Historically speaking, women have been underrepresented in professions heavy in science technology, engineering, and mathematics (the STEM fields). You wouldn’t know it to look at the 2017 class of Petit Undergraduate Research Scholars.
This year’s class – tied for the largest number of students, 22, with last year’s class – features 16 women, a record number in the program’s 18-year history.
Since it was established as a summer research experience in 2000, the program has supported hundreds of top undergraduate researchers who have moved on to successful careers in research, medicine, and industry. But it has never supported this many women at one time. That first year, six of the seven scholars were men.
Oh, how times have changed.
“It’s empowering to be surrounded by motivated women who aren’t going to stop moving forward in STEM just because the field has been traditionally male dominated,” says Madeline Smerchansky, a third-year student in the Wallace H. Coulter Department of Biomedical Engineering, who has been doing undergraduate research for about a year.
“But I’m excited about the Petit Scholars program because of how independent it will allow me to be in the lab,” she adds. “I think it will help me solidify my post-graduation plans while providing valuable experience and networking in the research world.”
The Petit Scholars program, open to all Atlanta area university students, basically gives scholars room to breathe intellectually. What makes the program unique is that it provides for a full year of research in state-of-the-art labs of the Parker H. Petit Institute for Bioengineering and Bioscience.
“The scholars will work alongside graduate students or postdoctoral mentors in labs across the spectrum of bioengineering and bioscience,” explains Raquel Lieberman, the Petit Institute researcher who serves as faculty mentor for the program.
“The sustained research effort over the course of a year will enable the Petit Scholars to contribute to a research project in a substantive way,” adds Lieberman, an associate professor in the School of Chemistry and Biochemistry.
This year’s group of students come from three different universities (while most come from Georgia Tech, two students are from Morehouse and one is from Agnes Scott).
They represent nine different majors, reflecting the multi-disciplinary approach the Petit Institute takes toward research. The largest group (six students) is majoring in biomedical engineering (BME) in the Coulter Department.
“I’ve been interested in becoming a biomedical engineer since I was a sophomore in high school and my math teacher brought in real data from a hospital for us to work on,” says Isabelle Stasenko, one of the BME undergrads. “I loved the idea of doing the math and research behind the medicine, and I still do.”
Stasenko figures the the program will help confirm if a career in research is the right path for her. In the meantime, the Petit Scholar experience is a source of empowerment for her.
“It’s exciting to have so many powerful women pursuing and excelling in engineering fields,” she says. “Georgia Tech was originally an all-boys institution, so to see the number of women growing like this is amazing.”
Another BME undergrad, Rebecca Keate, says she knows a rare opportunity when she sees one: "As a second-year undergraduate, I recognize that a lot of students are not granted the same opportunities as I am, to have such a sophisticated research experience at a powerhouse like Georgia Tech."
But she admits to being tired of hearing that she, as a woman, is, “prone to be less successful in any STEM program. I disagree with this opinion. I refuse to believe that my intelligence is any less than a man’s. And as an engineer, I hope to be held to the highest standards, regardless of being a woman.”
