I would like to acknowledge Dr. Thomas Rademacher for providing the transgenic tobacco seeds and Ibrahim Al Amedi for cultivating the tobacco plants. I wish to thank Dr. Richard M Twyman for editorial assistance and Prof. Dr. Rainer Fischer for fruitful discussions. This work was funded in part by the European Research Council Advanced Grant ''Future-Pharma'', proposal number 269110, the Fraunhofer-Zukunftsstiftung (Fraunhofer Future Foundation) and the Fraunhofer-Gesellschaft Internal Programs under Grant No. Attract 125-600164.

1. Develop an Adequate Experimental Strategy
<ol>
	<li>Identify the environmental and process parameters that are relevant for the flocculation procedure to be established or optimized, i.e. which factors have the strongest effect on flocculation. Typically, there are several such parameters so a DoE approach as recently described 20 is necessary due to the lack of mechanistic models.
	<ol>
		<li>Select parameters (factors) based on literature data 12, prior knowledge and experience with the system. Typical factors include buffer pH, buffer conductivity, incubation time and temperature as well as polymer type and concentration 15,16,27.</li>
		<li>Use the same references (see 1.1) to define meaningful ranges for each numeric factor and levels for categorical factors.</li>
		<li>Define the experimental outcomes (responses) to be monitored and used to evaluate the efficiency of flocculation. Depending on the system, this can be filtrate or supernatant turbidity, settling velocity, aggregate size or the capacity of a subsequent filter 16,23,28-30.</li>
		<li>Ensure the assays used to measure the responses are quantitative, robust and repeatable/reproducible so that the resulting high-quality data can be augmented with experiments performed later or by another operator.</li>
	</ol>
	</li>
	<li>Choose a DoE type suiting the number of factors to be investigated and the degree of knowledge already accumulated about the system. Use available literature to identify a suitable DoE type 20.
	<ol>
		<li>Select a screening design if there is little information about the flocculation system to be investigated, a large number of parameters must be screened or little is known about meaningful ranges for the parameters. Typical screening designs are full and fractional factorial designs. Include center points in the design if the parameters are expected to have a non-linear impact, e.g. saturation above a certain threshold 19.</li>
		<li>Select a response surface methodology (RSM), e.g. central composite design (CCD) 31 or optimal 32,33, if only a few factors with well-known ranges need to be characterized precisely.</li>
	</ol>
	</li>
	<li>Set up the DoE with appropriate software, ensuring a priori quality criteria such as the fraction of design space are met 20.</li>
</ol>
2. Prepare the Flocculation Experiments
<img alt="Figure 1" src="/files/ftp_upload/53940/53940fig1.jpg" /> 
Figure 1: Plant extract flocculation workflow: process scale (left) and benchtop scale (right). Following protein extraction with aqueous buffers, dispersed particles of cell debris are aggregated by the addition of flocculants. The aggregates are then removed by a cascade of bag and depth filtration and the capacity of these filters along with the filtrate turbidities can be used directly to measure the efficiency of flocculation.
<ol>
	<li>Develop a General Experimental Work Flow (Figure 1).
	<ol>
		<li>Use an extraction device that results in the same particle size distribution expected (or already observed) at the final application scale, e.g. a specialized homogenizer. If possible, design a scale-down model of the extractor as described for the homogenization of tobacco leaves 10.</li>
		<li>Define the extract volumes used during flocculation experiments (here 20 ml). Select a volume that allows a representative number of particles to be present in the reaction vessel, e.g. flocculation experiments in 20 ml aliquots yielded reproducible and scalable results for tobacco extracts containing ~7% [w/v] solids 34 and particle sizes of ~0.5 &#181;m to ~3 mm 16.</li>
		<li>Design all monitoring and post-flocculation operations so that they are representative of the final application scale, e.g. select filters with the same particle retention behavior as those used at the production scale.</li>
	</ol>
	</li>
	<li>Cultivate the Plants from Which the Extracts Will be Derived.
	<ol>
		<li>Use the same plant line, here Nicotiana tabacum cv. Petit Havana SR1, and cultivation conditions that will be used during production as previously described 33.</li>
		<li>If other feed stocks will be processed, prepare these feed stocks so that they are representative of the final application scale, e.g. use authentic buffers, take into account any dilution steps during the process and stick to the anticipated pH and conductivity, here pH 7.5 and conductivity 30 mS cm-1.</li>
	</ol>
	</li>
	<li>Prepare Filtration Utilities, Turbidity-Monitoring Devices and Sampling Vessels.
	<ol>
		<li>Cut the filter materials to the required sizes, here 15 x 15 cm2, if they are not ready-to-use modules. Ensure all monitoring and analysis devices are functional and label all sample tubes.</li>
		<li>Even though these are simple tasks, prepare these items in time to ensure that they will not cause interruptions during the actual flocculation experiments. Avoid delays because they can interfere with the results given that flocculation is a time-dependent process.</li>
	</ol>
	</li>
	<li>Prepare Flocculant Stock Solutions. CAUTION: Wear appropriate personal protection equipment when handling flocculants, e.g. gloves. The materials can be dangerous (hazard labels according to Europe UE 67/548/CEE, 1999/45/CE include N, Xi or Xn). Avoid dust and refer to the material safety data sheets. Work under a fume hood.
	<ol>
		<li>Choose a stock concentration for each flocculant, here 80.0 g L-1 for the two PEI flocculants that were used. Select concentrations as high as possible to avoid sample dilution when adding the flocculant, which would reduce particle concentration and thus affect flocculation efficiency.</li>
		<li>Account for any pre-dilution that reflects the manufacturer&#39;s formulation of the polymer, e.g. if the polymer is already supplied as an aqueous 50% [w/v] solution. Flocculant stock solutions of 4-8% [w/v] were found to be the most suitable so far.</li>
		<li>Bearing in mind the points discussed above, make sure the flocculant concentration does not generate a highly viscous solution that inhibits pipetting, potentially causing errors because the final flocculant concentration is not adjusted correctly.</li>
		<li>Use the same stock concentration for all flocculants if possible because this will facilitate the setup of a pipetting scheme (2.5) thus reducing the likelihood of errors.</li>
		<li>Adjust the pH and conductivity of each flocculant stock solution to match the conditions of the extracts, here pH 4&#8722;10 and conductivity 15&#8722;55 mS cm-1. Prepare individual stocks for a single flocculant if more than one set of pH and/or conductivity conditions is tested for that polymer.</li>
		<li>Prepare flocculant stock solutions freshly, no longer than 48 h before use. Even though flocculation can be induced with polymer stocks stored for more than 4 weeks, the efficiency may decline due to polymer hydrolysis at high or low pH values. See the manufacturer&#39;s documentation for further details.</li>
		<li>Make sure that the parameters selected for the DoE can be adjusted precisely for each sample during the experiment, e.g. ensure there are heating/cooling baths available to adjust incubation temperatures, here 4 &#176;C, 20 &#176;C and 37 &#176;C. If mixing during flocculation is part of the experiment, ensure that the mixing device is representative of the final application scale in terms of critical parameters such as power input.</li>
	</ol>
	</li>
	<li>Convert the DoE Schedule into a Pipetting Scheme.
	<ol>
		<li>Convert the different flocculant concentrations to be tested into volumes of stock solution that will be added to the extract samples: divide the final flocculant concentrations by the stock concentration and multiply by the sample volume used in the flocculation experiments. Identify the largest resulting final volume, e.g. if 20 ml of sample is mixed with a maximum of 2 ml flocculant stock solution this will be 22 ml.</li>
		<li>Calculate volumes of buffer required to maintain the same final volume in all flocculation aliquots based on the largest volume of flocculant stock to be added, e.g. if 0.75 ml of flocculant stock must be added to a sample then 1.25 ml of buffer is required to maintain the final sample volume of 22 ml (2.5.1).</li>
		<li>Sum up the volumes of flocculant stock solution for each polymer and flocculation condition to calculate the absolute volumes of stock solution that are required for the DoE.</li>
	</ol>
	</li>
	<li>Harvest Tobacco Leaves and Prepare the Extract.
