Cesar de la Fuente and his team at the University of Pennsylvania are using algorithms to find potential new antibiotics derived from extinct animals such as Neanderthals and woolly mammoths. This pursuit involves “molecular de-extinction,” a process of searching genetic databases for fragments of ancient animal DNA that might have properties capable of combating bacteria.
Lab robots are pivotal in this process, reviving the most promising DNA fragments and testing their effectiveness against infections in mice. This innovative approach aims to combat the growing issue of antibiotic resistance, which was responsible for approximately 1.2 million deaths in 2019.
Despite some skepticism from the scientific community, De la Fuente’s team plans to incorporate modern mammal DNA into their research. They view this as an opportunity to take advantage of expanding genetic libraries, potentially uncovering new drugs to treat various infections and diseases.
The process of “molecular de-extinction” involves resurrecting fragments of ancient animal DNA, and the lab robots play a crucial role in bringing these fragments back to life. These revived fragments are then tested for their ability to fight infections in mice.
This approach, though unorthodox, is seen as a potential solution to the increasing problem of antibiotic resistance. It is predicted that this growing threat will only become more serious in the future, underlining the importance of finding new methods to combat it.
De la Fuente’s team is undeterred by the skepticism from some quarters of the scientific community and plans to expand their research to include the DNA of modern mammals. They believe that the growing genetic libraries present a significant opportunity to discover new drugs for a range of diseases and infections.
In the face of rising antibiotic resistance and the threat it poses to global health, the innovative approach of using algorithms to discover potential new antibiotics from the DNA of long-extinct animals offers a glimmer of hope. By looking to the past, we might just find the solutions we need for the future.
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