How to fit in: The learning principles of cell differentiation
Authors: Brun-Usan Miguel , Watson Richard A. 
Published: January 2019

Cell differentiation in multicellular organisms requires cells to respond to complex combinations of extracellular cues, such as morphogen concentrations. However, most models of phenotypic plasticity assume that the response is a relatively simple function of a single environmental cue. Accordingly, a general theory describing how cells should integrate multi-dimensional signals is lacking.

In this work, we propose a novel theoretical framework for understanding the relationships between environmental cues (inputs) and phenotypic responses (outputs) underlying cell plasticity. We describe the relationship between environment and cell phenotype using logical functions, making the evolution of cell plasticity formally equivalent to a simple categorisation learning task. This abstraction allows us to apply principles derived from learning theory to understand the evolution of multi-dimensional plasticity.

Our results show that natural selection is capable of discovering adaptive forms of cell plasticity associated with arbitrarily complex logical functions. However, developmental dynamics causes simpler functions to evolve more readily than complex ones. By using conceptual tools derived from learning theory we further show that under some circumstances, the evolution of plasticity enables cells to display appropriate plastic responses to environmental conditions that they have not experienced in their evolutionary past. This is possible when the complexity of the selective environment mirrors the developmental bias favouring the acquisition of simple plasticity functions – an example of the necessary conditions for generalisation in learning systems.

These results show non-trivial functional parallelisms between learning in neural networks and the action of natural selection on environmentally sensitive gene regulatory networks. This functional parallelism offers a theoretical framework for the evolution of plastic responses that integrate information from multiple cues, a phenomenon that underpins the evolution of multicellularity and developmental robustness.

Author summary

In organisms composed of many cell types, the differentiation of cells relies on their ability to respond to complex extracellular cues, such as morphogen concentrations, a phenomenon known as cell plasticity. Although cell plasticity plays a crucial role in development and evolution, it is not clear how, and if, cell plasticity can enhance adaptation to a novel environment and/or facilitate robust developmental processes. We argue that available conceptual tools limit our understanding since they only describe simple relationships between the environmental cues (inputs) and the phenotypic responses (outputs) – so called ‘reaction norms’. In this work, we use a new theoretical framework based on logical functions and learning theory that allows us to characterize arbitrarily complex multidimensional reaction norms. By doing this we reveal a strong and previously unnoticed bias towards the acquisition of simple forms of cell plasticity, which increases their ability to adapt to novel environments. Results emerging from this novel approach provide new insights on the evolution of multicellularity and the inherent robustness of the process of development.