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Raul Rabadan, PhD, Named Highly Cited Researcher

Raul Rabadan, PhD, professor of systems biology and of biomedical informatics, has been named a 2020 Highly Cited Researcher by Clarivate. Announced Nov. 18, Dr. Rabadan is one of 45 Columbia University faculty members who were selected for the annual list. 

The Highly Cited Researchers annual report recognizes researchers who have had major impacts in their fields. To be named to the list, researchers must produce multiple papers ranking in the top 1% globally by citations for their field and year of publication, demonstrating significant research influence among their peers.

Dr. Rabadan, founding director of Columbia's Program for Mathematical Genomics, also was named to the list in 2019, along with fellow Systems Biology faculty member, Xuebing Wu, PhD.

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Ancient Part of Immune System May Underpin Severe COVID

One of the immune system’s oldest branches, called complement, may be influencing the severity of COVID disease, according to a new study from Drs. Sagi Shapira and Nicholas Tatonetti at the Department of Systems Biology.

Drs. Sagi Shapira (right) and Nick Tatonetti
Drs. Nicholas Tatonetti (left) and Sagi Shapira

Among other findings linking complement to COVID, the researchers found that people with age-related macular degeneration—a disorder caused by overactive complement—are at greater risk of developing severe complications and dying from COVID.

The connection with complement suggests that existing drugs that inhibit the complement system could help treat patients with severe COVID-19.

The study was published in Nature Medicine . For the full article , visit the Columbia University Irving Medical Center Newsroom. 

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Dynamics of Gut Bacteria Follow Ecological Laws

The seemingly chaotic bacterial soup of the gut microbiome is more organized than it first appears and follows some of the same ecological laws that apply to birds, fish, tropical rainforests, and even complex economic and financial markets, according to a new paper in Nature Microbiology by researchers led by Dennis Vitkup , PhD, associate professor of systems biology , at Columbia Univesrity Irving Medical Center .

One of the main challenges facing researchers who study the gut microbiome is its sheer size and amazing organizational complexity. Many trillions of bacteria, representing thousands of different species, live in the human intestinal tract, interacting with each other and the environment in countless and constantly changing ways.

"Up to now, it has been an open question whether there are any natural laws describing dynamics of these complex bacterial communities.”-Dr. Vitkup

The study’s discovery of multiple principles of gut bacterial dynamics should help researchers to understand what makes a gut microbiome healthy, how it may become perturbed in disease and unhealthy diets, and also suggest ways we could alter microbiomes to improve health. Read the full article in the CUIMC Newsroom. 

The study is titled “Macroecological dynamics of gut microbiota.” The other contributors are Brian W. Ji (Columbia), Ravi U. Sheth (Columbia), Purushottam D. Dixit (Columbia and University of Florida, Gainesville, FL), and Konstantine Tchourine (Columbia).

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A Systems Biology Approach to Target Pancreatic Cancer

In recognition of Dr. Andrea Califano's recent Ruth Leff Siegel Award , an annual prize that honors and supports an investigator who has made outstanding contributions to our understanding of pancreatic cancer, Let's Win! Pancreatic Cancer has published the following feature article spotlighting his innovative approach to cancer research.

Dr. Andrea Califano
Dr. Andrea Califano, 2019 recipient of annual Ruth Leff Sigel Award for pancreatic cancer research. (Photo: Jörg Meyer/Columbia Magazine)

If you look at our basic biology, humans are big, cumbersome living organisms with a lot of moving parts.

For most of our lives, the cellular machinery that keeps us functioning goes off without a hitch. Starting at conception, cells have been growing and dividing, structuring themselves in a highly organized fashion. Liver cells know their job. And brain and spinal cord cells know their jobs, too.

Cancer is also a living organism. After all, it grows and evolves just like healthy cells. But cancer cells are cheats, ignoring the rules that other healthy cells play by. They mutate and divide uncontrollably, finding ways to evade our immune systems, which try to keep these invaders in check. To complicate matters, cancer cells are what scientists call heterogeneous. That means that even in the same malignant tumor there can be a variety of mutations, which is one reason why cancer treatment often fails. Drugs simply can’t target all of those mutations.

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Book Offers Intro to Rapidly Growing Field of Topological Data Analysis

New Book Coauthored by Raul Rabadan, PhD
Dr. Raul Rabadan coauthors new book that introduces techniques of topological data analysis, a rapidly growing subfield of mathematics. (Cambridge University Press)

The deluge of data in the diverse field of biology comes with it the challenge of extracting meaningful information from large biological data sets. A new book, Topological Data Analysis for Genomics and Evolution, introduces central ideas and techniques of topological data analysis and aims to explain in detail a number of specific applications to biology.

