Name: standards for quantitative metalloproteomic analysis using size exclusion icp-ms
Uploaded: 2016-04-13T15:00:00
Duration: 9 min 51 s
Description: Watch this Scientific Journal Video about Standards for Quantitative Metalloproteomic Analysis Using Size Exclusion ICP-MS at JoVE.com

We would like to acknowledge support from Victorian Government&#39;s Operational Infrastructure Support Program, the Australian Research Council Linkage Projects Scheme (with Agilent Technologies), the Australian National Health and Medical Research Council, the Victorian brain bank, Cooperative Research Centre for Mental Health and the Neuroproteomics facility.

1. Preparation of Buffers and Samples
<ol>
	<li>Prepare 500 ml&#160;of buffer, 200 mM ammonium nitrate pH 7.6 - 7.8 (pH adjusted with ammonium hydroxide (NH4OH)) with cesium (Cs) and antinomy (Sb) added to a final concentration of 10 ppb. Use cesium and antinomy as internal standards to monitor for any drift in the response of ICP-MS. Filter buffer prior to use through a 0.22 &#956;m filter.</li>
	<li>Prepare sample depending on the type of sample: liquid, tissue or cell culture.
	<ol>
		<li>For samples that require homogenization (e.g., tissue or cells), ensure that they do not contain detergent. Use Tris buffers for sample preparation. Alternatively, use phosphate buffers but they can negatively affect the metalloproteome over time or with freeze thaw cycles12.</li>
		<li>Homogenize tissue or cell culture samples by manual dounce or sonication for 5 min&#160;using Tris buffered saline (50 mM Tris pH 8.0, 150 mM sodium chloride (NaCl) + ethylenediaminetetraacetic acid (EDTA) free protease inhibitors).</li>
		<li>Clarify homogenates by centrifugation at 16,000 x g for 5 min. Collect the resulting supernatant. Keep samples at 4 &#176;C. 
		Note: All samples must be centrifuged prior to loading into the high performance liquid chromatography (HPLC) vials to prevent particulates from blocking the size exclusion chromatography (SEC) column.</li>
	</ol>
	</li>
	<li>Normalize the total amount of protein loaded on the column across the samples. Determine protein concentrations at 280 nm using a micro volume UV spectrophotometer13. Load between 20 and 150 &#181;g protein. Use typical injection volumes ranging from 2 - 80 &#181;l&#160;depending on the sample concentration.
	<ol>
		<li>Clean the sample arm of the micro volume UV spectrophotometer with distilled water before sample loading. The sample arm is where the protein samples are loaded.</li>
		<li>Blank the instrument against 2 &#181;l&#160;of the sample buffer. Then, load 2 &#181;l&#160;of each sample onto the arm and measure the absorbance at 280 nm.</li>
		<li>Determine the concentrations. For crude protein samples, use an extinction coefficient of 1 Abs = 1 mg/ml. To determine the concentration of protein in the samples, use the Beer-Lambert Law, A = &#949; x l x c, where A is the absorbance, &#949; is the extinction coefficient, l is the path length in centimeters and c is the concentration.</li>
	</ol>
	</li>
</ol>
2. Bulk Analysis of Metalloprotein Standards Using Inductively Coupled Plasma - Mass Spectrometry
<ol>
	<li>Warm-up and tune the instrument using manufacturer&#39;s protocols.</li>
	<li>Once instrument is warmed up and tuned, perform bulk ICP-MS. 
	Note: Stock solutions of purified metalloproteins generally need to be diluted before measurement. The metal concentration of the standard can be estimated from the known protein:metal stochiometries and the estimated protein concentration. This information can be used to determine the dilution that will be appropriate to fall within the range of the standard curve generated.
	<ol>
		<li>Dilute metalloprotein standards, thyroglobulin, ferritin, ceruloplasmin, Cu/Zn SOD and Vitamin B12, to ensure they fall within the range of 0 - 500 &#181;g/L, using 1% nitric acid. To achieve standards within this range, do not use dilutions exceeding 1 in 20. Perform serial dilutions in water to dilute the stocks prior to this if required.</li>
		<li>Set up the order of injections. First, analyze the seven calibration levels, concentrations ranging from 0 - 500 &#181;g/L, followed by the metalloprotein standards. The seven calibration levels are 0, 1, 5, 10, 50, 100 and 500 &#181;g/L.</li>
		<li>Select elements of interest. Here, use Fe, Cu, Zn, Co and I, as they are the elements that the protein standards are bound to. Select the elements in the acquisition method by opening the element selector tab and adding the elements and their respective isotope masses that are to be analysed.</li>
		<li>Perform sample analysis with the instrument and the instrument software automatically creates the calibration curves for each of the elements being analyzed. The calibration curves are created by the software by plotting the counts/sec&#160;of the metal detected against the amount of metal that the standard is meant to contain, in &#181;g/L. Use the calibration curves to determine the concentration of metal in the unknown samples. 
		Note: Using the calibration curve, the software determines the concentration of metal in each of the metalloprotein standards.</li>
		<li>From the bulk analysis results, generate metalloprotein standards that include the three most abundant trace elements in mammalian tissues using a mixture of Cu, Zn superoxide dismutase (SOD) diluted to 200 &#181;g/L of copper and zinc and ferritin (FTN) at a final concentration of 2,000 &#181;g/L of iron.</li>
	</ol>
	</li>
</ol>
3. HPLC System Setup and Size Exclusion Chromatography Column Equilibration&#160;
Note: This section should be performed in parallel to the previous, since they both required about 1 - 1.5 hr&#160;to complete.
<ol>
	<li>Purge HPLC pumps with buffer made in step 1.1 and purge the pumps for 5 min&#160;at a flow rate of 5 ml/min.</li>
	<li>Once the system is purged, set the flow rate at 0.1 ml/min and connect the size exclusion column (4.6 x 300 mm, 3 &#181;m, 150 &#197;). 
	Note: A wet connection between the tubing and the column avoids any air bubbles being trapped during connection of the column.</li>
	<li>Connect the opposite end of the column to the UV detector set to measure absorbance at 280 nm using PEEK tubing.</li>
	<li>Gradually increase the flow rate of the column in increments of 0.05 - 0.1 ml/min until a final flow rate of 0.4 ml/min is reached. While this is occurring, check the tubing connections to the column for any leaks. Monitor the pressure of the system to ensure it does not exceed the column requirements by observing the pressure trace on the chromatogram in the software.</li>
	<li>Leave the column to equilibrate at the required flow rate over 5 -&#160;10 column volumes. After it is equilibrated, connect the instruments to allow sample analysis to occur.</li>
	<li>Set up the HPLC method up to pump buffer A over the column at 0.4 ml/min for 15 min.</li>
</ol>
4. Setting Up and Running Size Exclusion - Inductively Coupled Plasma - Mass Spectrometry&#160;
Note: Operating procedures may vary between instruments and models. Contact the instrument technical specialist to learn more about how to configure the ICP-MS being used.
<ol>
	<li>Place the ICP - MS into standby mode before changing the hardware setting.
	<ol>
		<li>Once in standby mode, turn off the communication for the auto sampler and change the sample introduction to &#34;other&#34;. 
		Note: Depending on the software and hardware configuration selecting &#34;HPLC&#34; as a sample introduction source can be used. Contact the instrument technical specialist to learn if this option is available.</li>
	</ol>
	</li>
	<li>Use PEEK tubing (ID 0.13 mm) to connect the out flow from the UV detector directly to the nebulizer on the ICP-MS.</li>
	<li>Power back up the ICP - MS and allow the instrument to warm up for 10 - 20 min.</li>
	<li>After the plasma has ignited, connect the remote cable from the ICP - MS to the back of the HPLC autosampler. Do this once the plasma has ignited; otherwise the HPLC system will automatically shut down since the ICP - MS is not on.</li>
	<li>Change the ICP-MS method to collect data for LC-ICP-MS.
	<ol>
		<li>Alter the acquisition method from spectrum to time resolve acquisition (TRA).</li>
		<li>Select the elements to be analyzed, Fe, Cu, Zn, Co, I as well as any other elements of interest, and set integration times (typically between 0.05 - 0.3 sec). After the elements of interest are chosen, adjust the acquisition time to match the run time for the chromatography (e.g., 900 sec for a 15 min chromatography run).</li>
		<li>Manually tune the ICP - MS for sensitivity and collision cell helium (He) gas flow rates with the chromatography buffer flowing using Cs and Sb included in the buffer. The He flow rates are typically ~1 ml/min less than those used for bulk analysis. Once the metal ion counts have stabilized and relative standard deviation (RSD) values are below 5%, the system is ready to use.</li>
	</ol>
	</li>
	<li>Make sample run lists in both the HPLC and ICP-MS software programs. The sample run list contains the order in which each of the samples is to be injected as well as the name by which the data will be saved. Check that the total number of samples in the list match between the two programs.</li>
	<li>Start the sample batch for the ICP-MS before the HPLC, as the injection of the sample by the HPLC will trigger the ICP - MS to start collecting data. If this is not done in the correct order it will result in missing data.</li>
	<li>Generate calibration curve points by injecting varying volumes of the SOD and FTN mixed standard from 200 &#181;g/L to 6,000 &#181;g/L injected on column for Cu &#38; Zn and 2,000 &#181;g/L up to 60,000 &#181;g/L for Fe. Injection volumes range from 1 to 30 &#181;l. 
	Note: These concentration ranges encompass the concentrations of Fe, Cu and Zn typically observed in complex homogenates. For samples that contain only purified proteins the maximum range of the curve should be adjusted accordingly. As the amount of metal associated with the protein may require a smaller or larger range since there is less contamination in the sample from other factors.</li>
	<li>Analyze each of the unknown samples tissue, plasma or cell culture.</li>
</ol>
5. Data Analysis, Manipulation and Visualization
<ol>
	<li>Store the data in the comma separated value (csv) file format and load into processing programs as required.</li>
	<li>In order to control for instrument drift, divide the counts per second for each element by the counts per second for either Cs or Sb.</li>
	<li>Generate calibration curves for each of the elements.
	<ol>
		<li>Determine the area under the metal peak that corresponds to the metalloprotein that it is bound to for each of the injections by performing peak integration in the preferred data analysis software.</li>
		<li>Plot the area under the metal peak against the total amount of the metal that was injected onto the column in each run, 200 - 6,000 &#181;g/L for Cu and Zn and 2,000 - 60,000 &#181;g/L for Fe. Perform linear regression analysis according to the software protocol.</li>
		<li>Use the slope results from the linear regression analysis as a factor to convert counts per second to pg/sec. Divide each of the counts per second data points across the chromatogram by the gradient of the line value.</li>
	</ol>
	</li>
	<li>Graph the data in pg/sec against the chromatogram time. Determine the area under the peaks of interest. The area under the peak represents the total amount of metal that the protein&#160;is bound to, in pg.</li>
	<li>Generate a calibration based on the molecular weight of the known metalloproteins and the time at which they elute. Use this to estimate the size of the protein peaks in complex samples.</li>
</ol>

