This work is partly supported by the Cooperative Agriculture Research Center, and Integrated Food Security Research Center of the College of Agriculture and Human Sciences, Prairie View A&#38;M University. We thank Hua Tian for his technical support.

1. Preparation of starch samples
<ol>
	<li>Prepare two (or three) gram-scale replicate starch samples from starch-accumulating tissues of various plant species following the established procedures (e.g., potatoes15, sweetpotatoes28, wheat grains13,29, and maize kernels30, etc.).</li>
	<li>Thoroughly wash starch samples with acetone or toluene 3-4x to minimize granule aggregates and dry them completely. 
	NOTE: Use extraction procedures that yield more than 1 g of starch per preparation. One or two 0.5-g aliquots from each of the three or two replicate extracts, respectively, are sampled for granule sizing analysis of one starch extract.</li>
</ol>
2. Electrolyte preparation
<ol>
	<li>Prepare 500 mL of 50 g/L lithium chloride in methanol for four sizing runs for replication starch samples (100 mL per run plus an extra 100 mL). Preferably, make the electrolyte in large-volume batches, e.g., 4 to 8 L at a time, to minimize the concentration variation.</li>
	<li>Cool the container on ice or in a 4 &#176;C cabinet to speed up dissolution of the lithium chloride.</li>
</ol>
3. Setting up the analyzer
<ol>
	<li>Choose an aperture tube with a particle diameter range covering the known (in the literature or through trial runs) granule size range of starch samples to be analyzed, e.g., a 100 &#956;m aperture for sweetpotato starches. For starch samples of unknown granule size range, select an appropriate aperture through trial runs using several aperture tubes having overlapping particle diameter ranges. 
	NOTE: The particle diameter range of an aperture tube is its accurate sizing range between 2 to 60% of, and with an extended sizing range to 80% of its orifice diameter. Table 1 lists properties of three most useful aperture tubes for sizing granules of major crop starches. If the granule size range of a starch sample is wider than the sizing range of a single aperture tube, perform a multi-tube overlap analysis combining up to five particle size distributions measured with apertures of different sizes. Each aperture is identifiable by its diameter and part number labeled on the tube. Its diameter and serial number contained in a barcode on the tube can be scanned into the analyzer software using the Bar Code Reader on the Control Panel of the analyzer.</li>
	<li>Chose a 100 or 200 mL analytical beaker (over cuvettes) for the determination of starch granule sizes, and set up automatic stirring (below) to maintain a good granule suspension during measurement.</li>
	<li>Create a Standard Operating Method (SOM) to specify run settings, and a Preferences file for analyzing, viewing, and printing the results. Combine SOM and Preferences file into a Standard Operating Procedure (SOP) as needed. 
	NOTE: For non-standardizable analyses, use SOM to run the analyses, and adjust the SOM settings between runs through the Edit the SOM window (see below) as needed. After run completion, analyze, view, and print the run results by changing the Preferences as desired. For standardizable granule sizing analyses, use an SOP to run the analyses.
	<ol>
		<li>Start the analyzer software. On the Main Manu, click SOP | Create SOM Wizard or Edit the SOM, or on the Status Panel, click Edit SOM. Use the wizard or the Edit the SOM window to select settings for an SOM. Settings typically used for sizing granules of sweetpotato starch samples are summarized in Table 2.</li>
		<li>Save the created SOM to a File in the SOM Wizard-Summary of Settings window, or in the Edit the SOM window.</li>
		<li>On the Main Manu, Click SOP | Create Preferences Wizard or Edit Preferences. Use the wizard or tabs in the Preferences edit window to select preference settings as those in Table 3 or others as desired.</li>
		<li>Save the selected Preferences to a file in the Create Preferences Wizard-Summary of Settings window or in the Edit Preferences window.</li>
		<li>On the Main Menu, click SOP | Create SOP Wizard. Following the step-by-step guide of the wizard, enter a description, select the SOM and Preferences file to create and save an SOP.</li>
	</ol>
	</li>
</ol>
4. Granule sizing analyses of the starch samples
<ol>
	<li>Prepare the Analyzer
	<ol>
		<li>Turn on the analyzer, open the software in the computer and verify the Ready status at the top of the Status Panel after its automatic connection to the analyzer.</li>
		<li>Fill the electrolyte jar with electrolyte, empty the waste jar if necessary.</li>
		<li>Properly install and secure the chosen aperture tube following the guide in the user&#8217;s manual. For an uncalibrated new aperture tube, calibrate it following the step-by-step guide under Calibration | Calibrate Aperture on the Main Menu. For a calibrated aperture tube, verify the calibration following the step-by-step guide of the Change Aperture Tube Wizard under the Run or Calibration | Verify Aperture Calibration on the Main Menu.</li>
		<li>Unlock the assay platform by pushing the lock-release clip (on the middle front of the left sample compartment wall) and manually lower the platform to the bottom. Place an analytical beaker containing 100 mL of electrolyte on the platform, move the stirrer to the stirring position, and manually raise the platform to the self-locking upper position to immerse the aperture tube and stirrer in the electrolyte.</li>
		<li>Click Fill on the bottom instrument Toolbar to have the analyzer automatically fill the system with the electrolyte and click Flush to have the analyzer automatically flush the system.</li>
		<li>Load the SOM by clicking SOP | Load an SOM on the Main Menu, and use the SOM to run an analysis without a Preferences file. Alternatively, load an SOP by clicking SOP | Load an SOP on the Main Menu or Load SOP on the Status Panel, and use the SOP to run an analysis.</li>
		<li>If using an SOP, click SOP | SOM Info or Preference Info on the Main Menu to verify the SOM and Preference settings. Click Sample | Enter Sample Info on the Main Menu or Edit Info on the Status Panel to enter the sample information for the run.</li>
	</ol>
	</li>
	<li>Prepare starch-methanol sample and sizing suspensions
	<ol>
