BIOREACTORS FOR STEM CELL CULTURE

Transcription

1 BIOREACTORS FOR STEM CELL CULTURE Bioreactors: are basically the ones used for mammalian animal cells in general. Why? Tissue culture flasks are limited in terms of the total cell number that is possible to achiee for potential clinical use. Modeling - Conclusions Aim: design of large scale ex-io expansion/differentiation systems for. stem cells, maintaining their functionality in itro and in io, capable of generating clinically significant cell numbers for multiple therapies.

2 BIOREACTORS FOR STEM CELL CULTURE Example: HSC expansion. Modeling - Conclusions Source: Cabrita, G.M et al, Trends in Biotechnology, 2004

3 BIOREACTORS FOR STEM CELL CULTURE. Modeling - Conclusions Source: Cabrita, G.M et al, Trends in Biotechnology, 2004

4 BIOREACTORS FOR STEM CELL CULTURE Perfusion Chamber: Aastrom Replicell System: an automated continuous perfusion clinical-scale culture system for expansion of unselected BM cells; When BM MNC are inoculated, stromal cells proliferate to form a dense adherent layer, supporting HSC surial, proliferation, and differentiation; Modeling - Conclusions Radial-flow type chambers proide a uniform enironment due to the absence of walls parallel to the flow path that create slow flowing regions; A modification of the flat-bed perfusion chamber consists of retaining the cells through the addition of grooes perpendicular to the flow direction, at the chamber bottom, allowing the ex-io expansion of CB and PB HSC with supplemented cytokines in the absence of stroma.

5 BIOREACTORS FOR STEM CELL CULTURE Example Ex-io Expansion of Human Bone Marrow Mesenchymal Stem Cells Modeling - Conclusions

6 AIM OF STUDIES To establish a 3-D culture system for the efficient expansion of BM MSC using macroporous microcarriers Cultispher S ; To optimize culture parameters: feeding and agitation regimens in the microcarrier-based spinner flask system; To ealuate the differentiatie potential and hematopoietic supportie capacity of cultured BM MSC in the 3-D systems studied.

7 MSC ISOLATION BM harest Ficol Hypaque gradient to isolate MNC Blood Ficoll Plasma MNC Ficoll RBC Magnetic cell sorting of MNC based on Stro-1 positiity Culture with MSC growth medium (MSCGM )

8 Expansion: Why Stirred Culture? Why 3-D? Spinner Flask Ready scalability and relatie simplicity More homogeneous nature compared to the static system, minimizing concentration gradients (nutrients, cytokines...) Microcarriers Increase the aailable surface area 3-D enironment more closely to the in io conditions Cultispher S microcarriers

9 Microcarrier-based Spinner Flask culture system Study of the Feeding Regimens Medium Change: 25% eery 2 days 50% eery 4 days 7.E+06 6.E+06 5.E % medium change 50 % medium change 50rpm MTT Day 2 Day 10 Cell Counts 4.E+06 3.E+06 2.E+06 Dapi 1.E+06 0.E time (days) Cell Adhesion, metabolic actiity, 3-D occupancy

10 Microcarrier-based Spinner Flask culture system Study of the Feeding Regimens Metabolite Analysis 25% Medium Change eery 2 days 50% Medium Change eery 4 days Concentration (mm) Glucose Glutamine Time (days) Concentration (mm) Glucose Glutamine Time (days) Concentration (mm) Ammonia Lactate Time (days) C o n c en tratio n (m M ) Ammonia Lactate Time (days)

11 Microcarrier-based Spinner Flask culture system Study of the Feeding Regimens Metabolite Analysis 25% Medium Change eery 2 days 50% Medium Change eery 4 days Specific Consumption/Production rate (mmol/(day.cell)) 8,E-07 6,E-07 4,E-07 2,E-07 0,E Time (days) gluc glut lact amm Specific Consumption/Production rate (mmol/(day.cell)) 8,E-07 6,E-07 4,E-07 2,E-07 0,E+00 gluc glut lact amm Time (days) Day period Y Lact./Gluc FRI FRII Y ammo./glut FRI FRII

12 Hematopoietic Supportie Capacity of Expanded Cells Experimental design Microcarrier-immobilized Mitomycin C-treated MSC (24 well plates) Bottom area 100% 50% 25% Static Co-culture Co-culture Proliferation and phenotypic analyzes UCB CD34 + -enriched cells

