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Poster

Analysis of a Medically Relevant Microbial Community in a Bioreactor

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons86449

Riedele,  C.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86468

Schmidt,  J. K.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86446

Regestein,  L.
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;
RWTH, Aachen;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons86448

Reichl,  U.
Otto-von-Guericke-Universität Magdeburg;
Bioprocess Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, Max Planck Society;

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Zitation

Riedele, C., Schmidt, J. K., Regestein, L., & Reichl, U. (2007). Analysis of a Medically Relevant Microbial Community in a Bioreactor. Poster presented at Microbial Community Networks, Wernigerode, Germany.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-97B1-2
Zusammenfassung
Pseudomonas aeruginosa, Burkholderia cepacia and Staphylococcus aureus are opportunistic infectants, which occur as mixed cultures in the lungs of cystic fibrosis (CF) patients. Knowledge on possible interactions and growth characteristics of the microbial community in the lung obviously cannot be obtained in situ. It would be very desirable to be able to predict the mixed culture’s reaction, e.g. on antibiotic treatment, for optimal therapy of patients. We established a mixed culture in a chemostat bioreactor and use it as a model system related to the microbial community in CF lungs. Our experimental setup ensures defined and controllable conditions for the mixed culture and highly reproducible results. With comprehensive quantitative analytical methods we study bacterial growth characteristics and metabolic activity. In combination with mathematical modelling we focus on identifying microbial interactions and analyze the dynamics of the system, e.g. by disturbing the quasi steady state in chemostat experiments. In previous studies an apparent coexistence of at least two of the species was shown for more than 33 volume exchanges [1]. Also with complex models that e.g. include amino acids alternatively as a) co-substrate, b) mixed substrate or c) second carbon source, the experimental results of the three species culture could not be described in silico with adequate accuracy. This indicates that additional single species properties or interactions between the different species need to be included in corresponding models. From antibiotic pulse experiments we hope to gain further insight about the validity of existing models and learn more about possible other interactions. For measuring absolute and species specific cell numbers in mixed culture samples, a quantitative T-RFLP method was established and optimized [1]. Here, we show the applicability of our method as a valid quantification tool for cell numbers of the three species in single and mixed culture after treatment with ceftazidim, an antibiotic used in therapy of CF-patients. T-RFLP derived cell numbers are compared to plate counts and viability staining as reference methods. Additionally, we will present results of antibiotic pulse experiments and simulation studies of single and mixed cultures. The experimental part was realized in stirred tank reactors in a parallel small-scale system with off-gas analyser and a digital process control system (VL = 200 mL, fedbatch-pro®, GA4 and EasyAccess, dasgip, Germany). For modelling and simulation Matlab 7.1 (The MathWorks, Inc.) was used. Quantitative analysis of amino acids and ceftazidim was done by HPLC methods (anion exchange chromatography, DX600, Dionex and reversed phase chromatography, Agilent 1200, Agilent). Glucose was determined with an automated enzyme detector (YSI 7100 MBS, Kreienbaum wiss. Meßsysteme). [1] Schmidt, J.K. et al.: (2007) BiotechBioeng 96(4):738-756