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ORNL’s Tomás Rush explores the secret lives of fungi and plants for insights into the interactions that determine plant health. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Tomás Rush began studying the mysteries of fungi in fifth grade and spent his college intern days tromping through forests, swamps and agricultural lands searching for signs of fungal plant pathogens causing disease on host plants.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

ORNL scientists created a new microbial trait mapping process that improves on classical protoplast fusion techniques to identify the genes that trigger desirable genetic traits like improved biomass processing. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy. Reprinted with the permission of Oxford University Press, publisher of Nucleic Acids Research

ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.

An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy

To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.

Carrie Eckert

Carrie Eckert applies her skills as a synthetic biologist at ORNL to turn microorganisms into tiny factories that produce a variety of valuable fuels, chemicals and materials for the growing bioeconomy.

Summer Widner, Stephanie Timbs, James Gaugler and James Avenell of ORNL are part of a team that processes thorium-228, a byproduct of actinium-227. As new uses for thorium are realized, particularly in medicine, the lab expects the demand for the radioisotope to grow.

As a medical isotope, thorium-228 has a lot of potential — and Oak Ridge National Laboratory produces a lot.

ORNL metabolic engineer Adam Guss develops genetic tools to modify microbes that can perform a range of processes needed to create sustainable biofuels and bioproducts. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

As a metabolic engineer at Oak Ridge National Laboratory, Adam Guss modifies microbes to perform the diverse processes needed to make sustainable biofuels and bioproducts.

Researchers studying secondary metabolites in the fungus Aspergillus flavus, pictured, found unique mixes of metabolites corresponding to genetically distinct populations. The finding suggests local environmental conditions play a key role in secondary metabolite production, influencing the discovery of drugs and other useful compounds. Credit: Tomás Allen Rush/ORNL, U.S. Dept. of Energy.

Scientists at ORNL and the University of Wisconsin–Madison have discovered that genetically distinct populations within the same species of fungi can produce unique mixes of secondary metabolites, which are organic compounds with applications in

ORNL’s Josh Michener, a microbiologist and metabolic engineer, led the discovery of a useful new enzyme that breaks down stubborn bonds in lignin, a polymer found in plants that typically becomes waste during bioconversion. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

In a step toward increasing the cost-effectiveness of renewable biofuels and bioproducts, scientists at ORNL discovered a microbial enzyme that degrades tough-to-break bonds in lignin, a waste product of biorefineries.

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy

An ORNL-led team comprising researchers from multiple DOE national laboratories is using artificial intelligence and computational screening techniques – in combination with experimental validation – to identify and design five promising drug therapy approaches to target the SARS-CoV-2 virus.