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arXiv · 2506.00389

Decoding Cellular Temperature via Neural Network-Aided Fluorescent Thermometry

Tong Zhang·Tian-Tian Li·Jing-Ru Wang·Yu-Wen Zhang·Chao Sun·Zheng Huang·Jing-Juan Xu·Bin Kang
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Abstract

The temperature distribution within cells, especially the debates on mitochondrial temperature, has recently attracted widespread attention. Some studies have claimed that the temperature of mitochondria can reach up to 50-53 degrees Celsius. Yet others have questioned that this is due to measurement errors from fluorescent thermometry caused by other factors, like cell viscosity. Here we present a neural network-aided fluorescent thermometry and decouple the effect of cellular viscosity on temperature measurements. We found that cellular viscosity may cause significant deviations in temperature measurements. We investigated the dynamic temperature changes in different organelles within the cell under stimulation and observed a distinct temperature gradient within the cell. Eliminating the influence of viscosity, the upper limit of mitochondrial temperature does not exceed 42-43 degrees Celsius, supporting our knowledge about the inactivation temperature of enzymes. The temperature of mitochondria is closely related to their functions and morphology, such as fission and fusion. Our results help to clarify the question of "how hot are mitochondria?" and promote a better understanding on cellular thermodynamics.

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Tong Zhang, Tian-Tian Li, Jing-Ru Wang, Yu-Wen Zhang, Chao Sun, Zheng Huang, Jing-Juan Xu, Bin Kang. 2025-05-31. Decoding Cellular Temperature via Neural Network-Aided Fluorescent Thermometry. https://arxiv.org/abs/2506.00389

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