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


Authors: Yan, J.; Estanbouli, H.; Liao, C.; Kim, W.; Monk, J. M.; Rahman, R.; Kamboj, M.; Palsson, B. O.; Qiu, W.; Xavier, J. B.
Article Title: Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection
Abstract: 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. Copyright: © 2019 Yan et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Keywords: cancer chemotherapy; gene mutation; drug targeting; genetic analysis; gene overexpression; in vivo study; transcriptomics; mathematical model; health care cost; antibiotic resistance; drug mechanism; bacterium isolate; bone marrow transplantation; loss of function mutation; membrane transport; metabolic regulation; bacterial gene; evolutionary adaptation; human; article; pseudomonas infection; aztreonam; nald gene
Journal Title: PLoS Computational Biology
Volume: 15
Issue: 12
ISSN: 1553-7358
Publisher: Public Library of Science  
Date Published: 2019-12-20
Start Page: e1007562
Language: English
DOI: 10.1371/journal.pcbi.1007562
PUBMED: 31860667
PROVIDER: scopus
PMCID: PMC6944390
DOI/URL:
Notes: Source: Scopus
Altmetric
Citation Impact
MSK Authors
  1. Mini Kamboj
    137 Kamboj
  2. Joao Debivar Xavier
    92 Xavier
  3. Jinyuan Yan
    9 Yan
  4. Chen Liao
    15 Liao