November 17, 2018

Ribonucleotide monophosphates (rNMPs) and deoxyribonucleotide monophosphates are the basic building blocks of RNA and DNA. The difference between them is that  rNMPs contain ribose instead of deoxyribose as their sugar component. During processes like DNA replication and repair, rNMPs become embedded in genomic DNA, influencing DNA fragility, mutability, and ultimately the stability of the genome.

Because rNMPs alter the way DNA works in both structure and function, it’s important to be able to identify them and their sites of genomic incorporation. Recent advances in high-throughput sequencing techniques now make it possible to tag rNMPs embedded in genomic DNA. Simultaneously with three other methods to capture rNMPs in DNA, a unique and robust  technique called ribose-seq was developed by the lab of Francesca Storici, professor in the School of Biological Sciences at the Georgia Institute of Technology, and her collaborators.

They published a description of the technique and the discoveries it yielded a few years ago in the journal Nature Methods. While their method is applicable to DNA from virtually any source and organism (including humans), allowing the researchers to determine the full profile of rNMPs embedded in genomic DNA, it essentially generates  large, complex datasets like the other three approaches to study ribonucleotides in DNA.

“But there is no standardized system to analyzing the data from ribose-seq or the three other techniques,” notes Alli Gombolay, a fourth-year PhD student in Storici’s lab. “We wanted to create a bioinformatics toolkit that could rapidly and effectively analyze the data from any of those techniques to study all types of data and gather as much information as possible.”

Standard computational pipelines designed to map embedded rNMPs are customized for data generated using only one kind of sequencing technique. So Gombolay and her co-advisors – Storici and Fred Vannberg, researchers in the Petit Institute for Bioengineering and Bioscience – developed Ribose-Map.

They recently published their research in the journal Nucleic Acids Research. In their paper, entitled “Ribose-Map: a bioinformatics toolkit to map ribonucleotides embedded in DNA,” they describe how to transform raw sequencing data into summary datasets and publication-ready results, which would allow researchers to identify sites of embedded rNMPs, study the nucleotide sequence context of these rNMPs, and explore their genome-wide distribution.

 “Ribose-Map increases reproducibility and allows us to directly compare the data, and ultimately gather more information.” says Gombolay.

Other labs are already interested in making those comparisons. This became abundantly clear to Gombolay in September when she attended the 15th RNase H meeting in Warsaw, Poland, a biennial international gathering.

For researchers who want to know more about Ribose-Map and how to use it, Gombolay has created a GitHub page, where she describes how to set-up, install, and run the toolkit.

“It’s a simpler approach to mapping ribose in DNA or other modifications,” she says. “It’s particularly helpful for people with limited bioinformatics skillsets, or for people who are new to the relatively small field of ribonucleotide mapping. But since we can now map ribonucleotides in DNA, we think the field could grow faster.”

November 14, 2018

Trillions of cubic feet of natural gas is thought to lie in cold storage within Earth’s permafrost and under its oceans. That gas, however, is trapped within chemical cage-like structures called methane clathrates. Scientists are very interested in these structures, because they may have cousins hidden under the surface of the icy moons in the outer solar system.

Whether the clathrates are on Earth or the Jovian moon Europa, science wants to know: What role did microbes play in their formation and stability? How are they involved when Earthbound clathrates start deteriorating, releasing this greenhouse methane gas into an already-warming global atmosphere? Is that process underway millions of miles from Earth?

An interdisciplinary team of Georgia Tech geo-microbiologists, biochemists, and geo-engineers will have a chance to answer those questions, thanks to a grant from the NASA Exobiology Program that comes with a heady title: Microbial Interactions with Methane Clathrate: Implications for Habitability of Icy Moons. The investigators, which include College of Sciences researchers, will search for DNA blueprints of potential clathrate-binding proteins, will reproduce those proteins in a laboratory, and will test their impact on methane clathrate properties. 

