From molecular noise to behavioural variability in a single bacterium.

Area of Science:

• Microbiology and Molecular Biology
• Systems Biology
• Biophysics

Background:

• The Escherichia coli chemotaxis network is a model system for understanding signal transduction and biological complexity.
• Traditional studies infer network properties from population averages, potentially obscuring single-cell dynamics.
• Intracellular signaling events exhibit temporal fluctuations not captured by population-level measurements.

Purpose of the Study:

• To investigate fundamental properties of the bacterial chemotaxis network at the single-cell level.
• To analyze intracellular signaling noise and its impact on bacterial behavior.
• To determine if population-level observations of adaptation are conserved in individual cells.

Main Methods:

• Noise analysis of behavioral variations in individual Escherichia coli.
• Focus on temporal fluctuations in non-stimulated cells over timescales of seconds to minutes.
• Identification of molecular events within the signaling network responsible for noise generation.

Main Results:

• Population-level properties, such as adapted states, are not conserved at the single-cell level.
• Non-stimulated bacteria exhibit temporal behavioral variations exceeding expected statistical fluctuations.
• The chemotaxis signaling network intrinsically generates this noise; specific molecular events were identified.

Conclusions:

• Bacterial chemotaxis exhibits significant intrinsic noise at the single-cell level.
• This noise is a property of the signaling network itself and not solely random statistical variation.
• Variability appears to be a selected feature of this adaptive system, potentially linked to network component concentrations.