondary metastatic deposits as drivers of primary tumour growth.

Authors:  Jacob G Scott; David Basanta; Alexander R A Anderson; Philip Gerlee
Journal:  J R Soc Interface       Date:  2013-02-20       Impact factor: 4.118

Review 7.  Virtual and real brain tumors: using mathematical modeling to quantify glioma growth and invasion.

Authors:  Kristin R Swanson; Carly Bridge; J D Murray; Ellsworth C Alvord
Journal:  J Neurol Sci       Date:  2003-12-15       Impact factor: 3.181

8.  Visualizing spatiotemporal dynamics of multicellular cell-cycle progression.

Authors:  Asako Sakaue-Sawano; Hiroshi Kurokawa; Toshifumi Morimura; Aki Hanyu; Hiroshi Hama; Hatsuki Osawa; Saori Kashiwagi; Kiyoko Fukami; Takaki Miyata; Hiroyuki Miyoshi; Takeshi Imamura; Masaharu Ogawa; Hisao Masai; Atsushi Miyawaki
Journal:  Cell       Date:  2008-02-08       Impact factor: 41.582

Review 9.  Hallmarks of cancer: the next generation.

Authors:  Douglas Hanahan; Robert A Weinberg
Journal:  Cell       Date:  2011-03-04       Impact factor: 41.582

10.  Real-time cell cycle imaging during melanoma growth, invasion, and drug response.

Authors:  Nikolas K Haass; Kimberley A Beaumont; David S Hill; Andrea Anfosso; Paulus Mrass; Marcia A Munoz; Ichiko Kinjyo; Wolfgang Weninger
Journal:  Pigment Cell Melanoma Res       Date:  2014-06-27       Impact factor: 4.693

View more
  7 in total

1.  Effects of cell cycle variability on lineage and population measurements of messenger RNA abundance.

Authors:  Ruben Perez-Carrasco; Casper Beentjes; Ramon Grima
Journal:  J R Soc Interface       Date:  2020-07-08       Impact factor: 4.118

2.  Identifying density-dependent interactions in collective cell behaviour.

Authors:  Alexander P Browning; Wang Jin; Michael J Plank; Matthew J Simpson
Journal:  J R Soc Interface       Date:  2020-04-29       Impact factor: 4.118

3.  Examining Go-or-Grow Using Fluorescent Cell-Cycle Indicators and Cell-Cycle-Inhibiting Drugs.

Authors:  Sean T Vittadello; Scott W McCue; Gency Gunasingh; Nikolas K Haass; Matthew J Simpson
Journal:  Biophys J       Date:  2020-02-05       Impact factor: 4.033

4.  Synchronized oscillations in growing cell populations are explained by demographic noise.

Authors:  Enrico Gavagnin; Sean T Vittadello; Gency Gunasingh; Nikolas K Haass; Matthew J Simpson; Tim Rogers; Christian A Yates
Journal:  Biophys J       Date:  2021-02-20       Impact factor: 4.033

5.  Designing and interpreting 4D tumour spheroid experiments.

Authors:  Nikolas K Haass; Matthew J Simpson; Ryan J Murphy; Alexander P Browning; Gency Gunasingh
Journal:  Commun Biol       Date:  2022-01-24

6.  A stochastic mathematical model of 4D tumour spheroids with real-time fluorescent cell cycle labelling.

Authors:  Jonah J Klowss; Alexander P Browning; Ryan J Murphy; Elliot J Carr; Michael J Plank; Gency Gunasingh; Nikolas K Haass; Matthew J Simpson
Journal:  J R Soc Interface       Date:  2022-04-06       Impact factor: 4.118

7.  Counting generations in birth and death processes with competing Erlang and exponential waiting times.

Authors:  Giulia Belluccini; Martín López-García; Grant Lythe; Carmen Molina-París
Journal:  Sci Rep       Date:  2022-07-04       Impact factor: 4.996

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.