Mammalian protein expression noise: scaling principles and the implications for knockdown experiments

Area of Science:

• Molecular Biology
• Cell Biology
• Systems Biology

Background:

• Protein abundance varies within single cells and across cell populations.
• Cell-to-cell variability in protein expression is a key biological phenomenon.
• The gamma distribution model effectively describes protein expression variability.

Purpose of the Study:

• Investigate the properties of noisy protein expression in mammalian cells.
• Analyze how different perturbations affect protein expression noise.
• Clarify the implications for interpreting experimental results, especially knockdown experiments.

Main Methods:

• Combined theoretical modeling with experimental approaches.
• Utilized the gamma distribution model for protein expression variability.
• Manipulated protein levels by altering transcription rates, mRNA half-life, and protein half-life.

Main Results:

• Protein expression noise (squared coefficient of variation) remains constant when altering transcription rates or mRNA half-life.
• Noise decreases as mean protein levels increase when manipulating protein half-life.
• Natural cell-to-cell variability can lead to overlap in protein levels between control and knockdown populations.

Conclusions:

• The relationship between mean protein levels and noise depends on the perturbation method.
• Experimental manipulations can affect both mean protein levels and noise.
• Understanding noise is crucial for accurate interpretation of knockdown experiments and single-cell measurements.