Giant clams, pollen, and squid eyes — blueprints for a better world

Studying the evolution of biological soft matter and the mechanisms by which they assembled, may lead to creating new biofuels, chemicals, and materials.
Giant clam.


Alison Sweeney has long suspected the best blueprints for innovation already exist in nature.

They’re encrypted in the iridescence of giant clams. They’re hidden in the eyes of mid-ocean squid. They’re inscribed on the surface patterns of pollen.

You just have to look closely for them and determine how they work, says Sweeney, an associate professor of physics and ecology and evolutionary biology (EEB) in the Faculty of Arts and Sciences.

Sweeney joined the Yale faculty in 2019. Her lab focuses on the evolution of biological soft matter and the mechanisms by which they assembled themselves over time. Understanding those mechanisms, she says, may offer the means for creating new biofuels, chemicals, and materials that help sustain planet Earth.

YaleNews spoke with Sweeney recently about her research.

How did you come to study biological features and the way they evolved?

Alison Sweeney: I was drawn to be a scientist in the first place when I realized that evolution is much smarter and subtler than we are. Evolutionary intelligence — the clever things that result from the iterative process of evolution — is capable of coming up with incredible solutions to questions we continue to pose today.

A really beautiful lens for seeing and understanding this cleverness is in the realm of optics. It’s a very straightforward question to ask, “How does light propagate through a material and what implications does that have for optical function?” I realized pretty early on in graduate school that asking these optical questions about evolved materials was a good way to come up with satisfying, sometimes literally clear answers, about what evolution was doing. Since then I’ve moved into other engineering questions, but this notion that optical questions would lead to good answers was an early insight for me.

Your specialties — physics, and ecology and evolutionary biology — are an interesting combination. How does each discipline help inform your research?

Sweeney: For me, it’s two different kinds of rigor that I find satisfying.

EEB brings with it a very specific wealth of knowledge about animal diversity. In my lab, we study giant clams, and although we tend to talk about them as a composite animal, there are seven to 10 species of giant clams. Each of them has its own subtleties and nuances of where they like to live and what they look like. You can’t brainstorm or problem solve about their evolutionary mechanisms unless you’ve done the hard, organizational biology work to figure out all of the differences.

On the other side, physicists are famously rigorous about mechanisms. Physicists are not interested in problems or ideas that can’t be expressed or described as lines of math. That’s a clarifying way of looking at the world that I really enjoy. That combination of knowing exactly what we’re talking about in terms of organism diversity, and then this idea that if I can’t write it down in math, maybe I should move on to something else — I love that. I look for places where I can knit those two things together, and giant clams are one of those places.

How so? What do we know about giant clams that can be helpful in other ways?

Sweeney: We’re working on a paper now that makes a strong claim that giant clams are the most efficient solar energy system on Earth. By that I mean giant clams take in the greatest fraction of sunlight and convert it into chemical energy. We can compare it to any other system, from tropical rainforests to cornfields in Iowa. The thing that comes closest is boreal spruce forests. We actually think the giant clam has done a recapitulation of the solar harvesting strategies that exist in spruce forests — they’ve just squeezed the whole thing down.

This is where the physics comes in. We can write down a mathematical description of how this works. It has to do with the way light scatters from spherical particles onto vertical surfaces. What both the giant clam and the spruce forests have discovered is that you can physically absorb a lot more sunlight if your absorbing surfaces are parallel to the incoming light rather than perpendicular to them. And then you have to spread that light out over the vertical surfaces.

Clams and spruce forests both have these vertical pillars and a mechanism to redistribute and wrap light around them. The spruce forests are surrounded by a cloudy haze that acts as a light redistribution layer and the trees themselves are vertical catchers of the light; in the clams, their iridocytes [cells filled with iridescent crystals] are very similar to clouds and there are pillars inside the clam that catch the light.

How about pollen? Why is their surface shape important?

Sweeney: Knowing how to control surface patterns at the scale of a few nanometers is very useful for chemistry, materials science, quantum science, and a number of other fields. And it just so happens that pollen do that exquisitely.

Through our work, we now know the physics underlying where pollen shapes come from. Although we’re convinced that in pollen these patterns are random, we’re able to show engineers how pollen control surface shapes at the nano scale.

Now let’s talk about squid and their eyesight.

Sweeney: Human eyes are able to bend light because of our cornea, which puts air and water in front of the eye. But when you’re a squid living in the ocean, you don’t have a cornea. You have to make this big, honking spherical lens that does the job of both the lens and the cornea.

Squid and fish need this big, dense sphere to have enough light-bending power to make good pictures in the ocean, but the spheres by themselves suffer from spherical aberration — they lose focus. To correct this, they have to build a density gradient of proteins in their lens that makes up for the spherical aberration. That part has been known for a long time, but we’ve discovered how, specifically, the squid builds this density gradient, by way of self-assembling.

In physics, there is a theory of how particles with “sticky” spots are able to self-assemble in useful ways. It’s called patchy particles and it works like this: We have a collection of particles — almost like Lego bricks — with a certain number of sticky spots. If you know exactly what your bricks/particles look like, you can predict what you’ll get when they assemble. This theory lives mostly in the realm of equations, but we found that what the squid lens does is build these little Lego bricks out of proteins that then make the things they’re supposed to make. It’s the first natural example of the patchy particle theory.

Realistically, engineers would like to leverage this principle to build addressable materials that know where they are going in an assembly. The squid shows us this fully worked example of how to make a sophisticated, addressable material this way.

What technologies come into play as you conduct your work?

Sweeney: What really makes our work possible is computers and the ability to do numerical simulations of these biological systems. For example, let’s say I wanted to throw a bunch of sticky particles into a box and see how they’d interact over a long period of time — that kind of simulation depends on modern computing. It allows us to create this link between theory and biology that wouldn’t have been possible before.

What evolutionary mechanisms will you be looking at next?

Sweeney: My Yale colleagues Casey Dunn, Jing Yan, and I have a new collaboration around the extracellular polymer networks that biological cells create. There’s an indication that the tipping point between the chemistry of small things and the materials properties of large things occurs when single cells start to become collectives of cells. So how did single cells learn to make materials, when making those materials depended on cooperation with other cells? We’re hoping to get at that from looking at the polymer networks rather than at looking at cell behavior.

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