All posts by: Sarah Hansen, M.S. '15

Cell migration—how, when, and why cells move—has important implications for understanding development and diseases such as blood cell disorders, rheumatoid arthritis, and metastatic cancer. Michelle Starz-Gaiano, associate professor of biological sciences, has learned a great deal about cell migration from observing Drosophila melanogaster, the humble fruit fly, in her lab. She’s also learned that experimental tools have their limitations.

“We have fantastic genetic tools in Drosophila, and we have great live imaging, so we can get pretty far doing that,” Starz-Gaiano says. “But then we encounter things that we can’t explain.”

That’s where her decade-plus collaboration with Brad Peercy, associate professor of mathematics, comes in. In their partnership, Peercy develops mathematical models to represent the movement of cells across developing eggs in the fly ovary. Now, a three-year, $370,000 NSF grant will support the duo as they combine their expertise to further explore the regulation of cell movement.

“I think this project has really big implications for how we think about development and how organs and tissues function,” Starz-Gaiano says, “because it’s looking at aspects that people haven’t yet paid attention to.”

A fresh perspective

Scientists can learn a lot about cell migration through experimental approaches like those Starz-Gaiano employs. However, some experiments are too complex or too expensive to attempt without a powerful reason to believe they will reveal new and useful information.

Turning to mathematical modeling has been particularly helpful for pointing wet lab scientists in the right direction before they invest in complicated experiments. “The collaboration has been incredible in making the best predictions for how to explain confusing results. It’s enabled us to narrow down the set of things to test,” Starz-Gaiano says.

For example, cell migration in the fruit fly ovary happens in several complex stages. Chemical signaling and the geometry of the ovary both play a role in regulating the process. “There are lots of different interesting features that are ripe for having a mathematical framework put around them,” Peercy says, “and the math can sometimes point to looking at something a little bit differently than biologists might otherwise.”

Now the challenge is that the math has pointed to certain attributes of the migration process that may be impossible to test in a live organism with today’s technology. “The models that Brad’s group has made are so compelling that now we have to figure out if we can show that biologically,” Starz-Gaiano says. “That’s a big focus of some of the work in the lab now.”

Uncharted territory

This new grant focuses on the math side of the work. Peercy and Starz-Gaiano have been collaborating since 2008, when they partnered to work with undergraduates as part of the former, NSF-funded Interdisciplinary Training for Undergraduates in Biological and Mathematical Sciences program.

Since then, Peercy and his team have developed several models for different aspects of the cell migration process. The next step is “integrating some of the models that we’ve already developed into a more comprehensive model of the system,” he explains. For that, Peercy and Starz-Gaiano will benefit from the computational expertise of Matthias Gobbert, professor of mathematics, who is another co-investigator on the grant. He will help make the computational processing more efficient, and therefore feasible in a reasonable amount of time.

Another aim of the project is to further investigate a set of chemical reactions, known as a signaling cascade, involved in triggering cell migration. “The signaling cascade that the model is for is very well conserved across species, and it’s implicated in a lot of human diseases,” Starz-Gaiano says. “The model pointed to a certain kind of regulation that hasn’t been very well explored, so we want to follow up on that.”

The team will also work to better understand how the restricted space of the egg chamber affects how cells and chemical signals move, and how that affects cell migration. “Being able to map that complicated geometry into a computational framework is something we’re interested in,” Peercy says. For this part of the project, they’re collaborating with Tagide deCarvalho, director of UMBC’s Keith R. Porter Imaging Facility.

Looking at the space between cells is a new area of research. “People haven’t done that,” Starz-Gaiano says. “They just think this one sends a signal and that one gets it and it’s over, and we’re saying, well, what happens in between?” Failure of a signal to reach its final destination can contribute to some birth defects, Starz-Gaiano explains. She also wonders if the same could be true for some cancers.

A new approach

As scientific discovery marches onward, researchers in fields that were once seemingly disparate find themselves relying on each other more and more. “The biology is insufficient to capture what’s going on, so we need different approaches,” Starz-Gaiano says.

Collaborations between researchers in different fields can be tricky to navigate, as each side learns to speak a new language and engage in different ways of thinking. But when everyone involved is on board, the results can be groundbreaking.

“You see strong collaborations between experimentalists and theoreticians when they are willing to sit in uncomfortable situations,” Peercy says. That might mean a biologist thinking about differential equations or a mathematician trying to understand the reproductive process of a fruit fly.

Peercy and Starz-Gaiano’s easy rapport and long history of working together makes it clear that they’ve crossed that bridge and are comfortable taking on the unknown together. They recognize the benefits that combining their unique research skill sets can offer.

“The only way that you can solve complex problems now is to use multiple strategies at the same time,” Starz-Gaiano says. “And increasingly, that’s what we’re faced with in biology—these problems are too complicated for one method to tackle them.”

