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Stochastic noise reduction upon complexification: positively correlated birth-death type systems
Marianne Rooman1, Jaroslav Albert1, Mitia Duerinckx2
1BioModeling, BioInformatics & BioProcesses, Université Libre de Bruxelles, avenue Roosevelt 50, CP165/61, 1050 Brussels, Belgium.
Journal of Theoretical Biology
|March 18, 2014
Summary
Connecting cellular systems to buffers can reduce molecular noise, enhancing cellular process accuracy. This noise reduction is most significant when molecules in the system and buffer are positively correlated.
Area of Science:
- Systems biology
- Biophysics
- Computational biology
Background:
- Cellular systems involve complex molecular interactions influencing function.
- Increased organism complexity correlates with higher accuracy and specificity in cellular processes.
- Understanding how system complexity impacts molecular noise (variance) is crucial.
Purpose of the Study:
- To investigate how system complexification, modeled by birth-death processes, can reduce molecular noise.
- To compare a standalone system with one connected to a buffer, maintaining the same average molecule count.
Main Methods:
- Modeling using Itō stochastic differential equations in discrete time.
- Analyzing the variance in molecule numbers for systems with and without buffers.
- Testing results on model cases involving protein states and protein monomers/dimers.
Main Results:
- Connecting a system to a positively correlated buffer generally decreases molecular variance.
- Noisy buffers can increase noise in the main system.
- Non-linear interconversion terms (protein monomers/dimers) showed more pronounced noise reduction, up to 20% Fano factor decrease.
- Interconnecting two systems with positively correlated molecules typically reduces total noise.
Conclusions:
- Buffer systems can effectively reduce molecular noise in cellular processes.
- The degree of noise reduction depends on the correlation between system and buffer molecules and the nature of their interactions.
- Interconnection of biological systems offers a strategy for enhancing cellular process reliability.
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