Some Bacteria Could Have A Rudimentary Form Of Memory

When we think of bacteria, we think of simple single-celled organisms that basically exist to consume resources and reproduce. They don’t think, feel, or remember… or do they? Bacteria don’t have brains, and as far as we know, they’re incapable of thought. But could they react to an experience and recall it later?

New research suggests that some bacteria could have a rudimentary form of memory of their experiences in the environment. They could even pass this memory down across generations via a unique mechanism. Let’s dive into the latest research that is investigating just what bacteria know, and how they happen to know it.

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Ecological System Dynamics For Computing

Some of you may remember that the ship’s computer on Star Trek: Voyager contained bioneural gel packs. Researchers have taken us one step closer to a biocomputing future with a study on the potential of ecological systems for computing.

Neural networks are a big deal in the world of machine learning, and it turns out that ecological dynamics exhibit many of the same properties. Reservoir Computing (RC) is a special type of Recurrent Neural Network (RNN) that feeds inputs into a fixed-dynamics reservoir black box with training only occurring on the outputs, drastically reducing the computational requirements of the system. With some research now embodying these reservoirs into physical objects like robot arms, the researchers wanted to see if biological systems could be used as computing resources.

Using both simulated and real bacterial populations (Tetrahymena thermophila) to respond to temperature stimuli, the researchers showed that ecological system dynamics has the “necessary conditions for computing (e.g. synchronized dynamics in response to the same input sequences) and can make near-future predictions of empirical time series.” Performance is currently lower than other forms of RC, but the researchers believe this will open up an exciting new area of research.

If you’re interested in some other experiments in biocomputing, checkout these RNA-based logic gates, this DNA-based calculator, or this fourteen-legged state machine.

AI Creates Killer Drug

Researchers in Canada and the United States have used deep learning to derive an antibiotic that can attack a resistant microbe, acinetobacter baumannii, which can infect wounds and cause pneumonia. According to the BBC, a paper in Nature Chemical Biology describes how the researchers used training data that measured known drugs’ action on the tough bacteria. The learning algorithm then projected the effect of 6,680 compounds with no data on their effectiveness against the germ.

In an hour and a half, the program reduced the list to 240 promising candidates. Testing in the lab found that nine of these were effective and that one, now called abaucin, was extremely potent. While doing lab tests on 240 compounds sounds like a lot of work, it is better than testing nearly 6,700.

Interestingly, the new antibiotic seems only to be effective against the target microbe, which is a plus. It isn’t available for people yet and may not be for some time — drug testing being what it is. However, this is still a great example of how machine learning can augment human brainpower, letting scientists and others focus on what’s really important.

WHO identified acinetobacter baumannii as one of the major superbugs threatening the world, so a weapon against it would be very welcome. You can hope that this technique will drastically cut the time involved in developing new drugs. It also makes you wonder if there are other fields where AI techniques could cull out alternatives quickly, allowing humans to focus on the more promising candidates.

Want to catch up on machine learning algorithms? Google can help. Or dive into an even longer course.

Combining Acoustic Bioprinting With Raman Spectroscopy For High-Throughput Identification Of Bacteria

Rapidly analyzing samples for the presence of bacteria and similar organic structures is generally quite a time-intensive process, with often the requirement of a cell culture being developed. Proposed by Fareeha Safir and colleagues in Nano Letters is a method to use an acoustic droplet printer combined with Raman spectroscopy. Advantages of this method are a high throughput, which could make analysis of samples at sewage installations, hospitals and laboratories significantly faster.

Raman spectroscopy works on the principle of Raman scattering, which is the inelastic scattering of photons by matter, causing a distinct pattern in the thus scattered light. By starting with a pure light source (that is, a laser), the relatively weak Raman scattering can be captured and the laser light filtered out. The thus captured signal can be analyzed and matched with known pathogens. Continue reading “Combining Acoustic Bioprinting With Raman Spectroscopy For High-Throughput Identification Of Bacteria”

Honey, Did You Feed The Lamp? Company Wants To Create Living Light Bulbs

The BBC’s [Peter Yeung] had an interesting post about a small French town experimenting with using bioluminescent organisms to provide lighting. A firm called Glowee is spearheading the effort in Rambouillet and other towns throughout France, using a variety of biological techniques to harness nature’s light sources.

Glowing animals are reasonably common ranging from fireflies to railroad worms. In the case of the French street lighting, Glowee is using a marine bacterium known as aliivibrio fischeri. A salt-water tube contains nutrients and when air is flowing through the tube, the bacteria glow with a cool turquoise light. The bacteria enter an anaerobic state and stop glowing if you shut off the air.

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Open-Source Insulin: Biohackers Aiming For Distributed Production

When you’ve got a diabetic in your life, there are few moments in any day that are free from thoughts about insulin. Insulin is literally the first coherent thought I have every morning, when I check my daughter’s blood glucose level while she’s still asleep, and the last thought as I turn out the lights, making sure she has enough in her insulin pump to get through the night. And in between, with the constant need to calculate dosing, adjust levels, add corrections for an unexpected snack, or just looking in the fridge and counting up the number of backup vials we have on hand, insulin is a frequent if often unwanted intruder on my thoughts.

And now, as my daughter gets older and seeks like any teenager to become more independent, new thoughts about insulin have started to crop up. Insulin is expensive, and while we have excellent insurance, that can always change in a heartbeat. But even if it does, the insulin must flow — she has no choice in the matter. And so I thought it would be instructional to take a look at how insulin is made on a commercial scale, in the context of a growing movement of biohackers who are looking to build a more distributed system of insulin production. Their goal is to make insulin affordable, and with a vested interest, I want to know if they’ve got any chance of making that goal a reality.

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How Researchers Used Salt To Give Masks An Edge Against Pathogens

Masks are proven tools against airborne diseases, but pathogens — like the COVID-19 virus — can collect in a mask and survive which complicates handling and disposal. [Ilaria Rubino], a researcher at the University of Alberta, recently received an award for her work showing how treating a mask’s main filtration layer with a solution of mostly salt and water (plus a surfactant to help the wetting process) can help a mask inactivate pathogens on contact, thereby making masks potentially re-usable. Such masks are usually intended as single-use, and in clinical settings used masks are handled and disposed of as biohazard waste, because they can contain active pathogens. This salt treatment gives a mask a kind of self-cleaning ability.

Analysis showing homogenous salt coating (red and green) on the surface of fibers. NaCl is shown here, but other salts work as well.

How exactly does salt help? The very fine salt coating deposited on the fibers of a mask’s filtration layer first dissolves on contact with airborne pathogens, then undergoes evaporation-induced recrystallization. Pathogens caught in the filter are therefore exposed to an increasingly-high concentration saline solution and are then physically damaged. There is a bit of a trick to getting the salt deposited evenly on the polypropylene filter fibers, since the synthetic fibers are naturally hydrophobic, but a wetting process takes care of that.

The salt coating on the fibers is very fine, doesn’t affect breathability of the mask, and has been shown to be effective even in harsh environments. The research paper states that “salt coatings retained the pathogen inactivation capability at harsh environmental conditions (37 °C and a relative humidity of 70%, 80% and 90%).”

Again, the salt treatment doesn’t affect the mask’s ability to filter pathogens, but it does inactivate trapped pathogens, giving masks a kind of self-cleaning ability. Interested in the nuts and bolts of how researchers created the salt-treated filters? The Methods section of the paper linked at the head of this post (as well as the Methods section in this earlier paper on the same topic) has all the ingredients, part numbers, and measurements. While you’re at it, maybe brush up on commercially-available masks and what’s inside them.