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Evolutionary bet-hedging at the nanoscale

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Abstract Evolutionary bet-hedging (EBT) is a theory describing a trade-off between the mean and the variance of fitness. It explains how in varying environments, lower-quality adaptations to a broader diversity of conditions (reduced mean fitness with low variances) can be evolutionary favored over an ideal adaptation to a specific narrow condition (high mean fitness with higher variances)1-5. Examples of EBT include strategies governing germination of desert annual plants, egg size variability of birds, metabolic switching in bacteria, and many more2,3,6. EBT at the nanoscale, however, has never been observed. Analyzing corneal nanocoatings7,8 across Coleoptera species (beetles), we here come across sexually dimorphic nanostructures garmenting eye surfaces of fireflies from the genera Lampyris and Luciola. While in Lampyris, as in other previously studied arthropods, corneal nanocoatings display dichotomy between the two competing functionalities – anti-reflectivity and anti-adhesion8,9, those of Luciola are surprisingly superb in both. Turing reaction-diffusion mechanism based on interactions of a protein Activator and a lipid Inhibitor governs assembly of corneal nanocoatings7,8; modeling predicts that the unique Luciola nanostructures can only form within a narrow set of parameters, suggesting the sensitivity of these insects’ vision to environmental conditions, such as temperature. Corroborating this prediction, the areal of Luciola is restricted to the mild Mediterranean, while that of Lampyris spreads across most of Eurasia. In a forward-engineering approach, artificial Turing nanocoatings can be produced8,10,11. We find that modifying the diffusion coefficient of the Turing Activator creates Luciola firefly-like nanocoatings whose parameter space is restricted as compared to the parental structures: they can form only in a narrowed range of temperatures. Our work thus describes the first example of EBT at the nanoscale; its translation to nanotechnology permits thermal control, through light interference and plasmon resonance, of surface nanopatterning for variety of applications.
Title: Evolutionary bet-hedging at the nanoscale
Description:
Abstract Evolutionary bet-hedging (EBT) is a theory describing a trade-off between the mean and the variance of fitness.
It explains how in varying environments, lower-quality adaptations to a broader diversity of conditions (reduced mean fitness with low variances) can be evolutionary favored over an ideal adaptation to a specific narrow condition (high mean fitness with higher variances)1-5.
Examples of EBT include strategies governing germination of desert annual plants, egg size variability of birds, metabolic switching in bacteria, and many more2,3,6.
EBT at the nanoscale, however, has never been observed.
Analyzing corneal nanocoatings7,8 across Coleoptera species (beetles), we here come across sexually dimorphic nanostructures garmenting eye surfaces of fireflies from the genera Lampyris and Luciola.
While in Lampyris, as in other previously studied arthropods, corneal nanocoatings display dichotomy between the two competing functionalities – anti-reflectivity and anti-adhesion8,9, those of Luciola are surprisingly superb in both.
Turing reaction-diffusion mechanism based on interactions of a protein Activator and a lipid Inhibitor governs assembly of corneal nanocoatings7,8; modeling predicts that the unique Luciola nanostructures can only form within a narrow set of parameters, suggesting the sensitivity of these insects’ vision to environmental conditions, such as temperature.
Corroborating this prediction, the areal of Luciola is restricted to the mild Mediterranean, while that of Lampyris spreads across most of Eurasia.
In a forward-engineering approach, artificial Turing nanocoatings can be produced8,10,11.
We find that modifying the diffusion coefficient of the Turing Activator creates Luciola firefly-like nanocoatings whose parameter space is restricted as compared to the parental structures: they can form only in a narrowed range of temperatures.
Our work thus describes the first example of EBT at the nanoscale; its translation to nanotechnology permits thermal control, through light interference and plasmon resonance, of surface nanopatterning for variety of applications.

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