1. Respiration Activity Monitoring System
Bioprocessoptimisation
Respiration Activity Monitoring System
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2. Online – respiration activity measurement
The RAMOS® System
Online – respiration activity measurement
(OTR, CTR, RQ)
in shaking flasks
In the following presentation I will introduce you to a device which determines sterile the respiration activities of bactria, yeast, plant, insect and mammalian cell cultures in shaken bioreactors.
The device has the name RAMOS which is an abbreviation for
Respiration activity monitoring system.
Respiration Activity Monitoring System
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3. The Tray
At the tray, which can be withdrawn completely, 8 instrumented flasks can be found. Up to 6 standard additional flasks can be added.
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4. Fields of Application Online-tracing of the metabolic activity
of pro- and eukaryotic cultures in shaking flasks
An example diagram where you can see the continouse measurement of data-points. The effect of an increase of temperature can be detected within no time.
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5. Possibilities Easy Determination of parameters:
- oxygen transfer rate (OTR)
- carbon dioxide transfer rate (CTR)
- respiration quotient (RQ)
- maximum growth rate (µmax)
- volumetric oxygen transfer coefficient (kLa) …,
which afford a safe Scale-Up.
Typical measuring parameters of RAMOS are (…)
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6. Unlimited growth on minimal media oxygen transfer capacity
Possibilities
Detection of characteristic biological phenomena (OTR)
Unlimited growth on minimal media
Substrate limitation
(except C-source)
Oxygen limitation
maximum
oxygen transfer capacity
Oxygen transfer rate
Oxygen transfer rate
Oxygen transfer rate
Time of fermentation
Time of fermentation
Time of fermentation
To show you the effects of some biological phenomena on the OTR I created this transparency. All graphs have in common that you see on the x-axis the time of fermentation and on the y-axis the OTR. The first picture shows a unlimited growth of micro organisms. The OTR rises exponentially with the number of micro organisms. Then the essential substrate mostly the carbon source is exhausted. The micro organisms stop their respiration and the OTR cracks off and drops down. This step decrease is nearly always an indication, that the carbon source is exhausted. Is an other substrate limited like nitrogen or phosphate, the micro organisms stop growing and this lead to a slowly declining of the OTR. Is oxygen the limiting substrate you will get this shape of a curve. The curve reaches the maximum possible oxygen transfer capacity ends in a plateau like you can see here. Furthermore you can detect a product inhibition which leads to a slowly decreasing of the slope of the OTR as the toxic product increases. The next biological phenomena I want to mention here is the diauxic growth. That means that Culture is able to consume two different carbon sources. The first CS lead to a rise of the OTR till the depletion of it. Than the culture respiration activity increases again, because they can consume a second carbon source. The last information you can extract from the OTR curve is the total oxygen consumption of the micro organisms. Therefore you have to integrate the OTR from the beginning of the fermentation till the end. With this information it is possible to balance a bioprocess. This examples of course are the theory in the praxis you have nearly always a mixture of these basic types.
Product inhibition
( e.g. pH)
Diauxic growth =
Total oxygen
consumption [mol/l]
Oxygen transfer rate
Oxygen transfer rate
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Time of fermentation
Time of fermentation

7. Possibilities Detection of characteristic biological phenomena
CTR development:
To show you the effects of some biological phenomena on the OTR I created this transparency. All graphs have in common that you see on the x-axis the time of fermentation and on the y-axis the OTR. The first picture shows a unlimited growth of micro organisms. The OTR rises exponentially with the number of micro organisms. Then the essential substrate mostly the carbon source is exhausted. The micro organisms stop their respiration and the OTR cracks off and drops down. This step decrease is nearly always an indication, that the carbon source is exhausted. Is an other substrate limited like nitrogen or phosphate, the micro organisms stop growing and this lead to a slowly declining of the OTR. Is oxygen the limiting substrate you will get this shape of a curve. The curve reaches the maximum possible oxygen transfer capacity ends in a plateau like you can see here. Furthermore you can detect a product inhibition which leads to a slowly decreasing of the slope of the OTR as the toxic product increases. The next biological phenomena I want to mention here is the diauxic growth. That means that Culture is able to consume two different carbon sources. The first CS lead to a rise of the OTR till the depletion of it. Than the culture respiration activity increases again, because they can consume a second carbon source. The last information you can extract from the OTR curve is the total oxygen consumption of the micro organisms. Therefore you have to integrate the OTR from the beginning of the fermentation till the end. With this information it is possible to balance a bioprocess. This examples of course are the theory in the praxis you have nearly always a mixture of these basic types.
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8. Possibilities Recognition of suitable conditions for conventional
mass screening
(operation duration, culture media, operation conditions …)
Optimisation of substrate concentrations and
reduction of media development time
Fermentation balancing (cytotoxycity- and
proliferation assays)
The fields of application are (...)
Growth control under sterile conditions
Targeted sampling depending on oxygen transfer rate
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Quality control

