Researchers Create Database of Antibiotic-Resistant Bacteria

Researchers at the Technical University of Denmark (DTU) have created a “Wikipedia” for antibiotic-resistant bacteria. Based on 214,000 microbiome samples, the platform will help public health authorities and healthcare workers track the problem of antibiotic resistance across countries, people, and environments.

In the future, even a small infection can become life-threatening for people if disease-causing bacteria become resistant to traditional treatment with antibiotics. To gain an understanding of how antibiotic resistance is spreading across the world, it is important to know where, which and how many resistance genes are found in all the environments that surround us. The genes that provide resistance can spread between animals, humans, and the environment.

Today, there is a large amount of data available in various online repositories and a number of limited data sets on the occurrence of resistant bacteria in, for example, sewage, soil, animals, or humans. But the data is not actively being used, because it until now has been difficult to get access to, handle, and, especially, utilize these large datasets due to the computing power needed.

To build the freely available database, the team at DTU National Food Institute analyzed 214,000 samples from, among other things, animals, humans, and soil, and organized them in a way that makes it possible for others to use them.

"You can compare it to a large encyclopedia, like Wikipedia, which collects knowledge from many different sources and organizes it in a way so that everyone can access it. In the same way, we collect data on antibiotic resistance in bacteria and share it with everyone," says Hannah-Marie Martiny PhD-student at the DTU National Food Institute and one of the driving forces behind the database.

Analysis of the 214,000 samples required almost 300 terabytes and took months to complete, even with high-performance computing capabilities.

"Such large quantities of data are interesting because we can find new patterns and connections between disease-causing microorganisms and antibiotic resistance,” Martiny says. “For example, we can see that certain types of antibiotic resistance have very different prevalence in different parts of the world. This knowledge we can use to tailor guidelines on how to combat resistance in different places in the world.” 

The work is detailed in a recent issue of PLoS Biology.