Evidence map›Paper›PMID 40253721›Full record

ReviewCurrent opinion in chemical biology2025

Chemical strategies for targeting lipid pathways in bacterial pathogens.

Alyssa M Carter, Emily C Woods, Matthew Bogyo

Abstract readReview
In one paragraph

Review in Current opinion in chemical biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Anti-infective compounds forSustainable microbiology · 2026
    Review
  2. Review
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

3 authors.

Alyssa M CarterDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA.
Emily C WoodsDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
Matthew BogyoDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA; Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, CA, USA. Electronic address: mbogyo@stanford.edu.

Funding

Targeting bacterial proteases involved in PAR signaling to treat inflammatory bowel diseasesR01DK130293 · NIDDK · STANFORD UNIVERSITY · PI BOGYO, MATTHEW · 2021 to 2025
$2.4M
Molecular Pharmacology Training ProgramT32GM136631 · NIGMS · STANFORD UNIVERSITY · PI BOGYO, MATTHEW, CHEN, JAMES K · 2021 to 2025
$2.0M
Staphylococcus serine hydrolases as targets for therapeutic and imaging contrast agentsR01EB026332 · NIBIB · STANFORD UNIVERSITY · PI BOGYO, MATTHEW · 2018 to 2021
$1.4M
NIBIB NIH HHS R01 EB026332NIDDK NIH HHS R01 DK130293NIGMS NIH HHS T32 GM136631
6 · The paper itself

Abstract

Microbial pathogens continue to plague human health and develop resistance to our current frontline treatments. Over the last few decades, there has been limited development of antibiotics with new mechanisms of action, highlighting our need to identify processes that can be targeted by next generation therapeutics. Recent advancements in our understanding of the roles that lipids play in key bacterial processes suggest that these biomolecules are a potentially valuable site for disruption by therapeutic agents. Specifically, the success of a pathogen depends on its ability to make fatty acids de novo or scavenge lipids from its host. This review focuses on recent advances using chemical biology tools for defining and disrupting lipid pathways in bacteria.

Indexed as

Anti-Bacterial AgentsBacteriaLipid MetabolismLipidsHumansAnti-Bacterial AgentsLipids

Identifiers

PMID40253721
PMCPMC12146079

What OpenQuestion holds

Textmetadata
LicenceTDM
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.