Georgia’s saltwater marshes — living where the land meets the ocean — stretch along the state’s entire 100-mile coastline. These rich ecosystems are largely dominated by just one plant: grass.

Known as cordgrass, the plant is an ecosystem engineer, providing habitats for wildlife, naturally cleaning water as it moves from inland to the sea, and holding the shoreline together so it doesn’t collapse. Cordgrass even protects human communities from tidal surges.

Understanding how these plants stay healthy is of crucial ecological importance. For example, one known plant stressor prevalent in marsh soils is the dissolved sulfur compound, sulfide, which is produced and consumed by bacteria. But while the Georgia coastline boasts a rich tradition of ecological research, understanding the nuanced ways bacteria interact with plants in these ecosystems has been elusive. Thanks to recent advances in genomic technology, Georgia Tech biologists have begun to reveal never-before-seen ecological processes.

The team’s work was published in Nature Communications. 

Joel Kostka, the Tom and Marie Patton Distinguished Professor and associate chair for Research in the School of Biological Sciences, and Jose Luis Rolando, a postdoctoral fellow, set out to investigate the relationship between the cordgrass Spartina alterniflora and the microbial communities that inhabit their roots, identifying the bacteria and their roles.

“Just like humans have gut microbes that keep us healthy, plants depend on microbes in their tissues for health, immunity, metabolism, and nutrient uptake,” Kostka said. “While we’ve known about the reactions that drive nutrient and carbon cycling in the marsh for a long time, there’s not as much data on the role of microbes in ecosystem functioning.”

Out in the Marsh

A major way that plants get their nutrients is through nitrogen fixation, a process in which bacteria convert nitrogen into a form that plants can use. In marshes, this role has mostly been attributed to heterotrophs, or bacteria that grow and get their energy from organic carbon. Bacteria that consume the plant toxin sulfide are chemoautotrophs, using energy from sulfide oxidation to fuel the uptake of carbon dioxide to make their own organic carbon for growth.

“Through previous work, we knew that Spartina alterniflora has sulfur bacteria in its roots and that there are two types: sulfur-oxidizing bacteria, which use sulfide as an energy source, and sulfate reducers, which respire sulfate and produce sulfide, a known toxin for plants,” Rolando said. “We wanted to know more about the role these different sulfur bacteria play in the nitrogen cycle.”

Kostka and Rolando headed to Sapelo Island, Georgia, where they have regularly conducted fieldwork in the salt marshes. Wading into the marsh, shovels and buckets in hand, the researchers and their students collected cordgrass along with the muddy sediment samples that cling to their roots. Back at the field lab, the team gathered around a basin filled with creek water and carefully washed the grass, gently separating the plant roots.

Next, they used a special technique involving heavier versions of chemical elements that occur in nature as tracers to track the microbial processes. They also analyzed the DNA and RNA of the microbes living in different compartments of the plants.

Using a sequencing technology known as shotgun metagenomics, they were able to retrieve the DNA from the whole microbial community and reconstruct genomes from newly discovered organisms. Similarly, untargeted RNA sequencing of the microbial community allowed them to assess which microbial species and specific functions were active in close association with plant roots.

Using this combination of techniques, they found that chemoautotrophic sulfur-oxidizing bacteria were also involved in nitrogen fixation. Not only did these bacteria help plants by detoxifying the root zone, but they also played a crucial role in providing nitrogen to the plants. This dual role of the bacteria in sulfur cycling and nitrogen fixation highlights their importance in coastal ecosystems and their contribution to plant health and growth.

"Plants growing in areas with high levels of sulfide accumulation tend to be smaller and less healthy," said Rolando. "However, we found that the microbial communities within Spartina roots help to detoxify the sulfide, enhancing plant health and resilience."

Local to Global Significance

Cordgrasses aren’t just the main player in Georgia marshes; they also dominate marsh landscapes across the entire Southeast, including the Carolinas and the Gulf Coast. Moreover, the researchers found that the same bacteria are associated with cordgrass, mangrove, and seagrass roots in coastal ecosystems across the planet.

