Latest News

Clues beginning to emerge on asymtomatic SARS-CoV-2 infection
Back in November of 2020, during the first wave of the COVID-19 pandemic, I was teaching an in-person microbiology laboratory. One of my students had just been home to see his parents, and they all c…
Read more
Could there maybe be better uses of genetics and probiotics?
Professor Meng Dong and his laboratory have created a probiotic that can metabolize alcohol quickly and maybe prevent some of the adverse effects of alcohol consumption. The scientists cloned a highl…
Read more
ChatGPT is not the end of essays in education
The takeover of AI is upon us! AI can now take all our jobs, is the click-bait premise you hear from the news. While I cannot predict the future, I am dubious that AI will play such a dubious role in…
Read more
Fighting infections with infections
Multi-drug-resistant bacterial infections are becoming more of an issue, with 1.2 million people dying of previously treatable bacterial infections. Scientists are frantically searching for new metho…
Read more
A tale of two colleges
COVID-19 at the University of Wisconsin this fall has been pretty much a non-issue. While we are wearing masks, full in-person teaching is happening on campus. Bars, restaurants, and all other busine…
Read more

News

New powerful antibiotics discovered using machine learning


  Bacteria are amazing creatures. They adapt rapidly to any stress that is put on them or at least some part of the population. Because of the careless use of antibiotics to treat illnesses where they are not effective, antibiotic resistance has arisen. Some countries even allow the sale of antibiotics over the counter. The problem is getting out of control to the point that drug-resistant strains of bacteria that can no longer be treated are becoming a serious threat. About 35,000 people a year die from these infections.
New antibiotics are desperately needed. Stokes et al. have developed a novel way of searching for antibiotics using machine learning. Using artificial intelligence programming they trained an algorithm to identify the types of molecules that kill bacteria by feeding it 2,500 drugs and natural compounds and comparing that to how well the compound killed E. coli. The program learned the traits of a successful antibiotic. After training, they set the algorithm to screen 6,000 compounds to see if any of them had the traits that would make it a bacteria killer, and that is was unlike currently known antibiotics. After a few hours, the algorithm suggested several compounds. When tested, one of them proved to be very effective against known drug-resistant strains. The authors dubbed the compound Halicin in honor of the computer Hal in 2010 A Space Odessy. The Guardian has an excellent summary of the work.