How can a precise characterisation of microbial communities result in the development of new strategies against biofilm-associated infections?

What is this research project about?

Biofilme: There is a lack of treatment options for infections associated with them.

What is this research project about?

Bacteria in biofilms are embedded in a self-produced extracellular matrix and exhibit an increased resistance to adverse conditions. In the human host, biofilm bacteria are responsible for persistent infections and efficiently withstand antibiotic treatment and the host immune response. Once a bacterial biofilm infection is established it becomes very difficult to eradicate, even in the absence of genotypic resistance. Biofilm infections affect millions of people and every year chronic infections in patients due to biofilm formation are a multi-billion Euro burden to national healthcare systems. With progress of medical sciences, more and more indwelling devices for the purpose of medical treatments and foreign body implants are applied. Infection continues to be a major complication of their use. Also, there are biofilm infections not associated with foreign bodies, such as chronic infections of the lungs of cystic fibrosis patients and of patients with chronic obstructive pulmonary diseases. Ongoing inflammation and changes in the structure and function of the affected tissue largely determine morbidity and mortality in these patients.

We want to identify biomarkers whose presence is correlated with the resistance of the Pseudomonas aeruginosa biofilm and genetic / metabolic patterns and which characterize the switch to the establishment of pathogenic biofilms on implants. This will serve to develop a diagnostic tool for biofilm resistance and disease excitation Profiling and innovative treatment strategies targeting biofilm resistance mechanisms.

What’s the current status?

Although chronic biofilm-associated infections have been extensively studied, there are many open questions and the general recalcitrance of biofilm-grown bacteria is only incompletely understood. The successful use of antibiotics to eradicate biofilm-associated infection relies on our ability to overcome several main problems. First, for a more targeted anti-biofilm therapy, knowledge on the biofilm-specific resistance profile of individual bacterial isolates is essential, as well as knowledge on when natural colonizing bacterial communities transition to pathogenic biofilms e.g. on implants. In addition, new therapy options will have to be developed to overcome the second limitation of current treatment, which is the general recalcitrance of biofilm populations.

Biofilms of clinical idolates of Pseudomonas aeruginosa, living cells are green, dead cells are red. Source: TWINCORE / Jann Thöming

What are the project goals?

The combination of detailed information of the infecting pathogens with advanced phenotypic and genotypic profiling methodologies holds considerable promise for improving strategies to combat chronic biofilm-associated infections. Knowledge on etiological mechanisms underlying the evolution of biofilm resistance has the promise to change the way physicians treat chronic infections. This work is undertaken with the view to address a critical unmet medical need and to provide the necessary conditions to develop effective individualized diagnostic and therapeutic intervention strategies for the control of biofilm-associated infections.

How do we get there?

Our research groups have established extensive expertise in the analysis of the structure, assembly and microbiological diversity of medical biofilms, and have applied methodologies including DNA/RNA sequencing and machine learning approaches to describe the genomic and transcriptional landscape of infecting pathogens in vitro and ex vivo. Within RESIST we want to transfer gained knowledge and experience from our work on bacterial biofilms and establish a genome-based prediction of bacterial phenotypes by integrating complex OMICS-data also using machine learning classifiers, phylogenomic clustering and feature selection techniques.

Biofilms of clinical idolates of Pseudomonas aeruginosa, living cells are green, dead cells are red. Source: TWINCORE / Jann Thöming


Project title: Biofilm profling

Prof. Dr. Susanne Häußler

Projects: C1, C2

Prof. Dr. Meike Stiesch

Projects: C1, C2

Project C1 Publications

Publications 2024

Tetramerization is essential for the enzymatic function of the Pseudomonas aeruginosa virulence factor UDP-glucose pyrophosphorylase. Dirr, L., S. Cleeves, I. Ramón Roth, L. Li, T. Fiebig, T. Ve, S. Häussler, A. Braun, M. von Itzstein, and J. I. Führing. 2024.  mBio 15: e0211423.

Publications 2023

An expanded CRISPR-Cas9-assisted recombineering toolkit for engineering genetically intractable Pseudomonas aeruginosa isolates. Pankratz D, Gomez NO, Nielsen A, Mustafayeva A, Gür M, Arce-Rodriguez F, Nikel PI, Häussler S, Arce-Rodriguez A. Nat Protoc. 2023 Nov;18(11):3253-3288.

Transcriptome Dynamics of Pseudomonas aeruginosa during Transition from Overlapping To Non-Overlapping Cell Cycles. Alpers K, Vatareck E, Gröbe L, Müsken M, Scharfe M, Häussler S, Tomasch J.  mSystems. 2023 Feb 14:e0113022.

The Origin of the Intracellular Silver in Bacteria: A Comprehensive Study using Targeting Gold-Silver Alloy Nanoparticles. Streich C, Stein F, Jakobi J, Ingendoh-Tsakmakidis A, Heine N, Rehbock C, Winkel A, Grade S, Kühnel M, Migunov V, Kovács A, Knura T, Stiesch M, Sures B, Barcikowski S. Adv Healthc Mater. 2023 Dec;12(30):e2302084. doi: 10.1002/adhm.202302084. Epub 2023 Sep 17. PMID: 37661312.

Publications 2022

Distinct Long- and Short-Term Adaptive Mechanisms in Pseudomonas aeruginosa. Koska M, Kordes A, Erdmann J, Willger SD, Thöming JG, Bähre H, Häussler S. Microbiol Spectr. 2022 Dec 21;10(6):e0304322. Epub 2022 Nov 14.

Genomic epidemiology of clinical ESBL-producing Enterobacteriaceae in a German hospital suggests infections are primarily community- and regionally-acquired. Neffe L, Forde TL, Oravcova K, Köhler U, Bautsch W, Tomasch J, Häussler S.  Microb Genom. 2022 Dec;8(12):mgen000901.

Transcriptional Profiling of Pseudomonas aeruginosa Infections. Thöming JG, Häussler S.  Adv Exp Med Biol. 2022;1386:303-323.

Evolution of biofilm-adapted gene expression profiles in lasR-deficient clinical Pseudomonas aeruginosa isolates. Jeske A, Arce-Rodriguez A, Thöming JG, Tomasch J, Häussler S. NPJ Biofilms Microbiomes.

Pseudomonas aeruginosa Is More Tolerant Under Biofilm Than Under Planktonic Growth Conditions: A Multi-Isolate Survey. Thöming JG, Häussler S.  Front Cell Infect Microbiol.

Pseudomonas aeruginosa post-translational responses to elevated c-di-GMP levels. Bense S, Witte J, Preuße M, Koska M, Pezoldt L, Dröge A, Hartmann O, Müsken M, Schulze J, Fiebig T, Bähre H, Felgner S, Pich A, Häussler S. Mol Microbiol.

Critical Assessment of Metagenome Interpretation: the second round of challenges. Meyer F, Fritz A, Deng ZL, Koslicki D, Lesker TR, Gurevich A, Robertson G, Alser M, Antipov D, Beghini F, Bertrand D, Brito JJ, Brown CT, Buchmann J, Buluç A, Chen B, Chikhi R, Clausen PTLC, Cristian A, Dabrowski PW, Darling AE, Egan R, Eskin E, Georganas E, Goltsman E, Gray MA, Hansen LH, Hofmeyr S, Huang P, Irber L, Jia H, Jørgensen TS, Kieser SD, Klemetsen T, Kola A, Kolmogorov M, Korobeynikov A, Kwan J, LaPierre N, Lemaitre C, Li C, Limasset A, Malcher-Miranda F, Mangul S, Marcelino VR, Marchet C, Marijon P, Meleshko D, Mende DR, Milanese A, Nagarajan N, Nissen J, Nurk S, Oliker L, Paoli L, Peterlongo P, Piro VC, Porter JS, Rasmussen S, Rees ER, Reinert K, Renard B, Robertsen EM, Rosen GL, Ruscheweyh HJ, Sarwal V, Segata N, Seiler E, Shi L, Sun F, Sunagawa S, Sørensen SJ, Thomas A, Tong C, Trajkovski M, Tremblay J, Uritskiy G, Vicedomini R, Wang Z, Wang Z, Wang Z, Warren A, Willassen NP, Yelick K, You R, Zeller G, Zhao Z, Zhu S, Zhu J, Garrido-Oter R, Gastmeier P, Hacquard S, Häußler S, Khaledi A, Maechler F, Mesny F, Radutoiu S, Schulze-Lefert P, Smit N, Strowig T, Bremges A, Sczyrba A, McHardy AC. Nat Methods.

