ArticleFolia microbiologica2026
Network-based bioinformatics for the prediction of candidate SNPs in Staphylococcus aureus virulence and resistance genes.
Article in Folia microbiologica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study proposes a network-based bioinformatics strategy to predict candidate genes for SNPs in Staphylococcus aureus that act as points of convergence between antimicrobial resistance and biofilm formation. Based on 19 Staphylococcus aureus resistance and virulence genes, a protein-protein interaction network was constructed on the STRING platform and expanded with 20 first-degree interactors. The topology revealed central hubs with high connectivity, such as IcaA (degree 18), Atl (14), SarA (11), ClfA/FnbA (15-21), and low-degree proteins such as vraSR (2) and mgrA (4). MCL analysis divided the network into 10 functional clusters; Cluster 1 grouped adhesion and biofilm proteins together with the mecA resistance gene, highlighting molecular integration. Functional enrichment (Gene Ontology) showed significant over-representation of cell adhesion (FDR = 1.83 × 10⁻⁶) and transcriptional regulation (FDR = 0.042), with an overall interaction p-value < 1.0 × 10⁻¹⁶. The hubs were stratified into regulators (Group 1: SarA, MgrA, VraS), with a cascade effect, and effectors (Group 2: IcaA, Atl, ClfA/FnbA), with a direct effect on the structure. These six predicted candidate genes may represent the main points of convergence between resistance mechanisms and biofilm formation, constituting priority targets for genomic association studies and for the development of new therapeutic strategies.
Indexed as
Identifiers
42550451What Socratic 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 Socratic graph.