E.J.N.G. is supported by the Wellcome Trust (grant 106098/Z/14/Z). Other funding has been provided by the SMA Trust (SMA UK Consortium; T.H.G. &#38; Y-T.H.), SMA Europe (T.H.G, D.v.D.H. &#38; E.J.N.G.), the University of Edinburgh DTP in Precision Medicine (T.H.G., L.L. &#38; A.M.M.), and the Euan MacDonald Centre for Motor Neurone Disease Research (T.H.G).

Tissues for this procedure were obtained from animal studies that were approved by the internal ethics committee at the University of Edinburgh and were performed in concordance with institutional and UK Home Office regulations under the authority of relevant personal and project licenses.
NOTE: This protocol has been optimized using standardized, commercially available kits and reagents in order to increase reproducibility (see Table of Materials).
1. Preparation of samples
<ol>
	<li>Protein extraction 
	<ol>
		<li>Transfer snap-frozen cell or tissue samples from -80 &#176;C on dry ice, thaw on ice, and wash as required with ice cold 1x phosphate-buffered saline (PBS) (for details on tissues and PBS washes, see Table 1). Avoid unnecessary freeze-thaw cycles as this will affect protein quality.</li>
		<li>Add radioimmunoprecipitation assay (RIPA) buffer (25 mM Tris-HCl (pH 7.6), 150 mM NaCl, 1% NP-40, 1% sodium deoxycholate, 0.1% SDS) containing 1x protease inhibitor to each sample, using the optimal amount per tissue weight (see Table 1 for recommendations). 
		NOTE: Depending on the application, the type and amount of homogenization buffer may need further optimization.</li>
		<li>Use a hand-held electric homogenizer with a polypropylene pestle to homogenize tissue samples. Between each sample, wash the pestle in double-distilled water and dry with a clean tissue. Change the pestle between different experimental conditions and tissues.</li>
		<li>Leave the samples on ice for 10 min after homogenization. Centrifuge the samples at &#62;10,000 x g at 4 &#176;C for 10 min.</li>
		<li>Transfer the supernatant to a new tube on ice without disturbing the pellet. The supernatant is the protein sample. Store the extracted protein at -80 &#176;C or directly proceed to measuring the protein concentration.</li>
	</ol>
	</li>
	<li>Quantification and normalization of protein concentration 
	<ol>
		<li>Measure the protein concentration using a bicinchoninic acid (BCA) assay. Prepare a BCA assay mix according to the manufacturer&#8217;s instructions in a 96-well optical plate using 200 &#181;L of BCA mix per well. 
		NOTE: Other quantification methods such as Lowry and Bradford assays can also be used to determine protein concentration as long as protein concentration is quantified consistently across experiments.</li>
		<li>Prepare bovine serum albumin (BSA) standards at increasing concentrations in triplicate and add 1 &#181;L of each protein sample in duplicate. Incubate the 96-well plate in a preheated heat block at 60 &#176;C for 10 min or longer if the protein concentration is expected to be low.</li>
		<li>After incubation, measure the absorption at 560 nm using a plate reader.</li>
		<li>Export the plate reader measurements and calculate the protein concentration by comparing the average absorbance values of each sample to a standard curve obtained using the protein standard. The R-squared value for the standard curve should be greater than or equal to 0.98 to accurately estimate sample protein concentration.</li>
		<li>Normalize the amount of protein by preparing dilutions of protein samples in sample buffer and ultrapure water. The total volume can be adjusted depending on the type of gel used. Loading 30 &#181;g of protein per lane as a starting amount is recommended. Add reducing agent such as dithiothreitol (DTT; final concentration 5 mM) or beta-mercaptoethanol (final concentration 200 mM) to each sample as required. Pipette undiluted beta-mercaptoethanol in a fume hood.</li>
		<li>Incubate the samples in a heat block at 70 &#176;C for 10 min. Put the samples on ice, vortex and spin down briefly to collect. Keep on ice until loading the gel.</li>
	</ol>
	</li>
</ol>
2. Gel electrophoresis of protein samples
<ol>
	<li>Device and gel set up
	<ol>
		<li>Setup a precast 4&#8211;12% Bis-Tris gradient gel (see Table of Materials) in the gel electrophoresis chamber system. Rinse the gels using double-distilled water before use. 
		NOTE: Depending on the size, interactions and abundance of the protein of interest, gels with a different gradient, buffering agent or well size and number can be used.</li>
		<li>Add 500 mL of 1x MES SDS running buffer diluted in double-distilled water per tank. Carefully remove the comb from the gels after adding the running buffer without disturbing the wells in the stacking gel.</li>
	</ol>
	</li>
	<li>Protein loading
	<ol>
		<li>Load 3.5 &#181;L of a protein standard into the well. Depending on the sample layout, loading a protein ladder on both sides of the gel can aid in more accurately estimating protein size. Use fine-tipped gel loading tips for more accurate sample loading.</li>
		<li>When using an internal standard for between-membrane normalization (see step 5 below and discussion), load an amount that is equal to the other samples into the first 3 wells next to the protein ladder.</li>
		<li>Load 30 &#181;g of each sample in the remaining wells. Add 1x sample buffer to all empty wells.</li>
