Quantifying the Dynamics of Hematopoiesis by In Vivo IdU Pulse-Chase, Mass Cytometry, and Mathematical Modeling

Overview

Journal Cytometry A

Specialties Cell Biology
Radiology

Date 2019 Jun 1

PMID 31150166

Authors

Amir Erez

Ratnadeep Mukherjee

Gregoire Altan-Bonnet

Affiliations

Soon will be listed here.

Abstract

We present a new method to directly quantify the dynamics of differentiation of multiple cellular subsets in unperturbed mice. We combine a pulse-chase protocol of 5-iodo-2'-deoxyuridine (IdU) injections with subsequent analysis by mass cytometry (CyTOF) and mathematical modeling of the IdU dynamics. Measurements by CyTOF allow for a wide range of cells to be analyzed at once, due to the availability of a large staining panel without the complication of fluorescence spillover. These are also compatible with direct detection of integrated iodine signal, with minimal impact on immunophenotyping based on the surface markers. Mathematical modeling beyond a binary classification of surface marker abundance allows for a continuum of cellular states as the cells transition from one state to another. Thus, we present a complete and robust method for directly quantifying differentiation at the systemic level, allowing for system-wide comparisons between different mouse strains and/or experimental conditions. Published 2019. This article is a U.S. Government work and is in the public domain in the USA.

References

Hofer T, Barile M, Flossdorf M . Stem-cell dynamics and lineage topology from in vivo fate mapping in the hematopoietic system. Curr Opin Biotechnol. 2016; 39:150-156. DOI: 10.1016/j.copbio.2016.04.001. View

La Manno G, Soldatov R, Zeisel A, Braun E, Hochgerner H, Petukhov V . RNA velocity of single cells. Nature. 2018; 560(7719):494-498. PMC: 6130801. DOI: 10.1038/s41586-018-0414-6. View

Lee J, Spidlen J, Boyce K, Cai J, Crosbie N, Dalphin M . MIFlowCyt: the minimum information about a Flow Cytometry Experiment. Cytometry A. 2008; 73(10):926-30. PMC: 2773297. DOI: 10.1002/cyto.a.20623. View

Bendall S, Davis K, Amir E, Tadmor M, Simonds E, Chen T . Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell. 2014; 157(3):714-25. PMC: 4045247. DOI: 10.1016/j.cell.2014.04.005. View

Hija A, Salpeter S, Klochendler A, Grimsby J, Brandeis M, Glaser B . G0-G1 transition and the restriction point in pancreatic β-cells in vivo. Diabetes. 2013; 63(2):578-84. PMC: 3900543. DOI: 10.2337/db12-1035. View

Yona S, Kim K, Wolf Y, Mildner A, Varol D, Breker M . Fate mapping reveals origins and dynamics of monocytes and tissue macrophages under homeostasis. Immunity. 2013; 38(1):79-91. PMC: 3908543. DOI: 10.1016/j.immuni.2012.12.001. View

Van de Casteele M, Leuckx G, Baeyens L, Cai Y, Yuchi Y, Coppens V . Neurogenin 3+ cells contribute to β-cell neogenesis and proliferation in injured adult mouse pancreas. Cell Death Dis. 2013; 4:e523. PMC: 3613830. DOI: 10.1038/cddis.2013.52. View

Cotari J, Voisinne G, Altan-Bonnet G . Diversity training for signal transduction: leveraging cell-to-cell variability to dissect cellular signaling, differentiation and death. Curr Opin Biotechnol. 2013; 24(4):760-6. PMC: 3863640. DOI: 10.1016/j.copbio.2013.05.002. View

Van Furth R, COHN Z . The origin and kinetics of mononuclear phagocytes. J Exp Med. 1968; 128(3):415-35. PMC: 2138527. DOI: 10.1084/jem.128.3.415. View

10.

Pieper K, Grimbacher B, Eibel H . B-cell biology and development. J Allergy Clin Immunol. 2013; 131(4):959-71. DOI: 10.1016/j.jaci.2013.01.046. View

11.

Fontenot J, Gavin M, Rudensky A . Foxp3 programs the development and function of CD4+CD25+ regulatory T cells. Nat Immunol. 2003; 4(4):330-6. DOI: 10.1038/ni904. View

12.

Wang F, Zhan R, Chen L, Dai X, Wang W, Guo R . RhoA promotes epidermal stem cell proliferation via PKN1-cyclin D1 signaling. PLoS One. 2017; 12(2):e0172613. PMC: 5319766. DOI: 10.1371/journal.pone.0172613. View

13.

Wells S, Kantor A, Stall A . CD43 (S7) expression identifies peripheral B cell subsets. J Immunol. 1994; 153(12):5503-15. View

14.

Oyler-Yaniv J, Oyler-Yaniv A, Shakiba M, Min N, Chen Y, Cheng S . Catch and Release of Cytokines Mediated by Tumor Phosphatidylserine Converts Transient Exposure into Long-Lived Inflammation. Mol Cell. 2017; 66(5):635-647.e7. PMC: 6611463. DOI: 10.1016/j.molcel.2017.05.011. View

15.

Yu W, Jiang N, Ebert P, Kidd B, Muller S, Lund P . Clonal Deletion Prunes but Does Not Eliminate Self-Specific αβ CD8(+) T Lymphocytes. Immunity. 2015; 42(5):929-41. PMC: 4455602. DOI: 10.1016/j.immuni.2015.05.001. View

16.

Behbehani G, Bendall S, Clutter M, Fantl W, Nolan G . Single-cell mass cytometry adapted to measurements of the cell cycle. Cytometry A. 2012; 81(7):552-66. PMC: 3667754. DOI: 10.1002/cyto.a.22075. View

17.

Tung J, Mrazek M, Yang Y, Herzenberg L, Herzenberg L . Phenotypically distinct B cell development pathways map to the three B cell lineages in the mouse. Proc Natl Acad Sci U S A. 2006; 103(16):6293-8. PMC: 1458871. DOI: 10.1073/pnas.0511305103. View

18.

Qiu P, Simonds E, Bendall S, Gibbs Jr K, Bruggner R, Linderman M . Extracting a cellular hierarchy from high-dimensional cytometry data with SPADE. Nat Biotechnol. 2011; 29(10):886-91. PMC: 3196363. DOI: 10.1038/nbt.1991. View

19.

Setty M, Tadmor M, Reich-Zeliger S, Angel O, Salame T, Kathail P . Wishbone identifies bifurcating developmental trajectories from single-cell data. Nat Biotechnol. 2016; 34(6):637-45. PMC: 4900897. DOI: 10.1038/nbt.3569. View

20.

Erez A, Vogel R, Mugler A, Belmonte A, Altan-Bonnet G . Modeling of cytometry data in logarithmic space: When is a bimodal distribution not bimodal?. Cytometry A. 2018; 93(6):611-619. PMC: 7983168. DOI: 10.1002/cyto.a.23333. View