Literature DB >> 25687877

Dynamic quantification of antigen molecules with flow cytometry.

A E Moskalensky1, A V Chernyshev1, M A Yurkin1, V M Nekrasov1, A A Polshchitsin2, D R Parks3, W A Moore3, A Filatenkov4, V P Maltsev5, D Y Orlova6.   

Abstract

Traditional methods for estimating the number of expressed molecules, based on the detection of target antigens bound with fluorescently labeled antibodies, assume that the antigen-antibody reaction reaches equilibrium. A calibration procedure is used to convert the intensity of the fluorescence signal to the number of target molecules. Along with the different limitations of every calibration system, this substantially limits the applicability of the traditional approaches especially in the case of low affinity antibodies. We address this problem here with studies in which we demonstrate a new approach to the antigen molecule quantification problem. Instead of using a static calibration system, we analyzed mean fluorescence values over time by flow cytometry during antibody-antigen binding. Experimental data obtained with an LSRII cytometer were fitted by a diffusion-reaction mathematical model using the Levenberg-Marquardt nonlinear least squares curve-fitting algorithm in order to obtain the number of target antigen molecules per cell. Results were compared with the Quanti-BRITE calibration system. We conclude that, instead of using experiment-specific calibration, the value of the binding rate constant for each particular antibody-antigen reaction can be used to quantify antigen molecules with flow cytometry. The radius of CD8 antibody molecule binding site was found, that allows recalculating the binding rate constant for other conditions (different sizes of reagent molecules, fluorescent label, medium viscosity and temperature). This approach is independent of specially prepared calibration beads, antibody reagents and the specific dye and can be applied to both low and high affinity antibodies, under both saturating and non-saturating binding conditions. The method was demonstrated on a human blood sample dataset investigating CD8α antigen on T cells in stable binding conditions.
Copyright © 2015 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Antibody–antigen binding; Antigen molecules quantification; CD8α antigen concentration; Flow cytometry; Mathematical model; Reaction rate constant

Mesh:

Substances:

Year:  2015        PMID: 25687877      PMCID: PMC4380687          DOI: 10.1016/j.jim.2015.02.001

Source DB:  PubMed          Journal:  J Immunol Methods        ISSN: 0022-1759            Impact factor:   2.303


  17 in total

1.  CD8 kinetically promotes ligand binding to the T-cell antigen receptor.

Authors:  Dmitry M Gakamsky; Immanuel F Luescher; Aladdin Pramanik; Ronen B Kopito; François Lemonnier; Horst Vogel; Rudolf Rigler; Israel Pecht
Journal:  Biophys J       Date:  2005-06-24       Impact factor: 4.033

2.  Human CD8 co-receptor is strictly involved in MHC-peptide tetramer-TCR binding and T cell activation.

Authors:  Rita Campanelli; Belinda Palermo; Silvia Garbelli; Stefania Mantovani; Patrizia Lucchi; Antje Necker; Erica Lantelme; Claudia Giachino
Journal:  Int Immunol       Date:  2002-01       Impact factor: 4.823

Review 3.  A deep profiler's guide to cytometry.

Authors:  Sean C Bendall; Garry P Nolan; Mario Roederer; Pratip K Chattopadhyay
Journal:  Trends Immunol       Date:  2012-04-02       Impact factor: 16.687

4.  Critical role for CD8 in binding of MHC tetramers to TCR: CD8 antibodies block specific binding of human tumor-specific MHC-peptide tetramers to TCR.

Authors:  G Denkberg; C J Cohen; Y Reiter
Journal:  J Immunol       Date:  2001-07-01       Impact factor: 5.422

5.  Cytofluorometric quantification of cell-surface antigens by indirect immunofluorescence using monoclonal antibodies.

Authors:  P Poncelet; P Carayon
Journal:  J Immunol Methods       Date:  1985-12-17       Impact factor: 2.303

6.  Blood basophils from cystic fibrosis patients with allergic bronchopulmonary aspergillosis are primed and hyper-responsive to stimulation by aspergillus allergens.

Authors:  Yael Gernez; Colleen E Dunn; Cassie Everson; Erin Mitsunaga; Lakshmi Gudiputi; Karolina Krasinska; Zoe A Davies; Leonore A Herzenberg; Rabindra Tirouvanziam; Richard B Moss
Journal:  J Cyst Fibros       Date:  2012-05-16       Impact factor: 5.482

7.  Distribution function approach to the study of the kinetics of IgM antibody binding to FcγRIIIb (CD16b) receptors on neutrophils by flow cytometry.

Authors:  Darya Yu Orlova; Vyacheslav I Borisov; Vladimir S Kozhevnikov; Valeri P Maltsev; Andrei V Chernyshev
Journal:  J Theor Biol       Date:  2011-09-08       Impact factor: 2.691

8.  Development of clinical standards for flow cytometry.

Authors:  A Schwartz; E Fernández-Repollet
Journal:  Ann N Y Acad Sci       Date:  1993-03-20       Impact factor: 5.691

9.  Mathematical modeling the kinetics of cell distribution in the process of ligand-receptor binding.

Authors:  I V Surovtsev; I A Razumov; V M Nekrasov; A N Shvalov; J T Soini; V P Maltsev; A K Petrov; V B Loktev; A V Chernyshev
Journal:  J Theor Biol       Date:  2000-10-07       Impact factor: 2.691

10.  Quantitative fluorescence flow cytometry: a comparison of the three techniques for direct and indirect immunofluorescence.

Authors:  S Serke; A van Lessen; D Huhn
Journal:  Cytometry       Date:  1998-10-01
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Review 3.  Mathematical Models for Immunology: Current State of the Art and Future Research Directions.

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