Raman2RNA: Live-cell label-free prediction of single-cell expression profiles by Raman microscopy (Conference Presentation)

Koseki J. Kobayashi-Kirschvink; Charles S. Comiter; Ke Zhang; Jeon Woong Kang; Jian Shu; Peter So; Aviv Regev

doi:10.1117/12.2649072

15 March 2023 Raman2RNA: Live-cell label-free prediction of single-cell expression profiles by Raman microscopy (Conference Presentation)

Koseki J. Kobayashi-Kirschvink, Charles S. Comiter, Ke Zhang, Jeon Woong Kang, Jian Shu, Peter So, Aviv Regev

Author Affiliations +

Proceedings Volume PC12383, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XXI; PC1238309 (2023) https://doi.org/10.1117/12.2649072
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

Single-cell RNA-seq and other profiling assays have opened new windows into understanding cells' properties, regulation, dynamics, and function at unprecedented resolution and scale. However, these assays are inherently destructive, precluding us from tracking their temporal dynamics. Here, we present Raman2RNA (R2R), an experimental and computational framework to infer single-cell expression profiles in live cells through Raman microscopy images and domain translation using Generative Adversarial Networks. We demonstrate R2R in reprogramming mouse fibroblasts or differentiating mouse embryonic stem cells and show that their expression profiles can be accurately predicted in live cells. R2R paves the way to understanding gene expression dynamics at scale in vitro and in vivo.

Conference Presentation

Citation Download Citation

Koseki J. Kobayashi-Kirschvink, Charles S. Comiter, Ke Zhang, Jeon Woong Kang, Jian Shu, Peter So, and Aviv Regev "Raman2RNA: Live-cell label-free prediction of single-cell expression profiles by Raman microscopy (Conference Presentation)", Proc. SPIE PC12383, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XXI, PC1238309 (15 March 2023); https://doi.org/10.1117/12.2649072

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