The authors would like to thank Keith Tarpley of the US EPA Office of Research and Development-Research Triangle Park (ORD-RTP) Graphic and Media team for development, taping, and editing of the instructional video. We would also like to thank Deborah Pritchett from ProteinSimple for helpful conversations regarding optimization of our data. JM Guynn was supported by the Oak Ridge Institute for Science and Education Research/Participation Program at the US Environmental Protection Agency.

NOTE: Ensure that all reagents and samples are prepared according to the manufacturer&#39;s protocol, outlined below. Please wear proper personal protection equipment during this procedure, which includes nitrile gloves, lab coat, closed-toed shoes, and safety goggles. A table of specific materials, reagents and equipment required is provided separately. Total protein concentration of samples should be determined beforehand using established methodologies that are compatible with the lysate buffer used, such as Bradford assay11.
1. Preparation of samples and reagents from the standard pack as supplied by the manufacturer
<ol>
	<li>To prepare the 400 mM working solution of dithiothreitol (DTT), add 40 &#181;L deionized water to the clear tube containing the supplied stock from the manufacturer. It is important to avoid introducing bubbles to the solution by mixing the solution with slow and gentle pipetting.</li>
	<li>Add 20 &#181;L 10X sample buffer and 20 &#181;L of the prepared 400 mM DTT solution to the pink tube containing fluorescent 5X master mix (see the Table of Materials). 
	NOTE: The Master Mix (MM) is sealed by the manufacturer with a foil cover and must be pierced by a pipette tip. Mix gently by slow pipetting to avoid splashing DTT in the pipette.</li>
	<li>Next, add 16 &#181;L deionized water, 2 &#181;L of supplied 10X sample buffer, and 2 &#181;L of the prepared 400 mM DTT solution to the white biotinylated ladder tube supplied by the manufacturer. Mix gently and transfer into a 0.6 mL tube for denaturing.</li>
	<li>Prepare 0.1x sample buffer by diluting the supplied 10X solution 1:100 with water. Prepare enough 0.1x sample buffer to dilute all samples.</li>
	<li>Calculate the amount of 0.1x sample buffer that is added to a sample, which will depend on the final desired concentration of the total protein. Mix 1 part 5x fluorescent MM with 4 parts diluted sample to achieve the desired final protein concentration.
	<ol>
		<li>Calculate volumes as follows: (i) Volume 5x fluorescent MM = (Desired final protein concentration)/5; (ii) Volume of protein stock = (Desired final protein concentration x Total volume needed)/ Protein stock concentration; (iii) Volume 0.1x sample buffer = Total volume - 5x&#160;MM volume - Protein stock volume.</li>
	</ol>
	</li>
</ol>
2. Denaturation of samples and ladder
<ol>
	<li>Place prepared samples and biotinylated ladder in a 95 &#176;C heat block for 5 min. Vortex tubes immediately after incubation, execute a spin for ~5 s in a tabletop centrifuge, and place on ice. 
	NOTE: Some proteins may require gentler denaturing conditions (e.g., 70 oC for 10 min) to prevent protein aggregation and improve migration in the capillary matrix. Consider this option if there is heavy smearing at the higher molecular weights (see video for example).</li>
</ol>
3. Preparation of antibodies
<ol>
	<li>As determined by optimization (see Representative Results and video), prepare the desired dilution(s) of primary antibody (e.g., 1:50, 1:100) in the provided Antibody Diluent 2. 
	NOTE: Antibodies are generally used at higher concentrations for capillary-based immunoassay than for traditional western blotting. The supplied secondary antibody is ready to use without dilution.</li>
</ol>
4. Preparation of Luminol-S and Peroxide
<ol>
	<li>Prepare a 1:1 mixture of luminol-S and peroxide.</li>
	<li>Vortex to mix and store on ice. 
	NOTE: It is important that this mixture is prepared fresh for each experimental assay. 250ul total mix is needed to run a full plate.</li>
</ol>
5. Preparation of the assay plate
<ol>
	<li>As shown in Figure 1, load the samples and reagents prepared above into the assay plate. See detailed instructions below for each row. To minimize evaporation from the wells, ensure that the plate lid is replaced between reagent additions.</li>
	<li>In row A, pipet 5 &#181;L of Biotinylated Ladder into well A1. For the remaining row, pipet prepared samples (5 &#181;L each) into wells A2-A25. 
	NOTE: It is imperative that the A1 well always contains ladder, as the first capillary in the cartridge is optimized for running this standard.</li>
	<li>In row B, pipet 10 &#181;L of Antibody Diluent 2 into each well (B1-B25).</li>
	<li>In row C, pipet 10 &#181;L of Antibody Diluent 2 into well C1. In the remaining row C wells, pipet 10 &#181;L of primary antibody (wells C2-C25).</li>
	<li>In row D, pipet 10 &#181;L of Streptavidin-HRP into well D1. In the remaining row D wells, pipet 10 &#181;L of secondary antibody (wells D2-D25).</li>
	<li>In row E, pipet 10 &#181;L of the freshly prepared luminol-peroxide mix into each well (E1-E25).</li>
	<li>Finally, add 500 &#181;L wash buffer per compartment to each of the top 3 rows of buffer wells. 
	NOTE: It is important to minimize bubble formation by pipetting gently and not expelling the final volume from the tip as bubbles may interfere with the capillary loading and run.</li>
	<li>Once all wells are loaded, centrifuge the plate at ~1000 x g for 5 min at room temperature to remove bubbles and ensure the liquid is in the bottom of the wells. Pop any visible bubbles with a small pipette tip or clean needle (e.g., 25 gauge sterile &#34;rep top&#34; needle).</li>
</ol>
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/55911/55911fig1.jpg" /> 
Figure 1. Pipetting template for assay plate. Color coding represents proper reagents and samples (up to 24 total) added to the assay plate. Add biotinylated ladder to well A1 (orange), prepared samples from wells A2 up to A25 (light blue), Antibody Diluent 2 to wells B1-B25 and C1 (light green), primary antibody to wells C2 up to C25 (blue), streptavidin-HRP to well D1 (dark pink), secondary antibody to wells D2 up to D25 (dark green), and luminol-peroxide mix to wells E1 up to E25 (purple). Wash buffer is added to the first three rows of the larger mid-plate wells (dark blue). <a href="//cloudfront-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55911/55911fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
6. Starting the capillary immunoassay instrument
<ol>
	<li>Ensure that the instrument and the accompanying computer are turned on. No warm up time is needed.</li>
	<li>Open the instrumentation software on the computer. First, select the &#34;Assay&#34; tab on the right of the window and &#34;New Assay&#34; under the &#34;File Menu&#34; on the left. Select the size, size range (e.g., 12-230 kDa), and cartridge type (e.g., 25 capillary) that was used for the particular assay. 
	NOTE: One may also input assay parameters, including protein concentration, antibody type, and dilution, if desired, but these are not required to start the assay.</li>
	<li>Open the door on the instrument by pushing the button on top of the orange panel.</li>
