Evidence map›Paper›PMID 35379437›Full record

ArticleMethods in enzymology2022

Impact of crossbridge structure on peptidoglycan crosslinking: A synthetic stem peptide approach.

Alexis J Apostolos, Marcos M Pires

Open access · greenAbstract read
In one paragraph

Article in Methods in enzymology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
8.4field-weighted citation impact, top 2% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

  1. Review
  2. Non-canonical peptidoglycan cross-linking is essential forbioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. 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 at 1 institution in 1 country.

Alexis J ApostolosDepartment of Chemistry, University of Virginia, Charlottesville, VA, United States.
Marcos M PiresDepartment of Chemistry, University of Virginia, Charlottesville, VA, United States. Electronic address: mpires@virginia.edu.
University of Virginia · US

Funding

Unraveling Bacterial Cell Wall Biosynthesis and Sensing via Synthetic AnalogsR35GM124893 · NIGMS · UNIVERSITY OF VIRGINIA · PI Marcos M. Pires · 2017 to 2026
$3.6M
NIGMS NIH HHS R35 GM124893
6 · The paper itself

Abstract

The bacterial cell wall, whose main component is peptidoglycan (PG), provides cellular rigidity and prevents lysis from osmotic pressure. Moreover, the cell wall is the main interface between the external environment and internal cellular components. Given its essentiality, many antibiotics target enzymes related to the biosynthesis of cell wall. Of these enzymes, transpeptidases (TPs) are central to proper cell wall assembly and their inactivation is the mechanism of action of many antibiotics including β-lactams. TPs are responsible for stitching together strands of PG to make the crosslinked meshwork of the cell wall. This chapter focuses on the use of solid-phase peptide synthesis to build PG analogs that become site-selectively incorporated into the cell wall of live bacterial cells. This method allows for the design of fluorescent handles on PG probes that will enable the interrogation of substrate preferences of TPs (e.g., amidation at the glutamic acid residue, crossbridge presence) by analyzing the level of probe incorporation within the native cell wall of live bacterial cells.

Indexed as

Cell WallPeptidoglycanAnti-Bacterial AgentsBacteriaAnti-Bacterial AgentsPeptidoglycanAcyl acceptorBacteriaPeptidoglycanSynthetic stem peptideTripeptide

Identifiers

PMID35379437
PMCPMC9295140
OpenAlexW4210540774

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.