The researchers investigate diverse Type I-F CRISPR-Cas systems and engineer them to add genetic cargo — up to 10,000 additional genetic code letters — to the transposon’s cargo to make desired changes to a bacterium — in this case, E. coli.

The findings expand the CRISPR toolbox and could have significant implications in the manipulation of bacteria and other organisms at a time of need for flexible genome editing in therapeutics, biotechnology and more sustainable and efficient agriculture.

Bacteria use CRISPR-Cas as adaptive immune systems to withstand attacks from enemies like viruses. These systems have been adapted by scientists to remove or cut and replace specific genetic code sequences in a variety of organisms. The new finding shows that exponentially larger amounts of genetic code can be moved or added, potentially increasing CRISPR’s functionality.

“In nature, transposons have co-opted CRISPR systems to, selfishly, move themselves around an organism’s genome to help themselves survive. We’re in turn co-opting what occurs in nature by integrating with transposons a programmable CRISPR-Cas system that can move around genetic cargo that we design to perform some function,” said Rodolphe Barrangou, the Todd R. Klaenhammer Distinguished Professor of Food, Bioprocessing and Nutrition Sciences at NC State and corresponding author of a paper describing the research.

“Using this method, we showed that we can engineer genomes by moving chunks of DNA up to 10,000 letters,” Barrangou said. “Nature already does this — the bioinformatic data shows examples of up to 100,000 genetic letters moved around by transposon-based CRISPR systems — but now we can control and engineer it by using this system.

“To complete the hitchhiking analogy, we’re engineering the hitchhiker to bring certain luggage or cargo into the car to deliver some type of payload when the car arrives at its destination.”

The study shows the researchers proving the method’s effectiveness both in vitro on the lab bench and in vivo in E. coli. The researchers selected 10 different CRISPR-associated transposons to test the method’s effectiveness. The approach worked with all 10 transposons, although they varied in effectiveness based on factors like temperature and the size of the transposon’s cargo load.

“It was exciting to find that all of the systems we tested were functional after reconstructing them into genome editing tools from their native biological forms,” said Avery Roberts, an NC State graduate student and first author of the study. “We uncovered new features of these systems, but there’s likely many more relevant findings and applications to come as the field moves at a rapid pace.”

The research also showed that the method could be used with different transposons at the same time.

“Instead of just one gene — as is the case with other CRISPR systems like the more familiar Type II Cas-9 system — we can bring in a whole metabolic pathway to incorporate a whole new set of functions to an organism,” Barrangou said. “In the future, that could mean providing more flexible disease resistance or drought resistance to plants, for example.”

“We are excited about these findings and see the potential for applying these newly discovered systems in crop plants to accelerate the development of more resilient, higher-yielding varieties,” said Gusui Wu, global head of seeds research for Syngenta Seeds.

Barrangou and Wu add that the work in this study provides a great example of public-private partnerships that drive scientific discovery and train the workforce of tomorrow.

The paper appears in Nucleic Acids Research. Funding was provided by Syngenta Seeds. Co-authors of the paper include NC State graduate student Avery Roberts and former NC State Ph.D. student Matthew Nethery.

Story Source:

Materials provided by North Carolina State University. Original written by Mick Kulikowski. Note: Content may be edited for style and length.

Researchers at University of Limerick’s Bernal Institute worked with an international team of scientists to create a new type of organic material that learns from its past behaviour.

The discovery of the ‘dynamic molecular switch’ that emulate synaptic behaviour is revealed in a new study in the international journal Nature Materials.

The study was led by Damien Thompson, Professor of Molecular Modelling in UL’s Department of Physics and Director of SSPC, the UL-hosted Science Foundation Ireland Research Centre for Pharmaceuticals, together with Christian Nijhuis at the Centre for Molecules and Brain-Inspired Nano Systems in University of Twente and Enrique del Barco from University of Central Florida.

Working during lockdowns, the team developed a two-nanometre thick layer of molecules, which is 50,000 times thinner than a strand of hair and remembers its history as electrons pass through it.

Professor Thompson explained that the “switching probability and the values of the on/off states continually change in the molecular material, which provides a disruptive new alternative to conventional silicon-based digital switches that can only ever be either on or off.”

The newly discovered dynamic organic switch displays all the mathematical logic functions necessary for deep learning, successfully emulating Pavlovian ‘call and response’ synaptic brain-like behaviour.

The researchers demonstrated the new materials properties using extensive experimental characterisation and electrical measurements supported by multi-scale modelling spanning from predictive modelling of the molecular structures at the quantum level to analytical mathematical modelling of the electrical data.

To emulate the dynamical behaviour of synapses at the molecular level, the researchers combined fast electron transfer (akin to action potentials and fast depolarization processes in biology) with slow proton coupling limited by diffusion (akin to the role of biological calcium ions or neurotransmitters).

