Research Will Study How Diversity Helps Microbial Communities Respond to Change
At Lake Eufaula in Georgia, Georgia Tech researchers are studying how complex microbial systems use their genetic diversity to respond to human-induced perturbations. They are focusing on man-made lakes located along the Chattahoochee River, such as Lake Lanier and Lake Eufaula. (Georgia Tech Photo courtesy of Kostas Konstantinidis and Despina Tsementzi)
Researchers at the Georgia Institute of Technology have received a five-year, $1.8 million grant from the National Science Foundation (NSF) to study how complex microbial systems use their genetic diversity to respond to human-induced change. The work is important because these microbial communities play critical roles in the environment, breaking down pollutants, recycling nutrients – and serving as major sources of nitrogen and carbon.
Despite the importance of the microbes, relatively few among the thousands of species that make up a typical microbial community have been studied extensively. The relatively unknown organisms within these communities may have genes that could help address critical environmental, energy and other challenges.
“We are all dependent on these microbes,” said Kostas Konstantinidis, an assistant professor in Georgia Tech’s School of Civil and Environmental Engineering and the grant’s principal investigator. “There are many different species and a huge amount of diversity out there. This project will allow us to look at the details of how this diversity is generated, how redundant it is and how these microbes are changing in response to perturbations in the environment.”
The funding, from the NSF’s “Dimensions of Biodiversity” program, will support a collaborative effort involving Konstantinidis and two other Georgia Tech researchers: Eberhardt Voit and Jim Spain. Voit holds the David D. Flanagan Chair in Biological Systems within the Department of Biomedical Engineering at Georgia Tech and Emory University, and is a Georgia Research Alliance Eminent Scholar. Spain is a professor in the School of Civil and Environmental Engineering.
The research will initially focus on Lake Lanier, a large man-made lake located near Atlanta. Beyond the experimental work, the research will involve extensive mathematical modeling of the complex microbial communities.
“We want to see how the microbial communities of the lake change over time, and how the perturbations affect that,” said Konstantinidis, who holds the Carlton S. Wilder Chair in Environmental Engineering at Georgia Tech. “We then want to extend our understanding to other ecosystems, such as the Gulf of Mexico.”
The researchers will set up mesocosms – bioreactors – in the laboratory with microbial populations from Lake Lanier. They will feed these populations pollutants such as hydrocarbons, antibiotics and pesticides to see how they respond and how they deal with compounds to which they may not have been exposed.
“Sometimes they may not have the genes to break down the pollutants and may not encode the right enzymes,” Konstantinidis said. “But if you give them enough time, these microbes somehow innovate. We want to understand the genetic mechanisms that allow the microbes to break down a compound that they are seeing for the first time.”
The grant will allow the Georgia Tech researchers to expand knowledge of “rare” microbes, largely unknown organisms that may harbor useful genes.
“We think these unusual microbes may be the key ones,” Konstantinidis said. “Though they may be low in abundance, the whole community may depend on them. When you have a new pollutant, these rare microbes may become more important by providing the genetic diversity needed.”
Extending this understanding will be challenging, however, because few species can be cultured in the laboratory. That difficulty is leading Konstantinidis and his team to develop new tools that allow studying the organisms in the field, without culturing them under laboratory settings. Addressing those challenges may lead to the creation of additional techniques that could benefit other areas of biology, engineering and medicine.
“One of the most common techniques is to take the microbial DNA and decode it,” he explained. “From the DNA, we can tell what the organism is and what it may be doing in the environment.”
But studying DNA brings another set of challenges. The genes are rarely recovered intact based on these genomic techniques, and frequently include only part of the genome or are contaminated by DNA from other species.
“Bioinformatics is a big issue for us, because that is how we can put the pieces together,” Konstantinidis explained. “We have to make sense of pieces of DNA from perhaps thousands of organisms. This is where biology, computing and engineering are merging to find clever ways to accomplish such tasks.”
Part of investigating how the microbial community responds to change will include assessing the effects of rising temperatures. Will global climate change cause increased respiration among the microbes and therefore boost carbon dioxide output, or will temperature change lead the organisms to store carbon, pulling CO2 out of the atmosphere?
“A big part of the scientific community is working on questions like this to get a better understanding and better model of how microbial systems will respond,” Konstantinidis said.
Modeling will be important to understand not only how microbial communities will respond to broad climate changes, but also how they might react to such dramatic perturbations as large oil spills.
“From small experiments in the lab, the goal is to eventually model whole ecosystems – how Lake Lanier works or how the Gulf of Mexico works in terms of the microbes that are there,” he said. “We want to have a more predictive model of how these communities that are so diverse will respond to a perturbation like an oil spill or rising tempeartures. With so many thousands of organisms from different species, we need modeling to put it all together.”
This research has been supported by the National Science Foundation (NSF) under grant DEB-1241046 . The content of this article is solely the responsibility of the authors and does not necessarily represent the official views of the NSF.
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