The authors are grateful to Dr. Thomas Rademacher for providing the pPAM plant expression vector and Ibrahim Al Amedi for cultivating the tobacco plants used in this study. We would like to thank Dr. Richard M. Twyman for his assistance with editing the manuscript. This work was in part funded by the European Research Council Advanced Grant &#8220;Future-Pharma&#8221;, proposal number 269110 and the Fraunhofer Zukunftsstiftung (Fraunhofer&#160;Future Foundation).

1. Planning a DoE Strategy
<ol>
	<li>Identify relevant factors and responses for inclusion in the design.
	<ol>
		<li>Define one or several responses for measurement. Here, 2G12 and DsRed expression levels were used (&#956;g/ml), including the minimum detectable difference regarded as relevant (10 and 20 &#956;g /ml, respectively) and an approximate value for the estimated standard deviation of the system (4 and 8 &#956;g/ml, respectively) based on previous experiments.</li>
		<li>Use the available literature, data fro...

<ol>
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The publication fee was partially sponsored by the companies Statease, Inc. (USA) and Statcon (Germany), which were not involved in the involved in the preparation of the manuscript or responsible for any of its contents.

Every experiment requires careful planning because resources are often scarce and expensive. This is particularly true for DoE strategies because errors during the planning phase (e.g. selecting a base model that does not cover all significant factor interactions) can substantially diminish the predictive power of the resulting models and thus devalue the entire experiment. However, these errors can easily be avoided by following basic procedures.
Considerations during DoE planning
<...

The production of biopharmaceutical proteins in plants is advantageous because plants are inexpensive to grow, the platform can be scaled up just by growing more plants, and human pathogens are unable to replicate 1,2. Transient expression strategies based for example on the infiltration of leaves with Agrobacterium tumefaciens provides additional benefits because the time between the point of DNA delivery and the delivery of a purified product is reduced from years to less than 2 months 3. Transient expression is also used for functional analysis, e.g. to test genes for their ability to complement loss-of-function mutants or to investigate protein interactions 4-6. However, transient expression levels tend to show greater batch-to-batch variation than expression levels in transgenic plants 7-9. This reduces the likelihood that biopharmaceutical manufacturing processes based on transient expression will be approved in the context of good manufacturing practice (GMP) because reproducibility is a critical quality attribute and is subject to risk assessment 10. Such variation can also mask any interactions that researchers intend to investigate. Therefore, we set out to identify the major factors that affect transient expression levels in plants and to build a high-quality quantitative predictive model.
The one-factor-at-a-time (OFAT) approach is often used to characterize the impact (effect) of certain parameters (factors) on the outcome (response) of an experiment 11. But this is suboptimal because the individual tests (runs) during an investigation (experiment) will be aligned like pearls on a string through the potential area spanned by the factors that are tested (design space). The coverage of the design space and hence the degree of information derived from the experiment is low, as shown in Figure 1A 12. Furthermore, interdependencies among different factors (factor interactions) can remain concealed resulting in poor models and/or the prediction of false optima, as shown in Figure 1B 13.
The drawbacks described above can be avoided by using a design of experiments (DoE) approach in which the runs of an experiment are scattered more evenly throughout the design space, meaning that more than one factor is varied between two runs 14. There are specialized designs for mixtures, screening factors (factorial designs) and the quantitation of factor impacts on responses (response surface methods, RSMs) 15. Furthermore, RSMs can be realized as central-composite designs but can also be achieved effectively by using specialized software that can apply different criteria for the selection of runs. For example, the so called D-optimality criterion will select runs so to minimize the error in the coefficients of the resulting model, whereas the IV-optimality criterion selects runs that achieve the lowest prediction variance throughout the design space 15,16. The RSM we describe here allows the precise quantitation of transient protein expression in plants, but it can easily be transferred to any system involving several (~5-8) numeric factors (e.g. temperature, time, concentration) and a few (~2-4) categoric factors (e.g. promoter, color) in which a mechanistic description is unavailable or too complex to model.
The DoE approach originated in the agricultural sciences but has spread to other areas because it is transferable to any situation where it is useful to reduce the number of runs necessary to obtain reliable data and generate descriptive models for complex processes. This in turn has led to the inclusion of DoE in the &#34;Guidance for Industry, Q8(R2) Pharmaceutical Development&#34; published by the International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) 17. DoE is now used widely in scientific research and industry 18. However, care must be taken during the planning and execution of the experiment because selecting an improper polynomial degree for the multiple-linear-regression model (base model) can introduce a need for additional runs to model all factor effects correctly. Furthermore, corrupted or missing data generate incorrect models and flawed predictions, and may even prevent any model building attempt as described in the protocol and discussion sections 18. In the protocol section, we will initially set out the most important planning steps for a RSM-based experiment and then explain the design based on the DoE software DesignExpert v8.1. But similar designs can be built with other software including JMP, Modde, and STATISTICA. The experimental procedures are followed by instructions for data analysis and evaluation.
<img alt="Figure 1" fo:content-width="5in" fo:src="/files/ftp_upload/51216/51216fig1highres.jpg" src="/files/ftp_upload/51216/51216fig1.jpg" /> 
Figure 1. Comparison of OFAT and DoE. A. Sequential variation of one factor at a time (OFAT) in an experiment (black, red and blue circles) achieves a low coverage of the design space (hatched regions). In contrast, the variation of more than one factor at a time using the design of experiments (DoE) strategy (green circles) enhances the coverage and thus the precision of the resulting models. B. The biased design space coverage means that OFAT experiments (black circles) can also fail to identify optimal operating regions (red) and predict sub-optimal solutions (large black circle), whereas DoE strategies (black stars) are more likely to identify preferable conditions (large black star).

