Methods for Bioinformatic Prediction of Genuine sRNAs from Outer Membrane Vesicles.
Methods Mol Biol
; 2843: 37-54, 2024.
Article
de En
| MEDLINE
| ID: mdl-39141293
ABSTRACT
The molecular pathogenesis of Gram-negative bacteria remains a complex and incompletely understood phenomenon. Various factors are believed to contribute to the pathogenicity of these bacteria. One key mechanism utilized by Gram-negative bacteria is the production of outer membrane vesicles (OMVs), which are small spherical particles derived from the bacterial outer membrane. These OMVs are crucial in delivering virulence factors to the host, facilitating host-pathogen interactions. Within these OMVs, small regulatory RNAs (sRNAs) have been identified as important players in modulating the host immune response. One of the main challenges in studying OMVs and their cargo of sRNAs is the difficulty in isolating and purifying sufficient quantities of OMVs, as well as accurately predicting genuine sRNAs computationally. In this chapter, we present protocols aimed at overcoming these obstacles.
Mots clés
Texte intégral:
1
Collection:
01-internacional
Base de données:
MEDLINE
Sujet principal:
Biologie informatique
/
Petit ARN non traduit
/
Membrane bactérienne externe
Langue:
En
Journal:
Methods Mol Biol
Sujet du journal:
BIOLOGIA MOLECULAR
Année:
2024
Type de document:
Article
Pays d'affiliation:
États-Unis d'Amérique
Pays de publication:
États-Unis d'Amérique