Mitochondrial impairment and intracellular reactive oxygen species alter primary cilia morphology.

Primary cilia have recently emerged as cellular signaling organelles. Their homeostasis and function require a high amount of energy. However, how energy depletion and mitochondria impairment affect cilia have barely been addressed. We first studied the spatial relationship between a mitochondria subset in proximity to the cilium in vitro, finding similar mitochondrial activity measured as mitochondrial membrane potential compared with the cellular network. Next, using common primary cilia cell models and inhibitors of mitochondrial energy production, we found alterations in cilia number and/or length due to energy depletion and mitochondrial reactive oxygen species (ROS) overproduction. Finally, by using a mouse model of type 2 diabetes mellitus, we provided in vivo evidence that cilia morphology is impaired in diabetic nephropathy, which is characterized by ROS overproduction and impaired mitochondrial metabolism. In conclusion, we showed that energy imbalance and mitochondrial ROS affect cilia morphology and number, indicating that conditions characterized by mitochondria and radicals imbalances might lead to ciliary impairment.

Time-Dependent Image Restoration of Low-SNR Live-Cell Ca2 Fluorescence Microscopy Data.

Live-cell Ca2+ fluorescence microscopy is a cornerstone of cellular signaling analysis and imaging. The demand for high spatial and temporal imaging resolution is, however, intrinsically linked to a low signal-to-noise ratio (SNR) of the acquired spatio-temporal image data, which impedes on the subsequent image analysis. Advanced deconvolution and image restoration algorithms can partly mitigate the corresponding problems but are usually defined only for static images. Frame-by-frame application to spatio-temporal image data neglects inter-frame contextual relationships and temporal consistency of the imaged biological processes. Here, we propose a variational approach to time-dependent image restoration built on entropy-based regularization specifically suited to process low- and lowest-SNR fluorescence microscopy data. The advantage of the presented approach is demonstrated by means of four datasets: synthetic data for in-depth evaluation of the algorithm behavior; two datasets acquired for analysis of initial Ca2+ microdomains in T-cells; finally, to illustrate the transferability of the methodical concept to different applications, one dataset depicting spontaneous Ca2+ signaling in jGCaMP7b-expressing astrocytes. To foster re-use and reproducibility, the source code is made publicly available.