Fang, C. | Search bioRxiv

bioRxiv2018

Flavor compounds in fermented Chinese alcoholic beverage alter gut microbiota and attenuate ethanol-induced liver

Alcoholic beverages which are consumed widely in most parts of the world have long been identified as a major risk factor for all liver diseases, particularly alcohol-induced liver disease (ALD). Recent compositional analyses suggest that Chinese Baijiu (CB), a clear alcoholic liquid distilled from fermented grains, contains large amounts of small molecule bioactive compounds in addition to a significant amount of ethanol. Here, in an experimental mouse model, we show that CB caused lower degrees of liver injury than pure ethanol by protecting against the decrease of the relative abundance of Akkermansia and increased relative abundance of Prevotella in the gut thereby preventing the destruction of the intestinal barrier. Furthermore, we demonstrated that ethanol-induced alteration of the gut microbiota profoundly affected the host metabolome. Compared with ethanol feeding, CB feeding resulted in higher concentrations of functional saturated LCFAs and SCFAs. Our results provide supporting evidence that ALD was profoundly influenced by host-gut microbiota metabolic interactions and that small molecule organic compounds in CB could attenuate ALD.

microbiology↗

bioRxiv2018

Deep-learning light-sheet fluorescence microscopy for high-throughput, voxel-super-resolved imaging of biomedical specimens

Although three-dimensional (3D) fluorescence microscopy is an essential tool for life science research, the fundamentally-limited optical throughput, as reflected in the compromise between speed and resolution, so far prevents further movement towards faster, clearer, and higher-throughput applications. We herein report a dual-stage mutual-feedback deep-learning approach that allows gradual reversion of microscopy degradation from high-resolution targets to low-resolution images. Using a single blurred-and-pixelated 3D image as input, our trained network infers a 3D output with notably higher resolution and improved contrast. The performance is better than conventional 1-stage network approaches. It pushes the throughput limit of current 3D fluorescence microscopy in three ways: notably reducing the acquisition time for accurate mapping of large organs, breaking the diffraction limit for imaging subcellular events with faster lower-toxicity measurement, and improving temporal resolution for capturing instantaneous biological processes. Combining our network approach with light-sheet fluorescence microscopy, we demonstrate the imaging of vessels and neurons in the mouse brain at single-cell resolution and with a throughput of 6 minutes for a whole brain. We also image cell organelles beyond the diffraction limit at a 2-Hz volume rate, and map neuronal activities of freely-moving C. elegans at single-cell resolution and 30-Hz volume rate.

biophysics↗