13 Hematopoietic Supportie Capacity of Expanded MSC Microcarrier-immobilized MSC with UCB CD34 + enriched cells C e ll c o u n ts 2.E+07 1.E+07 5.E+06 2-D Control 25% 50% 100% Fold Increase CD D Control 25% 50% 100% 0.E Time (days) Time (days) Microcarrier-immobilized expanded-msc retained their hematopoietic supportie capacity

14 Differentiatie Potential of Expanded MSC Experimental Design Osteogenic inducing medium Alkaline Phosphatase Tetracycline incorporation Von Kossa Cell haresting and plating in 6-well plates Microcarrierimmobilized MSC Adipogenic inducing medium Oil Red-O

15 Differentiatie Potential of Expanded MSC Osteogenic Lineage ALP Staining Von Kossa Tetracycline incorporation Adipogenic Lineage Oil Red-O Microcarrier-immobilized expanded MSC retained their differentiatie potential towards osteogenic and adipogenic lineages

16 CONCLUSIONS The 3-D culture systems were suitable for the ex-io BM MSC expansion under dynamic conditions; A more programmed feeding regimen led to higher expansion leels in the spinner flask culture system; BM MSC expanded in the 3-D systems retained their hematopoietic supportie capacity and multilineage differentiation potential.

17 MODELING Definition: quantitatie description of the main phenomena that hae an influence on the growth, death and metabolic actiities of cells, i.e. acceptance of mathematical expressions that relate the rates of cellular growth and metabolism to the composition of the medium. An efficient tool of kinetic analysis of cellular processes for: the design and the optimization of media and reactor operational parameters in batch or continuous operation due to predictie capabilities; Useful in the deelopment of software sensors to estimate on line the time ariation of the media composition. Steps for the construction of a kinetic model: 1) Kinetic analysis of experimental results with the formulation of hypotheses on the nature of the rate limiting steps; 2) Choice of rate expressions describing the influence of this phenomena on the cellular processes; 3) Ealuation of parameter alues ; 4) Validation of the model with different experimental results.

18 Cell Growth Terminology Growth parameters: Viable cell concentration, n Fraction of iable cells, f Specific growth rate, µ dn = increase in cell number dt = time interal n = cell number Doubling time, Dt (i.e. time for a population to double ln2 D t = in number) µ Population doubling time, PD (i.e. total number of population doublings of a cell line since its initiation in itro) µ = PD 1 n = dn dt log( n n 0 log2 ) Specific death rate, k d

19 MODELING (cont.) Background: Rates usually measured: µ and k d, q glucose and q glutamine, q lactate and q ammonia (and rate of secretion of a product); Rate-limiting effects most frequently obsered: depletion of glucose and glutamine and accumulation of ammonia and lactate. Method for kinetic model construction: 1) Experimental data Culture System Batch Continuous Adantages Simplest to perform Nutrient and metabolite concentration can be maintained constant for seeral days Disadantages Concentration of all nutrients and metabolites change simultaneously with time Require more sophisticated equipment and long-term operation extending to seeral weeks Note: Important to control precisely the physicochemical parameters of the medium (temperature, ph, dissoled oxygen and osmolality).

20 MODELING (cont.) 2) Kinetic Analysis: Identify the rate-limiting nutrients and metabolites; calculate total cell production, µ, k d, q nutrient, q metabolites, q product. 3) Model deelopment: Select a rate expression for µ; Select a rate expression for k d; Select the rate expressions for nutrient uptake; Select the rate expression for metabolite and product; Write the mass balance equations for the different species; Integrate equations by a numerical method (e.g. Runge-Kutta method).

21 MODELING (cont.) 4) Parameter identification: Objectie: obtain the best agreement between the calculated time ariations of the medium composition and the measured experimental results; 2 ways to ealuate the parameters: Parameters calculated directly from the experimental results Parameters ealuated by a cure-fitting procedure

22 KINETIC STUDY OF THE EX-VIVO EXPANSION OF HSC -specific cell expansion rate: µ - specific cell death constant: k k Estimation of Kinetic Parameters dx dt = µ. X k. X = µ dx dt k = k k. X ( k ) k X X concentration of iable cells X k concentration of dead cells Gonçales, R., Lobato da Sila, C. et al, Biotechnology Letters, 28, (2006) k

23 KINETIC STUDY OF HSC EXPANSION CONCLUSION Total cell expansion is similar for both BM and CB, while cell death seems to be related with the presence/absence of hu-st in the culture. A simple two-parameter model gies a global measure of culture performance and addresses the dependency of cell death on the enironment in which cell are cultured (stroma ersus stroma-free).

