Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection

Author summary Our incomplete understanding of complex molecular networks, the collateral effects of resistance mutations, and unknown functions in bacterial genomes hinders our ability to prevent and treat antibiotic-resistant infections. Here we combined clinical, experimental and computational approaches to investigate how a recurring loss-of-function mutation in the transcriptional regulator NalD of Pseudomonas aeruginosa can confer antibiotic resistance in patients acutely infected by this opportunistic pathogen, driving the rapid evolution of resistance. Computational modeling revealed metabolic pathways that could be involved in the pathogen's response to the antibiotic resistance mutation, and which may help offset a fitness cost in the absence of antibiotics. These results provide insights on a recurrent driver of antibiotic resistance in a major human pathogen. Pseudomonas aeruginosa, a main cause of human infection, can gain resistance to the antibiotic aztreonam through a mutation in NalD, a transcriptional repressor of cellular efflux. Here we combine computational analysis of clinical isolates, transcriptomics, metabolic modeling and experimental validation to find a strong association between NalD mutations and resistance to aztreonam-as well as resistance to other antibiotics-across P. aeruginosa isolated from different patients. A detailed analysis of one patient's timeline shows how this mutation can emerge in vivo and drive rapid evolution of resistance while the patient received cancer treatment, a bone marrow transplantation, and antibiotics up to the point of causing the patient's death. Transcriptomics analysis confirmed the primary mechanism of NalD action-a loss-of-function mutation that caused constitutive overexpression of the MexAB-OprM efflux system-which lead to aztreonam resistance but, surprisingly, had no fitness cost in the absence of the antibiotic. We constrained a genome-scale metabolic model using the transcriptomics data to investigate changes beyond the primary mechanism of resistance, including adaptations in major metabolic pathways and membrane transport concurrent with aztreonam resistance, which may explain the lack of a fitness cost. We propose that metabolic adaptations may allow resistance mutations to endure in the absence of antibiotics and could be targeted by future therapies against antibiotic resistant pathogens.