		<li>Weigh two or one 0.5 g sample from each of the two or three replicate starch extracts, respectively.</li>
		<li>Add each of the 0.5 g starch aliquots to 5 mL methanol in a 50 mL conical centrifuge tube, and fully disperse starch granules using several pulses of low intensity ultrasound (12&#8211;24 W/cm2) from an ultrasonic processor.</li>
		<li>Using a disposable transfer pipette, apply one small drop of the starch-methanol suspension (~0.2 mL) to the 100 mL of 50 g/L LiCl methanol electrolyte under constant stirring in the beaker. Close the sample compartment door.</li>
	</ol>
	</li>
	<li>Perform a sizing run
	<ol>
		<li>Click Preview in the bottom Instrument Toolbar to start a preview run. On the Status Panel, verify that the dynamically displayed concentration bar is in green, and shows a 5 to 8% nominal concentration range for the suspension.</li>
		<li>Click Stop on the bottom Toolbar to stop the Preview run. If necessary, dilute the starch-electrolyte suspension by replacing an aliquot of the suspension with the electrolyte, and then repeat a Preview run. 
		NOTE: The 5% to 8% nominal concentration range of the suspension is critical for completion of a run without stoppage due to aperture blockage by aggregated granules. If needed, adjust the drop-sample size, and/or the concentration of the starch-methanol suspension to make a new starch-electrolyte suspension having the nominal concentration in the optimal range.</li>
		<li>After the verification, click Start on the bottom Toolbar to start the run. The analyzer automatically completes the run once the total count of sized granules, which is displayed along with the run time on the Status Panel in a run, reaches the set Total Count (125,000 or 250,000) by the Control Mode of the SOM. Depending on the suspension concentration (within 5-8% range or lower), a single run takes 2 to 5 min or more. 
		NOTE: When the analyzer automatically detects an aperture blockage per blockage detection settings of the SOM, it will abort the run, flush to unblock the aperture and start a new run. This blockage action is set to maximally repeat for four times before the analyzer cancels the run operation. This run-aborting blockage problem may be overcome by using two technical methods as noted in Table 2 and detailed in the discussion.</li>
		<li>If needed, perform a technical repeat run (see Table 2 and detailed in Discussion) using the same starch-electrolyte suspension by simply clicking Start or Repeat on the bottom Toolbar.</li>
		<li>After completion of a run or repeat runs, empty the beaker, rinse it with methanol, and refill it with 100 mL fresh electrolyte solution for the next run.</li>
		<li>During a run, if an Extended Size Range notification dialog appears when the count of granules larger than 60 &#181;m exceeds 0.1% of the total count (per the SOM setting), click Run 60% to 80% for running an extended dynamic sizing range to 80% of the aperture diameter. 
		NOTE: The Extended Size Range setting controls actions for granules larger than 60% of the aperture diameter (100 &#181;m, in this case). The setting in the SOM specifies inclusion of starch granules larger than 60 &#181;m when their counts reach over 0.1% of the total count. The completion of the run is still controlled by the total count, and may take slightly less time than otherwise without inclusion of the larger granules totaling less than 0.1% (presumed statically insignificant amount) of the total count.</li>
	</ol>
	</li>
	<li>Analyze the run results
	<ol>
		<li>If an SOM was used to control the runs, select Preferences settings as desired for viewing, printing, and statistical analyses of the results using the Create Preferences Wizard or the Edit Preferences under the SOP on the Main Menu.</li>
		<li>Overlay results from multiple runs on a single graph for comparison.
		<ol>
			<li>Click Overlay on the Main Toolbar or File | Overlay on the Main Menu to access the Overlay window. Navigate to and select multiple desired result files in the Files box, click Add to move them to the Selected Files box, and click OK to overlay the selected results on a single graph.</li>
			<li>To add a file to an open overlay, click RunFile | Open for Overlay on the Run Menu to access the Overlay window, navigate to the desired file, and click to add.</li>
		</ol>
		</li>
		<li>Average results from replicate analyses (2 extracts x 2 starch-sampling or 3 extracts x 1 starch-sampling), and view or print the average granule size distribution and statistics in a list or graph.
		<ol>
			<li>On the Main Menu, click File | FileTool | Average to open the Average window. Navigate to and select multiple desired result files in the Files box, click Add to move them to the Selected Files box, and click OK to average the selected results and display the average on a single graph.</li>
			<li>To include an additional result file in an average distribution, on the Run Menu, click RunFile | Open and Add to Average to open the Add to Average window, navigate to and add the file. The new average appears on the graph in the Run (result) window or listing.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>
5. Specifying the average distribution
<ol>
	<li>In the Run-Menu window displaying the average distribution, click Calculate | Averaged Statistics on the Run Menu to open the statistics summary window, which displays the average statistics in rows, and the graph statistics for the average distribution in the columns.</li>
	<li>Use the graphic geometric mean (<img alt="Equation 1" src="/files/ftp_upload/61586/61586eq1.jpg" />) and S.D. (s*) in the graph statistics column to specify the average distribution in the <img alt="Equation 1" src="/files/ftp_upload/61586/61586eq1.jpg" /> x/ s* form. Calculate the CV measuring variations among the averaged replicate distributions by dividing the mean (&#181;, the same as the <img alt="Equation 1" src="/files/ftp_upload/61586/61586eq1.jpg" /> of the average distribution) of the geometric means of the averaged distributions with the average S.D. (&#963;) listed in the average statistics row. 
	NOTE: The average S.D. (for &#181;) assessing variations among the means of the replicate distributions is different from the graphic geometric S.D. (for <img alt="Equation 1" src="/files/ftp_upload/61586/61586eq1.jpg" />) measuring the spread of the average distribution.</li>
</ol>