“This is a truly interdisciplinary project to understand how microbial life survives in methane clathrates under the seafloor,” says Jennifer Glass, assistant professor in the School of Earth and Atmospheric Sciences. Glass will serve as the team’s principal investigator.

“These deep microbes encode genes that are different from any found on the Earth's surface,” Glass says. “This grant will be one of the first efforts to study the biochemistry of these new biomolecules, and how they affect the structure and properties of methane clathrate. This research is only possible because our Georgia Tech team is uniquely working at the interface between microbial ecology, biochemistry, and geoengineering."

Clathrates are lattice-like structures made of a solid similar to ice. They are buried in polar permafrost and under the world’s oceans, and scientists believe they could hold anywhere from 100,000 to 1 million Tcf (trillion cubic feet) of natural gas. The gas molecules are trapped inside the crystalline structures, but large-scale commercial extraction isn’t available yet. However, plumes of methane have been recorded leaking from Arctic permafrost thanks to global warming. (Methane is already produced via decaying organic matter in landfills, traditional oil and gas exploration, and within the stomachs of domestic livestock.)

Visits from planetary probes, spectroscopy readings, and other research indicate that methane clathrates may exist on the icy moons of Jupiter and Saturn. They may be part of developing ecosystems. Did microbes interact with those clathrates? Could they be tapped in the search for life in the solar system? Could those gas resources help sustain human habitats on the Jovian moon Europa?

"We are excited to learn more about the fascinating molecules that bind methane ice in this unique environmental niche,” says Raquel Lieberman, professor in the School of Chemistry and Biochemistry, and one of the methane clathrate team members. “These proteins don’t look like any others known in temperate environments."

In addition to Glass and Lieberman, other team members include research scientist Anton Petrov and Professor Loren Williams, both with the School of Chemistry and Biochemistry; and Sheng Dai, assistant professor in the School of Civil and Environmental EngineeringAbbie Johnson, an EAS graduate student in the Ocean Science & Engineering Program, will work on the project for her doctoral dissertation. 

Glass has a courtesy appointment with the School of Biological Sciences. She also is on the faculty of the Parker H. Petit Institute for Bioengineering and Biosciences.

 

November 12, 2018

So audacious was Marcus Bray’s experiment that even he feared it would fail.

In the system inside cells that translates genetic code into life, he replaced about 1,000 essential linchpins with primitive substitutes to see if the translational system would survive and function. It seemed impossible, yet it went swimmingly, and Bray had compelling evidence that the system would have worked as it is today in extremely harsh conditions 4 billion years ago when it evolved.

The experiment’s success reaffirmed the translational system’s place at the earliest foundations of life on Earth and its robustness through the eons.

The translational system

Every living thing exists because the translational system receives messages from DNA delivered to it by RNA and translates the messages into proteins. The system centers on a cellular machine called the ribosome, which is made of multiple large molecules of RNA and protein and is ubiquitous in life as we know it.

“There’s nothing alive without ribosomes,” said Loren Williams, a professor at the Georgia Institute of Technology’s School of Chemistry and Biochemistry. “The ribosome is about the oldest and most universal part of biology, and its origins go very far back to a time not too long after Earth had formed and cooled.”

Magnesium linchpins yanked

Those linchpins that hold it all together and that Bray yanked out and replaced were metal ions (atoms with charges, in this case positive).

In today’s ribosome, and in the whole translational system, the linchpins are magnesium ions, and Bray’s experiment replaced them all with iron ions and manganese ions, which were overabundant on primordial Earth. Williams and Jennifer Glass, the principal investigators in the new study, also had their doubts the system would hold up without the magnesium.

“I thought, ‘It’s not going to work, but we might as well try the moonshot’,” said Williams who has led similar work before but on simpler molecules. “The fact that swapping out all the magnesium in the translational system actually worked was mind-boggling.”

That’s because in living systems today, magnesium helps shape ribosomes and help them work. It is needed in addition to the ribosome for some 20 enzymes of the translational system. It’s one reason why dietary magnesium (Mg) is so important.

