Size matters: Bioinformatics accurately detects short, fat antibiotic-resistant bacteria

Researchers have found that antibiotic-resistant bacteria are fatter and shorter than their antibiotic-sensitive parental strains, and that these morphological changes correlate with changes in the expression of genes related to energy metabolism and antibiotic resistance. A machine learning approach was able to distinguish between antibiotic-resistant and antibiotic-sensitive bacteria in the absence of drug treatment based on microscope images, suggesting that bioinformatics could be used to detect antibiotic resistance in patient samples.