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The authors have nothing to disclose

The outlined procedure has resolved some critical issues in several existing methods for starch granule size analyses, including inappropriate 1D or 2D sizing of 3D granules, distortion of sizing measurements due to none-uniform granule shapes, poor reproducibility and dubious statistical validity due to limited granule-sample sizes, inaccurate or improper specification (especially the use of the average size) of granule sizes in the presence of both granule shape and none-normal size distributions. It uses the ESZ techn...

Starch granules are the physical structure in which two main reserve homoglucan polymers in plant photosynthesis and storage tissues, the linear or sparsely branched amylose and the highly branched amylopectin, are orderly packed along with some minor components, including lipids and proteins. Starch granules from various plant species exhibit many three-dimensional (3D) shapes (reviewed in ref.1,2), including spheres, ellipsoids, polyhedrons, platelets, cubes, cuboids, and irregular tubules. Even those from the same tissue or different tissues of the same plant species could have a set of shapes with varying occurrence frequencies. In other words, starch granules from a plant species may have a characteristic statistical shape distribution, rather than a specific shape. The non-uniform and non-spherical granule shapes make it difficult to properly measure and define starch granule sizes. Additionally, starch granules from the same tissues of a plant species are of a range of sizes with different proportions, i.e., exhibiting a characteristic size distribution. This size distribution further complicates the analysis and description of starch granule sizes.
Starch granule sizes have been analyzed using several categories of particle sizing techniques (reviewed in ref.3), including microscopy, sedimentation/steric field-flow fractionation (Sd/StFFF), laser diffraction and electrical sensing zone (ESZ). However, these techniques are not equally suited for the determination of starch granule sizes in the presence of a granule shape and a size distribution. Microscopy, including light, confocal and scanning electron microscopy, is excellent for the studies of morphology4,5,6,7, structure8,9 and development10,11 of starch granules, but hardly suited for defining their size distributions due to some inherent shortcomings. Direct measurements of microscopic granule images or software-assisted image analysis of optical microscopy data (IAOM), which have been used for the determination of granule sizes of starches from several species, including maize12, wheat13,14, potato15 and barley16, can measure only 1D (usually maximal length) or 2D (surface area) sizes of very limited numbers (tens to a few thousands) of starch granule images. The small granule sampling sizes that are inherently constrained by the techniques could rarely be statistically representative, considering the enormous granule numbers per unit weight of starch (~120 x 106 per gram, assuming all 10 &#181;m spheres at 1.5 g/cm&#179; density), and, therefore, could lead to the poor reproducibility of the results. The Sd/StFFF technique may have high speed and resolution, and narrow size fractions of starch granules17, but has been rarely used probably because its accuracy could be severely affected by damages, different shapes, and density of starch granules. The laser diffraction technique is the most widely used, and has been applied for starch granule size analyses for all major crop species3,14,16. Although the technique has many advantages, it is actually not suited for determinations of starch granule sizes in the presence of a granule shape distribution. Most of the concurrent laser diffraction instruments rely on the Mie light-scattering theory18 for uniform spherical particles and the modified Mie theory18 for some other shapes of uniformity. The technique is, therefore, inherently very sensitive to particle shapes, and not entirely suited even for certain shapes of uniformity19, let alone for starch granules having a set of shapes of varying proportions. The ESZ technique measures the electric field disturbance proportional to the volume of the particle passing through an aperture. It provides granule volume sizes, as well as the number and volume distribution information, etc., at high resolutions. Since the ESZ technique is independent of any optical properties of particles including color, shape, composition or refractive index, and results are very reproducible, it is particularly suited for determining size distributions of starch granules having a set of shapes.
Starch granule sizes have also been defined by using many parameters. They were often simplistically described by average diameters, which in some cases were the arithmetic means of the microscopically measured maximal lengths of 2D images12,20, or averages of equivalent sphere diameters3. In other cases, the granule size distributions were specified by using size ranges21,22, the distribution mean volume or mean diameter (sphere equivalent, weighted by number, volume, or surface area) assuming a normal distribution14,23,24,25,26. These descriptors of starch granule sizes from various analyses are of a vastly different nature, and not strictly comparable. It could be very misleading if these &#8220;sizes&#8221; of starch granules from different species or even the same tissues of the same species were directly compared. Furthermore, the spread (or shape) parameter of the assumed normal distributions, i.e., the standard deviation &#963; (or graphic standard deviation &#963;g) measuring the width of the distribution (i.e., the spread of the sizes), has been ignored in most studies.
To resolve the aforementioned critical issues facing starch granule sizing analyses, we outlined a procedure for reproducible and statistically valid determinations of granule size distributions of starch samples using the ESZ technique, and for properly specifying the determined granule lognormal size distributions using an adopted two-parameter multiplicative form27 with improved accuracy and comparability. For validation and demonstration, we performed replicate granule sizing analyses of sweetpotato starch samples using the procedure, and specified the lognormal differential volume-percentage volume-equivalent-sphere diameter distributions using their graphic geometric means <img alt="Equation 1" src="/files/ftp_upload/61586/61586eq1.jpg" /> and multiplicative standard deviations s* in a <img alt="Equation 1" src="/files/ftp_upload/61586/61586eq1.jpg" /> x/ (multiply and divide) s* form.