“High-throughput genomics has profoundly transformed the field of modern biology and has made it possible for scientists to make rapid scientific advances,” says the book’s co-author Dr. Raul Rabadan, professor of systems biology and founding director of Columbia University’s Program for Mathematical Genomics. “The explosion of data has hit biology, and as a result, we need new, more innovative analytical and computational tools to make sense of it all.”

Co-authored with Andrew J. Blumberg, PhD, professor of mathematics at University of Texas at Austin, the new book discusses techniques of topological data analysis, a rapidly developing subfield of mathematics that provides a methodology for analyzing the shape of data sets. The book offers several examples of these techniques and their use in multiple areas of biology, including the evolution of viruses, bacteria and humans, genomics of cancer, and single cell characterization of developmental processes.

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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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Highly Cited Researchers

Raul Rabadan Highly Cited
Raul Rabadan, PhD, (standing) with Francesco Brundu, postdoctoral research scientist in the Rabadan lab (Credit: Jeffrey Schifman)

Congratulations to Drs. Raul Rabadan and Xuebing Wu who were recently named a Highly Cited Researcher, according to the 2019 list from the Web of Science Group . Overall, Columbia University ranked 15th on the list of global institutions, with a total of 47 Highly Cited Researchers.

The Highly Cited Researchers list, which was released Nov. 19,  identifies scientists and social scientists who have produced multiple papers ranking in the top 1% by citations for their field and year of publication, demonstrating significant research influence among their peers.

Xuebing Wu, PhD
Xuebing Wu, PhD

Dr. Rabadan is professor of systems biology , with a joint appointment in biomedical informatics, at Columbia’s Vagelos College of Physicians and Surgeons . At Columbia, the Rabadan lab consists of an interdisciplinary team developing mathematical and computational tools to extract useful biological information from large data sets. In 2017, Dr. Rabadan established the Program for Mathematical Genomics , a multidisciplinary research hub that brings together researchers from the fields of mathematics, physics, computer science, engineering, and medicine, with the common goal of solving pressing biomedical problems through quantitative methods and analyses. He also serves as program lead for the Cancer Genomics and Epigenomics Program at the Herbert Irving Comprehensive Cancer Center at NYP/Columbia. 

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Examining Genetic Risk Factors in Severe Birth Defect

Congenital diaphragmatic hernia (CDH) is a severe birth defect. For babies born with CDH, their diaphragms are not developed properly, with some or all parts of the abdominal organs pushed into the chest. The displacement of these critical organs can have a significant impact on how the lungs develop and grow. 

Dr. Yufeng Shen
Yufeng Shen, PhD, associate professor of systems biology

A recent study , led by Yufeng Shen , PhD, and Wendy Chung , MD, PhD, and their labs at Columbia University Irving Medical Center , investigated the genetic risk factors linked to CDH and analyzed data from whole genome sequencing and exome sequencing to determine novel mutations. The study also uncovered the link between CDH and additional developmental disorders. 

“Many babies with this birth defect also have lung hypoplasia or pulmonary hypertension and babies have difficulty breathing. Even with advanced care available, the mortality rate is still about 20 percent,” says Dr. Shen, associate professor of systems biology at Columbia, with a joint appointment in the Department of Biomedical Informatics . 

“One hypothesis is that the lung condition is not necessarily caused by the physical compression on the developing lungs in the chest,” explains Dr. Shen, “it can be caused by the same genetic defect that causes CDH. Finding those genes is absolutely necessary to improve care and develop effective treatment in the long run.”   

Scientists have been aiming to identify new risk genes in CDH—and other developmental disorders—with  the hope that with improved genetic diagnosis more tailored or long-term care for patients born with this defect could be provided, as well as potential targets for intervention down the road. 

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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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New Method Detects Genetic Expression Disruptors, Improves Diagnosis of Rare Disease

Dr. Tuuli Lappalainen Science Study

The illustration above depicts with an example of four genes, how knowing how variable genes are in the normal population helps to find candidate disease genes in a patient. Above, top: Tuuli Lappalainen, PhD; bottom: Pejman Mohammadi, PhD.

For individuals with rare diseases, getting a diagnosis is often a long and complicated odyssey. Over the past few years, this has been greatly improved by genome sequencing that can pinpoint the mutation that breaks a gene and leads to a severe disease. However, this approach is still unsuccessful in the majority of patients, largely because of our inability to read the genome to identify all mutations that disrupt gene function.