"Much of the shoreline in tropical and temperate climates is covered by coastal wetlands,” Rolando said. “These areas likely harbor similar microbial symbioses, which means that these interactions impact ecosystem functioning on a global scale."  

Looking ahead, the researchers plan to further explore the details of how marsh plants and microbes exchange nitrogen and carbon, using state-of-the-art microscopy techniques coupled with ultra-high-resolution mass spectrometry to confirm their findings at the single-cell level.

"Science follows technology, and we were excited to use the latest genomic methods to see which types of bacteria were there and active,” Kostka said. “There's still much to learn about the intricate relationships between plants and microbes in coastal ecosystems, and we are beginning to uncover the extent of the microbial complexity that keeps marshes healthy.”

Citation: Rolando, J.L., Kolton, M., Song, T. et al. Sulfur oxidation and reduction are coupled to nitrogen fixation in the roots of the salt marsh foundation plant Spartina alterniflora. Nat Commun 15, 3607 (2024).

DOI: https://doi.org/10.1038/s41467-024-47646-1

Funding: This work was supported in part by an institutional grant (NA18OAR4170084) to the Georgia Sea Grant College Program from the National Sea Grant Office, National Oceanic and Atmospheric Administration, US Department of Commerce, and by a grant from the National Science Foundation (DEB 1754756).

When looking for an environmentally friendly and cost-effective way to clean up contaminated water and soil, Georgia Tech researchers Patricia Stathatou and Christos Athanasiou turned to yeast. A cheap byproduct from fermentation processes — e.g., something your local brewery discards in mass quantities after making a batch of beer — yeast is widely known as an effective biosorbent. Biosorption is a mass transfer process by which an ion or molecule binds to inactive biological materials through physicochemical interactions.

When they initially studied this process, Stathatou and Athanasiou found that yeast can effectively and rapidly remove trace lead — at challenging initial concentrations below one part per million — from drinking water. Conventional water treatment methods either fail to eliminate lead at these low levels or result in high financial and environmental costs to do so. In a paper published today in RSC Sustainability, the researchers show how this process can be scaled.

“If you put yeast directly into water to clean it, you will need an additional treatment step to remove the yeast from the water afterward,” said Stathatou, a research scientist at the Renewable Bioproducts Institute and an incoming assistant professor at the School of Chemical and Biomolecular Engineering. “To implement this process at scale without requiring additional separation steps, the yeast cells need a housing.”

“Additionally, because yeast is abundant— in some cases, brewers even pay companies to haul it away as a waste byproduct — this process gives the yeast a second life,” said Athanasiou, an assistant professor in the Daniel Guggenheim School of Aerospace Engineering. “It’s a plentiful low, or even negative, value resource, making this purification process inexpensive and scalable.”

To develop a housing for the yeast, Stathatou and Athanasiou partnered with MIT chemical engineers Devashish Gokhale and Patrick S. Doyle. Gokhale and Stathatou are the lead authors of this new study that demonstrates the yeast water purification process’s scalability.

“We decided to make these hollow capsules— analogous to a multivitamin pill — but instead of filling them up with vitamins, we fill them up with yeast cells,” Gokhale said. “These capsules are porous, so the water can go into the capsules and the yeast are able to bind all of that lead, but the yeast themselves can’t escape into the water.”

The yeast-laden capsules are sufficiently large, about half a millimeter in diameter, for easy separation from water by gravity. This means they can be used to make packed-bed bioreactors or biofilters, with contaminated water flowing through these hydrogel-encased yeast cells and coming out clean.

Stathatou and Athanasiou envision using these hydrogel yeast capsules in small biofilters consumers can put on their kitchen faucets, or biofilters large enough to fit municipal or industrial wastewater treatment systems. But to enable such scalability, the yeast-laden capsules’ ability to withstand the force generated by water flowing inside such systems needed to be studied as well.

To determine this, Athanasiou tested the capsules’ mechanical robustness, which is how strong and sturdy they are in the presence of waterflow forces. He found they can withstand forces like those generated by water running from a faucet, or even flows like those in water treatment plants that serve a few hundred homes. “In previous attempts to scale up biosorption with similar approaches, lack of mechanical robustness has been a common cause of failure,” Athanasiou said. “We wanted to make sure our work addressed this issue from the very beginning to ensure scalability.”

