Concordance of MERFISH spatial transcriptomics with bulk and single-cell RNA sequencing.

Spatial transcriptomics extends single-cell RNA sequencing (scRNA-seq) by providing spatial context for cell type identification and analysis. Imaging-based spatial technologies such as multiplexed error-robust fluorescence in situ hybridization (MERFISH) can achieve single-cell resolution, directly mapping single-cell identities to spatial positions. MERFISH produces a different data type than scRNA-seq, and a technical comparison between the two modalities is necessary to ascertain how to best integrate them. We performed MERFISH on the mouse liver and kidney and compared the resulting bulk and single-cell RNA statistics with those from the Tabula Muris Senis cell atlas and from two Visium datasets. MERFISH quantitatively reproduced the bulk RNA-seq and scRNA-seq results with improvements in overall dropout rates and sensitivity. Finally, we found that MERFISH independently resolved distinct cell types and spatial structure in both the liver and kidney. Computational integration with the Tabula Muris Senis atlas did not enhance these results. We conclude that MERFISH provides a quantitatively comparable method for single-cell gene expression and can identify cell types without the need for computational integration with scRNA-seq atlases.

Virtual Excited State Reference for the Discovery of Electronic Materials Database: An Open-Access Resource for Ground and Excited State Properties of Organic Molecules.

This letter announces the Virtual Excited State Reference for the Discovery of Electronic Materials Database (VERDE materials DB), the first database to include downloadable excited-state structures (S0, S1, T1) and photophysical properties. VERDE materials DB is searchable, open-access via www.verdedb.org , and focused on light-responsive π-conjugated organic molecules with applications in green chemistry, organic solar cells, and organic redox flow batteries. It includes results of our active and past virtual screening studies; to date, more than 13 000 density functional theory (DFT) calculations have been performed on 1 500 molecules to obtain frontier molecular orbitals and photophysical properties, including excitation energies, dipole moments, and redox potentials. To improve community access, we have made VERDE materials DB available via an integration with the Materials Data Facility. We are leveraging VERDE materials DB to train machine learning algorithms to identify new materials and structure-property relationships between molecular ground- and excited-states. We present a case-study involving photoaffinity labels, including predictions of new diazirine-based photoaffinity labels anticipated to have high photostabilities.