In a new study published on October 10 in Science , researchers from New York Genome Center , Columbia University , and Scripps Research Institute propose a solution to this problem. Building a new computational method for analyzing genomes together with transcriptome data from RNA-sequencing, they can now identify genes where genetic variants disrupt gene expression in patients and improve the diagnosis of rare genetic disease.

The new method introduced in this study, Analysis of Expression Variation or ANEVA, first takes allele-specific expression data from a large reference sample of healthy individuals to understand how much genetic regulatory variation each gene harbors in the normal population. Then, using the ANEVA Dosage Outlier Test, researchers can analyze the transcriptome of any individual – such as a patient – to find a handful of genes where he or she carries a genetic variant with an unusually large effect compared to what healthy individuals have. By applying this test to a cohort of muscle dystrophy and myopathy patients, the researchers demonstrated  the performance of their method and diagnosed additional patients where previous methods of genome and RNA analysis had failed to find the broken genes.

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Biological ‘Rosetta Stone’ Brings Scientists Closer to Deciphering How the Body is Built

Time lapse of a developing drosophila embryo. (Credit: Carlos Sanchez-Higueras/Hombría lab/CABD)

Every animal, from an ant to a human, contains in their genome pieces of DNA called Hox genes. Architects of the body, these genes are keepers of the body’s blueprints; they dictate how embryos grow into adults, including where a developing animal puts its head, legs and other body parts. Scientists have long searched for ways to decipher how Hox genes create this body map; a key to decoding how we build our bodies.

Now an international group of researchers from Columbia University and the Spanish National Research Council (CSIC) based at the Universidad Pablo de Olavide in Seville, Spain have found one such key: a method that can systematically identify the role each Hox gene plays in a developing fruit fly. Their results, reported recently in Nature Communications , offer a new path forward for researchers hoping to make sense of a process that is equal parts chaotic and precise, and that is critical to understanding not only growth and development but also aging and disease.

“The genome, which contains thousands of genes and millions of letters of DNA, is the most complicated code ever written,” said study co-senior author Richard Mann , PhD, principal investigator at Columbia’s Mortimer B. Zuckerman Mind Brain Behavior Institute and a faculty member in the Department of Systems Biology . “Deciphering this code has proven so difficult because evolution wrote it in fits and starts over hundreds of millions of years. Today’s study offers a key to cracking that code, bringing us closer than ever to understanding how Hox genes build a healthy body, or how this process gets disrupted in disease.”

Read the full article at the Zuckerman Institute. 

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Detailed Map Gives Scientists a New Window into how Human-Infecting Viruses Work

Sagi Shaipra PHIPSTer Cell Paper
Researchers implement P-HIPSTer, an in silico computational framework that leverages protein structure information to identify approximately 282,000 protein-protein interactions across all fully-sequenced human-infecting viruses (1001 in all). This image highlights that in addition to rediscovering known biology, P-HIPSTer has yielded a series of new findings and enables discovery of a previously unappreciated universe of cellular circuits and biological principles that act on human-infecting viruses. (Image Courtesy of Dr. Sagi Shapira)

Researchers at Columbia University Irving Medical Center have leveraged a computational method to map protein-protein interactions between all known human-infecting viruses and the cells they infect. The method, along with the data that it generated, has spawned a wealth of information toward improving our understanding of how viruses manipulate the cells that they infect and cause disease. Among its findings, the work uncovered a role for estrogen receptor in regulating Zika Virus (ZIKV) infection, as well as links between cancer and the human papillomavirus (HPV).

The research, led by Sagi Shapira , PhD, Assistant Professor in the Department of Systems Biology and the Department of Microbiology & Immunology at Columbia University Vagelos College of Physicians and Surgeons , appears today in the journal, Cell . Dr. Shapira’s collaborators include Professors Barry Honig , PhD, of Systems Biology and of Biochemistry and Molecular Biophysics and Raul Rabadan , PhD, of Systems Biology and of Biomedical Informatics. 

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Designer Proteins Come with Built-In Safeguards

Protein engineering is a relatively young field that creates new proteins never seen before in nature. Today’s protein engineers usually create synthetic proteins by making small changes to the gene that encodes a naturally occurring protein. The variety of synthetic proteins range from stain-removing enzymes that have improved detergents to a long-acting insulin that’s used by millions of people with diabetes.

But two big unsolved challenges for protein engineers remain: The gene encoding the synthetic protein needs to be contained to prevent escape into other organisms and the gene needs to resist mutating over time so the protein doesn’t lose its function.