	</ol>
	</li>
	<li>Electrophoresis
	<ol>
		<li>Assemble the gel tank after loading the samples. Run the samples through the stacking gel at 80 V for 10 min followed by 150 V for an additional 45-60 min.</li>
	</ol>
	</li>
</ol>
3. Protein transfer
NOTE: Protein transfer in this protocol is performed using a commercially available semi-dry blotting system (see Table of Materials) for fast and consistent outcomes.
<ol>
	<li>Prepare the protein transfer by pre-soaking filter paper in double-distilled water and ensuring the gel knife, plastic Pasteur pipette, blotting roller and forceps are ready to use.</li>
	<li>Open the transfer stack by carefully removing all wrapping foil. Remove the top from the bottom stack and set it aside. Quickly moisten the membrane on the bottom stack with several drops of electrophoresis running buffer (2-3 mL). Once the transfer stack is open, it is important to prevent the PVDF membrane from drying out.</li>
	<li>After stopping the electrophoresis, open the pre-cast gel using the gel knife and cut off the stacking gel. Cut the gel around its edges to free it from the plastic cast. Keep the gel knife wet to prevent damage to the gel.</li>
	<li>Assemble the transfer stack from bottom to top: bottom stack (containing the PVDF membrane), protein gel, filter paper. Use the blotting roller to remove all air bubbles. Place the top stack on top of the filter paper and roll the stack again to remove air bubbles. Do not push too strongly as this may cause the gel to deform during protein transfer.</li>
	<li>Transfer the whole stack into the transfer device with the electrode on the left side of the device and place the gel sponge on top of the stack so that it is aligned with the corresponding electrical contacts on the device. Close the lid, select and start the appropriate program (20 V for 7 min is a recommended starting point).</li>
	<li>When finished, leave the lid closed for 2 min to allow the stack to cool down and to prevent the membrane from drying out. Remove the transfer stack and cut the membrane to the gel size. Wash the cut membrane quickly with double-distilled water before continuing with the total protein stain.</li>
</ol>
4. Total protein staining
NOTE: Using fluorescent detection provides a substantial benefit over more traditional approaches (e.g., ECL detection), as the linear range and sensitivity can be much better controlled4. Therefore, in steps 4 and 5, a fluorescent TPS and fluorescent secondary antibodies are used (see Table of Materials).
<ol>
	<li>Roll the membrane into a 50-mL tube with the protein side facing inwards. Because of light sensitivity of the fluorescent TPS and secondary antibodies, all subsequent steps are carried out in the dark.</li>
	<li>Add 5 mL of protein stain solution (see Table of Materials) and incubate on a roller for 5 min at room temperature. Because TPS and wash buffer contain methanol, carry these steps out in a fume hood.</li>
	<li>Discard the staining solution and wash twice quickly with the 5 mL of wash solution (6.3% acetic acid in 30% methanol). Place the tube briefly back on the roller between wash steps. Rinse the membrane briefly with ultrapure water before continuing.</li>
</ol>
5. Blocking, antibody incubation and detection
<ol>
	<li>Blocking the membrane: Add 3 mL of blocking buffer (see Table of Materials) to the 50 mL tube containing the membrane. Incubate the membrane on a roller for 30 min at room temperature. Depending on the choice of antibody, the type of blocking buffer used may require optimization.</li>
	<li>Primary antibody incubation
	<ol>
		<li>Discard the blocking buffer and replace with the primary antibody at the appropriate, optimized concentration (Figure 1 and Figure 2: mouse-anti-SMN, at 1:1,000, diluted in blocking buffer). 
		NOTE: Adequate optimization of primary antibodies should include confirmation that the antibody detects a protein product of the right size whilst showing no or minimal binding to other, unspecific protein products. If possible, test and compare multiple antibodies against the protein of interest.</li>
		<li>Incubate the membrane on a roller overnight at 4 &#176;C. The next day, remove the antibody solution and wash 6 times for 5 min with 1x PBS on a roller at room temperature (RT).</li>
	</ol>
	</li>
	<li>Secondary antibody incubation
	<ol>
		<li>Prepare the specific secondary antibody at 1:5,000 against the host of the primary antibody in 5 mL blocking buffer. Other secondary antibodies may require other dilutions or the use of alternative blocking buffers.</li>
		<li>Incubate the membrane with the secondary antibody solution on a roller for 1 h at RT. After incubation, wash the membrane three times 30 min with 1x PBS on a roller.</li>
		<li>Dry the membrane and keep the membrane protected from light using aluminum foil until detection. Membranes can be kept at 4 &#176;C for long term storage.</li>
	</ol>
	</li>
	<li>Image acquisition
	<ol>
		<li>Login to the computer attached to the scanner. Place the membrane on the scanner with the protein side facing down and select the scanning area in the software.</li>
		<li>Optimize the laser intensity for both (700 nm and 800 nm) channels, by confirming no saturation occurs. Acquire the images in both channels and export the images for further analysis (step 6).</li>