<table border="0" cellpadding="0" cellspacing="0" width="946">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Design-Expert(R) 8</td>
			<td style="width:195px;">Stat-Ease, Inc.</td>
			<td style="width:119px;">n.a.</td>
			<td style="width:272px;">DoE software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Tryptone</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">8952.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Yeast extract</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">2363.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Sodium chloride</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">P029.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Ampicillin</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">K029.2</td>
			<td>Antibiotic</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Agar-Agar</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">5210.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Escherichia coli K12 DH5a</td>
			<td style="width:195px;">Life technologies</td>
			<td style="width:119px;">18263-012</td>
			<td>Microorganism</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">pPAM</td>
			<td style="width:195px;">GenBank</td>
			<td style="width:119px;">AY027531</td>
			<td>Cloning/expression vector;&#160;</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">NucleoSpin Plasmid&#160;</td>
			<td style="width:195px;">MACHEREY-NAGEL GmbH</td>
			<td style="width:119px;">740588.250</td>
			<td>Plasmid DNA isolation kit</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">NucleoSpin Gel and PCR Clean-up</td>
			<td style="width:195px;">MACHEREY-NAGEL GmbH</td>
			<td style="width:119px;">740609.250</td>
			<td>Plasmid DNA purification kit</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">NanoDrop 2000</td>
			<td style="width:195px;">Thermo Scientific</td>
			<td style="width:119px;">n.a.</td>
			<td>Spectrophotometer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">NcoI</td>
			<td style="width:195px;">New England Biolabs Inc.</td>
			<td style="width:119px;">R3193L</td>
			<td>Restrictionendonuclease</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">EcoRI</td>
			<td style="width:195px;">New England Biolabs Inc.</td>
			<td style="width:119px;">R3101L</td>
			<td>Restrictionendonuclease</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">AscI</td>
			<td style="width:195px;">New England Biolabs Inc.</td>
			<td style="width:119px;">R0558L</td>
			<td>Restrictionendonuclease</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">NEB 4</td>
			<td style="width:195px;">New England Biolabs Inc.</td>
			<td style="width:119px;">B7004S</td>
			<td>Restrictionendonuclease buffer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">TRIS</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">4855.3</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Disodium tetraborate</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">4403.3</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">EDTA</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">8040.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Agarose</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">6352.4</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Bromophenol blue</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">A512.1</td>
			<td>Color indicator</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Xylene cyanol</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">A513.1</td>
			<td>Color indicator</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Glycerol</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">7530.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Mini-Sub Cell GT Cell</td>
			<td style="width:195px;">BioRad</td>
			<td style="width:119px;">170-4406</td>
			<td>Gel electrophoresis chamber</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Agrobacterium tumefaciens strain GV3101:pMP90RK</td>
			<td style="width:195px;">DSMZ</td>
			<td style="width:119px;">12365</td>
			<td>Microorganism</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Electroporator 2510</td>
			<td style="width:195px;">Eppendorf</td>
			<td style="width:119px;">4307000.658</td>
			<td>Electroporator</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Beef extract</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">X975.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Peptone</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">2365.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Sucrose</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">4621.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Magnesium sulfate</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">0261.3</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Carbenicillin</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">6344.2</td>
			<td>Antibiotic</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Kanamycin</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">T832.3</td>
			<td>Antibiotic</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Rifampicin</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">4163.2</td>
			<td>Antibiotic</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">FWD primer</td>
			<td style="width:195px;">Eurofins MWG Operon</td>
			<td style="width:119px;">n.a.</td>
			<td>CCT CAG GAA GAG CAA TAC</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">REV primer</td>
			<td style="width:195px;">Eurofins MWG Operon</td>
			<td style="width:119px;">n.a.</td>
			<td>CCA AAG CGA GTA CAC AAC</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">2720 Thermal cycler</td>
			<td style="width:195px;">Applied Biosystems</td>
			<td style="width:119px;">4359659</td>
			<td>Thermocycler</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">RNAfold webserver</td>
			<td style="width:195px;">University of Vienna</td>
			<td style="width:119px;">n.a.</td>
			<td>Software</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Ferty 2 Mega</td>
			<td style="width:195px;">Kammlott</td>
			<td style="width:119px;">5.220072</td>
			<td>Fertilizer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Grodan Rockwool Cubes 10x10cm</td>
			<td style="width:195px;">Grodan</td>
			<td style="width:119px;">n.a.</td>
			<td>Rockwool block</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Greenhouse</td>
			<td style="width:195px;">n.a.</td>
			<td style="width:119px;">n.a.</td>
			<td>For plant cultivation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Phytotron</td>
			<td style="width:195px;">Ilka Zell</td>
			<td style="width:119px;">n.a.</td>
			<td>For plant cultivation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Omnifix-F Solo</td>
			<td style="width:195px;">B. Braun</td>
			<td style="width:119px;">6064204</td>
			<td>Syringe</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Murashige and Skoog salts</td>
			<td style="width:195px;">Duchefa</td>
			<td style="width:119px;">M 0222.0010</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Glucose</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">6780.2</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Acetosyringone</td>
			<td style="width:195px;">Sigma-Aldrich</td>
			<td style="width:119px;">D134406-5G</td>
			<td>Phytohormon analogon</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">&#160;BioPhotometer plus</td>
			<td style="width:195px;">Eppendorf</td>
			<td style="width:119px;">&#160;6132 000.008</td>
			<td>Photometer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Osram cool white 36 W</td>
			<td style="width:195px;">Osram</td>
			<td style="width:119px;">4930440</td>
			<td>Light source</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Disodium phosphate</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">&#160;4984.3&#160;</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Centrifuge 5415D</td>
			<td style="width:195px;">Eppendorf</td>
			<td style="width:119px;">5424 000.410</td>
			<td>Centrifuge</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Forma -86C ULT freezer</td>
			<td style="width:195px;">ThermoFisher</td>
			<td style="width:119px;">88400</td>
			<td>Freezer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Synergy HT</td>
			<td style="width:195px;">BioTek</td>
			<td style="width:119px;">SIAFRT</td>
			<td>Fluorescence plate reader</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Biacore T200</td>
			<td style="width:195px;">GE Healthcare</td>
			<td style="width:119px;">n.a.</td>
			<td>SPR device</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Protein A</td>
			<td style="width:195px;">Life technologies</td>
			<td style="width:119px;">10-1006</td>
			<td>Antibody binding protein</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">HEPES</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">9105.3</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Tween-20</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">9127.3</td>
			<td>Media component</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">2G12 antibody</td>
			<td style="width:195px;">Polymun</td>
			<td style="width:119px;">AB002</td>
			<td>Reference antibody</td>
		</tr>
	</tbody>
</table>

