Limiting the Emergence of Antimicrobial Resistance to Urinary Tract Infection Antibiotics

Making our data and publications open has allowed us to further the reach of our work, including to research groups and countries which may not be able to afford access to paywalled journals or expensive software.

-Alasdair Hubbard, Beth James, Maria Rosa Domingo-Sananes

Tell us a bit about you and your research.

Antimicrobial resistance (AMR) in bacteria is a huge global health issue, which was associated with 4.95 million deaths globally in 2019 and is predicted to rise to 8.22 million by 2050. Our Microbial Evolution research team – made up of Maria Rosa Domingo-Sananes (Senior Lecturer, Biosciences), Beth James (Research Assistant, Microbiology), and Alasdair Hubbard (Senior Lecturer in Microbiology) - was established at NTU in 2022 and is focused on using experimental evolution to understand bacterial AMR to optimise the use of current and novel antibiotics to limit the emergence of AMR.

Tell us about a project you were involved in which used Open Research practices and principles?

This research project is focused on AMR in urinary tract infections (UTIs). AMR is a serious global health concern, with 4.95 million global deaths associated with AMR in 2019 alone. Additionally, UTIs are common in women and account for 22% of antimicrobial prescriptions, costing £47.6 million annually and resistance rates in UTIs caused by Escherichia coli.

In this proof of principle study, we aimed to determine whether AMR to one antibiotic affects the way bacteria respond to other antibiotics. Understanding this may allow us to inform how antibiotics are used to treat UTIs to select the most effective antibiotic, limit any subsequent AMR which may arise and improve the outcomes of treatment. By publishing all data and computer code used for analysis from this project open access, we wanted to encourage re-analysis, increase confidence in the outcomes of the project and encourage engagement with potential stakeholders and policymakers.

Describe the open research practice(s) employed in your study. Why did you select them?

Whole genome sequencing data from this project has been submitted to publicly available repositories. All raw quantitative data produced in the project from biological assays, as well as R code for analysis and production of figures, were made publicly available via the group's GitHub page. Ensuring all data is available via repositories and/or GitHub allows for re-analysis and replication of our work to ensure confidence in our data and outcomes. All analyses of data were performed using publicly available and free-to-use programmes to increase the accessibility and ability for replication.

The study was initially published on the preprint server BioRxiv. This allows others to read and comment on the study before, during and after peer review. The paper has now been accepted to the open access journal npj Antimicrobials and Resistance. Data availability statements are present in both preprint and peer-reviewed publications with links to the appropriate data and repositories.

Did you face any challenges in the project, and how did you overcome them?

The major challenge for this project was time and investment in learning and training how to put in a framework to share the raw and analysed data presented in the publications.    To allow for accurate replication and re-analysis, data had to be cleaned and organised so that it was clear what data was in each file. Additionally, as all assays included multiple samples and/or conditions, it was important to make clear which data related to which sample/condition and match these to the format used in the publication.

As this was the first publication from our newly established research group, we wanted to implement open data access policies for our publications and research from the outset. This has meant establishing group-specific repositories and navigating how best to make the data available to a wide audience, and therefore we decided to use GitHub due to its simplicity and wide availability and use of the platform.

Finally, to allow for replication of the analysis we used publicly available software, i.e. R packages and open source linux-based bioinformatics programmes. As these were different from our normal, paid-subscription programmes, training and learning was required. This has been of significant benefit to the group and their development.

What has been the impact of adopting open research practice(s) in your project?

This project has allowed us to adopt an open approach to research at the outset of publishing within our newly formed research group. This has given us a baseline to work to for future research projects and publications. It has also encouraged the group to seek out ways we can further the openness of our research outputs.

Making our data and publications open has allowed us to further the reach of our work, including to research groups and countries which may not be able to afford access to paywalled journals or expensive software. Releasing raw and analysed data, as well as the code for analysis publicly, has increased the confidence in and reproducibility of our work, as others can re-analyse the data for confirmation. Finally, the availability of whole genome sequence data will allow for new analysis for different projects or when new tools are published to generate new findings.

What did you learn from making this project ‘open’? Do you have any advice for others considering adopting open research practices?

While implementing open research has been intimidating, we have found it a rewarding experience. It has exposed us to different open research practices, allowing us to find the right path for our research and publications, which suits how we want to release our data publicly. Ensuring all data is available publicly has allowed us to be more confident in the outcomes and recommendations of our publication. Now we have established a baseline for open research, we can now continue to expand and refine to be more open as the group’s research also expands. Finally, it is exciting that the community and other research projects may use and include our data in new and innovative research projects, which will only lead to beneficial changes to society and exciting leaps forward in science.

Publications

BioRxiv preprint: https://doi.org/10.1101/2023.11.14.567005

This work has been presented as an oral presentation at the British Society for Antimicrobial Chemotherapy’s (BSAC) The Challenge of Urinary Tract Infections conference (2023, A.H.) and BSAC’s Antimicrobial Resistance Mechanisms Workshop (2023, B.J.).

In addition, this work was present as a poster at the Microbial Ecology and Evolution Hub-based Conference (2024, B.J.) and Microbiology Society Annual Conference (2024, B.J.). Part of this work was also in an oral presentation at the EMBO workshop on Predicting Evolution (2023, M.R.D.S.).

B.J. is an early career research who completed their integrated masters degree (MBiol) in Microbiology at NTU in 2023 and subsequently became a research assistant within the group.

Alasdair Hubbard | Nottingham Trent University

Maria Rosa Domingo-Sananes | Nottingham Trent University

Beth James (Research Assistant, Microbiology)