New Investigators on the NLM Block!

How NLM’s newest investigators are advancing discovery through exhilarating research

NLM is enhancing its Intramural Research Program to better serve scientists, health professionals, and the public.We would like to introduce you to two exciting, new additions to the NLM team: Xiaofang Jiang, PhD, and Lauren Porter, PhD, recently joined NLM as tenure-track investigators. Both play important roles in supporting NLM’s pioneering research to advance knowledge in biomedical informatics, computational biology, and data science.

Dr. Jiang’s research focuses on the development of computational methods to advance our understanding of the human microbiome, which plays a vital role in our health. Her lab uses bioinformatic methods to predict what the trillions of microbes living in and on the human body do, how they spread between people, and which kinds of genes the microbiome community shares.

Dr. Porter is a Stadtman-Tenure Track Invesitgator researching proteins—specifically fold-switching proteins—which act like transformers because they can change their structures and functions in response to changes in their environment. Proteins play many critical roles in the body. Dr. Porter also has a joint appointment at the National Heart, Lung, and Blood Institute, where she directs an experimental laboratory. This allows her to participate in the entire process of scientific discovery: her data-driven calculations help her to generate hypotheses that she can test in the lab.

Xiaofang Jiang, PhD

What is the focus of your NLM research?

We are developing computational methods to advance our understanding of the human microbiome. My lab seeks to use bioinformatic methods to predict what the microbes that live in and on us are doing, how they spread between individuals, and what kind of genes are shared in the microbiome community.

Why is it significant, in your opinion?

Despite large amount of microbiome data available, turning this data into actionable insights is challenging and demands both comprehension of the biological literature and bioinformatic skills. My lab is developing approaches to fill this gap.

For example, one project we are working on is developing a functional profiling framework for the prediction of the functional capabilities of microbiomes based on metagenomic sequencing data. This project will provide a health-relevant feature database as well as a search tool for effective in silico identification of health-relevant features of the human microbiome. This could lead to insights amenable to experimental validation and potentially support clinical decisions.

I believe that there is an enormous opportunity to modulate the human microbiome to improve health. The tools my lab is developing will help to understand the microbiome to determine what alterations can be made to improve health.

What or who inspired you to pursue your career?

I’ve had amazing teachers, mentors, friends and colleagues that have supported me and helped pave my path to becoming an investigator at NLM.

Ever since I was a kid, I liked to be intellectually challenged and had a strong curiosity about how things work.

Although I am enthusiastic about science and research, I did not have a strong academic ambition at an early stage. It was my Ph.D. mentor, as well as one very close colleague, who saw my potential and encouraged me to pursue a career in academia.
How did you get started in your career?

I’ve had a long interest in math and physics ever since I was in middle school. However, I was discouraged to choose math or physics as a major when I entered college. My family and friends thought that I would have a hard time finding a good job as a female in those fields, at least based on what they saw in China at that time. In the end, I chose biology as my major. In a way, this turned out to be a great experience because it opened a new door for me. It provided the foundation for my current research and led me to a beautiful world of evolution and life science.

For my Ph.D., I chose computational biology because it combines my passion in computer science as well as biology. I came to the U.S. and completed my Ph.D. at Virginia Tech. That was when I met a group of wonderful scientists and began my journey as a researcher. Later, I got interested in the microbiome and started to use bioinformatics to study large-scale biological data in the microbiome research field as a postdoctoral researcher at MIT and the Broad Institute. 
What really gets you jazzed about science and research?about yourself.The privilege to be the first one to discover something new.

The fulfillment of discovering something new that could improve human health.

The eureka moment after countless efforts.
If you weren’t doing what you’re doing now, what else might you be doing?Maybe I’d be a mathematician or a physicist, but most likely I would be a computer programmer.
Tell us something surprising about yourself.I am a fan of magical realism novels. I love the book “One Hundred Years of Solitude” by Colombian author Gabriel García Márquez.
What made you want to come to NLM?

I believe that NLM is one of the few places where I can establish my data-science research program.

There is a critical mass of truly exceptional and top-notch scientists here. It is joyful and intellectually stimulating to work with them. I also find that people at NLM are approachable—from the director to the top scientist. You can just knock on their door and talk with them.

In addition, I have access to the phenomenal resources available to investigators in the NIH intramural research program.NLM is a fantastic place for data-driven research. The interdisciplinary nature of data science requires people from diverse backgrounds to work together, and NLM is dedicated to creating a friendly, safe environment for everyone.

I was also impressed by the leadership of NLM and the mission and directions they want to pursue.

In a few words, I believe NLM is the place where I can do the science I enjoy, and make an impact.

Lauren Porter, PhD

In lay terms, what is the focus of your NLM research?