	<ol>
		<li>Remove the top six leaves (or as many as indicated by in the process instructions) from tobacco plants of an appropriate age, e.g. 6 weeks old, and transfer to a suitable extraction device such as a homogenizer or screw press.</li>
		<li>Add three volumes of extraction buffer per gram biomass, e.g. 300 ml per 100 g, and blend for 8 min.</li>
		<li>Prepare individual extracts with the appropriate buffers if different pH and/or conductivities are being tested. Here, this involves homogenizing the plant material for 3 x 30 sec in a blender or a juicer 34.</li>
		<li>Alternatively, prepare the extract in a manner that is representative of the process under investigation.</li>
	</ol>
	</li>
	<li>Aliquot the Extract and Add the Buffer.
	<ol>
		<li>Manually and thoroughly stir the extract during the entire procedure to ensure the samples are homogeneous with an even distribution of particles.</li>
		<li>Precisely distribute the extract among the pre-labeled reaction tubes by decanting, here 20 ml in each vessel. Self-standing 50 ml tubes simplify handling and are ideal for 20 ml samples.</li>
		<li>Add the volume of each extraction buffer required to maintain the fixed final volume for each individual reaction tube using a suitable pipette.</li>
	</ol>
	</li>
</ol>
3. Flocculate the Plant Extracts with Different Polymers
<ol>
	<li>Pipette the required volume of flocculant stock solution, here 0.1&#8722;2.0 ml, to the samples sequentially as indicated by the randomized run order of the DoE. Thoroughly mix each sample immediately after the addition of flocculant by intense manual shaking for precisely 20 sec.
	<ol>
		<li>If required, adjust the shaking time for other feed stocks to ensure thorough mixing, but strictly ensure consistent mixing times for all samples. Bear in mind that prolonged mixing may cause the irreversible disruption of flocs and inconsistently applied force during shaking can distort the flocculation results.</li>
	</ol>
	</li>
	<li>Optional: Modify the procedure described above for the simultaneous application of two or more flocculants.
	<ol>
		<li>Option 1: Instead of a single polymer add a mixture of two or more flocculants, here PEI and chitosan. Use the flocculant combinations defined in the DoE. Incorporate the ratio and absolute concentrations of the polymers as individual parameters during the DoE setup (1.1).</li>
		<li>Option 2: Add two or more polymers sequentially to the extract.
		<ol>
			<li>Use the individual polymer concentrations, their type, and the incubation time between each addition to the extract, as additional factors during the DoE setup.</li>
			<li>Also use this approach to test whether the repeated addition of a single polymer can improve flocculation. Use a stepwise addition to simulate the slow addition of a flocculant, e.g. four steps, each adding 0.25 ml 80 g L-1 flocculant stock to a 20 ml volume over 4 min can mimic the addition of flocculant with a flow rate of 0.25 ml min-1.</li>
			<li>In all cases, identify a new maximum final sample volume for this setup by adding the maximum volumes of all flocculants to the sample volume, here still 22 ml, and recalculate the required volumes of flocculant stock solutions and buffers for volume adjustment if necessary.</li>
		</ol>
		</li>
	</ol>
	</li>
	<li>Incubate the samples for the times defined in the DoE, typically 3-30 min, to allow floc formation. Make sure all other incubation conditions, e.g. temperature, are set according to the DoE.</li>
	<li>Observe and document floc formation. Record the progress of floc formation as required, e.g. as mm of floc settling per min by measuring the height of the settled solids. If necessary, prolong flocculation for an extended time period such as overnight.</li>
	<li>Filter the Flocculated Extract.
	<ol>
		<li>Use the filter materials prepared earlier (2.3) to clarify the flocculated extract after the appropriate incubation time by decanting the flocculated samples through the filter material and into a clean vessel or reaction tube.
		<ol>
			<li>Do not re-suspend the settled flocs before filtration and apply the extract with at a rate of ~300 ml min-1 to the filter, corresponding to 3&#8722;4 sec for a 20 ml sample.</li>
			<li>Confirm the performance of the filtration step if a different material is used in the bench-top experiments compared to the final process in terms of particle retention, e.g. by measuring the particle size distribution in both sample types 11.</li>
		</ol>
		</li>
		<li>Analyze the filtrate in terms of turbidity and/or particle size distribution as required using appropriate devices, e.g. a turbidimeter.</li>
		<li>Optional: repeat the analysis after extended incubation times, e.g. 12&#8722;24 hr, to investigate the formation or reformation of unstable flocs.</li>
	</ol>
	</li>
	<li>Analyze the Samples in Terms of the Pre-defined Responses (1.1.3).
	<ol>
		<li>Take samples from the filtrates and analyze them for additional response parameters, e.g. the concentrations of different target proteins or valuable products.</li>
		<li>Optional: Analyze the retentate (mostly solids) for the same parameters to close the mass balance of the process. In particular, quantify the effect of flocculants on liquid recovery by comparing the solids mass remaining after samples are treated or not treated with flocculant.</li>
	</ol>
	</li>
	<li>Confirm the data quality and transfer the results to the DoE software.
	<ol>
		<li>Look for extreme values in the collected response data, e.g. unexpectedly high values.</li>
		<li>Ensure that all response data are correctly aligned with their corresponding experimental conditions.</li>
		<li>Transfer the results into the DoE software and make sure the standard and randomized run orders are not mixed up.</li>
	</ol>
	</li>
</ol>
4. Evaluate the DoE
<ol>
	<li>Use the built-in data analysis tools of the DoE software to develop a predictive model as previously described 20.
	<ol>
		<li>Select a proper data transformation mode if required to facilitate model building, here log10. A ratio larger than 10 for largest vs. smallest response value indicates that a data transformation may be required. Identify the most suitable transformation using the appropriate statistical tools, e.g. a Box-Cox plot 35.</li>
		<li>Chose a base model that (i) fits to the selected DoE (1.2) and (ii) agrees with previous knowledge about the system under investigation based on the analysis of variance (ANOVA) tools of the DoE software, e.g. a second-order polynomial often fits better to the observed effect of incubation time than a first-order polynomial.</li>
		<li>Remove insignificant model factors, e.g. p &#62;0.05, or factor interactions iteratively by deselecting them, thereby reducing the model complexity and increasing its predictive power.</li>
		<li>Confirm the model quality by comparing R2, adjusted R2 and predicted R2 along with the normal probability plot of the studentized residuals, residuals-vs-run, predicted-vs-actual and Box-Cox plots 36. All R2 values should be within a 0.2 range.</li>
		<li>Make sure that the final model agrees with basic assumptions of physics and thermodynamics, e.g. no negative concentrations are predicted.</li>
	</ol>
	</li>
	<li>Use the model to predict conditions that are most favorable for the system under investigation, here a low turbidity.
	<ol>
		<li>Select the most important responses and their preferred states, e.g. minimal turbidity. Combine these selections by maximizing a desirability function or similar tools, which are built-in features of several DoE software packages 36.</li>
		<li>Depending on the intended application of the model, select confirmation runs to verify the optimal conditions and/or the predictive power of the model in general, e.g. if the conditions predicted to be most favorable were not part of the initial DoE select them as follow-up experiments.</li>
	</ol>
	</li>
</ol>
5. Improve the Model and Verify the Predictive Power
<ol>
	<li>Narrow down the initial design space to the most desirable operation conditions, e.g. low turbidity in the 0&#8722;1,000 nephelometric turbidity units (NTU) range, based on the model predictions (4.2).</li>
	<li>Set up a new DoE within these ranges, including only those factors that have been identified as significant or relevant (4.1.2)). 
	NOTE: A factor can be significant in terms of model analysis but irrelevant for a process, i.e. its effect on a response is &#60;1% compared to that of other factors.</li>
	<li>Repeat steps 1-5.2 until the quality of the model predictions matches the requirements, e.g. the standard deviation of the model as indicated by the software is sufficient for the intended application. Modify the experimental strategy if required for these iterations, e.g. use only one flocculant in the refinement.</li>
	<li>Transfer and confirm the results from the scale-down model to the pilot scale or final production scale.</li>
</ol>