<ol>
	<li>Holm, R. H., Kennepohl, P., Solomon, E. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Structural+and+Functional+Aspects+of+Metal+Sites+in+Biology.">Structural and Functional Aspects of Metal Sites in Biology.</a> Chem Rev. 96, 2239-2314 (1996).</li><li>Andreini, C., Bertini, I., Cavallaro, G., Holliday, G., Thornton, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Metal+ions+in+biological+catalysis:+from+enzyme+databases+to+general+principles.">Metal ions in biological catalysis: from enzyme databases to general principles.</a> J Biol Inorg Chem. 13, 1205-1218 (2008).</li><li>Roberts, B. R., Ryan, T. M., Bush, A. I., Masters, C. L., Duce, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+metallobiology+and+amyloid-beta+peptides+in+Alzheimer's+disease.">The role of metallobiology and amyloid-beta peptides in Alzheimer's disease.</a> J Neurosci. 120 (Suppl 1), 149-166 (2012).</li><li>Roberts, B. R., 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=Oral+Treatment+with+CuII+(atsm)+Increases+Mutant+SOD1+In+Vivo+but+Protects+Motor+Neurons+and+Improves+the+Phenotype+of+a+Transgenic+Mouse+Model+of+Amyotrophic+Lateral+Sclerosis.">Oral Treatment with CuII (atsm) Increases Mutant SOD1 In Vivo but Protects Motor Neurons and Improves the Phenotype of a Transgenic Mouse Model of Amyotrophic Lateral Sclerosis.</a> J Neurosci. 34, 8021-8031 (2014).</li><li>Hare, D. J., 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=Decreased+plasma+iron+in+Alzheimer's+disease+is+due+to+transferrin+desaturation.">Decreased plasma iron in Alzheimer's disease is due to transferrin desaturation.</a> ACS CHEM NEUROSCI. , (2015).</li><li>Cvetkovic, A., 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=Microbial+metalloproteomes+are+largely+uncharacterized.">Microbial metalloproteomes are largely uncharacterized.</a> Nature. 466, 779-782 (2010).</li><li>Barnett, J., Scanlan, D., Blindauer, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Protein+fractionation+and+detection+for+metalloproteomics:+challenges+and+approaches.">Protein fractionation and detection for metalloproteomics: challenges and approaches.</a> Anal Bioanal Chem. 402, 3311-3322 (2012).</li><li>Fernandez Sanchez, L., Szpunar, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Speciation+analysis+for+iodine+in+milk+by+size-exclusion+chromatography+with+inductively+coupled+plasma+mass+spectrometric+detection(SEC-ICP+MS).">Speciation analysis for iodine in milk by size-exclusion chromatography with inductively coupled plasma mass spectrometric detection(SEC-ICP MS).</a> J. Anal. At. Spectrom. 14, 1697-1702 (1999).</li><li>Manley, S., Byrns, S., Lyon, A., Brown, P., Gailer, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simultaneous+Cu-,+Fe-,+and+Zn-specific+detection+of+metalloproteins+contained+in+rabbit+plasma+by+size-exclusion+chromatography-inductively+coupled+plasma+atomic+emission+spectroscopy.">Simultaneous Cu-, Fe-, and Zn-specific detection of metalloproteins contained in rabbit plasma by size-exclusion chromatography-inductively coupled plasma atomic emission spectroscopy.</a> J Biol Inorg Chem. 14, 61-74 (2009).</li><li>Richarz, A. N., Br&#228;tter, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Speciation+analysis+of+trace+elements+in+the+brains+of+individuals+with+Alzheimer's+disease+with+special+emphasis+on+metallothioneins.">Speciation analysis of trace elements in the brains of individuals with Alzheimer's disease with special emphasis on metallothioneins.</a> Anal Bioanal Chem. 372, 412-417 (2002).</li><li>Hare, D. J., 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=Profiling+the+iron,+copper+and+zinc+content+in+primary+neuron+and+astrocyte+cultures+by+rapid+online+quantitative+size+exclusion+chromatography-inductively+coupled+plasma-mass+spectrometry.">Profiling the iron, copper and zinc content in primary neuron and astrocyte cultures by rapid online quantitative size exclusion chromatography-inductively coupled plasma-mass spectrometry.</a> Metallomics. 5, 1656-1662 (2013).</li><li>Balkhi, S. E., 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=Human+Plasma+Copper+Proteins+Speciation+by+Size+Exclusion+Chromatography+Coupled+to+Inductively+Coupled+Plasma+Mass+Spectrometry.+Solutions+for+Columns+Calibration+by+Sulfur+Detection.">Human Plasma Copper Proteins Speciation by Size Exclusion Chromatography Coupled to Inductively Coupled Plasma Mass Spectrometry. Solutions for Columns Calibration by Sulfur Detection.</a> Anal Chem. 82, 6904-6910 (2010).</li><li>Desjardins, P., Hansen, J. B., Allen, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microvolume+Protein+Concentration+Determination+using+the+NanoDrop+2000c+Spectrophotometer.">Microvolume Protein Concentration Determination using the NanoDrop 2000c Spectrophotometer.</a> J Vis Exp. , e1610 (2009).</li></ol>

