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Related Experiment Video

Updated: Jul 6, 2025

Real-time Imaging of Single Engineered RNA Transcripts in Living Cells Using Ratiometric Bimolecular Beacons

Real-time Imaging of Single Engineered RNA Transcripts in Living Cells Using Ratiometric Bimolecular Beacons

Published on: August 6, 2014

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

Koseki J Kobayashi-Kirschvink^1,2, Charles S Comiter^3,4,5, Shreya Gaddam^3,6

¹Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA. kkobayas@broadinstitute.org.

Nature Biotechnology

|January 10, 2024

Summary

This summary is machine-generated.

Raman2RNA (R2R) infers single-cell gene expression from label-free Raman microscopy images, enabling nondestructive live-cell analysis. This method overcomes limitations of destructive profiling, offering new insights into cellular dynamics.

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Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy

Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy

Published on: May 29, 2012

Related Experiment Videos

Last Updated: Jul 6, 2025

Real-time Imaging of Single Engineered RNA Transcripts in Living Cells Using Ratiometric Bimolecular Beacons

Real-time Imaging of Single Engineered RNA Transcripts in Living Cells Using Ratiometric Bimolecular Beacons

Published on: August 6, 2014

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects

An Integrated Raman Spectroscopy and Mass Spectrometry Platform to Study Single-Cell Drug Uptake, Metabolism, and Effects

Published on: January 9, 2020

Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy

Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy

Published on: May 29, 2012

Area of Science:

Biotechnology
Cell Biology
Spectroscopy

Background:

Single-cell RNA sequencing offers high resolution but is destructive.
Raman microscopy is label-free and nondestructive but lacks genetic interpretability.

Purpose of the Study:

To develop a method for inferring single-cell RNA sequencing profiles from label-free Raman microscopy images.
To enable nondestructive, live-cell analysis of cellular dynamics and gene expression.

Main Methods:

Developed Raman2RNA (R2R), a method using hyperspectral Raman microscopy and domain translation.
Employed anchor-based integration with single molecule fluorescence in situ hybridization and anchor-free adversarial autoencoders.
Validated R2R by comparing its performance against brightfield imaging.

Main Results:

R2R accurately predicted single-cell RNA sequencing profiles from Raman images (cosine similarity >0.85).
Inferred cell states during fibroblast reprogramming and traced early lineage divergence in stem cell differentiation.
Demonstrated superior performance compared to brightfield image-based inference (<0.15 cosine similarity).

Conclusions:

Raman2RNA (R2R) provides a nondestructive method for inferring gene expression profiles in live cells.
Enables longitudinal studies of cellular processes, overcoming limitations of destructive assays.
Paves the way for exploring live genomic dynamics and cellular heterogeneity.