<table border="0" cellpadding="0" cellspacing="0" style="width:1001px;" width="1001">
	<colgroup>
		<col />
		<col />
		<col />
		<col />
	</colgroup>
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:261px;">Analytical beaker</td>
			<td style="width:211px;">Beckman Coulter Life Sciences</td>
			<td style="width:171px;">A35595</td>
			<td style="width:359px;">Smart-Technology (ST) beaker</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Aperture tube, 100 &#181;m</td>
			<td>Beckman Coulter Life Sciences</td>
			<td>A36394</td>
			<td>For the MS4E, , 1000 &#181;m</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Disposable transfer pipettor,</td>
			<td>Fisher Scientific (Fishersci.com)</td>
			<td style="width:171px;">13-711-9AM</td>
			<td style="width:359px;">Other disposable transfer pipettors with similar orifice can also be used.</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;width:261px;">Fisherbrand Conical Polypropylene Centrifuge Tubes, 50 ml</td>
			<td>Fisher Scientific (Fishersci.com)</td>
			<td>05-539-13</td>
			<td>Any other similar types of tubes can be used.</td>
		</tr>
		<tr height="60">
			<td height="60" style="height:60px;width:261px;">Glass beakers, 150 to 250 ml</td>
			<td>Fisher Scientific (Fishersci.com)</td>
			<td>02-540K</td>
			<td style="width:359px;">These beakers are used to contain methanol for washing the aperture tube and stirer between runs.</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:261px;">LiCl</td>
			<td style="width:211px;">Fisher Chemical</td>
			<td>L121-100</td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:261px;">Methanol</td>
			<td>Fisher Chemical</td>
			<td>A412-500</td>
			<td>Buy in bulk as the analysis uses a large quantity of methanol.</td>
		</tr>
		<tr height="40">
			<td height="40" style="height:40px;">Mettler Toledo ML-T Precision Balances</td>
			<td>Mettler Toledo</td>
			<td style="width:171px;">30243412</td>
			<td style="width:359px;">Any other precision balance with a readablity 0.01 g to 1 mg will work.</td>
		</tr>
		<tr height="100">
			<td height="100" style="height:100px;">Multisizer 4e Coulter Counter</td>
			<td>Beckman Coulter Life Sciences</td>
			<td>B23005</td>
			<td style="width:359px;">The old model, Multisizer 3 can also be used with slight adjustment of parameters. The 4e model comes with a 100 &#956;m aperture tube. Other aperture tubes of different diameter can be purchased separately from the company.</td>
		</tr>
		<tr height="140">
			<td height="140" style="height:140px;">Ultrasonic processor UP50H</td>
			<td>Hielscher Ultrasound Technology</td>
			<td>UP50H</td>
			<td style="width:359px;">Other laborator sonicator having a low-power (&#60;50 Watt) output can be also used. Both MS1 and MS2 sonotrodes for the particular sonicator can be used to disperse starch granules in 5 ml methanol. Always use the lowest setting first, 20% amplitude and 0.1 or 0.2 cycle, and raise the setting if aggregates persist in suspension.</td>
		</tr>
	</tbody>
</table>

