Ribosome demand links transcriptional bursts to protein expression noise

Area of Science:

• Molecular Biology
• Systems Biology
• Genetics

Background:

• Stochastic variation in protein expression (phenotypic heterogeneity) impacts antibiotic persistence, tumor growth, and therapy resistance.
• While transcription noise is well-studied, translation's role in modulating protein noise and cellular heterogeneity is increasingly recognized.
• A positive correlation between translational efficiency and protein noise exists across organisms, but its molecular basis is unclear.

Purpose of the Study:

• To elucidate the molecular basis for the association between translational efficiency and protein noise.
• To investigate how gene coding sequences and promoter activity influence protein expression noise.
• To understand the role of translation in generating phenotypic heterogeneity.

Main Methods:

• Stochastic modeling of translation dynamics at the single mRNA molecule level.
• Empirical measurements of protein noise in cellular populations.
• Analysis of the relationship between translational efficiency, ribosome demand, and gene transcription patterns (bursty vs. non-bursty).

Main Results:

• High translational efficiency in a gene increases ribosome demand, which drives the correlation between translational efficiency and protein noise.
• This correlation is specifically observed in genes exhibiting bursty transcription patterns.
• The study identifies coding sequences and promoter characteristics as key regulators of protein noise.

Conclusions:

• Ribosome demand, influenced by translational efficiency and transcription burstiness, is the molecular driver linking translational efficiency to protein noise.
• Understanding these regulatory mechanisms is crucial for deciphering phenotypic heterogeneity in biological systems.
• Findings provide insights into controlling protein noise and its consequences in various biological contexts.