	</ol>
	</li>
</ol>
6. Western blot analysis and quantification
NOTE: These recommendations are based on the freely available Image Studio software. However, comparable analyses can also be done using other software packages, such as ImageJ.
<ol>
	<li>Import the file: Create a local workspace on the computer used for analysis. This generates a database of image files for acquired western blots. Import files obtained on the scanner and select the image for analysis.</li>
	<li>TPS analysis
	<ol>
		<li>Display the 700 nm channel to show the total protein staining result. An example of a TPS image is included in Figure 1 in which different tissues from neonatal (P5) (Figure 1A-B) and 10-week old mice (Figure 1C-D) are compared directly. Similarly, Figure 2 shows an example of a direct comparison of brain tissue from mice of different ages.</li>
		<li>Select Analysis tab from top right corner and select Add Rectangle to define the area of interest for normalization (Figure 1B, D). Copy and paste the first rectangle area onto each individual sample to ensure the defined region is at the same size for all analyzed lanes.</li>
		<li>Copy the result from the Shapes tab in the bottom left corner of the software.</li>
	</ol>
	</li>
	<li>Quantification 
	NOTE: The optimal approach for quantifying samples depends on the experimental design. We will here provide an illustrative example of the detection of the survival motor neuron protein (Smn; a key protein involved in the neuromuscular disease spinal muscular atrophy20,21), that is known to decrease over time19 and how normalization of Smn signal intensity to TPS provides reliable estimates of protein expression development.
	<ol>
		<li>Figure 2 shows a decrease of Smn expression with increasing age of the animal with TPS as protein loading control. Repeat Step 6.2.1-6.2.3 to quantify protein loading (Figure 2B). Repeat Step 6.2.1-6.2.3 in the 800 nm channel (Figure 2A) to analyze the protein of interest.</li>
		<li>Copy the results from both TPS and protein of interest to a spreadsheet program. On the spreadsheet, first normalize the protein loading by determining the highest TPS signal and dividing each TPS signal value by this value to obtain the normalized protein loading value.</li>
		<li>Divide the 800 nm signal value from each individual sample by its corresponding normalized protein value to calculate the relative protein expression ratio in different samples.</li>
		<li>After the first normalization, compare various time points or tissues to the average value of the internal standard to allow direct comparisons across different membranes and experiments.</li>
	</ol>
	</li>
</ol>
7. Statistics
<ol>
	<li>To determine any statistically significant differences in protein expression across complex and large groups of samples, appropriate statistical methodology is required. Although a detailed discussion of statistical background goes beyond the scope of this paper, we want to highlight several considerations and detail a successful approach that we have used previously19.</li>
	<li>As for many experiments, protein quantification measurements do not represent completely independent data. Here, for example, multiple tissues are generally obtained from single animals to determine protein levels across multiple organs at a single experimental time-point. Therefore, we used a mixed effects models to analyze differences in protein expression over time, and between tissues.&#160; In general, mixed effects models provide an effective means to deal with non-independence and thereby avoid pseudo-replication22,23. In the present case, mixed effects models increase statistical power by accounting for repeated measurements among tissues, within individuals. We use the statistical software package R to perform these analyses, as this is freely available and versatile. However, other commercially available packages may be able to perform similar analyses. &#160;</li>
	<li>The current experimental design involves a &#8220;split plot&#8221; design because each mouse belonged to only one age group. Therefore, we modeled individual mice (mouse ID) as a random effect with a unique identifier; we also accounted for tissue, age, and their interaction as fixed effects. We modeled the data using the function lmer in the R library, lme4. As a quality control step, we visualized residuals to assess the assumptions of equal variance and a normal distribution and transformed the data where necessary to meet these assumptions. To test for a significant interaction between tissue and age, we fit an identical model that lacked this interaction, and compared the models using parametric bootstrapping (R function PBmodcomp in the library, pbkrtest).&#160; Where significant interactions arose, we used the function emmeans (in the emmeans R library) to determine the cause of the interaction.&#160; For example, we compared mean expression among age classes within each tissue; a significant interaction may arise between age and tissue if, say, two given age classes differed significantly for one tissue but not another. In summary, these approaches provide a way to extend the robustness of conclusions from western blot experiments by providing statistical support to these results.</li>
</ol>

