A sensor for detecting bacterial resistance to antibiotics using a neural network was developed by scientists from Tomsk Polytechnic University and Siberian State Medical University together with colleagues from the Czech Republic. The results of the research were published in the journal. Analytica Chimica Acta.
Researchers have created a device that can perform spectral analysis of a sample, analyze the result using a neural network, and give the answer: there is a resistance gene, it is absent, the sample does not represent a DNA structure, or additional data is needed. Answer with a certain accuracy.
The scientists tested the method on a DNA sequence encoding resistance to beta-lactam antibiotics. Analysis of the samples revealed the presence of a specific DNA sequence at a picomolar concentration.
The researchers hope that the results will make it possible to identify antibiotic-resistant bacteria in a very short time and cannot be compared with standard methods.
Formerly from University of Manchester suggested Create new antibiotics through genome editing. As the researchers experimented with the E. coli genes, they changed domains that recognize different amino acids. So they were able to create “assembly lines” for the new peptides. True, scientists did not find a cure for the superbugs, but that was not their task – they showed that genome editing could be a viable tool for creating new antibiotics.
The researchers explain that the new approach makes it possible to quickly and efficiently create complex enzymes that can produce new antibiotics. This will accelerate the development of drugs to deal with infections resistant to existing antibiotics.