“The number of different things magnesium does in the ribosome and in the translational system is just enormous,” said Williams. “There are so many types of catalytic activities in translation, and magnesium is involved in almost all of them.”

Lava-belching Earth

When first life evolved, fissures in Earth’s crust still belched lava and meteor impacts were still common. There was no breathable oxygen and the planet was brimming with iron and manganese.

This may have made them attractive for the translational system to use as the dominant ions. Magnesium was likely involved, too, though it was probably less available than today.

The researchers wanted to know if the translational system first evolved to function with those other metals as their linchpins. So, Bray, a graduate research assistant in Williams’s and in Glass’s lab, swapped out the magnesium ions for them, tabula rasa.

“We didn’t have any substantial reason to believe it would work, and it was a huge surprise to all of us when it did,” Bray said. And it strongly corroborated that the translational system would have thrived under early Earth conditions.

Bray, co-first author Timothy Lenz and co-principal investigators Glass and Williams published their results in the journal Proceedings of the National Academy of Sciences on November 9, 2018. The research was funded by the NASA Exobiology program. Glass is an assistant professor in Georgia Tech’s School of Earth and Atmospheric Sciences.

‘Textbook-rewriting results’

Amazingly, the atomic swaps barely changed the shape of the ribosome. 

“It’s totally unbelievable this would work because biology makes very specific use of things. Change one atom and it can wreck a whole protein,” Williams said. “When we probed the structure, we saw that all three metals do essentially the same thing to the structure.”

When they tested the performance of the translational system with iron replacing magnesium, it was 50 to 80 percent as efficient as normal (with magnesium). “Manganese worked even better than iron,” Bray said.

“I think these may be textbook-rewriting results since the whole field of ribosome research involves magnesium,” Bray said. “Now, with what we’ve done, it’s no longer the case that only magnesium works.”

Primordial gas tent

Bray incubated ribosomes in the presence of magnesium, iron, or manganese inside a special chamber with an artificial atmosphere devoid of oxygen, like the Earth four billion years ago.

He found that the magnesium replacement went far beyond atoms in the ribosome.

“Surrounding the ribosome is also a huge cloud of magnesium atoms. It’s called an atmosphere, or shell, and engulfs it completely. I replaced everything, including that, and the whole system still worked.”

Eons down the road, the evolution of the translational system in the presence of magnesium may have given it an adaptive advantage. As oxygen levels on Earth rose, binding up free manganese and iron, and making them less available to biology, magnesium probably comfortably assumed the thousands of roles it occupies in the translational system today.

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Also READ: Laughing Gas May Have Helped Warm Early Earth and Given Breath to Life

These researchers coauthored the study: Jay Haynes, Jessica Bowman, Anton Petrov, Amit Reddi, and Nicholas Hud, all of Georgia Tech. The research was funded by the NASA Exobiology program (grants NNX14AJ87G, NNX16AJ28G, and NNX16AJ29G). Findings, conclusions, opinions, and recommendations in the material are those of the authors and not necessarily of NASA. 

Study in PNAS: http://www.pnas.org/content/early/2018/10/30/1810140115

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Writer: Ben Brumfield

November 9, 2018

The Mysteries of Animal Movement

The New York Times
Nov. 5, 2018

David Hu's unfettered curiosity leads him to investigate the physics at work in some very odd corners of the natural world. Read his profile about winning the Ig Nobel Prize, measuring the eyelashes of sheep, and his new book, "How to Walk on Water and Climb up Walls: Animal Movements and Robotics of the Future".

November 8, 2018

Ever wondered why your dog’s back-and-forth shaking is so effective at getting you soaked? Or how bugs, birds, and lizards can run across water—but we can’t? Or how about why cockroaches are so darn good at navigating in the dark? 

