Detecting ALDH2 activity in live cells via conditional metabolic labeling

Area of Science:

• Biochemistry
• Cell Biology
• Chemical Biology

Background:

• Detecting enzyme activity in live cells is challenging.
• Existing metabolic labeling methods lack specificity.
• Enzyme activity is crucial for cellular function and disease.

Purpose of the Study:

• To introduce a novel strategy, cMLEAD, for detecting specific enzyme activity in live cells.
• To demonstrate the utility of cMLEAD for measuring aldehyde dehydrogenase 2 (ALDH2) activity.
• To establish cMLEAD as a platform for drug discovery and understanding enzyme function in disease.

Main Methods:

• Developed cMLEAD using an azido-tagged precursor metabolized by ALDH2.
• Utilized click chemistry for fluorescence-based detection of metabolic incorporation.
• Validated ALDH2 activity measurements through genetic and pharmacological modulation.
• Applied cMLEAD to study ALDH2 activity in cellular senescence and oxidative stress.

Main Results:

• cMLEAD reliably detects ALDH2 activity in live cells.
• ALDH2 activity was suppressed in cellular senescence and oxidative stress.
• Identified sennoside A as an ALDH2 activator using a cMLEAD-based screening platform.
• Sennoside A alleviated light-induced retinal degeneration in mice.

Conclusions:

• cMLEAD is a robust and versatile platform for enzyme activity detection in native cellular contexts.
• cMLEAD facilitates the discovery of enzyme modulators with therapeutic potential.
• The cMLEAD strategy can be adapted for detecting other enzyme activities.