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The authors have no competing interests to disclose.

With the appropriate experimental design, control measures and statistical analysis, western blotting can be used to make reliable quantitative estimates of protein expression within and between a varied range of biological samples. The protocol we describe in the current manuscript aims to serve as a guideline for researchers looking to use Western blotting to undertake quantitative analysis across larger and more complex groups of samples, by using a combination of fluorescence-based detection methods, total protein lo...

Western blotting is a technique that is commonly used to detect and quantify protein expression, including in tissue homogenates or extracts. Over the years, this technique has led to many advances in both basic and clinical research, where it can be used as a diagnostic tool to identify the presence of disease1,2. Western blotting was first described in 1979 as a method to transfer proteins from polyacrylamide gels to nitrocellulose sheets and subsequently visualize proteins using secondary antibodies that were either radioactively labelled or conjugated to fluorescein or peroxidase3. Through the development of commercially available kits and equipment, Western blotting methods have been increasingly standardized and simplified over the years. Indeed, the technique is now readily performed by scientists with varying backgrounds and levels of experience. However, as with many similar experimental techniques, the outcome of Western blot analyses is easily influenced by choices made in the design and execution of the experiment. It is important, therefore, that the accessibility of standardized Western blotting methods does not obscure the need for careful experimental planning and design. Experimental considerations include, but are not limited to, sample preparation and handling, selection and validation of antibodies for protein detection, and gel-to-membrane transfer efficiency of particularly small or large (&#60;10 or &#62;140 kDa) proteins4,5,6,7,8,9. Protein quality of the original sample plays a significant role in determining the outcome of the subsequent Western blot analysis. As protein can be extracted from a wide variety of samples and sources, including cell lines, tissues from animal models, and post-mortem human tissues, consistency in handling and processing is required to obtain reproducible results. For example, when long-term storage of samples for protein extraction is required, it is important to realize that, although protein is generally stable at -80 &#176;C, differences in protein stability between extracted proteins and intact tissues at -80 &#176;C have been reported10. Moreover, to obtain reproducible estimates of protein quantities, consistent homogenization of samples is crucial. Optimizing different lysis buffers and homogenization methods (e.g., manual homogenization compared to automated methods) may be required before starting a large-scale quantitative experiment.
Normalization strategies to correct for protein loading and quantification variability are essential to obtain robust, quantitative results of protein expression. Housekeeping proteins such as &#946;-actin, &#945;-tubulin, &#946;-tubulin, and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) have traditionally been used to normalize protein levels for quantification. However, normalization to specific housekeeping proteins for quantification purposes has been increasingly criticized over the past few years11,12. For example, the expression of housekeeping proteins can change across different developmental stages13,14, across tissues from the same animal4, and under various disease conditions4,15,16,17. Therefore, the use of specific housekeeping proteins limits the possibilities of making more complex comparisons between protein expression from different tissues, at different timepoints and under varying experimental conditions. An alternative to housekeeping proteins to control for protein loading variation is the use of a total protein stain (TPS) that labels and visualizes all proteins present in a sample. TPS allows signal normalization based on total protein load rather than levels of one specific protein and therefore quantification of TPS signal should be comparable and reproducible regardless of experimental condition, sample type or developmental timepoint. Examples of total protein stains include Ponceau S, stain-free gels, Coomassie R-350, Sypro-Ruby, Epicocconone, Amydo Black, and Cy5 (reviewed in ref. 18). Each of these methods has specific advantages and limitations and method selection depends on the time and tools available as well as the experimental setup4,18.
In addition to using a TPS to correct for within-membrane loading and quantification variability, it may be necessary to compare samples between different membranes, particularly when performing large-scale protein expression analysis. However, variability in factors such as antibody binding efficiency and total protein stain intensity may introduce further variability between protein samples that are analyzed on separate gels and membranes. For robust quantification in this situation, it is therefore necessary to introduce a further normalization step to account for between-membrane variability. This can be achieved by including an internal loading standard on each of the separately analyzed membranes that is kept constant across experiments. This standard can take the form of any protein lysate that can be obtained in sufficient quantities to be used across all membranes included in the experiment. Here, we use a lysate of mouse brain (obtained from 5 day old control mice), as brain is readily homogenized and the obtained protein lysate contains a significant amount of protein at a high concentration. Loading an internal standard in triplicate allows samples on separate membranes to be normalized and compared directly.
Here, we describe a detailed protocol that we have developed to allow us to undertake complex comparisons of protein expression variation across different tissues, mouse models (including disease models), and developmental timepoints19. By combining a fluorescent TPS with the use of an internal loading standard, we were able to overcome existing limitations in the number of samples and experimental conditions that can be compared within a single experiment. This approach expands the use of traditional Western blot techniques, thereby allowing researchers to better explore protein expression across different tissues and samples.

<table>
	<tbody>
		<tr>
			<td>Fine Tipped Gel Loading Tips</td>
			<td>Alpha Laboratories</td>
			<td>GL20057SNTL</td>
			<td></td>
		</tr>
		<tr>
			<td>Halt Protease Inhibitor Cocktail, EDTA-free 100x 5mL</td>
			<td>ThermoFisher Scientific</td>
			<td>78437</td>
			<td></td>
		</tr>
		<tr>
			<td>Handheld homogeniser&#160;</td>
			<td>VWR Collection</td>
			<td>431-0100</td>
			<td></td>
		</tr>
		<tr>
			<td>iBlot 2 Gel Transfer Device</td>
			<td>ThermoFisher Scientific</td>
			<td>IB21001</td>
			<td></td>
		</tr>
		<tr>
			<td>iBlot Transfer Stack, PVDF, regular size</td>
			<td>ThermoFisher Scientific</td>
			<td>IB401031</td>
			<td></td>
		</tr>
		<tr>
			<td>Image Studio Lite</td>
			<td>Licor</td>
			<td>N/A</td>
			<td>Free download from https://www.licor.com/bio/products/software/image_studio_lite/</td>
		</tr>
		<tr>
			<td>IRDye 800CW secondary antibodies</td>
			<td>Licor</td>
			<td>--</td>
			<td>Select appropriate secondary antibody that is specific against host of primary antibody.</td>
		</tr>
		<tr>
			<td>Micro BCA Protein Assay Kit</td>
			<td>ThermoFisher Scientific</td>
			<td>23235</td>
			<td></td>
		</tr>
		<tr>
			<td>Novex Sharp Pre-stained Protein Standard</td>
			<td>ThermoFisher Scientific</td>
			<td>LC5800</td>
			<td></td>
		</tr>
		<tr>
			<td>NuPAGE 4-12% Bis-Tris Protein Gels, 1.0 mm, 15-well</td>
			<td>ThermoFisher Scientific</td>
			<td>NP0323BOX</td>
			<td></td>
		</tr>
		<tr>
			<td>NuPAGE LDS Sample Buffer (4X)</td>
			<td>ThermoFisher Scientific</td>
			<td>NP0007</td>
			<td></td>
		</tr>
		<tr>
			<td>NuPAGE MOPS SDS Running Buffer (20X)</td>
			<td>ThermoFisher Scientific</td>
			<td>NP0001</td>
			<td></td>
		</tr>
		<tr>
			<td>Odyssey Blocking Buffer</td>
			<td>Licor</td>
			<td>927-40000</td>
			<td></td>
		</tr>
		<tr>
			<td>Purified Mouse anti-SMN (survival motor neuron) monoclonal antibody</td>
			<td>BD Transduction Laboratories</td>
			<td>610646</td>
			<td>Is used extensively in the SMN/SMA literature and gives consistent results regardsless of lot number</td>
		</tr>
		<tr>
			<td>REVERT Total Protein Stain, 250 mL&#160;</td>
			<td>Licor</td>
			<td>926-11021&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>REVERT Wash Solution&#160;</td>
			<td>Licor</td>
			<td>926-11012&#160;</td>
			<td></td>
		</tr>
		<tr>
			<td>RIPA Lysis and Extraction Buffer</td>
			<td>ThermoFisher Scientific</td>
			<td>89900</td>
			<td></td>
		</tr>
		<tr>
			<td>XCell&#160;SureLock Mini-Cell</td>
			<td>ThermoFisher Scientific</td>
			<td>EI0001</td>
			<td></td>
		</tr>
	</tbody>
</table>

