As a carnivorous plant, Venus flytraps have always been a fascinating subject of study. One of their many mysteries is how they differentiate an insect visit from less nutritious stimulants such as a windblown pebble. Now scientists are one step closer to deciphering the underlying mechanism, assisted by a new ability to visualize calcium changes in real time.
Calcium has long been suspected to play an important part in a Venus flytrap’s close/no-close decision process, but scientists couldn’t verify their hypothesis before. Standard chemical tests for calcium would require cutting the plant apart, which would only result in a static snapshot. The software analogy would be killing the process for a memory dump but unable to debug the process at runtime. There were tantalizing hints of a biological calcium-based analog computer at work, but mother nature had no reason to evolve JTAG test points on it.
Lacking in-circuit debug headers, scientists turned to the next best thing: add diagnostic indicator lights. But instead of blinking LEDs, genes were added to produce a protein that glows in the presence of calcium. Once successful, they could work with the engineered plants and get visual feedback. Immediately see calcium levels change and propagate in response to various stimuli over different time periods. Confirming that the trap snaps shut only in response to patterns of stimuli that push calcium levels beyond a threshold.
With these glowing proteins in place, researchers found that calcium explained some of the behavior but was not the whole picture. There’s something else, suspected to be a fast electrical network, that senses prey movement and trigger calcium release. That’ll be something to dig into, but at least we have more experience working with electrical impulses and not just for plants, either.
There’s an old joke that you can’t trust atoms — they make up everything. But until fairly recently, there was no real way to see individual atoms. You could infer things about them using X-ray crystallography or measure their pull on tiny probes using atomic force microscopes, but not take a direct image. Until now. Two laboratories recently used cryo-electron microscopy to directly image atoms in a protein molecule with a resolution of about 1.2 x 10-7 millimeters or 1.2 ångströms. The previous record was 1.54 ångströms.
Recent improvements in electron beam technology helped, as did a device that ensures electrons that strike the sample travel at nearly the same speeds. The latter technique resulted in images so clear, researchers could identify individual hydrogen atoms in the apoferritin molecule and the water surrounding it.
A great big Thank You to everyone who answered the call to participate in Folding@Home, helping to understand proteins interactions of SARS-CoV-2 virus that causes COVID-19. Some members of the FAH research team hosted an AMA (Ask Me Anything) session on Reddit to provide us with behind-the-scenes details. Unsurprisingly, the top two topics are “Why isn’t my computer doing anything?” and “What does this actually accomplish?”
The first is easier to answer. Thanks to people spreading the word — like the amazing growth of Team Hackaday — there has been a huge infusion of new participants. We could see this happening on the leader boards, but in this AMA we have numbers direct from the source. Before this month there were roughly thirty thousand regular contributors. Since then, several hundredthousands more started pitching in. This has overwhelmed their server infrastructure and resulted in what’s been termed a friendly-fire DDoS attack.
Here’s a summary of current Folding@Home situation :
* We know about the work unit shortage
* It’s happening because of an approximately 20x increase in demand
* We are working on it and hope to have a solution very soon.
* Keep your machines running, they will eventually fold on their own.
* Every time we double our server resources, the number of Donors trying to help goes up by a factor of 4, outstripping whatever we do.
Why don’t they just buy more servers?
The answer can be found on Folding@Home donation FAQ. Most of their research grants have restrictions on how that funding is spent. These restrictions typically exclude capital equipment and infrastructure spending, meaning researchers can’t “just” buy more servers. Fortunately they are optimistic this recent fame has also attracted attention from enough donors with the right resources to help. As of this writing, their backend infrastructure has grown though not yet caught up to the flood. They’re still working on it, hang tight!
Computing hardware aside, there are human limitations on both input and output sides of this distributed supercomputer. Folding@Home need field experts to put together work units to be sent out to our computers, and such expertise is also required to review and interpret our submitted results. The good news is that our contribution has sped up their iteration cycle tremendously. Results that used to take weeks or months now return in days, informing where the next set of work units should investigate.
On Wednesday morning we asked the Hackaday community to donate their extra computer cycles for Coronavirus research. On Thursday morning the number of people contributing to Team Hackaday had doubled, and on Friday it had doubled again. Thank you for putting those computers to work in pursuit of drug therapies for COVID-19.
