Focus on NLM Scientists: Dr. Teresa Przytycka Goes the Distance

Where are you from?

“The question is always ambiguous for me,” says Teresa Przytycka, PhD.

“Do you mean geographically or scientifically?”

Both answers cover long distances for this NIH senior investigator.

Dr. Przytycka leads the Algorithmic Methods in Computational and Systems Biology section at Computational Biology Branch at NLM’s National Center for Biotechnology Information (NCBI).

The geographical journey

She was born and raised in Myszków, Poland, a small city with three factories surrounded by a rural area. “It was not a particularly intellectual city,” she says. Even though her parents were educated, they were coming from an area where this was unusual.

“Both of my parents came from a village where, at that time, people typically ended their education at basic reading and writing skills,” Dr. Przytycka explains. “In fact, since they grew up during the war, a good chunk of my parents’ schooling was within the Polish underground education system—very brave but not very rigorous.”

Casual, full-body image of Teresa Przytycka isolated against a white backgroundDespite growing up under unassuming circumstances, Dr. Przytycka considers herself fortunate.

She says, “Sometimes when you go through school, you’re lucky to have a group of curious friends. I was, and I think we inspired each other in dreaming big.”

That curiosity and big dreams stayed with her.

She studied at Warsaw University, earning a master’s degree in mathematics with a concentration in computer science. “The department of mathematics wasn’t infiltrated by the communist party,” Dr. Przytycka says, “and thus was an enclave of anti-communist opposition.”

After graduating, she stayed at the university, working as a research and teaching assistant in the Department of Mathematics, Mechanics and Informatics. It was there she met her husband, Jozef. He had a PhD in mathematics from Columbia University. Shortly after they married, Jozef was offered a postdoctoral position at the University of British Columbia (UBC), Vancouver.

So she applied to a PhD program in computer science at the same university.

Again, Dr. Przytycka felt fortunate—UBC accepted her.

She explains, “Poland was still communist and would be for another two years. It was extremely rare to do a PhD abroad.”

Plus, Dr. Przytycka was accepted without taking an English test. She would need to take it later.

“I think I was accepted despite a lack of proof that I could actually speak English because one of the faculty members, a Slovak professor, recognized the names of some of the mathematicians who taught me,” she explains. “The so-called ‘Polish School of Mathematics,’ the mathematics community in Poland, had international recognition. UBC had faith in me.”

It was only after arriving in Vancouver that Dr. Przytycka had to take English exams. Even though she didn’t take English in school, her knowledge of German and a friendship with an American journalist proved to be helpful.

“The journalist wanted to learn about life under communism, so we spent lots of time together,” she says. “I was a member of ‘Solidarity’—an underground anti-communist movement. Sometimes, I helped translate texts from underground newspapers for her.”

Dr. Przytycka planned to get her PhD and return to Warsaw University. “I got a four-year leave from my job there, and I had the best intentions to come back to it,” she says.

Four years later in 1990, she not only earned her PhD in computer science, she had two babies—two boys. “One was a toddler and one was an infant.”

And she gained something else.

“I wouldn’t have thought to push myself to get a PhD and give birth to two children in four years. That kind of builds your self-confidence,” she says. “I thought, wow, that was possible!”

But moving back to Poland wasn’t possible.

“I knew that if I went back with two children this age, I wouldn’t be able to return to my job, because of two things—lack of support for children this young and social pressure to be a stay-at-home mom,” she says. “There were very few day care centers for such young children. I don’t know if they were really bad or it was simply not acceptable for a self-respecting mother to use them.”

Either way, she wasn’t going to find out.

“That’s when the fun started!” Dr. Przytycka says with a smile.

With two children in tow, she chased down opportunities in the departments of computer science at Odense University in Denmark and the University of California, Riverside. Her husband followed when he could, but often she was on her own with the children.

She was also many times the only female member of the computer science faculty. She remembers receiving an invitation to a faculty barbecue that included, “Wives are welcome.” She joked, “Can Jozef come?” But most of the time she says she didn’t think very much about being the only woman (and later one of two) in the department.

The beginnings of a new direction

In the mid-1990s, she told her husband, “Next time you find a position, I’ll follow you.”

Unbeknownst to her at the time, she would be doing more than following her husband. She would be forging a new career.

A woman and man sit together, both reading documents. The man holds an infant.

Dr. Przytycka and her husband collaborate on parenting and a research paper in this 1987 photo taken at the University of British Columbia.

When her husband secured a tenure position at George Washington University, Dr. Przytycka, as promised, followed him, starting with a visiting position at the University of Maryland.

At the same time, while her research was still focused on the theory of algorithms, she began working on questions that were motivated by biology.

She explains, “There were some nice mathematical questions that arise in the context of evolution and other interesting, biologically motivated mathematical problems. How would you construct evolutionary trees? How to measure an agreement between two evolutionary trees constructed with different methods? Those are very mathematical questions, and while they don’t require biological understanding, they started my interest in biology.”

Her interest was piqued even more when she learned from the Notices of American Mathematical Society that the Department of Energy and the Sloan Foundation had announced a new fellowship in computational biology.

