Integration of hyperspectral imaging and transcriptomics from individual cells with SpectralSeq

Area of Science:

• Single-cell biology
• Molecular imaging
• Genomics

Background:

• Microscopy and omics offer complementary insights into cellular states.
• Integrating imaging and sequencing on the same cell remains a challenge.

Purpose of the Study:

• To develop and validate SpectralSeq, a novel method combining hyperspectral autofluorescence imaging with transcriptomics.
• To analyze cellular heterogeneity and molecular states in MCF-7 breast cancer cells at single-cell resolution.

Main Methods:

• SpectralSeq workflow: hyperspectral autofluorescence imaging coupled with single-cell transcriptomics.
• Application to MCF-7 breast cancer cells to correlate spectral features with gene expression.
• Analysis of cell morphology, spectral properties (including NADH fluorescence), and gene expression.

Main Results:

• Identification of a subpopulation of MCF-7 cells with plasma membrane autofluorescence rings.
• Ringed cells exhibit higher apoptosis-related gene expression and lower ATP production gene expression.
• Downregulation of spliceosome members in larger MCF-7 cells and varied exon usage across cell sizes.
• Correlation of NADH fluorescence with metabolic states.

Conclusions:

• SpectralSeq provides a streamlined workflow for integrated spectral, morphological, and transcriptomic single-cell analysis.
• The study links optical phenotypes to specific molecular and metabolic states in cancer cells.
• SpectralSeq enhances understanding of cellular heterogeneity and disease mechanisms.