Evidence map›Paper›PMID 40179664›Full record

ReviewCurrent opinion in microbiology2025

Pathogen adaptation to lung metabolites.

Gaurav Kumar Lohia, Sebastián A Riquelme

Abstract readReview
In one paragraph

Review in Current opinion in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Itaconate and its derivatives in human health and diseases.Signal transduction and targeted therapy · 2026
    Review
  2. Article
  3. 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

2 authors.

Gaurav Kumar LohiaDepartment of Pediatrics, Columbia University, New York, NY 10032, USA.
Sebastián A RiquelmeDepartment of Pediatrics, Columbia University, New York, NY 10032, USA. Electronic address: sr3302@cumc.columbia.edu.

Funding

Impact of nucleotide metabolism on bacterial clearanceR35GM146776 · NIGMS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Sebastian Alejandro Riquelme Colet · 2022 to 2026
$2.0M
Impact of Regulatory T Cells on Host Susceptibility to Pseudomonas Aeruginosa InfectionR21AI181780 · NIAID · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Sebastian Alejandro Riquelme Colet · 2025 to 2026
$445k
NIAID NIH HHS R21 AI181780NIGMS NIH HHS R35 GM146776
6 · The paper itself

Abstract

Opportunistic pathogens like Pseudomonas aeruginosa and Staphylococcus aureus rapidly adapt to the dynamic metabolic landscape of the respiratory mucosa during infection. Host phagocytes recognize these pathogens and trigger metabolic reprogramming, releasing immunometabolites such as succinate and itaconate. P. aeruginosa preferentially consumes succinate as a carbon source to enhance planktonic growth. In response to itaconate-induced membrane stress, it forms protective biofilms, allowing bacterial survival despite host defenses. Additionally, host ketone bodies support microbial communities that are less immunostimulatory and better tolerated by the lung. Similarly, S. aureus responds to itaconate by forming biofilms, aiding colonization in glucose-limited airways. In this milieu, S. aureus consumes proline, linking its survival with the metabolic activity of proline-producing fibroblasts. Here, we will review the competence of both P. aeruginosa and S. aureus to hijack host metabolic pathways, underscoring pathogen metabolic plasticity as an essential strategy to thrive in the human lung.

Indexed as

Adaptation, PhysiologicalLungPseudomonas aeruginosaStaphylococcus aureusAnimalsBiofilmsHost-Pathogen InteractionsHumansSuccinatesSuccinic AcidSuccinatesSuccinic Acid

Identifiers

PMID40179664
PMCPMC12136998

What OpenQuestion holds

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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.