Potential anti-breast cancer drug identified
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Updates every hour. Last Updated: 18-Jun-2025 15:10 ET (18-Jun-2025 19:10 GMT/UTC)
A natural alternative to pesticides may be hiding in a misunderstood plant compound — but it could come at an environmental cost.
For years, scientists knew little about isoprene, a natural chemical produced by plants. New Michigan State University research 40 years in the making now sheds light on how this natural chemical can repel insects — and how some plants that don’t normally make isoprene could activate production in times of stress.
Tom Sharkey, a University Distinguished Professor in the Michigan State University-Department of Energy Plant Research Laboratory, the MSU Plant Resilience Institute and Department of Biochemistry and Molecular Biology, has studied isoprene for much of his career. Now, his lab has published findings that could provide a path for engineering plants that are more resilient to environmental change and pest outbreaks.
The protein MmpL5 is an efflux transporter, a critical pump that helps the pathogen M. tuberculosis grow by scavenging essential iron. Unfortunately, overexpressed MmpL5 can also pump out bedaquiline — the first new turberculosis drug in over 40 years — making the bacteria drug-resistant. Diabling the efflux transporter of M. tuberculosis with an inhibitor would strike a double blow — restore microbial sensitivity to antibiotic bedaquiline and break the cycle that gathers scarce iron. Researchers have now solved the structure of MmpL4, a close homolog of MmpL5 that has the same function.
Many types of bacteria produce a protein complex that injects toxins into neighbouring cells to eliminate competitors. For the first time, researchers at ETH Zurich and Eawag discovered that these killer bacteria also use this weapons to feed on their neighbours.
Researchers have found that chunks of ‘flipped’ DNA can help fish quickly adapt to new habitats and evolve into new species, acting as evolutionary ‘superchargers’.
The ability to precisely predict movements is essential not only for humans and animals, but also for many AI applications — from autonomous driving to robotics. Researchers at the Technical University of Munich (TUM) have now discovered that artificial neural networks can perform this task better when trained with biological data from early visual system development.