ArticlePLoS computational biology2021
Building blocks and blueprints for bacterial autolysins.
Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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.
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.
Who cites it
19 citing papers in PubMed, 26 citations in OpenAlex.
- Persistent Gaps in the Ultimate Mechanisms of Antimicrobial-Induced Bacterial Killing.Antibiotics (Basel, Switzerland) · 2026Review
- Low-Cost Protocol for Quantitative Measurement ofLife (Basel, Switzerland) · 2025Article
- Antibiotic-Induced Bacterial Cell Death: A "Radical" Way of Dying?Current topics in microbiology and immunology · 2025Article
- Archaea produce peptidoglycan hydrolases that kill bacteria.PLoS biology · 2025Article
- Extracellular DNA filaments associated with surface polysaccharide II give Clostridioides difficile biofilm matrix a network-like structure.NPJ biofilms and microbiomes · 2025Article
- Temperature-dependent regulation of bacterial cell division hydrolases by the coordinated action of a regulatory RNA and the ClpXP protease.Cell surface (Amsterdam, Netherlands) · 2025Article
- The impact of metagenomic analysis on the discovery of novel endolysins.Applied microbiology and biotechnology · 2025Review
- Synergistic potential of LeuBMC microbiology · 2024Article
- Agents Targeting the Bacterial Cell Wall as Tools to Combat Gram-Positive Pathogens.Molecules (Basel, Switzerland) · 2024Review
- TargetingAntibiotics (Basel, Switzerland) · 2024Article
- "Tear down that wall"-a critical evaluation of bioinformatic resources available for lysin researchers.Applied and environmental microbiology · 2024Review
- What do we need to move enzybiotic bioinformatics forward?Frontiers in microbiology · 2024Article
- Article
- Staphylococcus aureus sacculus mediates activities of M23 hydrolases.Nature communications · 2023Article
- Synthetic Biology Facilitates Semisynthetic Development of Type V Glycopeptide Antibiotics Targeting Vancomycin-ResistantJournal of medicinal chemistry · 2023Article
- Influence of NaCl and pH on lysostaphin catalytic activity, cell binding, and bacteriolytic activity.Applied microbiology and biotechnology · 2022Article
- One fold, many functions-M23 family of peptidoglycan hydrolases.Frontiers in microbiology · 2022Review
- Genomic Insights into the Distribution and Phylogeny of Glycopeptide Resistance Determinants within theAntibiotics (Basel, Switzerland) · 2021Article
- Two New M23 Peptidoglycan Hydrolases With Distinct Net Charge.Frontiers in microbiology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Bacteria utilize a wide variety of endogenous cell wall hydrolases, or autolysins, to remodel their cell walls during processes including cell division, biofilm formation, and programmed death. We here systematically investigate the composition of these enzymes in order to gain insights into their associated biological processes, potential ways to disrupt them via chemotherapeutics, and strategies by which they might be leveraged as recombinant antibacterial biotherapies. To do so, we developed LEDGOs (lytic enzyme domains grouped by organism), a pipeline to create and analyze databases of autolytic enzyme sequences, constituent domain annotations, and architectural patterns of multi-domain enzymes that integrate peptidoglycan binding and degrading functions. We applied LEDGOs to eight pathogenic bacteria, gram negatives Acinetobacter baumannii, Klebsiella pneumoniae, Neisseria gonorrhoeae, and Pseudomonas aeruginosa; and gram positives Clostridioides difficile, Enterococcus faecium, Staphylococcus aureus, and Streptococcus pneumoniae. Our analysis of the autolytic enzyme repertoires of these pathogens reveals commonalities and differences in their key domain building blocks and architectures, including correlations and preferred orders among domains in multi-domain enzymes, repetitions of homologous binding domains with potentially complementarity recognition modalities, and sequence similarity patterns indicative of potential divergence of functional specificity among related domains. We have further identified a variety of unannotated sequence regions within the lytic enzymes that may themselves contain new domains with important functions.
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What OpenQuestion holds
Registered trials
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.