Since the electron transfer and proton coupling steps inside the material occur at very different time scales, the transformation can emulate the plastic behaviour of synapse neuronal junctions, Pavlovian learning, and all logic gates for digital circuits, simply by changing the applied voltage and the duration of voltage pulses during the synthesis, they explained.

“This was a great lockdown project, with Chris, Enrique and I pushing each other through zoom meetings and gargantuan email threads to bring our teams combined skills in materials modelling, synthesis and characterisation to the point where we could demonstrate these new brain-like computing properties,” explained Professor Thompson.

“The community has long known that silicon technology works completely differently to how our brains work and so we used new types of electronic materials based on soft molecules to emulate brain-like computing networks.”

The researchers explained that the method can in the future be applied to dynamic molecular systems driven by other stimuli such as light and coupled to different types of dynamic covalent bond formation.

This breakthrough opens up a whole new range of adaptive and reconfigurable systems, creating new opportunities in sustainable and green chemistry, from more efficient flow chemistry production of drug products and other value-added chemicals to development of new organic materials for high density computing and memory storage in big data centres.

“This is just the start. We are already busy expanding this next generation of intelligent molecular materials, which is enabling development of sustainable alternative technologies to tackle grand challenges in energy, environment, and health,” explained Professor Thompson.

Professor Norelee Kennedy, Vice President Research at UL, said: “Our researchers are continuously finding new ways of making more effective, more sustainable materials. This latest finding is very exciting, demonstrating the reach and ambition of our international collaborations and showcasing our world-leading ability at UL to encode useful properties into organic materials.”

Magnets generate invisible fields that attract certain materials. A common example is fridge magnets. Far more important to our everyday lives, magnets also can store data in computers. Exploiting the direction of the magnetic field (say, up or down), microscopic bar magnets each can store one bit of memory as a zero or a one — the language of computers.

Scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory want to replace the bar magnets with tiny magnetic vortices. As tiny as billionths of a meter, these vortices are called skyrmions, which form in certain magnetic materials. They could one day usher in a new generation of microelectronics for memory storage in high performance computers.

“The bar magnets in computer memory are like shoelaces tied with a single knot; it takes almost no energy to undo them,” said Arthur McCray, a Northwestern University graduate student working in Argonne’s Materials Science Division (MSD). And any bar magnets malfunctioning due to some disruption will affect the others.

“By contrast, skyrmions are like shoelaces tied with a double knot. No matter how hard you pull on a strand, the shoelaces remain tied.” The skyrmions are thus extremely stable to any disruption. Another important feature is that scientists can control their behavior by changing the temperature or applying an electric current.

Scientists have much to learn about skyrmion behavior under different conditions. To study them, the Argonne-led team developed an artificial intelligence (AI) program that works with a high-power electron microscope at the Center for Nanoscale Materials (CNM), a DOE Office of Science user facility at Argonne. The microscope can visualize skyrmions in samples at very low temperatures.

The team’s magnetic material is a mixture of iron, germanium and tellurium. In structure, this material is like a stack of paper with many sheets. A stack of such sheets contains many skyrmions, and a single sheet can be peeled from the top and analyzed at facilities like CNM.

“The CNM electron microscope coupled with a form of AI called machine learning enabled us to visualize skyrmion sheets and their behavior at different temperatures,” said Yue Li, a postdoctoral appointee in MSD.

“Our most intriguing finding was that the skyrmions are arranged in a highly ordered pattern at minus 60 degrees Fahrenheit and above,” said Charudatta Phatak, a materials scientist and group leader in MSD. ?”But as we cool the sample the skyrmion arrangement changes.” Like bubbles in beer foam, some skyrmions became larger, some smaller, some merge and some vanish.

At minus 270, the layer reached a state of nearly complete disorder, but order came back when the temperature returned to minus 60. This order-disorder transition with temperature change could be exploited in future microelectronics for memory storage.

“We estimate the skyrmion energy efficiency could be 100 to 1000 times better than current memory in the high performance computers used in research,” McCray said.

Energy efficiency is essential to the next generation of microelectronics. Today’s microelectronics already account for roughly 10% of the world’s electricity. And that number could double by 2030. More energy-efficient electronics must be found.

“We have a way to go before skyrmions find their way into any future computer memory with low power,” Phatak said. ?”Nonetheless, this kind of radical new way of thinking about microelectronics is key to next generation devices.”

This research was supported by the DOE Office of Basic Energy Sciences. The team’s machine learning program was run on supercomputing resources at the Argonne Leadership Computing Facility, a DOE Office of Science user facility.

This research appeared in Nano Letters. In addition to Phatak, Li, and McCray, Argonne authors include Amanda K. Petford-Long, Daniel P. Phelan and Xuedan Ma. Other authors include Rabindra Basnet, Krishna Pandey and Jin Hu from the University of Arkansas.