Probiotics have shown positive effects on gastrointestinal diseases; they have barrier-modulating effects and change the inflammatory response towards pathogens in studies in vitro. The aim of this investigation has been to examine the response of intestinal epithelial cells to Enterococcus faecium NCIMB 10415 (E. faecium), a probiotic positively affecting diarrhea incidence in piglets, and two pathogenic Escherichia coli (E. coli) strains, with specific focus on the probiotic modulation of the response to the pathogenic challenge. Porcine (IPEC-J2) and human (Caco-2) intestinal cells were incubated without bacteria (control), with E. faecium, with enteropathogenic (EPEC) or enterotoxigenic E. coli (ETEC) each alone or in combination with E. faecium. The ETEC strain decreased transepithelial resistance (TER) and increased IL-8 mRNA and protein expression in both cell lines compared with control cells, an effect that could be prevented by pre- and coincubation with E. faecium. Similar effects were observed for the increased expression of heat shock protein 70 in Caco-2 cells. When the cells were challenged by the EPEC strain, no such pattern of changes could be observed. The reduced decrease in TER and the reduction of the proinflammatory and stress response of enterocytes following pathogenic challenge indicate the protective effect of the probiotic.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4408629PMC
http://dx.doi.org/10.1155/2015/304149DOI Listing

Publication Analysis

Top Keywords

enterococcus faecium
8
faecium ncimb
8
ncimb 10415
8
heat shock
8
shock protein
8
response intestinal
8
intestinal cells
8
pathogenic challenge
8
cells
6
response
5

Similar Publications

Introduction: Antimicrobial resistance remains a global threat with increasing morbidity and mortality rates. The aim of this study was to identify the antimicrobial resistance trends among ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp.) isolated from clinical samples at a Health Practice and Research Hospital over five years.

View Article and Find Full Text PDF

SL70, a Novel Exopolysaccharide Producer from Traditional Sourdough Fermentation of Einkorn ( L. ssp. ).

Food Technol Biotechnol

December 2024

Department of Food Engineering, Gumushane University, Baglarbasi Road, 29100 Gumushane, Turkey.

Research Background: Given the potential of microbial exopolysaccharides from lactic acid bacteria in various industrial processes, alternative sources for the isolation of lactic acid bacteria are highly topical. In this study, we used a traditional sourdough from einkorn ( L. ssp.

View Article and Find Full Text PDF

Unlabelled: As sequencing costs decrease, short-read and long-read technologies are indispensable tools for uncovering the genetic drivers behind bacterial pathogen resistance. This study explores the differences between the use of short-read (Illumina) and long-read (Oxford Nanopore Technologies, ONT) sequencing in detecting antimicrobial resistance (AMR) genes in ESKAPE pathogens ( and ). Utilizing a dataset of 1,385 whole genome sequences and applying commonly used bioinformatic methods in bacterial genomics, we assessed the differences in genomic completeness, pangenome structure, and AMR gene and point mutation identification.

View Article and Find Full Text PDF

Polymeric Anti-Antibiotic Microparticles to Prevent Antibiotic Resistance Evolution.

Small

January 2025

Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, 16802, USA.

Vancomycin (VAN) and daptomycin (DAP) are among the last-resort antibiotics for treating multidrug-resistant Gram-positive bacterial infections. They are administered intravenously (IV); however, ≈5 - 10% of the total IV dose is released in the gastrointestinal (GI) tract via biliary excretion, driving resistance emergence in commensal Enterococcus faecium (E. faecium) populations.

View Article and Find Full Text PDF

Artificial intelligence (AI) is a promising approach to identify new antimicrobial compounds in diverse microbial species. Here we developed an AI-based, explainable deep learning model, EvoGradient, that predicts the potency of antimicrobial peptides (AMPs) and virtually modifies peptide sequences to produce more potent AMPs, akin to in silico directed evolution. We applied this model to peptides encoded in low-abundance human oral bacteria, resulting in the virtual evolution of 32 peptides into potent AMPs.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!