“After assessing the mechanical robustness of the yeast-laden capsules, we made a prototype biofilter using a 10-ml syringe,” Stathatou explained. “The initial lead concentration of water entering the biofilter was 100 parts per billion; we demonstrated that the biofilter could treat the contaminated water, meeting EPA drinking water guidelines, while operating continuously for 12 days.”

The researchers hope to identify ways to isolate and collect specific contaminants left behind in the filtering yeast, so those too can be used for other purposes.

“Apart from lead, which is widely used in systems for energy generation and storage, this process could be used to remove and recover other metals and rare earth elements as well,” Athanasiou said. “This process could even be useful in space mining or other space applications.”

They also would like to find a way to keep reusing the yeast. “But even if we can’t reuse yeast indefinitely, it is biodegradable,” Stathatou noted. “It doesn’t need to be put into an industrial composter or sent to a landfill. It can be left on the ground, and the yeast will naturally decompose over time, contributing to nutrient cycling.”

This circular approach aims to reduce waste and environmental impact, while also creating economic opportunities in local communities. Despite numerous lead contamination incidents across the U.S., the team’s successful biosorption method notably could benefit low-income areas historically burdened by pollution and limited access to clean water, offering a cost-effective remediation solution. “We think there’s an interesting environmental justice aspect to this, especially when you start with something as low-cost and sustainable as yeast, which is essentially available anywhere,” Gokhale says.

Moving forward, Stathatou and Athanasiou are exploring other uses for their hydrogel-yeast purification method. The researchers are optimistic that, with modifications, this process can be used to remove additional inorganic and organic contaminants of emerging concern, such as PFAS — or “forever” chemicals — from the water or the ground.

Citation: Devashish Gokhale, Patritsia M. Stathatou, Christos E. Athanasiou, and Patrick S. Doyle, “Yeast-laden Hydrogel Capsules for Scalable Trace Lead Removal from Water,” RSC Sustainability. 

DOI: https://doi.org/10.1039/D4SU00052H

Funding: Patricia Stathatou was supported by funding from the Renewable Bioproducts Institute at Georgia Tech. Devashish Gokhale was supported by the Rasikbhai L. Meswani Fellowship for Water Solutions and the MIT Abdul Latif Jameel Water and Food Systems Lab (J-WAFS).

Georgia Tech researcher Jie He set out to predict how rainfall will change as Earth’s atmosphere continues to heat up. In the process,  he made some unexpected discoveries that might explain how greenhouse gas emissions will impact tropical oceans, affecting climate on a global scale.

“This is not a story with just one punch line,” said He, assistant professor in Georgia Tech’s School of Earth and Atmospheric Sciences, whose most recent work appeared in the journal Nature Climate Change. “I didn’t really expect to find anything this interesting—there were a few surprises.”

He is principal investigator of the Climate Modeling and Dynamics Group, which combines expertise in physics, mathematics, and computer science to study climate change. The team’s latest study, a collaboration with Mississippi State University and Princeton University, examines hydrological sensitivity in the planet’s three tropical basins: the central portions of both the Pacific and Atlantic oceans and most of the Indian Ocean, an equatorial belt girding the Earth between the Tropic of Cancer (north) and Tropic of Capricorn (south).

Hydrological sensitivity (HS) refers to the precipitation change per degree of surface warming. Hydrological sensitivity is a key metric researchers use in evaluating or predicting how rainfall will respond to future climate change. Positive HS indicates a wetter climate, while negative HS indicates a drier climate.

“The projection of hydrological sensitivity and future precipitation has been widely investigated, but most studies look at global averages — nobody had yet looked closely at each individual basin,” He said. “And the real impact on global climate change will come from the regional scale.”

In other words, what happens in tropical waters has far-reaching effects.

Long Reach of the Tropics

He wanted to specifically examine the tropical basins because they already have a well-known influence on remote locations: El Niños and La Niñas. These weather patterns that shift every couple of years are examples of tropical oceanic precipitation changes that have a global impact.

