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Updated: Jan 9, 2026

Non-contact, Label-free Monitoring of Cells and Extracellular Matrix using Raman Spectroscopy
Published on: May 29, 2012
Elucidating time-resolved intracellular metabolic dynamics via label-free Raman microspectroscopy and 2D correlation
Zohreh Mirveis1,2, Nitin Patil1,2, Hugh J Byrne1
1FOCAS Research Institute, TU Dublin, City Campus, Camden Row, Dublin 8, Ireland. D21127294@mytudublin.ie.
Raman spectroscopy with 2D-COS reveals cellular metabolic dynamics. Glucose-glutamine enhances metabolic variability compared to glucose alone, offering insights into cellular function and disease.
Area of Science:
- Cellular metabolism
- Biophysics
- Spectroscopy
Background:
- Metabolic processes like glycolysis and glutaminolysis are crucial for cellular function and disease.
- Dysregulation of these pathways is linked to various disorders.
- Raman spectroscopy offers a non-invasive method to study cellular dynamics.
Purpose of the Study:
- To investigate cellular metabolic responses to glucose and glucose-glutamine using Raman spectroscopy and 2D-COS.
- To understand the specific role of glutamine in modulating metabolic dynamics.
- To validate the use of 2D-COS for analyzing complex metabolic data.
Main Methods:
- Cells were starved and then exposed to glucose or glucose-glutamine.
- Spectroscopic monitoring was performed at 15-minute intervals for up to 2 hours.
- Two-dimensional correlation spectroscopy (2D-COS) was applied to analyze Raman spectra and kinetic data.
Main Results:
- Simulated data confirmed 2D-COS reliability in tracking dynamic variables.
- Cells under glucose-only conditions showed synchronized metabolic responses with oscillations.
- Glucose-glutamine conditions exhibited accelerated and amplified metabolic variability, with increased correlation and nucleic acid band activity.
Conclusions:
- Raman 2D-COS effectively resolves intracellular metabolic dynamics from complex datasets.
- Glutamine significantly influences metabolic variability and synchronization.
- This technique holds promise for advancing diagnostics and therapeutic interventions in metabolic disorders.
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