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Current Affairs

Bacterial biofilms have memory similar to neurons

Date: 29 April 2020 Tags: Biotechnology


Researchers have used light to imprint a 'memory' on a bacterial biofilm and discovered that the microbes acted surprisingly similarly to neurons.



Bacteria aren't well known for their smarts. They grow, they adapt, and they grow some more, but we don't usually catch them remembering things.



  • Simple bacteria can encode memory at the level of their cellular membrane potential, which is similar to the memory process of neurons in the brain.

  • When neurons 'fire' in our brains, ions flood into the tiny gap between nerve cells, telling the next neuron that a message has been received, and triggering it to continue passing on that message.

  • The flood of ions produces a cellular membrane potential, a difference in electrical charge between the inside and outside of the cell. Pretty much all living things use this phenomenon to power mechanisms in the cellular membrane and to transmit signals between different areas of the body.

  • In neurons, this change in cellular membrane potential is known to be involved in the process of memory formation; now, it seems that something similar can happen in biofilms.

  • Bacteria that were exposed to light, persistently exhibited a different membrane potential compared to those bacteria that were not exposed, thus it was clear that these bacteria 'remembered' being exposed to light.

  • The team looked at a simple bacterial species called grass bacillus (Bacillus subtilis) and gave them a five second blast of blue light from a laser.

  • They found this light causes a change in the membrane potential, with ions constantly flooding out of the cell, and then back in again. This effect stuck around for several hours after the light exposure.

  • Because the bacteria had been genetically engineered to fluoresce when the concentration of membrane potential reporter thioflavin-T rises, the research team was able to physically watch the biofilm as it pulsed.

  • The current team of researchers hopes that they may be able to use their findings for biological computation and synthetic biology, but that's a long way off yet.