Kiel researchers develop software that reconstructs the metabolism of bacteria

The gapseq software uses information about genetic material to create computer models of bacteria.

Humans are colonized by an unimaginably large variety of microorganisms. The natural microbiome, i.e. the totality of microorganisms that live in and on a body, is of primary importance for the whole organism: it supports food utilization, for example, and is important for maintaining the balance in the gut. Disruptions to the microbiome can jointly influence many diseases, such as chronic inflammatory bowel diseases or diabetes. Research into the highly complex interactions between host organism and microorganisms, as well as between the microorganisms themselves, is therefore becoming increasingly important. Researchers at Kiel University (CAU) have now developed a software tool which allows them to quickly and accurately build computer models of the metabolism of bacteria present in the microbiome. Dr. Johannes Zimmermann, Professor Christoph Kaleta and Professor Silvio Waschina recently published the software called gapseq in the renowned scientific journal Genome Biology.

Gapseq uses existing information from biochemical databases that contain details about which enzymes enable the conversion of substances. The researchers linked this information with the genetic information of the bacteria, which was obtained from sequencing. “We have the genetic information of the bacteria, but we don't know exactly what they do in their natural environment, such as the gut. With the gapseq software, we use genetic information to determine which metabolic processes the bacteria can perform, and from this we create complex metabolic networks for each individual bacterium," explained Silvio Waschina, Professor of Nutri-informatics at the Faculty of Agricultural and Nutritional Sciences at the CAU and member of the Cluster of Excellence "Precision Medicine in Chronic Inflammation" (PMI). Each network connects the substances that are converted into one another by the respective bacteria. In turn, these metabolic networks of the individual bacteria also interact with each other. The software calculates these complex interactions, and thus simulates how the bacterial community works in its entirety. "For example, we can also predict how the intestinal microbiome will react to certain diets, or how it might metabolize specific active substances in drugs," said Waschina.

"The previous methods do not work as well and do not use all available data to predict the metabolic networks of the bacteria," explained first author Dr. Johannes Zimmerman, research associate at the Institute of Experimental Medicine at the CAU and member of the Cluster of Excellence PMI. “In order to be able to identify the interactions of the microbiome, it is important that the predictions are as accurate as possible. Here, gapseq is significantly better than previous methods, which we have been able to prove with a comprehensive comparison," added Zimmermann.

The scientists have already been able to use gapseq in specific research projects. Together with other members of the Cluster of Excellence PMI, they showed how the metabolism of the intestinal microbiome is related to the response to antibody treatment in chronic inflammatory bowel diseases (IBD). Antibody treatments using so-called biologicals are known to only work in some IBD patients. "We were able to show that patients in whom biologicals successfully combat symptoms already had a completely different metabolism in their microbiome before the start of treatment, compared with patients in whom the treatment does not work," explained Professor Christoph Kaleta, head of the Medical Systems Biology working group at the Institute of Experimental Medicine at the CAU, also a member of the Cluster of Excellence PMI as well as the Collaborative Research Centre "Origin and Function of Metaorganisms". "On the basis of these results, dietary interventions could be developed in such a way that they specifically influence the metabolism of the intestinal microbiome, and thus possibly improve the response to treatment," continued Kaleta, who co-developed gapseq.

The researchers are currently using gapseq in cooperation with the Department of Pediatric and Adolescent Medicine at the University Medical Center Schleswig-Holstein (UKSH), Campus Lübeck, to understand how the gut of preterm infants are colonized and which metabolic functions are important in this process. The colonization of the gut with microorganisms is very important for the development of preterm infants, as otherwise infections or even sepsis may occur. It is therefore important to understand what happens in the gut of preterm infants and how the colonization could be influenced by a targeted diet or by probiotics. In cooperation with Professor Jan Rupp and Dr. Julia Pagel from the Department of Infectious Diseases and Microbiology at the UKSH, Campus Lübeck, and Professor Christoph Härtel from the University Hospital of Würzburg (UKW), the team is collecting stool samples from the diapers of preterm infants. From these samples, they isolate the genetic information of the bacteria present. Gapseq can use this data to reconstruct the metabolism of the intestinal microbiome of the preterm infants.

The gapseq program can be used by interested research teams worldwide and is open source software. "We have already had several requests from groups around the world, with very different priority research areas. These range from biogas plants to soil bacteria, right through to the symbiosis of bacteria with algae," explained Zimmermann. "Knowing that our system is advancing research in such different areas is a very good feeling," added Zimmermann.

Scientific contacts:

Prof. Dr. Silvio Waschina
Institute of Human Nutrition and Food Science, Kiel University (CAU)
0431 880-4681

Prof. Dr. Christoph Kaleta
Institute of Experimental Medicine, Kiel University (CAU)
0431 500 30340

grafical image of a network
© Kiel Life Science

Symbolic image. With the newly developed software tool, researchers can use existing data to predict the metabolic networks of bacteria.

three portrait photos
© v.l.: G. Dethlefsen, private, cluster of excellence PMI.

The authors of the gapseq tool from left: Prof. Silvio Waschina, Dr. Johannes Zimmermann, Prof. Christoph Kaleta, all from Kiel University (CAU).

Original publication:

Johannes Zimmermann, Christoph Kaleta, Silvio Waschina: gapseq: informed prediction of bacterial metabolic pathways and reconstruction of accurate metabolic models, Genome Biology (2021).  DOI:    


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About the Cluster of Excellence PMI

The Cluster of Excellence "Precision Medicine in Chronic Inflammation" (PMI) is being funded from 2019 to 2025 through the German Excellence Strategy (ExStra). It succeeds the "Inflammation at Interfaces” Cluster, which was already funded in two periods of the Excellence Initiative (2007-2018). Around 300 members from eight institutions at four locations are involved: Kiel (Kiel University, University Medical Center Schleswig-Holstein (UKSH), Muthesius University of Fine Arts and Design, Kiel Institute for the World Economy (IfW), Leibniz Institute for Science and Mathematics Education (IPN)), Lübeck (University of Lübeck, University Medical Center Schleswig-Holstein (UKSH)), Plön (Max Planck Institute for Evolutionary Biology) and Borstel (Research Center Borstel - Leibniz Lung Center).

The goal is to translate interdisciplinary research findings on chronic inflammatory diseases of barrier organs to healthcare more intensively, as well as to fulfil previously unsatisfied needs of the patients. Three points are important in the context of successful treatment, and are therefore at the heart of PMI research: the early detection of chronic inflammatory diseases, the prediction of disease progression and complications, and the prediction of individual responses to treatment.

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