Broadly speaking, I research proteins. Proteins play many important roles in human health—carrying oxygen in our blood, digesting food, and helping our eyes to detect light are just a few examples. Many proteins, including the ones just mentioned, require a stable three-dimensional structure, or fold, to carry out their functions. My research focuses specifically on fold-switching proteins, a recently discovered class of proteins that can change their structures and functions in response to changes in their environment.

Why is it significant, in your opinion?No introductory-level biochemistry textbook is complete without a chapter about how a protein’s primary sequence of amino acids determines its fold. Protein structures are so important that several Nobel Prizes have been awarded for determining them. Despite much technical progress, solving protein structures experimentally remains very laborious and expensive, and knowing the structures of diverse proteins is crucial for both basic research and drug design. Thus, computational prediction of a protein’s structure from its amino acid sequence is a challenge of major importance.

Nearly all computational work so far has focused on predicting a single protein structure from the protein’s amino acid sequence. My research challenges the one-sequence-one-structure paradigm. In a recent publication, Loren Looger and I found nearly 100 examples of proteins that can adopt more than one stable fold. This structural heterogeneity allows proteins either to perform more than one function or to be highly regulated in cells. Now I am taking my research to the next level by developing computational approaches to predict which amino acid sequences can switch folds. Also, I have a joint appointment at the National Heart, Lung, and Blood Institute (NHLBI), where I can validate these predictions experimentally. So far, they seem to be working.

This basic research has significant implications for human health. A number of fold-switching proteins are associated with diseases such as cancer, autoimmune disorders, and bacterial and viral infections. Right now, very little is known about how these proteins work. Understanding their mechanisms could lead to development of new therapeutics.
What or who inspired you to pursue your career?

In college, I majored in physics and math. During my sophomore year, my dad was diagnosed with stage IV lymphoma and began treatment at Johns Hopkins University Hospital. Thankfully, his life was saved through many rounds of chemo and a bone marrow transplant. Watching him suffer through those treatments made me think that there must be a better way to treat cancer, and probably other diseases, too. Because of that, I decided to get a Ph.D. in biophysics, hoping to use quantitative approaches to advance medical and biological research.

How did you get started in your career?

After getting my Ph.D. in biophysics at Johns Hopkins University, I did postdoctoral work on protein fold switching, beginning at the University of Maryland, where I learned to do experimental protein engineering. The Maryland Academy of Sciences awarded me an Outstanding Young Scientist Award in 2015 for that work. Soon afterwards, I took a Research Scientist position at Howard Hughes Medical Institute, Janelia Research Campus, where I focused on the role of fold switching in biological processes.

What really gets you jazzed about science and research?

There is nothing that satisfies me more than making a computational prediction that’s consistent with experimental observations, and I love that I get to do both computation at NLM and experiments at NHLBI. I also enjoy working with trainees. Seeing a postdoc or student grasp a concept or independently generate and test their own ideas is very exciting.

If you weren’t doing what you’re doing now, what else might you be doing?

That’s very hard to imagine. Maybe data analytics.

Tell us something surprising about yourself

I love to travel. My favorite trip (so far) was a two-week vacation to Malaysian Borneo. There, my husband and I climbed a mountain, caved, and went on a river safari.

What attracted you/made you interested in working at NLM?

The high caliber of scientific work done by NLM’s scientists was definitely a draw. My research is built on some of the tools and work that came out of NLM’s intramural research program at NCBI. A few examples include protein BLAST, Eugene Koonin’s work on protein evolution, and databases such as Genbank.

Now, it’s great to be part of the team. Other NLM investigators are not only leaders in their fields but also very approachable and helpful. Furthermore, I have the opportunity to collaborate with top-notch scientists in other Institutes. I am fortunate to have a joint appointment with NHLBI, where I do experiments. Interactions with the investigators there also have been positive.

Furthermore, NLM offers world-class resources to do heavy-duty computation and has experts with whom I can consult when I want to try something new. For example, I would like my lab to eventually lead the way to the development of new protein structure/function databases that incorporate our insights and can be queried online. Although I have never done this before, plenty of my colleagues have, so I’m optimistic about realizing this goal.

One of the pillars of NLM’s strategic plan is to accelerate data-driven discovery. Can you tell us more about your research and how it supports NLM’s strategic plan?

To date, all experimentally characterized fold-switching proteins have been discovered by chance. I am currently using data-driven approaches to identify fold-switching proteins from their genomic sequences, and it appears to be working. This is remarkable because more typical approaches, such as protein prediction software like Rosetta, haven’t had much success at this.

My research aligns with a number of the NLM’s objectives, especially “connect[ing] the resources of a digital research enterprise.” Specifically, we combine data and computational tools from a number of different resources to obtain novel and interesting results. My current research combines more than 10,000 sequences from Genbank, found by protein BLAST, curated by UniProt, and analyzed by JPRED, a computational tool for predicting protein secondary structure. I am optimistic that this approach will accelerate the discovery of more fold-switching proteins, revealing their biological roles and suggesting possible treatments for disease.

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