Here they are, the 2017 Petit Scholars (plus, their school, their mentor, and the Petit Institute researcher’s lab they’ll be spending the year in):
• Ashley Alexander (Georgia Tech, Dong-Dong Yang, Frank Rosenzweig)
• Cedric Bowe (Morehouse, Vineet Tiruvadi, Rob Butera)
• Mi Hyun Choi (Georgia Tech, Joshua Lee, Frank Hammond)
• Hassan Fakhoury (Georgia Tech, Quoc Mac, Gabe Kwong)
• Sarah Ghalayini (Georgia Tech, Moustafa Ali, Mostafa El-Sayed)
• Daniel Gurevich (Georgia Tech, Ilija Uzelac, Flavio Fenton)
• Connor Huddleston (Georgia Tech, Zhenglun “Alan” Wei, Ajit Yoganathan)
• Rebecca Keate (Georgia Tech, Shlomi Cohen, Jennifer Curtis)
• Siyi “Sophie” Li (Georgia Tech, Aline Yonesawa, Mike Davis)
• Amelia Matthews (Georgia Tech, Sam Tonddast-Navaei, Jeff Skolnick)
• Esperance Mugabekazi (Agnes Scott, Sang-Eon Park, Robert Gross)
• Michelle Myrick (Georgia Tech, Inseung Kang, Aaron Young)
• Franck Nijimbere (Morehouse, Bo Broadwater, Harold Kim)
• Chiagoziem “Chichi” Obi (Georgia Tech, Udita Brahmachari, Bridgette Barry)
• Renee Puvvada (Georgia Tech, Katily Ramirez/Michael Bellavia*, Todd Sulchek)
• Celeste Runnels (Georgia Tech, Nicholas Kovacs, Loren Williams)
• Arushi Saini (Georgia Tech, Osiris Martinez-Guzman, Amit Reddi)
• Amanda Schaefer (Georgia Tech, Emily Jackson, Hang Lu)
• Madeline Smerchansky (Georgia Tech, Kirsten Parratt, Krishnendu Roy)
• Isabelle Stasenko (Georgia Tech, Efraín Cermeno, Andrés García)
• Moya Tomlin (Georgia Tech, Dustin Huard, Raquel Lieberman)
• Corey Zheng (Georgia Tech, Seung Yup “Paul” Lee, Erin Buckley)
Communications Officer II
Parker H. Petit Institute for
Bioengineering and Bioscience
When Alfred H. Merrill launched his career as an assistant professor at Emory University in 1981, he wanted to carve out his own unique niche, to do something that would distinguish himself while contributing to the growing body of research in biochemistry and molecular biology. So, he jumped into an enigma.
Merrill, a professor in the School of Biology in the College of Sciences and Smithgall Institute Chair of Molecular Cell Biology at the Georgia Institute of Technology, became a pioneering researcher in the field of sphingolipids (named “sphingo,” for “sphinx,” because sphingolipids are considered as enigmatic as the Great Sphinx).
Now, 30 years later, his early work is being recognized as some of the most influential research of its kind – classic stuff, literally.
“Right off the bat, my lab had the good luck to find that the textbook pathway for biosynthesis of sphingolipids was wrong,” says Merrill.
Niche carved, first contribution made.
Then came the bigger surprise: that sphingolipids are involved in cell signaling. This came through an exciting collaboration that resulted in publication of three back-to-back papers in 1986 that have just been designated as “Classics” by The Journal of Biological Chemistry (JBC). The Classics are selected from articles that have previously appeared in the JBC (since its founding in 1905), and considered particularly impactful. They’re reprinted in their original form, along with an explanation of the research’s groundbreaking contribution to science.
“The JBC is considered one of the most prestigious journals in basic biochemistry, so for one’s work to be selected as a ‘Classic’ is a real honor,” says Merrill, a researcher in the Petit Institute for Bioengineering and Bioscience, who finds himself in some elite company, as the Classics series includes papers by many of the all-time legends in biological chemistry.
“In some cases, such as ours,” he adds, “the specifics of the papers are probably not as important as that they turned people’s minds around and got them to look at a field from a different angle.” The JBC Classics entry calls out the research’s impact right there in the headline: “Solving the Riddle of the Role of Sphingolipids in Cell Signaling.”
Merrill likes to emphasize that these findings were the synthesis of ideas and expertise from many scientists, not just one investigator. It started with his former post-doctoral mentor, Robert M. Bell at Duke University.
“In Dr. Bell’s lab, the major focus was glycerolipid metabolism, but he had become intrigued that diacylglycerols were being claimed to be signaling molecules that activate protein kinase C (PKC),” Merrill says. “Skeptical of the idea at first, Yusuf Hannun and others in his lab developed sophisticated ways to study PKC and they not only became leading experts in how lipids activate this kinase but also happened to notice that a sphingolipid, sphingosine, could inhibit it.”
This was the underpinning of the first of the three papers, entitled, “Sphingosine inhibition of protein kinase C activity and of phorbol dibutyrate binding in vitro and in human platelets.”
“Since these were compounds that my lab had been studying, we became heavily involved,” says Merrill, whose only other co-author for all three papers was Bell. Hannun co-authored two of the papers.
“But as the project became even more sophisticated, additional collaborators were needed,” Merrill adds.