robust comparison of protein levels across tissues and throughout development using standardized quantitative western blotting

Western blotting is a technique that is commonly used to detect and quantify protein expression. Over the years, this technique has led to many advances in both basic and clinical research. However, as with many similar experimental techniques, the outcome of Western blot analyses is easily influenced by choices made in the design and execution of the experiment. Specific housekeeping proteins have traditionally been used to normalize protein levels for quantification, however, these have a number of limitations and have therefore been increasingly criticized over the past few years. Here, we describe a detailed protocol that we have developed to allow us to undertake complex comparisons of protein expression variation across different tissues, mouse models (including disease models), and developmental timepoints. By using a fluorescent total protein stain and introducing the use of an internal loading standard, it is possible to overcome existing limitations in the number of samples that can be compared within experiments and systematically compare protein levels across a range of experimental conditions. This approach expands the use of traditional western blot techniques, thereby allowing researchers to better explore protein expression across different tissues and samples.

We include examples of the use of TPS and an internal standard to facilitate comparisons of protein levels across tissues and time points. Figure 1 shows results from Western blotting on protein extracted from tissues obtained from neonatal (postnatal day 5) in comparison to adult mice (10-week old). TPS and Smn immunoblot are shown in Figure 1A, C. Quantification of fluorescence intensity of the TPS was achieved...

Watch this Scientific Journal Video about Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting at JoVE.com

Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting

This method describes a robust and reproducible approach for the comparison of protein levels in different tissues and at different developmental timepoints using a standardized quantitative western blotting approach.

Western blotting is a technique that is commonly used to detect and quantify protein expression. Over the years, this technique has led to many advances ...

robust-comparison-protein-levels-across-tissues-throughout

Research

JoVE Journal

Biochemistry

14.0K Views.  University of Edinburgh. This method describes a robust and reproducible approach for the comparison of protein levels in different tissues and at different developmental timepoints using a standardized quantitative western blotting approach.

Video: Robust Comparison of Protein Levels Across Tissues and Throughout Development Using Standardized Quantitative Western Blotting

Using Scaffold Liposomes to Reconstitute Lipid-proximal Protein-protein Interactions In Vitro

Studies of integral membrane proteins in vitro are frequently complicated by the presence of a hydrophobic transmembrane domain. Further complicating these studies, reincorporation of detergent-solubilized membrane proteins into liposomes is a stochastic process where protein topology is impossible to enforce. This paper offers an alternative method to these challenging techniques that utilizes a liposome-based scaffold. Protein solubility is enhanced by deletion of the transmembrane domain, and these amino acids are replaced with a tethering moiety, such as a His-tag. This tether interacts with an anchoring group (Ni2+ coordinated by nitrilotriacetic acid (NTA(Ni2+)) for His-tagged proteins), which enforces a uniform protein topology at the surface of the liposome. An example is presented wherein the interaction between Dynamin-related protein 1 (Drp1) with an integral membrane protein, Mitochondrial Fission Factor (Mff), was investigated using this scaffold liposome method. In this work, we have demonstrated the ability of Mff to efficiently recruit soluble Drp1 to the surface of liposomes, which stimulated its GTPase activity. Moreover, Drp1 was able to tubulate the Mff-decorated lipid template in the presence of specific lipids. This example demonstrates the effectiveness of scaffold liposomes using structural and functional assays and highlights the role of Mff in regulating Drp1 activity.

Using Scaffold Liposomes to Reconstitute Lipid-proximal Protein-protein Interactions In Vitro

This paper describes a method for assessing the interactions and assemblies of integral membrane proteins in vitro with various partner factors in a lipid-proximal environment.

Studies of integral membrane proteins in vitro are frequently complicated by the presence of a hydrophobic transmembrane domain. Further complicating ...