The authors have nothing to disclose

Ensuring the native state of the protein means special attention to the buffers used and storage of the sample are needed. Not all chromatography techniques or sample preparation techniques can be employed. It is important that the buffers used throughout sample preparation and chromatography are devoid of metal chelators and use buffers that mimic physiological pH and salt concentrations. Other conditions to avoid include heating the sample or addition of protein denaturants (e.g., urea). It is critical to minimize the number of freeze thaw cycles. The ability of the chosen buffer to bind divalent metals is also important and is a reason that Tris or ammonium nitrate buffers are chosen over phosphate based buffers.
The low resolution and peak capacity of the size exclusion chromatography relative to other forms of chromatography is a major limitation of this technique. However, the gentle nature of size exclusion chromatography is important to maintain the native state of the protein and thus preserve the relatively weak metal-protein bonds. The requirement to maintain the native state of the proteins requires special attention to the treatment of the samples including limiting the number of freeze thaw cycles, avoiding metal chelators (e.g., EDTA) or chaotropic salts and detergents.&#160;
This low resolution of this technique impacts the ability to quantify the amount of metal associated with a specific protein if it is in a complex sample as the peaks seen will contain more then one protein. Therefore, the amount of metal determined using the peak integration would be an indication of the total amount of metal associated with all of the proteins eluting at this time point and not just one specific protein. In order to overcome this limitation the protein of interest would have to be further purified under native conditions. This would allow for the quantification of the metal associated with this protein to be reported with a higher degree of certainity. Another potential limitation of this technique would be the loss of protein due to non reversible binding to the column. In order to determine if this is happening a recovery experiment should be carried out whereby the amount of protein eluting off the column is analysed to determine if this matches the amount injected. The same can be done by measuring the metal content of the elution material and the starting material by bulk ICP-MS. Column recovery can differ depending on the conditions used, but it has been shown that complete recovery of proteins from a size exclusion column is possible9. Thus it is important to check whether or not there is any loss under the operating conditions being used.
Modifications to the protocol can be related to the metalloprotein standards that are used as well as the elements analyzed. The type of metalloprotein standard used will differ depending on the elements that are of interest. For elements such as Cu, Fe and Zn proteins, SOD and ferritin are employed. Any other metalloprotein that have known stoichometries can also be used and a few examples have been shown here.
One major complication that can arise from using this technique is the build up of salt crystals in the torch of the ICP-MS. To prevent the build-up of salt crystals, the torch is washed with distilled water after every 500 - 1,000 ml&#160;of buffer that has been passed through the system or when it is determined by visual inspection that the torch should be washed. Another problem that can arise is a more rapid decline in the cleanliness of the sample and extraction cones. These need to be cleaned regularly following manufacturer&#39;s protocols.
The initial sample preparation is the most critical step in the protocol. If there are any changes to the protein - metal complex the information generated will not be valid. This is one of the major limitations of the technique; in addition the use of the low resolution, size exclusion column yields a limited detailed view of the true complexity of metalloproteins in biology.
The technique described here allows the expansion of knowledge of the metalloproteome of an organism. Bulk analysis only gives a crude indication of changes to the amount of metal within a sample. Besides the general considerations that need to be taken into account, this technique provides a tool that can be used to quantitate the amount of metal associated with proteins&#160;as well as identifying metalloproteins that differ by comparing the traces obtained. The use of this technique can be employed to identify differences between disease states. The identified metalloproteins can then be further investigated to help determine the role they play in disease processes. The application of hyphenated ICP-MS has a growing future to determine the role of drugs that have a heteroatom such as platinum, iodine or copper as the ICP-MS can be used to identify the proteins that the drug binds.