Two were other faculty at Emory, Dr. Jack Kinkade for the paper entitled, “Inhibition of phorbol ester-dependent differentiation of human promyelocytic leukemic (HL-60) cells by sphinganine and other long-chain bases,” and Dr. J. David Lambeth for the third paper, “Inhibition of the oxidative burst in human neutrophils by sphingoid long-chain bases. Role of protein kinase C in activation of the burst.”
According to George Carman, director of Rutgers University’s Center for Lipid Research (and the JBC associate editor who nominated the trilogy for Classic status), the papers “showed that a lipid backbone of sphingolipids could affect a cell signaling pathway (Protein Kinase C) at not only by inhibiting the in vitro activity but also by affecting diverse cell functions dependent on protein kinase C (platelet activation, the neutrophil respiratory burst and cell differentiation). This work started a whole sub discipline of lipid signaling that affects cell physiology.”
Before these papers, according to Merrill, there was no clear understanding of why sphingolipids were built upon the sphingosine backbone, which differs from all other lipid categories. The research demonstrated that sphingosine is a highly bioactive molecule capable of altering cell signaling and a wide spectrum of cell functions.
"Once the papers stimulated scientists to think about sphingolipids from that perspective, additional bioactive metabolites were discovered and characterized, resulting in a now very large field of cellular regulation by sphingolipid mediators,” Merrill says. “This, in turn, led to discoveries about how defects in these pathways result in disease and new strategies to prevent and treat disease.”
Almost everything that Merrill’s lab has subsequently discovered has been built on this new perspective on sphingolipids, and involved some sort of collaboration: The connection of sphingolipids with diseases caused by the fumonisin mycotoxins, in collaboration with Ron Riley at the USDA; that dietary sphingolipids suppress colon cancer with Dirck Dillehay, and development of drug leads based on sphingolipids with Dennis Liotta (both at Emory); development of mass spectrometric methods to quantify all of the known bioactive sphingolipids and discover new ones, with Cameron Sullards, director of the Georgia Tech Department of Chemistry and Biochemistry Mass Spectrometry Center; characterization of the mammalian genes and enzymes that make ceramides, with Tony Futerman at the Weizmann Institute; changes in sphingolipid metabolism in ovarian cancer, with John McDonald (Petit Institute); and so on.
With the assistance of research technician Samuel Kelly, Merrill has returned to working fulltime in the lab, to develop new ways to study sphingolipid structure and function. Thinking back over his career, Merrill is proudest of the approach his lab and collaborators have taken in their research, rather than any one specific finding.
“We have expended a lot of effort to develop better methods to analyze sphingolipids and model systems to study them more definitively,” he says. “This has often been slow and sometimes tedious, but it has resulted in solid data that have stood the test of time, and in many unexpected discoveries.”
Communications Officer II
Parker H. Petit Institute for
Bioengineering and Bioscience
Four faculty in the College of Sciences, one in the Scheller College of Business, and one in the Ivan Allen College of Liberal Arts have been named fellows of the American Association for the Advancement of Science for 2015. Fellows are elected by their peers in recognition of distinguished contributions to science or its application.
Those recognized include:
- School of Biology Professor Yury Chernoff: For distinguished contributions to the field of molecular/cellular biology, particularly for understanding prion formation and deciphering the chaperone role in prion propagation in yeast.
- School of Chemistry and Biochemistry Professor Christoph J. Fahrni: For distinguished contributions on the development of metal ion sensors and for discoveries on the mechanisms for metal transport and storage during growth and development.
- School of Earth and Atmospheric Sciences Professor Jean Lynch-Stieglitz: For bringing physical oceanography approaches to the study of transient circulation changes during ice ages, providing a window into the ocean’s interaction with today’s climate change.
- School of Public Policy Professor Philip Shapira: For distinguished contributions to science, technology and innovation policy, particularly for contributions to improved understanding of effective means of modernizing manufacturing.
- Scheller College of Business Regents Professor Marie Thursby: For research contributions to the role universities play in innovation and the development of pioneering graduate programs that prepare students for careers commercializing new technologies.
- School of Chemistry and Biochemistry Professor Emeritus Paul H. Wine: For distinguished contributions to the fields of physical and atmospheric chemistry, particularly for experimental studies of the kinetics and mechanisms of fast free radical reactions.
