Squids’ aberration-free eyes

The deep ocean is a dim place. The intensity of light reaching a depth of 300 m can be 1/10 000 that at the surface. To optimize the light-gathering ability of their eyes, squid species such as the glass squid pictured here have evolved large spherical lenses. A second evolutionary adaptation has enabled squid to grow lenses that don’t suffer spherical aberration: The refractive index of the lens varies from 1.3 at the edge, matching seawater’s refractive index, to 1.6 at the center.
To learn how squid build their graded-index lenses, the University of Pennsylvania’s Alison Sweeney
Sweeney and colleagues analyzed their data using an approach known as patchy colloid theory, which treats individual proteins as spherical particles with sticky patches. Particles with two patches can attach to two other particles. That picture represents the case in which a protein’s two loops each link up with a loop in another protein. Sometimes, a protein’s loop simultaneously links with loops from two different proteins, or the body of the protein attaches to the loop of another. Those cases would be represented by particles with more than two patches.
According to the theory, such patchy particles become gels when the particle density reaches some threshold determined by the number of patches on the constituent particles. Sweeney and her colleagues found that squid-lens cells produce differing mixtures of S-crystallin variants at different lens radial positions. At the lens periphery, the predominance of long-looped proteins results in an average of about two patches per particle. At the core, a greater number of short-looped proteins means more patches per particle. The consequent radially varying protein density leads to a gradient in the refractive index.
Sweeney doesn’t expect that the discovery will lead directly to aberration-free optical lenses for human applications. But she points out that the squid lens is a natural system that has evolved to take advantage of self-assembly in ways that materials scientists can learn from. (J. Cai et al., Science 357, 564, 2017