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Decoding and Targeting RNA with CRISPR

At first, Xuebing Wu , PhD, was on track to pursue a research career in computer engineering. After taking a course by Dr. Yanda Li, a pioneer of bioinformatics, Dr. Wu’s interest quickly shifted and he soon got hooked on genomics research and computational biology.

Xuebing Wu, PhD
Xuebing Wu, PhD

“Around that time—2003 to 2004—the human genome project had just been completed, and there had been lots of enthusiasm about using computational approaches to decipher the human genome,” he said. “I was excited to dive into this field that seemed wide open for research possibilities.”

Dr. Wu joined Columbia University’s Department of Systems Biology in the fall of 2018, with a joint appointment in the Department of Medicine’s Cardiology Division . He also is a member of the Herbert Irving Comprehensive Cancer Center at NewYork-Presbyterian/Columbia and the Columbia Data Science Institute , and his lab straddles basic science and computational biology. Dr. Wu and collaborators often consider how their work can make an impact in novel therapeutics. 

At the center of his interests is understanding the fundamental principles of gene regulation in human cells through integrative genomics approaches. His previous work has uncovered important roles of RNA sequence and structure signals in controlling the expression and evolution of the mammalian genome. His lab currently studies RNA-centric gene regulation, focusing on mRNA structures and mRNA translation. Dr. Wu and his team are increasingly turning their attention to the development of genomic technologies such as the revolutionary CRISPR/Cas system and a high throughput analysis technology called massively parallel reporter assays (MPRA), as well as novel computational tools and deep learning models to study gene regulation at a global scale. 

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Yufeng Shen, PhD: Seeking Discovery of Novel Genetic Variants that Cause Disease

Yufeng Shen , PhD, found his passion for science in childhood, but he developed a fascination for both math and physics as his education progressed. In an earlier generation, he would have needed to choose between divergent paths. Instead, he chased his calling within an important emerging discipline. 

Yufeng Shen, PhD
Dr. Yufeng Shen

Dr. Shen was awarded tenure and promoted to the rank of associate professor in Columbia University's Departments of Systems Biology and Biomedical Informatics (DBMI) last summer. Utilizing new methods, he answers long-standing questions that impact health. Specifically, his research has focused on discovering novel genetic variants that cause human diseases.

His current work focuses on developing new computational methods to interpret genome data, identifying genetic causes of human diseases by integrating multiple types of genomic data, and modeling of immune cell populations. That research has led to important findings, including his work on the Deep Genetic Connection between Cancer and Developmental Disorders , published in Human Mutation.

Using innovative sequencing techniques from published studies of cancer and developmental disorders, Dr. Shen and his students identified a significant number of genes implicated in both diseases.

“This project allows us to use the larger cancer data to inform analysis in genetic variations of developmental disorders, and to find new risk genes and new risk variance,” he said. “It also provides a new perspective on how to optimize care for kids with developmental disorders. There is probably two to three times more risk of developing cancer for kids with developmental disorders than otherwise healthy kids.”

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Nicholas Tatonetti, PhD: Always Thinking Outside the Box

Nicholas Tatonetti, PhD
Nicholas Tatonetti, Phd

Nicholas Tatonetti , PhD, solves problems. He has always enjoyed it, and as the informatics community has discovered, he is both creative and proficient in his methods.

Dr. Tatonetti, who was recently awarded tenure and promoted to the rank of Associate Professor in the Columbia Department of Biomedical Informatics (DBMI) and Department of Systems Biology , focuses on the use of advanced data science methods, including artificial intelligence and machine learning, to investigate medicine safety. Using emerging resources, such as electronic health records (EHR) and genomics databases, his lab is working to identify for whom these drugs will be safe and effective and for whom they will not.

His path to Columbia wasn’t a traditional one, but that fits his work. Since joining in 2012, Dr. Tatonetti has used non-traditional thinking to benefit both health and healthcare.

Utilizing both data mining of medical records and prospective lab experiments, Dr. Tatonetti created a methodology for both finding and validating adverse drug reactions and drug-drug interactions. During a two-year collaboration with Pulitzer Prize-winning journalist Sam Roe of the Chicago Tribune , Dr. Tatonetti discovered that the drugs ceftriaxone and lansoprazole, when taken together, induces an arrhythmia in the heart.

The data mining identified adverse effects, while the lab experiments established causality. Dr. Tatonetti wasn’t specifically looking for a negative reaction of those particular drugs; he had no reason to suspect them.

“We are able to find things that nobody expects to happen because the world of hypotheses we consider is basically everything,” he said. “We consider every possible combination, a type of analysis that would be impossible without a huge data set and significant computational power.”

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Systems Biology and Women's Health: A Q+A with Tal Korem, PhD

As a member of Columbia University’s Program for Mathematical Genomics (PMG) , Tal Korem, PhD, is bringing his interests in systems biology, quantitative research, and the human microbiome to areas of clinical relevance. For Dr. Korem, that clinical focus is women’s reproductive health. 

“There is still a lot we don’t understand that relates to women’s health, to fertility, and to birth outcomes, and how microbes play a role in all of this,” says Dr. Korem, assistant professor of systems biology, with a joint appointment in obstetrics and gynecology at Columbia University Vagelos College of Physicians and Surgeons. A current focus of the Korem lab is preterm birth, i.e., birth that occurs prior to 37 weeks of gestation, though Dr. Korem intends to expand into other areas such as infertility and endometriosis. 