Essential metals play a vital role in normal biological functions, including secondary messenger pathways, metabolism pathways and organelle functions. 30% of all proteins are thought to be metalloproteins1 and 50% of all enzymes2. Metalloenzymes use these trace metals as cofactors to catalyze chemical reactions, stabilize protein structure, and for regulatory roles such as secondary messengers. Some of the most studied trace elements in regards to neurodegeneration are copper, iron and zinc3. They are thought to be involved in many disease pathways where by dyshomeostasis can have adverse affects. For example the metal status of superoxide dismutase (SOD) directly impacts the life span and phenotype of the transgenic mice models of familial type of amyotrophic lateral sclerosis (ALS)4. In Alzheimer&#39;s disease, metalloproteomics techniques have been used to discover a decrease in the metal status of transferrin in plasma5. These studies highlight the important role metalloproteins can play in disease.
The study of metalloproteins directly from biological tissues is a developing field. Although some metalloenzymes have been characterized, the majority still remain uncharacterized or unknown6. One of the major challenges in measuring metalloproteins is the requirement to maintain the native state of the protein7. Classical bottom-up proteomic techniques rely on the digestion of the proteins into peptides. This process disrupts the non-covalent interaction of metals and their proteins. Thus, no information about the metal status of a protein is gained.
One way to overcome this issue is by using size exclusion chromatography paired with inductively coupled plasma - mass spectrometry8,9 (SEC-ICP-MS). This generates information about the protein&#39;s approximate size as well as any metals that are associated with it10. Further, size exclusion is a gentle chromatographic technique that can preserve the native state of an enzyme or protein-protein complex. One advantage of using inductively coupled plasma - mass spectrometry (ICP-MS) is the quantitative nature of the technology. Using a set of metalloproteins standards it is possible to provide absolute quantitation of metalloproteins from biological samples9,11. This is achieved by generating a standard curve by injecting known metalloproteins over a range of metal concentrations.
This protocol shows an example of how this can be achieved for a variety of metalloprotein standards. In this paper we aim to create standard curves for metals that are largely investigated in biological fields including iron (Fe), copper (Cu), zinc (Zn), iodine (I), and cobalt (Co).

<table>
	<tbody>
		<tr>
			<td>Agilent 1290 Infinity Binary Pump</td>
			<td>Agilent</td>
			<td>G4220A</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent 1290 Infinity Autosampler</td>
			<td>Agilent</td>
			<td>G4226A</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent 1200 Series Autosampler Thermostat</td>
			<td>Agilent</td>
			<td>G1330B</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent 1290 Infinity Thermostatted Column Compartment</td>
			<td>Agilent</td>
			<td>G1316C</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent 1290 Infinity Variable Wavelength Detector</td>
			<td>Agilent</td>
			<td>G1314E</td>
			<td></td>
		</tr>
		<tr>
			<td>Agilent 7700 ICP-MS</td>
			<td>Agilent</td>
			<td>G3282A</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Ammonium hydroxide trace metal basis&#160;&#160;&#160;</td>
			<td>Sigma</td>
			<td>338818</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Ammonium nitrate&#160;</td>
			<td>Sigma&#160;</td>
			<td>256064</td>
			<td>Make fresh 200mM solution on day of experiment</td>
		</tr>
		<tr>
			<td>&#160;Antinomy&#160;</td>
			<td>Choice analytical&#160;</td>
			<td>10002-3&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Ceruloplasmin&#160;</td>
			<td>Sigma</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Cesium&#160;</td>
			<td>Choice analytical&#160;</td>
			<td>100011-1&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Complete, EDTA free protease inhibitors&#160;&#160;</td>
			<td>Roche</td>
			<td>11873580001</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Conalbumin&#160;</td>
			<td>Sigma</td>
			<td>C7786</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Concanavalin A from Canavalia ensiformis (Jack bean)&#160;</td>
			<td>Sigma</td>
			<td>L7647</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Cu, Zn Superoxide dismutase&#160;</td>
			<td>Sigma</td>
			<td>S9697</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Ferritin&#160;</td>
			<td>Sigma</td>
			<td>F4503</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;ICP-MS multielemental calibration standards&#160;</td>
			<td>AccuStandard</td>
			<td></td>
			<td>Made up to required concentrations in 1% nitric acid</td>
		</tr>
		<tr>
			<td>&#160;Microvolume UV spectrophotometer&#160;</td>
			<td>Thermo Scientific</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;65% Nitric acid&#160;</td>
			<td>Millipore</td>
			<td>100441</td>
			<td>Diluted to 1% for use</td>
		</tr>
		<tr>
			<td>&#160;Peek tubing&#160;&#160;</td>
			<td>Agilent</td>
			<td>5042-6461</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Size exclusion column BioSEC-3 PLC. column, 4.6x300mm, 3&#956;m, 150&#197;&#160;</td>
			<td>Agilent</td>
			<td>5190-2508</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Sodium Chloride&#160;</td>
			<td>Chem Supply</td>
			<td>SA046</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Tris Hydrochloride&#160;</td>
			<td>ICN Biomedicals inc.&#160;</td>
			<td>103130</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Thyroglobulin&#160;</td>
			<td>Sigma</td>
			<td>T9145</td>
			<td></td>
		</tr>
		<tr>
			<td>&#160;Vitamin B12&#160;</td>
			<td>Sigma</td>
			<td>V2876</td>
			<td></td>
		</tr>
	</tbody>
</table>

