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Category: News

Listing of news from the Institute of Bioinformatics at University of Georgia

Dr. Jessica Kissinger elected AAAS Fellow!

Three UGA faculty elected as AAAS Fellows

(L to R) Patricia Yager, Jessica Kissinger, James E. Byers.

(L to R) Patricia Yager, Jessica Kissinger, James E. Byers.

Three University of Georgia faculty have been named Fellows of the American Association for the Advancement of Science.

In a tradition stretching back to 1874, these individuals are elected annually by the AAAS Council for their extraordinary achievements leading to the advancement of science. Fellows must have been AAAS members for at least four years.

“Researchers are elected Fellows of the AAAS by their peers in recognition of significant contributions to their field,” said Karen Burg, vice president for research. “As we expand our research and innovation ecosystem, it’s exciting to see our faculty continue to be honored for their superb scholarship. I congratulate all of them on this wonderful achievement.”

The 2021 class of AAAS Fellows includes 564 scientists, engineers and innovators spanning 24 scientific disciplines who are being recognized for their scientifically and socially distinguished achievements. The new Fellows will be honored at the annual AAAS meeting in Philadelphia, Feb. 17-20.  Along with the rest of their 2021 class, UGA’s three new Fellows will receive an official certificate and a gold and blue rosette pin whose colors represent science and engineering.

Including these three, 37 faculty at UGA are Fellows of the American Association for the Advancement of Science.

UGA’s 2021 AAAS Fellows are:

James E. Byers: Meigs Distinguished Teaching Professor and associate dean for research and operations in the Odum School of Ecology, Byers was selected for distinguished contributions to the field of ecology, particularly in invasion biology, parasite ecology, ecosystem engineering and range boundaries in marine environments, as well as excellence in teaching.

Jessica Kissinger: Distinguished Research Professor of genetics in the Franklin College of Arts and Sciences, Kissinger was selected for distinguished contributions to the field of the evolution of infectious diseases, particularly for bioinformatics approaches.

Patricia Yager: Professor of marine science in the Franklin College, Yager was selected for outstanding work on climate-driven processes and their impact on marine ecosystems.

To view a list of all AAAS Fellows from UGA, visit the Office of Research website.

Xu Tan Successfully Defends Dissertation

Xu Tan of Dr. Andrew Paterson’s lab has successfully defended his dissertation, “Comprehensive analysis of resistance gene evolution, structural variation and recent genome rearrangement in plant genomes” on Wednesday, December 15, 2021. Congratulations Dr. Tan!

Dr. Liliana Salvador, Infectious Diseases & Institute of Bioinformatics, Receives Award from Research Corporation for Science Advancement and the U.S. Department of Agriculture

Research Corporation for Science Advancement and the U.S. Department of Agriculture have awarded a total of $1.25 million to 10 multidisciplinary teams of early career scientists — including Liliana Salvador, Infectious Diseases & Institute of Bioinformatics, University of Georgia — in the first year of the Scialog: Mitigating Zoonotic Threats initiative. Each of the 25 individual awards is $50,000. 

Awards will go to 20 early career researchers from a variety of institutions, including two U.S. Department of Agriculture agencies working together at the National Bio and Agro-Defense Facility — the Animal and Plant Health Inspection Service and the Agricultural Research Service. The funded projects, to launch new research in the detection and mitigation of emerging animal-borne infectious diseases, include seven new partnerships between USDA and academic scientists. 

Read the full announcement. 

Shunhua Han Successfully Defends Dissertation

Shunhua Han of Dr. Casey Bergman’s lab has successfully defended his dissertation, “Novel computational strategies for the analysis of transposable elements in Drosophila cell culture genomes.” on Friday, November 19, 2021. Congratulations Dr. Han!

IOB Faculty News | Alexander Bucksch, NSF Research News: Adapting plant roots to a hotter planet could help ease pressure on food supply

Research News

Supercomputer-powered 3D imaging of roots helps develop climate change-adapted plants

Composite artwork of a photograph and a reconstructed 3D model of the same maize root.

Composite artwork of a photograph and a reconstructed 3D model of the same maize root.

 

November 3, 2021

The shoots of plants get all the glory, with their fruit and flowers and visible structure. But it’s the portion that lies below the soil — the branching, reaching arms of roots and hairs pulling up water and nutrients — that has deep implications for the future, according to plant physiologist and computer scientist Alexander Bucksch of the University of Georgia.

The ability to grow enough food to support the population despite a changing climate, and soil’s ability to fix carbon from the atmosphere, are critical to human and other species’ survival. The solutions, Bucksch believes, lie in the quality of roots.

