A new computer model of blue-green algae can predict which of the organism's genes are central to capturing energy from sunlight and other critical processes.
Described in a paper published in the journal Molecular BioSystems, the model could advance efforts to produce biofuel and other energy sources from blue-green algae, known as cyanobacteria. Researchers from the Department of Energy's Pacific Northwest National Laboratory, Washington University in St. Louis and Purdue University developed the model, which was made for the single-celled marine cyanobacterium Cyanothece 51142.
"Our model is the first of its kind for cyanobacteria," said the paper's lead author, PNNL computational biologist Jason McDermott. "Previous models have only zoomed in on specific aspects of cyanobacteria. Ours looks at the entire organism to find out what makes Cyanothece tick."
The research was funded by EMSL, the Department of Energy's Environmental Molecular Sciences Laboratory, a national user facility at PNNL, as part of EMSL's Membrane Biology Grand Challenge. The challenge encouraged scientists to take a systems biology approach to understand the network of genes and proteins that are responsible for photosynthesis and nitrogen fixation in cyanobacteria.
Cyanobacteria are noteworthy because they share qualities with both plants and microbes. They use the sun's energy to make sugar via photosynthesis like plants. And, like microbes, cyanobacteria also convert atmospheric nitrogen an important nutrient for many organisms into accessible forms, a process called nitrogen fixation.
Working day and night
Many cyanobacteria physically separate their photosynthetic and nitrogen fixation activities in different cells. But Cyanothece is unusual because the same cell switches between these functions every 12 hours. It makes sugar when there's daylight and then spends the night breaking down that sugar to fix nitrogen and to produce other compounds.
"By understanding which genes trigger Cyanothece to start and stop photosynthesis and other important energy production functions, we may be able to better use cyanobacteria to make renewable energy," McDermott said. Genes serve as the blueprint for the creation of proteins, the cell's workers.
Mapping a gene's purpose
Researchers many of whom also worked on the model sequenced Cyanothece's genome in 2008. But knowing how many genes an organism has doesn't necessarily explain what those genes do. So scientists kept studying Cyanothece in the lab. By making a simple linear graph of when different genes were expressed over a 24-hour cycle, McDermott and his co-authors saw that many genes were expressed at similar levels and at similar times. The team hypothesized that such genes were involved in similar processes, such as photosynthesis or nitrogen fixation.
But there isn't always a straight line between one gene being turned on and a cellular process starting. Sometimes a series of genes have to be turned on or off before a process can begin. To better understand these complex relationships, McDermott crafted a circular graph that illustrates how genes are expressed around the clock. Each point on the graph represented a gene being expressed at a particular time. Lines connecting the dots demonstrated how some related genes are expressed one after another in a series.
Points of control
The wreath-like graph revealed a complicated, intertwined network of Cyanothece genes. In some cases, different series of related genes expressed one after another intersected at the same place, at an individual gene or a handful of genes. It appeared that the genes at these intersections serve as bottlenecks, or control points, for the subsequent expression of other genes down the road. The team predicted that if the bottleneck genes were removed, expression of the downstream genes would be affected. Amazingly, 11 of the 25 top bottlenecks identified were genes or proteins whose specific role in Cyanothece weren't previously known.
The next challenge was to figure out how each of these bottlenecks affects Cyanothece's daily life. The team could have done experiments in the lab, removing each of these bottlenecks one at the time from the organism's genome to see what happened. But such experiments can be time-consuming. Seeking a simpler, more methodical solution, the authors built a computer model that would predict the roles of individual genes in Cyanothece.
They started with a previous whole-organism modeling approach called the Inferelator, which was developed at the Institute for Systems Biology in Seattle for a different microorganism. The team adapted the Inferelator's code to compute the cyclic nature of the connections between Cyanothece's genes. They also added code to improve their ability to test the model's accuracy. When looking at low-oxygen conditions similar to those encountered by Cyanothece at night, the model predicted gene expression levels correctly the equivalent of about 75 percent of the time, in comparison to actual measurements.
The model predicted the roles that a number of bottleneck genes play for Cyanothece. For example, the model predicted that the patB gene is a bottleneck for the production of nitrogenase, the enzyme needed to fix nitrogen. If patB were removed from Cyanothece, the model predicted that nitrogenase production could decrease by as much as 80 percent. The model also identified an unnamed gene, currently labeled as gene cce_0678, as being key to the cyanobacterium's production of RuBisCO, a well-known enzyme that's important in photosynthesis. Without cce_0678, the model predicted RuBisCO production would decrease by about 60 percent.
Next, the research team will seek to further validate the model with lab experiments. They'll remove or increase the expression of specific genes predicted to be bottlenecks to test whether or not they impact Cyanothece's energy production as the model predicted. The researchers will also use the model to examine the complex interactions between important processes in cyanobacteria, such as photosynthesis and nitrogen fixation.
"This model can serve as a first step toward a complete simulation of Cyanothece," McDermott said. "Knowing the detailed inner workings of cyanobacteria could be used to design efficient methods to make bioenergy and manage the carbon cycle, including the greenhouse gas carbon dioxide."
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Jason E. McDermott, Christopher S. Oehmen, Lee Ann McCue, Eric Hill, Daniel M. Choi, Jana Stöckel, Michelle Liberton, Himadri B. Pakrasi and Louis A. Sherman, A model of cyclic transcriptomic behavior in the cyanobacterium Cyanothece sp. ATCC 51142, Molecular BioSystems, published online June 23, 2011, DOI: 10.1039/C1MB05006K