	<li>Carefully remove the capillary cartridge from its packaging. Without touching the glass capillaries themselves, place the cartridge into the cartridge holder. Verify cartridge seating by observing the interior light change from orange to blue.</li>
	<li>Hold the plate firmly on the bench and carefully peel off the evaporation seal from the lower portion of the plate. Pop any bubbles seen in these separation matrix wells with a small pipet tip or clean needle (e.g., 25 gauge sterile &#34;rep top&#34; needle).</li>
	<li>Place the assay plate on the plate holder, ensuring it is fully seated, and close the instrument door.</li>
	<li>Click the &#34;Start&#34; button in the software. 
	NOTE: If no Start button appears, the connection with the instrument has been lost. Choose Instrument from the top left menu, then Connect. A pop-up should appear with the instrument serial number; select this, then click Connect. The Start button should now appear.</li>
	<li>When the run is complete, discard the plate. Remove the cartridge and place in a sharps container for disposal, along with any needles that may have been used to pop bubbles. Leave the power on to avoid connection problems if the instrument is being used regularly (e.g., at least weekly).</li>
</ol>
7. Experiment analysis
<ol>
	<li>Before analysis, ensure the following quality checks are performed.
	<ol>
		<li>Verify fluorescent standards by selecting the &#34;Show Standards&#34; icon. Check that the standards are correctly identified in the &#34;Graph View&#34; tab. If they are incorrect, go to the &#34;Single View&#34; icon, right click on the correct peak, and select &#34;Force Standard&#34;, or right click on the incorrect peak and select &#34;Not a Standard&#34;. Perform this check for each new capillary.</li>
		<li>Verify biotinylated ladder by clicking on the &#34;Samples&#34; and &#34;Single View&#34; icons. Select the ladder in the experiment tab. If a peak is incorrectly identified, right click on it in &#34;Graph View&#34; and select &#34;Remove Peak&#34;. 
		NOTE: For example, the biotinylated ladder used for the 12 - 230 kDa kit should show 12, 40, 66, 116, 180, and 230 kDa&#160;sizing peaks. If this step is not performed, the sizing of the sample peaks will be incorrectly calculated, producing spurious results.</li>
		<li>View and analyze sample peaks. Derive data from the peaks table, including molecular weight, peak area, peak height, and signal to noise (S/N), as needed for experimental calculations.</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Bradley, H. L., Sabnis, H., Pritchett, D., Bunting, K. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Hematopoietic stem cell protocols. 1185, (2014).</li><li>Guo, L., Eldridge, S., Furniss, M., Mussio, J., Davis, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+Human+Induced+Pluripotent+Stem+Cell-Derived+Cardiomyocytes+(hiPSC-CMs)+to+Monitor+Compound+Effects+on+Cardiac+Myocyte+Signaling+Pathways.">Use of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes (hiPSC-CMs) to Monitor Compound Effects on Cardiac Myocyte Signaling Pathways.</a> Curr Protoc Chem Biol. 7 (3), 141-185 (2015).</li><li>Chen, J. Q., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Absolute+quantitation+of+endogenous+proteins+with+precision+and+accuracy+using+a+capillary+Western+system.">Absolute quantitation of endogenous proteins with precision and accuracy using a capillary Western system.</a> Anal Biochem. 442 (1), 97-103 (2013).</li><li>Chen, J. Q., Wakefield, L. M., Goldstein, D. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Capillary+nano-immunoassays:+advancing+quantitative+proteomics+analysis,+biomarker+assessment,+and+molecular+diagnostics.">Capillary nano-immunoassays: advancing quantitative proteomics analysis, biomarker assessment, and molecular diagnostics.</a> J Transl Med. 13, 182 (2015).</li><li>Liu, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Application+of+a+Novel+Nanovolume+Capillary+Electrophoresis-+Based+Protein+Analysis+System+in+Personalized+&amp;+Translational+Medicine+Research.">The Application of a Novel Nanovolume Capillary Electrophoresis- Based Protein Analysis System in Personalized &amp; Translational Medicine Research.</a> J Bioanal Biomed. S3 (004), (2013).</li><li>ProteinSimple Western. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Size Assay Development Guide, Revision 1. , (2014).</li><li>Eaton, S. L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+guide+to+modern+quantitative+fluorescent+western+blotting+with+troubleshooting+strategies.">A guide to modern quantitative fluorescent western blotting with troubleshooting strategies.</a> J Vis Exp. (93), (2014).</li><li>Eslami, A., Lujan, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Western++blotting:+sample+preparation+to+detection.">Western blotting: sample preparation to detection.</a> J Vis Exp. (44), (2010).</li><li>Silva, J. M., McMahon, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+fastest+Western+in+town:+a+contemporary+twist+on+the+classic+Western+blot+analysis.">The fastest Western in town: a contemporary twist on the classic Western blot analysis.</a> J Vis Exp. (84), e51149 (2014).</li><li>Thorn, C. F., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Doxorubicin+pathways:+pharmacodynamics+and+adverse+effects.">Doxorubicin pathways: pharmacodynamics and adverse effects.</a> Pharmacogenet Genomics. 21 (7), 440-446 (2011).</li><li>Ernst, O., Zor, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Linearization+of+the+bradford+protein+assay.">Linearization of the bradford protein assay.</a> J Vis Exp. (38), (2010).</li><li>Taira, N., Yoshida, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Post-translational+modifications+of+p53+tumor+suppressor:+determinants+of+its+functional+targets.">Post-translational modifications of p53 tumor suppressor: determinants of its functional targets.</a> Histol Histopathol. 27 (4), 437-443 (2012).</li><li>Thompson, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phosphorylation+of+p53+on+key+serines+is+dispensable+for+transcriptional+activation+and+apoptosis.">Phosphorylation of p53 on key serines is dispensable for transcriptional activation and apoptosis.</a> J Biol Chem. 279 (51), 53015-53022 (2004).</li><li>Currier, J. M., Cheng, W. Y., Menendez, D., Conolly, R., Chorley, B. N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Developing+a+Gene+Biomarker+at+the+Tipping+Point+of+Adaptive+and+Adverse+Responses+in+Human+Bronchial+Epithelial+Cells.">Developing a Gene Biomarker at the Tipping Point of Adaptive and Adverse Responses in Human Bronchial Epithelial Cells.</a> PLoS One. 11 (5), e0155875 (2016).</li><li>Moser, A. C., Hage, D. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Capillary+electrophoresis-based+immunoassays:+principles+and+quantitative+applications.">Capillary electrophoresis-based immunoassays: principles and quantitative applications.</a> Electrophoresis. 29 (16), 3279-3295 (2008).</li><li>Shintani, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Handbook of Capillary Electrophoresis Applications. , (1997).</li><li>. Wes reagents and consumables :: ProteinSimple Available from: <a target="_blank" href="https://www.proteinsimple.com/consumables_sw_wes.html">https://www.proteinsimple.com/consumables_sw_wes.html</a> (2017)</li></ol>

