Identification of differences in gene expression implicated in the Adherent-Invasive Escherichia coli phenotype during in vitro infection of intestinal epithelial cells

Introduction: Adherent-invasive Escherichia coli (AIEC) is strongly associated with the pathogenesis of Crohn's disease (CD). However, no molecular markers currently exist for AIEC identification. This study aimed to identify differentially expressed genes (DEGs) between AIEC and non-AIEC strains that may contribute to AIEC pathogenicity and to evaluate their utility as molecular markers.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 wzb and cueR gene expression were proposed with an accuracy of = 85% in our strain collection.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.

Automated summary

This study compared the gene expression differences between AIEC and non-AIEC strains using transcriptomics and identified several genes that may contribute to the pathogenicity of AIEC. Two potential biomarkers for AIEC identification were also proposed.