standards for quantitative metalloproteomic analysis using size exclusion icp-ms

Metals are essential for protein function as cofactors to catalyze chemical reactions. Disruption of metal homeostasis is implicated in a number of diseases including Alzheimer's and Parkinson's disease, but the exact role these metals play is yet to be fully elucidated. Identification of metalloproteins encounters many challenges and difficulties. Here we report an approach that allows metalloproteins in complex samples to be quantified. This is achieved using size exclusion chromatography coupled with inductively coupled plasma - mass spectrometry (SEC-ICP-MS). Using six known metalloproteins, the size exclusion column can be calibrated and the respective trace elements (iron, copper, zinc, cobalt, iodine) can be used for quantification. SEC-ICP-MS traces of human brain and plasma are presented. The use of these metalloprotein standards provides the means to quantitatively compare metalloprotein abundances between biological samples. This technique is poised to help shed light on the role of metalloproteins in neurodegenerative disease as well as other diseases where imbalances in trace elements are implicated.

The use of metalloprotein standards allows for the calibration of the size exclusion column. Figure 1A shows the elution profile for the standards thyroglobulin, ferritin, ceruloplasmin, Cu/Zn SOD and Vitamin B12 based on the metal that they are bound to (Fe, Co, Cu, Zn and I). Figure 1B shows the calibration curve for the size exclusion column based on the molecular weight of protein standards and their elution time, presented in the format of elution volume (Ve) divided by the void volume of the column (Vo). The proteins used to generate this standard curve are concanavalin A, conalbumin, ceruloplasmin, ferritin, SOD and thyroglobulin.
Figure 2A shows the elution of ferritin over a range of 2,000 - 60,000 pg of Fe injected on column and Figure 2D is the regression analysis performed using peak area. Figures 2B and 2C are the elution profiles for Cu/Zn SOD for Cu and Zn and 2E and 2F are the regression analyses generated using peak areas. The results of the regression analysis are used to convert the raw data in counts/sec&#160;to pg/sec&#160;so the amount of metal associated with the protein can be determined quantitatively. The conversion is done by dividing the counts/sec&#160;by the slope of the linear regression (e.g., 334.6 (counts/sec) x (sec/pg) of copper).
As stated, this technique can be used to identify metalloproteins in complex biological samples. Human brain and plasma have been subjected to this technique and Figures 3 and 4, respectively, show the results obtained. Human brain separated by SEC-ICP-MS is shown in Figures 3A-3C, each of which represent a different metal of interest (Cu, Zn or Fe). Figures 4A-4C show the traces&#160;obtained when human plasma is subjected to this technique. The complexity and abundance of the sample will impact the number of peaks that are seen. As expected plasma is dominated by a few metalloproteins including ceruloplasmin and transferrin.
<img alt="Figure 1" src="/files/ftp_upload/53737/53737fig1.jpg" /> 
Figure 1.&#160;Calibration of Size Exclusion Chromatography - Inductively Coupled Plasma&#160;- Mass Spectrometry Using Known Metalloproteins. (A) Elution profile for the metalloprotein standards based on their respective metals. (B) Molecular weight calibration curve for protein standards thyroglobulin (i), ferritin (ii), ceruloplasmin (iii), conalbumin (iv), Cu/Zn SOD (v) and concanavalin A (vi). <a href="https://www.jove.com/files/ftp_upload/53737/53737fig1large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" src="/files/ftp_upload/53737/53737fig2.jpg" /> 
Figure 2.&#160;Use of Ferritin and Cu/Zn SOD as Metalloprotein Standards to Determine the Amount of Cu, Fe or Zn Associated with Metalloproteins in a Complex Biological Sample. (A) Elution profile for ferritin over the injection range 2,000 - 60,000 &#181;g/L of iron. (B) and (C) Elution profile for Cu/Zn SOD over the injection range of 200 - 6,000 &#181;g/L of copper and zinc, respectively. (D), (E) and (F) show the regression analysis results for the metals iron, copper and zinc, respectively. <a href="https://www.jove.com/files/ftp_upload/53737/53737fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" src="/files/ftp_upload/53737/53737fig3.jpg" /> 
Figure 3.&#160;Cu, Fe and Zn Metalloproteome of Human Brain. (A) Copper trace (B) Iron trace (C) Zinc trace. Elution of the protein standards for each metal is shown by the black trace with their molecular weight indicated under the graph. <a href="https://www.jove.com/files/ftp_upload/53737/53737fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" src="/files/ftp_upload/53737/53737fig4.jpg" /> 
Figure 4.&#160;Cu, Fe and Zn Metalloproteome for Human Plasma. (A) Copper trace (B) Iron trace (C) Zinc trace. Elution of the protein standards for each metal is shown by the black trace with their molecular weight indicated under the graph. <a href="https://www.jove.com/files/ftp_upload/53737/53737fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about Standards for Quantitative Metalloproteomic Analysis Using Size Exclusion ICP-MS at JoVE.com

Standards for Quantitative Metalloproteomic Analysis Using Size Exclusion ICP-MS

Size exclusion chromatography hyphenated with inductively coupled plasma - mass spectrometry (ICP-MS) is a powerful tool to measure changes in the abundance of metalloproteins directly from biological samples. Here we describe a set of metalloprotein standards used to estimate molecular mass and the amount of metal associated with unknown proteins.