“These precipitation changes create heating and cooling in the atmosphere that set off atmospheric waves affecting remote climates across the globe,” He said. During El Niño winters, for example, the southeastern U.S. typically gets more precipitation than usual.

But El Niños and La Niñas are naturally occurring, whereas the tropical precipitation changes He identified are projected as outcomes of human-induced global warming — a simulation, part of a climate model.

Climate models are an essential tool for He and other researchers, who use them to simulate possible future scenarios. These are computer programs that rely on complex math equations to project the atmospheric interactions of energy and matter likely to occur across the planet.

What surprised He was the substantial difference in HS between tropical basins. Essentially, in He’s model the Pacific tropical basin has an HS more than twice as large as the Indian basin, with the Atlantic basin projected as a negative value.

“It was surprising because these differences can’t be explained by the mainstream theories on tropical precipitation changes,” He said. “In other words, none of the theories we knew would have predicted it.”

Modeling the Sensitive Future

The effects of such diverging hydrological sensitivity would be widespread, according to He. For example, his experiments suggest that the continental U.S. will get wetter, and the Amazon will become drier.

“If these model projections are true, these effects will materialize as the climate continues to warm,” said He, who can’t predict exactly how long it will be before these effects can be detected in actual observations of our three-dimensional world.

That’s because they only have reliable observations of oceanic tropical precipitation since 1979. Precipitation changes over decades are strongly affected by internal climate variability — that is, climate change that isn’t caused by humans. When human-induced precipitation changes are significantly greater than internal climate variability, we should be able to detect the wide-ranging effects of diverging hydrological sensitivity.

But the challenges of continuing climate change do not allow the luxury of waiting until every aspect of climate projection becomes a reality, He noted, adding, “We are relying on climate projections to some extent to guide our adaptation and mitigation plans. Therefore, it is important to study and understand the climate projections.”

Based on the scenario projected by climate models used in He’s research, the effects of El Niños and La Niñas on remote climates will become stronger.

“What we can imply is that this strengthening would be partly due to the diverging HS among tropical basins,” He concluded.

While the future effects of HS on El Niños and La Niñas weren’t discussed in this study, He believes it would make a very interesting research subject going forward.

To avoid catastrophic climate impacts, excessive carbon emissions must be addressed. At this point, cutting emissions isn’t enough. Direct air capture, a technology that pulls carbon dioxide out of ambient air, has great potential to help solve the problem.

But there’s a big challenge. For direct air capture technology, every type of environment and location requires a uniquely specific design. A direct air capture configuration in Texas, for example, would necessarily be different from one in Iceland. These systems must be designed with exact parameters for humidity, temperature, and air flows for each place.

Now, Georgia Tech and Meta have collaborated to produce a massive database, potentially making it easier and faster to design and implement direct air capture technologies. The open-source database enabled the team to train an AI model that is orders of magnitude faster than existing chemistry simulations. The project, named OpenDAC, could accelerate climate solutions the planet desperately needs.

The team’s research was published in ACS Central Science, a journal of the American Chemical Society.

“For direct air capture, there are many ideas about how best to take advantage of the air flows and temperature swings of a given environment,” said Andrew J. Medford, associate professor in the School of Chemical and Biomolecular Engineering (ChBE) and a lead author of the paper. “But a major problem is finding a material that can capture carbon efficiently under each environment’s specific conditions.”

Their idea was to “create a database and a set of tools to help engineers broadly, who need to find the right material that can work,” Medford said. “We wanted to use computing to take them from not knowing where to start to giving them a robust list of materials to synthesize and try.”

Containing reaction data for 8,400 different materials and powered by nearly 40 million quantum mechanics calculations, the team believes it’s the largest and most robust dataset of its kind.

Building a Partnership (and a Database)

Researchers with Meta’s Fundamental AI Research (FAIR) team were looking for ways to harness their machine learning prowess to address climate change. They landed on direct air capture as a promising technology and needed to find a partner with expertise in materials chemistry as it relates to carbon capture. They went straight to Georgia Tech.