Rapid and accurate identification of ribosomal RNA sequences via deep learning. Deng ZL, Münch PC, Mreches R, McHardy AC. Nucleic Acids Res.

Publications 2021

Quo vadis clinical diagnostic microbiology? Haag S, Häussler S. Clin Microbiol Infect.

Removable denture is a risk indicator for peri-implantitis and facilitates expansion of specific periodontopathogens: a cross-sectional study. Grischke J, Szafrański SP, Muthukumarasamy U, Haeussler S, Stiesch M. BMC Oral Health.

Publications 2020

Parallel evolutionary paths to produce more than one Pseudomonas aeruginosa biofilm phenotype. Thöming JG, Tomasch J, Preusse M, Koska M, Grahl N, Pohl S, Willger SD, Kaever V, Müsken M, Häussler S. NPJ Biofilms Microbiomes.

Genetic determinants of Pseudomonas aeruginosa fitness during biofilm growth. Schinner S, Engelhardt F, Preusse M, Thöming JG, Tomasch J, Häussler S. Biofilm.

Organism-specific depletion of highly abundant RNA species from bacterial total RNA. Engelhardt F, Tomasch J, Häussler S.  Access Microbiol. 

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

Analysis of the organization and expression patterns of the convergent Pseudomonas aeruginosa lasR/rsaL gene pair uncovers mutual influence. Schinner S, Preusse M, Kesthely C, Häussler S. Mol Microbiol. 

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

Evolution of Pseudomonas aeruginosa toward higher fitness under standard laboratory conditions. Grekov I, Thöming JG, Kordes A, Häussler S. ISME J.

Expression of the MexXY Aminoglycoside Efflux Pump and Presence of an Aminoglycoside-Modifying Enzyme in Clinical Pseudomonas aeruginosa Isolates Are Highly Correlated. Seupt A, Schniederjans M, Tomasch J, Häussler S.  Antimicrob Agents Chemother.

Biofilm formation on zirconia and titanium over time-An in vivo model study. Desch A, Freifrau von Maltzahn N, Stumpp N, Dalton M, Yang I, Stiesch M.  Clin Oral Implants Res. 2020 Sep;31(9):865-880. doi: 10.1111/clr.13632. Epub 2020 Jul 9. PMID: 32583509.

Non-Invasive Luciferase Imaging of Type I Interferon Induction in a Transgenic Mouse Model of Biomaterial Associated Bacterial Infections: Microbial Specificity and Inter-Bacterial Species Interactions. Rahim MI, Winkel A, Lienenklaus S, Stumpp NS, Szafrański SP, Kommerein N, Willbold E, Reifenrath J, Mueller PP, Eisenburger M, Stiesch M.  Microorganisms. 2020 Oct 21;8(10):1624. doi: 10.3390/microorganisms8101624. PMID: 33096869; PMCID: PMC7589032.

