Single-cell analysis of EphA clustering phenotypes to probe cancer cell heterogeneity

Adding Highly Variable Genes to Spatially Variable Genes Can Improve Cell Type Clustering Performance in Spatial Transcriptomics Data

Spatial transcriptomics has allowed researchers to analyze transcriptome data in its tissue sample's spatial context. Various methods have been developed for detecting spatially variable genes (SV genes), whose gene expression over the tissue space shows strong spatial autocorrelation. Such genes are often used to define clusters in cells or spots downstream. However, highly variable (HV) genes, whose quantitative gene expressions show significant variation from cell to cell, are conventionally used in clustering analyses. In this report, we investigate whether adding highly variable genes to spatially variable genes can improve the cell type clustering performance in spatial transcriptomics data. We tested the clustering performance of HV genes, SV genes, and the union of both gene sets (concatenation) on over 50 real spatial transcriptomics datasets across multiple platforms, using a variety of spatial and non-spatial metrics. Our results show that combining HV genes and SV genes can improve overall cell-type clustering performance.

Geometric Control of Cell Behavior by Biomolecule Nanodistribution

Many dynamic interactions within the cell microenvironment modulate cell behavior and cell fate. However, the pathways and mechanisms behind cell–cell or cell–extracellular matrix interactions remain understudied, as they occur at a nanoscale level. Recent progress in nanotechnology allows for mimicking of the microenvironment at nanoscale in vitro; electron-beam lithography (EBL) is currently the most promising technique. Although this nanopatterning technique can generate nanostructures of good quality and resolution, it has resulted, thus far, in the production of only simple shapes (e.g., rectangles) over a relatively small area (100 × 100 μm), leaving its potential in biological applications unfulfilled. Here, we used EBL for cell-interaction studies by coating cell-culture-relevant material with electron-conductive indium tin oxide, which formed nanopatterns of complex nanohexagonal structures over a large area (500 × 500 μm). We confirmed the potential of EBL for use in cell-interaction studies by analyzing specific cell responses toward differentially distributed nanohexagons spaced at 1000, 500, and 250 nm. We found that our optimized technique of EBL with HaloTags enabled the investigation of broad changes to a cell-culture-relevant surface and can provide an understanding of cellular signaling mechanisms at a single-molecule level.