Banner image: Michelle Starz-Gaiano (right) works with Jeffrey Inen ’18 in her lab. Photo by Marlayna Demond ’11 for UMBC.

Salamanders regenerate their tails. Sea stars regenerate their arms. Most species of planaria, a type of flatworm, can regenerate everything from their heads (complete with brain) to their digestive organs. But if you lose part of a finger in a shop class accident, or while chopping vegetables for dinner, you’re out of luck—for now.

“Why can the worm do it, and we cannot?” asks Daniel Lobo, assistant professor of biological sciences. That’s not really the question, though, he explains.

“We were able to generate ourselves when we were embryos. So we have all the information of how to generate a new hand, for example,” Lobo points out. “The genes are there. You have the same information in your cells.” So why can’t humans generate body parts after that early stage of development? 

“Actually, we could,” Lobo argues, if we could somehow reactivate the same genes that enabled us to develop in the womb. So, “Can we reactivate them?” he asks. That’s the real question, which he is working to answer with a five-year, $1.9 million grant from the National Institutes of Health.

Restoring independence

Lobo is tackling this question through a unique combination of techniques: wet lab experiments with planaria, and machine learning approaches that use computers to help deduce genetic regulatory networks. Previous work successfully restored the regeneration capacity of a species of planaria that had lost that ability. While still a long way from growing a human finger back, it’s a sign that the promise of reclaiming regeneration is not so far-fetched.  

This line of research could eventually make it possible for people with limb loss, such as injured veterans, to regrow lost body parts. By increasing understanding of genetic regulation, Lobo’s work might also enhance knowledge of development and developmental diseases, and how cancerous tumors work around regulatory networks to grow unchecked.

The right worm for the job

Lobo uses an approach known as systems biology to tackle these big ideas. “We mix the fields of math, computer science, and biology,” he says. “We use computational techniques to extract knowledge from biological data sets.” The result is mathematical models that can explain observations the team makes in the lab. The models can also make predictions, which researchers can test in the lab.

Planaria are the ideal model organism for lab work, because of their astonishing ability to regenerate. Even a worm in eight pieces will grow back into eight complete worms with proper proportions. Like mammals, the worms also grow when they have enough to eat. However, when hungry, rather than simply getting thinner, their whole bodies shrink to maintain proper proportions. So, beyond regeneration, “The general idea is to understand how gene regulation works to specify shapes and forms in biology,” Lobo says.

Teamwork and flexibility

“This program is too hard to do with just wet lab or just computational approaches,” Lobo says. “You need both.” 

Because the work requires such a range of techniques, it also requires team members with a range of skills. Lobo’s lab includes undergraduate and graduate students in math, computer science, bioinformatics, and biology. The new grant will also allow him to bring on two new postdoctoral fellows, one on the wet lab side and one computational.

“We will be able to create that synergy and get people trained in both fields in the same lab,” says Lobo. He describes the interactions between lab members from different fields as essential to the success of the research.

Rather than fund a specific project, Lobo’s new Outstanding Investigator Grant will fund the lab as a whole. “It gives you a lot of freedom to adapt to whatever discoveries you make,” he says. “You have the flexibility to pursue the details that you need to.”

Teaching computers so they can teach us

The computers the team uses are powerful, but for now, they still benefit from some human guidance. To give the computers a head start on figuring out the genetic regulatory networks, the team inputs certain rules before they add loads of data from their own experiments and other labs’ work. That also ensures the computers don’t come up with a solution that is biologically impossible.  

“We know that genes generally interact in certain fashions, and those interactions can be represented in different ways mathematically,” Lobo explains. “So we can tell the computer what kinds of interactions a gene can have. And then it is free to put those interactions together in ways that make sense.”

Lobo compares it to working with Lego blocks. “How many structures can you make with Legos? Unlimited, right?” he asks. “So the computer also has an unlimited space to search, but only with things that can be put together. You cannot make a perfectly round Lego ball, for example, if you only have square blocks.”

Speeding up the science

Combining wet lab and computational approaches will drastically increase the pace of discovery. A high performance cluster of computers can come up with a probable solution by testing more than a billion possible models of a regulatory network in a few days—a task that would take infinitely long for a team of humans.

Using computers to come up with plausible models, testing the models’ predictions in the lab, and then feeding the new data back into the computers to refine the model will bring researchers ever closer to understanding how different biological systems work. Research teams can apply the same investigative process to any number of biological questions, from regeneration to metastasis.

Some biologists may shy away from programming, but as Lobo says, “Biology is more and more computational. We are reaching a point that without a computer to process the data you cannot do almost any experimental work in biology.” 

He argues that interdisciplinary teams like his are the future—that diverse groups of researchers will increasingly combine multiple approaches to answer the big questions, to speed up scientific progress in ways that will have real, positive impact.

Banner image: Daniel Lobo in front of the Biological Sciences Building mural. Photo by Marlayna Demond ’11 for UMBC.