The authors declare that they have no competing financial interests. This manuscript has been reviewed by the National Health and Environmental Effects Research Laboratory and approved for publication. The content does not necessarily reflect the views of the US EPA nor does mention of trade names or commercial products constitute endorsement or recommendation for use.

For decades, there has been sustained interest in the development of capillary electrophoretic-based immunoassay methods because of low sample and reagent expenditure, decreased processing time when compared to traditional methods, and high compatibility to automate the procedure4,15. There are a number of different protocols for the separation of proteins that have utilized capillaries, including electrophoretic, electrokinetic, polymer sieving, and isoelectric methods, which isolate proteins by different properties (respectively, electrostatic charge, partition equilibrium, sieving properties of the separating matrix, and pH)16. Here, we describe an antibody-based (or immunoassay) capillary electrophoresis method, using a polymer sieving separation, that has been automated and commercially adopted3. Advantages of this system include ease of use and operation, standardized and commercially available reagents, and reliable, sensitive measurements that require less reagent and samples compared to traditional protein assays such as western blot, enzyme-linked immunoassay, and other formats3,4,5. It has been noted in previous assessments of this technology that the size range of protein that can be assessed has been limited by the available separation matrix4, however recent offerings have expanded the measurable range from 2 to 440 kDa17. In addition, some lysate buffers are known to be incompatible with the assay18, therefore selection of the experimental reagents used must be considered beforehand.
A major advantage of an automated procedure with commercially available components is consistency of results through standardized methods and reagents. This minimizes chances of assay failure by automating critical steps within the procedure. However, it is important to note that certain practices must be adhered to during the protocol to minimize issues with the capillary electrophoretic-based immunoassay. First, it is critical that the luminol-S/peroxide mixture is prepared fresh and immediately before plate loading. Consistent timing will result in consistent luminescence after the oxidizing agent is added, which will result in consistent measurements for a particular antibody assay after assay. Furthermore, it is important that non-expired reagents are used, which primarily affects the potency of the oxidizing agent. Additionally, it is important that the loading order of samples, antibodies, and other reagents be strictly followed (see Figure 1). Any reagent pipetted out of place will result in assay failure and a wasted run.
Besides these critical steps, primary issues experienced with the technique can generally be overcome through optimization. Indeed, these conditions are specific to each model system/antibody combination and therefore should be determined empirically for each new assay. In this article, we focus on three common optimization procedures: exposure time, lysate titration, and primary antibody dilution. The ability to generate measurable results depends on analysis of an exposure time when the luminol substrate is not being rapidly depleted, as substrate depletion results in loss of signal. Lysate titration determines the linear dynamic range of each assay, which can differ with different model systems, as well as different antibodies, even for the same protein target. Antibody dilutions chosen at or near saturating concentrations ensure changes in signal will not be affected by a shortage of free antibody, but only by differing amount of available protein target epitope. Other considerations during the optimization process may include antibody incubation time and stacking/sample loading time. In most cases the default settings for the instrument offer the best balance of resolution and sensitivity. However, in some cases, poor resolution or sensitivity can be improved by adjusting these parameters.
Capillary electrophoretic-based immunoassay methods provide fast, efficient, and reproducible protein measurements. While these methods have primarily been utilized in research and development settings, the consistency of these technologies has potential utility in regulatory and clinical applications. For example, the identification of susceptible subpopulations to environmental toxicants or patients with progression of disease can be based on protein biomarkers measured in accessible matrices, such as blood, urine, and saliva. As reagent and operation costs drop and the number of samples and targets that can be simultaneously assessed increases, we will likely see capillary electrophoretic-based immunoassay methods used for these types of applications.