analysis and specification of starch granule size distributions

Starch from all plant sources are made up of granules in a range of sizes and shapes having different occurrence frequencies, i.e., exhibiting a size and a shape distribution. Starch granule size data determined using several types of particle sizing techniques are often problematic due to poor reproducibility or lack of statistical significance resulting from some insurmountable systematic errors, including sensitivity to granule shapes and limits of granule-sample sizes. We outlined a procedure for reproducible and statistically valid determinations of starch granule size distributions using the electrical sensing zone technique, and for specifying the determined granule lognormal size distributions using an adopted two-parameter multiplicative form with improved accuracy and comparability. It is applicable to all granule sizing analyses of gram-scale starch samples, and, therefore, could facilitate studies on how starch granule sizes are molded by the starch biosynthesis apparatus and mechanisms; and how they impact properties and functionality of starches for food and industrial uses. Representative results are presented from replicate analyses of granule size distributions of sweetpotato starch samples using the outlined procedure. We further discussed several key technical aspects of the procedure, especially, the multiplicative specification of granule lognormal size distributions and some technical means for overcoming frequent aperture blockage by granule aggregates.

To validate the procedure, and demonstrate reproducibility of the determined granule size distribution, we performed replicate sizing analyses of sweetpotato starch samples. We prepared replicate (S1 and S2) starch samples from field-grown sweetpotatoes of a breeding line SC1149-19 at a similar developmental age using a previously described procedure28. From each starch extract, two 0.5 g aliquots (a and b) were sampled, suspended in 5 mL of methanol and sonicated with several pulses of low-energy...

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Analysis and Specification of Starch Granule Size Distributions

Presented here is a procedure for reproducible and statistically valid determinations of starch granule size distributions, and for specifying the determined granule lognormal size distributions using a two-parameter multiplicative form. It is applicable to all granule sizing analyses of gram-scale starch samples for plant and food science research. &#160;

Starch from all plant sources are made up of granules in a range of sizes and shapes having different occurrence frequencies, i.e., exhibiting a size and ...

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4.9K Views.  Prairie View A&M University. Presented here is a procedure for reproducible and statistically valid determinations of starch granule size distributions, and for specifying the determined granule lognormal size distributions using a two-parameter multiplicative form. It is applicable to all granule sizing analyses of gram-scale starch samples for plant and food science research.  

Video: Analysis and Specification of Starch Granule Size Distributions

Method for Identifying Small Molecule Inhibitors of the Protein-protein Interaction Between HCN1 and TRIP8b

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are expressed ubiquitously throughout the brain, where they function to regulate the excitability of neurons. The subcellular distribution of these channels in pyramidal neurons of hippocampal area CA1 is regulated by tetratricopeptide repeat-containing Rab8b interacting protein (TRIP8b), an auxiliary subunit. Genetic knockout of HCN pore forming subunits or TRIP8b, both lead to an increase in antidepressant-like behavior, suggesting that limiting the function of HCN channels may be useful as a treatment for Major Depressive Disorder (MDD). Despite significant therapeutic interest, HCN channels are also expressed in the heart, where they regulate rhythmicity. To circumvent off-target issues associated with blocking cardiac HCN channels, our lab has recently proposed targeting the protein-protein interaction between HCN and TRIP8b in order to specifically disrupt HCN channel function in the brain. TRIP8b binds to HCN pore forming subunits at two distinct interaction sites, although here the focus is on the interaction between the tetratricopeptide repeat (TPR) domains of TRIP8b and the C terminal tail of HCN1. In this protocol, an expanded description of a method for purifying TRIP8b and executing a high throughput screen to identify small molecule inhibitors of the interaction between HCN and TRIP8b, is described. The method for high throughput screening utilizes a Fluorescence Polarization (FP) -based assay to monitor the binding of a large TRIP8b fragment to a fluorophore-tagged eleven amino acid peptide corresponding to the HCN1 C terminal tail. This method allows &#39;hit&#39; compounds to be identified based on the change in the polarization of emitted light. Validation assays are then performed to ensure that &#39;hit&#39; compounds are not artifactual.

The interaction between HCN channels and their auxiliary subunit has been identified as a therapeutic target in Major Depressive Disorder. Here, a fluorescence polarization-based method for identifying small molecule inhibitors of this protein-protein interaction, is presented.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are expressed ubiquitously throughout the brain, where they function to regulate the ...