SorLA and CLC:CLF-1-dependent Downregulation of CNTFR&#945; as Demonstrated by Western Blotting, Inhibition of Lysosomal Enzymes, and Immunocytochemistry

The heterodimeric cytokine Cardiotrophin-like Cytokine:Cytokine-like Factor-1 (CLC:CLF-1) targets the glycosylphosphatidylinositol (GPI)-anchored CNTFR&#945; to form a trimeric complex that subsequently recruits glycoprotein 130/Leukemia Inhibitory Factor Receptor-&#946; (gp130/LIFR&#946;) for signaling. Both CLC and CNTFR&#945; are necessary for signaling but so far CLF-1 has only been known as a putative facilitator of CLC secretion. However, it has recently been shown that CLF-1 contains three binding sites: one for CLC; one for CNTFR&#945; (that may promote assembly of the trimeric complex); and one for the endocytic receptor sorLA. The latter site provides high affinity binding of CLF-1, CLC:CLF-1, as well as the trimeric (CLC:CLF-1:CNTFR&#945;) complex to sorLA, and in sorLA-expressing cells the soluble ligands CLF-1 and CLC:CLF-1 are rapidly taken up and internalized. In cells co-expressing CNTFR&#945; and sorLA, CNTFR&#945; first binds CLC:CLF-1 to form a membrane-associated trimeric complex, but it also connects to sorLA via the free sorLA-binding site in CLF-1. As a result, CNTFR&#945;, which has no capacity for endocytosis on its own, is tugged along and internalized by the sorLA-mediated endocytosis of CLC:CLF-1.
The present protocol describes the experimental procedures used to demonstrate i) the sorLA-mediated and CLC:CLF-1-dependent downregulation of surface-membrane CNTFR&#945; expression; ii) sorLA-mediated endocytosis and lysosomal targeting of CNTFR&#945;; and iii) the lowered cellular response to CLC:CLF-1-stimulation upon sorLA-mediated downregulation of CNTFR&#945;.

The present protocol describes how Western blotting and immunocytochemistry combined with inhibition of lysosomal enzymes can be used to demonstrate the downregulation of Ciliary Neurotrophic Factor Receptor-&#945; (CNTFR&#945;), which is conveyed by the interaction between Cytokine-like Factor-1 (CLF-1) and the endocytic receptor sorLA.

The heterodimeric cytokine Cardiotrophin-like Cytokine:Cytokine-like Factor-1 (CLC:CLF-1) targets the glycosylphosphatidylinositol (GPI)-anchored ...

Enhanced Sample Multiplexing of Tissues Using Combined Precursor Isotopic Labeling and Isobaric Tagging (cPILOT)

There is an increasing demand to analyze many biological samples for disease understanding and biomarker discovery. Quantitative proteomics strategies that allow simultaneous measurement of multiple samples have become widespread and greatly reduce experimental costs and times. Our laboratory developed a technique called combined precursor isotopic labeling and isobaric tagging (cPILOT), which enhances sample multiplexing of traditional isotopic labeling or isobaric tagging approaches. Global cPILOT can be applied to samples originating from cells, tissues, bodily fluids, or whole organisms and gives information on relative protein abundances across different sample conditions. cPILOT works by 1) using low pH buffer conditions to selectively dimethylate peptide N-termini and 2) using high pH buffer conditions to label primary amines of lysine residues with commercially-available isobaric reagents (see Table of Materials/Reagents). The degree of sample multiplexing available is dependent on the number of precursor labels used and the isobaric tagging reagent. Here, we present a 12-plex analysis using light and heavy dimethylation combined with six-plex isobaric reagents to analyze 12 samples from mouse tissues in a single analysis. Enhanced multiplexing is helpful for reducing experimental time and cost and more importantly, allowing comparison across many sample conditions (biological replicates, disease stage, drug treatments, genotypes, or longitudinal time-points) with less experimental bias and error. In this work, the global cPILOT approach is used to analyze brain, heart, and liver tissues across biological replicates from an Alzheimer&#39;s disease mouse model and wild-type controls. Global cPILOT can be applied to study other biological processes and adapted to increase sample multiplexing to greater than 20 samples.

Enhanced Sample Multiplexing of Tissues Using Combined Precursor Isotopic Labeling and Isobaric Tagging cPILOT

Combined precursor isotopic labeling and isobaric tagging (cPILOT) is a quantitative proteomics strategy that enhances sample multiplexing capabilities of isobaric tags. This protocol describes the application of cPILOT to tissues from an Alzheimer's disease mouse model and wild-type controls.

There is an increasing demand to analyze many biological samples for disease understanding and biomarker discovery. Quantitative proteomics strategies ...

A Western Blotting Protocol for Small Numbers of Hematopoietic Stem Cells

Hematopoietic stem cells (HSCs) are rare cells, with the mouse bone marrow containing only ~25,000 phenotypic long term repopulating HSCs. A Western blotting protocol was optimized and suitable for the analysis of small numbers of HSCs (500 - 15,000 cells). Phenotypic HSCs were purified, accurately counted, and directly lysed in Laemmli sample buffer. Lysates containing equal numbers of cells were analyzed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), and the blot was prepared and processed following standard Western blotting protocols. Using this protocol, 2,000 - 5,000 HSCs can be routinely analyzed, and in some cases data can be obtained from as few as 500 cells, compared to the 20,000 to 40,000 cells reported in most publications. This protocol should be generally applicable to other hematopoietic cells, and enables the routine analysis of small numbers of cells using standard laboratory procedures.