Capillary electrophoretic immunoassays measure protein expression in cell lysates using size or charge separation systems and provide several advantages over the traditional immunoassays. For example, when compared to western blot, the automated capillary-based procedure eliminates the need for gels, transfer devices, and manual washes. In addition, the absolute amount of protein required is approximately 10 times less, making capillary-based systems ideal for use with rare cell types or limited sample1,2. Results are obtained in as little as 3 h using automated systems and have previously been demonstrated to be more quantitative and reproducible than conventional western blot procedures3,4,5. The process for size-based assays consists of loading samples containing sodium dodecyl sulfate (SDS), dithiothreitol (DTT), and fluorescently labeled molecular weight markers into capillary columns containing stacking and separation matrices. Voltage applied to the capillaries separates the proteins in the samples according to size, and UV light immobilizes the separated proteins to the capillary wall. The capillary is then immuno-probed with target-specific primary antibody and horseradish peroxidase (HRP)-conjugated secondary antibody. Luminol and peroxide catalyze chemiluminescent light generation which is measured by a charge coupled device (CCD) camera and analyzed to quantitate protein.
Despite the relative ease and speed of an automated capillary-based electrophoretic immunoassay platform, optimization of assay conditions such as protein concentration, antibody dilution, and exposure time is important for obtaining accurate, reproducible results. In general, the following procedures should be performed to optimize an assay for these systems:
1) A screen should be performed to evaluate and choose antibodies for signal and specificity to the protein target. If available, purified protein or target epitope can be used to assess specificity; however, it is still important to assess potential non-specific signal in total protein sourced from the model system.
2) Next, the dynamic range of the assay needs to be determined. In an ideal situation, signal doubling (measured using peak area) is observed as sample concentration is doubled; however, in practice, a proportional change in signal to input in a predictable manner (e.g., linear fit) is sufficient for protein quantification. Additionally, this optimization will define protein concentration with high signal but still within the linear range for the experimental model.
3) Determine the optimal antibody concentration using the fixed protein concentration chosen in optimization step 2. As the antibody concentration increases, the signal increases until it plateaus at saturation. An antibody concentration near this saturation level is required for accurate measurement of protein concentration.
The process used to optimize protein concentrations, antibody dilutions, and exposure times for an automated capillary-based size assay6 is demonstrated using whole cell extracts isolated from BEAS-2B, an SV-40 transformed human bronchial epithelial cell line. Protein isolation from cell or tissue extracts can be performed using a number of published protocols7,8,9 and will not be covered here. Results of a trial experiment using the optimized conditions are also reported for total and phosphorylated (serine 15, serine 20) p53 in cultures exposed to doxorubicin (a common chemotherapeutic agent that induces cell apoptosis10) at 1.2, 1.8, and 2.4 &#181;g/mL media for 4 h prior to harvest. The p53 peak areas are normalized to &#593;-tubulin, which is used as a loading control.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Wes instrument</td>
			<td>ProteinSimple (Santa Clara, CA)</td>
			<td>004-600</td>
			<td></td>
		</tr>
		<tr>
			<td>P53 DO-1 primary antibody</td>
			<td>Santa Cruz Biotechnology, Inc.</td>
			<td>sc-126</td>
			<td></td>
		</tr>
		<tr>
			<td>phosphorylated p53 (ser 15) primary antibody</td>
			<td>Cell Signaling Technology</td>
			<td>9286</td>
			<td></td>
		</tr>
		<tr>
			<td>phosphorylated p53 (ser 20) primary antibody</td>
			<td>Cell Signaling Technology</td>
			<td>9287</td>
			<td></td>
		</tr>
		<tr>
			<td>alpha-tubulin primary antibody</td>
			<td>Cell Signaling Technology</td>
			<td>3873</td>
			<td>used as a loading control</td>
		</tr>
		<tr>
			<td>Compass Software</td>
			<td>ProteinSimple (Santa Clara, CA)</td>
			<td></td>
			<td>provided with the Wes</td>
		</tr>
		<tr>
			<td>12-230 kDa Master kit</td>
			<td>ProteinSimple (Santa Clara, CA)&#160;</td>
			<td>PS MK02 (since replaced by a new kit #)</td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td>www.proteinsimple.com/consumables_sw_wes.html</td>
			<td>INCLUDES PART NO: 
			Wash Buffer (60 mL) 042-202 
			10X Sample Buffer (440 &#956;L) 042-195 
			Pre-Filled Microplates (8) PS-PP01 
			Capillary Cartridges (8) PS-CC01 
			Antibody Diluent II (20 mL) 042-203 
			Luminol-S (1.5 mL) 042-233 
			Peroxide (1.5 mL) 042-234 
			Streptavidin-HRP (132 &#956;L) 042-414 
			Standard Pack (8): Biotinylated ladder, fluorescent 5X master mix, DTT, and empty 0.6 mL tube PS-ST01 
			Anti-Rabbit Secondary Antibody 042-206 
			or 
			Anti-Mouse Secondary Antibody 042-205</td>
			<td></td>
		</tr>
		<tr>
			<td>Name&#160;</td>
			<td>Company</td>
			<td>Catalog Number</td>
			<td>Comments</td>
		</tr>
		<tr>
			<td colspan="3">Cell culture, treatment, and harvest (using vendor recommended protocols; protocols not included in manuscript)</td>
			<td></td>
		</tr>
		<tr>
			<td>BEAS-2B cells</td>
			<td>American Type Culture Collection (ATCC, Manassas, VA)</td>
			<td>CRL-9609</td>
			<td></td>
		</tr>
		<tr>
			<td>keratinocyte growth medium, KGM Gold</td>
			<td>Lonza Ltd (Basel, Switzerland)</td>
			<td>192152</td>
			<td>for cell culture</td>
		</tr>
		<tr>
			<td>keratinocyte basal medium, KBM Gold</td>
			<td>Lonza Ltd (Basel, Switzerland)</td>
			<td>192151</td>
			<td>serum free medium for chemical dosing</td>
		</tr>
		<tr>
			<td>doxorubicin</td>
			<td>Sigma-Aldrich (St. Louis, MO)</td>
			<td>D1515</td>
			<td></td>
		</tr>
		<tr>
			<td>Coomassie Blue Bradford Assays</td>
			<td>ThermoFisher Scientific (Waltham, MA)</td>
			<td>23200</td>
			<td>for protein quantification</td>
		</tr>
		<tr>
			<td>Nuclear Extract kit</td>
			<td>Active Motif (Carlsbad, CA)</td>
			<td>D1515</td>
			<td>used to prepare whole cell lysates</td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td>INCLUDES:</td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td>Lysis Buffer AM1</td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td>1M dithiothreitol (DTT)</td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td>Protease Inhibitor Cocktail</td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td>10X PBS&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td></td>
			<td>Phosphatase Inhibitors</td>
			<td></td>
		</tr>
	</tbody>
</table>

procedure and key optimization strategies for an automated capillary electrophoretic-based immunoassay method

