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Saccharomyces cerevisiae  :

Saccharomyces cerevisiae  :. Evoutions in Bio Sciences. Ecology Quantitative ecology Physiology, Quantitative biology Systemic Biology Holistic Biology. Yeast as cell factory. Yeast. Semi Anaerobiosis Anaerobiosis. Aerobiosis. Baker yeast Yeast extract Flavouring agents

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Saccharomyces cerevisiae  :

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  1. Saccharomyces cerevisiae : GG LISBP INSA Toulouse

  2. Evoutions in Bio Sciences • Ecology • Quantitative ecology • Physiology, • Quantitative biology • Systemic Biology • Holistic Biology GG LISBP INSA Toulouse

  3. Yeast as cell factory Yeast Semi Anaerobiosis Anaerobiosis Aerobiosis Baker yeast Yeast extract Flavouring agents Metabolites, ex food additives Waste water treatment Yeast as co productanimal feed Ethanol (ETBE) Ethanol solvant chemistry alcoolic beverages Recombinant yeast  enzyme pharmacentical GG LISBP INSA Toulouse

  4. MICROBIAL/BIO REACTOR ENGINEERING:A BASIC TOOL FOR KNOWLEDGE IN HOLISTIC BIOLOGY G.Goma,S Guillouet,C Jouve,J L Uribellarea Laboratoire d ingenierie des systémes biologique et des procédés UMR CNRS,INRA,INSA GG LISBP INSA Toulouse

  5. Red biotechs Green biotechs Agro-food biotechs White biotechs Intersections on technology and common fields Generic technology  Synthetics, pathways  Biocatalysis engineering  Bioprocessing Basic knowledges • Focused on  life sciences … engineerig sciences biomathematics physics • Economy, sociology, ... GG LISBP INSA Toulouse

  6. Microbial Engineering:a part of biotechnologies Find and improve the microorganisms for bio processing Find the conditions of bio processing where the microrganism is economicaly performant A multidisciplinary approach A contraint : find the bottlenecks,eliminate them An obligation:need of handling a complete tool box:from genes to bioproducts and bioprocess GG LISBP INSA Toulouse

  7. What are the criteria of production ? • Production of « active agents » • Cost ? • Invisible technology • Relatively safe technology • Reproducible protocols simplest as possible • Semi speciality What kind of technological strategy? • Low tech ? • High tech ? • Right tech for the goal • « de novo » technology? use of existing tools of production? GG LISBP INSA Toulouse

  8. The IB Value Chain Bulk Biofuels H2 Ethanol Biomaterials Polylactic acid 1,3 propane diol PHAs Sugars Agricultural (by)products Physical treatment and/or enzymes (Micro-)organisms biocatalysis Biochemicals Food Ingredients Pharmaceuticals Fine Chemicals Fine GG LISBP INSA Toulouse

  9. The steps • Factory and his environment • The reactors ,biorector:biocatalist,srategy • Raw materials and biocatalist,bioreaction engineering • The biocatalist • Global implementation ;find the differents bottleneks and solve the problems • Need a tool box,and combining experimentals datas(strategy?) and simulations GG LISBP INSA Toulouse

  10. Take down, culture medium, gaz out, biomass, products,,,,,,,,,, X Si products:j Feeds, Substrat(s), air, regulations and controls X GG LISBP INSA Toulouse

  11. Industrial (White) Biotechnology Biofuels Biomaterials Biochemicals Sugars Cell factories GG LISBP INSA Toulouse

  12. Gaz out:analyse control Gaz in Tank,mixing, température control Measures Régulations logging Correction pH, Antifoam GG LISBP INSA Toulouse

  13. RPM Qair Pressure CO2,O2 ? Gas balance OD? Ph (controlled) Temperature For this 2 controlled parameters, the analysis of the « work » of the control regulator gives informations Starters  milk, silage, … Baker yeast  bread Alcoholic beverages Lactic acid/organic acids (citric) Antibiotics Vaccines Monoclonal antibodies Recombinant proteins (or toxin ?) Waste water treatment Bioleaching Dual use of fermentors Instrumentation of a fermentor Use of fermentors GG LISBP INSA Toulouse

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  15. Mixing Réalisation FLUIDIC Mixing Jets GG LISBP INSA Toulouse

  16. AERATION : TECHNOLOGIES d’AERATION FERMENTEUR type air-lift ICI, Ltd. factory, Billingham, UK, (Chem. Eng. News, 18-Sep-78) GG LISBP INSA Toulouse

  17. Metabolic descriptor • Mass conservation • Elemental biologicals reactions • Macroscopic kinetics • Matrix of reactions combining kinetics and stoechiometry of elemental reaction of metabolic pathways • Combining kinetics observed by on line measurements by robusts sensors evaluation of metabolics fluxes « on line » and nutritionals needs • Identification of some bottlenecks GG LISBP INSA Toulouse

