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Mapping the Emergent Spatial Organization of Mammalian Cells using Micropatterns and Quantitative Imaging

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Only accessible information is useful: insights from gradient-mediated patterning.

Mikhail Tikhonov¹, Shawn C Little², Thomas Gregor²

¹Joseph Henry Laboratories of Physics , Princeton University , Princeton, NJ 08544, USA ; Harvard Center of Mathematical Sciences and Applications , Harvard University , Cambridge, MA 02138, USA ; Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, MA 02138, USA ; Kavli Institute for Bionano Science and Technology, Harvard University , Cambridge, MA 02138, USA.

Royal Society Open Science

|December 31, 2015

Summary

This summary is machine-generated.

Information theory in biology can be misinterpreted. This study shows that focusing on usable information explains why biological systems use multi-tiered gene expression networks, despite added noise.

Keywords:

Drosophila developmental biology genetic regulation information theory

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Area of Science:

Systems Biology
Developmental Biology
Information Theory

Background:

Information theory is increasingly used to analyze biological systems.
Standard information quantification often overlooks system accessibility and usability, leading to misinterpretations.
Developmental systems often use multi-tiered gene expression cascades, which appear inefficient due to noise accumulation.

Purpose of the Study:

To distinguish between total information and system-accessible information in biological contexts.
To explain the prevalence of multi-tiered gene expression networks in developmental systems.
To resolve limitations in standard information-theoretic characterizations of biological signaling.

Main Methods:

Information-theoretic analysis focusing on accessible information.
Modeling of pattern-forming developmental systems with sequential gene expression.
Empirical validation using fruit fly embryo development.

Main Results:

Quantifying system-accessible information naturally explains the utility of multi-tiered network architectures.
Noise inherent in gene expression control is a key factor favoring such architectures.
Standard information measures can be misleading when applied to biological signaling.

Conclusions:

Multi-tiered gene expression networks are an optimal strategy for utilizing noisy positional information.
A focus on accessible information provides a more accurate framework for understanding biological signaling.
This approach clarifies the functional role of network architecture in developmental processes.