Observation, algorithm, robot help understand parasite's movement

A group of researchers at Stanford University has combined live observation, mathematical insights and robots to reveal the movement of parasitic larvae through the water and then cause schistosomiasis, a tropical disease, among people.

People become infected with schistosomiasis when the larval form of the parasite leaves the freshwater snail host, swims through the water and penetrates human skin.

Once in a person, the larvae develop into adult schistosomes. The female parasites later release eggs, which are either passed out of the body through urine and stool or trapped in bodily tissues, triggering an immune response and large-scale organ damage.

When the eggs from urine or stool enter a water body with the freshwater snail hosts, the cycle begins again.

"We started thinking about the ecological context for the schistosomiasis disease cycle when, out in the field, we were seeing the terrible trauma it inflicts on people," said Manu Prakash, an assistant professor of bioengineering at Stanford and senior author of a study published on Monday in the journal Nature Physics.

"It manifests over long periods of time, and if the water body near you is infected, there is a very high likelihood that you will get the disease. So, effectively, you can take drugs that could cure you for some time but you get re-infected again."

Schistosomiasis infection often produces abdominal pain, diarrhea and blood in the stool or urine. It can also cause learning deficiencies in children and an inability to work in adults that traps families in a poverty cycle.

Over the years, adults can develop bladder cancer or severe kidney damage, which reduces their quality of life. In some cases the disease results in death.

It disproportionately impacts people who live in poverty, as they are more likely to be vulnerable to infection because they often have less access to adequate sanitation or to safe water for drinking, chores, recreation, fishing or agriculture. Even after treatment, people are often re-infected through their constant contact with contaminated water.

The World Health Organization (WHO) estimates that 258 million people required preventive treatment for schistosomiasis in 2014, with an estimated 20,000 deaths.

Prakash turned his attention to preventing infections at the first place and decided to investigate how schistosomiasis larvae swim to find a human host. This is a valuable question because, in its larval form, the parasite has no feeding mechanism and must find a host within about 12 hours or die. It stands to reason, then, that the larvae likely have some special, extremely efficient swimming skills.

"This was unlike anything I had seen before," Deepak Krishnamurthy, a PhD student in the Prakash Lab and lead author of the study, was quoted as saying in a news release from Stanford, in northern California on the U.S. west coast.

"When I looked at this parasite, I was fascinated by the fact that it was swimming in a completely different way as compared to any other microorganism I knew about. The parasite had a mysterious forked tail, something that has never been seen before in any other swimming microorganisms."

The researchers imaged live parasite larvae with high-speed microscopy, created a mathematical model to understand how the parasite interacted with the surrounding fluid, and then translated that model into a scaled-up robotic swimmer as a physical extension to learn more about physical parameters at play.

The team noticed a few swimming styles that schistosomiasis larvae employ in different situations, and which differ primarily in the position of the forked tail.

Of those, one stood out as unique: the larvae stick the tail out perpendicular from the body, like the letter T, prompting the researchers to dub them T-swimmers. The larvae switch to T-swimming when they are moving against gravity, which they seem to do in order to be near the water's surface, where they are most likely to find a human host.

"We spent countless hours watching hundreds of these parasites swim -- it's like an obsession," said Yorgos Katsikis, a former PhD student in the Prakash Lab and co-author of this study. "Then we developed image-processing algorithms that would process this data automatically without any experimental bias."

These custom algorithms revealed in detail the exact kinematics of how the larvae bend their body and rotate their head, how fast they move and how they accelerate and decelerate and perturb the surrounding fluid.

The researchers developed multiple mathematical and robotic models for how a T-swimmer could swim. The mathematical representations look like three rods, one representing the larvae's forked tail and the other two its bending tail and body. The robots were similarly structured and swam through corn syrup, a 10,000 times more viscous counterpart to the water the larvae infests, to recreate the same physical effects.

With these models, they could make the model larvae do strokes that involved varying combinations of tail stiffness and bending movement.

"In many cases, we try to replicate nature in robots. This was very different," said Krishnamurthy. "On the face of it, it looks like I'm trying to make a robot that swims like a parasite, but the truth is that it was the exact opposite: I was building a robot to actually understand how the biological parasite swims."

What these models and various modifications revealed is the larvae's real swimming stroke was indeed the optimal version.

Prakash and Krishnamurthy, who have been in Madagascar collecting infected snails and studying the ecology of this parasite in open water in rural villages, hope their work in and out of the lab will bring them one step closer to an ecological solution to this widespread disease. Endit