9. ? OTR CTR RQ State of the Art stirred bioreactor shaking bioreactor
online-exhaust
gas analytik
OTR
CTR RQ
online ?
Therefore online measurement of the oxygen transfer and carbon dioxide rate, respectively the respiratory quotient with an exhaust gas analysis is state of the art in stirred bioreactors.
Regarding online measurement of the respiration activity the shaking bioreactor is still black box or better black flask.
stirred
bioreactor
shaking
bioreactor
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10. Motivation
„The disadvantage of the shake flask as an experimental system is that the experimenter has only limited capabilities for on-line
monitoring and control.“
Payne et al., 1990
...
„Weakness of small-scale liquid fermentations:
discontinuous monitoring“
Hilton, 1999
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11. trace elements, vitamins
What kind of Online Signal?
trace elements, vitamins
carbon source
(glutamine, glucose, ...)
nitrogen source
(ammonia sulfate, urea,
yeast extract, peptone, ...)
phosphorus source
(phosphate, phytin)
Oxygen
Carbon dioxide
sulfate source
(sulfate, cysteine, ...)
There are many possibilities of components to measure online signals, like (…)
You can measure a carbon source for example Glucose or glycerol of a product alcohol or proteins.
But as known, the only universal signal for all micro organisms are the components oxygen and the carbon dioxide.
product
(proteins, alcohol
amino acids, ...)
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12. ? Unknown Fermentation Process normal shaking flask: A B
culture process A ? B
The first reason is, that we do not know the course of the fermentation.
To show you how important this information is, I show you an exemplary fermentation. With this fermentation somebody wants to compare two strains A and B in order to choose the microorganisms with the highest product yield. To find the better strain the operator takes a sample at any point of the fermentation. The analysis of the sample indicates that strain A has the higher product concentration. So of course strain A is the better one and strain B is discarded.
Time
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end of experiment

13. Known Fermentation Process
culture process A B B A
But if he would have had an online signal they would get this product curves. And now his favourite would not be the strain A but B, because B has the higher product concentration at an earlier moment of the fermentation. This is of course a example, which is a little bit overdone. But I we know real cases, where this kind of mistake has happened and has lead to a wrong choice of a strain. With this example I want to point out, that it is important to have a online signal to control the bioprocess during the whole fermentation time and it is also important to get this information at the beginning of the bioprocess development, for example during the screening phase.
Time
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end of experiment

14. Solution measures online the respiration activities (OTR, CTR, RQ)
of aerobic biological systems
in shaking flasks under
sterile conditions
To solve this problem we invented RAMOS which measures online the respiration activities rate in shaking flasks under sterile conditions.
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15. Distinct Advantages more information about microbiological processes
in shaking flasks
rapid characterisation and targeted optimisation of media
replaces expensive experiments in the fermenter
parallel technology (time, comparability ...)
casily handling
creates optimal repoducabilty options
Your benefits are (…)
visualising the perfect inoculation point
virtual non-stop operation by very short set-up time
reduction of experimental time to the actually required time
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distinction of process-related and biological effects

16. Graduated flask
Our goal is to create identical fermentation conditions in the measuring flask as in the normal shake flask. To fulfil this we have to generate on the one hand identical hydrodynamic conditions of the liquid and on the other hand identical gas concentration in the headspace of the shaking flask. On this picture you see the normal shake flask with the cotton plug as a sterile boundary. Next to it is the new designed measuring shake flask. The modification, we did, affect only the upper part of the shake flask. The important thing here is, that we did not change anything at the lower part of the shake flask where the liquid is rotating. So we did not disturb the hydrodynamic of the liquid. We also did not install a sensor in the shake flask which touches the liquid. Our sensor in attached at the top of the shake flask and measures the partial pressure of oxygen in the gas phase. If the sensor would touch the liquid it would act as baffle and change the flow of the liquid enormously. Both characteristics of the modified flask mentioned here lead to an identical hydrodynamic of the liquid like in a normal shake flask.
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17. Sample Fermentations
Determination of the optimal inoculation- and fed-batch starting time
Mammalian cell culture Hybridoma (50 ml liquid volume)
OTR
CTR
cell density
OTR/CTR [mol/(L·h)]
Cell density [N/mL]
This diagram shows the mammalian cell culture Hybridoma over 200 hours.
You can see that the cell density runs exactly like the OTR in the EXP-Phase. That indicates that the OTR is proportional to the proliferation rate.
The CTR runs above the OTR because of the glutamine in the media which produces such a high CTR. It gives while dissoziating CO2 to the gas phase and produces in that way a higher CTR.
After nearly 90 hours the OTR and CTR decreases within 15 hours. That indicates a total consumption of the limitating substrate – hear glutamine. Within these 15 hours the cells change from gltamine consumption to glucose consumption. After that 15 hours it is not possible to lead the cells back on glutamine consumption.
After 90 hours is the best time point to inoculate the cells into a bigger fermenter or to start a feeding system.
glutamine- and
glucose consumption
glucose consumption
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100
150
200
Time of Fermentation [h]