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E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Host+selection+as+a+downstream+strategy:+Polyelectrolyte+precipitation+of+beta-glucuronidase+from+plant+extracts.">Host selection as a downstream strategy: Polyelectrolyte precipitation of beta-glucuronidase from plant extracts.</a> Biotechnol. Bioeng. 77, 148-154 (2002).</li><li>Holler, C., Vaughan, D., Zhang, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Polyethyleneimine+precipitation+versus+anion+exchange+chromatography+in+fractionating+recombinant+beta-glucuronidase+from+transgenic+tobacco+extract.">Polyethyleneimine precipitation versus anion exchange chromatography in fractionating recombinant beta-glucuronidase from transgenic tobacco extract.</a> J. Chromatogr. A. 1142, 98-105 (2007).</li><li>Buyel, J. F., Fischer, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synthetic+polymers+are+more+effective+than+natural+flocculants+for+the+clarification+of+tobacco+leaf+extracts.">Synthetic polymers are more effective than natural flocculants for the clarification of tobacco leaf extracts.</a> J. Biotechnol. 195, 37-42 (2014).</li><li>Pearson, C. R., Heng, M., Gebert, M., Glatz, C. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Zeta+potential+as+a+measure+of+polyelectrolyte+flocculation+and+the+effect+of+polymer+dosing+conditions+on+cell+removal+from+fermentation+broth.">Zeta potential as a measure of polyelectrolyte flocculation and the effect of polymer dosing conditions on cell removal from fermentation broth.</a> Biotechnol. Bioeng. 87, 54-60 (2004).</li><li>Buyel, J. F., Gruchow, H. M., Boes, A., Fischer, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Rational+design+of+a+host+cell+protein+heat+precipitation+step+simplifies+the+subsequent+purification+of+recombinant+proteins+from+tobacco.">Rational design of a host cell protein heat precipitation step simplifies the subsequent purification of recombinant proteins from tobacco.</a> Biochem. Eng. J. 88, 162-170 (2014).</li><li>Wang, S., Liu, C., Li, Q. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impact+of+polymer+flocculants+on+coagulation-microfiltration+of+surface+water.">Impact of polymer flocculants on coagulation-microfiltration of surface water.</a> Water Res. 47, 4538-4546 (2013).</li><li>Menkhaus, T. J., Anderson, J., Lane, S., Waddell, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Polyelectrolyte+flocculation+of+grain+stillage+for+improved+clarification+and+water+recovery+within+bioethanol+production+facilities.">Polyelectrolyte flocculation of grain stillage for improved clarification and water recovery within bioethanol production facilities.</a> Bioresour. Technol. 101, 2280-2286 (2010).</li><li>Mune, M. A. M., Minka, S. R., Mbome, I. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimising+functional+properties+during+preparation+of+cowpea+protein+concentrate.">Optimising functional properties during preparation of cowpea protein concentrate.</a> Food Chem. 154, 32-37 (2014).</li><li>Buyel, J. F., Fischer, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Predictive+models+for+transient+protein+expression+in+tobacco+(Nicotiana+tabacum+L.)+can+optimize+process+time,+yield,+and+downstream+costs.">Predictive models for transient protein expression in tobacco (Nicotiana tabacum L.) can optimize process time, yield, and downstream costs.</a> Biotechnol. Bioeng. 109, 2575-2588 (2012).</li><li>Buyel, J. F., Kaever, T., Buyel, J. J., Fischer, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Predictive+models+for+the+accumulation+of+a+fluorescent+marker+protein+in+tobacco+leaves+according+to+the+promoter/5'UTR+combination.">Predictive models for the accumulation of a fluorescent marker protein in tobacco leaves according to the promoter/5'UTR combination.</a> Biotechnol. Bioeng. 110, 471-482 (2013).</li><li>Buyel, J. F., Fischer, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+juice+extractor+can+simplify+the+downstream+processing+of+plant-derived+biopharmaceutical+proteins+compared+to+blade-based+homogenizers.">A juice extractor can simplify the downstream processing of plant-derived biopharmaceutical proteins compared to blade-based homogenizers.</a> Process Biochem. 50, 859-866 (2014).</li><li>Anderson, M. J., Whitcomb, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> DOE Simplified: Practical Tools for Effective Experimentation. Vol. 1. 1, (2000).</li><li>Anderson, M. J., Whitcomb, P. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Response Surface Methods Simplified. , (2005).</li><li>Buyel, J. F., Fischer, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Generic+chromatography-based+purification+strategies+accelerate+the+development+of+downstream+processes+for+biopharmaceutical+proteins+produced+in+plants.">Generic chromatography-based purification strategies accelerate the development of downstream processes for biopharmaceutical proteins produced in plants.</a> Biotechnol. J. 9, 566-577 (2014).</li><li>Myers, R. H., Montgomery, D. C., Anderson-Cook, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Response Surface Methodology: Process and Product Optimization Using Designed Experiments. , (2009).</li></ol>

