Doing more with less: Efficient experiments for bacterial engineering
Shewanella oneidensis is a bacterium known for its ability to break down heavy metals and make them less soluble in groundwater. If scientists could engineer the organism in certain ways, it could be used in a variety of environmental and biofuel applications, such as microbial fuel cells.
However, like many bacteria that are fairly recent discoveries, Shewanella's genome has been sequenced, but its actual metabolic behaviors are not well understood. This information is critical to engineer the organism for biotechnology applications, but doing so via traditional experimental approaches would take a very long time.
Chemical and Biological Engineering Assistant Professor Jennifer Reed has received a National Science Foundation Faculty Early Career Development Award (CAREER) grant to design and conduct new experiments that will more quickly reveal answers about the metabolism of organisms like Shewanella.
Researchers use computational models of organisms like Escherichia coli (E. coli) to predict how that organism will behave in certain conditions. They then conduct experiments, and if the predictions don't match the results, they tweak the model and test again. E. coli is studied by a large community of scientists, meaning there is an extensive amount of data to help researchers improve their models. These accurate models allow researchers to design bacteria strains with more desirable behaviors.
The same volume of data doesn't exist for other organisms, like Shewanella, and Reed hopes that more efficiency during the modeling and experimental processes will help make up the difference.
"We're trying to essentially do more with less," she says. "We want to do fewer experiments and get more information out of the experiments we do."
Reed is looking at how to design new experiments that can best test model predictions. She then will study how to automate the process of refining the models by evaluating discrepancies found between model predictions and experiments.
Say for example that an experiment uncovers an error in the researcher's assumption about a metabolic process. Instead of altering one gene's regulation in the model and then performing another experiment to see if that particular solution solves the problem, Reed's approach will allow researchers to test multiple options and combinations of options at once.
"We can quickly figure out how the change not only affects one experiment but also 10 to 15 experiments," she says.
For the CAREER award, Reed will look at two strains of Shewanella. "The interesting thing about this organism is it can take electrons from the carbon source it's growing on and put them on electrodes," she says.
Once she develops the models, Reed will determine what experiments should be done to learn more about how the organism uses its metabolism as well as how its cells regulate the expression of metabolic enzymes. "This will lead to a better understanding of cellular behavior," she says.
That better understanding could in turn allow other researchers to optimize Shewanella's ability to interact with electrodes to generate products like ethanol. Eventually, the bacteria could be used in microbical fuel cells.
A portion of every CAREER award is dedicated to outreach activities, and with her award Reed aims to encourage female students interested in engineering. She is an active presence at state high school science fairs, and she also will develop a group for female chemical and biological engineering graduate students at UW-Madison. The group will help the students connect with each other and with professionals in academia and industry.
Reed also plans to expand access to microbial modeling via an open website. She already provides computer code for free to people interested in learning how to use bacterial models and run simulations. The CAREER award will allow Reed to develop multimedia components and additional content to make model approaches more accessible to students, researchers and educators.