18. Sample Fermentations Media optimisation Example: optimum of osmolarity
Mammalian cell culture Hybridoma (50 ml liquid volume)
optimum of osmolarity
at 0,318 osmol/kg
Growth rate µ [h-1]
In this diagram the growth rate on different osmolaritiey is measured. In eight flasks were different osmolarities in the media. The maximum growth rate is the slope of the OTR in the exponential phase, because the OTR runs the exact way the proliferation rate does. So a higher slope in the EXP of OTR is a higher slope in growth rate.
This is an example for a easfy and fast media optimisation. You can use every component of the media which has an effect of the metabolic activity.
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Osmolarity [osmol/kg]

19. Sample Fermentations
Comparison of RAMOS to a stirred reactor with online exhaust gas analytics
Mammalian cell culture Hybridoma
Dipl.-Ing. M. Canzoneri
stirred tank reactor (2 litre culture volume)
RAMOS (0,05 litre culture volume)
OTR [mol/(L·h)]
This diagram shows the comparison between a 2 liter fermenter and the RAMOS. Here you can see that the OTR of RAMOS and the OTR of the fermenter are nearly the same. This is a strong argument for the RAMOS as an alternative for expensive fermentation in liter-scale fermenters. You can gain the same results with 40-fold lower media consumption.
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Time of Fermentation [h]

20. Sample Fermentations Effect of different liquid volumes
Bacterium Corynebacterium glutamicum
OTR [mol/(L·h)]
Time of Fermentation [h]
Flask 1 : 10 mL
Flask 2 : 15 mL
Flask 3 : 20 mL
Flask 4 : 30 mL
Flask 5 : 40 mL
Flask 6 : 50 mL
oxygen limitation
This diagram shows how the filling level affects the max. oxygen transfer. The more a flask is filled, the less is the oxygen transfer.
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21. Sample Fermentations Effect of different substrate concentrations
Bacterium Pseudomonas fluorescens
OTR [mol/(L·h)]
fermentation time [h]
1x concentrated
2x concentrated
4x concentrated
This diagram shows a fermentation of the bacteria Pseudomanas floureszenz. You see the data of three fermentations, which were carried out parallel in three measuring flasks. The differences between the flasks are, that we varied the concentration of the media. One fold , two fold and four fold concentrated. The pre culture of this main fermentation had an one fold concentrated medium. The first result is that you get deviations in the lag-phase duration. The medium which is identical to the pre culture has the shortest lag time, because the micro organisms do not have to adapt to a new media. Than more the medium concentration differs from the pre culture medium than longer is the lag phase, respectively the time the micro organisms need to adapt to the new media. The second result is than higher medium concentration is than lower is the maximum achievable oxygen transfer capacity. The reason is, that than more the media is concentrated than lower is the solubility of oxygen and the maximum oxygen transfer capacity.
The last point I want to mention here is that with the rise of the osmotic pressure the maximum growth rate declines, too.
This example shows very well the effects of medium variations on the course of the oxygen transfer rate and how RAMOS for example helps you to find the optimal end of fermentation.
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22. Sample Fermentations Media- and process optimisation
Yeast Hansenula polymorpha
OTR [mol/(L·h)]
Time of Fermentation [h]
Media with 100% comp. 1,
30 ml liquid
Media with 200% comp. 1,
20 ml liquid
This diagram shows the history of a media optimisation.
1.) The initial situation is showed in the green curve. The decreasing slope of the curve lets suspect a substrate limitation.
2.) After doubling the concentration of component 1, you get the blue curve, which shows a oxygen limitation.
3.) After reducing the filling level, we get the optimal shape.
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23. Sample Fermentations Cell-growth within a RAMOS experiment
Mammalian cell cultures Hybridoma
Dipl.-Ing. M. Canzoneri
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24. 8-time parallel measurement
Sample Fermentations
Cell proliferation within a RAMOS experiment
Mammalian cell culture Hybridoma
Dipl.-Ing. M. Canzoneri
Cell density [N/ml]
This diagram shows the cell density between the 8 shaking flasks in the RAMOS. You see that the proliferation rate is nearly the same in each flask.
This diagramm shows the comparability of the eight shaking flasks.
8-time parallel measurement
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120
160
Time of Fermentation [h]