A formal ceremony to induct new fellows will be held during the AAAS Annual Meeting in February.
Viruses infect more than humans or plants. For microorganisms in the oceans – including those that capture half of the carbon taken out of the atmosphere every day – viruses are a major threat. But a paper published January 25 in the journal Nature Microbiology shows that there’s much less certainty about the size of these viral populations than scientists had long believed.
Collecting and re-examining more than 5,600 estimates of ocean microbial cell and virus populations recorded over the past 25 years, researchers have found that viral populations vary dramatically from location to location, and at differing depths in the sea. The study highlights another source of uncertainty governing climate models and other biogeochemical measures.
“What was surprising was that there was not a constant relationship, as people had assumed, between the number of microbial cells and the number of viruses,” said Joshua Weitz, an associate professor in the School of Biology at the Georgia Institute of Technology and one of the paper’s two senior co-authors. “Because viruses are parasites, it was assumed that their number would vary linearly with the number of microbes. We found that the ratio does not remain constant, but decreases systematically as the number of microbes increases.”
The research, which involved authors from 14 different institutions, was initiated as part of a working group from the National Institute for Mathematical and Biological Synthesis (NIMBioS), which is supported by the National Science Foundation. The research was completed with additional support from the Burroughs Wellcome Fund and the Simons Foundation. The research was co-led by Steven Wilhelm, a professor of microbiology at the University of Tennessee, Knoxville.
In the datasets examined by the researchers, the ratio of viruses to microbes varied from approximately 1 to 1 and 150 to 1 in surface waters, and from 5 to 1 and 75 to 1 in the deeper ocean. For years, scientists had utilized a baseline ratio of 10 to 1 – ten times more viruses than microbes – which may not adequately represent conditions in many marine ecosystems.
“A marine environment with 100-fold more viruses than microbes may have very different rates of microbial recycling than an environment with far fewer viruses,” said Weitz. “Our study begins to challenge the notion of a uniform ecosystem role for viruses.”
A key target for viruses are cyanobacteria – marine microorganisms that obtain their energy through photosynthesis in a process that takes carbon out of the atmosphere. What happens to the carbon these tiny organisms remove may be determined by whether they are eaten by larger grazing creatures – or die from viral infections.
When these cyanobacteria die from infections, their carbon is likely to remain in the top of the water column, where it can nourish other microorganisms. If they are eaten by larger creatures, their carbon is likely to sink into the deeper ocean as the grazers die or excrete the carbon in in their feces.
“Viruses have a role in shunting some of the carbon away from the deep ocean and keeping it in the surface ocean,” said Wilhelm. “Quantifying the strength of the viral shunt remains a vital issue.”
Influenza and measles come to mind when most people think of viruses, but the bulk of world’s viruses actually infect microorganisms. Estimates suggest that a single liter of seawater typically contain more than ten billion viruses.
To better understand this population, the researchers conducted a meta-analysis of the microbial and virus abundance data that had been collected over multiple decades, including datasets collected by many of the co-authors whose laboratories are based in the United States, Canada and Europe. The data had been obtained using a variety of techniques, including epifluorescence microscopy and flow cytometry.
By combining data collected by 11 different research groups, the researchers created a big picture from many smaller ones. The statistical relationships between viruses and microbial cells, analyzed by first-author Charles Wigington from Georgia Tech and second-author Derek Sonderegger from Northern Arizona University, show the range of variation.
The available data provides information about the abundance of viral particles, not their diversity. Viruses are selective in the microbes they target, meaning the true rates of infection require a renewed focus on virus-microbe infection networks.
“Future research should focus on examining the relationship between ocean microorganisms and viruses at the scale of relevant interactions,” said Weitz, “More ocean surveys are needed to fill in the many blanks for this critical part of the carbon cycle. Indeed, virus infections of microbes could change the flux of carbon and nutrients on a global scale.”
This work was supported by National Science Foundation (NSF) grants OCE-1233760 and OCE-1061352, a Career Award at the Scientific Interface from the Burroughs Wellcome Fund and a Simons Foundation SCOPE grant. This work arose from discussions in the Ocean Viral Dynamics working group at the National Institute for Mathematical and Biological Synthesis, an Institute sponsored by the National Science Foundation through NSF Award DBI-1300426, with additional support from The University of Tennessee, Knoxville. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Science Foundation.