New technologies that utilize capillary-based immunoassays promise faster and more quantitative protein assessment compared to traditional immunoassays. However, similar to other antibody-based protein assays, optimization of capillary-based immunoassay parameters, such as protein concentration, antibody dilution, and exposure time is an important prerequisite to the generation of meaningful and reliable data. Measurements must fall within the linear range of the assay where changes in signal are directly proportional to changes in lysate concentration. The process of choosing appropriate lysate concentrations, antibody dilutions, and exposure times in the human bronchial epithelial cell line, BEAS-2B, is demonstrated here. Assay linearity is shown over a range of whole cell extract protein concentrations with p53 and &#945;-tubulin antibodies. An example of signal burnout is seen at the highest concentrations with long exposure times, and an &#945;-tubulin antibody dilution curve is shown demonstrating saturation. In addition, example experimental results are reported for doxorubicin-treated cells using optimized parameters.

Exposure time - Determining signal burnout
Signal burnout can occur when the luminol and peroxide substrate is depleted too quickly. This can be determined by examining the data at different chemiluminescence exposure times. In the analysis software, go to &#34;Edit -&#62; Analysis -&#62; Images&#34;. Exposures range from 5 to 480 s. The y-axis in an electropherogram reports signal/time, so the data from each exposure should have a similar signal/time coefficient. This coefficient decreases with sequentially longer exposures if luminol becomes depleted, as seen with the p53 DO-1 antibody (Figure 2). Because of substrate depletion, this assay can be considered measurable up to the 0.2 &#181;g/&#181;L concentration only at the 5 - 30 s exposures. Therefore, in this example, 15 s was determined to be the optimal data analysis exposure time for p53.
Lysate titration - Determining linear dynamic range
It is important that measurements be taken within the linear dynamic range of each assay, where changes in signal as measured by peak area are proportional to changes in the amount of protein in the sample. Using the optimal exposure time of 15 s chosen in the previous section, assay linearity is demonstrated for both p53 and &#593;-tubulin over greater than a 15-fold range of concentration (Figure 3). In our experience, a R2 value of &#62;0.9 of a linear regression fit is considered acceptable for a dilution range of purified protein of known quantity (if assay is an absolute quantitative measurement) or sample lysate of unknown target protein (if assay is a relative quantitative measurement).
Optimization of antibody dilution
Using antibodies at saturating concentrations helps ensure that any signal changes measured are due only to changes in protein amount. As a demonstration, two BEAS-2B cell line whole cell extracts (0.2 &#181;g/&#181;L total protein loaded into the assay) were probed with serially diluted &#593;-tubulin antibody concentrations ranging from 1:25 - 1:800 (Figure 4). Chemiluminescent signal (here, measured as peak area) was plotted against antibody dilution. Saturation was observed near the 1:50 dilution where the curve begins a noticeable plateau.
Experimental trial - Doxorubicin treatment in BEAS-2B cells
Using optimized assay conditions, BEAS-2B cell culture was treated with three different concentrations of doxorubicin (1.2, 1.8, and 2.4 &#181;g/mL) for 4 h (Figure 5, Table 1). Activation of p53 through post-translational modifications mediates several cellular responses, including cell cycle arrest, senescence, and apoptosis12. Specifically, the phosphorylation of serine 15 has been attributed to transcriptional activation of p53, resulting in apoptosis after doxorubicin treatment13. In this demonstration, &#593;-tubulin normalized peak areas are presented as fold of control. Interestingly, 3.5 to 4-fold increases in p53 phosphorylation at serine 15 and 2-fold increases in the level of p53 phosphorylated at serine 20 were observed after 4 h exposure to doxorubicin. These results indicate activation of p53; however, no dose-response is seen for the concentrations chosen (conversely, the lowest dose tested elicited the highest response). Total p53 did not demonstrate a clear treatment response in this model system. We have previously observed activation of p53 phosphorylation in the absence of increased levels of total p53 under similar conditions in zinc-treated BEAS-2B cells14.
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/55911/55911fig2v3.jpg" /> 
Figure 2. Exposure image comparison to detect signal burnout. Lane views show decreasing protein concentrations for BEAS-2B lysates probed with p53 DO-1 antibody at a 1:500 dilution. Chemiluminescence signal coefficients, reported as peak heights in the instrument software, are superimposed. Unlike the peak heights, the visual band intensities are automatically generated and adjusted by the instrument to aid viewing of the bands and are not comparable from one panel to another. Note the decrease in chemiluminescence signal as exposure time increases, with the signal beginning to disappear (split peak) at the two longest exposures, indicating substrate depletion. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55911/55911fig2v3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/55911/55911fig3v3.jpg" /> 
Figure 3. Lysate titration showing the lane views. Lysate titration showing the lane views (A) of BEAS-2B lysate when probed with 1:500 p53 DO-1 or 1:50 &#593;-tubulin. Unlike the peak area values, the visual band intensities are automatically generated and adjusted by the instrument to aid viewing of the bands and are not comparable from one panel to another.&#160;Linear regression analysis (B) confirms the assays are linear over the entire range tested, from 0.01 to 0.20 &#181;g/&#181;L and 0.025 to 0.40 &#181;g/&#181;L, with R2 values of 0.999 and 0.985, respectively. Total protein concentrations in the middle of the linear range were chosen to accommodate potential target protein variation in either direction (e.g., 0.2 &#181;g/&#181;L for &#945;-tubulin).&#160;<a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55911/55911fig3v3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/55911/55911fig4.jpg" /> 
Figure 4. &#945;-tubulin antibody dilution curves for two separate BEAS-2B protein lysates with and without baseline normalization. A definite departure from linearity is seen at the 1:50 (0.02) dilution, indicating saturation. 1:50 was therefore chosen as the optimal dilution for this antibody. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55911/55911fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/55911/55911fig5.jpg" /> 
Figure 5.Effect of 4 h doxorubicin (DXN) treatment on total and serine phosphorylated p53 protein expression of BEAS-2B cells. Peak areas are normalized to &#945;-tubulin and plotted as fold of control (CTL). <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55911/55911fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Table 1" src="/files/ftp_upload/55911/55911tbl1.jpg" /> 
Table 1. Effect of 4 h doxorubicin (DXN) treatment on total and serine phosphorylated p53 protein expression of BEAS-2B cells. <a href="https://cloudflare-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/55911/55911tbl1large.jpg" target="_blank">Please click here to view a larger version of this table.</a>

