Literature DB >> 28669884

Determining the control networks regulating stem cell lineages in colonic crypts.

Jienian Yang1, David E Axelrod2, Natalia L Komarova3.   

Abstract

The question of stem cell control is at the center of our understanding of tissue functioning, both in healthy and cancerous conditions. It is well accepted that cellular fate decisions (such as divisions, differentiation, apoptosis) are orchestrated by a network of regulatory signals emitted by different cell populations in the lineage and the surrounding tissue. The exact regulatory network that governs stem cell lineages in a given tissue is usually unknown. Here we propose an algorithm to identify a set of candidate control networks that are compatible with (a) measured means and variances of cell populations in different compartments, (b) qualitative information on cell population dynamics, such as the existence of local controls and oscillatory reaction of the system to population size perturbations, and (c) statistics of correlations between cell numbers in different compartments. Using the example of human colon crypts, where lineages are comprised of stem cells, transit amplifying cells, and differentiated cells, we start with a theoretically known set of 32 smallest control networks compatible with tissue stability. Utilizing near-equilibrium stochastic calculus of stem cells developed earlier, we apply a series of tests, where we compare the networks' expected behavior with the observations. This allows us to exclude most of the networks, until only three, very similar, candidate networks remain, which are most compatible with the measurements. This work demonstrates how theoretical analysis of control networks combined with only static biological data can shed light onto the inner workings of stem cell lineages, in the absence of direct experimental assessment of regulatory signaling mechanisms. The resulting candidate networks are dominated by negative control loops and possess the following properties: (1) stem cell division decisions are negatively controlled by the stem cell population, (2) stem cell differentiation decisions are negatively controlled by the transit amplifying cell population.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Control networks; Differentiation; Gastrointestinal cancers; Stem cell lineages

Mesh:

Year:  2017        PMID: 28669884      PMCID: PMC5689466          DOI: 10.1016/j.jtbi.2017.06.033

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  66 in total

1.  A model of the control of cellular regeneration in the intestinal crypt after perturbation based solely on local stem cell regulation.

Authors:  U Paulus; C S Potten; M Loeffler
Journal:  Cell Prolif       Date:  1992-11       Impact factor: 6.831

2.  The Lgr5 intestinal stem cell signature: robust expression of proposed quiescent '+4' cell markers.

Authors:  Javier Muñoz; Daniel E Stange; Arnout G Schepers; Marc van de Wetering; Bon-Kyoung Koo; Shalev Itzkovitz; Richard Volckmann; Kevin S Kung; Jan Koster; Sorina Radulescu; Kevin Myant; Rogier Versteeg; Owen J Sansom; Johan H van Es; Nick Barker; Alexander van Oudenaarden; Shabaz Mohammed; Albert J R Heck; Hans Clevers
Journal:  EMBO J       Date:  2012-06-12       Impact factor: 11.598

3.  Crypt dynamics and colorectal cancer: advances in mathematical modelling.

Authors:  I M M van Leeuwen; H M Byrne; O E Jensen; J R King
Journal:  Cell Prolif       Date:  2006-06       Impact factor: 6.831

Review 4.  Orchestrating transcriptional control of adult neurogenesis.

Authors:  Jenny Hsieh
Journal:  Genes Dev       Date:  2012-05-15       Impact factor: 11.361

Review 5.  Microenvironmental regulation of stem cells in intestinal homeostasis and cancer.

Authors:  Jan Paul Medema; Louis Vermeulen
Journal:  Nature       Date:  2011-06-15       Impact factor: 49.962

6.  Cancer stem cells in solid tumors: is 'evading apoptosis' a hallmark of cancer?

Authors:  Heiko Enderling; Philip Hahnfeldt
Journal:  Prog Biophys Mol Biol       Date:  2011-04-05       Impact factor: 3.667

7.  Pathways to tumorigenesis--modeling mutation acquisition in stem cells and their progeny.

Authors:  Rina Ashkenazi; Sara N Gentry; Trachette L Jackson
Journal:  Neoplasia       Date:  2008-11       Impact factor: 5.715

8.  Identification of stem cells in small intestine and colon by marker gene Lgr5.

Authors:  Nick Barker; Johan H van Es; Jeroen Kuipers; Pekka Kujala; Maaike van den Born; Miranda Cozijnsen; Andrea Haegebarth; Jeroen Korving; Harry Begthel; Peter J Peters; Hans Clevers
Journal:  Nature       Date:  2007-10-14       Impact factor: 49.962

9.  Principles of regulation of self-renewing cell lineages.

Authors:  Natalia L Komarova
Journal:  PLoS One       Date:  2013-09-03       Impact factor: 3.240

10.  Cell lineages and the logic of proliferative control.

Authors:  Arthur D Lander; Kimberly K Gokoffski; Frederic Y M Wan; Qing Nie; Anne L Calof
Journal:  PLoS Biol       Date:  2009-01-20       Impact factor: 8.029

View more
  8 in total

1.  Effect of feedback regulation on stem cell fractions in tissues and tumors: Understanding chemoresistance in cancer.

Authors:  Lora D Weiss; P van den Driessche; John S Lowengrub; Dominik Wodarz; Natalia L Komarova
Journal:  J Theor Biol       Date:  2020-10-29       Impact factor: 2.691

2.  Mathematical modeling of the impact of cytokine response of acute myeloid leukemia cells on patient prognosis.

Authors:  Thomas Stiehl; Anthony D Ho; Anna Marciniak-Czochra
Journal:  Sci Rep       Date:  2018-02-12       Impact factor: 4.379

3.  Spatial dynamics of feedback and feedforward regulation in cell lineages.

Authors:  Peter Uhl; John Lowengrub; Natalia Komarova; Dominik Wodarz
Journal:  PLoS Comput Biol       Date:  2022-05-06       Impact factor: 4.779

4.  Clonal dominance and transplantation dynamics in hematopoietic stem cell compartments.

Authors:  Peter Ashcroft; Markus G Manz; Sebastian Bonhoeffer
Journal:  PLoS Comput Biol       Date:  2017-10-09       Impact factor: 4.475

5.  Patterns of Tumor Progression Predict Small and Tissue-Specific Tumor-Originating Niches.

Authors:  Thomas Buder; Andreas Deutsch; Barbara Klink; Anja Voss-Böhme
Journal:  Front Oncol       Date:  2019-01-10       Impact factor: 6.244

6.  Modelling stem cell ageing: a multi-compartment continuum approach.

Authors:  Yanli Wang; Wing-Cheong Lo; Ching-Shin Chou
Journal:  R Soc Open Sci       Date:  2020-03-18       Impact factor: 2.963

7.  Mathematical modeling reveals the factors involved in the phenomena of cancer stem cells stabilization.

Authors:  Nikolay Bessonov; Guillaume Pinna; Andrey Minarsky; Annick Harel-Bellan; Nadya Morozova
Journal:  PLoS One       Date:  2019-11-11       Impact factor: 3.240

8.  A compartment size-dependent selective threshold limits mutation accumulation in hierarchical tissues.

Authors:  Dániel Grajzel; Imre Derényi; Gergely J Szöllősi
Journal:  Proc Natl Acad Sci U S A       Date:  2020-01-06       Impact factor: 11.205

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.