Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA.

ABSTRACT: Single-cell RNA sequencing and other profiling assays have helped interrogate cells at unprecedented resolution and scale, but are inherently destructive. Raman microscopy reports on the vibrational energy levels of proteins and metabolites in a label-free and nondestructive manner at subcellular spatial resolution, but it lacks genetic and molecular interpretability. Here we present Raman2RNA (R2R), a method to infer single-cell expression profiles in live cells through label-free hyperspectral Raman microscopy images and domain translation. We predict single-cell RNA sequencing profiles nondestructively from Raman images using either anchor-based integration with single molecule fluorescence in situ hybridization, or anchor-free generation with adversarial autoencoders. R2R outperformed

SUBMITTER: Kobayashi-Kirschvink KJ 

PROVIDER: S-EPMC11233426 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature