Projects Molekular Bacteriology

Projects Molekular Bacteriology

Targeting biofilm resistance

The proposed project is committed to develop innovative diagnostics and to strive for therapeutic solutions in patients suffering from biofilm-associated infections. The objective is to apply data-driven science in order to unlock the potential of microbial genomics. We will apply genome-wide association studies on an existing large sequence variation and gene expression dataset of a plethora of clinical Pseudomonas aeruginosa isolates that has been generated the last five years. New innovative treatment strategies that target biofilm resistance mechanisms to enhance the efficacy of current antibiotics will be validated and optimized in in vitro and in vivo biofilm models. Our approach does not only aim to provide a prediction of biofilm resistance based on the bacteria´s genotype but also to transform treatment paradigms for the management of chronic infections in order to combat biofilm-associated infections. 

Publications

Molecular resistance profiling

In spite of the initial enthusiasm and the huge literature on their diagnostic use, gene-detection-based molecular methods have not yet had the dramatic impact on routine diagnostic microbiology that many predicted. In order to further develop molecular testing methods and bring them into clinical practice, we will sequence a large number of clinical strains and correlate the DNA sequence variations with the resistance profiles of the clinical isolates. In the future, it will be of great importance to show that the use of molecular methods to determine the clonal identity and resistance profile of clinical strains has a significant impact on the management of multi-resistant infections in hospitals. 

Publications

Targeting biofilm resistance

Thoming JG, Tomasch J, Preusse M, Koska M, Grahl N, Pohl S, Willger SD, Kaever V, Musken M, Haussler S (2020) Parallel evolutionary paths to produce more than one Pseudomonas aeruginosa biofilm phenotype. NPJ Biofilms Microbiomes 6: 2.

Kordes A, Preusse M, Willger SD, Braubach P, Jonigk D, Haverich A, Warnecke G, Haussler S (2019) Genetically diverse Pseudomonas aeruginosa populations display similar transcriptomic profiles in a cystic fibrosis explanted lung. Nat Commun 10(1): 3397.

Erdmann J, Thoming JG, Pohl S, Pich A, Lenz C, Haussler S (2019) The Core Proteome of Biofilm-Grown Clinical Pseudomonas aeruginosa Isolates. Cells 8(10)

Müsken M, Pawar V, Schwebs T, Bähre H, Felgner S, Weiss S, Häussler S. Breaking the Vicious Cycle of Antibiotic Killing and Regrowth of Biofilm-Residing Pseudomonas aeruginosa. Antimicrob Agents Chemother. 2018 Nov 26;62(12).

Kordes A, Grahl N, Koska M, Preusse M, Arce-Rodriguez A, Abraham WR, Kaever V, Häussler S. Establishment of an induced memory response in Pseudomonas aeruginosa during infection of a eukaryotic host. ISME J. 2019 Apr 5. doi: 10.1038/s41396-019-0412-1. 

Müsken M, DiFiore S, Römling U, Häussler S (2010) 96-well plate based optical method for the quantitative and qualitative evaluation of Pseudomonas aeruginosa biofilm formation and its application for susceptibility testing. Nat Protoc. 5:1460-9. 

Blanka A, Düvel J, Dötsch A, Klinkert B, Abraham WR, Kaever V, Ritter C, Narberhaus F, Häussler S (2015) Constitutive production of c-di-GMP is associated with mutations in a variant of Pseudomonas aeruginosa with altered membrane composition. Science Signaling 14;8(372).

Bielecki P, Jensen V, Schulze W, Gödeke J, Strehmel J, Eckweiler D, Nicolai T, Bielecka A, Wille T, Gerlach RG, Häussler S (2015) Cross talk between the response regulators PhoB and TctD allows for the integration of diverse environmental signals in Pseudomonas aeruginosa. Nucleic Acids Res. 43(13):6413-25. 

Molecular resistance profiling

Grekov I, Thöming GJ, Kordes A, Häussler S (2020) Evolution of Pseudomonas aeruginosa towards higher fitness under standard laboratory conditions. ISME J 15(4): 1165-1177.

Donnert M, Elsheikh S, Arce Rodriguez A, Pawar V, Braubach P, Jonigk D, Haverich A, Weiss S, Müsken M, Häussler S. (2020) Targeting bioenergetics is key to counteracting the drug-tolerant state of biofilm-grown bacteria. PLoS Pathog 16(12): 1-22

Felgner S, Preusse M, Beutling U, Stahnke S, Pawar V, Rohde M, Brönstrup M, Stradal T, Häussler S. (2020) Host-induced spermidine production in motile Pseudomonas aeruginosa triggers phagocytic uptake. Elife 9. 

Khaledi A, Weimann A, Schniederjans M, Asgari E, Kuo TH, Oliver A, Cabot G, Kola A, Gastmeier P, Hogardt M, Jonas D, Mofrad MR, Bremges A, McHardy AC, Haussler S (2020) Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics. EMBO Mol Med: 12(3): e10264.

Hornischer K, Khaledi A, Pohl S, Schniederjans M, Pezoldt L, Casilag F, Muthukumarasamy U, Bruchmann S, Thöming J, Kordes A, Häussler S. BACTOME-a reference database to explore the sequence- and gene expression-variation landscape of Pseudomonas aeruginosa clinical isolates. Nucleic Acids Res. 2019 Jan 8;47(D1):D716-D720. 

Dötsch A, Schniederjans M, Khaledi A, Hornischer K, Schulz S, Bielecka A, Eckweiler D, Pohl S, Häussler S. (2015) The Pseudomonas aeruginosa transcriptional landscape is shaped by environmental heterogeneity and genetic variation. MBio 6(4):e00749

Schulz S, Eckweiler D, Bielecka A, Nicolai T, Franke R, Dötsch A, Hornischer K, Bruchmann S, Düvel J, Häussler S (2015) Elucidation of Sigma Factor-Associated Networks in Pseudomonas aeruginosa Reveals a Modular Architecture with Limited and Function-Specific Crosstalk. PLoS Pathog. 11(3):e1004744. 

Pommerenke C, Müsken M, Becker T, Dötsch A, Overhage J, Klawonn F, Häussler S (2010) Global Phenotype-Genotype correlations in Pseudomonas aeruginosa. PLoS Pathog 26(3): pii: e1001074.