Watch this Scientific Journal Video about Procedure and Key Optimization Strategies for an Automated Capillary Electrophoretic-based Immunoassay Method at JoVE.com

Procedure and Key Optimization Strategies for an Automated Capillary Electrophoretic-based Immunoassay Method

A capillary-based immunoassay using a commercial platform to measure target proteins from total protein preparations is demonstrated. In addition, assay parameters of exposure time, protein concentration, and antibody dilution are optimized for a cell culture model system.

New technologies that utilize capillary-based immunoassays promise faster and more quantitative protein assessment compared to traditional immunoassays. ...

procedure-key-optimization-strategies-for-an-automated-capillary

Nanyang Technological University

Research

JoVE Journal

Biology

10.9K Views.  U.S. Environmental Protection Agency. A capillary-based immunoassay using a commercial platform to measure target proteins from total protein preparations is demonstrated. In addition, assay parameters of exposure time, protein concentration, and antibody dilution are optimized for a cell culture model system.

Video: Procedure and Key Optimization Strategies for an Automated Capillary Electrophoretic-based Immunoassay Method

Optimization of the Ugi Reaction Using Parallel Synthesis and Automated Liquid Handling

The optimization of a Ugi reaction involving the mixing of furfurylamine, benzaldehyde, boc-glycine and t-butylisocyanide is described. Triplicate runs of 48 parallel experiments are reported, varying concentration, solvent and the excess of some of the reagents. The isolation of the product was achieved by a simple filtration and wash procedure. The highest yield obtained was 66% from 0.4 M methanol with 1.2 eq. of imine. This is significantly above the 49% yield obtained from the initial reaction under equimolar concentration at 0.4 M in methanol. Methanol solutions with reagent concentrations of 0.4M or 0.2M gave superior yields while all solvent systems at 0.07M performed poorly. At 0.2M, methanol and ethanol/methanol (60/40) mixtures were statistically equally good while THF/methanol (60/40) was poor and acetonitrile/methanol (60/40) was intermediate. Good reproducibility of the precipitate yields was obtained in these replicate experiments, allowing for subtle interaction effects to be positively identified.

The Ugi reaction has proved to be a convenient way to quickly create diverse libraries of compounds. It involves the reaction of an amine, an aldehyde, a carboxylic acid and an isonitrile typically in methanol at room temperature. In this video, we utilize a 48-slot Mettler-Toledo MiniBlock equipped with filtration tubes and a Mettler-Toledo MiniMapper automated liquid handler was used to deliver the reagents and solvent. The parameters of interest were the concentration, the solvent composition and the excess of some of the reagents.

The optimization of a Ugi reaction involving the mixing of furfurylamine, benzaldehyde, boc-glycine and t-butylisocyanide is described.  Triplicate runs ...

Polymerase Chain Reaction: Basic Protocol Plus Troubleshooting and Optimization Strategies

In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of microbiology was transformed with the advent of Anton van Leeuwenhoek&#39;s microscope, which allowed scientists to visualize prokaryotes for the first time. The development of the polymerase chain reaction (PCR) is one of those innovations that changed the course of molecular science with its impact spanning countless subdisciplines in biology. The theoretical process was outlined by Keppe and coworkers in 1971; however, it was another 14 years until the complete PCR procedure was described and experimentally applied by Kary Mullis while at Cetus Corporation in 1985. Automation and refinement of this technique progressed with the introduction of a thermal stable DNA polymerase from the bacterium Thermus aquaticus, consequently the name Taq DNA polymerase.
PCR is a powerful amplification technique that can generate an ample supply of a specific segment of DNA (i.e., an amplicon) from only a small amount of starting material (i.e., DNA template or target sequence). While straightforward and generally trouble-free, there are pitfalls that complicate the reaction producing spurious results. When PCR fails it can lead to many non-specific DNA products of varying sizes that appear as a ladder or smear of bands on agarose gels. Sometimes no products form at all. Another potential problem occurs when mutations are unintentionally introduced in the amplicons, resulting in a heterogeneous population of PCR products. PCR failures can become frustrating unless patience and careful troubleshooting are employed to sort out and solve the problem(s). This protocol outlines the basic principles of PCR, provides a methodology that will result in amplification of most target sequences, and presents strategies for optimizing a reaction. By following this PCR guide, students should be able to: 
 
&#9679; Set up reactions and thermal cycling conditions for a conventional PCR experiment 
&#9679; Understand the function of various reaction components and their overall effect on a PCR experiment 
&#9679; Design and optimize a PCR experiment for any DNA template 
&#9679; Troubleshoot failed PCR experiments

PCR has emerged as a common technique in many molecular biology laboratories. Provided here is a quick guide to several conventional PCR protocols. Because each reaction is a unique experiment, optimal conditions required to generate a product vary. Understanding the variables in a reaction will greatly enhance troubleshooting efficiency, thereby increasing the chance to obtain the desired result.

In the biological sciences there have been technological advances that catapult the discipline into golden ages of discovery. For example, the field of ...