A standard Western blotting protocol was optimized for analyzing as few as 500 hematopoietic stem or progenitor cells. Optimization involves careful handling of the cell sample, limiting transfers between tubes, and directly lysing the cells in Laemmli sample buffer.

Hematopoietic stem cells (HSCs) are rare cells, with the mouse bone marrow containing only ~25,000 phenotypic long term repopulating HSCs. A Western ...

High Throughput, Absolute Determination of the Content of a Selected Protein at Tissue Levels Using Quantitative Dot Blot Analysis (QDB)

Lacking a convenient, quantitative, high throughput immunoblot method for absolute determination of the content of a specific protein at cellular and tissue level significantly hampers the progress in proteomic research. Results derived from currently available immunoblot techniques are also relative, preventing any efforts to combine independent studies with a large-scale analysis of protein samples. In this study, we demonstrate the process of quantitative dot blot analysis (QDB) to achieve absolute quantification in a high throughput format. Using a commercially available protein standard, we are able to determine the absolute content of capping actin protein, gelsolin-like (CAPG) in protein samples prepared from three different mouse tissues (kidney, spleen, and prostate) together with a detailed explanation of the experimental details. We propose the QDB analysis as a convenient, quantitative, high throughput immunoblot method of absolute quantification of individual proteins at the cellular and tissue level. This method will substantially aid biomarker validation and pathway verification in various areas of biological and biomedical research.

High Throughput, Absolute Determination of the Content of a Selected Protein at Tissue Levels Using Quantitative Dot Blot Analysis QDB

Here we demonstrate a detailed process of quantitative dot blot analysis (QDB) by determining the absolute content of a targeted protein, capping actin protein, gelsolin-like (CAPG), in three different mouse tissues. We demonstrate a high throughput, convenient, quantitative immunoblot technique for biomarker validation at the cellular and tissue level.

Lacking a convenient, quantitative, high throughput immunoblot method for absolute determination of the content of a specific protein at cellular and ...

A11-positive &#946;-amyloid Oligomer Preparation and Assessment Using Dot Blotting Analysis

&#946;-amyloid (A&#946;) is a hydrophobic peptide with an intrinsic tendency to self-assemble into aggregates. Among various aggregates, A&#946; oligomer is widely accepted as the leading neurotoxin in the progress of Alzheimer&#39;s disease (AD) and is considered to be the crucial event in the pathogenesis of AD. Therefore, A&#946; oligomer inhibitors might prevent neurodegeneration and have the potential to be developed as disease-modifying treatments of AD. However, different formation protocols of A&#946; oligomer might lead to oligomers with different characteristics. Moreover, there are not many methods to effectively screen A&#946;1-42 oligomer inhibitors. An A11 antibody can react with a subset of toxic A&#946;1-42 oligomer with anti-parallel &#946;-sheet structures. In this protocol, we describe how to prepare an A11-positive A&#946;1-42 oligomer-rich sample from a synthetic A&#946;1-42 peptide in vitro and to evaluate relative amounts of A11-positive A&#946;1-42 oligomer in samples by a dot blotting analysis using A11 and A&#946;1-42-specific 6E10 antibodies. Using this protocol, inhibitors of A11-positive A&#946;1-42 oligomer can also be screened from semi-quantitative experimental results.

This protocol describes how to prepare A&#946; oligomers from a synthetic peptide in vitro and to evaluate relative amounts of A&#946; oligomer by a dot blotting analysis.

&#946;-amyloid (A&#946;) is a hydrophobic peptide with an intrinsic tendency to self-assemble into aggregates. Among various aggregates, A&#946; oligomer ...

High Sensitivity Measurement of Transcription Factor-DNA Binding Affinities by Competitive Titration Using Fluorescence Microscopy

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing approaches suffer from significant limitations, we have developed a new method for determining TF-DNA binding affinities with high sensitivity on a large scale. The assay relies on the established fluorescence anisotropy (FA) principle but introduces important technical improvements. First, we measure a full FA competitive titration curve in a single well by incorporating TF and a fluorescently labeled reference DNA in a porous agarose gel matrix. Unlabeled DNA oligomer is loaded on the top as a competitor and, through diffusion, forms a spatio-temporal gradient. The resulting FA gradient is then read out using a customized epifluorescence microscope setup. This improved setup greatly increases the sensitivity of FA signal detection, allowing both weak and strong binding to be reliably quantified, even for molecules of similar molecular weights. In this fashion, we can measure one titration curve per well of a multi-well plate, and through a fitting procedure, we can extract both the absolute dissociation constant (KD) and active protein concentration. By testing all single-point mutation variants of a given consensus binding sequence, we can survey the entire binding specificity landscape of a TF, typically on a single plate. The resulting position weight matrices (PWMs) outperform those derived from other methods in predicting in vivo TF occupancy. Here, we present a detailed guide for implementing HiP-FA on a conventional automated fluorescent microscope and the data analysis pipeline.

