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Cell Phase Identification in a Three-Dimensional Engineered Tumor Model by Infrared Spectroscopic Imaging
Pei-Hsuan Hsieh1, Yamuna Phal2, Kannanganattu V Prasanth3
1Department of Bioengineering and Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.
Analytical Chemistry
|December 27, 2022
Summary
Fourier transform infrared (FT-IR) spectroscopic imaging identifies cell cycle phases in 3D cultures. This label-free method tracks biochemical changes, aiding disease model development and diagnostics.
Area of Science:
- Biomedical Engineering
- Spectroscopy
- Cell Biology
Background:
- Cell cycle progression is crucial for cellular functions like proliferation and metabolism.
- Three-dimensional (3D) cell cultures are vital in vitro disease models.
- Integrating cell cycle dynamics into 3D models is essential for accuracy.
Purpose of the Study:
- To utilize Fourier transform infrared (FT-IR) spectroscopic imaging for identifying cell cycle phases (G1/S and G2/M) in 3D cell cultures.
- To establish spectral markers for cell cycle analysis without staining.
- To characterize the impact of cell cycle progression on 3D biological systems.
Main Methods:
- Synchronized 2D cell cultures were analyzed using FT-IR spectroscopic imaging.
- Flow cytometry and DNA quantification confirmed cell cycle states.
- Two specific wavenumbers (1059 and 1219 cm-1) were identified as spectral indicators.
Main Results:
- FT-IR imaging successfully identified G1/S and G2/M phases in 2D and 3D cell cultures.
- Spectral markers distinguished cell cycle stages across normal to metastatic cancer cell lines in 3D models.
- Early 3D acini development showed higher proliferation, with later stages exhibiting stable composition but spatial cell phase differences.
Conclusions:
- FT-IR spectroscopic imaging offers a label-free, quantitative method for cell cycle phase analysis in 3D cultures.
- This approach can characterize cell cycle impacts on tissue-like 3D structures.
- The findings support the use of IR imaging in disease diagnostics and 3D biological system studies.