CITATION: Charles H. Wigington, et al., “Re-examination of the relationship between marine virus and microbial cell abundances,” (Nature Microbiology, 2016). http://dx.doi.org/10.1038/nmicrobiol.2015.24
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Dr. Brendan Hunt, a postdoctoral researcher in the labs of Drs. Michael Goodisman and Soojin Yi, has been selected as the recipient of the 2012 VWR Postdoctoral Award for Scientific Excellence. Supported by a generous gift from VWR, this award is given annually to a postdoc who has made a significant research contribution in the field of experimental biology.
Dr. Hunt (Ph.D., 2011, Georgia Tech) studies the evolutionary genomics of insects and has published his research in several leading journals, including the Proceedings of the National Academy of Sciences USA. As the recipient of this award, Dr. Hunt will present his research to the Georgia Tech community in an upcoming seminar (March 29th). A reception will follow the presentation. Congratulations to Dr. Hunt!
Studying blood serum compounds of different molecular weights has led scientists to a set of biomarkers that may enable development of a highly accurate screening test for early-stage ovarian cancer.
Using advanced liquid chromatography and mass spectrometry techniques coupled with machine learning computer algorithms, researchers have identified 16 metabolite compounds that provided unprecedented accuracy in distinguishing 46 women with early-stage ovarian cancer from a control group of 49 women who did not have the disease. Blood samples for the study were collected from a broad geographic area – Canada, Philadelphia and Atlanta.
While the set of biomarkers reported in this study are the most accurate reported thus far for early-stage ovarian cancer, more extensive testing across a larger population will be needed to determine if the high diagnostic accuracy will be maintained across a larger group of women representing a diversity of ethnic and racial groups.
The research was reported November 17 in the journal Scientific Reports, an open access journal from the publishers of Nature.
“This work provides a proof of concept that using an integrated approach combining analytical chemistry and learning algorithms may be a way to identify optimal diagnostic features,” said John McDonald, a professor in the School of Biology at the Georgia Institute of Technology and director of its Integrated Cancer Research Center. “We think our results show great promise and we plan to further validate our findings across much larger samples.”
Ovarian cancer has been difficult to treat because it typically is not diagnosed until after it has metastasized to other areas of the body. Researchers have been seeking a routine screening test that could diagnose the disease in stage one or stage two – when the cancer is confined to the ovaries.
Working with three cancer treatment centers in the U.S. and Canada, the Georgia Tech researchers obtained blood samples from women with stage one and stage two ovarian cancer. They separated out the serum, which contains proteins and metabolites – molecules produced by enzymatic reactions in the body.
The serum samples were analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), which is two instruments joined together to better separate samples into their individual components. Heavier molecules are separated from lighter molecules, and the molecular signatures are determined with enough accuracy to identify the specific compounds. The Georgia Tech researchers decided to look only at the metabolites in their research.
“People have been looking at proteins for diagnosis of ovarian cancer for a couple of decades, and the results have not been very impressive,” said Facundo Fernández, a professor in Georgia Tech’s School of Chemistry and Biochemistry who led the analytical chemistry part of the research. “We decided to look in a different place for molecules that could potentially provide diagnostic capabilities. It’s one of the places that people had really not studied before.”
Samples from each of the 46 cancer patients were divided so they could be analyzed in duplicate. The researchers also looked at serum samples from 49 women who did not have cancer. The work required eliminating unrelated compounds such as caffeine, and molecules that were not present in all the cancer patients.
“We used really high resolution equipment and instrumentation to be able to separate most of the components of the samples,” Fernández explained. “Otherwise, detection of early-stage ovarian cancer is very difficult because you have a lot of confounding factors.”
The chemical work identified about a thousand candidate compounds. That number was reduced to about 255 through the work of research scientist David Gaul, who removed duplicates and unrelated molecules from the collection.
These 255 compounds were then analyzed by a learning algorithm which evaluated the predictive value of each one. Molecules that did not contribute to the predictive accuracy of the screening were eliminated. Ultimately, the algorithm produced a list of 16 molecules that together differentiated cancer patients with extremely high accuracy – greater than 90 percent.