Online Size-exclusion and Ion-exchange Chromatography on a SAXS Beamline

Biological small angle X-ray scattering (BioSAXS) is a powerful technique in molecular and structural biology used to determine solution structure, particle size and shape, and surface-to-volume ratio of macromolecules. The technique is applicable to a very wide variety of solution conditions spanning a broad range of concentrations, pH values, ionic strengths, temperatures, additives, etc., but the sample is required to be monodisperse. This caveat led to the implementation of liquid chromatography systems on SAXS beamlines. Here, we describe the upstream integration of size-exclusion (SEC) and ion-exchange chromatography (IEC) on a beamline, different methods for optimal background subtraction, and data reduction. As an example, we describe how we use SEC- and IEC-SAXS on a fragment of the essential vaccinia virus protein D5, consisting of a D5N helicase domain. We determine its overall shape and molecular weight, showing the hexameric structure of the protein.

The determination of the solution structure of a protein by small angle X-ray scattering (SAXS) requires monodisperse samples. Here, we present two possibilities to ensure minimal delays between sample preparation and data acquisition: online size-exclusion chromatography (SEC) and online ion-exchange chromatography (IEC).

Biological small angle X-ray scattering (BioSAXS) is a powerful technique in molecular and structural biology used to determine solution structure, ...

Protein Digestion, Ultrafiltration, and Size Exclusion Chromatography to Optimize the Isolation of Exosomes from Human Blood Plasma and Serum

Exosomes, a type of nanovesicle released from all cell types, can be isolated from any bodily fluid. The contents of exosomes, including proteins and RNAs, are unique to the cells from which they are derived and can be used as indicators of disease. Several common enrichment protocols, including ultracentrifugation, yield exosomes laden with soluble protein contaminants. Specifically, we have found that the most abundant proteins within blood often co-purify with exosomes and can confound downstream proteomic studies, thwarting the identification of low abundance biomarker candidates. Of additional concern is irreproducibility of exosome protein quantification due to inconsistent representation of non-exosomal protein levels. The protocol detailed here was developed to remove non-exosomal proteins that co-purify along with exosomes, adding rigor to the exosome purification process. Five methods were compared using paired blood plasma and serum from five donors. Analysis using nanoparticle tracking analysis and micro bicinchoninic acid protein assay revealed that a combined protocol utilizing ultrafiltration and size exclusion chromatography yielded the optimal vesicle enrichment and soluble protein removal. Western blotting was used to verify that the expected abundant blood proteins, including albumin and apolipoproteins, were depleted.

Here, we present a protocol to purify exosomes from both plasma and serum with reduced co-purification of non-exosomal blood proteins. The optimized protocol includes ultrafiltration, protease treatment, and size exclusion chromatography. Enhanced purification of exosomes benefits downstream analyses, including more accurate quantification of vesicles and proteomic characterization.

Exosomes, a type of nanovesicle released from all cell types, can be isolated from any bodily fluid. The contents of exosomes, including proteins and ...

Use of Two Dimensional Semi-denaturing Detergent Agarose Gel Electrophoresis to Confirm Size Heterogeneity of Amyloid or Amyloid-like Fibers

Amyloid or amyloid-like fibers have been associated with many human diseases, and are now being discovered to be important for many signaling pathways. The ability to readily detect the formation of these fibers under various experimental conditions is essential for understanding their potential function. Many methods have been used to detect the fibers, but not without some drawbacks. For example, electron microscopy (EM), or staining with Congo Red or Thioflavin T often requires purification of the fibers. On the other hand, semi-denaturing detergent agarose gel electrophoresis (SDD-AGE) allows detection of the SDS-resistant amyloid-like fibers in the cell extracts without purification. In addition, it allows the comparison of the size difference of the fibers. More importantly, it can be used to identify specific proteins within the fibers by Western blotting. It is less time consuming and more easily accessible to a wider number of labs. SDD-AGE results often show variable degree of heterogeneity. It raises the question whether part of the heterogeneity results from the dissociation of the protein complex during the electrophoresis in the presence of SDS. For this reason, we have employed a second dimension of SDD-AGE to determine if the size heterogeneity seen in SDD-AGE is truly a result of fiber heterogeneity in vivo and not a result of either degradation or dissociation of some of the proteins during electrophoresis. This method allows fast, qualitative confirmation that the amyloid or amyloid-like fibers are not partially dissociating during the SDD-AGE process.

Here we use two-dimensional semi-denaturing agarose gel electrophoresis to confirm the presence of amyloid-like fibers of heterogeneous size and exclude the possibility that the size heterogeneity is due to dissociation of the amyloid fibers during the gel running process.

Amyloid or amyloid-like fibers have been associated with many human diseases, and are now being discovered to be important for many signaling pathways. ...