“When there is a problem in the world, humans can move. But what does the plant do?” said Bucksch. “It says, ‘Let’s alter our genome to survive.’ It evolves.”

Until recently, farmers and plant breeders didn’t have a good way to gather information about the root system of plants or make decisions about the optimal seeds to grow deep roots.

In a paper published in Plant Physiology, Bucksch and colleagues introduce Digital Imaging of Root Traits, or DIRT/3D, an image-based 3D root phenotyping platform that can measure 18 architecture traits from mature field-grown maize root crowns.

The system reliably computed all traits, including the distance between whorls and the number, angles and diameters of nodal roots for 12 contrasting maize genotypes with an 84% agreement when compared to manual measurements. The research is supported by the U.S. National Science Foundation.

Scientists who use DIRT/3D to image roots will soon be able to upload their data to a service called PlantIT that can perform the same analyses that Bucksch and his collaborators describe in their paper. PlantIT provides information on a wide range of traits from young nodal root length to root system eccentricity. These data let researchers and breeders compare the root systems of plants from similar or different seeds.

The framework is made possible by massive number-crunching capabilities behind the scenes provided by the Texas Advanced Computing Center.

Gerald Schoenknecht, a program director in NSF’s Division of Integrative Organismal Systems, added, “This is a great example how the interdisciplinary application of high-performance computing on plant physiology enables new experimental approaches and provides new biological insights.”

—  NSF Public Affairs, Researchnews@nsf.gov

Dr. Kannan: New UGA study maps the structural diversity of sugar building enzymes using AI

Tuesday, October 5, 2021 – 10:22am

By:Alan Flurry

Sugars in our bodies, and in nearly all living organisms, are synthesized and built by a large family of proteins called Glycosyltransferases (GTs) that adopt unique three-dimensional structures and folds to perform a diverse array of cellular functions. Understanding the structure and fold of these proteins is an important first step towards characterizing their functions, which is critical for developing effective glycovaccines and for improving crop yields and sustainable biofuels through the synthetic design of glycoproteins with desirable functional properties.

However, despite significant efforts in the structural characterization of GTs, mapping the full functional and fold landscape remains a challenge because of the large and diverse nature of these proteins and the cost and time associated with their structural characterization.

To address this challenge, an inter-disciplinary team of UGA researchers have leveraged recent advances in deep learning to predict and classify GT folds from primary sequences with high accuracy. Deep learning is a branch of artificial intelligence (AI) that uses interconnected artificial neural networks to automatically find patterns in large datasets.

The methods are designed to mimic the learning process of the human brain and are widely used in a range of applications from marketing to self-driving cars. However, their application in biology is only being realized, thanks to the massive amounts of biological data generated from gene sequencing studies.

“With over a half million GT sequences available, investigating the relationships connecting primary sequence, fold and function is a problem well poised for the application of deep learning methods” said Natarajan Kannan, professor of biochemistry and molecular biology and the Institute of Bioinformatics in the Franklin College of Arts and Sciences who led the research team.

Their work, published in the journal Nature Communications, reports the development of an “interpretable” deep learning model for predicting GT fold and function from primary sequences.

“One unique aspect of our model is that it is simple and interpretable, meaning that the neural network can be tracked by identifying the neurons that get activated during the learning process, which, in turn, helps in the biological interpretation of the prediction and classification process,” said Sheng Li, assistant professor of computer science and co-author on the study. “This is conceptually different from most existing deep learning models that operate as a “black box.”

“By predicting GTs that can adopt novel folds, this study provides a range of structural templates along with their crucial functional features for the design and synthesis of novel GTs for various applications,” said Kannan, who received a Maximizing Investigator Research Award, or MIRA, from the National Institute of General Medical Sciences in March 2021.

“This method promises to be a valuable tool for the glycobiology community and marks a significant milestone towards leveraging the full potential of GTs in biomedicine and other industries. It’s one great advantage to receiving the NIGMS award, which provides us with the flexibility to move in new and exciting directions,” he said.

The award and the new study help support interdisciplinary graduate training in the Institute of Bioinformatics and the department of computer science, as well build new synergies with campus-wide AI initiatives at UGA.

Image: Figure 2 from the studyDots represent 2D UMAP projection of features for individual sequences.

 

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UGA’s Art Edison is co-principal investigator of $40M NSF grant for NMR network

Science & Technology

UGA part of $40M grant for NMR network

GRA Eminent Scholar Arthur Edison in the NMR Facility at the CCRC. (Photo by Andrew Davis Tucker/UGA)

UGA’s Art Edison is co-principal investigator for the NSF-funded project

Researchers all over the world will have access to the University of Georgia’s expertise in nuclear magnetic resonance, or NMR, thanks to a new infrastructure funded by a $40 million grant from the National Science Foundation.