The author has no conflicts of interest to disclose.

The most important aspect to consider when setting up a DoE to characterize particle flocculation is that the design must in principle be able to detect and describe the anticipated or possible effects 36,38, e.g. the influence of pH, polymer type and polymer concentration 16. Therefore, it is important to evaluate the fraction of design space (FDS) before starting the actual experiments. The FDS is the fraction of the multidimensional experimental space (covered by the design factors, ...

Plants are widely used to produce food commodities such as fruit juices, but they can also be developed as platforms for the manufacture of higher-value biopharmaceutical products 1-3. In both cases, downstream processing (DSP) often begins with the extraction of liquids from tissues such as leaves or fruits, followed by the clarification of particle-laden extracts 4,5. For the manufacture of biopharmaceuticals, the costs of DSP can account for up to 80% of the overall production costs 6,7 and this in part reflects the high particle burden present in extracts prepared by disruptive methods such as blade-based homogenization 8,9. Although the rational selection of filter layers to match the particle size distribution in the extract can increase filter capacity and reduce costs 10,11, the improvement can never exceed the ceiling of absolute capacity defined by the number of particles that must be retained per unit of filter area to achieve clarification.
The ceiling can be lifted if fewer particles reach the surface of the finest filters in the filtration train, and this can be achieved if dispersed particles are mixed with polymers known as flocculants that promote aggregation to form large flocs 12. Such flocs can be retained further upstream by coarser and less expensive bag filters, reducing the particle burden reaching the finer and more expensive depth filters. The polymers must have safety profiles suitable for their applications, e.g. for biopharmaceuticals they must be compliant with good manufacturing practice (GMP), and typically they must have a molar mass &#62;100 kDa and can either be neutral or charged 13. Whereas neutral flocculants generally act by cross-linking dispersed particles causing their aggregation and the formation of flocs with diameters &#62;1 mm 11, charged polymers neutralize the charge of dispersed particles, reducing their solubility and thus causing precipitation 14.
Flocculation can be improved by adjusting parameters such as buffer pH or conductivity, and the polymer type or concentration, to match the properties of the extract 15,16. For tobacco extracts pretreated with 0.5-5.0 g L-1 polyethylenimine (PEI), a greater than 2-fold increase in depth filter capacity was reported in a 100-L pilot-scale process. The cost of this polymer is less than &#8364;10 kg-1 so its introduction into the process resulted in cost savings of about &#8364;6,000 for filters and consumables per batch 16 or even more when combined with cellulose-based filter aids 17. Even so, predictive models are required to evaluate the a priori economic benefits of flocculants because their inclusion can require hold steps of 15-30 min 16,18, resulting in further investment costs for storage tanks. However, there are currently no mechanistic models available that can predict the outcome of such experiments due to the complex nature of flocculation. Therefore, a more appropriate design-of-experiments (DoE) approach 19 was developed as described in this article. A protocol for the general DoE procedure has recently been published 20.
Small-scale devices are now available for the high-throughput screening of flocculation conditions 21. However, these devices may not realistically simulate conditions during the flocculation of plant extracts because the dimensions of the reaction vessel (~7 mm for wells on a 96-well plate) and the particles or flocs can be less than an order of magnitude apart. This can affect mixing patterns and thus the predictive power of the model. Furthermore, it can be difficult to scale down processes involving precipitation due to non-linear changes in the mixing behavior and precipitate stability 22. Therefore, this article outlines a bench-top-scale screening system with a throughput of 50-75 samples per day, yielding results that are scalable from the initial 20 ml reaction volume to a 100 L pilot-scale process 16. When combined with a DoE approach, this allows the predictive models to be used for process optimization and documentation as part of a quality-by-design concept.
The method described below may also be adapted to biopharmaceuticals produced in cell culture-based processes, where flocculants are also being considered as a cost-saving tool 23. It can also be used to model the precipitation of target proteins from a crude extract as part of a purification strategy, as demonstrated for &#946;-glucuronidase produced in canola, maize and soybean 24,25. A detailed description of flocculant properties can be found elsewhere 16,26 and it is important to ensure that the polymer concentrations are either non-toxic or below harmful levels in the final product 11.

