Bacteria negotiate obstacles in their way

24 May 2019

BACTERIA

Artists impression of bacteria

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Bacteria in an obstacle course reach food almost as quickly as bacteria with a clear path.

The new research from Carnegie Mellon University, published in the journal PNAS, allows better modelling of how bacteria move in a complex environment such as the body.

The researchers built a tiny obstacle course in a chamber 1mm by 1mm, with square and round obstacles, and tracked how bacteria moved across it.

Bacteria move by “swim and tumble” - they swim in a straight line for a bit, then tumble about in a circle and go in a new direction. The tumbles allow bacteria to adjust their course.

Bacteria can’t see food in the distance (they can’t “see” anything), but if the food diffuses in the environment, it creates a gradient that the bacteria can sense and follow towards the source, like we might follow a delicious smell to the kitchen.

The same process applies if there is a toxin, but with the bacteria always trying to move down the gradient rather than up.

This is known as chemotaxis, and has been well-studied in bacteria, but only when they’re moving in a clear space.

In this experiment, the group built multiple obstacle courses, from 0% obstacle coverage up to 64% obstacle coverage, and timed how long it took 90% of a group of bacteria to cross the chamber to a food source.

The existing model of bacterial movement predicted that obstacles would significantly slow them down, but this wasn’t the case. “Despite how much we increased obstacle coverage, the time it takes for the bacterial cells to escape from the chamber is roughly the same,” says Dr Sabrina Rashid, lead author of the study.

Following this result, the researchers tracked individual bacteria to see how they were moving, and saw the bacteria were reducing how often they tumbled. “When they are moving in the right direction, they can continue that run for a much longer period of time,” explains Rashid.

This adaptive tumbling mechanism allowed them to compensate for the increased distance they had to travel around the obstacles to reach their target.

The group has made an updated model of bacterial movement to reflect their results, which they hope can be used to better predict the spread of bacteria in real world situations, such as E. coli in the gastrointestinal tract. It could offer a new angle for treatment, “in the case of antibiotic resistance, maybe if we want to take a physical approach to how to stop spreading harmful bacterial cells [...] we can probably come up with a better informed mechanism to how to do that.”

It could also be applied to study how cancer cells move around the body. While the extent to which cancer cells move like bacterial cells will vary with the different cancer cell types, “overall the idea that there is some kind of feedback from the physical environment, that insight might be helpful,” says Rashid.

As well as biology, the new model has been applied to simulations of swarms of search and rescue robots finding victims in an emergency.

Rashid explains, “the way the swarm robots are working is similar to the way the bacteria is finding its food source. Oftentimes, if you’re doing these kind of search and rescue mission, there will be many many obstacles that the robots have to encounter.”

Using the bacterial adaptive tumbling mechanism, the swarm robots found their targets faster in simulations.

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