25. Easy Handling little required space – RAMOS fits to normal bench top
virtual non-stop operation by very short set-up time
easy and fast-learnable appliance
fully automated user software
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26. Operating Interface
The user interface of the RAMOS controll program is clearly structured. The workflow follows the sequence of the buttons: new experiment, parameterize, ocygen calibration ...
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27. Flask Overview
The overview window shows the diagrams of 8 RAMOS flasks. By clicking on the enlarge button you brach to a full screen diagram of a flask.
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28. Oxygen Transfer Rate (OTR)
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29. Detail View for each Flask
(OTR, CTR, RQ)
Here are the different metaboloc-stages shown.
lag-phase
Exponential-phase – OTR reaches oxygen limitation, yeast does crap-tree
Limiting substrate is consumed – CTR decreases rapidly
After 48 h metabolism has changed and yeast is now consuming ethanol – after that it is consuming everything which contains a C-source
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30. O2-, CO2 - Transfer Balancing of the total
oxygen transfer during the fermentation process
Via the registers at the bottom you can branch to diagrams for OT, CT, growth rate (next page) etc.
Oxygen transfer (OT)
Carbon dioxide transfer (CT)
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31. maximum Growth Rate µ maximum growth rate µ growth rate µ
The maximum growth rate is a fully calculated value. In the diagrams only the highest point is on interest – it is the time of maximum growth
e.g. curve 4 at about hours and curve 2 at 18 hours.
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growth rate µ

32. Shedding light on your process
OTR
CTR
Shedding light on your process!
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33. Economic efficiency consideration
OTR [mol/(L·h)]
Time of Fermentation [h]
Media with 100% comp. 1,
30 ml liquid
Media with 200% comp. 1,
20 ml liquid
The variation of the media concentration led to an
reduction of the time of fermentation of ca. 37 %
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Time of amortisation: ca. 6 months

34. Cell culture (Hybridoma)
Dosing
Tabellengestützte Dosierprofile. Frei programmierbare Feed-Strategien.
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35. FTT® Fluid-Train System
Dosing and automated samplin
Dosierung und Probenahme durch einen einzigen Schlauch.
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36. FTT® Fluid-Train System
controlled loop dosing
Feed-Regelung auf den OTR.
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37. RQFeed™ - Feeding algorithm
determination of RQ by OUR, CER online measurement
exact feeding of cultures
significant increase in production rates
shortening of the fermentation periods
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38. CellDrum™ - Cell force measurement
reproducable biomechanical measurement
personalised drug and toxin research
alternative to animal experiments
integrated, fully automated and heat sterilisable pipetting unit
Multiwell units with integrated sensorics
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39. HiSense™ - Precision Gas Analysis
1 to 8(5) Measurement Channels for 1 to 4 Fermenters
High Resolution Measurement
Humidity Compensation (-c Version)
"True" OUR, CER and RQ Measurements (-c Version)
Low Interference
Possible Overpressure
Wear-resistant Sensor System
Compact Design
Additional Functions can be integrated
Optionally free Programmability
Numerous Coupling Options
Data Export is possible
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40. Cell culture (Hybridoma)
Without dosing
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41. Cell culture (Hybridoma)
Dosing according to OTR controlled loop starting at RQ<1
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42. Cell culture (Hybridoma)
Dosing program
Scriptsprache für Feed-Algorithmen, online Auswertung etc.
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43. Cell culture (Hybridoma)
Parameterisation of taking samples
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44. Cooperations and Publications
Prof. Dr. Manfred Biselli
Aachen University of Applied Science, Division Jülich
Faculty of Biotechnology
Prof. Dr.-Ing. Jochen Büchs
RWTH Aachen University,
Faculty of Bioprocess Engineering
Publications: 
Anderlei T., Büchs J., Device for sterile online measurement of the oxygen transfer
rate in shaking flasks, Biochem. Eng. J. 7(2), , 2001 
Stöckmann Ch., Maier U., Anderlei T., Knocke Ch., Gellissen G., Büchs J.,
The Oxygen Transfer Rate as Key Parameter for the Characterisation of Hansenula polymorpha
Screening Cultures, J. Ind. Microbiol. Biotechnol. 30, , 2003 
Anderlei T., Zang W., Büchs J., Online respiration activity measurement (OTR, CTR, RQ)
in shake flasks, Biochem. Eng. J. 17(3), , 2004 
Lotter St., Büchs J. Utilization of power input measurements for optimisation of culture
conditions in shaking flasks, Biochem. Eng. J. 17(3), , 2004
© HiTec Zang GmbH - HRE 
Losen M., Lingen B., Pohl M., BüchsJ., Effect of oxygen-limitation and medium composition
on Escherichia coli in small-scale cultures, Biotechnol. Progress. (accepted)