C13C4.5/Spinster, an evolutionarily conserved protein that regulates fertility in C. elegans through a lysosome-mediated lipid metabolism process

Lipid droplets, which are conserved across almost all species, are cytoplasmic organelles used to store neutral lipids. Identification of lipid droplet regulators will be conducive to resolving obesity and other fat-associated diseases. In this paper, we selected 11 candidates that might be associated with lipid metabolism in Caenorhabditis elegans. Using a BODIPY 493/503-based flow cytometry screen, 6 negative and 3 positive regulators of fat content were identified. We selected one negative regulator of lipid content, C13C4.5, for future study. C13C4.5 was mainly expressed in the worm intestine. We found that this gene was important for maintaining the metabolism of lipid droplets. Biochemical results revealed that 50% of triacylglycerol (TAG) was lost in C13C4.5 knockout worms. Stimulated Raman scattering (SRS) signals in C13C4.5 mutants showed only 49.6% of the fat content in the proximal intestinal region and 86.3% in the distal intestinal region compared with wild type animals. The mean values of lipid droplet size and intensity in C13C4.5 knockout animals were found to be significantly decreased compared with those in wild type worms. The LMP-1-labeled membrane structures in worm intestines were also enlarged in C13C4.5 mutant animals. Finally, fertility defects were found in C13C4.5(ok2087) mutants. Taken together, these results indicate that C13C4.5 may regulate the fertility of C. elegans by changing the size and fat content of lipid droplets by interfering with lysosomal morphology and function.

Ultrafast, accurate, and robust localization of anisotropic dipoles

The resolution of single molecule localization imaging techniques largely depends on the precision of localization algorithms. However, the commonly used Gaussian function is not appropriate for anisotropic dipoles because it is not the true point spread function. We derived the theoretical point spread function of tilted dipoles with restricted mobility and developed an algorithm based on an artificial neural network for estimating the localization, orientation and mobility of individual dipoles. Compared with fitting-based methods, our algorithm demonstrated ultrafast speed and higher accuracy, reduced sensitivity to defocusing, strong robustness and adaptability, making it an optimal choice for both two-dimensional and three-dimensional super-resolution imaging analysis.