Tal Korem, PhD
Tal Korem, PhD

Dr. Korem’s interest in  women’s health research is personal, stemming from several impactful experiences that hit close to home. 

“My aunt passed away from ovarian cancer and I have seen friends and family members struggle with idiopathic infertility,” he says. “Also, witnessing the complications with the birth of my first child, which involved emergency procedures, motivated my interest in this area, and I am very excited about the potential to contribute to women’s health with my own research.” 

Dr. Korem, a native of Tel Aviv, Israel, is the first in his family to earn a PhD, and had entered academia as a medical student. After completing  his undergraduate degree, he enrolled in a MD/PhD graduate program. There, he realized that research was what he enjoyed the most. He is a trained computational biologist, and studied under Professor Eran Segal at the Weizmann Institute of Science, where his work focused on the  human microbiome, a complex system of microbial communities that inhabit every body part. 

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Grad Spotlight: Brian Ji, PhD

Brian Ji_2
Systems Biology Graduate Brian Ji, PhD

For Brian Ji, the big draw to systems biology stemmed from his passion for applying quantitative approaches to understanding biology. While an undergraduate at the University of Wisconsin-Madison, Ji studied nuclear engineering and credits that training for the way in which he tackles scientific questions: creatively, and as a problem solver. 

“There is no one right approach to asking a question and setting out to answer it, and that freedom is what makes science fun for me,” he says. 

Ji studied under Dr. Dennis Vitkup in the Vitkup lab and completed his thesis defense for systems biology in the fall of 2018.  Also an MD student in Columbia’s Vagelos College of Physicians and Surgeons , Ji was attracted to Columbia because of the close interplay between the Systems Biology Department and the Columbia University Irving Medical Center. “Ultimately,” he says, “the opportunity to sit at the intersection between math, biology and medicine was too good to pass up.”

Ji’s PhD work focused on understanding spatiotemporal dynamics of human gut microbiota. He developed several frameworks that leveraged the increasing availability of high-throughput sequencing data to better understand and precisely quantify patterns of human gut microbiota variability across time and space. His work showed that characterizing dynamics—changes in bacterial abundances in our gut—are critical to understanding how these ecosystems function and is highly connected to multiple factors such as host diet, travel and diet. 

Ji also spent part of his PhD studying limitations of cancer cell growth in different environmental conditions. He credits Columbia for exposing him to a variety of research topics. 

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Q+A with Dr. Laura Landweber

Oxytricha

Oxytricha. (Credit: Bob Hammersmith)

Laura Landweber, PhD, loves a challenge. So it’s no surprise that she has built a scientific career unraveling the hows and whys of a unique single-cell organism known for its biological complexity.  

An evolutionary biologist whose work sits at the interface of genetics and molecular biology, Dr. Landweber, for nearly 20 years, has focused much of her research on Oxytricha trifallax , a microbial organism that is prevalent in ponds, feeds on algae and has a highly complex genome architecture, making it an attractive, albeit challenging, model organism to study. Compared to humans, with 46 chromosomes containing some 25,000 genes, Oxytricha is known to comprise many thousands of chromosomes, in the ballpark of 16,000 tiny “nanochromosomes”. Yet not only is it complex in sheer numbers of chromosomes but the information carried in those individual chromosomes can be scrambled, like information compression, and the process of development in Oxytricha must descramble this information so that it can be converted into RNA and proteins.

“DNA can be flipped and inverted in Oxytricha and the cellular machinery actually knows how to restore order,” says Dr. Landweber. “Hence, it’s this wonderful paragon for understanding genome integrity and the maintenance and establishment of genome integrity.” 

Even more perplexing, in cell division, Oxytricha reproduces asexually when it wants to produce more in number, and it reproduces sexually when it needs to rebuild its genome. It also has the ability to “clean up” its genome, so to speak, eliminating nearly all of the non-coding DNA, or so-called junk DNA. Much of why Oxytricha presents such an intricate genomic landscape remains a mystery, and for Dr. Landweber, the leading expert on this single-celled protist, that wide-open field for potential discovery is what got her hooked. 

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At the Vanguard of a Revolution in Computational Genetics

Itsik Pe'erItsik Pe'er, an Associate Professor in the Department of Computer Science and member of the Columbia Initiative in Systems Biology, is using mathematics and computer analytics to identify the genetic makeup of the founding Ashkenazi Jews. By analyzing the full DNA sequences of hundreds of their descendants in the New York City area and comparing them to reference sets of non-Ashkenazi DNA, his goal is to identify Ashkenazi-specific genetic mutations associated with diseases such as Tay-Sachs, Crohn's, and Parkinson's disease. As a new article in Columbia News explains:

By examining similarities in DNA segments shared by large numbers of related individuals, his lab developed statistical models that allow him to make generalizations about entire populations. The mix of genes that every child inherits from each parent travels in long sequences of code that remain together and are remarkably consistent from one generation to the next.

"The size of the gene chunks gets smaller with each generation, but they diminish at a consistent and predictable rate. As a result, Pe’er can use his models to determine distant relationships shared by two individuals by measuring the length of their common DNA segments."

Read the complete article here.

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