Search bioRxiv⌕ Search

Biology subjects

Bradbury, J.

Publications and source records attributed to Bradbury, J..

2 recordsLinked to original sources

A novel ciprofloxacin analogue enables daptomycin-mediated killing of resistant Staphylococcus aureus by increasing septum formation

Quinolone antibiotics such as ciprofloxacin inhibit DNA gyrase, leading to DNA double-strand breaks that result in rapid bacterial killing and induction of the mutagenic SOS DNA repair response. By contrast, the ciprofloxacin analogue IMP-1700 inhibits ciprofloxacin-induced SOS, suggesting a novel mechanism of action. Here, we provide evidence that IMP-1700 targets the quinolone binding domain of DNA gyrase but triggers a significantly higher frequency of division septa in S. aureus compared with other DNA gyrase targeting antibiotics, including ciprofloxacin. In keeping with this finding, the lipopeptide antibiotic daptomycin, which targets the division septum, bound more strongly to IMP-1700-treated cells relative to S. aureus exposed to other DNA gyrase inhibitors, leading to increased bacterial killing. This finding extended to a panel of paired daptomycin susceptible and resistant clinical isolates. We conclude that the ciprofloxacin analogue IMP-1700 has distinct effects on the cell envelope of S. aureus, despite appearing to share the same target as the parent drug, which result in the resensitisation of daptomycin resistant bacteria to the lipopeptide antibiotic.

microbiology↗

PhenoMeNal: Processing and analysis of Metabolomics data in the Cloud

BackgroundMetabolomics is the comprehensive study of a multitude of small molecules to gain insight into an organisms metabolism. The research field is dynamic and expanding with applications across biomedical, biotechnological and many other applied biological domains. Its computationally-intensive nature has driven requirements for open data formats, data repositories and data analysis tools. However, the rapid progress has resulted in a mosaic of independent - and sometimes incompatible - analysis methods that are difficult to connect into a useful and complete data analysis solution.\n\nFindingsThe PhenoMeNal (Phenome and Metabolome aNalysis) e-infrastructure provides a complete, workflow-oriented, interoperable metabolomics data analysis solution for a modern infrastructure-as-a-service (IaaS) cloud platform. PhenoMeNal seamlessly integrates a wide array of existing open source tools which are tested and packaged as Docker containers through the projects continuous integration process and deployed based on a kubernetes orchestration framework. It also provides a number of standardized, automated and published analysis workflows in the user interfaces Galaxy, Jupyter, Luigi and Pachyderm.\n\nConclusionsPhenoMeNal constitutes a keystone solution in cloud infrastructures available for metabolomics. It provides scientists with a ready-to-use, workflow-driven, reproducible and shareable data analysis platform harmonizing the software installation and configuration through user-friendly web interfaces. The deployed cloud environments can be dynamically scaled to enable large-scale analyses which are interfaced through standard data formats, versioned, and have been tested for reproducibility and interoperability. The flexible implementation of PhenoMeNal allows easy adaptation of the infrastructure to other application areas and omics research domains.

bioinformatics↗