“The algorithm looks at the metabolic features and correlates them with whether the samples were from cancer or control patients,” McDonald explained. “The algorithm has no idea what these compounds are. It is simply looking for the combination of molecules that provides the optimal predictive accuracy. What is encouraging is that many of the diagnostic features identified are metabolites that have been previously implicated in ovarian cancer.”
As a next step, McDonald and Fernández would like to study samples from a larger population that includes significant numbers of different ethnic and racial groups. Those individuals may have different metabolites that could serve as biomarkers for ovarian cancer.
Though sophisticated laboratory equipment was required to identify the 16 molecules, a screening test would not require the same level of sophistication, Fernández said.
“Once you know what these molecules are, the next step would be to set up a clinical assay,” he said. “Mass spectrometry is a common tool in this field. We could use a clinical mass spectrometer to look at only the molecules we are interested in. Moving this to a clinical assay would take work, but I don’t see any technical barriers to doing it.”
The Fernández and McDonald groups have used a similar approach with prostate cancer and plan to explore its utility for detecting other types of cancer.
The research was supported by grants from The Laura Crandall Brown Ovarian Cancer Foundation, The Ovarian Cancer Research Fund, The Ovarian Cancer Institute, Northside Hospital (Atlanta), The Robinson Family Fund, and the Deborah Nash Endowment Fund.
CITATION: David A. Gaul, et al., “Highly-accurate metabolomics detection of early-stage ovarian cancer,” (Scientific Reports, 2015). http://www.dx.doi.org/10.1038/srep16351
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In the current issue of the journal Science, researchers at Michigan State University, the Georgia Institute of Technology and the University of Texas at Austin demonstrate how a new virus evolves, which sheds light on how easy it can be for diseases to gain dangerous mutations.
The scientists showed for the first time how the virus called “Lambda” evolved to find a new way to attack host cells, an innovation that took four mutations to accomplish. This virus infects bacteria, in particular the common E. coli bacterium. Lambda isn’t dangerous to humans, but this research demonstrated how viruses evolve complex and potentially deadly new traits, said Justin Meyer, MSU graduate student, who co-authored the paper with Richard Lenski, MSU Hannah Distinguished Professor of Microbiology and Molecular Genetics.
“We were surprised at first to see Lambda evolve this new function, this ability to attack and enter the cell through a new receptor – and it happened so fast,” Meyer said. “But when we re-ran the evolution experiment, we saw the same thing happen over and over.”
This paper comes on the heels of news that scientists in the U.S. and the Netherlands produced a deadly version of bird flu. Even though bird flu is a mere five mutations away from becoming transmissible between humans, it’s highly unlikely the virus could naturally obtain all of the beneficial mutations all at once. However, it might evolve sequentially, gaining benefits one-by-one, if conditions are favorable at each step, he added.
Through research conducted at BEACON, MSU’s National Science Foundation Center for the Study of Evolution in Action, Meyer and his colleagues’ ability to duplicate the results implied that adaptation by natural selection, or survival of the fittest, had an important role in the virus’ evolution.
When the genomes of the adaptable virus were sequenced, they always had four mutations in common.
“The parallelism shown in the evolutionary history of adaptable viruses was striking and was far beyond what is expected by chance,” noted paper co-author Joshua Weitz, an assistant professor in the School of Biology at Georgia Tech.
In contrast, the viruses that didn’t evolve the new way of entering cells had some of the four mutations but never all four together, said Meyer, who holds the Barnett Rosenberg Fellowship in MSU’s College of Natural Science.
“In other words, natural selection promoted the virus’ evolution because the mutations helped them use both their old and new attacks,” Meyer said. “The finding raises questions of whether the five bird flu mutations may also have multiple functions, and could they evolve naturally?”
Additional authors of the paper include Devin Dobias, former MSU undergraduate (now a graduate student at Washington University in St. Louis); Ryan Quick, MSU undergraduate; and Jeff Barrick, a former Lenski lab researcher now on the faculty at the University of Texas at Austin.
Funding for the research was provided in part by the National Science Foundation, Defense Advanced Research Projects Agency, James S. McDonnell Foundation and Burroughs Wellcome Fund.
