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Putting bacteria to work

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Posted July 23, 2018

The idea of bacteria as diverse, complex perceptive entities that can hunt prey in packs, remember past experiences and interact with the moods and perceptions of their human hosts sounds like the plot of some low-budget science fiction movie. But these are exactly some of the traits that scientists attribute to “bacterial cognition,” which treats the microscopic creatures as something like information processing systems.

Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory and the University of Illinois at Chicago are finding new computational ways to describe bacterial cognition, a concept that emerged in the 1940s. These methods enable scientists to quantitatively measure how bacteria collect information, store that information and use it to interact with their environments.

This sulfur regulome of P. fluorescens SBW25 shows a set of sensors, transcription factors and regulated genes. Circles represent chemoinformatic features of nutrients, diamonds represent transcription factors and rounded rectangles represent groups of genes. (Image by Argonne National Laboratory.)

“If we can describe information in these systems in the same ways that we would describe the internet or cryptography or cell phone networks, then we could use tools not previously considered for biology to answer questions that we could not previously address,” said Peter Larsen, a computational biologist in Argonne’s biosciences division. Larsen and his co-authors recently reported their findings in mSystems, a journal of the American Society for Microbiology.

“If we can describe information in these systems in the same ways that would describe the internet or cryptography or cell phone networks, then we could use tools not previously considered for biology to answer questions that we could not previously address.”
— Peter Larsen, computational biologist at Argonne

The work provides new insights that will be required to engineer exotic strains of bacteria for bio-manufacturing. The U.S. bio-economy is valued at an estimated $250 billion annually. The Argonne scientists intend to translate their findings into a comprehensive information model that can be used to computationally predict what combination of nutrients could optimally induce a metabolic pathway of industrial interest.

“Engineering a bacterium to perform a function is difficult — they’re slippery little guys,” Larsen said. “You make a change and then there’s this huge cascade of consequences that you just can’t accommodate in the standard reductionist model.”

The reductionist model, which views complex phenomena in terms of their basic parts, considers bacteria as a collection of chemical reactions seeking to attain dynamic equilibrium with their environment.

“That description frankly doesn’t describe most of the really interesting things that bacteria do,” Larsen said. They explore their surroundings and interact with each other and with other bacterial communities to change their environment. To understand how they do these things, “we have to look at their information-processing capacities,” he said.

The researchers focused on Pseudomonas fluorescens, a soil bacterium that colonizes roots and protects plants from various nutrient stresses and pathogens. Previous Argonne experiments have shown that even closely related species of Pseudomonad bacteria affect plants in dramatically different ways when nutrient deficiencies are introduced. The bacteria can change the concentration of stress hormones in plant tissue, the amount of chlorophyll in leaves and the quantity of biomass the plants generate above and below ground.

Source: ANL

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