Breaking down the microbiology world one bite at a time
Smart slime – memory without a nervous system.
Slime molds are fascinating. They were originally classified as a fungus (hence the name slime mold) but were later grouped within the Protista kingdom. A protist is a eukaryotic organism (the cells contain a nucleus) that is neither an animal, plant, nor fungus. Slime molds are unique: they reside at the crossroad between the plant, animal, and fungus kingdoms and give us an insight into the early evolutionary history of eukaryotes.
The slime mold Physarum polycephalum (or ‘the many-headed slime’, a.k.a. “The Blob“) has been studied extensively in the lab. Their body is one big cell, consisting of ‘tubes’ that form an intricate network that can stretch for centimeters, or even, meters! They can be found in damp, shady habitats like forest floors or (dead) bark of trees. But P. polycephalum captures interest because of something else. They seem able to memorize information about (past) food availability, a trait that is generally linked to organisms with a nervous system (cognition). In addition, they can find the shortest way in a maze by continually arranging their tube-body. Recently, it has even been launched into space to investigate how microgravity affects its behavior!
Normally species without a nervous system can encode some form of memory with alternative strategies including epigenetics, cell memory during chemotaxis, and tunable circadian clocks (can bacteria tell the time? read it in this article). These actions take at least half an hour, if not a full day to take place, only allowing for ‘slow decisions’. However, P. polycephalum seems to make decisions within 10-20 minutes to solve complex problems alluding to an unknown alternative strategy.
In a recent study, Mirna Kramar and Karen Alim studied how the slime mold pulled this off. Specifically, they investigated how the location of a nutrient source is encoded within the morphology of the network. They introduced a nutrient source close to the slime mold and observed that the tubes closest to the food widened and that the tubes furthest away from the food seemed to shrink. The result of this is that the slime mold reorganized itself in favor of the food and was able to migrate towards the food source. But what is the underlying mechanism of this behavior?
The researchers found that the speed of tube-dilation matched the speed of particles flowing through the tube network: 15 micrometers per second, which is 5,4 centimeter per hour (for comparison, the average snail can travel 4800 cm/h). The researchers hypothesized that there must be a chemical signal that uses the network like a highway. And indeed, they found that as soon as the slime mold came in contact with a food source, a soluble chemical agent was released within the cytoplasm (the inside of the slime tubes), which softened the tube wall and triggered the widening of the tubes. This effect spread throughout the network as the chemical was transported through the network by the cytoplasmic flows.
As the tube dilation is permanent (at least, the dilation lasted until the end of the experiment), previous food sources are ‘encoded’ in the network by areas that have bigger tubes. And the closer to the food source, the bigger the tubes (more chemicals available). The total volume of the slime mold does not change, so if parts of the network expand, other parts have to shrink, something they also saw in their experiments. When introducing a food source further away from the big tube network, the slime mold reoriented itself by dilating tubes close to the new nutrients and shrinking the old tube system. So the old ‘memory’ of the previous food source is now overwritten by the new food source.
The researchers built a mathematical model to simulate the detection and response of the slime mold to a potential food source and compared that to the experimental data. The predictions strongly resembled what they saw in the experiments!
The research results not only provide insight into the problem-solving capabilities of P. polycephalum but also could help in the advancement of ‘smart material’ or ‘soft robot’ production. For instance, these robots can adapt their morphology to unstructured environments, and/or carry and touch fragile objects because they have flexible components. This makes them useful for applications in rescue and human interaction such as care for the elderly and prosthetics. By using the models and theory based on the relatively simple mechanisms of P. polycephalum, these materials could be given new properties such as the capability to interact with and respond to environmental cues.
Link to the original post: Mirna Kramar, Karen Alim (2021), Encoding memory in tube diameter hierarchy of living flow network, Proceedings of the National Academy of Sciences, 118 (10) e2007815118; DOI: 10.1073/pnas.2007815118