Handy, C. | Search bioRxiv

bioRxiv2017

Single-cell transcriptome analysis identifies distinct cell types and intercellular niche signaling in a primary gastric organoid model

The diverse cellular milieu of the gastric tissue microenvironment plays a critical role in normal tissue homeostasis and tumor development. However, few cell culture model can recapitulate the tissue microenvironment and intercellular signaling in vitro. Here we applied an air-liquid interface method to culture primary gastric organoids that contains epithelium with endogenous stroma. To characterize the microenvironment and intercellular signaling in this model, we analyzed the transcriptomes of over 5,000 individual cells from primary gastric organoids cultured at different time points. We identified epithelial cells, fibroblasts and macrophages at the early stage of organoid formation, and revealed that macrophages were polarized towards wound healing and tumor promotion. The organoids maintained both epithelial and fibroblast lineages during the course of time, and a subset of cells in both lineages expressed the stem cell marker Lgr5. We identified that Rspo3 was specifically expressed in the fibroblast lineage, providing an endogenous source of the R-spondin to activate Wnt signaling. Our studies demonstrate that air-liquid-interface-derived organoids provide a novel platform to study intercellular signaling and immune response in vitro.

genomics↗

bioRxiv2017

De novo assembly of microbial genomes from human gut metagenomes using barcoded short read sequences

Although shotgun short-read sequencing has facilitated the study of strain-level architecture within complex microbial communities, existing metagenomic approaches often cannot capture structural differences between closely related co-occurring strains. Recent methods, which employ read cloud sequencing and specialized assembly techniques, provide significantly improved genome drafts and show potential to capture these strain-level differences. Here, we apply this read cloud metagenomic approach to longitudinal stool samples from a patient undergoing hematopoietic cell transplantation. The patients microbiome is profoundly disrupted and is eventually dominated by Bacteroides caccae. Comparative analysis of B. caccae genomes obtained using read cloud sequencing together with metagenomic RNA sequencing allows us to predict that particular mobile element integrations result in increased antibiotic resistance, which we further support using in vitro antibiotic susceptibility testing. Thus, we find read cloud sequencing to be useful in identifying strain-level differences that underlie differential fitness.

bioinformatics↗