Those are just a few of the day-to-day mysteries answered in the new book How to Walk on Water and Climb Up Walls: Animal Movement and the Robots of the Future, by Georgia Tech's David Hu. Hu is an associate professor in the Schools of Mechanical Engineering and of Biological Sciences and an adjunct associate professor in the School of Physics.  

Listen to the Science Friday episode that aired on Nov. 2, 2018.

November 7, 2018

The nation needs to ramp up efforts to suck heat-trapping gases out of the air to fight climate change, a new U.S. report said. The report from the National Academy of Sciences says technology to do so has gotten better, and climate change is worsening....The good news is that technology in this field has advanced more in the past nine months than it had in the previous decade, said study co-author Christopher Jones, an engineering professor of Georgia Tech. Jones is also a professor in the Georgia Tech School of Chemistry and Biochemistry. 

Read the full story here as it appeared in the Miami Herald on Oct. 24, 2018.

November 6, 2018

The selection of a first-line chemotherapy drug to treat many types of cancer is often a clear-cut decision governed by standard-of-care protocols, but what drug should be used next if the first one fails?

That’s where Georgia Institute of Technology researchers believe their new open source decision support tool could come in. Using machine learning to analyze RNA expression tied to information about patient outcomes with specific drugs, the open source tool could help clinicians chose the chemotherapy drug most likely to attack the disease in individual patients.

In a study using RNA analysis data from 152 patient records, the system predicted the chemotherapy drug that had provided the best outcome 80 percent of the time. The researchers believe the system’s accuracy could further improve with inclusion of additional patient records along with information such as family history and demographics.

“By looking at RNA expression in tumors, we believe we can predict with high accuracy which patients are likely to respond to a particular drug,” said John McDonald, a professor in the Georgia Tech School of Biological Sciences and director of its Integrated Cancer Research Center. “This information could be used, along with other factors, to support the decisions clinicians must make regarding chemotherapy treatment.”

The research, which could add another component to precision medicine for cancer treatment, was reported November 6 in the journal Scientific Reports. The work was supported in part by the Atlanta-based Ovarian Cancer Institute, the Georgia Research Alliance, and a National Institutes of Health fellowship.

As with other machine learning decision support tools, the researchers first “trained” their system using one part of a data set, then tested its operation on the remaining records. In developing the system, the researchers obtained records of RNA from tumors, along with with the outcome of treatment with specific drugs. With only about 152 such records available, they first used data from 114 records to train the system. They then used the remaining 38 records to test the system’s ability to predict, based on the RNA sequence, which chemotherapy drugs would have been the most likely to be useful in shrinking tumors.

The research began with ovarian cancer, but to expand the data set, the research team decided to include data from other cancer types – lung, breast, liver and pancreatic cancers – that use the same chemotherapy drugs and for which the RNA data was available. “Our model is predicting based on the drug and looking across all the patients who were treated with that drug regardless of cancer type,” McDonald said.

The system produces a chart comparing the likelihood that each drug will have an effect on a patient’s specific cancer. If the system were to be used in a clinical setting, McDonald believes doctors would use the predictions along with other critical patient information.

Because it measures the expression levels for genes, analysis of RNA could have an advantage over sequencing of DNA, though both types of information could be useful in choosing a drug therapy, he said. The cost of RNA analysis is declining and could soon cost less than a mammogram, McDonald said.

The system will be made available as open source software, and McDonald’s team hopes hospitals and cancer centers will try it out. Ultimately, the tool’s accuracy should improve as more patient data is analyzed by the algorithm. He and his collaborators believe the open source approach offers the best path to moving the algorithm into clinical use.

“To really get this into clinical practice, we think we’ve got to open it up so that other people can try it, modify if they want to, and demonstrate its value in real-world situations,” McDonald said. “We are trying to create a different paradigm for cancer therapy using the kind of open source strategy used in internet technology.”

Open source coding allows many experts across multiple fields to review the software, identify faults and recommend improvements, said Fredrik Vannberg, an assistant professor in the Georgia Tech School of Biological Sciences. “Most importantly, that means the software is no longer a black box where you can’t see inside. The code is openly shared for anybody to improve and check for potential issues.”

