Noise⁻Seeded Developmental Pattern Formation in Filamentous Cyanobacteria

Area of Science:

• Developmental biology
• Microbiology
• Systems biology

Background:

• Multicellular cyanobacteria like *Anabaena* sp. PCC 7120 differentiate into specialized cells (heterocysts) under nitrogen-poor conditions.
• Pattern formation is regulated by diffusing morphogens acting as activators and inhibitors.

Purpose of the Study:

• To evaluate the limitations of classical Turing mechanisms for pattern formation.
• To introduce and explain the paradigm of stochastic Turing patterns for a more robust description of developmental patterns.

Main Methods:

• Analysis of deterministic Turing mechanisms.
• Focus on birth-death processes to model pattern formation.
• Pedagogical illustration of stochastic Turing patterns.

Main Results:

• Deterministic Turing mechanisms have limitations in explaining observed patterns.
• Stochastic Turing patterns provide a more robust framework for pattern formation.
• Demographic noise (cell-to-cell molecular number differences) is crucial for seeding stochastic Turing patterns over a wider parameter range.

Conclusions:

• Stochastic Turing patterns, influenced by demographic noise, offer a superior model for cyanobacterial differentiation compared to deterministic approaches.
• Cellular noise plays a fundamental role in biological pattern formation.