Antimicrobial resistance (AMR) is one of the largest public health concerns at global level. Continuous surveillance of the AMR situation is essential to compare situations between countries and regions and determine effects of interventions. AMR surveillance programs typically focus on isolates from patients. It has however, proven difficult and expensive to establish comparable surveillance globally.

Furthermore, the clinical perspective is not enough for us to completely understand how AMR spreads and evolves. AMR is an inherent component of the microbial communities and ecosystems surrounding us. From our natural environments, through agriculture, animal populations (wild and domesticated), through our urban societies and us – our microbiomes – and then once in a while, AMR “surfaces” as something we detect in sick individuals, who are being treated for an infection. This last part, is of course where we tend to notice AMR, because this is where it causes problems, for example with patients and medical staff experiencing difficult-to-treat infections. The bigger picture going far beyond the patient, is also known as one health (McEwen & Collignon 2018, DOI: 10.1128/microbiolspec.ARBA-0009-2017).

Photo credit: Trey Ratcliff, Creative Commons Attribution

So if we are to understand the dynamics of the spread and emergence of AMR, we need to study AMR in a diverse portfolio of contexts: the urban society context, is one of these. Sewage, or waste water, is a way to “capture” the combined microbial community coming from the people in an urban area (Aarestrup and Woolhouse 2020, DOI: 10.1126/science.aba3432). The majority of these people are not sick, but they all have a microbiome full of bacteria. Some of these bacteria carry resistance-conferring genes, which would allow those bacteria to tolerate antimicrobial treatments, should they find themselves in a situation where they are causing infection. These genes are what we’re looking for, because they can be shared between bacteria in a bacterial community and spread that way. What we use to study these genes from urban sewage, is called metagenomics (Carrido-Cardenas & Manzano-Agugliaro 2017, DOI: 10.1007/s00294-017-0693-8).

We have since 2016 been piloting whether it is feasible to perform continuous surveillance of AMR based on globally collected urban sewage (Hendriksen et al 2019, DOI: 10.1038/s41467-019-08853-3).

This web app, is a way for us to share our insights from performing metagenomics on urban sewage samples in our search for resistance-genes. The web app is supposed to allow users to access the knowledge coming from our research, in the most basic way possible. The main disclaimer here therefore, is that there’s really nothing basic about metagenomics, but we implore you to check out the data anyway, and have fun with it!

The application

The app: in the “Resistance” tab, the user is allowed to look at the predicted antimicrobial resistance levels detected in the sewage samples from those places. The “predicted” antimicrobial resistance, is based on the presence of genes that are known to cause resistance towards a particular class of antimicrobial drugs. In the “Tables” tab, the user is given a tabular view of the data, so that the numbers depicted on the graphs (and many other numbers not visualized) can be explored. This tabular view has search and filter functions and the data can be downloaded with a readme file explaining how the data was produced.

Research impact