Vannberg envisions using the decision-support tool to create “virtual tumor boards” that would bring together broad expertise to examine RNA data from patients worldwide. 

“The hope would be to provide this kind of analysis for any new cancer patient who has this kind of RNA analysis done,” he added. “We could have a consensus of dozens of the smartest people in oncology and make them available for each patient’s unique situation.”

The tool is available on the open source Github repository for download and use. Hospitals and cancer clinics may install the software and use it without sharing their results, but the researchers hope organizations using the software will help the system improve.

“The accuracy of machine learning will improve not only as the amount of training data increases, but also as the diversity within that data increases,” said Evan Clayton, a Ph.D. student in the Georgia Tech School of Biological Sciences. “There's potential for improvement by including DNA data, demographic information and patient histories. The model will incorporate any information if it helps predict the success of specific drugs."

In addition to those already mentioned, the research team included Cai Huang, Lilya Matyunina, and DeEtte McDonald from the Georgia Tech School of Biological Sciences, and Benedict Benigno from the Georgia Tech Integrated Cancer Research Center and the Ovarian Cancer Institute.

Support for the project came from the Ovarian Cancer Institute, and equipment used was provided by the Georgia Research Alliance. In addition, the National Institutes of Health supported a graduate fellowship.

CITATION: Cai Huang, et al., “Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy,” (Scientific Reports 2018). http://dx.doi.org/10.1038/s41598-018-34753-5

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Media Relations Contact: John Toon (404-894-6986) (jtoon@gatech.edu).

Writer: John Toon

November 6, 2018

The h-index has become a widely cited measure of a researcher’s influence and citation impact. A researcher with an index of h has published h papers which have been cited in other papers at least h times. If someone has an h-index of 100, it means that 100 papers by this researcher have been cited  in at least 100 other research publications.

Scoring an h-index of more than 100 is a singular feat that is achieved by few researchers. According to a recent survey of public Google Scholar profiles, several professors in the College of Sciences have achieved this milestone:

  • Jean-Luc Bredas, School of Chemistry and Biochemistry
  • Mostafa El Sayed, School of Chemistry and Biochemistry
  • Uzi Landman, School of Physics
  • Seth Marder, School of Chemistry and Biochemistry
  • Zhong Lin Wang, School of Chemistry and Biochemistry, adjunct
  • Younan Xia, School of Chemistry and Biochemistry

Image Credit: en:user:Ael 2, vectorized by pl:user:Vulpecula - vectorized version of File:H-index_plot.PNG, Public Domain, https://commons.wikimedia.org/w/index.php?curid=8716387

November 5, 2018

Dan Margalit and Chongchun Zeng have been named to the 2018 class of Fellows of the American Mathematical Society (AMS).

Margalit and Zeng are professors in the School of Mathematics. Margalit is recognized for “contributions to low-dimensional topology and geometric group theory, exposition, and mentoring.” Zeng is honored for “contributions to applied dynamical systems and nonlinear partial differential equations.”

AMS Fellows are selected for their outstanding contributions to the creation, exposition, advancement, communication, and utilization of mathematics.

“This year's class of AMS Fellows has been selected from a large and deep pool of superb candidates,” said AMS President Kenneth Ribet, a professor of mathematics in the University of California, Berkeley. “It is my pleasure and honor as AMS President to congratulate the new Fellows for their diverse contributions to the mathematical sciences and to the mathematics profession.”

November 1, 2018

NASA Astrobiology Program awards $7 million to Georgia Tech-led Oceans Across Space and Time alliance to intensify the search for life in our solar system’s present and past oceans

NASA has navigated our solar system with spacecraft and landers, but still, our celestial neighbors remain vast frontiers, particularly in the search for life. Now, an alliance of researchers will accelerate the quest to find it.