This research was supported in part by the Defense Advanced Research Projects Agency (DARPA) (Award No. HR0011-09-1-0055) and the National Science Foundation (NSF). The content is solely the responsibility of the principal investigator and does not necessarily represent the official views of DARPA or NSF.
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Scientists from Baylor College of Medicine and the Georgia Institute of Technology have won $900,000 from the Ovarian Cancer Research Fund to investigate the early detection of ovarian cancer.
The research, which comprises three separate projects, includes work with a new mouse model of ovarian cancer to identify early detection biomarkers; an effort to characterize proteins and protein variants secreted from ovarian tumors that could serve as serum biomarkers; and work to identify metabolic changes that could help diagnose the disease.
"This grant is a program project development grant, and the idea is to bring together a number of individuals around a common theme," Martin Matzuk, a BCM professor of pathology and immunology and one of the leaders of the project, told ProteoMonitor. "We were previously funded by OCRF along with a number of investigators to focus on the role of microRNAs in ovarian cancer. That work has gone very well, so we put together another proposal in which we decided to focus on biomarkers, whether they're protein or small molecule."
Matzuk is collaborating on the work with his BCM colleague Laising Yen as well as John McDonald, a professor, the associate dean for biology program development in the school of Biology at Georgia Tech, and a chief research scientist at Atlanta's Ovarian Cancer Institute.
McDonald, who will head up the search for metabolomic biomarkers, leads a research team that published a paper in August 2010 detailing a metabolomic ovarian cancer diagnostic that identified women with ovarian cancer with 100 percent accuracy in a 94-subject trial (PM 8/20/2010).
That test used direct-analysis-in-real-time mass spectrometry to measure thousands of metabolites in subjects' blood samples, classifying them with a functional support vector machine-based machine-learning algorithm. McDonald's team is still validating their findings, McDonald told ProteoMonitor this week, but thus far "everything is looking good," and, he said, the researchers hope to finish validating the results sometime within the year.
Under the OCRF grant, the Georgia Tech team plans to use LC-MS/MS to identify specific metabolites detected by their DART-MS work in hopes of combining them with protein biomarkers identified by Matzuk's lab to build an early detection panel for ovarian cancer.
The DART analysis "gives us thousands of features, and for most of them we don't know what they are," McDonald said. "From a diagnostic point of view we don't really care as long as it's a reliable diagnostic. But at the same time we're now running LC-MS/MS to try to whittle it down to identify … the specific metabolites involved."
"The idea is that we'll put it together [with Matzuk's markers] to see what an optimal diagnostic might consist of," he said.
Matzuk and the BCM researchers will be looking for protein biomarkers using a recently developed mouse model of high-grade serous ovarian cancer in which the cancer actually begins in the fallopian tube as opposed to the ovary itself. The model reflects an alternate view of ovarian cancer development "that is gaining a lot of support," Matzuk said.
Because ovarian cancer is difficult to detect early, often by the time patient samples are collected it's "too late to be trying to figure out what are the changes with regard to proteins or metabolic changes," he said. "The nice thing about having a mouse model is that these animals get cancers universally, and so you can open the animals up at a certain period and say, 'OK, at this time point what are the expression changes in these cancers? What are the earliest time points [they are visible]?"
"The goal of all three projects is to [identify] the various transcripts that are out there in these cancers," Matzuk said. "The idea is, once we catalog all of them, to go back in and then screen or develop antibodies to new variants of proteins or new secreted proteins and see whether or not those could be better markers."
The ultimate goal of the work, he said, "is to generate enough data so that we could actually go into the National Institutes of Health for a bigger project that we could start not only between our groups, but also with other groups and centers to look at various biomarkers."
Price will be a major consideration for any early detection test, Matzuk said, noting that he thinks even existing triage tests like Vermillion's OVA1 don't offer enough to justify their cost. Given the low prevalence of ovarian cancer in the general population, he said, any broad screening test for the disease would need to cost under $50 for it to be covered widely by insurers.
"I run a clinical chemistry laboratory in the county hospital, and for us to be doing this kind of screening of healthy women you need to have the cost low," he said.