24 PREDICTIVE MODELING OF HSC BEHAVIOR CFU-G,M [ X ] d dt = k X e γ X [ ] [ ] Y X X + k P k [ X ] k [ X ] d X Granulocytes Y d k Myeloid Stem Cell (MSC) CFU-MEG Monocytes First-order kinetic including: Predictie Modeling Pluripotent Hematopoietic Stem Cell Stem(PSC) Cell (HSC) d [ SC] dt Stem Cell (SC) = k γ e Lymphoid Stem Cell (LSC) BFU-E CFU-Eo self-renewal term k e X CFU-E cell death term, k k X T and B cells of the immune system Platelets Erythrocytes Eosinophils term accounting for the differentiation k d X limitation factor γ [ ] SC[ ] MySC[ ] LySC SC + k HSC k SC k [ SC] k [ SC] d Lobato da Sila, C. et al, Bioprocess Biosystems Eng., 25, (2003) d d k

25 MODELING OF HSC EXPANSION AND DIFFERENTIATION BM 7.0E E+08 BM + hu-st 3.0E E+08 BM - hu-st Total Viable Cells 5.0E E E E E+08 Total Viable Cells 2.0E E E E E E Experimen tal Theoretical Time (days) Experimental Theoretical Time (days ) BM Modeling Results CD E E+06 CD34 + CD34 + CD38-4.0E+06 CD E E E E E E E E E E E E E CD Experimental Theoretical Time (days) Experimental Theoretical Time (days) Experimental Theoretical Time (days) Lobato da Sila, C. et al, Bioprocess Biosystems Eng., 25, (2003) CD 33 +

26 MODELING OF HSC EXPANSION AND DIFFERENTIATION BM BM Modeling Results Lobato da Sila, C. et al, Bioprocess Biosystems Eng., 25, (2003)

27 MODELING OF HSC EXPANSION AND DIFFERENTIATION CONCLUSIONS The model indicates that the presence of the stromal layer is useful for the ex-io expansion of HSC since: i) Enhances the expansion of the majority of the more mature cells ii) Reduces the death rate constant for the more primitie cell HSC iii) Reduces the differentiation for the more mature cells Modeling - Conclusions. Predictie kinetic models are important in the deelopment of stem cell bioreactors systems capable of being tuned for the production of specific blood products.

28 MODELING - Example Hybridoma culture (cell line VO 208) in a batch system * Conditions: Medium used: RPMI % (/) FCS + 2% (/) MEM aminoacids + 1% (/) non-essential aminoacids Initial glucose concentration: 13 mm Initial glutamine concentration: 4.5 mm Bioreactor working olume: 1 l Starting cell density: iable cells l -1 ph = 7 (maintained with 0.2 M NaOH solution and gaseous CO 2 ) Temperature = 37 ºC Oxygen supply: 50% of air saturation of gaseous air and nitrogen Rotating speed: 50 rpm Measurements: Liing and dead cells concentration by the trypan blue exclusion method using a hemacytometer; Glucose, lactate and glutamine and ammonia using a multiparameter analyzer; Monoclonal antibodies (product) by ELISA assay. *Source of data and figures presented : Doyle, A, Griffiths, J.B, Cell and Tissue Culture: Laboratory Procedures in Biotechnology, Griffiths, John Wiley & Sons Ltd, 1998

29 MODELING Example (cont.) Calculations: 1) Total Cell Production: X total cells n non-iable cells iable cells X = X + t X d dx t 1 2) Specific growth rate: µ = ( h ) X dt dx d 1 3) Specific death rate: k = ( h ) d X dt

30 MODELING Example (cont.) Calculations: 4) Specific rate of nutrient consumption: ν Glc [ Glc] ( 9 1 mmol 10 cells ) d = h X dt ν G ln [ ln] k deg [ Gln] ( 9 1 mmol 10 cells ) d G = h X dt X 5) Specific rate of metabolites and antibodies production: π NH 4 π Lac π MAbs [ NH ] k [ ] 4 deg NH 4 ( 9 1 mmol10 cells ) d = h X dt X [ Lac] ( 9 1 mmol10 cells ) d = h X dt [ MAbs] ( 9 1 mmol 10 cells ) d = h X dt

31 MODELING Example (cont.)

32 MODELING Example (cont.) 2 culture periods: Phase 1 Lasts about 30 h and is where the different rates increase; this corresponds to the classical obsered lag phase, where cells progressiely adapt to their new enironment. Phase 2 is from 40 to 140 h, where all the specific rates progressiely decrease except k d, which continues to rise. This reduction in the specific rate of growth and metabolism is mainly due to glutamine limitation (accumulation of lactate and ammonia may also hae a kinetic effect).

