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Question about total protein normalisation in western blot image analysis

Question about total protein normalisation in western blot image analysis



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I am analysing western blot data and I am using total protein normalisation using Ponceau S. My supervisor and I have agreed to use total protein normalisation for my western blots instead of using housekeeping proteins such as Beta-actin and GAPDH, due to the fact that studies have shown that housekeeping proteins levels differ between experimental groups, and during different developmental phases. I've also read literature where single protein loading controls were compared with total protein stains and it was found that the total protein stains lead to more reproducible and accurate quantification.

When quantifying Ponceau S staining, I have seen in multiple papers that they outline the entire lane, and measure its integrated density. However, I have two western blots, so I am analysing two Ponceau-stained membrane images. In one image of my Ponceau-stained membrane, there are bubbles which obscure parts of the top and sides of some of the lanes. So I cannot outline the entire lane when doing quantification. My supervisor has advised me that I should instead outline a band on the lane corresponding to where my protein of interest is, and use that for normalisation. I have also seen in a paper they outline a small rectangular section of the lane when doing total protein normalisation instead of the whole lane.

However, I don't understand how total protein in each sample can be quantified if one is outlining only a portion of the lane. If you're outlining only a rectangular band on the lane, you are only measuring a portion of the total protein in the sample. As a result, you are not normalising against the total protein in the sample. I was wondering if anyone knows what the reasoning is behind outlining a portion of the lane when doing normalisation with total protein stains?


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Defining the New Normal in Quantitative Western Blot Data

Do you know that journals like the JBC strongly caution against the use of housekeeping proteins for normalization? Most journals now demand rigorous standards for presentation of western blotting data. While housekeeping proteins (HKP) have traditionally been used for decades, the problems with their usage have come to the fore only recently. More validation is required for presenting data using HKP. Normalization using total proteins present in the sample has gained significant traction and has proved to be a reliable method for normalization of western blots. Here we illustrate why the total protein normalization (TPN) method is superior and the way to go for western blotting.

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Total Protein Normalization

Total protein normalization (TPN) is a technique that can be used to quantify the abundance of the protein of interest without relying on housekeeping genes. Traditionally, TPN is performed by incubating the membrane with a total protein stain, either before or after detection with antibodies. The abundance of the protein of interest is normalized to the total amount of protein in each lane, removing variations associated with comparing abundance to a single protein. TPN is also more compatible with detecting proteins of lower abundance.

Normalization with total protein stains can be complex and time-consuming. While some stains can be used prior to immunodetection, others are incompatible with downstream antibody detection. In addition, some stains fade quickly making it difficult to document the results. A newer technique, called the stain-free approach, increases the sensitivity and reduces the complexity while saving time.

Total protein stains

Total protein stains bind to all proteins on a Western blot membrane and provide a visual image after transfer. Depending on the type of stain, total protein stains can be used either prior to or after immunodetection. Some of the more common stains are described below.

Pre-Antibody Stains

Anionic dyes, such as Ponceau S, and fluorescent dyes, like Sypro Ruby, Deep Purple and AdvanStain Scarlet are common stains used prior to antibody staining.

Ponceau S

Ponceau S is rapid and economical. Proteins stain red after just 5 minutes of incubation. The dye is easily removed after visualization by incubation in PBS or wash buffer. Although Ponceau S has no effect on downstream immunodetection, the intensity of the staining decreases quickly over time, making it difficult to capture an image. The red bands can also be difficult to photograph.

Fluorescent stains

Although more expensive and time-consuming than Ponceau S, fluorescent stains are highly sensitive, permanent, total protein stains that can also be used prior to antibody detection. Several companies sell fluorescent stains that have limits of detection ranging from 1.0 ng-8.0 ng. The stains are long-lasting and photostable, enabling long exposure times. Most stains can be excited with either UV or visible light and require a fluorescent imager for detection. Staining can be documented on photographic film or with a CCD camera. The staining procedure can take 30 minutes – 1 hours, depending on the stain.

