PRJNA485123
Predicting the emergence of antibiotic resistance through multi-omics approaches and Immune System-surveillance
The rise of antibiotic resistance in bacterial populations reflects inadequate counterselection by the antibiotic itself, by host immunity, or by fitness costs of the resistance mechanism. Our inability to control resistance stems from limited understanding of these three forces of selection and especially of the interplay between antibiotic dosage, how bacteria populations respond to antibiotics, and host immunity. This project maps these interactions in high definition for the bacterial pathogens Streptococcus pneumoniae and Acinetobacter baumannii, both of which are serious threats and can cause antibiotic-resistant pneumonia. The goal of this project is to design a 'plug-and-play learning toolbox' that is able to forecast the likelihood of the emergence of antibiotic resistance and prioritize antibiotic and immune therapies that enable more rapid, effective treatment with minimal risk of treatment failure.