Strategies for optimized biotechnological production of rhamnolipids:



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: Forum Life Science 2013 March 13-14, 2013, Technische Universität München - Garching Marius Henkel, Anke Schmidberger, Christian Kühnert, Janina Beuker, Thomas Schwartz, Thomas Bernard, Christoph Syldatk and Rudolf Hausmann Green surfactants based on renewable resources INSTITUTE OF PROCESS ENGINEERING IN LIFE SCIENCES SECTION TECHNICAL BIOLOGY KIT University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association www.kit.edu

INTRODUCTION 2

Biosurfactants Very diverse substances Lipopeptides Lipopolysaccharides Glycolipids Surfactin Bacillus subtilis Emulsan Acinetobacter sp. Rhamnolipids Pseudomonas sp. 3

Rhamnolipids Glycolipids 1-2 rhamnose & 1-2 β-hydroxy fatty acids mono-rhamnolipid Pseudomonas aeruginosa m, n = 2-14 Biotechnological production with different carbon sources di-rhamnolipid Many advantages Production based on renewable resources Biodegradeable Low-aqua toxicity Many potential fields of application 4

Potential applications for rhamnolipids Household detergents & washing powder Cosmetics Food additives (e.g. emulsifiers) Antibiotics Microbial soil remediation New Scientist, 20. Feb. 2010 5

Biotechnological production of rhamnolipids Most intensively studied glycolipid Known for decades (first described by Bergström et al 1956) Current processes for rhamnolipid production heuristical approaches Aim of the project a model for rhamnolipid production in a bioreactor optimized processes & process control 6

PLATFORM PROCESS 7

Production of rhamnolipids in a bioreactor mineralsalt medium (NO 3- ) + sunflower oil (CH 1,77 O 0,11 ) 57 batch process P. aeruginosa (CH 1,68 O 0,31 N 0,24 ) n Air (CO 2, O 2 ) 30-L bioreactor Mono-rhamnolipids (CH 1,85 O 0,35 ) 26 Di-rhamnolipide (CH 1,81 O 0,41 ) 32 polysaccharide (CH 1,64 O 0,82 ) 5,5 other byproducts CO 2 H 2 O 8

Production of rhamnolipids in a bioreactor Excessive foaming during the process Rhamnolipids Fatty acids (from oil) Mechanical foam disruption 9

Production of rhamnolipids in a bioreactor 0,20 biomass concentration [g/l] rhamnolipid concentration [g/l] 30 20 10 0,15 0,10 0,05 specific rhamnolipid production rate (q RL ) [g RL /(h*g BM )] 0 0 20 40 60 80 100 cultivation time [h] Understand & model rhamnolipid production in a bioreactor Predict optimized process control strategies 10

MODELING & SIMULATION 11

Modeling rhamnolipid production in a bioreactor Simulation of Biomass Implementation in MATLAB Substrate(s) (oil, glycerol, fatty acids) Nitrate Rhamnolipids (mono- and di-rhamnolipid) Process model System identification & parameter fitting Implementation of genetic data and regulatory mechnisms 12

Modeling rhamnolipid production in a bioreactor Kinetic assumptions growth Stoichiometry 3x 2x 1x MONOD HALDANE enzyme kinetics (lipase) Gene expression profiling Process model (q)rt-pcr of genes involved in rhamnolipid synthesis (lasr/i, rhlr/i, rhlabc, rpon ) Quorum sensing Cell-density dependent regulatory mechanisms C mono-rhamnolipid (t) C di-rhamnolipid (t) 13

Results: Simulation of rhamnolipid production Simulation: Biomass Simulation: mono-rhamnolipid concentration 20 15 Biomass concentration [g/l] 15 10 5 mono-rhamnolipid concentration [g/l] 10 5 0 0 50 100 150 200 Cultivation time [h] 0 0 50 100 150 200 Cultivation time [h] 14

Results: Simulation of rhamnolipid production Simulation: nitrate concentration Simulation: glycerol concentration 15 5 Nitrate concentration [g/l] 10 5 Glycerol concentration [g/l] 4 3 2 1 0 0 50 100 150 Cultivation time [h] 0 0 50 100 150 Cultivation time [h] 15

Results: Simulation of rhamnolipid production Status quo Process model established & implemented in MATLAB System identification and parameter setting performed Data from gene expression profiling and quorum sensing implemented Currently under investigation Strategies for optimized product yields The model as a tool for online process-control 16

RECOMBINANT PRODUCTION OF RHAMNOLIPIDS 17

Recombinant production of rhamnolipids Rhamnolipid synthesis in non-pathogenic host strains Pseudomonas putida rhlab and rhlc genes for rhamnolipid synthesis missing Soberón-Chávez G, Lépine F, Déziel E. 2005. Production of rhamnolipids by Pseudomonas aeruginosa. Applied Microbiology and Biotechnology 68(6):718-725. 18

Recombinant production of rhamnolipids Rhamnolipid synthesis in non-pathogenic host strains Pseudomonas putida Strain engineering: Introduction of rhlab to allow for production of mono-rhamnolipids Soberón-Chávez G, Lépine F, Déziel E. 2005. Production of rhamnolipids by Pseudomonas aeruginosa. Applied Microbiology and Biotechnology 68(6):718-725. 19

Production of rhamnolipids in P. putida Mono-rhamnolipid Di-rhamnolipid IPTG P. aeruginosa (PAO1) (supernatant) P. putida KT2440 pvlt33_rhlab control (supernatant) Strain engineering by: Dr. Frank Rosenau (Institute of Pharmaceutical Biotechnology, Ulm University) P. putida KT2440 pvlt33_rhlab induced with IPTG (supernatant) 20

Recombinant production of rhamnolipids Status quo Inducible expression system in P. putida established Production of mono-rhamnolipids Currently under investigation Optimized production strategies Constitutive expression systems 21

Cooperation partners & sponsors Institute of Functional Interfaces Microbiology of Natural and Technical Interfaces Dr. rer. nat. Thomas Schwartz Dipl.-Biol. Anke Schmidberger Fraunhofer Institute of Optronics, System Technologies and Image Exploitation Dr.-Ing. Thomas Bernard Dipl.-Ing. Christian Kühnert 22

Thank you very much for your attention! Microbial Biosurfactants research group at the KIT - Technical Biology Prof. Dr. rer. nat. Christoph Syldatk Prof. Dr.-Ing. Rudolf Hausmann (now at University of Hohenheim) M.Sc. Janina Beuker Dipl. Biotechnol. Johannes Kügler M.Sc. Judit Maur Dipl.-Ing. Michaela Zwick and the staff of the TeBi 23