Metals are essential for protein function as cofactors to catalyze chemical reactions. Disruption of metal homeostasis is implicated in a number of ...

standards-for-quantitative-metalloproteomic-analysis-using-size

Research

Education

JoVE Core

JoVE Journal

Analytical Chemistry

Chemistry

Unit 1

Atomic Spectroscopy

SCIENTISTS IN ACTION

Quantitative Proteomics Using Reductive Dimethylation for Stable Isotope Labeling

Stable isotope labeling of peptides by reductive dimethylation (ReDi labeling) is a method to accurately quantify protein expression differences between samples using mass spectrometry. ReDi labeling is performed using either regular (light) or deuterated (heavy) forms of formaldehyde and sodium cyanoborohydride to add two methyl groups to each free amine. Here we demonstrate a robust protocol for ReDi labeling and quantitative comparison of complex protein mixtures. Protein samples for comparison are digested into peptides, labeled to carry either light or heavy methyl tags, mixed, and co-analyzed by LC-MS/MS. Relative protein abundances are quantified by comparing the ion chromatogram peak areas of heavy and light labeled versions of the constituent peptide extracted from the full MS spectra. The method described here includes sample preparation by reversed-phase solid phase extraction, on-column ReDi labeling of peptides, peptide fractionation by basic pH reversed-phase (BPRP) chromatography, and StageTip peptide purification. We discuss advantages and limitations of ReDi labeling with respect to other methods for stable isotope incorporation. We highlight novel applications using ReDi labeling as a fast, inexpensive, and accurate method to compare protein abundances in nearly any type of sample.

Stable isotope labeling of peptides by reductive dimethylation (ReDi labeling) is a rapid, inexpensive strategy for accurate mass spectrometry-based quantitative proteomics. Here we demonstrate a robust method for preparation and analysis of protein mixtures using the ReDi approach that can be applied to nearly any sample type.

Stable isotope labeling of peptides by reductive dimethylation (ReDi labeling) is a method to accurately quantify protein expression differences between ...

Quantitative and Qualitative Examination of Particle-particle Interactions Using Colloidal Probe Nanoscopy

Colloidal Probe Nanoscopy (CPN), the study of the nano-scale interactive forces between a specifically prepared colloidal probe and any chosen substrate using the Atomic Force Microscope (AFM), can provide key insights into physical interactions present within colloidal systems. Colloidal systems are widely existent in several applications including, pharmaceuticals, foods, paints, paper, soil and minerals, detergents, printing and much more.1-3 Furthermore, colloids can exist in many states such as emulsions, foams and suspensions. Using colloidal probe nanoscopy one can obtain key information on the adhesive properties, binding energies and even gain insight into the physical stability and coagulation kinetics of the colloids present within. Additionally, colloidal probe nanoscopy can be used with biological cells to aid in drug discovery and formulation development. In this paper we describe a method for conducting colloidal probe nanoscopy, discuss key factors that are important to consider during the measurement, and show that both quantitative and qualitative data that can be obtained from such measurements.

Colloidal probe nanoscopy can be used within a variety of fields to gain insight into the physical stability and coagulation kinetics of colloidal systems and aid in drug discovery and formulation sciences using biological systems. The method described within provides a quantitative and qualitative means to study such systems.

Colloidal Probe Nanoscopy (CPN), the study of the nano-scale interactive forces between a specifically prepared colloidal probe and any chosen substrate ...

Au-Interaction of Slp1 Polymers and Monolayer from Lysinibacillus sphaericus JG-B53 - QCM-D, ICP-MS and AFM as Tools for Biomolecule-metal Studies

In this publication the gold sorption behavior of surface layer (S-layer) proteins (Slp1) of Lysinibacillus sphaericus JG-B53 is described. These biomolecules arrange in paracrystalline two-dimensional arrays on surfaces, bind metals, and are thus interesting for several biotechnical applications, such as biosorptive materials for the removal or recovery of different elements from the environment and industrial processes. The deposition of Au(0) nanoparticles on S-layers, either by S-layer directed synthesis 1 or adsorption of nanoparticles, opens new possibilities for diverse sensory applications. Although numerous studies have described the biosorptive properties of S-layers 2-5, a deeper understanding of protein-protein and protein-metal interaction still remains challenging. In the following study, inductively coupled mass spectrometry (ICP-MS) was used for the detection of metal sorption by suspended S-layers. This was correlated to measurements of quartz crystal microbalance with dissipation monitoring (QCM-D), which allows the online detection of proteinaceous monolayer formation and metal deposition, and thus, a more detailed understanding on metal binding.
The ICP-MS results indicated that the binding of Au(III) to the suspended S-layer polymers is pH dependent. The maximum binding of Au(III) was obtained at pH 4.0. The QCM-D investigations enabled the detection of Au(III) sorption as well as the deposition of Au(0)-NPs in real-time during the in situ experiments. Further, this method allowed studying the influence of metal binding on the protein lattice stability of Slp1. Structural properties and protein layer stability could be visualized directly after QCM-D experiment using atomic force microscopy (AFM). In conclusion, the combination of these different methods provides a deeper understanding of metal binding by bacterial S-layer proteins in suspension or as monolayers on either bacterial cells or recrystallized surfaces.

Au-Interaction of Slp1 Polymers and Monolayer from Lysinibacillus sphaericus JG-B53 - QCM-D, ICP-MS and AFM as Tools for Biomolecule-metal Studies

To obtain basic information on the sorption and recycling of gold from aqueous systems the interaction of Au(III) and Au(0) nanoparticles on S-layer proteins were investigated. The sorption of protein polymers was investigated by ICP-MS and that of proteinaceous monolayers by QCM-D. Subsequent AFM enables the imaging of the nanostructures.

In this publication the gold sorption behavior of surface layer (S-layer) proteins (Slp1) of Lysinibacillus sphaericus JG-B53 is described. These ...