By merging two genes into a single DNA sequence, Columbia University synthetic biologists have created a method that could prevent human-engineered proteins from spreading into the wild, as well as stabilize synthetic proteins so they don’t change over time. The work, recently published in Science, was developed by Harris Wang, PhD, assistant professor of systems biology, with graduate student, Tomasz Blazejewski and postdoctoral scientist, Hsing-I Ho, PhD. 

In devising the method, the researchers were inspired by overlapping genes in viruses. When two different genes overlap, they occupy the same sequence of DNA. But the genes are read in different frames so that two different proteins are produced.

In overlapping genes, a random mutation in the sequence may not affect one gene, but it’s likely that it will harm the second gene.

“Overlapping genes essentially lock in a specific DNA sequence, and we thought we could exploit this idea for synthetic biology ...Ten years ago, we didn’t have the technology that would make this possible,” says Dr. Wang. “We didn’t have enough sequences in the database to make informed predictions and we didn’t have a way to synthesize long DNA sequences for testing our predictions.”

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Sampling Neighborhoods of the Gut Microbiome

The gut microbiome–composed of hundreds of different species of bacteria–is a complex community and a challenge for scientists to unravel. One specific challenge is the spatial distribution of different microbes, which are not evenly distributed throughout the gut. A new method developed by the lab of Dr. Harris Wang should help scientists locate and characterize these neighborhoods, which could shed light on how microbes influence the health of their hosts.

Techniques that can identify all species in the gut microbiome only work with homogenized samples (like stool), but methods that preserve spatial information can only cope with a handful of species.

Dr. Wang, assistant professor of systems biology and of pathology & cell biology, and graduate student Ravi Sheth in the Department of Systems Biology, tested the new technique with mice who switched from a low-fat to a high-fat diet. Diet is known to change the abundance of specific bacteria in the gut within days, but the new technique also revealed that the switch caused wholesale changes of microbial neighborhoods.

“Specific regions of bacteria were entirely lost with a switch in diet,” Sheth says. “This was exciting to us as it will give us clues to understanding how that change happens and how the change may impact health.”

Read the full article in the CUIMC Newsroom. 

The research, titled “Spatial metagenomic characterization of microbial biogeography in the gut,” was published July 22 in Nature Biotechnology.

 

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Making Strides in Mapping the Human Cell Atlas

Columbia investigators win Chan Zuckerberg Initiative grants to accelerate development of cellular roadmap of the human body.

In two groundbreaking research projects contributing to the Human Cell Atlas, Columbia University scientists are tasked with mapping complete cells in the immune system and the human spine. The global effort is aiming to identify and define every cell type of the human body and create a collection of maps for navigating the cellular basis of human health and disease.

Peter Sims, PhD
Peter Sims, PhD, assistant professor of systems biology

The Columbia teams, which include co-principal investigators from the Department of Systems Biology Drs. Peter Sims and Raul Rabadan , are among the 38 collaborative science teams launching the Chan Zuckerberg Initiative’s (CZI) Seed Networks for the Human Cell Atlas project announced today. The three-year projects, receiving a total of $68 million in award funding by Seed Networks, are collaborative groups that are bringing together expertise in science, computational biology, software engineering, and medicine to support the ongoing progress of the Human Cell Atlas .

Investigating the Immune System + Aging

Dr. Sims, part of an international team including close collaborator Dr. Donna Farber of the Department of Surgery , is combining single-cell sequencing technologies, data analysis, and immunology expertise to better understand how the immune system ages and gain new insights into how human diseases occur. 

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Novel Computational Tool Models RNA-Binding Specificity, Provides Better Understanding of Gene Expression Regulation

Chaolin Zhang
Chaolin Zhang, PhD, associate professor of systems biology

A new study by researchers in Dr. Chaolin Zhang’s lab at Columbia’s Department of Systems Biology details a novel computational method that models how RNA-binding proteins (RBPs) recognize specific sites in the target RNA transcripts, precisely and accurately. The researchers’ findings include identification of entirely new motifs (RNA sequence patterns), and their research in complex RNA regulation contributes to our understanding of the molecular basis of disease and conditions, and down the road, could aid in the development of targeted therapies. 

The study, led by Dr. Zhang, associate professor of systems biology, with senior co-authors Suying Bao, PhD, and Huijuan Feng, PhD, appears today in Molecular Cell. 

