Single-cell resolution of intracellular T cell Ca 2+ dynamics in response to frequency-based H 2 O 2 stimulation

• Published in: Integrative biology (Cambridge) Vol. 9; no. 3; p. 238
• Main Authors: Kniss-James, Ariel S, Rivet, Catherine A, Chingozha, Loice, Lu, Hang, Kemp, Melissa L
• Format: Journal Article
• Language: English
• Published: England 01.03.2017
• Subjects: Biological Clocks - drug effects; Biological Clocks - immunology; Calcium - immunology; Calcium Signaling - immunology; Cell Separation - instrumentation; Computer Simulation; Equipment Design; Flow Injection Analysis - instrumentation; Humans; Hydrogen Peroxide - administration & dosage; Hydrogen Peroxide - immunology; Jurkat Cells; Lab-On-A-Chip Devices; Models, Biological; Oscillometry - methods; Systems Integration; T-Lymphocytes - drug effects; T-Lymphocytes - immunology
• ISSN: 1757-9708
• DOI: 10.1039/C6IB00186F

Adaptive immune cells, such as T cells, integrate information from their extracellular environment through complex signaling networks with exquisite sensitivity in order to direct decisions on proliferation, apoptosis, and cytokine production. These signaling networks are reliant on the interplay between finely tuned secondary messengers, such as Ca and H O . Frequency response analysis, originally developed in control engineering, is a tool used for discerning complex networks. This analytical technique has been shown to be useful for understanding biological systems and facilitates identification of the dominant behaviour of the system. We probed intracellular Ca dynamics in the frequency domain to investigate the complex relationship between two second messenger signaling molecules, H O and Ca , during T cell activation with single cell resolution. Single-cell analysis provides a unique platform for interrogating and monitoring cellular processes of interest. We utilized a previously developed microfluidic device to monitor individual T cells through time while applying a dynamic input to reveal a natural frequency of the system at approximately 2.78 mHz stimulation. Although our network was much larger with more unknown connections than previous applications, we are able to derive features from our data, observe forced oscillations associated with specific amplitudes and frequencies of stimuli, and arrive at conclusions about potential transfer function fits as well as the underlying population dynamics.