Purification and Reconstitution of TRPV1 for Spectroscopic Analysis

Polymodal ion channels transduce multiple stimuli of different natures into allosteric changes; these dynamic conformations are challenging to determine and remain largely unknown. With recent advances in single-particle cryo-electron microscopy (cryo-EM) shedding light on the structural features of agonist binding sites and the activation mechanism of several ion channels, the stage is set for an in-depth dynamic analysis of their gating mechanisms using spectroscopic approaches. Spectroscopic techniques such as electron paramagnetic resonance (EPR) and double electron-electron resonance (DEER) have been mainly restricted to the study of prokaryotic ion channels that can be purified in large quantities. The requirement for large amounts of functional and stable membrane proteins has hampered the study of mammalian ion channels using these approaches. EPR and DEER offer many advantages, including determination of the structure and dynamic changes of mobile protein regions, albeit at low resolution, that might be difficult to obtain by X-ray crystallography or cryo-EM, and monitoring reversible gating transition (i.e., closed, open, sensitized, and desensitized). Here, we provide protocols for obtaining milligrams of functional detergent-solubilized transient receptor potential cation channel subfamily V member 1 (TRPV1) that can be labeled for EPR and DEER spectroscopy.

This article describes specific methods to obtain biochemical quantities of detergent-solubilized TRPV1 for spectroscopic analysis. The combined protocols provide biochemical and biophysical tools that can be adapted to facilitate structural and functional studies for mammalian ion channels in a membrane-controlled environment.

Polymodal ion channels transduce multiple stimuli of different natures into allosteric changes; these dynamic conformations are challenging to determine ...

Extraction and Analysis of Taiwanese Green Propolis

Taiwanese green propolis is rich in prenylated flavonoids and exhibits a broad range of biological activities, such as antioxidant, antibacterial, and anticancer ones. The bioactive compounds of Taiwanese green propolis are propolins, namely C, D, F, and G. The concentration of propolins in Taiwanese green propolis varies depending on the season and geographic location. Thus, it is critical to establish a standard and repeatable procedure for determining the quality of Taiwanese green propolis. Here, we present a protocol that uses ethanol-based extraction, high-performance liquid chromatography, and an antibacterial activity analysis to characterize Taiwanese green propolis quality. This method indicates that 95% and 99.5% ethanol extractions achieve the maximum dry matter yields from Taiwanese green propolis, thereby yielding the highest concentrations of propolins that have antibacterial properties. According to these findings, the present protocol is deemed reliable and repeatable for determining the quality of Taiwanese green propolis.

We present a protocol for using ethanol as a solvent to extract and characterize Taiwanese green propolis that exhibits antibacterial activity.

Taiwanese green propolis is rich in prenylated flavonoids and exhibits a broad range of biological activities, such as antioxidant, antibacterial, and ...

Study on the Metabolism of Six Systemic Insecticides in a Newly Established Cell Suspension Culture Derived from Tea (Camellia Sinensis L.) Leaves

A platform for studying insecticide metabolism using in vitro tissues of tea plant was developed. Leaves from sterile tea plantlets were induced to form loose callus on Murashige and Skoog (MS) basal media with the plant hormones 2,4-dichlorophenoxyacetic acid (2,4-D, 1.0 mg L-1) and kinetin (KT, 0.1 mg L-1). Callus formed after 3 or 4 rounds of subculturing, each lasting 28 days. Loose callus (about 3 g) was then inoculated into B5 liquid media containing the same plant hormones and was cultured in a shaking incubator (120 rpm) in the dark at 25 &#177; 1 &#176;C. After 3&#8722;4 subcultures, a cell suspension derived from tea leaf was established at a subculture ratio ranging between 1:1 and 1:2 (suspension mother liquid: fresh medium). Using this platform, six insecticides (5 &#181;g mL-1 each thiamethoxam, imidacloprid, acetamiprid, imidaclothiz, dimethoate, and omethoate) were added into the tea leaf-derived cell suspension culture. The metabolism of the insecticides was tracked using liquid chromatography and gas chromatography. To validate the usefulness of the tea cell suspension culture, the metabolites of thiamethoxan and dimethoate present in treated cell cultures and intact plants were compared using mass spectrometry. In treated tea cell cultures, seven metabolites of thiamethoxan and two metabolites of dimethoate were found, while in treated intact plants, only two metabolites of thiamethoxam and one of dimethoate were found. The use of a cell suspension simplified the metabolic analysis compared to the use of intact tea plants, especially for a difficult matrix such as tea.

Study on the Metabolism of Six Systemic Insecticides in a Newly Established Cell Suspension Culture Derived from Tea Camellia Sinensis L. Leaves

This work presents a protocol for establishing a cell suspension culture derived from tea (Camellia sinensis L.) leaves that can be used to study the metabolism of external compounds that can be taken up by the whole plant, such as insecticides.

A platform for studying insecticide metabolism using in vitro tissues of tea plant was developed. Leaves from sterile tea plantlets were induced to form ...