However, Matzuk suggested, declining instrumentation prices could help bring costs down in the future – particularly in the case of mass spec-based tests, where multiplexing could significantly lower the price of multi-analyte assays.
"Maybe everyone will have [mass spec] analysis of their serum at some point," he said. "I think right now the instrumentation is too expensive and the testing is too expensive to go ahead and say this is for general [screening] tests, but if it turns out that these tests are extremely valuable, people are going to find a way to make them cheaper."
High-throughput DNA sequencing technologies are leading to a revolution in how clinicians diagnose and treat cancer. The molecular profiles of individual tumors are beginning to be used in the design of chemotherapeutic programs optimized for the treatment of individual patients. The real revolution, however, is coming with the emerging capability to inexpensively and accurately sequence the entire genome of cancers, allowing for the identification of specific mutations responsible for the disease in individual patients.
There is only one downside. Those sequencing technologies provide massive amounts of data that are not easily processed and translated by scientists. That’s why Georgia Tech has created a new data analysis algorithm that quickly transforms complex RNA sequence data into usable content for biologists and clinicians. The RNA-Seq analysis pipeline (R-SAP) was developed by School of Biology Professor John McDonald and Ph.D. Bioinformatics candidate Vinay Mittal. Details of the pipeline are published in the journal Nucleic Acids Research.
“A major bottleneck in the realization of the dream of personalized medicine is no longer technological. It’s computational,” said McDonald, director of Georgia Tech’s newly created Integrated Cancer Research Center. “R-SAP follows a hierarchical decision-making procedure to accurately characterize various classes of gene transcripts in cancer samples.”
There are at least 23,000 pieces of RNA in the human genome that encode the sequence of proteins. Millions of other pieces help regulate the production of proteins. R-SAP is able to quickly determine every gene’s level of RNA expression and provide information about splice variants, biomarkers and chimeric RNAs. Biologists and clinicians will be able to more readily use this data to compare the RNA profiles or “transcriptomes” of normal cells with those of individual cancers and thereby be in a better position to develop optimized personal therapies.
Personalized approaches to cancer medicine are already in widespread use for a few “cancer biomarkers” including variants of the BRAC 1 gene that can be used to identify women with a high risk of developing breast and ovarian cancer.
“Our goal was to design a pipeline that is easily installable with parallel processing capabilities,” said Mittal. “R-SAP can make 100 million reads in just 90 minutes. Running the program simultaneously on multiple CPUs can further decrease that time.”
R-SAP is open source software, freely accessible at the McDonald Lab website.
“This is another example of Georgia Tech’s ability to merge computer technology with science to create an essential feature of next-generation bioinformatics tools,” said McDonald. “We hope that R-SAP will be a useful and user-friendly instrument for scientists and clinicians in the field of cancer biology.”
If we were able to resurrect a dinosaur in the laboratory today how could we be certain that the particular dinosaur actually existed in the distant past and does not simply represent some mutant frankensaurus?
Ongoing research at Georgia Tech aims to answer this question in an experimental approach by adding rigor to the methods and protocols used to resurrect components of ancient life.
Dr. Eric Gaucher, Associate Professor in the School of Biology, was recently awarded $700K from the National Science Foundation (NSF) to, for the first time, benchmark ancestral sequence reconstruction methods. Prof. Gaucher’s approach involves generating a known experimental phylogeny in the lab using fluorescent proteins cloned into bacteria. Generating such a “known” phylogeny with evolved sequences will, in turn, allow the group to test resurrection predictions since the true ancestral proteins are generated in the laboratory and are thus known.
An important component of the funding involves integrating evolutionary and molecular biology research into the greater Atlanta community. In collaboration with Dunwoody High school, Dr. Gaucher and Ryan Randall have developed a new Biotechnology curriculum whereby students are introduced to the connections between genotype and phenotype by evolving fluorescent proteins at the high school. In addition, The Gaucher Group annually hosts a team of Dekalb county high school students competing in the National Siemens Competition in Math, Science and Technology, that involves bioengineering of fluorescent proteins.
For his efforts, Prof. Gaucher is also a recent recipient of Georgia Tech’s Class of 1934 Teaching Award. This award is based on student evaluations and presented to faculty with the highest ratings in overall effectiveness in teaching.