  18. Qe Glucose + 2 NADPH,H CO O2 CO2 ATP 2 Glucose6-P Pentose P Fructose-P ATP + NADH,H ATP glycerol GlycerolP TrioseP Sedoheptulose7 P + + + S P X O2 CO2 NADH,H NADH,H H 0 + 4 H 2 ATP Glycerate3P NAD 1/2 O Erythrose4P 2 + FADH 2 H 0 + 2 H 2 PEP FAD 1/2 O 2 ATP + 3 H ATP Pyruvate HS-CoA + NADH,H CO 2 CO 2 + ATP Qs NADPH,H CO Acetyl CoA CO 2 Acétate Qresp 2 ATP HS-CoA OAA + NADPH,H ATP %pO2 Citrate ANABOLISME Malate + NADH,H pH IsoCitrate + CO NADH,H Fumarate 2 Temps + NADPH,H SH-CoA FadH CO 2 Succinate 2 a Kglu Suc-CoA GTP CO 2 SH-CoA + NADH,H Predictive modelisation and implementation of microbial processes • Phenomenogical models • Behavioural models • Structured models and stoechiometric/metabolic descriptors Experimental strategies GG LISBP INSA Toulouse

  19. Plate-forme métabolomique, fluxomique Vers une biologie des systèmes par la réconciliation des niveaux métaboliques, génétiques et moléculaires Interface de la cellule et échanges 3 Système d’échanges Système métabolique 2 Système protéique Système: Système d’adaptation et de génomique défense 1 GG LISBP INSA Toulouse

  20. Sequences genes Profiles proteins Prerequisite to “Systemic Biology” Data base (x2 every 18 months) Analytical methods in situ continue on linein parallel micro samples Metabolome Definition of functions , networks « OMICS » Metabolic pathways coupled kineticsrelaxation time,regulations, Kinetics Flux, Stocks Technology GG LISBP INSA Toulouse

  21. Top Down strategy • Fit the macroscopic environnment,bioreactor • Find reproducible conditions:signature recognition • Biokinetics • Quantitative physiologie • Metabolic pathways • Proteomic • transcriptomics GG LISBP INSA Toulouse

  22. Comparison with another fermentation with better performances > sequencial feeding glucose > Titer 50 h = 147 g/L, viability = 30% > Viability = 80% at 120g/L • Analysis of first fermentation • How osmotic conditions affect response to ethanol? • Genes and mechanisms involved? GG LISBP INSA Toulouse

  23. Motivation The physiological state recognition The cell population expresses stable characteristics within every physiological state, thus an invariant control strategy can be effectively applied in each state. • Normally, we have sensors only for the environmental variables. • Physiological states are tracked through offline measurements and analysis, with an implied delay. • The physiological state can be identified by the fusion of environmental measurements. GG LISBP INSA Toulouse 2

  24. Identification and Classification of Physiological States • A bottlenek for « the omics »studies,for control strategies and « quality » • Morphometry • Kinetics and stoechiometrics « parameters » • Differentiation of biologicals and environmental effects GG LISBP INSA Toulouse

  25. The family growth by budding Cycle G1, G2, G3,G4,… I am stressed – I became a filament S1 sugarS2 oxygene yes/no S3 ethanol I work I have a limitation I am ill I work My job is to produce cell biomass My job is bioconversion I do nothing I am injuried Finish : End ; cryptic growth !!! I am a substrate Yeast :Axenic culture gives a population production linked to some mechanims GG LISBP INSA Toulouse

  26. The Tool box Bio: the “omics” + Traditional technologies + mathematical tools “the rule of innovation” GG LISBP INSA Toulouse

  27. Raw materials Biocatalysis strategy Screening ü Screening ü ü Diversity Genes* Engineering ü Natural Genes* metabolic* Natural et functions Diversity of and functions ü Building strains ü Eco-systems screening Eco-systems screening ü DNA shuffling ü Global analysis “Omics and engineering” ü Bioprocess strategy Production-formulation Production-formulation premières « Bioprocédés » « Bioprocesses » Strategy on co-products /bio-products Co-products Biomolecules High added value Needs in size of market : animal feed Biomaterial on energy Biomolécules plus value Increase the value * e.biotechnology's and engineering GG LISBP INSA Toulouse

  28. Microbial engineering is multidisciplinary : need of quantitative and “system” biology Molecular physiological engineering Microbial process analysis and control engineering Microbial engineering Physiological engineering Microbial processing GG LISBP INSA Toulouse + system biology modelling

  29. Dual use of fermentors What is a fermentor ? Elemental biokinetics x Biomass p Product s Substrats t Time x p s t x p s1 t ou x p s1 GG LISBP INSA Toulouse s2 t

  30. Cell and glucose ethanol concentration vs time (Fed batch with nutritional strategy) GG LISBP INSA Toulouse

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  32. III VI V IV I II 20 18 16 14 12 10 8 6 4 2 Study of a reference fermentation Ethanol Glucose (g/L) Biomass (g/L) Viability • 2 phenomena:- Decoupling growth-production- Loss of viability GG LISBP INSA Toulouse