Using Capillary Electrophoresis to Quantify Organic Acids from Plant Tissue: A Test Case Examining Coffea arabica Seeds

Carboxylic acids are organic acids containing one or more terminal carboxyl (COOH) functional groups. Short chain carboxylic acids (SCCAs; carboxylic acids containing three to six carbons), such as malate and citrate, are critical to the proper functioning of many biological systems, where they function in cellular respiration and can serve as indicators of cell health. In foods, organic acid content can have significant impact on taste, with increased SCCA levels resulting in a sour or &#34;acid&#34; taste. Because of this, methods for the rapid analysis of organic acid levels are of particular interest to the food and beverage industries. Unfortunately, however, most methods used for SCCA quantification are dependent on time-consuming protocols requiring the derivatization of samples with hazardous reagents, followed by costly chromatographic and/or mass spectrometric analyses. This method details an alternate method for the detection and quantification of organic acids from plant material and food samples using free zonal capillary electrophoresis (CZE), sometimes simply referred to as capillary electrophoresis (CE). CZE provides a cost-effective method for measuring SCCAs with a low limit of detection (0.005 mg/ml). This article details the extraction and quantification of SCCAs from plant samples. While the method provided focuses on measurement of SCCAs from coffee beans, the method provided can be applied to multiple plant-based food materials.

Using Capillary Electrophoresis to Quantify Organic Acids from Plant Tissue: A Test Case Examining Coffea arabica Seeds

This article presents a method for the detection and quantification of organic acids from plant material using free zonal capillary electrophoresis. An example of the potential application of this method, determining the effects of a secondary fermentation on organic acid levels in coffee seeds, is provided.

Carboxylic acids are organic acids containing one or more terminal carboxyl (COOH) functional groups. Short chain carboxylic acids (SCCAs; carboxylic ...

Measurement of Particle Size Distribution in Turbid Solutions by Dynamic Light Scattering Microscopy

A protocol for measuring polydispersity of concentrated polymer solutions using dynamic light scattering is described. Dynamic light scattering is a technique used to measure the size distribution of polymer solutions or colloidal particles. Although this technique is widely used for the assessment of polymer solutions, it is difficult to measure the particle size in concentrated solutions due to the multiple scattering effect or strong light absorption. Therefore, the concentrated solutions should be diluted before measurement. Implementation of the confocal optical component in a dynamic light scattering microscope1 helps to overcome this barrier. Using such a microscopic system, both transparent and turbid systems can be analyzed under the same experimental setup without a dilution. As a representative example, a size distribution measurement of a temperature-responsive polymer solution was performed. The sizes of the polymer chains in an aqueous solution were several tens of nanometers at a temperature below the lower critical solution temperature (LCST). In contrast, the sizes increased to more than 1.0 &#181;m when above the LCST. This result is consistent with the observation that the solution turned turbid above the LCST.

A protocol for the direct measurement of particle size distribution in concentrated solutions using dynamic light scattering microscopy is presented.

A protocol for measuring polydispersity of concentrated polymer solutions using dynamic light scattering is described. Dynamic light scattering is a ...

Fabrication and Testing of Photonic Thermometers

In recent years, a push for developing novel silicon photonic devices for telecommunications has generated a vast knowledge base that is now being leveraged for developing sophisticated photonic sensors. Silicon photonic sensors seek to exploit the strong confinement of light in nano-waveguides to transduce changes in physical state to changes in resonance frequency. In the case of thermometry, the thermo-optic coefficient, i.e., changes in refractive index due to temperature, causes the resonant frequency of the photonic device such as a Bragg grating to drift with temperature. We are developing a suite of photonic devices that leverage recent advances in telecom compatible light sources to fabricate cost-effective photonic temperature sensors, which can be deployed in a wide variety of settings ranging from controlled laboratory conditions, to the noisy environment of a factory floor or a residence. In this manuscript, we detail our protocol for the fabrication and testing of photonic thermometers.

We describe the process of fabrication and testing of photonic thermometers.

In recent years, a push for developing novel silicon photonic devices for telecommunications has generated a vast knowledge base that is now being ...

Disentangling High Strength Copolymer Aramid Fibers to Enable the Determination of Their Mechanical Properties

Traditionally, soft body armor has been made from poly(p-phenylene terephthalamide) (PPTA) and ultra-high molecular weight polyethylene. However, to diversify the fiber choices in the United States body armor market, copolymer fibers based on the combination of 5-amino-2-(p-aminophenyl) benzimidazole (PBIA) and the more conventional PPTA were introduced. Little is known regarding the long-term stability of these fibers, but as condensation polymers, they are expected to have potential sensitivity to moisture and humidity. Therefore, characterizing the strength of the materials and understanding their vulnerability to environmental conditions is important for evaluating their use lifetime in safety applications. Ballistic resistance and other critical structural properties of these fibers are predicated on their strength. To accurately determine the strength of the individual fibers, it is necessary to disentangle them from the yarn without introducing any damage. Three aramid-based copolymer fibers were selected for the study. The fibers were washed with acetone followed by methanol to remove an organic coating that held the individual fibers in each yarn bundle together. This coating makes it difficult to separate single fibers from the yarn bundle for mechanical testing without damaging the fibers and affecting their strength. After washing, fourier transform infrared (FTIR) spectroscopy was performed on both washed and unwashed samples and the results were compared. This experiment has shown that there are no significant variations in the spectra of poly(p-phenylene-benzimidazole-terephthalamide-co-p-phenylene terephthalamide) (PBIA-co-PPTA1) and PBIA-co-PPTA3 after washing, and only a small variation in intensity for PBIA. This indicates that the acetone and methanol rinses are not adversely affecting the fibers and causing chemical degradation. Additionally, single fiber tensile testing was performed on the washed fibers to characterize their initial tensile strength and strain to failure, and compare those to other reported values. Iterative procedural development was necessary to find a successful method for performing tensile testing on these fibers.

The primary goal of the study is to develop a protocol to prepare consistent specimens for accurate mechanical testing of high strength copolymer aramid fibers, by removing a coating and disentangling the individual fiber strands without introducing significant chemical or physical degradation.

Traditionally, soft body armor has been made from poly(p-phenylene terephthalamide) (PPTA) and ultra-high molecular weight polyethylene. However, to ...

