ISIS Neutron and Muon Source Data Journal

NR study of antimicrobial synergy from pairing of lipopeptides and antibiotics against drug-resistant bacteria

Abstract: Antimicrobial peptides kill microbes differently from antibiotics. There is a great potential in seeking the synergy from the combined use of the two in clinical treatment. However, few studies have been made to pursue the development toward the combinational therapy. This work represents the first effort toward this goal. Cationic lipopeptides can self-assemble and easily bind to anionic bacterial membranes. When used as a binary mixture with antibiotics such as tetracycline (TC), they interact strongly to form new aggregates. Thus, binary lipopeptide-TC complexes may interact with bacterial membrane differently from their individual components. The broad aim of this work is to reveal how representative pairs of lipopeptide-antibiotic mixtures interact with model bacterial membranes by NR. 4 days of INTER/OFFSPEC time is requested for this first round of study.

Principal Investigator: Professor Jian Lu
Experimenter: Dr Mingrui Liao
Experimenter: Dr Arwel Hughes
Local Contact: Dr Maxmilian Skoda
Experimenter: Mr Zeyuan ZHUANG
Experimenter: Mr kangcheng shen
Experimenter: Dr Xuzhi Hu
Experimenter: Miss Tianhao Ge
Experimenter: Miss Caroline Ding

DOI: 10.5286/ISIS.E.RB2220143

ISIS Experiment Number: RB2220143

Publisher: STFC ISIS Neutron and Muon Source

Data format: RAW/Nexus
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Data Citation

The recommended format for citing this dataset in a research publication is as:
[author], [date], [title], [publisher], [doi]

For Example:
Professor Jian Lu et al; (2022): NR study of antimicrobial synergy from pairing of lipopeptides and antibiotics against drug-resistant bacteria, STFC ISIS Neutron and Muon Source, https://doi.org/10.5286/ISIS.E.RB2220143

Data is released under the CC-BY-4.0 license.