  33. Off-line analyses On-line acquisitions and monitoring Measurement Fast sampling : & rates / 20 sec Gas balances (Mass spectr.) out in Q Q Measurement of extracellular metabolites- direct filtration through adaptated membrane air air q q Q O CO , , 2 2 resp rpm Controlled environment Measurement of intracellular metabolites Sample quenching in-60°C methanol T° control pH Monitoring p O2 Q, q H + µ Sampling for extraction of RNAs and proteins Biomass sensor X estim Studying the fast biological responses ... GG LISBP INSA Toulouse

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  35. The hyper yeast GG LISBP INSA Toulouse

  36. Data Acquisition : Measures Fermentation Parameters Time(h) GG LISBP INSA Toulouse

  37. Système d’échanges Le biotope du système microbien crée un environnement; « en soi , un système » Système métabolique Connaissance de systèmes ; interactions de systèmesle micro-organisme en tant que système est constitué d’« infra » systèmes système protéique Système génomique Système: d’adaptation et de défense « interactions de systèmes et hiérarchies » Le microorganisme est un système biocatalytique évoluant dans un système Biocatalyse enzymatique Biocatalyse microbienne « impact socio-économique » Interface de la cellule et échanges GG LISBP INSA Toulouse

  38. Cell 10-6 10-5 10-4 10-3 10-2 10-1 100 10+1 10+2 10+3 10+4 10+5 10+6 s- RNA control Mass action law Modification of enzymatic pools Allosteric controls Gradients due to mixing Continuous culture Environment Batch, Fed-batch Phenomenological model Metabolic model Behavioural models Virtual cell GG LISBP INSA Toulouse

  39. Extracellular components Segregation (size, viability, …) Intracellular components Descriptor of physiological state A Descriptor of physiological state B * Analysis of population or « dynamic systems » * Relaxation time Perspective : Use of behavioural modelling GG LISBP INSA Toulouse

  40. Bacteria Yeast Fungi Eucaryotic cells In every case The basic law of biokinetics and stoechiometry are the same But, every case have rules of utilisation with typical profile What kind of micro organisms What kind of profile GG LISBP INSA Toulouse

  41. CLASSES CATEGORISATION des SIGNAUX Item : temps SIMILITUDE Temps Item : temps Identification de classes de comportement Mesures pertinentes / Comportements physiologiques GG LISBP INSA Toulouse

  42. Qe Glucose + 2 NADPH,H CO O2 CO2 ATP 2 Glucose6-P Pentose P Fructose-P ATP + NADH,H ATP glycerol GlycerolP TrioseP Sedoheptulose7 P + + + S P X O2 CO2 NADH,H NADH,H H 0 + 4 H 2 ATP Glycerate3P NAD 1/2 O Erythrose4P 2 + FADH 2 H 0 + 2 H 2 PEP FAD 1/2 O 2 ATP + 3 H ATP Pyruvate HS-CoA + NADH,H CO 2 CO 2 + ATP Qs NADPH,H CO Acetyl CoA CO 2 Acétate Qresp 2 ATP HS-CoA OAA + NADPH,H ATP %pO2 Citrate ANABOLISME Malate + NADH,H pH IsoCitrate + CO NADH,H Fumarate 2 Temps + NADPH,H SH-CoA FadH CO 2 Succinate 2 a Kglu Suc-CoA GTP CO 2 SH-CoA + NADH,H Predictive modelisation and implementation of microbial processes • Phenomenogical models • Behavioural models • Structured models and stoechiometric/metabolic descriptors Experimental strategies GG LISBP INSA Toulouse

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  44. Study of a fermentation of reference First results:genes over expressed GG LISBP INSA Toulouse

  45. Study of a fermentation of reference First results:genes under expressed GG LISBP INSA Toulouse

  46. Plate-forme métabolomique, fluxomique Exploration fonctionnelle des systèmes métaboliques microbiens • Analyse des réseaux métaboliques • Reconstruction métabolique • Analyse topologique • Modélisation métabolique • Exploration fonctionnelle • Analyse in situ: RMN in vivo • Couplages bioréacteurs / RMN • Métabolisme énergétique, carboné, etc.. • Métabolomique • Identification/quantification des métabolites • Fluxomique • Quantification des flux métaboliques • Approches isotopiques (13C) • Biomathématique/ bioinformatique • Modélisatio métabolique • Calculs de flux • Réconciliation de données Environnement Génome Systèmes métaboliques Métabolisme central E. coli : 89 métabolites, 110 réactions GG LISBP INSA Toulouse

  47. Heterogeneities:gradients(flux,stocks,,,) :microbe population GG LISBP INSA Toulouse

  48. Top Down strategy • Fit the macroscopic environnment,bioreactor • Find reproducible conditions:signature recognition • Biokinetics • Quantitative physiologie • Metabolic pathways • Proteomic • transcriptomics GG LISBP INSA Toulouse

  49. Synthesis Engineers Top down strategies Biologists,bottum up , bioinformatics!!!!!!!!! Both strategies are necessary GG LISBP INSA Toulouse

  50. Basic concepts Analysis of information quality Fuzzy logic Hierarchical classification Programmed by inductive logic Classification machine Measures • 3 levels of multiscale analysis • Single cell, “statistic” Hypothesis or « Class » Biological and engineering knowledge Biological modelling Rules GG LISBP INSA Toulouse

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