Evidence map›Paper›PMID 34625561›Full record

ArticleNPJ systems biology and applications2021

An updated genome-scale metabolic network reconstruction of Pseudomonas aeruginosa PA14 to characterize mucin-driven shifts in bacterial metabolism.

Dawson D Payne, Alina Renz, Laura J Dunphy, Taylor Lewis, Andreas Dräger, Jason A Papin

Open access · goldAbstract read
In one paragraph

Article in NPJ systems biology and applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

17 citing papers in PubMed, 22 citations in OpenAlex.

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  6. Predicting Strain-Specific Metabolic Capabilities in the GenusComputational and structural biotechnology journal · 2026
    Article
  7. Unravelling three-way interactions betweenJournal of medical microbiology · 2025
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  11. NAR genomics and bioinformatics · 2024
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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

6 authors at 4 institutions in 2 countries.

Dawson D PayneDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.ORCID 0000-0001-5392-8492
Alina Renz *Institute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Tübingen, Germany.ORCID 0000-0003-3851-9978
Laura J Dunphy *Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA.
Taylor LewisDepartment of Chemical Engineering, University of Massachusetts Amherst, Amherst, MA, USA.
Andreas DrägerInstitute for Bioinformatics and Medical Informatics (IBMI), University of Tübingen, Tübingen, Germany.ORCID 0000-0002-1240-5553
Jason A PapinDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA. papin@virginia.edu.ORCID 0000-0002-2769-5805
University of Virginia · USGerman Center for Infection Research · DEUniversity of Massachusetts Amherst · USUniversity of Tübingen · DE

Funding

Multi-scale model of microbial phenotype modulation by mucinsR01AI154242 · NIAID · UNIVERSITY OF VIRGINIA · PI FORD, ROSEANNE, PAPIN, JASON · 2020 to 2024
$3.1M
Interdisciplinary Training in Systems & Biomolecular Data ScienceT32GM145443 · NIGMS · UNIVERSITY OF VIRGINIA · PI Kevin A Janes, Jason Papin · 2022 to 2026
$1.5M
NIAID NIH HHS R01 AI154242NIGMS NIH HHS T32 GM145443
6 · The paper itself

Abstract

Mucins are present in mucosal membranes throughout the body and play a key role in the microbe clearance and infection prevention. Understanding the metabolic responses of pathogens to mucins will further enable the development of protective approaches against infections. We update the genome-scale metabolic network reconstruction (GENRE) of one such pathogen, Pseudomonas aeruginosa PA14, through metabolic coverage expansion, format update, extensive annotation addition, and literature-based curation to produce iPau21. We then validate iPau21 through MEMOTE, growth rate, carbon source utilization, and gene essentiality testing to demonstrate its improved quality and predictive capabilities. We then integrate the GENRE with transcriptomic data in order to generate context-specific models of P. aeruginosa metabolism. The contextualized models recapitulated known phenotypes of unaltered growth and a differential utilization of fumarate metabolism, while also revealing an increased utilization of propionate metabolism upon MUC5B exposure. This work serves to validate iPau21 and demonstrate its utility for providing biological insights.

Indexed as

MucinsPseudomonas aeruginosaBacteriaMetabolic Networks and PathwaysMucins

Identifiers

PMID34625561
PMCPMC8501023
OpenAlexW3203505575

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.