Characterization of Proteins by Size-Exclusion Chromatography Coupled to Multi-Angle Light Scattering (SEC-MALS)

Analytical size-exclusion chromatography (SEC), commonly used for the determination of the molecular weight of proteins and protein-protein complexes in solution, is a relative technique that relies on the elution volume of the analyte to estimate molecular weight. When the protein is not globular or undergoes non-ideal column interactions, the calibration curve based on protein standards is invalid, and the molecular weight determined from elution volume is incorrect. Multi-angle light scattering (MALS) is an absolute technique that determines the molecular weight of an analyte in solution from basic physical equations. The combination of SEC for separation with MALS for analysis constitutes a versatile, reliable means for characterizing solutions of one or more protein species including monomers, native oligomers or aggregates, and heterocomplexes. Since the measurement is performed at each elution volume, SEC-MALS can determine if an eluting peak is homogeneous or heterogeneous and distinguish between a fixed molecular weight distribution versus dynamic equilibrium. Analysis of modified proteins such as glycoproteins or lipoproteins, or conjugates such as detergent-solubilized membrane proteins, is also possible. Hence, SEC-MALS is a critical tool for the protein chemist who must confirm the biophysical properties and solution behavior of molecules produced for biological or biotechnological research. This protocol for SEC-MALS analyzes the molecular weight and size of pure protein monomers and aggregates. The data acquired serve as a foundation for further SEC-MALS analyses including those of complexes, glycoproteins and surfactant-bound membrane proteins.

Characterization of Proteins by Size-Exclusion Chromatography Coupled to Multi-Angle Light Scattering SEC-MALS

This protocol describes the combination of size exclusion chromatography with multi-angle light scattering (SEC-MALS) for absolute characterization of proteins and complexes in solution. SEC-MALS determines the molecular weight and size of pure proteins, native oligomers, heterocomplexes and modified proteins such as glycoproteins.

Analytical size-exclusion chromatography (SEC), commonly used for the determination of the molecular weight of proteins and protein-protein complexes in ...

Analysis of SEC-SAXS data via EFA deconvolution and Scatter

BioSAXS is a popular technique used in molecular and structural biology to determine the solution structure, particle size and shape, surface-to-volume ratio and conformational changes of macromolecules and macromolecular complexes. A high quality SAXS dataset for structural modeling must be from monodisperse, homogeneous samples and this is often only reached by a combination of inline chromatography and immediate SAXS measurement. Most commonly, size-exclusion chromatography is used to separate samples and exclude contaminants and aggregations from the particle of interest allowing SAXS measurements to be made from a well-resolved chromatographic peak of a single protein species. Still, in some cases, even inline purification is not a guarantee of monodisperse samples, either because multiple components are too close to each other in size or changes in shape induced through binding alter perceived elution time. In these cases, it may be possible to deconvolute the SAXS data of a mixture to obtain the idealized SAXS curves of individual components. Here, we show how this is achieved and the practical analysis of SEC-SAXS data is performed on ideal and difficult samples. Specifically, we show the SEC-SAXS analysis of the vaccinia E9 DNA polymerase exonuclease minus mutant.

SEC-BioSAXS measurements of biological macromolecules are a standard approach for determining solution structure of macromolecules and their complexes. Here, we analyze SEC-BioSAXS data from two types of commonly encountered SEC traces&#8212;chromatograms with fully resolved and partially resolved peaks. We demonstrate the analysis and deconvolution using scatter and BioXTAS RAW.

BioSAXS is a popular technique used in molecular and structural biology to determine the solution structure, particle size and shape, surface-to-volume ...

Isolation and Analysis of Plasma Lipoproteins by Ultracentrifugation

Analysis of plasma lipoproteins and apolipoproteins is an essential part for the diagnosis of dyslipidemia and studies of lipid metabolism and atherosclerosis. Although there are several methods for analyzing plasma lipoproteins, ultracentrifugation is still one of the most popular and reliable methods. Because of its intact separation procedure, the lipoprotein fractions isolated by this method can be used for analysis of lipoproteins, apolipoproteins, proteomes, and functional study of lipoproteins with cultured cells in vitro. Here, we provide a detailed protocol to isolate seven lipoprotein fractions including VLDL (d&#60;1.006 g/mL), IDL (d=1.02 g/mL), LDLs (d=1.04 and 1.06 g/mL), HDLs (d=1.08, 1.10, and 1.21 g/mL) from rabbit plasma using sequential floating ultracentrifugation. In addition, we introduce the readers how to analyze apolipoproteins such as apoA-I, apoB, and apoE by SDS-PAGE and Western blotting and show representative results of lipoprotein and apolipoprotein profiles using hyperlipidemic rabbit models. This method can become a standard protocol for both clinicians and basic scientists to analyze lipoprotein functions.

Several methods have been used for analyzing plasma lipoproteins; however, ultracentrifugation is still one of the most popular and reliable methods. Here, we describe a method regarding how to isolate lipoproteins from plasma using sequential density ultracentrifugation and how to analyze the apolipoproteins for both diagnostic and research purposes.