Unknown

Dataset Information

0

Model architectures for bacterial membranes.


ABSTRACT: The complex composition of bacterial membranes has a significant impact on the understanding of pathogen function and their development towards antibiotic resistance. In addition to the inherent complexity and biosafety risks of studying biological pathogen membranes, the continual rise of antibiotic resistance and its significant economical and clinical consequences has motivated the development of numerous in vitro model membrane systems with tuneable compositions, geometries, and sizes. Approaches discussed in this review include liposomes, solid-supported bilayers, and computational simulations which have been used to explore various processes including drug-membrane interactions, lipid-protein interactions, host-pathogen interactions, and structure-induced bacterial pathogenesis. The advantages, limitations, and applicable analytical tools of all architectures are summarised with a perspective for future research efforts in architectural improvement and elucidation of resistance development strategies and membrane-targeting antibiotic mechanisms.

Supplementary information

The online version contains supplementary material available at 10.1007/s12551-021-00913-7.

SUBMITTER: Carey AB 

PROVIDER: S-EPMC8921416 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature

altmetric image

Publications

Model architectures for bacterial membranes.

Carey Ashley B AB   Ashenden Alex A   Köper Ingo I  

Biophysical reviews 20220201 1


The complex composition of bacterial membranes has a significant impact on the understanding of pathogen function and their development towards antibiotic resistance. In addition to the inherent complexity and biosafety risks of studying biological pathogen membranes, the continual rise of antibiotic resistance and its significant economical and clinical consequences has motivated the development of numerous in vitro model membrane systems with tuneable compositions, geometries, and sizes. Appro  ...[more]

Similar Datasets

| S-EPMC5955700 | biostudies-literature
| S-EPMC3156245 | biostudies-literature
| S-EPMC5899066 | biostudies-literature
| S-EPMC7358649 | biostudies-literature
| S-EPMC6843542 | biostudies-literature
| S-EPMC6309364 | biostudies-literature
| S-EPMC3985651 | biostudies-literature
| S-EPMC10902431 | biostudies-literature
| S-EPMC8778854 | biostudies-literature
| S-EPMC3607388 | biostudies-literature