Literature DB >> 19633185

A single-cell pedigree analysis of alternative stochastic lymphocyte fates.

E D Hawkins1, J F Markham, L P McGuinness, P D Hodgkin.   

Abstract

In contrast to most stimulated lymphocytes, B cells exposed to Toll-like receptor 9 ligands are nonself-adherent, allowing individual cells and families to be followed in vitro for up to 5 days. These B cells undergo phases typical of an adaptive response, dividing up to 6 times before losing the impetus for further growth and division and eventually dying by apoptosis. Using long-term microscopic imaging, accurate histories of individual lymphocyte fates were collected. Quantitative analysis of family relationships revealed that times to divide of siblings were strongly related but these correlations were progressively lost through consecutive divisions. A weaker, but significant, correlation was also found for death times among siblings. Division cessation is characterized by a loss of cell growth and the division in which this occurs is strongly inherited from the original founder cell and is related to the size this cell reaches before its first division. Thus, simple division-based dilution of factors synthesized during the first division may control the maximum division reached by stimulated cells. The stochastic distributions of times to divide, times to die, and divisions reached are also measured. Together, these results highlight the internal cellular mechanisms that control immune responses and provide a foundation for the development of new mathematical models that are correct at both single-cell and population levels.

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Year:  2009        PMID: 19633185      PMCID: PMC2715326          DOI: 10.1073/pnas.0905629106

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  29 in total

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Authors:  Jhagvaral Hasbold; Lynn M Corcoran; David M Tarlinton; Stuart G Tangye; Philip D Hodgkin
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2.  Stochastic model of T cell proliferation: a calculus revealing IL-2 regulation of precursor frequencies, cell cycle time, and survival.

Authors:  Elissa K Deenick; Amanda V Gett; Philip D Hodgkin
Journal:  J Immunol       Date:  2003-05-15       Impact factor: 5.422

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4.  THE DISTRIBUTION AND INTERDEPENDENCE OF GENERATION TIMES OF HELA CELLS.

Authors:  G FROESE
Journal:  Exp Cell Res       Date:  1964-07       Impact factor: 3.905

5.  VARIATIONS IN THE GENERATION TIMES OF A STRAIN OF RAT SARCOMA CELLS IN CULTURE.

Authors:  K B DAWSON; H MADOC-JONES; E O FIELD
Journal:  Exp Cell Res       Date:  1965-04       Impact factor: 3.905

6.  Do cells cycle?

Authors:  J A Smith; L Martin
Journal:  Proc Natl Acad Sci U S A       Date:  1973-04       Impact factor: 11.205

7.  Radiation-induced mammalian cell death: lapse-time cinemicrographic observations.

Authors:  G Marin; M A Bender
Journal:  Exp Cell Res       Date:  1966-09       Impact factor: 3.905

8.  B cell differentiation and isotype switching is related to division cycle number.

Authors:  P D Hodgkin; J H Lee; A B Lyons
Journal:  J Exp Med       Date:  1996-07-01       Impact factor: 14.307

9.  Sloppy size control of the cell division cycle.

Authors:  J J Tyson; O Diekmann
Journal:  J Theor Biol       Date:  1986-02-21       Impact factor: 2.691

10.  The rescaling method for quantifying the turnover of cell populations.

Authors:  Sergei S Pilyugin; Vitaly V Ganusov; Kaja Murali-Krishna; Rafi Ahmed; Rustom Antia
Journal:  J Theor Biol       Date:  2003-11-21       Impact factor: 2.691

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  63 in total

Review 1.  Mapping the life histories of T cells.

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Journal:  Nat Rev Immunol       Date:  2010-08-06       Impact factor: 53.106

Review 2.  Control systems and decision making for antibody production.

Authors:  Christopher C Goodnow; Carola G Vinuesa; Katrina L Randall; Fabienne Mackay; Robert Brink
Journal:  Nat Immunol       Date:  2010-07-20       Impact factor: 25.606

Review 3.  Clonal expansion under the microscope: studying lymphocyte activation and differentiation using live-cell imaging.

Authors:  Michal Polonsky; Benjamin Chain; Nir Friedman
Journal:  Immunol Cell Biol       Date:  2015-12-22       Impact factor: 5.126

4.  Inferring average generation via division-linked labeling.

Authors:  Tom S Weber; Leïla Perié; Ken R Duffy
Journal:  J Math Biol       Date:  2016-01-05       Impact factor: 2.259

5.  On the impact of correlation between collaterally consanguineous cells on lymphocyte population dynamics.

Authors:  Ken R Duffy; Vijay G Subramanian
Journal:  J Math Biol       Date:  2008-10-28       Impact factor: 2.259

6.  Identifying Noise Sources governing cell-to-cell variability.

Authors:  Simon Mitchell; Alexander Hoffmann
Journal:  Curr Opin Syst Biol       Date:  2017-12-06

7.  A new model for the estimation of cell proliferation dynamics using CFSE data.

Authors:  H T Banks; Karyn L Sutton; W Clayton Thompson; Gennady Bocharov; Marie Doumic; Tim Schenkel; Jordi Argilaguet; Sandra Giest; Cristina Peligero; Andreas Meyerhans
Journal:  J Immunol Methods       Date:  2011-08-24       Impact factor: 2.303

Review 8.  The generation of antibody-secreting plasma cells.

Authors:  Stephen L Nutt; Philip D Hodgkin; David M Tarlinton; Lynn M Corcoran
Journal:  Nat Rev Immunol       Date:  2015-02-20       Impact factor: 53.106

9.  An age-dependent branching process model for the analysis of CFSE-labeling experiments.

Authors:  Ollivier Hyrien; Rui Chen; Martin S Zand
Journal:  Biol Direct       Date:  2010-06-22       Impact factor: 4.540

10.  A minimum of two distinct heritable factors are required to explain correlation structures in proliferating lymphocytes.

Authors:  John F Markham; Cameron J Wellard; Edwin D Hawkins; Ken R Duffy; Philip D Hodgkin
Journal:  J R Soc Interface       Date:  2010-01-06       Impact factor: 4.118

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