“To get it, I had to find a mentor, a biologist,” she said.

This wasn’t going to be easy. She didn’t know any biologists.

She approached Rao Kosaraju, a professor at the computer science department at Johns Hopkins University, whom she knew from her career as a computer scientist: Did he know anyone at Hopkins who would be willing to work with her in case she got the fellowship?

He did. She met George Rose, a professor in the biophysics department at Johns Hopkins Medical School.

“Professor Rose, a well recognized biophysicist working on protein folding, was actually happy to serve as my mentor. Once again I was fortunate and got the fellowship,” she said.

With this fellowship in hand, she crossed the line from working on computer science questions that are motivated by biology to biological questions that require computer science.

The road to NCBI

A few years later in 2003, in response to an advertisement for a principal investigator position at NCBI, she applied. She was offered the position and immediately accepted.

Not only was it a dream position scientifically, but hers and Jozef’s “two body” problem—two researchers trying to find jobs in the same geographical area—was finally solved.

She was officially working toward a career in biology. This still seems to startle her.

“I never really liked biology in school. It wasn’t quantitative then,” Dr. Przytycka says. “Biology has changed. It became mathematical, more quantitative and, from my perspective, far more exciting.”

Perhaps biology became more like Dr. Przytycka.

“It was fortunate for me that this trend started when I was at a point in my career when I was open to a big change,” she says. “It’s fair to say that I was amongst the first group of computer scientists that made their way to biology.”

Working for NCBI, she says, “Here, I do feel the presence of more women even if it’s only a small percent more than I have experienced before.”

Through the years, she has built her team of men and women thoughtfully—albeit unconventionally.

“Often people come to my group without any knowledge of biology,” Dr. Przytycka says. “You are well-served if people in your group are strong in computer science, and since this is the field where I’m coming from, it’s easier for me to work with people who think mathematically. I am able to see where their strengths are and can help them navigate biology, so they can direct their talents toward solving biological questions.”

Currently her team, named the Algorithmic Methods in Computational and Systems Biology group, consists of two staff scientists, two post-doctoral fellows, one post-baccalaureate and one research fellow. She says with pride, “This is a very strong and dedicated group. We are trying to lead in developing new methods and new ways of looking at data.”

Three areas

The team works in three basic areas: cancer and diseases, gene regulation, and algorithms for efficient utilization of large datasets.

In the context of disease studies, her group develops computational methods advancing systems-level understanding of cancer, the emergence of complex phenotypes, and the detection of causal genetic mutations and their interactions. “It’s computational and data driven. It often calls for development of new methods and algorithms. This suits me very well coming from computer science.”

Selection cycle: incubation, partitioning, removal, elution, amplification, next-gen sequencing

Schematic of one selection cycle of HT-SELEX (High Throughput Systematic Evolution of Ligands by EXponential Enrichment), which is used to identify aptamers.

As for gene regulation, in collaboration with Brian Oliver’s group at the National Institute of Diabetes and Digestive Diseases, they work on gene regulation in flies. Specifically, her group is developing methods for constructing condition-specific regulatory networks. In addition, in collaboration with another experimentalist, Dr. David Levens at the Center for Cancer Research, they study non-B DNA structures (DNA conformation alternative to the canonical Watson-Crick B DNA structure) and their role in gene regulation, mutagenesis, and diseases.

“Our analysis of these alternative structures has a lot to do with sequencing data. It’s very computational, not so algorithmic or mathematical as our other work, but it’s very close to biology, and I enjoy that,” she says. “I work with experimental biologists, and I learn a lot.”

The third area relates to the Big Data analysis. For example they developed novel clustering and motif-finding algorithms. Just last July, her team’s results in this area were featured in an NIH news release.

The team developed a software tool called AptaTRACE that could help drug developers and scientists identify molecules that bind with high precision to targets of interest.

She says, “This research is an excellent example of how the benefits of ‘big data’ critically depend upon the existence of algorithms that are capable of transforming such data into information.”

Driven by curiosity

Whatever she’s working on, Dr. Przytycka appreciates the opportunities at NIH.

“Research wise, I’m working on a large spectrum of problems. I think that working for NIH particularly helps me do that,” she explains. “First, I am surrounded by experts working on diverse biological inquiries. Exposure to this variety of biological questions and the realization that they can be helped with novel computational methods makes it is hard to resist and not give them a try.”

She continues, “Importantly at NIH, we do research that’s PI-initiated. I don’t have to apply for grants and prove to the grant review panel that I can solve a problem before solving it, I can just go for it!”

For this mathematician computer scientist who works in biology, curiosity is a large part of what drives her.

And when that curiosity can be helped with an elegant computational algorithm, this is the best combination.

In NLM Focus on Scientists, we introduce you to some of the scientific leaders at the National Library of Medicine. Today we’re privileged to share Dr. Przytycka’s story. Last October, we wrote about Dr. Kim Pruitt. We’ll feature more scientists in 2017.

More Information
Algorithms for Life” | Research in Action, the online magazine for the NIH Intramural Research Program (January 2013)

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