Sequencing-based diagnostics and monitoring of the resistance situation and epidemiology of pathogens (especially viruses and bacteria) is becoming increasingly important in university medicine. Thanks to the latest sequencing technologies, such as Nanopore, the prices per sequenced sample are moving into a diagnostically acceptable range. The research group uses the Nanopore technology and develops special bioinformatics-analytical pipelines to answer scientific questions, but also to improve patient care. More information can also be found on the 'CaSe'-Webseite.
The group is participating in the sequencing of the SARS-CoV-19 genomes and has been included in the NFDI4Microbiota COVID-19 and DeCOI national networks. Since the new coronavirus surveillance regulation of the Federal Ministry of Health (18 Januar 2021) the group also sequences samples from Thuringia and transmits the data to the Robert Koch Institute.
Current Projects
Holistic sequencing-based pathogen diagnostics - Transcriptomics-based diagnostics
Project period: 01.07.2021- 30.06.2026
The careless use of antibiotics until the late 1990s and the neglected pharmaceutical sector of the since the 1970s, have led to the increasing spread of multi-drug resistant pathogenic bacteria (MDR) due to selective pressure, and at the same time the number of substances still effective against them is decreasing. Therefore, targeted, effective therapy tailored to the resistance profile of the pathogen is essential to reduce selective pressure. However, this requires rapid diagnostics that capture genotype and phenotype as much as possible, which is currently only possible through a combination of culture-based (phenotype) and molecular (genotype) methods. Both have advantages and disadvantages, but overall these tests take too long. The goal of this project is to develop a new and rapid diagnostic platform based on transcriptome data that is capable of detecting not only species but also resistance phenotypes and other important characteristics of a microorganism.
The project is being conducted within the Leibniz Center for Photonics in Infection Research (LPI) under grant number 13N15720
Host response biomarkers for bacterial infections by RNA profiling and Raman spectroscopy
Project duration: 01.09.2020- 31.08.2023
Cooperation partners: Leiden University, Uppsala University, Wein University, University of Bolognia, Paul Ehrlich Institute (PEI)
Pathogenic bacteria, such as Staphylococcus aureus, can escape the immune response by invading host cells or by biofilm formation, leading to chronic recurrent infections. There is also evidence that, in addition to these escape strategies, bacteria specifically stimulate the immune system and suppress the immune response. Thus, it could be shown that Treg cells, which are differentiated by stimulation with the S. aureus toxin SpA-, act as anti-inflammatory counterparts of Th17. From other unknown S. aureus effectors lead to such immunosuppression and thus may play a critical role in establishing S. aureus persistence in chronic infections. This question, and the role of antimicrobial therapy in biofilm-associated infections, will be addressed in the project. The goal is to identify host markers that allow early indication of therapy success or failure, or chronicity. In this context, transcriptome data from host cells as well as bacteria will be collected and analyzed.
The project is being conducted within the Innovative Training Network (ITN) entitled Training towards Innovative Personalized Antibiotic Therapy (TIPAT) under grant numbers EUUZI72085 and is funded by the European Union's Horizon 2020 research and innovation program under Marie Skłodowska-Curie grant agreement No. 861323.
AI-assisted assay development for phenotypic carbapenem resistance by porin loss and efflux overexpression in Gram-negative bacteria.
More information can be found here: PREPLEX and in the PREPLEX-Video
Project period: 01.09.2020- 31.08.2025
Collaborative partners: Curetis GmbH, Ares Genetics GmbH
Carbapenem resistance in Gram-negative bacteria poses one of the greatest challenges to therapy and diagnostics. However, a carbapenem-resistant phenotype is not always due to a carbapenemase, an enzyme that inactivates reserve antibiotics. Often, this phenotype is caused by secondary mechanisms, such as porin loss or increased efflux, which can be well treated with targeted combination therapies. Unfortunately, routine culture-based diagnostics do not differentiate the genotype and phenotype, whereas classical PCR-based molecular diagnostics only detect the genotype. However, the phenotype is always genetically encoded, so it would have to be theoretically inferred from genomic data, but this would have to take into account highly complex regulatory mechanisms and countless genes and even more allelic variants. This can no longer be reconstructed using simple methods. Therefore, deep-learning processes will be applied to infer phenotypes from genomic data. In this context, molecular markers will also be identified that differentiate a non-carbapenemase-related carbapenem resistance phenotype in simple mRNA-based assays in order to make them diagnostically useful.
The project is carried out within the framework of the research campus InfectoGnostics and is funded by the German Federal Ministry of Education and Research under grant number 13GW0457A.