<table border="0" cellpadding="0" cellspacing="0" width="946">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">2100P Portable Turbidimeter</td>
			<td style="width:195px;">Hach</td>
			<td style="width:119px;">4650000</td>
			<td style="width:272px;">Turbidimeter</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>
		<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;">28-9750-01</td>
			<td>SPR device</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">BP-410</td>
			<td style="width:195px;">Furh</td>
			<td style="width:119px;">2632410001</td>
			<td>Bag filter</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Catiofast VSH</td>
			<td style="width:195px;">BASF</td>
			<td style="width:119px;">79002360</td>
			<td>Flocculating agent</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;">Centrifuge tube 15 mL</td>
			<td style="width:195px;">Labomedic</td>
			<td style="width:119px;">2017106</td>
			<td>Reaction tube</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Centrifuge tube 50 mL self-standing</td>
			<td style="width:195px;">Labomedic</td>
			<td style="width:119px;">1110504</td>
			<td>Reaction tube</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Chitosan</td>
			<td style="width:195px;">Carl Roth GmbH</td>
			<td style="width:119px;">5375.1</td>
			<td>Flocculating agent</td>
		</tr>
		<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>DoE software</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;">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;">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;">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;">Grodan Rockwool Cubes 10x10cm</td>
			<td style="width:195px;">Grodan</td>
			<td style="width:119px;">102446</td>
			<td>Rockwool block</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;">K700P 60D</td>
			<td style="width:195px;">Pall</td>
			<td style="width:119px;">5302305</td>
			<td>Depth filter layer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">KS50P 60D</td>
			<td style="width:195px;">Pall</td>
			<td style="width:119px;">B12486</td>
			<td>Depth filter layer</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Miracloth</td>
			<td style="width:195px;">Labomedic</td>
			<td style="width:119px;">475855-1R</td>
			<td>Filter cloth</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">MultiLine Multi 3410 IDS</td>
			<td style="width:195px;">WTW</td>
			<td style="width:119px;">WTW_2020</td>
			<td>pH meter / conductivity meter</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;">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;">Polymin P</td>
			<td style="width:195px;">BASF</td>
			<td style="width:119px;">79002360</td>
			<td>Flocculating agent</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">POLYTRON PT 6100 D</td>
			<td style="width:195px;">Kinematica</td>
			<td style="width:119px;">11010110</td>
			<td>Homogenization device with custom blade tool</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;">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;">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;">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;">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;">VelaPad 60</td>
			<td style="width:195px;">Pall</td>
			<td style="width:119px;">VP60G03KNH4</td>
			<td>Filter housing</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:360px;">Zetasizer Nano ZS</td>
			<td style="width:195px;">Malvern</td>
			<td style="width:119px;">ZEN3600</td>
			<td>DLS particle size distribution measurement</td>
		</tr>
	</tbody>
</table>

procedure to evaluate the efficiency of flocculants for the removal of dispersed particles from plant extracts

Plants are important to humans not only because they provide commodities such as food, feed and raw materials, but increasingly because they can be used as manufacturing platforms for added-value products such as biopharmaceuticals. In both cases, liquid plant extracts may need to be clarified to remove particulates. Optimal clarification reduces the costs of filtration and centrifugation by increasing capacity and longevity. This can be achieved by introducing charged polymers known as flocculants, which cross-link dispersed particles to facilitate solid-liquid separation. There are no mechanistic flocculation models for complex mixtures such as plant extracts so empirical models are used instead. Here a design-of-experiments procedure is described that allows the rapid screening of different flocculants, optimizing the clarification of plant extracts and significantly reducing turbidity. The resulting predictive models allow the identification of robust process conditions and sets of polymers with complementary properties, e.g. effective flocculation in extracts with specific conductivities. The results presented for tobacco leaf extracts can easily be adapted to other plant species or tissues and will thus facilitate the development of more cost-effective downstream processes for commodities and plant-derived pharmaceuticals.

Flocculation of tobacco extract with different polymers
The method described above was successfully used to develop a process for the flocculation of tobacco extracts during the manufacture of a monoclonal antibody (the HIV-neutralizing antibody 2G12) and a fluorescent protein (DsRed) (Figure 1) 16, and has since been transferred to other proteins including lectins, malaria vaccine candidates and fusi...

Watch this Scientific Journal Video about Procedure to Evaluate the Efficiency of Flocculants for the Removal of Dispersed Particles from Plant Extracts at JoVE.com

Procedure to Evaluate the Efficiency of Flocculants for the Removal of Dispersed Particles from Plant Extracts

The design-of-experiments procedure presented here allows the evaluation of different flocculants in terms of their ability to aggregate dispersed particles in plant extracts, thus reducing turbidity and the costs of downstream processing.