I’m writing today for two reasons, we want to keep up this trend, and also answer some of the most common questions out there. Folding@Home (FAH) is an initiative that simulates proteins associated with several diseases, searching for indicators that will help medical researchers identify treatments. These are complex problems and your efforts right now are incredibly important to finding treatments faster. FAH loads the research pipeline, generating a data set that researchers can then follow in every step of the process, from identifying which chemical compounds may be effective and how to deliver them, to testing they hypothesis and moving toward human trials.
Donate your extra computer cycles to combat COVID-19. The Folding@Home project uses computers from all over the world connected through the Internet to simulate protein folding. The point is to generate the data necessary to discover treatments that can have an impact on how this virus affects humanity. The software models protein folding in a search for pharmaceutical treatments that will weaken the virus’ ability to attack the human immune system. Think of this like mining for bitcoin but instead we’re mining for a treatment to Coronavirus.
Initially developed at Standford University and released in the year 2000, this isn’t the first time Hackaday has advocated for Folding@Home. The “Team Hackaday” folding group was started by readers back in 2005 and that team number is still active, so let’s pile on and work our way up the rankings. At the time of writing, we’re ranked 267 in the world, can we get back up to number 30 like we were in 2008? To use the comparison to bitcoin once again, this is like a mining pool except what we end up with is a show of goodwill, something I think we can all use right about now.
“Know your enemy” is the essence of one of the most famous quotes from [Sun Tzu]’s Art of War, and it’s as true now as it was 2,500 years ago. It also applies far beyond the martial arts, and as the world squares off for battle against COVID-19, it’s especially important to know the enemy: the novel coronavirus now dubbed SARS-CoV-2. And now, augmented reality technology is giving a boost to search for fatal flaws in the virus that can be exploited to defeat it.
The video below is a fascinating mix of 3D models of viral structures, like the external spike glycoproteins that give coronaviruses their characteristic crown appearance, layered onto live video of [Tom Goddard], a programmer/analysts at the University of California San Francisco. The tool he’s using is called ChimeraX, a molecular visualization program developed by him and his colleagues. He actually refers to this setup as “mixed reality” rather than “augmented reality”, to stress the fact that AR tends to be an experience that only the user can fully appreciate, whereas this system allows him to act as a guide on a virtual tour of the smallest of structures.
Using a depth-sensing camera and a VR headset, [Tom] is able to manipulate 3D models of the SARS virus — we don’t yet have full 3D structure data for the novel coronavirus proteins — to show us exactly how SARS binds to its receptor, angiotensin-converting enzyme-2 (ACE-2), a protein expressed on the cell surfaces of many different tissue types. It’s fascinating to see how the biding domain of the spike reaches out to latch onto ACE-2 to begin the process of invading a cell; it’s also heartening to watch [Tom]’s simulation of how the immune system responds to and blocks that binding.
It looks like ChimeraX and similar AR systems are going to prove to be powerful tools in the fight against not just COVID-19, but in all kinds of infectious diseases. Hats off to [Tom] and his team for making them available to researchers free of charge.
In the cold, dark recesses of ocean floors around the world, hagfish slither around like sea snakes, searching for food. When a hagfish finds a suitable carcass, it devours the dead fish in two different ways. As it burrows face-first through the tissue, eating with its jaw-less, tentacled mouth, the hagfish also absorbs nutrients through its skin.
Hagfish are not the unholy result of dumping toxic waste in the ocean. They’re one of the oldest creatures on Earth, having been around for more than 300 million years. How have they lasted this long?
These ancient creatures have no eyes, no backbones, and no scales. They are often misidentified as eel, and often called ‘slime eels’, but they are definitely fish. They just don’t look like conventional fish. In fact, when conventional, gill-faced fish come after hagfish, those guys are in for a surprise, because hagfish have a disgusting but ingenious defense mechanism.
Whenever hagfish are attacked or even just stressed by nearby fish or curious grabby humans, they immediately emit amazing amounts of mucus at an alarming rate. At the same time, the hagfish shoots out silky strands of protein that hold the slime together in a cohesive blob. Any predator that tries to bite down on one of these velvety frankfurters of the deep sea will find its mouth and gills covered in a wad of suffocating slime.
How is it that hagfish haven’t slimed themselves out of existence? Whenever they get get a taste of their own medicine, these boneless noodles quickly twist themselves into a pretzel. In the same motion, they use their paddle-shaped tails to squeegee off the slime.