RNA has traditionally been considered mere “messengers” that transfer genetic information from DNA to proteins that ultimately carry out cellular functions. However, it is now increasingly appreciated that RNA can be tightly regulated to control gene expression and diversity protein products. RNA-binding proteins (RBPs) are at the center of such regulation, with important roles in many cellular processes, including cell function, transport, and location. Gaining mechanistic insights of the binding specificity of RBPs in a genome-wide scale helps advance our knowledge of gene regulation.

“RNA-binding proteins are crucial for gene expression,” says Dr. Feng, coauthor of the study and post-doctoral research scientist in the Zhang lab. “RNA is heavily regulated, and when this regulation goes wrong, instabilities or disease could occur.”  

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Behind the Technique: Systems Biology with Andrea Califano

Dr. Andrea Califano sits down with BioTechniques at AACR. Video: Courtesy of BioTechniques.

At the 2019 annual meeting of the American Association for Cancer Research (AACR), Dr. Andrea Califano sat down with BioTechniques News for an overview on the field of systems biology and its impact in cancer research and in precision medicine. Dr. Califano is a pioneering researcher in the fast-growing field of systems biology whose expertise is in developing innovative, systematic approaches to identify the molecular factors that lead to cancer progression and to the emergence of drug resistance at the single-cell level. A physicist by training, Dr. Califano is the Clyde and Helen Wu Professor of Chemical and Systems Biology, founding chair of the Department of Systems Biology at Columbia University Irving Medical Center, director of the Columbia Genome Center and a program leader at the Herbert Irving Comprehensive Cancer Center.

The video interview is part of the series, Behind the Technqiue by BioTechniques News. 

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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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Columbia Highlights MD/PhD Student Research

Phyllis Thangaraj
Phyllis Thangaraj, MD/PhD student (Tatonetti lab)

Aspiring physician-scientists from Columbia's Vagelos College of Physicians and Surgeons presented their research posters at the 14th annual MD-PhD Student Research Symposium on April 25. Their research delved into a range of topics, including Alzheimer’s disease, stroke, and stem cells. The event included a guest lecture by an alumna about her own career path as a physician-scientist, and culminated in the poster session judged by MD-PhD alumni who currently work at the University. Department of Systems Biology’s Phyllis Thangaraj, an MD/PhD student in the Nicholas Tatonetti lab , was named one of five poster winners at the event. 

She presented work on applying machine learning methods to phenotype acute ischemic stroke patients in the electronic health records. In cohort research studies, it is essential to identify a large number of subjects in an accurate and efficient manner, but often this requires time-consuming manual review of patient charts. 

“We applied machine learning methods to data within a patient’s electronic health records to develop a high-throughput way to define research cohorts,” explains Thangaraj. “Our test case is in acute ischemic stroke. We extracted clues within a person’s medical record that required minimal data processing to classify those who have had a stroke. In a separate cohort, the UK Biobank, we were able to use our model to identify patients with self-reported stroke but no mention in their medical data with 65-fold better precision than random selection of patients.” Although stroke was the test case in this particular work, she explained that their workflow could be applied to identify patients for cohorts of other diseases, particularly when the dataset has missing data. 

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Same Microbe, Different Effect

The Korem Lab

One of the structural variations detected in Anaerostipes hadrus, which is deleted in ~40% of the population (top), and associated with higher disease risk. Genes in this region (bottom) code a composite inositol catabolism - butyrate production pathway, potentially supplying the microbe with additional energy while supplying the host with butyrate, previously shown to have positive metabolic and anti-inflammatory effects. (Credit: Korem lab)

Our gut microbiome has been linked to everything from obesity and diabetes to heart disease and even neurological disorders and cancer. In recent years, researchers have been sorting through the multiple bacterial species that populate the microbiome, asking which of them can be implicated in specific disorders. But a paper recently published in Nature addressed a new question: "What if the same microbe is different in different people?" The study was co-led by Dr. Tal Korem , assistant professor of systems biology and core faculty member in the Program for Mathematical Genomics at Columbia University Irving Medical Center . 

It has been long known that the genomes of microbes are not fixed from birth, as ours are. They are able to lose some of their genes, exchange genes with other microorganisms, or gain new ones from their environment. Thus, a detailed comparison of the genomes of seemingly identical bacteria will reveal sequences of DNA that occur in one genome and not others, or possibly sequences that appear just once in one and several times over in others. These differences are called structural variants. Structural variants - even tiny ones - can translate into huge differences in the ways that microbes interact with their human hosts. A variant might be the difference between a benign presence and a pathogenic one, or it could give bacteria resistance to antibiotics.

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