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Thermodynamic costs of information processing in sensory adaptation.

Sartori P, Granger L, Lee CF, Horowitz JM - PLoS Comput. Biol. (2014)

Bottom Line: We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes.In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum.Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.

ABSTRACT
Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.

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Information-dissipation trade-off in E. coli chemotaxis.(A) Relationship between information erased/acquired and size of the signal increase. Shaded in green is the region of accurate adaptation (). (B) Entropy production as a function of information erased/acquired as step size is varied. The more information is processed by the cell the higher the entropic cost. Notice the linear scaling between dissipation and information for small information (small ligand changes). Dashed lines refer to values in Fig. 5C. Parameters as in Methods.
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pcbi-1003974-g006: Information-dissipation trade-off in E. coli chemotaxis.(A) Relationship between information erased/acquired and size of the signal increase. Shaded in green is the region of accurate adaptation (). (B) Entropy production as a function of information erased/acquired as step size is varied. The more information is processed by the cell the higher the entropic cost. Notice the linear scaling between dissipation and information for small information (small ligand changes). Dashed lines refer to values in Fig. 5C. Parameters as in Methods.

Mentions: We further explored the cost of sensing in E. coli by examining the net entropy production for ligand changes of different intensity. In Fig. 6A, we plot the amount of information erased/measured for different step changes of the signal up to taking as lower base . The green shading highlights the region where adaptation is accurate (). The information erased is always below 1 bit and saturates for high ligand concentrations, for which the system is not sensitive. The total entropic cost (that is, ) and its relation with the information erased appears in Fig. 6B. The dependence is monotonic, and thus reveals a trade-off between information processing and dissipation in sensory adaptation. Notably, for small acquisition of information (small ligand steps) it grows linearly with the information, an effect observed in ideal measurement systems [17].


Thermodynamic costs of information processing in sensory adaptation.

Sartori P, Granger L, Lee CF, Horowitz JM - PLoS Comput. Biol. (2014)

Information-dissipation trade-off in E. coli chemotaxis.(A) Relationship between information erased/acquired and size of the signal increase. Shaded in green is the region of accurate adaptation (). (B) Entropy production as a function of information erased/acquired as step size is varied. The more information is processed by the cell the higher the entropic cost. Notice the linear scaling between dissipation and information for small information (small ligand changes). Dashed lines refer to values in Fig. 5C. Parameters as in Methods.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263364&req=5

pcbi-1003974-g006: Information-dissipation trade-off in E. coli chemotaxis.(A) Relationship between information erased/acquired and size of the signal increase. Shaded in green is the region of accurate adaptation (). (B) Entropy production as a function of information erased/acquired as step size is varied. The more information is processed by the cell the higher the entropic cost. Notice the linear scaling between dissipation and information for small information (small ligand changes). Dashed lines refer to values in Fig. 5C. Parameters as in Methods.
Mentions: We further explored the cost of sensing in E. coli by examining the net entropy production for ligand changes of different intensity. In Fig. 6A, we plot the amount of information erased/measured for different step changes of the signal up to taking as lower base . The green shading highlights the region where adaptation is accurate (). The information erased is always below 1 bit and saturates for high ligand concentrations, for which the system is not sensitive. The total entropic cost (that is, ) and its relation with the information erased appears in Fig. 6B. The dependence is monotonic, and thus reveals a trade-off between information processing and dissipation in sensory adaptation. Notably, for small acquisition of information (small ligand steps) it grows linearly with the information, an effect observed in ideal measurement systems [17].

Bottom Line: We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes.In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum.Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.

View Article: PubMed Central - PubMed

Affiliation: Max Planck Institute for the Physics of Complex Systems, Dresden, Germany.

ABSTRACT
Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response.

Show MeSH