Tissue Characterization Unit The Tissue Characterization Unit will support the activities of this center by generating single-cell data used for constructing the pre-cancer atlas. Core technologies used in this unit includes inDrop single-cell RNA-seq for querying the transcriptomes of thousands of cells, and multiplex immunofluorescence (MxIF) imaging for profiling the spatial properties of the tissue. Antibody detection and RNA-FISH will be used concurrently in multiplex imaging on a single tissue section. We focus on characterization of epithelial and non-epithelial cells, as well as microbial components, in order to depict the pre-cancer ecosystem driving biofilm-host interaction biology. Bulk exome sequencing will also be performed, and limited functional assays will be used for validating correlative findings of the atlas. This unit will be responsible for human specimen preparation workflows, conduct of analytical assays, and collection of quantitative data suitable for downstream analysis. Tissue preparation strategies will be standardized for biopsies and surgical resection, as to generate the highest-quality single-cell data with variation control and minimal introduction of technical artefacts. The most informative panel of markers for distinguishing cell types and progression states, as informed by transcriptomic analysis, will be interrogated spatially using MxIF, and computational strategies will be used for extracting quantitative information from images. Clinically-relevant deliverables include an adaptable approach for detecting biofilms in human specimens, and the development of spatial biomarkers amenable for pathologic assessment of pre-cancer progression.
| Chen, Bob; Herring, Charles A; Lau, Ken S (2018) pyNVR: Investigating factors affecting feature selection from scRNA-seq data for lineage reconstruction. Bioinformatics : |
| Liu, Qi; Herring, Charles A; Sheng, Quanhu et al. (2018) Quantitative assessment of cell population diversity in single-cell landscapes. PLoS Biol 16:e2006687 |