Application of Voltage in Dynamic Light Scattering Particle Size Analysis

Dynamic light scattering (DLS) is a common method for characterizing the size distribution of polymers, proteins, and other nano- and microparticles. Modern instrumentation permits measurement of particle size as a function of time and/or temperature, but currently there is no simple method for performing DLS particle size distribution measurements in the presence of applied voltage. The ability to perform such measurements would be useful in the development of electroactive, stimuli-responsive polymers for applications such as sensing, soft robotics, and energy storage. Here, a technique using applied voltage coupled with DLS and a temperature ramp to observe changes in aggregation and particle size in thermoresponsive polymers with and without electroactive monomers is presented. The changes in aggregation behavior observed in these experiments were only possible through the combined application of voltage and temperature control. To obtain these results, a potentiostat was connected to a modified cuvette in order to apply voltage to a solution. Changes in polymer particle size were monitored using DLS in the presence of constant voltage. Simultaneously, current data were produced, which could be compared with particle size data, to understand the relationship between current and particle behavior. The polymer poly(N-isopropylacrylamide) (pNIPAM) served as a test polymer for this technique, as pNIPAM's response to temperature is well-studied. Changes in the lower-critical solution temperature (LCST) aggregation behavior of pNIPAM and poly(N-isopropylacrylamide)-block-poly(ferrocenylmethyl methacrylate), an electrochemically active block-copolymer, in the presence of applied voltage are observed. Understanding the mechanisms behind such changes will be important when trying to achieve reversible polymer structures in the presence of applied voltage.

Here, a protocol to apply voltage to solution during dynamic light scattering particle size measurements with the intent to explore the effect of voltage and temperature changes on polymer aggregation is presented.

Dynamic light scattering (DLS) is a common method for characterizing the size distribution of polymers, proteins, and other nano- and microparticles. ...

Setup of Capillary Electrophoresis-Inductively Coupled Plasma Mass Spectrometry (CE-ICP-MS) for Quantification of Iron Redox Species (Fe(II), Fe(III))

Dyshomeostasis of iron metabolism is accounted in the pathophysiological framework of numerous diseases, including cancer and several neurodegenerative conditions. Excessive iron results in free redox-active Fe(II) and can cause devastating effects within the cell like oxidative stress (OS) and death by lipid peroxidation known as ferroptosis (FPT). Therefore, quantitative measurements of ferrous (Fe(II)) and ferric (Fe(III)) iron rather than total Fe-determination is the key for closer insight into these detrimental processes. Since Fe(II)/(III) determinations can be hampered by fast redox-state shifts and low concentrations in relevant samples, like cerebrospinal fluid (CSF), methods should be available that analyze quickly and provide low limits of quantification (LOQ). Capillary electrophoresis (CE) offers the advantage of fast Fe(II)/Fe(III) separation and works without a stationary phase, which could interfere with the redox balance or cause analyte sticking. CE combined with inductively coupled plasma mass spectrometry (ICP-MS) as a detector offers further improvement of detection sensitivity and selectivity. The presented method uses 20 mM HCl as a background electrolyte and a voltage of +25 kV. Peak shapes and concentration detection limits are improved by conductivity-pH-stacking. For reduction of 56[ArO]+, ICP-MS was operated in the dynamic reaction cell (DRC) mode with NH3 as a reaction gas. The method achieves a limit of detection (LOD) of 3 &#181;g/L. Due to stacking, higher injection volumes were possible without hampering separation but improving LOD. Calibrations related to peak area were linear up to 150 &#181;g/L. Measurement precision was 2.2% (Fe(III)) to 3.5% (Fe(II)). Migration time precision was &#60;3% for both species, determined in 1:2 diluted lysates of human neuroblastoma (SH-SY5Y) cells. Recovery experiments with standard addition revealed accuracy of 97% Fe(III) and 105 % Fe(II). In real-life bio-samples like CSF, migration time can vary according to varying conductivity (i.e., salinity). Thus, peak identification is confirmed by standard addition.

Setup of Capillary Electrophoresis-Inductively Coupled Plasma Mass Spectrometry CE-ICP-MS for Quantification of Iron Redox Species FeII, FeIII

This iron redox speciation method is based on capillary electrophoresis-inductively coupled plasma mass spectrometry with sample stacking combined with short analysis in one run. The method quickly analyzes and provides low limits of quantification for iron redox species across a diverse range of tissues and biofluid samples.

Dyshomeostasis of iron metabolism is accounted in the pathophysiological framework of numerous diseases, including cancer and several neurodegenerative ...

Preparation of Nanoparticles for ToF-SIMS and XPS Analysis

Nanoparticles have gained increasing attention in recent years due to their potential and application in different fields including medicine, cosmetics, chemistry, and their potential to enable advanced materials. To effectively understand and regulate the physico-chemical properties and potential adverse effects of nanoparticles, validated measurement procedures for the various properties of nanoparticles need to be developed. While procedures for measuring nanoparticle size and size distribution are already established, standardized methods for analysis of their surface chemistry are not yet in place, although the influence of the surface chemistry on nanoparticle properties is undisputed. In particular, storage and preparation of nanoparticles for surface analysis strongly influences the analytical results from various methods, and in order to obtain consistent results, sample preparation must be both optimized and standardized. In this contribution, we present, in detail, some standard procedures for preparing nanoparticles for surface analytics. In principle, nanoparticles can be deposited on a suitable substrate from suspension or as a powder. Silicon (Si) wafers are commonly used as substrate, however, their cleaning is critical to the process. For sample preparation from suspension, we will discuss drop-casting and spin-coating, where not only the cleanliness of the substrate and purity of the suspension but also its concentration play important roles for the success of the preparation methodology. For nanoparticles with sensitive ligand shells or coatings, deposition as powders is more suitable, although this method requires particular care in fixing the sample.

A number of different procedures for preparing nanoparticles for surface analysis are presented (drop casting, spin coating, deposition from powders, and cryofixation). We discuss the challenges, opportunities, and possible applications of each method, particularly regarding the changes in the surface properties caused by the different preparation methods.

Nanoparticles have gained increasing attention in recent years due to their potential and application in different fields including medicine, cosmetics, ...