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm

Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals across the landscape is of primary importance in watershed management. Traditional economics methods of finding the lowest-cost solution in the watershed context (e.g.,5,12,20) assume that off-site impacts can be accurately described as a proportion of on-site pollution generated. Such approaches are unlikely to be representative of the actual pollution process in a watershed, where the impacts of polluting sources are often determined by complex biophysical processes. The use of modern physically-based, spatially distributed hydrologic simulation models allows for a greater degree of realism in terms of process representation but requires a development of a simulation-optimization framework where the model becomes an integral part of optimization.
Evolutionary algorithms appear to be a particularly useful optimization tool, able to deal with the combinatorial nature of a watershed simulation-optimization problem and allowing the use of the full water quality model. Evolutionary algorithms treat a particular spatial allocation of conservation practices in a watershed as a candidate solution and utilize sets (populations) of candidate solutions iteratively applying stochastic operators of selection, recombination, and mutation to find improvements with respect to the optimization objectives. The optimization objectives in this case are to minimize nonpoint-source pollution in the watershed, simultaneously minimizing the cost of conservation practices. A recent and expanding set of research is attempting to use similar methods and integrates water quality models with broadly defined evolutionary optimization methods3,4,9,10,13-15,17-19,22,23,25. In this application, we demonstrate a program which follows Rabotyagov et al.'s approach and integrates a modern and commonly used SWAT water quality model7 with a multiobjective evolutionary algorithm SPEA226, and user-specified set of conservation practices and their costs to search for the complete tradeoff frontiers between costs of conservation practices and user-specified water quality objectives. The frontiers quantify the tradeoffs faced by the watershed managers by presenting the full range of costs associated with various water quality improvement goals. The program allows for a selection of watershed configurations achieving specified water quality improvement goals and a production of maps of optimized placement of conservation practices.

This work demonstrates an integration of a water quality model with an optimization component utilizing evolutionary algorithms to solve for optimal (lowest-cost) placement of agricultural conservation practices for a specified set of water quality improvement objectives. The solutions are generated using a multi-objective approach, allowing for explicit quantification of tradeoffs.

Finding the cost-efficient (i.e., lowest-cost) ways of targeting conservation practice investments for the achievement of specific water quality goals ...

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review1 and recent examples2-4). Leaves are the primary photosynthetic organ, and their size and shape vary developmentally and environmentally within a plant. For these reasons studies on leaf morphology require measurement of multiple parameters from numerous leaves, which is best done by semi-automated phenomics tools5,6. Canopy shade is an important environmental cue that affects plant architecture and life history; the suite of responses is collectively called the shade avoidance syndrome (SAS)7. Among SAS responses, shade induced leaf petiole elongation and changes in blade area are particularly useful as indices8. To date, leaf shape programs (e.g. SHAPE9, LAMINA10, LeafAnalyzer11, LEAFPROCESSOR12) can measure leaf outlines and categorize leaf shapes, but can not output petiole length. Lack of large-scale measurement systems of leaf petioles has inhibited phenomics approaches to SAS research. In this paper, we describe a newly developed ImageJ plugin, called LeafJ, which can rapidly measure petiole length and leaf blade parameters of the model plant Arabidopsis thaliana. For the occasional leaf that required manual correction of the petiole/leaf blade boundary we used a touch-screen tablet. Further, leaf cell shape and leaf cell numbers are important determinants of leaf size13. Separate from LeafJ we also present a protocol for using a touch-screen tablet for measuring cell shape, area, and size. Our leaf trait measurement system is not limited to shade-avoidance research and will accelerate leaf phenotyping of many mutants and screening plants by leaf phenotyping.

Demonstration of key methods for high throughput leaf measurements. These methods can be used to accelerate leaf phenotyping when studying many plant mutants or otherwise screening plants by leaf phenotype.

High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review1 and recent examples2-4). Leaves are the ...

A Sensitive and Specific Quantitation Method for Determination of Serum Cardiac Myosin Binding Protein-C by Electrochemiluminescence Immunoassay

Biomarkers are becoming increasingly more important in clinical decision-making, as well as basic science. Diagnosing myocardial infarction (MI) is largely driven by detecting cardiac-specific proteins in patients' serum or plasma as an indicator of myocardial injury. Having recently shown that cardiac myosin binding protein-C (cMyBP-C) is detectable in the serum after MI, we have proposed it as a potential biomarker for MI. Biomarkers are typically detected by traditional sandwich enzyme-linked immunosorbent assays. However, this technique requires a large sample volume, has a small dynamic range, and can measure only one protein at a time.	
Here we show a multiplex immunoassay in which three cardiac proteins can be measured simultaneously with high sensitivity. Measuring cMyBP-C in uniplex or together with creatine kinase MB and cardiac troponin I showed comparable sensitivity. This technique uses the Meso Scale Discovery (MSD) method of multiplexing in a 96-well plate combined with electrochemiluminescence for detection. While only small sample volumes are required, high sensitivity and a large dynamic range are achieved. Using this technique, we measured cMyBP-C, creatine kinase MB, and cardiac troponin I levels in serum samples from 16 subjects with MI and compared the results with 16 control subjects. We were able to detect all three markers in these samples and found all three biomarkers to be increased after MI. This technique is, therefore, suitable for the sensitive detection of cardiac biomarkers in serum samples.

Measuring biomarkers in complex biological samples is increasingly guiding clinical decision-making. We describe a highly sensitive method to simultaneously measure cardiac myosin binding protein-C, creatine kinase MB, and cardiac troponin I in serum samples from subjects with myocardial infarction and healthy control subjects.

Biomarkers are becoming increasingly more  important in clinical decision-making, as well as basic science. Diagnosing  myocardial infarction (MI) is ...

An Innovative Method for Exosome Quantification and Size Measurement

Although the biological importance of exosomes has recently gained an increasing amount of scientific and clinical attention, much is still unknown about their complex pathways, their bioavailability and their diverse functions in health and disease. Current work focuses on the presence and the behavior of exosomes (in vitro as well as in vivo) in the context of different human disorders, especially in the fields of oncology, gynecology and cardiology.
Unfortunately, neither a consensus regarding a gold standard for exosome isolation exists, nor is there an agreement on such a method for their quantitative analysis. As there are many methods for the purification of exosomes and also many possibilities for their quantitative and qualitative analysis, it is difficult to determine a combination of methods for the ideal approach. 
Here, we demonstrate nanoparticle tracking analysis (NTA), a semi-automated method for the characterization of exosomes after isolation from human plasma by ultracentrifugation. The presented results show that this approach for isolation, as well as the determination of the average number and size of exosomes, delivers reproducible and valid data, as confirmed by other methods, such as scanning electron microscopy (SEM).

