Interfaculty Institute of Microbiology and Infection Medicine

Genome Mining in Actinobacteria

Our current research aims at getting a better understanding for the genetic mechanisms involved in the biosynthesis of nature products and their evolution. Here we focus on the phylum Actinobacteria. To understand the variation of secondary metabolite gene clusters within the context of the species’ evolution, genome mining and comparative genomics approaches are combined.

Working with the genus Amycolatopsis as a model organism and furthermore having the Tuebingen Actinomycetes strain collection at hand we focus on the discovery of novel antibiotic producing biosynthetic gene clusters. We have established a bioinformatic pipeline that allows strain classification and subsequent prioritization of biosynthetic gene clusters. Candidate gene clusters are analyzed and characterized in the lab in our ongoing research. 

Bioinformatic Tools for Genome Mining in Bacteria

Bacterial natural products are one of the main sources for the discovery of novel drugs. However, classical cultivation approaches are usually costly and time-consuming and often lead to the rediscovery of known compounds. This is where bioinformatics can help selecting strains and prioritizing biosynthetic gene clusters.


autoMLST (automated Multi-Locus Sequence Tree) is a quick and user-friendly tool that allows rapid taxonomic classification of any given bacterial genome. An accurate species phylogeny is based on the alignment of multiple core genes. Thereby up to 20 uploaded genomes are set in context with a large genome database that includes type strains for bacterial species. Furthermore, autoMLST provides a calculation of the ANI (average nucleotide identity) a measure for species affiliation and allows an estimation of the strains’ biosynthetic potential.


The antibiotic resistant target seeker (ARTS) is a bioinformatic tool that allows prediction of genes that represent target genes of antibiotics. Any given genome sequence can be screened for core genes that fulfill three different criteria: 1) Proximity to a biosynthetic gene cluster, 2) duplication and 3) gene phylogeny that differs from species phylogeny. Based on these criteria antibiotic target genes can be identified. Additionally, known resistance genes are highlighted. Moreover, precomputed results from > 70.000 bacterial (meta-) genomes are available from the ARTS database (ARTS-DB).

The Evolution of Glycopeptide Antibiotics

Glycopeptides like vancomycin or teichoplain are antibiotics with activity against Gram-positive bacteria and are currently in clinical use as last resort antibiotics against MRSA infections. The glycopeptide antibiotics (GPAs) are structurally highly diverse. Genome mining studies showed that there is also a huge genetic diversity in the GPA biosynthesis genes and there is a pool of yet unknown GPA-like biosynthetic gene clusters. We use this pool of genomic sequences to study the evolution of GPAs. We are interested in the mechanisms that shaped the GPA diversity, like horizontal gene transfer, recombination, gene gain or loss and genomic rearrangement. We are looking for patterns in the distribution of GPAs throughout the bacterial kingdom and study how acquisition of a GPA biosynthetic gene cluster affects changes in the primary metabolism of the producer strains. In collaboration with the AG Stegmann we aim at identifying new structures and learn how to effectively manipulate GPA scaffolds.

Metagenome Mining

A huge variety of biosynthetic gene clusters is hidden in the “uncultivable” microbial world. We are trying to tap into this source by soil metagenome sequencing and heterologous expression of metagenomic biosynthetic gene clusters. In collaboration with the Group of Geoecology in Tübingen we regularly probe our study sites at the Schönbuch forest in Tübingen to get an overview on biosynthetic gene diversity in different soil communities, depending on the physicochemical properties of the study sites and the actual sampling conditions. Within the scope of this project a bioinformatic tool for metagenome mining is developed. We work on establishing a computational pipeline to identify candidate microorganisms from diverse microbiomes that have not been cultivated before and have the potential of producing novel compounds. We focus on obtaining near complete metagenome assembled genomes (MAGs) from complex environments, such as soil. We assess their taxonomic novelty and capabilities for producing novel compounds, and identify genes that they encode with the help of metatranscriptomics that they can be used as targets for their isolation. We also examine the metabolic pathways of the identified organisms to provide insights into what needs to be in the medium for them to be cultured.

EU Project SECRETed

ECRETed is an EU-H2020 multidisciplinary project involving multiple stakeholders. Goal of project is it to develop novel hybrid molecules with tailor-made properties obtained from the combination of biosynthetic genes of amphiphilic compounds (biosurfactants and siderophores) produced by marine and extremophilic microorganisms. Therefore the ‘mix and match’ approach is used where modular genetic elements will be combined to get new tailor-made compounds based on their amphipathic nature.

The Role of Secondary Metabolites in Bacterial Communities

A healthy plant microbiome is essential for the plant growth and resistance to pathogens. The plant microbiota cultures the plant during different seasons and a changing environment. But how can they resist such hard times? Since microbes produce a number of bioactive secundary metabolites, we hyopthesize, that these compound play a huge role in stabilizing and shaping the microbiome.
With the Arabidopsis thaliana synthetic community (SynCom) from the lab of Prof. Dr. Eric Kemen, we aim to uncover the interaction network of secondary metabolites produced by SynCom bacteria.