Biology subjects

Ni, D.

Publications and source records attributed to Ni, D..

21 records · Page 2Linked to original sources

bioRxiv2020

Dietary protein increases T cell independent sIgA production through changes in gut microbiota-derived extracellular vesicles

Secretory IgA (sIgA) is a key mucosal component ensuring host-microbiota mutualism. Using nutritional geometry modelling in mice fed 10 different macronutrient-defined, isocaloric diets, we identified dietary protein as the major driver of sIgA production. Protein-driven sIgA induction was not mediated by T cell-dependent pathways or changes in gut microbiota composition. Instead, the microbiota of high-protein fed mice produced significantly higher quantities of extracellular vesicles (EV), compared to those of mice fed high-carbohydrate or high-fat diets. These EV activated TLR4 to increase the epithelial expression of IgA-inducing cytokine, APRIL, B cell chemokine, CCL28, and the IgA transporter, PIGR. We showed that succinate, produced in high concentrations by microbiota of high-protein fed animals, increased the generation of reactive oxygen species by bacteria, which in turn promoted EV production. This is the first report establishing a causal link between dietary macronutrient composition, gut microbial EV release and host sIgA response.

immunology↗

bioRxiv2020

Structural investigation of ACE2 dependent disassembly of the trimeric SARS-CoV-2 Spike glycoprotein

The human membrane protein Angiotensin-converting enzyme 2 (hACE2) acts as the main receptor for host cells invasion of the new coronavirus SARS-CoV-2. The viral surface glycoprotein Spike binds to hACE2, which triggers virus entry into cells. As of today, the role of hACE2 for virus fusion is not well understood. Blocking the transition of Spike from its prefusion to post-fusion state might be a strategy to prevent or treat COVID-19. Here we report a single particle cryo-electron microscopy analysis of SARS-CoV-2 trimeric Spike in presence of the human ACE2 ectodomain. The binding of purified hACE2 ectodomain to Spike induces the disassembly of the trimeric form of Spike and a structural rearrangement of its S1 domain to form a stable, monomeric complex with hACE2. This observed hACE2 dependent dissociation of the Spike trimer suggests a mechanism for the therapeutic role of recombinant soluble hACE2 for treatment of COVID-19.

biophysics↗

bioRxiv2020

A deep learning approach for tissue spatial quantification and genomic correlations of histopathological images

Epithelial and stromal tissue are components of the tumor microenvironment and play a major role in tumor initiation and progression. Distinguishing stroma from epithelial tissues is critically important for spatial characterization of the tumor microenvironment. We propose an image analysis pipeline based on a Convolutional Neural Network (CNN) model to classify epithelial and stromal regions in whole-slide images. The CNN model was trained using well-annotated breast cancer tissue microarrays and validated with images from The Cancer Genome Atlas (TCGA) project. Our model achieves a classification accuracy of 91.02%, which outperforms other state-of-the-art methods. Using this model, we generated pixel-level epithelial/stromal tissue maps for 1,000 TCGA breast cancer slide images that are paired with gene expression data. We subsequently estimated the epithelial and stromal ratios and performed correlation analysis to model the relationship between gene expression and tissue ratios. Gene Ontology enrichment analyses of genes that were highly correlated with tissue ratios suggest the same tissue was associated with similar biological processes in different breast cancer subtypes, whereas each subtype had its own idiosyncratic biological processes governing the development of these tissues. Taken all together, our approach can lead to new insights in exploring relationships between image-based phenotypes and their underlying genomic data and biological processes for all types of solid tumors.

bioinformatics↗