Predicting antimicrobial resistance in Pseudomonas aeruginosa with machine learning-enabled molecular diagnostics. 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, Häussler S. EMBO Mol Med. 2020 Mar 6;12(3):e10264. doi: 10.15252/emmm.201910264. Epub 2020 Feb 12. PMID: 32048461; PMCID: PMC7059009.

Publications 2019

Establishment of an induced memory response in Pseudomonas aeruginosa during infection of a eukaryotic host. Kordes A, Grahl N, Koska M, Preusse M, Arce-Rodriguez A, Abraham WR, Kaever V, Häussler S. ISME J.

Genetically diverse Pseudomonas aeruginosa populations display similar transcriptomic profiles in a cystic fibrosis explanted lung. Kordes A, Preusse M, Willger SD, Braubach P, Jonigk D, Haverich A, Warnecke G, Häussler S. Nat Commun.

The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens. Zhou N, Jiang Y, Bergquist TR, Lee AJ, Kacsoh BZ, Crocker AW, Lewis KA, Georghiou G, Nguyen HN, Hamid MN, Davis L, Dogan T, Atalay V, Rifaioglu AS, Dalkıran A, Cetin Atalay R, Zhang C, Hurto RL, Freddolino PL, Zhang Y, Bhat P, Supek F, Fernández JM, Gemovic B, Perovic VR, Davidović RS, Sumonja N, Veljkovic N, Asgari E, Mofrad MRK, Profiti G, Savojardo C, Martelli PL, Casadio R, Boecker F, Schoof H, Kahanda I, Thurlby N, McHardy AC, Renaux A, Saidi R, Gough J, Freitas AA, Antczak M, Fabris F, Wass MN, Hou J, Cheng J, Wang Z, Romero AE, Paccanaro A, Yang H, Goldberg T, Zhao C, Holm L, Törönen P, Medlar AJ, Zosa E, Borukhov I, Novikov I, Wilkins A, Lichtarge O, Chi PH, Tseng WC, Linial M, Rose PW, Dessimoz C, Vidulin V, Dzeroski S, Sillitoe I, Das S, Lees JG, Jones DT, Wan C, Cozzetto D, Fa R, Torres M, Warwick Vesztrocy A, Rodriguez JM, Tress ML, Frasca M, Notaro M, Grossi G, Petrini A, Re M, Valentini G, Mesiti M, Roche DB, Reeb J, Ritchie DW, Aridhi S, Alborzi SZ, Devignes MD, Koo DCE, Bonneau R, Gligorijević V, Barot M, Fang H, Toppo S, Lavezzo E, Falda M, Berselli M, Tosatto SCE, Carraro M, Piovesan D, Ur Rehman H, Mao Q, Zhang S, Vucetic S, Black GS, Jo D, Suh E, Dayton JB, Larsen DJ, Omdahl AR, McGuffin LJ, Brackenridge DA, Babbitt PC, Yunes JM, Fontana P, Zhang F, Zhu S, You R, Zhang Z, Dai S, Yao S, Tian W, Cao R, Chandler C, Amezola M, Johnson D, Chang JM, Liao WH, Liu YW, Pascarelli S, Frank Y, Hoehndorf R, Kulmanov M, Boudellioua I, Politano G, Di Carlo S, Benso A, Hakala K, Ginter F, Mehryary F, Kaewphan S, Björne J, Moen H, Tolvanen MEE, Salakoski T, Kihara D, Jain A, Šmuc T, Altenhoff A, Ben-Hur A, Rost B, Brenner SE, Orengo CA, Jeffery CJ, Bosco G, Hogan DA, Martin MJ, O’Donovan C, Mooney SD, Greene CS, Radivojac P, Friedberg I. Genome Biol. 2019 Nov 19;20(1):244.

Diversity patterns of bacteriophages infecting Aggregatibacter and Haemophilus species across clades and niches. Szafrański SP, Kilian M, Yang I, Bei der Wieden G, Winkel A, Hegermann J, Stiesch M.  ISME J.

Publications of the Project C1