Controle de redes reguladoras de genes padronizando tecidos orientado por morfogênese: mero acaso, fortuita necessidade ou princípios de design inteligente?

quinta-feira, novembro 16, 2023

Optimal control of gene regulatory networks for morphogen-driven tissue patterning

Alberto Pezzotta, 1, 2, James Briscoe, 1

1. Developmental Dynamics Laboratory, The Francis Crick Institute, 1 Midland Road, NW1 1AT London, UK

2. Gatsby Computational Neuroscience Unit, University College London, 25 Howland Street, W1T 4JG London, UK

Received 17 August 2022, Revised 6 June 2023, Accepted 10 October 2023, Available online 15 November 2023, Version of Record 15 November 2023.

Published: November 15, 2023 


• Morphogen signaling controls the pattern of gene expression in developing tissues

• Optimal control theory identifies signaling mechanisms for morphogen patterning    

• By incorporating feedback between signaling and gene regulation, it explains dynamics

• Provides an alternative framework to the “French Flag model” for morphogen patterning


The generation of distinct cell types in developing tissues depends on establishing spatial patterns of gene expression. Often, this is directed by spatially graded chemical signals—known as morphogens. In the “French Flag model,” morphogen concentration instructs cells to acquire specific fates. How this mechanism produces timely and organized cell-fate decisions, despite the presence of changing morphogen levels, molecular noise, and individual variability, is unclear. Moreover, feedback is present at various levels in developing tissues, breaking the link between morphogen concentration, signaling activity, and position. Here, we develop an alternative framework using optimal control theory to tackle the problem of morphogen-driven patterning: intracellular signaling is derived as the control strategy that guides cells to the correct fate while minimizing a combination of signaling levels and time. This approach recovers experimentally observed properties of patterning strategies and offers insight into design principles that produce timely, precise, and reproducible morphogen patterning.