Plants are important to humans not only because they provide commodities such as food, feed and raw materials, but increasingly because they can be used ...

procedure-to-evaluate-efficiency-flocculants-for-removal-dispersed

Research

JoVE Journal

Biology

8.8K Views.  Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e. V.. The design-of-experiments procedure presented here allows the evaluation of different flocculants in terms of their ability to aggregate dispersed particles in plant extracts, thus reducing turbidity and the costs of downstream processing.

Video: Procedure to Evaluate the Efficiency of Flocculants for the Removal of Dispersed Particles from Plant Extracts

Choice and No-Choice Assays for Testing the Resistance of A. thaliana to Chewing Insects

Larvae of the small white cabbage butterfly are a pest in agricultural settings. This caterpillar species feeds from plants in the cabbage family, which include many crops such as cabbage, broccoli, Brussel sprouts etc. Rearing of the insects takes place on cabbage plants in the greenhouse. At least two cages are needed for the rearing of Pieris rapae. One for the larvae and the other to contain the adults, the butterflies. In order to investigate the role of plant hormones and toxic plant chemicals in resistance to this insect pest, we demonstrate two experiments. First, determination of the role of jasmonic acid (JA - a plant hormone often indicated in resistance to insects) in resistance to the chewing insect Pieris rapae. Caterpillar growth can be compared on wild-type and mutant plants impaired in production of JA. This experiment is considered "No Choice", because larvae are forced to subsist on a single plant which synthesizes or is deficient in JA. Second, we demonstrate an experiment that investigates the role of glucosinolates, which are used as oviposition (egg-laying) signals. Here, we use WT and mutant Arabidopsis impaired in glucosinolate production in a "Choice" experiment in which female butterflies are allowed to choose to lay their eggs on plants of either genotype. This video demonstrates the experimental setup for both assays as well as representative results.

Plant resistance to chewing insect herbivores can be tested in several ways. Here, we demonstrate how to set-up a choice and a no-choice experiment with the model plant Arabidopsis thaliana to identify resistance against the pest species Pieris rapae.

Larvae of the small white cabbage butterfly are a pest in agricultural settings. This caterpillar species feeds from plants in the cabbage family, which ...

Testing the Physiological Barriers to Viral Transmission in Aphids Using Microinjection

Potato loafroll virus (PLRV), from the family Luteoviridae infects solanaceous plants. It is transmitted by aphids, primarily, the green peach aphid. When an uninfected aphid feeds on an infected plant it contracts the virus through the plant phloem. Once ingested, the virus must pass from the insect gut to the hemolymph (the insect  blood ) and then must pass through the salivary gland, in order to be transmitted back to a new plant. An aphid may take up different viruses when munching on a plant, however only a small fraction will pass through the gut and salivary gland, the two main barriers for transmission to infect more plants. In the lab, we use physalis plants to study PLRV transmission. In this host, symptoms are characterized by stunting and interveinal chlorosis (yellowing of the leaves between the veins with the veins remaining green). The video that we present demonstrates a method for performing aphid microinjection on insects that do not vector PLVR viruses and tests whether the gut is preventing viral transmission.
The video that we present demonstrates a method for performing Aphid microinjection on insects that do not vector PLVR viruses and tests whether the gut or salivary gland is preventing viral transmission.

Aphids are effective transmitters of plant viruses. Aphid microinjection of virus, the procedure we will show you today, is a technique allowing researchers to inject virus directly into the hemocoel of the aphid, bypassing the gut, one of the 2 major barriers for virus transmission in a circulative manner. The same technique is also used to inject dsRNA for RNAi.

Potato loafroll virus (PLRV), from the family Luteoviridae infects solanaceous plants. It is transmitted by aphids, primarily, the green peach aphid. When ...

Murine Renal Transplantation Procedure

Renal orthotopic transplantation in mice is a technically challenging procedure. Although the first kidney transplants in mice were performed by Russell et al over 30 years ago (1) and refined by Zhang et al years later (2), few people in the world have mastered this procedure. In our laboratory we have successfully performed 1200 orthotopic kidney transplantations with &gt; 90% survival rate. The key points for success include stringent control of reperfusion injury, bleeding and thrombosis, both during the procedure and post-transplantation, and use of 10-0 instead of 11-0 suture for anastomoses.
Post-operative care and treatment of the recipient is extremely important to transplant success and evaluation. All renal graft recipients receive antibiotics in the form of an injection of penicillin immediately post-transplant and sulfatrim in the drinking water continually. Overall animal health is evaluated daily and whole blood creatinine analyses are performed routinely with a portable I-STAT machine to assess graft function.

Renal transplantation in mice is a technically challenging procedure that requires careful post-operative care and treatment for success.

Renal orthotopic transplantation in mice is a technically challenging procedure. Although the first kidney transplants in mice were performed by Russell ...

A PCR-based Genotyping Method to Distinguish Between Wild-type and Ornamental Varieties of Imperata cylindrica

