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Updated: Jul 31, 2026

Mapping Metabolism: Monitoring Lactate Dehydrogenase Activity Directly in Tissue
Published on: June 21, 2018
Multienzyme System in Amorphous Metal-Organic Frameworks for Intracellular Lactate Detection
Yuanyu Zhang1, Lijun Xu1, Jun Ge1,2
1Key Lab for Industrial Biocatalysis, Ministry of Education, Department of Chemical Engineering, Tsinghua University, Beijing 100084, People's Republic of China.
Researchers developed a new method for detecting lactate inside cells using amorphous metal-organic frameworks (aMOFs). This system, acting as artificial organelles, significantly enhances intracellular lactate detection and shows potential for metabolite analysis.
Area of Science:
- Biochemistry
- Nanotechnology
- Cell Biology
Background:
- Lactate is a key metabolite in glycolysis, and its levels are linked to various diseases.
- Accurate intracellular lactate detection is crucial for understanding cellular metabolism and disease states.
Purpose of the Study:
- To develop a novel multienzyme system for sensitive and selective intracellular lactate detection.
- To utilize amorphous metal-organic frameworks (aMOFs) as a platform for constructing artificial organelles.
Main Methods:
- Coencapsulation of lactate oxidase (LOx) and horseradish peroxidase (HRP) within aMOFs.
- Delivery of the aMOF-based multienzyme system into living cells.
- Utilizing proximity-enhanced enzyme activity for signal amplification.
Main Results:
- The engineered multienzyme system demonstrated high activity and selectivity for intracellular lactate.
- The system improved the signal-to-noise ratio for lactate detection by approximately 650-fold.
- Experimental and simulation data confirmed that enzyme proximity within aMOFs enhanced detection efficiency.
Conclusions:
- The construction of multienzyme systems within aMOFs provides a promising strategy for intracellular metabolite detection.
- This approach offers a novel method for creating artificial organelles for enhanced biological sensing.
- The developed system holds potential for advancing diagnostics and research in metabolic diseases.
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