A bright cyan fluorescence calcium indicator for mitochondrial calcium with minimal interference from physiological pH fluctuations

Abstract

Genetically Encoded Calcium (Ca²⁺) indicators (GECIs) are indispensable tools for dissecting intracellular Ca²⁺ signaling and monitoring cellular activities. Mitochondrion acts as a Ca²⁺ sink and a central player for maintaining Ca²⁺ homeostasis. Accurately monitoring Ca²⁺ transients within the mitochondrial matrix that undergo constant pH fluctuations is challenging, as signals of most currently available GECIs suffer from artifacts induced by physiological pH variations. Multiplexed monitoring of optophysiology is also hindered by the limited availability of GECIs with cyan fluorescence. Based on the bright variant of cyan fluorescence protein (CFP), mTurquoise2, we developed a GECI designated as TurCaMP. Results from molecular dynamics simulations and ab initio calculations revealed that the deprotonation of the chromophore may be responsible for the Ca²⁺-dependent changes in TurCaMP signals. TurCaMP sensors showed inverse response to Ca²⁺ transients, and their responses were not affected by pH changes within the range of pH 6–9. The high basal fluorescence and insensitivity to physiological pH fluctuations enabled TurCaMP to faithfully monitor mitochondrial Ca²⁺ responses with a high signal-to-noise ratio. TurCaMP sensors allow simultaneous multi-colored imaging of intracellular Ca²⁺ signals, expanding the possibility of multiplexed monitoring of Ca²⁺-dependent physiological events.

Graphical abstract

Keywords

Genetically encoded calcium indicator / mTurquoise2 / pH / Mitochondria / MD simulations / Ab initio calculations

Acknowledgements

This work was supported by the Ministry of Science and Technology of China (2019YFA0802104), the National Key R&D Program of China (2023YB3813001), the National Natural Science Foundation of China (91954205, 92254301 and 22273034). Parts of the calculations were performed using computational resources on an IBM Blade cluster system from the High-Performance Computing Center (HPCC) of Nanjing University. We would like to thank the Experimental Technology Center for Lifesciences, Beijing Normal University.

RIGHTS & PERMISSIONS

2024 The Author(s)