Evidence map›Paper›PMID 31860667›Full record

ArticlePLoS computational biology2019

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

Jinyuan Yan, Henri Estanbouli, Chen Liao, Wook Kim, Jonathan M Monk, Rayees Rahman, Mini Kamboj, Bernhard O Palsson, Weigang Qiu, Joao B Xavier

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
0.7field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 18 citations in OpenAlex.

  1. Mechanisms involved in cefiderocol resistance in FrenchAntimicrobial agents and chemotherapy · 2026
    Article
  2. Beyond Resistance Genes:Life (Basel, Switzerland) · 2026
    Review
  3. Article
  4. Emergence of outbreak-driving high-riskMicrobial genomics · 2026
    Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. Comparative molecular profiling of multidrug-resistantJAC-antimicrobial resistance · 2024
    Article
  11. Article
  12. Whole-Genome Sequencing Reveals Diversity of Carbapenem-ResistantAntimicrobial agents and chemotherapy · 2022
    Article
  13. Article
  14. Review
  15. Antibiotic Resistance in Pseudomonas.Advances in experimental medicine and biology · 2022
    Article
  16. Review
  17. Article
  18. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 5 institutions in 1 country.

Jinyuan YanProgram for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Henri EstanbouliProgram for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Chen LiaoProgram for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.
Wook KimDepartment of Biological Sciences, Duquesne University, Pittsburgh, Pennsylvania, United States of America.ORCID 0000-0001-6818-9688
Jonathan M MonkDepartment of Bioengineering, University of California San Diego, La Jolla, California, United States of America.ORCID 0000-0002-3895-8949
Rayees RahmanIcahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Mini KambojInfection Control, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York, New York, United States of America.
Bernhard O PalssonDepartment of Bioengineering, University of California San Diego, La Jolla, California, United States of America.
Weigang QiuDepartment of Biological Sciences, Hunter College & Graduate Center, CUNY, New York, New York, United States of America.ORCID 0000-0003-4585-1872
Joao B XavierProgram for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, New York, United States of America.ORCID 0000-0003-3592-1689
Memorial Sloan Kettering Cancer Center · USUniversity of California San Diego · USDuquesne University · USIcahn School of Medicine at Mount Sinai · USThe Graduate Center, CUNY · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Systems Biology of Microbiome-mediated Resilience to Antibiotic-resistant PathogensU01AI124275 · NIAID · SLOAN-KETTERING INST CAN RESEARCH · PI PAMER, ERIC G., XAVIER, JOAO · 2016 to 2020
$8.9M
Mathematical ecology models of host-microbiota interaction in auto microbiota transplants (auto-FMT)R01AI137269 · NIAID · SLOAN-KETTERING INST CAN RESEARCH · PI TAUR, YING, XAVIER, JOAO · 2019 to 2023
$3.8M
NCI NIH HHS P30 CA008748NIAID NIH HHS R01 AI137269NIAID NIH HHS U01 AI124275
6 · The paper itself

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.

Indexed as

Loss of Function MutationAnti-Bacterial AgentsAztreonamBacterial ProteinsComputational BiologyDrug Resistance, BacterialGene Expression ProfilingGenes, BacterialHumansMetabolic Networks and PathwaysModels, BiologicalModels, MolecularPhylogenyPseudomonas aeruginosaPseudomonas InfectionsRepressor ProteinsAnti-Bacterial AgentsAztreonamBacterial ProteinsRepressor Proteins

Identifiers

PMID31860667
PMCPMC6944390
OpenAlexW2996376737

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.