David Sholl, ChBE professor, Cecile L. and David I.J. Wang Faculty Fellow, and director of Oak Ridge National Laboratory’s Transformational Decarbonization Initiative, is one of the world’s top experts in metal-organic frameworks (MOFs). These are a class of materials promising for direct air capture because of their cagelike structure and proven ability to attract and trap carbon dioxide. Sholl brought Medford, who specializes in applying machine learning models to atomistic and quantum mechanical simulations as they relate to chemistry, into the project.

Sholl, Medford, and their students provided all the inputs for the database. Because the database predicts the MOF interactions and the energy output of those interactions, considerable information was required.

They needed to know the structure of nearly every known MOF — both the MOF structure by itself and the structure of the MOF interacting with carbon dioxide and water molecules.

“To predict what a material might do, you need to know where every single atom is and what its chemical element is,” Medford said. “Figuring out the inputs for the database was half of the problem, and that’s where our Georgia Tech team brought the core expertise.”

The team took advantage of large collections of MOF structures that Sholl and his collaborators had previously developed. They also created a large collection of structures that included imperfections found in practical materials.

The Power of Machine Learning

Anuroop Sriram, research engineering lead at FAIR and first author on the paper, generated the database by running quantum chemistry computations on the inputs provided by the Georgia Tech team. These calculations used about 400 million CPU hours, which is hundreds of times more computing than the average academic computing lab can do in a year.

FAIR also trained machine learning models on the database. Once trained on the 40 million calculations, the machine learning models were able to accurately predict how the thousands of MOFs would interact with carbon dioxide.

The team demonstrated that their AI models are powerful new tools for material discovery, offering comparable accuracy to traditional quantum chemistry calculations while being much faster. These features will allow other researchers to extend the work to explore many other MOFs in the future.

“Our goal was to look at the set of all known MOFs and find those that most strongly attract carbon dioxide while not attracting other air components like water vapor, and using these highly accurate quantum computations to do so,” Sriram said. “To our knowledge, this is something no other carbon capture database has been able to do.”

Putting their own database to use, the Georgia Tech and Meta teams identified about 241 MOFs of exceptionally high potential for direct air capture.

Moving Forward With Impact

“According to the UN and most industrialized countries, we need to get to net-zero carbon dioxide emissions by 2050,” said Matt Uyttendaele, director of Meta’s FAIR chemistry team and a co-author on the paper. “Most of that must happen by outright stopping carbon emissions, but we must also address historical carbon emissions and sectors of the economy that are very hard to decarbonize — such as aviation and heavy industry. That’s why CO2 removal technologies like direct air capture must come online in the next 25 years.” 

While direct air capture is still a nascent field, the researchers say it’s crucial that groundbreaking tools — like the OpenDAC database made available in the team’s paper — are in development now. 

“There is not going to be one solution that will get us to net-zero emissions,” Sriram said. “Direct air capture has great potential but needs to be scaled up significantly before we can make a real impact. I think the only way we can get there is by finding better materials.”

The researchers from both teams hope the scientific community will join the search for suitable materials. The entire OpenDAC dataset project is open source, from the data to the models to the algorithms.

“I hope this accelerates the development of negative-emission technologies like direct air capture that may not have been possible otherwise,” Medford said. “As a species, we must solve this problem at some point. I hope this work can contribute to getting us there, and I think it has a real shot at doing that.”

Note: Georgia Tech ChBE graduate students Sihoon Choi, Logan Brabson, and Xiaohan Yu made major contributions and are co-authors of the paper.

Citation: A. Sriram et al, The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture, ACS Central Science (2024).

DOI: https://doi.org/10.1021/acscentsci.3c01629

The latest episode of the Generating Buzz podcast follows the College of Sciences’ Frontiers in Science event, giving listeners an opportunity to hear from experts, including dean and renowned oceanographer Susan Lozier, Associate Professor Alex Robel, Professor Valerie Thomas, and Associate Vice President of Sustainability Jennifer Chirico as they explore the intersection of science, policy, and human nature. April is Earth Month, and according to the National Oceanic and Atmospheric Administration, 2023 was the warmest year on record for our planet. As the global conversation around the climate and humans’ effect on it continues, Georgia Tech researchers are taking a leading role in quantifying the issues posed by climate change and crafting solutions for the road ahead.