High-throughput tagging of endogenous loci for rapid characterization of protein function.

To facilitate the interrogation of protein function at scale, we have developed high-throughput insertion of tags across the genome (HITAG). HITAG enables users to rapidly produce libraries of cells, each with a different protein of interest C-terminally tagged. HITAG is based on a modified strategy for performing Cas9-based targeted insertions, coupled with an improved approach for selecting properly tagged lines. Analysis of the resulting clones generated by HITAG reveals high tagging specificity, with most successful tagging events being indel free. Using HITAG, we fuse mCherry to a set of 167 stress granule-associated proteins and elucidate the features that drive a subset of proteins to strongly accumulate within these transient RNA-protein granules.

Exposure to high-sugar diet induces transgenerational changes in sweet sensitivity and feeding behavior via H3K27me3 reprogramming.

Human health is facing a host of new threats linked to unbalanced diets, including high-sugar diet (HSD), which contributes to the development of both metabolic and behavioral disorders. Studies have shown that diet-induced metabolic dysfunctions can be transmitted to multiple generations of offspring and exert long-lasting health burden. Meanwhile, whether and how diet-induced behavioral abnormalities can be transmitted to the offspring remains largely unclear. Here, we showed that ancestral HSD exposure suppressed sweet sensitivity and feeding behavior in the offspring in Drosophila. These behavioral deficits were transmitted through the maternal germline and companied by the enhancement of H3K27me3 modifications. PCL-PRC2 complex, a major driver of H3K27 trimethylation, was upregulated by ancestral HSD exposure, and disrupting its activity eliminated the transgenerational inheritance of sweet sensitivity and feeding behavior deficits. Elevated H3K27me3 inhibited the expression of a transcriptional factor Cad and suppressed sweet sensitivity of the sweet-sensing gustatory neurons, reshaping the sweet perception and feeding behavior of the offspring. Taken together, we uncovered a novel molecular mechanism underlying behavioral abnormalities spanning multiple generations of offspring upon ancestral HSD exposure, which would contribute to the further understanding of long-term health risk of unbalanced diet.

[An automatic 3D brain segmentation based on improved level-set method in micro-CT rat/mouse images].

OBJECTIVE: In vivo Micro-PETICT imaging of mouse/rat brain has been widely used to non-invasively monitor brain and provides researchers a better understanding of therapeutic effects in models of human neurological disease. For the need of further processing, extraction of brain tissue from head is required and vital. METHODS: An automatic multistep combination methods was proposed based on an improved level set framework, which includes (1) Use Fuzzy-C-Means method together with threshold and morphology methods to get the initial level-set surface automatically. (2) Combine gradient vector flow to enhance the gradient contrast and enforce the surface move toward to the object's surface much faster, especially obtain a significantly improvement in the regions of forehead and the joint between brain and neck. (3) introduce an automatic stop condition based on average bandwidth energy maximization to overcome the leakage problem. RESULTS: 3 Micro-CT images of rat and 3 of mouse have been tested using the proposed methods and the average accuracy has increased by 33% for rat and 6.7% for mouse. The average processing duration for rat and mouse are about 8 minutes and 4 minutes, respectively. CONCLUSIONS: The proposed methods were proved that it can be effectively used for Micro-PET/CT imaging of mouse/rat brain segmentation and have a great improvement on accuracy and convenience.

Automated analysis of zebrafish images for phenotypic changes in drug discovery.

Zebrafish has become one of the most popular and useful models in cell biology, development, and drug discovery. Because zebrafish embryo is transparent and can be observed under microscope without fixation, it is increasingly used in high-throughput screening. The small size of zebrafish embryos allows users to image them in a 96- or 384-well plate under various conditions, in turn, generating such a large amount of images that only automated analysis is feasible for processing and analyzing. We focus on developing an image processing algorithm to automatically quantify gene expression on zebrafish embryos that have been treated by various compounds. The challenge in this type of application includes aligning embryos of different orientations and automatically creating regions of interest (ROIs) to enclose specific areas in the head and torso of embryos. The image processing pipeline consists of alignment, segmentation, creation and quantification of ROIs. We test the algorithm using high-throughput images of zebrafish embryos obtained from an experiment screening compounds that may affect γ-secretase in Alzheimer's disease and results show that automated analysis can achieve satisfactory performance in a much shorter amount of time with a high level of objectivity.