ISIS Neutron and Muon Source Data Journal
This is a page describing data taken during an experiment at the ISIS Neutron and Muon Source. Information about the ISIS Neutron and Muon Source can be found at https://www.isis.stfc.ac.uk.
Molecular basis of lipopolysaccharide-mediated antibiotic resistance
Abstract: Antibiotic resistance in Gram-negative bacteria poses a critical global health threat, modifications of surface-exposed lipopolysaccharide (LPS) molecules reduce the efficacy of last-resort antibiotics such as polymyxin B (PmB). These modifications, often conferred by the plasmid-borne mcr-1 gene, alter the charge and structural properties of the bacterial outer membrane, hindering drug binding and efficacy. In this study, we propose to use neutron reflectometry to investigate how resistance-associated LPS modifications affect the penetration and membrane-disruptive action of PmB. By reconstituting deuterated LPS extracted from resistant E. coli strains into asymmetric model membranes, we will quantify the antibiotic?s interaction with the membrane under various conditions, including temperature variation and EDTA treatment. Our approach combines model-dependent and model-independent analysis of multiple-contrast NR data, enabling unique structural insight into the molecular basis of resistance. This work builds on our prior success in using neutron scattering to study antibiotic?membrane interactions and aims to provide fundamental knowledge to support the development of more effective antimicrobial strategies.
Principal Investigator: Dr Nicolò Paracini
Experimenter: Professor Martin Malmsten
Experimenter: Dr Zoë FIsher
Local Contact: Dr Luke Clifton
Experimenter: Dr Anna Leung
DOI: 10.5286/ISIS.E.RB2520472
ISIS Experiment Number: RB2520472
| Part DOI | Instrument | Public release date | Download Link |
|---|---|---|---|
| 10.5286/ISIS.E.RB2520472-1 | INTER | 19 December 2028 | Download |
Publisher: STFC ISIS Neutron and Muon Source
Data format: RAW/Nexus
Select the data format above to find
out more about it.
Data Citation
The recommended format for citing this dataset in a research
publication is as:
[author], [date], [title], [publisher],
[doi]
For Example:
Dr Nicolò Paracini et al; (2025): Molecular basis of lipopolysaccharide-mediated antibiotic resistance, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB2520472
Data is released under the CC-BY-4.0 license.
