Silkworm silk is fragile, which limits its uses, but a few extra genes can help.
Today, biomimetics is everywhere. Shark-inspired swimming trunks, gecko-inspired adhesives, and lotus-inspired water-repellents are all taken from observing the natural world. After millions of years of evolution, nature has quite a few tricks up its sleeve. They are tricks we can learn from. And now, thanks to some spider DNA and clever genetic engineering, we have another one to add to the list.
The elusive spider silk
We’ve known for a long time that spider silk is remarkable, in ways that synthetic fibers can’t emulate. Nylon is incredibly strong (it can support a lot of force), and Kevlar is incredibly tough (it can absorb a lot of force). But neither is both strong and tough. In all artificial polymeric fibers, strength and toughness are mutually exclusive, and so we pick the material best for the job and make do.
Spider silk, a natural polymeric fiber, breaks this rule. It is somehow both strong and tough. No surprise, then, that spider silk is a source of much study.The problem, though, is that spiders are incredibly hard to cultivate — let alone farm. If you put them together, they will attack and kill each other until only one or a few survive. If you put 100 spiders in an enclosed space, they will go about an aggressive, arachnocidal Hunger Games. You need to give each its own space and boundaries, and a spider hotel is hard and costly. Silkworms, on the other hand, are peaceful and productive. They’ll hang around all day to make the silk that has been used in textiles for centuries. But silkworm silk is fragile. It has very limited use.
The elusive – and lucrative – trick, then, would be to genetically engineer a silkworm to produce spider-quality silk. So far, efforts have been fruitless. That is, until now.
We can have silkworms creating silk six times as tough as Kevlar and ten times as strong as nylon.
Spider-silkworms
Junpeng Mi and his colleagues working at Donghua University, China, used CRISPR gene-editing technology to recode the silk-creating properties of a silkworm. First, they took genes from Araneus ventricosus, an East Asian orb-weaving spider known for its strong silk. Then they placed these complex genes – genes that involve more than 100 amino acids – into silkworm egg cells. (This description fails to capture how time-consuming, technical, and laborious this was; it’s a procedure that requires hundreds of thousands of microinjections.)
This had all been done before, and this had failed before. Where Mi and his team succeeded was using a concept called “localization.” Localization involves narrowing in on a very specific location in a genome. For this experiment, the team from Donghua University developed a “minimal basic structure model” of silkworm silk, which guided the genetic modifications. They wanted to make sure they had the exactly right transgenic spider silk proteins. Mi said that combining localization with this basic structure model “represents a significant departure from previous research.” And, judging only from the results, he might be right. Their “fibers exhibited impressive tensile strength (1,299 MPa) and toughness (319 MJ/m3), surpassing Kevlar’s toughness 6-fold.”
A world of super-materials
Mi’s research represents the bursting of a barrier. It opens up hugely important avenues for future biomimetic materials. As Mi puts it, “This groundbreaking achievement effectively resolves the scientific, technical, and engineering challenges that have hindered the commercialization of spider silk, positioning it as a viable alternative to commercially synthesized fibers like nylon and contributing to the advancement of ecological civilization.”
Around 60 percent of our clothing is made from synthetic fibers like nylon, polyester, and acrylic. These plastics are useful, but often bad for the environment. They shed into our waterways and sometimes damage wildlife. The production of these fibers is a source of greenhouse gas emissions. Now, we have a “sustainable, eco-friendly high-strength and ultra-tough alternative.” We can have silkworms creating silk six times as tough as Kevlar and ten times as strong as nylon.
We shouldn’t get carried away. This isn’t going to transform the textiles industry overnight. Gene-edited silkworms are still only going to produce a comparatively small amount of silk – even if farmed in the millions. But, as Mi himself concedes, this is only the beginning. If Mi’s localization and structure-model techniques are as remarkable as they seem, then this opens up the door to a great many supermaterials.
Nature continues to inspire. We had the bird, the gecko, and the shark. Now we have the spider-silkworm. What new secrets will we unravel in the future? And in what exciting ways will it change the world?
This article originally appeared on Freethink, home of the brightest minds and biggest ideas of all time.
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.