Wild-type I. cylindrica (cogongrass) is one of the top ten worst invasive plants in the world, negatively impacting agricultural and natural resources in 73 different countries throughout Africa, Asia, Europe, New Zealand, Oceania and the Americas1-2. Cogongrass forms rapidly-spreading, monodominant stands that displace a large variety of native plant species and in turn threaten the native animals that depend on the displaced native plant species for forage and shelter. To add to the problem, an ornamental variety [I. cylindrica var. koenigii (Retzius)] is widely marketed under the names of Imperata cylindrica 'Rubra', Red Baron, and Japanese blood grass (JBG). This variety is putatively sterile and noninvasive and is considered a desirable ornamental for its red-colored leaves. However, under the correct conditions, JBG can produce viable seed (Carol Holko, 2009 personal communication) and can revert to a green invasive form that is often indistinguishable from cogongrass as it takes on the distinguishing characteristics of the wild-type invasive variety4 (Figure 1). This makes identification using morphology a difficult task even for well-trained plant taxonomists. Reversion of JBG to an aggressive green phenotype is also not a rare occurrence. Using sequence comparisons of coding and variable regions in both nuclear and chloroplast DNA, we have confirmed that JBG has reverted to the green invasive within the states of Maryland, South Carolina, and Missouri. JBG has been sold and planted in just about every state in the continental U.S. where there is not an active cogongrass infestation. The extent of the revert problem in not well understood because reverted plants are undocumented and often destroyed.
Application of this molecular protocol provides a method to identify JBG reverts and can help keep these varieties from co-occurring and possibly hybridizing. Cogongrass is an obligate outcrosser and, when crossed with a different genotype, can produce viable wind-dispersed seeds that spread cogongrass over wide distances5-7. JBG has a slightly different genotype than cogongrass and may be able to form viable hybrids with cogongrass. To add to the problem, JBG is more cold and shade tolerant than cogongrass8-10, and gene flow between these two varieties is likely to generate hybrids that are more aggressive, shade tolerant, and cold hardy than wild-type cogongrass. While wild-type cogongrass currently infests over 490 million hectares worldwide, in the Southeast U.S. it infests over 500,000 hectares and is capable of occupying most of the U.S. as it rapidly spreads northward due to its broad niche and geographic potential3,7,11. The potential of a genetic crossing is a serious concern for the USDA-APHIS Federal Noxious Week Program. Currently, the USDA-APHIS prohibits JBG in states where there are major cogongrass infestations (e.g., Florida, Alabama, Mississippi). However, preventing the two varieties from combining can prove more difficult as cogongrass and JBG expand their distributions. Furthermore, the distribution of the JBG revert is currently unknown and without the ability to identify these varieties through morphology, some cogongrass infestations may be the result of JBG reverts. Unfortunately, current molecular methods of identification typically rely on AFLP (Amplified Fragment Length Polymorphisms) and DNA sequencing, both of which are time consuming and costly. Here, we present the first cost-effective and reliable PCR-based molecular genotyping method to accurately distinguish between cogongrass and JBG revert.

A PCR-based Genotyping Method to Distinguish Between Wild-type and Ornamental Varieties of Imperata cylindrica

We provide a cost-effective and rapid molecular genotyping protocol that employs variety-specific PCR primers that target DNA sequence differences within the chloroplast trnL-F spacer region to differentiate between varieties of Imperata cylindrica (cogongrass) that cannot be distinguished by morphology alone. These varieties include the federally listed noxious weed, cogongrass and closely-related, wide-spread ornamental variety, I. cylindrica var. koenigii (Japanese blood grass).

Wild-type I. cylindrica (cogongrass) is one of the top ten worst invasive plants in the world, negatively impacting agricultural and natural resources in ...

Isolation of Viable Multicellular Glands from Tissue of the Carnivorous Plant, Nepenthes

Many plants possess specialized structures that are involved in the production and secretion of specific low molecular weight compounds and proteins. These structures are almost always localized on plant surfaces. Among them are nectaries or glandular trichomes. The secreted compounds are often employed in interactions with the biotic environment, for example as attractants for pollinators or deterrents against herbivores.
Glands that are unique in several aspects can be found in carnivorous plants. In so-called pitcher plants of the genus Nepenthes, bifunctional glands inside the pitfall-trap on the one hand secrete the digestive fluid, including all enzymes necessary for prey digestion, and on the other hand take-up the released nutrients. Thus, these glands represent an ideal, specialized tissue predestinated to study the underlying molecular, biochemical, and physiological mechanisms of protein secretion and nutrient uptake in plants. Moreover, generally the biosynthesis of secondary compounds produced by many plants equipped with glandular structures could be investigated directly in glands.
In order to work on such specialized structures, they need to be isolated efficiently, fast, metabolically active, and without contamination with other tissues. Therefore, a mechanical micropreparation technique was developed and applied for studies on Nepenthes digestion fluid. Here, a protocol is presented that was used to successfully prepare single bifunctional glands from Nepenthes traps, based on a mechanized microsampling platform. The glands could be isolated and directly used further for gene expression analysis by PCR techniques after preparation of RNA.

Isolation of Viable Multicellular Glands from Tissue of the Carnivorous Plant, Nepenthes

Plants glands are specialized structures responsible for the biosynthesis and secretion of many compounds involved in interactions with the biotic environment. To enable studies on their molecular and biochemical features, a mechanical micropreparation technique was established in order to isolate single metabolically active glands, here from the carnivorous plant Nepenthes.

Many plants possess specialized structures that are involved in the production and secretion of specific low molecular weight compounds and proteins. ...

Identification of Post-translational Modifications of Plant Protein Complexes

Plants adapt quickly to changing environments due to elaborate perception and signaling systems. During pathogen attack, plants rapidly respond to infection via the recruitment and activation of immune complexes. Activation of immune complexes is associated with post-translational modifications (PTMs) of proteins, such as phosphorylation, glycosylation, or ubiquitination. Understanding how these PTMs are choreographed will lead to a better understanding of how resistance is achieved.
Here we describe a protein purification method for nucleotide-binding leucine-rich repeat (NB-LRR)-interacting proteins and the subsequent identification of their post-translational modifications (PTMs). With small modifications, the protocol can be applied for the purification of other plant protein complexes. The method is based on the expression of an epitope-tagged version of the protein of interest, which is subsequently partially purified by immunoprecipitation and subjected to mass spectrometry for identification of interacting proteins and PTMs.
This protocol demonstrates that: i). Dynamic changes in PTMs such as phosphorylation can be detected by mass spectrometry; ii). It is important to have sufficient quantities of the protein of interest, and this can compensate for the lack of purity of the immunoprecipitate; iii). In order to detect PTMs of a protein of interest, this protein has to be immunoprecipitated to get a sufficient quantity of protein.

We describe here a protocol for the purification and characterization of plant protein complexes. We demonstrate that by immunoprecipitating a single protein within a complex, so we can identify its post-translational modifications and its interacting partners.

