ArticleFrontiers in cellular and infection microbiology2023
Identification of differences in gene expression implicated in the Adherent-Invasive
Article in Frontiers in cellular and infection microbiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 8 citations in OpenAlex.
- Review
- Deciphering the Implications ofPathogens (Basel, Switzerland) · 2026Review
- Contribution of Toxin-Antitoxin Systems to Adherent-InvasiveMicroorganisms · 2024Review
- Review
- ChiA: a major player in the virulence of Crohn's disease-associated adherent and invasiveGut microbesArticle
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 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Adherent-invasive Methods: Comparative transcriptomics was performed on two closely related AIEC/non-AIEC strain pairs during Intestine-407 cell infection. DEGs were quantified by RT-qPCR in the same RNA extracts, as well as in 14 AIEC and 23 non-AIEC strains to validate the results across a diverse strain collection. Binary logistical regression was performed to identify DEGs whose quantification could be used as AIEC biomarkers. Results: Comparative transcriptomics revealed 67 differences in expression between the two phenotypes in the strain pairs, 50 of which (81.97%) were corroborated by RT-qPCR. When explored in the whole strain collection, 29 DEGs were differentially expressed between AIEC and non-AIEC phenotypes (p-value < 0.042), and 42 genes between the supernatant fraction of infected cell cultures and the cellular fraction containing adhered and intracellular bacteria (p-value < 0.049). Notably, six DEGs detected in the strain collection were implicated in arginine biosynthesis and five in colanic acid synthesis. Furthermore, two biomarkers based on Discussion: This is the first transcriptomic study conducted using AIEC-infected cell cultures. We have identified several genes that may be involved in AIEC pathogenicity, two of which are putative biomarkers for identification.
Indexed as
Identifiers
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.