» Articles » PMID: 36303793

Cyton2: A Model of Immune Cell Population Dynamics That Includes Familial Instructional Inheritance

Overview
Journal Front Bioinform
Specialty Biology
Date 2022 Oct 28
PMID 36303793
Authors
Affiliations
Soon will be listed here.
Abstract

Lymphocytes are the central actors in adaptive immune responses. When challenged with antigen, a small number of B and T cells have a cognate receptor capable of recognising and responding to the insult. These cells proliferate, building an exponentially growing, differentiating clone army to fight off the threat, before ceasing to divide and dying over a period of weeks, leaving in their wake memory cells that are primed to rapidly respond to any repeated infection. Due to the non-linearity of lymphocyte population dynamics, mathematical models are needed to interrogate data from experimental studies. Due to lack of evidence to the contrary and appealing to arguments based on Occam's Razor, in these models newly born progeny are typically assumed to behave independently of their predecessors. Recent experimental studies, however, challenge that assumption, making clear that there is substantial inheritance of timed fate changes from each cell by its offspring, calling for a revision to the existing mathematical modelling paradigms used for information extraction. By assessing long-term live-cell imaging of stimulated murine B and T cells , we distilled the key phenomena of these within-family inheritances and used them to develop a new mathematical model, Cyton2, that encapsulates them. We establish the model's consistency with these newly observed fine-grained features. Two natural concerns for any model that includes familial correlations would be that it is overparameterised or computationally inefficient in data fitting, but neither is the case for Cyton2. We demonstrate Cyton2's utility by challenging it with high-throughput flow cytometry data, which confirms the robustness of its parameter estimation as well as its ability to extract biological meaning from complex mixed stimulation experiments. Cyton2, therefore, offers an alternate mathematical model, one that is, more aligned to experimental observation, for drawing inferences on lymphocyte population dynamics.

Citing Articles

Quantifying Human Naïve B Cell Proliferation Kinetics and Differentiation in Controlled In Vitro Cell Culture.

Farchione A, Cheon H, Hodgkin P, Bryant V Methods Mol Biol. 2024; 2826:167-187.

PMID: 39017893 DOI: 10.1007/978-1-0716-3950-4_13.


Programmed death receptor 1 (PD-1) ligand Fc fusion proteins reduce T-cell proliferation in vitro independently of PD-1.

Biemond M, Vremec D, Gray D, Hodgkin P, Heinzel S Immunol Cell Biol. 2023; 102(2):117-130.

PMID: 38069638 PMC: 10952853. DOI: 10.1111/imcb.12714.


A mean-field description for the expansion kinetics of activated T cell populations.

Straube R, Schmidt B Proc Natl Acad Sci U S A. 2023; 120(45):e2305774120.

PMID: 37910551 PMC: 10636355. DOI: 10.1073/pnas.2305774120.


Survival and division fate programs are preserved but retuned during the naïve to memory CD8 T-cell transition.

Heinzel S, Cheon H, Belz G, Hodgkin P Immunol Cell Biol. 2023; 102(1):46-57.

PMID: 37840018 PMC: 10952575. DOI: 10.1111/imcb.12699.


Modeling T Cell Fate.

De Boer R, Yates A Annu Rev Immunol. 2023; 41:513-532.

PMID: 37126420 PMC: 11100019. DOI: 10.1146/annurev-immunol-101721-040924.


References
1.
Markham J, Wellard C, Hawkins E, Duffy K, Hodgkin P . A minimum of two distinct heritable factors are required to explain correlation structures in proliferating lymphocytes. J R Soc Interface. 2010; 7(48):1049-59. PMC: 2880079. DOI: 10.1098/rsif.2009.0488. View

2.
Dowling M, Kan A, Heinzel S, Zhou J, Marchingo J, Wellard C . Stretched cell cycle model for proliferating lymphocytes. Proc Natl Acad Sci U S A. 2014; 111(17):6377-82. PMC: 4036001. DOI: 10.1073/pnas.1322420111. View

3.
Abril-Pla O, Andreani V, Carroll C, Dong L, Fonnesbeck C, Kochurov M . PyMC: a modern, and comprehensive probabilistic programming framework in Python. PeerJ Comput Sci. 2023; 9:e1516. PMC: 10495961. DOI: 10.7717/peerj-cs.1516. View

4.
Duffy K, Wellard C, Markham J, Zhou J, Holmberg R, Hawkins E . Activation-induced B cell fates are selected by intracellular stochastic competition. Science. 2012; 335(6066):338-41. DOI: 10.1126/science.1213230. View

5.
Smith J, Martin L . Do cells cycle?. Proc Natl Acad Sci U S A. 1973; 70(4):1263-7. PMC: 433472. DOI: 10.1073/pnas.70.4.1263. View