Plants adapt quickly to changing environments due to elaborate perception and signaling systems. During pathogen attack, plants rapidly respond to ...

In Vitro Pancreas Organogenesis from Dispersed Mouse Embryonic Progenitors

The pancreas is an essential organ that regulates glucose homeostasis and secretes digestive enzymes. Research on pancreas embryogenesis has led to the development of protocols to produce pancreatic cells from stem cells 1. The whole embryonic organ can be cultured at multiple stages of development 2-4. These culture methods have been useful to test drugs and to image developmental processes. However the expansion of the organ is very limited and morphogenesis is not faithfully recapitulated since the organ flattens. 
We propose three-dimensional (3D) culture conditions that enable the efficient expansion of dissociated mouse embryonic pancreatic progenitors. By manipulating the composition of the culture medium it is possible to generate either hollow spheres, mainly composed of pancreatic progenitors expanding in their initial state, or, complex organoids which progress to more mature expanding progenitors and differentiate into endocrine, acinar and ductal cells and which spontaneously self-organize to resemble the embryonic pancreas. 
We show here that the in vitro process recapitulates many aspects of natural pancreas development. This culture system is suitable to investigate how cells cooperate to form an organ by reducing its initial complexity to few progenitors. It is a model that reproduces the 3D architecture of the pancreas and that is therefore useful to study morphogenesis, including polarization of epithelial structures and branching. It is also appropriate to assess the response to mechanical cues of the niche such as stiffness and the effects on cell&#180;s tensegrity.

In Vitro Pancreas Organogenesis from Dispersed Mouse Embryonic Progenitors

The three-dimensional culture method described in this protocol recapitulates pancreas development from dispersed embryonic mouse pancreas progenitors, including their substantial expansion, differentiation and morphogenesis into a branched organ. This method is amenable to imaging, functional interference and manipulation of the niche.

The pancreas is an essential organ that regulates glucose homeostasis and secretes digestive enzymes. Research on pancreas embryogenesis has led to the ...

Imaging Spatial Reorganization of a MAPK Signaling Pathway Using the Tobacco Transient Expression System

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular fluorescent complementation (BiFC) assay in tobacco epidermal cells, from testing protein-protein interaction to monitoring spatial distribution of signal transduction in plant cells. In this protocol, we used the BiFC assay to show that the interaction and the signaling between the Arabidopsis MAPKKK YODA and MAPK6 occur at the plasma membrane. When the scaffold protein BASL was co-expressed, the YODA-MAPK interaction redistributed and spatially co-polarized with CFP-BASL. This modified tobacco expression system allows for quick examination of signaling localization and dynamic changes (less than 4 days) and can accommodate multiple of fluorescent protein colors (at least three). We also presented detailed methods to quantify protein distribution (asymmetric spatial localization, or &#34;polarization&#34;) in tobacco cells. This advanced tobacco expression system has a potential to be used widely for quick testing of dynamic signaling events in live plant cells.

At the subcellular level, signaling events are dynamically modulated by developmental and environmental cues. Here we describe a protocol that employs the tobacco transient expression system to monitor dynamic protein-protein interaction and to disclose spatial organization of signal transduction in plant cells.

Visualization of dynamic signaling events in live cells has been a challenge. We expanded an established transient expression system, the biomolecular ...

Removal of Exogenous Materials from the Outer Portion of Frozen Cores to Investigate the Ancient Biological Communities Harbored Inside

The cryosphere offers access to preserved organisms that persisted under past environmental conditions. In fact, these frozen materials could reflect conditions over vast time periods and investigation of biological materials harbored inside could provide insight of ancient environments. To appropriately analyze these ecosystems and extract meaningful biological information from frozen soils and ice, proper collection and processing of the frozen samples is necessary. This is especially critical for microbial and DNA analyses since the communities present may be so uniquely different from modern ones. Here, a protocol is presented to successfully collect and decontaminate frozen cores. Both the absence of the colonies used to dope the outer surface and exogenous DNA suggest that we successfully decontaminated the frozen cores and that the microorganisms detected were from the material, rather than contamination from drilling or processing the cores.

The cryosphere offers access to preserved organisms that persisted under past environmental conditions. A protocol is presented to collect and decontaminate permafrost cores of soils and ice. The absence of exogenous colonies and DNA suggest that microorganisms detected represent the material, rather than contamination from drilling or processing.

The cryosphere offers access to preserved organisms that persisted under past environmental conditions. In fact, these frozen materials could reflect ...

Comparison of Tobacco Host Cell Protein Removal Methods by Blanching Intact Plants or by Heat Treatment of Extracts

Plants not only provide food, feed and raw materials for humans, but have also been developed as an economical production system for biopharmaceutical proteins, such as antibodies, vaccine candidates and enzymes. These must be purified from the plant biomass but chromatography steps are hindered by the high concentrations of host cell proteins (HCPs) in plant extracts. However, most HCPs irreversibly aggregate at temperatures above 60 &#176;C facilitating subsequent purification of the target protein. Here, three methods are presented to achieve the heat precipitation of tobacco HCPs in either intact leaves or extracts. The blanching of intact leaves can easily be incorporated into existing processes but may have a negative impact on subsequent filtration steps. The opposite is true for heat precipitation of leaf extracts in a stirred vessel, which can improve the performance of downstream operations albeit with major changes in process equipment design, such as homogenizer geometry. Finally, a heat exchanger setup is well characterized in terms of heat transfer conditions and easy to scale, but cleaning can be difficult and there may be a negative impact on filter capacity. The design-of-experiments approach can be used to identify the most relevant process parameters affecting HCP removal and product recovery. This facilitates the application of each method in other expression platforms and the identification of the most suitable method for a given purification strategy.

Three heat precipitation methods are presented that effectively remove more than 90% of host cell proteins (HCPs) from tobacco extracts prior to any other purification step. The plant HCPs irreversibly aggregate at temperatures above 60 &#176;C.

Plants not only provide food, feed and raw materials for humans, but have also been developed as an economical production system for biopharmaceutical ...