» Articles » PMID: 38383739

Dynamic Hydrogen Peroxide Levels Reveal a Rate-dependent Sensitivity in B-cell Lymphoma Signaling

Overview
Journal Sci Rep
Specialty Science
Date 2024 Feb 21
PMID 38383739
Authors
Affiliations
Soon will be listed here.
Abstract

Although in vivo extracellular microenvironments are dynamic, most in vitro studies are conducted under static conditions. Here, we exposed diffuse large B-cell lymphoma (DLBCL) cells to gradient increases in the concentration of hydrogen peroxide (HO), thereby capturing some of the dynamics of the tumour microenvironment. Subsequently, we measured the phosphorylation response of B-cell receptor (BCR) signalling proteins CD79a, SYK and PLCγ2 at a high temporal resolution via single-cell phospho-specific flow cytometry. We demonstrated that the cells respond bimodally to static extracellular HO, where the percentage of cells that respond is mainly determined by the concentration. Computational analysis revealed that the bimodality results from a combination of a steep dose-response relationship and cell-to-cell variability in the response threshold. Dynamic gradient inputs of varying durations indicated that the HO concentration is not the only determinant of the signalling response, as cells exposed to more shallow gradients respond at lower HO levels. A minimal model of the proximal BCR network qualitatively reproduced the experimental findings and uncovered a rate-dependent sensitivity to HO, where a lower rate of increase correlates to a higher sensitivity. These findings will bring us closer to understanding how cells process information from their complex and dynamic in vivo environments.

References
1.
Polikowsky H, Wogsland C, Diggins K, Huse K, Irish J . Cutting Edge: Redox Signaling Hypersensitivity Distinguishes Human Germinal Center B Cells. J Immunol. 2015; 195(4):1364-1367. PMC: 4530023. DOI: 10.4049/jimmunol.1500904. View

2.
Park S, Shin S, Cho K . A Regulated Double-Negative Feedback Decodes the Temporal Gradient of Input Stimulation in a Cell Signaling Network. PLoS One. 2016; 11(9):e0162153. PMC: 5008701. DOI: 10.1371/journal.pone.0162153. View

3.
Birtwistle M, Rauch J, Kiyatkin A, Aksamitiene E, Dobrzynski M, Hoek J . Emergence of bimodal cell population responses from the interplay between analog single-cell signaling and protein expression noise. BMC Syst Biol. 2012; 6:109. PMC: 3484110. DOI: 10.1186/1752-0509-6-109. View

4.
Heemskerk I, Burt K, Miller M, Chhabra S, Guerra M, Liu L . Rapid changes in morphogen concentration control self-organized patterning in human embryonic stem cells. Elife. 2019; 8. PMC: 6398983. DOI: 10.7554/eLife.40526. View

5.
Van P, Jiang W, Gottardo R, Finak G . ggCyto: next generation open-source visualization software for cytometry. Bioinformatics. 2018; 34(22):3951-3953. PMC: 6223365. DOI: 10.1093/bioinformatics/bty441. View