The NASA Astrobiology Program has announced the establishment of the Network for Life Detection, NFoLD, which connects researchers to pursue the detection of life and clues thereof on our neighboring planets and their moons. NFoLD includes an oceanic research alliance led by the Georgia Institute of Technology. 

It is called Oceans Across Space and Time, OAST, and has received a $7 million NASA Astrobiology grant with the long-range goal of extracting secrets from present and past oceans on Mars, Jupiter’s icy moon Europa, and Saturn’s moon Enceladus. But OAST will also ramp up the study of the conditions that spawned first life in Earth’s oceans.

“With OAST, we finally hit the perfect mix of people, science questions, and supporting activities to really go after some of the most important unknowns in astrobiology,” said Britney Schmidt, OAST’s principal investigator and an assistant professor in Georgia Tech’s School of Earth and Atmospheric Sciences.

NFoLD is one of five new Research Coordination Networks that the NASA Astrobiology Program has announced. The other RCNs pull together research communities that include the study of early Earth and its chemistry, evolution, distant habitable worlds, and exoplanet systems.

Yellow submarine on Europa 

Oceans Across Space and Time could one day help NASA put a submarine on a rocket to Europa to look for life in the ocean beneath its ice crust. Or OAST could join NFoLD colleagues to help NASA explore parched Martian landscapes that once were oceans.

But the path to our space neighbors leads through studying Earth. Field and lab experiments on our planet will divulge more knowledge about chemical and biological evolutionary strategies so that researchers can develop instruments and methodology that reliably detect signs of life on other planets and moons.

"We don't yet have a slam-dunk measurement that we could make on another planet to definitively say ‘this is life,’” said Schmidt, who coordinates OAST and led the application efforts to establish it. “OAST’s main goal is to take a suite of technologies into the field on Earth to make measurements side-by-side while returning samples to the lab to understand.” 

Then, when that is very finely honed, send it aloft.

Crucial target practice 

One of NFoLD’s goals is to participate in future astrobiology space missions from the start so that they can successfully identify target spots on other planets or moons where signs of life could actually be detected if present.

"A major challenge for life detection is where on a given planet or moon to look for life,” said Jeff Bowman, deputy principal investigator of OAST and an assistant professor at Scripps Institution of Oceanography at UC San Diego. “The density of life on our own planet extends across several orders of magnitude. Look for life in the wrong place and Earth could appear lifeless.”

OAST’s team has the expertise to bridge earthly data and celestial goals.

Many of its 18 co-investigators and their teams have already explored biogeochemistry in our own planet’s eons-old rock record, in the atmosphere, the oceans, and the icecaps with an eye to extrapolating the data to other worlds. Other OAST researchers have helped design Mars probes or build robotic submarines intended to one day dive into Europa’s subsurface ocean to detect life or at least a hint of it.

“OAST researchers have expertise in detecting and characterizing life in a variety of harsh environments like the Antarctic, the deepest ocean trenches, and lakes with extreme chemistry and salinity,” Bowman said. “We will leverage this expertise to understand how life may be distributed in different ocean environmental extremes around the solar system.”

Diverse member institutions

OAST includes investigators from Scripps Institution of Oceanography at the University of California San Diego; the University of Kansas; Louisiana State University; the Massachusetts Institute of Technology; Stanford University; the Blue Marble Space Institute of Science; the University of Texas; Colgate University; the University of California, the University of Central Florida; the University of Auckland; York University; the University of Otago, and the New Zealand National Institute of Water and Atmospheric Research.

“I'm particularly proud of the high number of women and pre-tenure scientists we've engaged through our project,” said Schmidt. Five leaders in OAST are women, and 12 researchers are early career or pre-tenure. The project will also support graduate and undergraduate students as well as postdoctoral researchers through the NASA Postdoctoral Program.

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Also READ: Laughing Gas May Have Helped Warm Early Earth and Given Breath to Life

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Media relations assistance: Ben Brumfield (404) 660-1408, ben.brumfield@comm.gatech.edu

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