Outdoor. Wild, beautiful nature? Over the past 3 years, I got into microbial evolution, and a little bit of ecology, too. The dramas, though only micrometers small, are amongst the most captivating and existential ones I know. The survival of a colony by sacrificing 90% of its members. The brutal dance between a predator’s hunger and the replenishment of its feed. The choice to live without food to grow, or instead risk being devoured while venturing out. As outdoor and beautiful as it gets.

Invited work for Groj and Van Did‘s ‘Outdoor’, release 4 April, 2013 on Parquet Recordings‘ compilation ‘Re:Cognition Vol. 5’. Microbe simulation based on a model developed in my recent article in Physical Biology.

Detailed breakdown of the video:

[0:00-0:34] A single cell, whose DNA encodes that its membrane is completely red, seeds the colony. On clapping, the cells double, showing how quick a colony can grow given nothing is threatening it or inhibiting its growth. Already, some of the offspring mutates and is less red, this is how variation enters into the population. Also, the cells that happen to be smaller can not move as quick as big ones.

[0:34-0:52] The histograms (graphs on the top left) show that the cells have already become quite mixed in terms of how red they are. Now the cost for being red is increased. In reaction, more and more cells die off, and only the ones that are not very red survive till last. This is selection – the cells do not become white to be white, but only the ones that are white survive, so we end up with a white population.

[Starting 0:52] This is an evolutionary bottleneck – only one cell, which is not very red, survives till it can reach the newly appeared food source. Therefore, it is the new seed for all other cells that are born from it, its DNA with all its other random changes is carried by its daughter cells, their daughter cells and so on…

[0:54-1:35] Here the population evolves more slowly, and develops an ability to stay close to the food source. As seen in the bars on the left hand, the decay goes up, representing a generally harsher environment for the cells. In consequence only the ones close to the food source survive and replicate, the others mutate heavily and/or die. A ‘popular’ way to go towards food and stay there is chemotaxis, meaning that cell motion gets adjusted to the level of a chemical (food) available. Cells that have a lot of chemotaxis genes move slower when close to the food source. So, after some time, one can see a shift in the ‘chemotaxis’ histogram towards high chemotaxis – evolutionary adaptation to a harsh environment and a localized food source.

[1-35-2:06] Each cell’s DNA is represented by a column of rectangles, going from left to right for each cell in the simulation. After the past two evolutionary adaptations, we can see that the top third (‘red genes’) are for the most part dark, the bottom third (‘chemotaxis genes’) is rather bright – meaning that the cells have evolved to be not very red and also rather sensitive to food being present. (In case you wondered – yes, the ‘DNA’ is made up of 0 and 1, not GTCA. Nobody is perfect.)

[2:06-2:32] Wha! The predator has entered the scene. The red curve (size of the predator) and the blue curve (number of live cells) already show an interesting interaction of the predator and the cells – first he eats all of them at once, becomes very large and hungry. Then, oops, no cells left and he shrinks due to lack of food, giving the cells a chance to regrow. Approaching the 2:32 mark, already hints of predator-prey dynamics become visible: Small predator -> many new cells can grown -> predator grows to bigger size -> big predator eats up almost all the cells -> no cells left for predator to eat -> predator shrinks to small size -> many new cells can grow -> predator grows to bigger size …

[2:32-3:08] The food source is taken away and the environment gets a little less harsh at first, and then harsher again. This allows the cells to get away from the food source and escape the predator. Interestingly, while the predator itself has no preference for left, right, top, bottom, once it starts eating it follows a path through the cells, leaving behind it a tail wave of death. Now, here I am not sure, but I think the interaction between spread out cells and the eating behavior of the predator let the predator pick up speed and proceed through the population in a somewhat coherent direction.

[3:08-3:39] The cells are now spawned off a spawn point at a pretty high rate. Here, the predator prey interactions become very visible – whenever the blue curve goes up (more live cells), the red curve (size of predator) follows right after, and makes sure to eat up the cells immediately. The cycles repeats a couple of times.

[3:39-4:12] The food source is added back in, across from the spawn point. Now things get pretty hectic. The cells can reach the food source, but the predator will follow once they really get settled there and become so big that he gobbles up everything. But, he is quite far away from the spawn point, so now cells can escape from the spawn point and run off to other ends of the screen. Such is nature – simple rules, leading to unruly chaos.

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