33 MODELING Example (cont.) Representation of the specific rates as a function of µ: ν Glc All the cures except for MAbs production show 2 distinct upper and lower parts: π Lac Upper part initial lag phase Lower part growth and death period ν Gln during initial lag phase, at gien µ, cells exhibit a faster rate of nutrient uptake and metabolite production; after initial lag phase, the rate of cellular metabolism can be considered to be proportional to µ. π NH4 π MAbs

34 MODELING Example (cont.) Model deelopment: Rate expression for cellular growth: µ = µ max K G ln [ Gln] 1 1 [ ] + Gln [ Lac] [ NH ] 1+ K Lac 1+ K NH 4 4 Rate expression for cellular death: k 1 = A d + k1 4 Lac [ Gln] 1+ C1 [ NH ] + k [ ] d 2 Rate expression for nutrient uptake: ν Glc Glc / X = Y µ + m Glc ν G ln = Y µ + m G ln/ X G ln Rate expression for metabolite and antibody production: = Y µ + m π Lac Lac / X Lac π Y NH4 NH = µ + m 4 NH YNH / X 4 4 = Y µ + m π MAbs MAbs / X MAbs

35 MODELING Example (cont.) Mass Balance Equations: dx = ( µ kd ) X dt d[ Glc] = ν Glc X dt d[ Lac] = π Lac X dt d[ Gln] = kdeg dt d[ NH4 ] = kdeg dt d[ MAbs] = π MAbs X dt [ Gln] [ Gln] + π ν G ln NH 4 X X

36 MODELING Final Results T a b l e 4. P a r aparameter m e t r alues a l u e s for f othe r tvo h e 208 V O hybridoma h cell y b rlinei d o m a c e l l l i n e P a r a m e t e r P a r a m e t e r a l u e s G r o w t h µ m a x h - 1 k G l n k L a c k N H m M 5 5 m M 1 0 m M D e a t h k d h - 1 C m M? m M - 1? m M - 1 G l u c o s e c o n s u m p t i o n Y G l c / X 9 m G l c L a c t a t e p r o d u c t i o n Y L a c / X 1 3 M L a c G l u t a m i n e c o n s u m p t i o n Y G l n / X 2. 5 m G l n A m m o n i a p r o d u c t i o n Y N H 4 / X 1. 7 m N H A n t i b o d y p r o d u c t i o n Y M A b s / X 4. 5 M M A b s

37 MONITORING Monitored parameters: Temperature: regulated by pre-heating the input media and by heating the surrounding water jacket regulated by feed-back from the temperature probe; ph: efficiently controlled using the CO 2 /HCO 3- concentration within the gas/liquid phase and/or by using base titration (e.g. NaOH); Dissoled oxygen: polarimetric electrodes are stable and accurate sensors often used, although with some limitations; Osmotic pressure: no commercially aailable system for on-line measurements; currently the standard method uses a freezing point osmometer. To maintain constant osmolarity, a second medium inlet system for distilled water must be installed; Agitation: can be regulated to reduce the shear stress;

38 MONITORING (cont.) Medium components: nutrients and metabolites concentration should be accurately monitorized in order to aoid cell growth limitations; Cell concentration (biomass): the number of cells and parameters such as ATP, DNA and protein are usually determined in samples drawn from the culture and used to calculate total biomass. Specific methods can be used for cell counting on line (e.g.infrared sensors). Note: When monolayer cell cultures are scaled-up (in a fixed-bed or hollowfiber bioreactor) it is no longer possible to obsere the cells directly, and cell counting and determining cell concentration becomes difficult.

39 Final Considerations In order to engineer the cells and the ast products excreted, manufactured and refined from animal cells, it is crucial to understand the structure, biochemistry and methods of cultiation; Complexity of animal cells are not fully characterized yet, but present technologies show the increasing potential usefulness and itality of animal cells for many important applications (e.g. biochemical, biomedical).