The Network for Advanced Nuclear Magnetic Resonance, or NAN, will allow researchers to access ultra-high field nuclear magnetic resonance spectrometers to study the structure, dynamics and interactions of biological systems and small molecules. The project is led by the University of Connecticut School of Medicine in partnership with UGA and the University of Wisconsin.

“This is much more than just a new expensive instrument—it’s an entirely different way of thinking about doing NMR,” said Art Edison, co-principal investigator and Georgia Research Alliance Eminent Scholar. “Once we started to think in those terms, a lot of ideas emerged. For example, we want to create an easy way for scientists to discover what is available to them, even if they aren’t NMR experts themselves. We also realized that everyone has the same problems dealing with data: saving it, processing it, analyzing it and depositing it into public databases. Centralizing this would be much more efficient.”

Edison teamed with colleagues at UConn and UW to develop the concept for NAN, which has three primary goals: to provide institutional researchers across the country easy access to the most powerful instruments, simplify the discovery and use of NMR resources, and foster good data stewardship. It will allow researchers across the U.S. to expand their own biomedical research study findings and collectively contribute any new scientific insights to the evolving NAN knowledge bases.

Researchers will be able to visit or deliver their samples for analysis using state-of-the-art 1.1 GHz instruments located in Athens, Georgia, and Madison, Wisconsin. Both instruments, as well as the large number of existing instruments at all three locations, will be linked to a central hub based at UConn Health in Farmington, Connecticut, that will assist discovery and scheduling, host knowledge bases with information on optimal experiment design, and securely archive the collected data.

“This new infrastructure, along with the network of scientists to support it, will advance research in biological sciences across the country through innovative experimentation and new biological insights,” said NSF Assistant Director for Biological Sciences Joanne Tornow.

The network will be led by UConn’s Jeffrey C. Hoch, along with Edison and co-principal investigators Katherine Henzler-Wildman and Chad Rienstra from the University of Wisconsin.

“Thanks to NSF’s funding, our new network will empower researchers to have open access to the latest advanced NMR technology with the necessary computational power to fuel future discoveries,” said Hoch, professor of molecular biology and biophysics at UConn School of Medicine. “Any researcher nationwide with a laptop will be able to make use of these powerful NMR instruments, methods and online data bank.”

NAN’s central hub at UConn has a computational resource that brings NMR processing and software into one location, and they’ll also be in charge of the primary database where people will deposit NMR data. UGA provides expertise in metabolomics and protein structural biology, especially with complex carbohydrate modifications—areas that were pioneered by Jim Prestegard, emeritus professor and GRA Eminent Scholar at the university’s Complex Carbohydrate Research Center. Edison is a member at the CCRC as well as the Institute of Bioinformatics.

“We are building two knowledge bases for NAN in these areas, and these will be designed to make it easier for non-experts to use our NMR resources to solve important problems,” said Edison, professor of biochemistry and molecular biology and genetics in the Franklin College of Arts and Sciences. “This is not going to be easy, but will have great impact.”

Edison’s field is metabolomics, and the overall goal is to measure metabolites in biological systems like human disease, plants and microbes. NAN will benefit collaborations across campus in areas like cell manufacturing, dog and cat health and nutrition, carbon cycling in the ocean, and basic biology of microbes. There is also potential for facilitating drug discovery by learning the shape and dynamics of proteins and carbohydrates, according to Edison. All of these areas are central to research in precision medicine.

“The University of Georgia’s partnership in this significant national project underscores our commitment to advancing discovery in a range of critically important fields,” said S. Jack Hu, the university’s senior vice president for academic affairs and provost. “We thank Georgia Research Alliance Eminent Scholar Dr. Art Edison for his national leadership on this project.”

UGA will also play an important role in connecting NAN with HBCUs.

“We have several strong relationships with HBCUs that we will build on to use NAN to help underrepresented students have more advanced NMR resources available for their research,” Edison said.

This grant award is part of NSF’s Mid-Scale Research Infrastructure II program, an NSF-wide effort to meet the research community’s needs for modern research infrastructure to support science and engineering research. More information about the Mid-Scale Research Infrastructure-2 program supporting the Network for Advanced NMR project can be found at nsf.gov.

Source: UGA Columns, JUN 16, 2021, https://news.uga.edu/uga-part-of-40m-grant-for-nmr-network/?utm_source=digital-issue&utm_medium=email&utm_campaign=columns-20210628