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FIBS-enabled Noninvasive Metabolic Profiling

FIBS-enabled Noninvasive Metabolic Profiling

Published on: February 3, 2014

FIBS-enabled noninvasive metabolic profiling.

Alireza Behjousiar¹, Antony Constantinou, Karen M Polizzi

¹Centre for Process Systems Engineering, Department of Chemical Engineering and Chemical Technology, Imperial College London.

Journal of Visualized Experiments : Jove

|February 12, 2014

Summary

Researchers developed novel in vivo biosensors for real-time monitoring of intracellular metabolites in Chinese hamster ovary (CHO) cells. This FRET integrated biological sensor (FIBS) technology enables noninvasive, accurate quantification of glucose and glutamine levels.

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Multimodal Optical Imaging Platform for Studying Cellular Metabolism

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Published on: June 6, 2025

Area of Science:

Computational biology
Systems biology
Biotechnology

Background:

High-throughput experimental systems are crucial for refining and validating computational models in biology.
Current methods for time-course data collection often involve destructive sampling, limiting real-time, noninvasive monitoring.
In vivo biological sensors offer a promising alternative for real-time, noninvasive monitoring of intracellular conditions.

Purpose of the Study:

To develop and validate a novel in vivo biosensor system for real-time, noninvasive monitoring of intracellular metabolite concentrations.
To construct Chinese hamster ovary (CHO) cell lines stably expressing FRET integrated biological sensors (FIBS) for glucose and glutamine.
To calibrate the FIBS in batch cell cultures for accurate in vivo quantification of intracellular metabolites.

Main Methods:

Construction of CHO cell lines engineered to constitutively express FRET integrated biological sensors (FIBS).
Development of FIBS based on Förster Resonance Energy Transfer (FRET) between fluorescent proteins linked by a ligand-binding domain.
In vivo calibration of FIBS in batch cell cultures and validation using fed-batch cultures and independent enzymatic assays.

Main Results:

Successfully generated CHO cell lines expressing functional FIBS for glucose and glutamine.
Demonstrated that FIBS exhibit spectral changes correlating with intracellular metabolite concentrations.
Validated the accuracy of FIBS-based quantification of intracellular glucose and glutamine using independent enzymatic assays.

Conclusions:

FRET integrated biological sensors (FIBS) provide a robust platform for real-time, noninvasive monitoring of intracellular metabolites in CHO cells.
This technology enables accurate quantification of key metabolites like glucose and glutamine, essential for bioprocess optimization.
FIBS represent a significant advancement for predictive modeling and bioprocess control in computational biology.