characterization of complex systems using the design of experiments approach: transient protein expression in tobacco as a case study

Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the additional advantage of short development and production times, but expression levels can vary significantly between batches thus giving rise to regulatory concerns in the context of good manufacturing practice. We used a design of experiments (DoE) approach to determine the impact of major factors such as regulatory elements in the expression construct, plant growth and development parameters, and the incubation conditions during expression, on the variability of expression between batches. We tested plants expressing a model anti-HIV monoclonal antibody (2G12) and a fluorescent marker protein (DsRed). We discuss the rationale for selecting certain properties of the model and identify its potential limitations. The general approach can easily be transferred to other problems because the principles of the model are broadly applicable: knowledge-based parameter selection, complexity reduction by splitting the initial problem into smaller modules, software-guided setup of optimal experiment combinations and step-wise design augmentation. Therefore, the methodology is not only useful for characterizing protein expression in plants but also for the investigation of other complex systems lacking a mechanistic description. The predictive equations describing the interconnectivity between parameters can be used to establish mechanistic models for other complex systems.

A descriptive model for DsRed accumulation during transient expression using different promoters and 5&#39;UTRs
DsRed fluorescence in leaf extracts was used to indicate the expression level of the recombinant protein and thus was used as the response in the DoE strategy. The minimum detectable difference we considered relevant was 20 &#956;g/ml&#160;and the estimated standard deviation of the system was 8 &#956;g/ml&#160;based on initial experiments. Factors included in the tr...

Watch this Scientific Journal Video about Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study at JoVE.com

Characterization of Complex Systems Using the Design of Experiments Approach: Transient Protein Expression in Tobacco as a Case Study

We describe a design of experiments approach that can be used to determine and model the influence of transgene regulatory elements, plant growth and development parameters, and incubation conditions on the transient expression of monoclonal antibodies and reporter proteins in plants.

Plants provide multiple benefits for the production of biopharmaceuticals including low costs, scalability, and safety. Transient expression offers the ...

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Research

JoVE Journal

Bioengineering

16.4K Görüntüleme.  RWTH Aachen University.  Bu bitkilerde monoklonal antikorlar ve raportör proteinlerin geçici transgen ifadesi üzerindeki düzenleyici elemanlar, bitki büyüme ve gelişme parametreleri ve inkübasyon koşullarının etkisini belirlemek ve modellemek için kullanılabilecek deneyler yaklaşımın bir tasarımını tarif eder. 