Here we present a novel method for determining binding affinities at equilibrium and in solution with high sensitivity on a large scale. This improves the quantitative analysis of transcription factor-DNA binding. The method is based on automated fluorescence anisotropy measurements in a controlled delivery system.

Accurate quantification of transcription factor (TF)-DNA interactions is essential for understanding the regulation of gene expression. Since existing ...

Identification of Functional Protein Regions Through Chimeric Protein Construction

The goal of this protocol encompasses the design of chimeric proteins in which distinct regions of a protein are replaced by their corresponding sequences in a structurally similar protein, in order to determine the functional importance of these regions. Such chimeras are generated by means of a nested PCR protocol using overlapping DNA fragments and adequately designed primers, followed by their expression within a mammalian system to ensure native secondary structure and post-translational modifications. 
The functional role of a distinct region is then indicated by a loss of activity of the chimera in an appropriate readout assay. In consequence, regions harboring a set of critical amino acids are identified, which can be further screened by complementary techniques (e.g. site-directed mutagenesis) to increase molecular resolution. Although limited to cases in which a structurally related protein with differing functions can be found, chimeric proteins have been successfully employed to identify critical binding regions in proteins such as cytokines and cytokine receptors. This method is particularly suitable in cases in which the protein's functional regions are not well defined, and constitutes a valuable first step in directed evolution approaches to narrow down the regions of interest and reduce the screening effort involved.

Structurally related proteins frequently exert distinct biological functions. The exchange of equivalent regions of these proteins in order to create chimeric proteins constitutes an innovative approach to identify critical protein regions that are responsible for their functional divergence.

The goal of this protocol encompasses the design of chimeric proteins in which distinct regions of a protein are replaced by their corresponding sequences ...

Characterization at the Molecular Level using Robust Biochemical Approaches of a New Kinase Protein

Extensive whole genome sequencing has identified many Open Reading Frames (ORFs) providing many potential proteins. These proteins may have important roles for the cell and may unravel new cellular processes. Among proteins, kinases are major actors as they belong to cell signaling pathways and have the ability to switch on or off many processes crucial to the fate of the cell, such as cell growth, division, differentiation, motility, and death.
In this study, we focused on a new potential kinase protein, LIMK2-1. We demonstrated its existence by Western Blot using a specific antibody. We evaluated its interaction with an upstream regulating protein using coimmunoprecipitation experiments. Coimmunoprecipitation is a very powerful technique able to detect the interaction between two target proteins. It may also be used to detect new partners of a bait protein. The bait protein may be purified either via a tag engineered to its sequence or via an antibody specifically targeting it. These protein complexes may then be separated by SDS-PAGE (Sodium Dodecyl Sulfate PolyAcrylamide Gel) and identified using mass spectrometry. Immunoprecipitated LIMK2-1 was also used to test its kinase activity in vitro by &#947;[32P] ATP labeling. This well-established assay may use many different substrates, and mutated versions of the bait may be used to assess the role of specific residues. The effects of pharmacological agents may also be evaluated since this technique is both highly sensitive and quantitative. Nonetheless, radioactivity handling requires particular caution. Kinase activity may also be assessed with specific antibodies targeting the phospho group of the modified amino acid. These kinds of antibodies are not commercially available for all the phospho modified residues.

We characterized a new kinase protein using robust biochemical approaches: Western Blot analysis with a dedicated specific antibody on different cell lines and tissues, interactions by coimmunoprecipitation experiments, kinase activity detected by Western Blot using a phospho-specific antibody and by &#947;[32P] ATP labeling.

Extensive whole genome sequencing has identified many Open Reading Frames (ORFs) providing many potential proteins. These proteins may have important ...

Use of Microscale Thermophoresis to Measure Protein-Lipid Interactions

The ability to determine the binding affinity of lipids to proteins is an essential part of understanding protein-lipid interactions in membrane trafficking, signal transduction and cytoskeletal remodeling. Classic tools for measuring such interactions include surface plasmon resonance (SPR) and isothermal titration calorimetry (ITC). While powerful tools, these approaches have setbacks. ITC requires large amounts of purified protein as well as lipids, which can be costly and difficult to produce. Furthermore, ITC as well as SPR are very time consuming, which could add significantly to the cost of performing these experiments. One way to bypass these restrictions is to use the relatively new technique of microscale thermophoresis (MST). MST is fast and cost effective using small amounts of sample to obtain a saturation curve for a given binding event. There currently are two types of MST systems available. One type of MST requires labeling with a fluorophore in the blue or red spectrum. The second system relies on the intrinsic fluorescence of aromatic amino acids in the UV range. Both systems detect the movement of molecules in response to localized induction of heat from an infrared laser. Each approach has its advantages and disadvantages. Label-free MST can use untagged native proteins; however, many analytes, including pharmaceuticals, fluoresce in the UV range, which can interfere with determination of accurate KD values. In comparison, labeled MST allows for a greater diversity of measurable pairwise interactions utilizing fluorescently labeled probes attached to ligands with measurable absorbances in the visible range as opposed to UV, limiting the potential for interfering signals from analytes.

Microscale thermophoresis obtains binding constants quickly at low material cost. Either labeled or label free microscale thermophoresis is commercially available; however, label free thermophoresis is not capable of the diversity of interaction measurements that can be performed using fluorescent labels. We provide a protocol for labeled thermophoresis measurements.