Transcriptomes and Raman spectra are linked linearly through a shared low-dimensional subspace

Abstract

AbstractRaman spectroscopy is an imaging technique that can reflect whole-cell molecular compositionsin vivo,and has been applied recently in cell biology to characterize different cell types and states. However, due to the complex molecular compositions and spectral overlaps, the interpretation of cellular Raman spectra have remained unclear. In this report, we compared cellular Raman spectra to transcriptomes ofSchizosaccharomyces pombeandEscherichia coli,and provide firm evidence that they can be computationally connected and interpreted. Specifically, we find that the dimensions of high-dimensional Raman spectra and transcriptomes measured by RNA-seq can be effectively reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to reconstruct global gene expression profiles by applying the calculated transformation matrix to Raman spectra, and vice versa. Strikingly, highly expressed ncRNAs contributed to the Raman-transcriptome linear correspondence more significantly than mRNAs inS. pombe,which implies their major role in coordinating molecular compositions. This compatibility between whole-cell Raman spectra and transcriptomes marks an important and promising step towards establishing spectroscopic live-cell omics studies.