A method for isolation of exosomes from whole blood and further analysis by nanoparticle tracking using a semi-automatic instrument is presented in this article. The presented technology provides an extremely sensitive method for visualizing and analyzing particles in liquid suspension.

Although the biological importance of exosomes has recently gained an increasing amount of scientific and clinical attention, much is still unknown about ...

Cryo-Electron Microscopic Grid Preparation for Time-Resolved Studies using a Novel Robotic System, Spotiton

The capture of short-lived molecular states triggered by the early encounter of two or more interacting particles continues to be an experimental challenge of great interest to the field of cryo-electron microscopy (cryo-EM). A few methodological strategies have been developed that support these &#34;time-resolved&#34; studies, one of which, Spotiton-a novel robotic system-combines the dispensing of picoliter-sized sample droplets with precise temporal and spatial control. The time-resolved Spotiton workflow offers a uniquely efficient approach to interrogate early structural rearrangements from minimal sample volume. Fired from independently controlled piezoelectric dispensers, two samples land and rapidly mix on a nanowire EM grid as it plunges toward the cryogen. Potentially hundreds of grids can be prepared in rapid succession from only a few microliters of a sample. Here, a detailed step-by-step protocol of the operation of the Spotiton system is presented with a focus on troubleshooting specific problems that arise during grid preparation.

The protocol presented here describes the use of Spotiton, a novel robotic system, to deliver two samples of interest onto a self-wicking, nanowire grid that mix for a minimum of 90 ms prior to vitrification in liquid cryogen.

The capture of short-lived molecular states triggered by the early encounter of two or more interacting particles continues to be an experimental ...

Strategies for Optimization of Cryogenic Electron Tomography Data Acquisition

Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current state-of-the-art cryoET combined with subtomogram averaging analysis enables the high-resolution structural determination of macromolecular complexes that are present in multiple copies within tomographic reconstructions. Tomographic experiments usually require a vast amount of tilt series to be acquired by means of high-end transmission electron microscopes with important operational running-costs. Although the throughput and reliability of automated data acquisition routines have constantly improved over the recent years, the process of selecting regions of interest at which a tilt series will be acquired cannot be easily automated and it still relies on the user's manual input. Therefore, the set-up of a large-scale data collection session is a time-consuming procedure that can considerably reduce the remaining microscope time available for tilt series acquisition. Here, the protocol describes the recently developed implementations based on the SerialEM package and the PyEM software that significantly improve the time-efficiency of grid screening and large-scale tilt series data collection. The presented protocol illustrates how to use SerialEM scripting functionalities to fully automate grid mapping, grid square mapping, and tilt series acquisition. Furthermore, the protocol describes how to use PyEM to select additional acquisition targets in off-line mode after automated data collection is initiated. To illustrate this protocol, its application in the context of high-end data collection of Sars-Cov-2 tilt series is described. The presented pipeline is particularly suited to maximizing the time-efficiency of tomography experiments that require a careful selection of acquisition targets and at the same time a large amount of tilt series to be collected.

The increasing demand for large-scale data collection in cryogenic electron tomography requires high-throughput image acquisition routines. Described here is a protocol that implements the recent developments of advanced acquisition strategies aimed at maximizing the time-efficiency and throughput of tomographic data collection.

Cryogenic electron tomography (cryoET) is a powerful method to study the 3D structure of biological samples in a close-to-native state. Current ...

Real-Time Detection of Reactive Oxygen Species Production in Immune Response in Rice with a Chemiluminescence Assay

Reactive oxygen species (ROS) play vital roles in a variety of biological processes, including the sensing of abiotic and biotic stresses. Upon pathogen infection or challenge with pathogen-associated chemicals (pathogen-associated molecular patterns [PAMPs]), an array of immune responses, including a ROS burst, are quickly induced in plants, which is called PAMP-triggered immunity (PTI). A ROS burst is a hallmark PTI response, which is catalyzed by a group of plasma membrane-localized NADPH oxidases-the RBOH family proteins. The vast majority of ROS comprise hydrogen peroxide (H2O2), which can be easily and steadily detected by a luminol-based chemiluminescence method. Chemiluminescence is a photon-producing reaction in which luminol, or its derivative (such as L-012), undergoes a redox reaction with ROS under the action of a catalyst. This paper describes an optimized L-012-based chemiluminescence method to detect apoplast ROS production in real-time upon PAMP elicitation in rice tissues. The method is easy, steady, standardized, and highly reproducible under firmly controlled conditions.

Here, we describe a method for the real-time detection of apoplastic reactive oxygen species (ROS) production in rice tissues in pathogen-associated molecular pattern-triggered immune response. This method is simple, standardized, and generates highly reproducible results under controlled conditions.

Reactive oxygen species (ROS) play vital roles in a variety of biological processes, including the sensing of abiotic and biotic stresses. Upon pathogen ...

Collecting Hemolymph from Small Arthropods

A Precise and Quantifiable Method for Collecting Hemolymph from Small Arthropods

Arthropods are known to transmit a variety of viruses of medical and agricultural importance through their hemolymph, which is essential for virus transmission. Hemolymph collection is the basic technology for studying virus-vector interactions. Here, we describe a novel and simple method for the quantitative collection of hemolymph from small arthropods using Laodelphax striatellus (the small brown planthopper, SBPH) as a research model, as this arthropod is the main vector of rice stripe virus (RSV). In this protocol, the process begins by gently pinching off one leg of the frozen arthropod with fine-tipped tweezers and pressing the hemolymph out of the wound. Then, a simple micropipette consisting of a capillary and a pipette bulb is used to collect the transudative hemolymph from the wound according to the principle of capillary forces. Finally, the collected hemolymph can be dissolved into a specific buffer for further study. This new method for collecting hemolymph from small arthropods is a useful and efficient tool for further research on arboviruses and vector-virus interactions.

Author Spotlight: A Precise and Quantifiable Method for Collecting Hemolymph from Small Arthropods  

We describe a method to collect quantifiable hemolymph efficiently from small arthropods for subsequent analysis.