Note: Some stains contain heavy metals, which require special disposal procedures.

Post-Antibody Stain

Amido black

Amido black is a commonly used permanent post-antibody anionic stain. Although not as sensitive as a fluorescent stain, it is more sensitive than Ponceau S and does not require special equipment for visualization. It is also more economical than fluorescent stains. The bright black bands are easy to document.

Colloidal Gold

Colloidal gold particles can be used as a total protein stain. When incubated with proteins bound to a membrane, the gold adsorbs to the proteins through electrostatic interactions resulting in a transient, reddish-pink color. The sensitivity can be enhanced through sliver enhancement, which results in a stable dark brown signal and detection of protein down to 1 ng. Colloidal gold staining is more expensive than other methods and cannot be used with downstream immunodetection.

Stain-free

Stain-free total protein detection is rapid and sensitive. The technology uses a trihalo compound that is directly incorporated into the gel. Upon UV exposure, the compound modifies tryptophan residues in proteins causing them to fluoresce. The fluorescent signal can be detected by a CCD camera. Proteins can be visualized in the gel prior to transfer and after transfer on the membrane. Stain-free detection does not interfere with downstream immunodetection. Pre-cast gels stain-free gels can be purchased or stain free gels can be made in the lab by mixing a trihalo compound with acrylamide. Stain-free technology cannot detect proteins that do not contain tryptophans and it is recommended that a protein contain at least 2 tryptophans to be readily detected.


Stain-Free technology as a normalization tool in Western blot analysis.

Western blots are used to specifically measure the relative quantities of proteins of interest in complex biological samples. Quantitative measurements can be subject to error due to process inconsistencies such as uneven protein transfer to the membrane. These non-sample-related variations need to be compensated for by an approach known as normalization. Two approaches to data normalization are commonly employed: housekeeping protein (HKP) normalization and total protein normalization (TPN). In this study, we evaluated the performance of Stain-Free technology as a novel TPN tool for Western blotting experiments in comparison with glyceraldehyde-3-phosphate dehydrogenase (GAPDH) as a representative of the HKP normalization strategy. The target protein (TP) used for this study was MCM7, a DNA licensing replication factor, which was shown previously to be down-regulated by 20% in irradiated lymphoblastoid cell lines (LCLs). We studied the regulation of MCM7 with a multiplex Western blotting approach based on fluorescently labeled secondary antibodies and found that Stain-Free technology appears to be more reliable, more robust, and more sensitive to small effects of protein regulation when compared with HKP normalization with GAPDH. Stain-Free technology offers the additional advantages of providing checkpoints throughout the Western blotting process by allowing rapid visualization of gel separation and protein transfer.


DISCUSSION

In general, the three weekly lab modules fit nicely together and formed a logical sequence in helping students to learn and understand the techniques of electrophoresis, Western blotting, immunodetection, and tissue printing. During the process, they also learned how to extract qualitative (i.e., relative abundance of Rubisco and its tissue distribution) and quantitative (i.e., molecular mass estimation of Rubisco large subunit) information from the results through image analysis and mathematical manipulation and to build connections between these results and what they represent in plant tissues. Postlab responses indicated that 80% of the students reported improved understanding of the lab techniques (Figure 4). Because each lab module focused on one technique, students had sufficient time to become familiar with each set of protocols during the lab period. The lapse of one week in between each lab session required students to recall essential background information and objectives of what they attempted to achieve in the previous lab to see the logic of continuity throughout. This repetition helped strengthen the retention of important concepts they learned each step of the way, as evidenced by improved performance on their postlab compared with prelab surveys (Table 2).

Students often experienced difficulty with math in the calculation of molecular mass of the Rubisco. They were instructed to enter the measured migration distances of the molecular mass markers and the molecular mass values into the Excel spreadsheet, plot the distance against the logarithm of the molecular mass of the marker proteins, find the trend-line in the form of a linear equation [i.e., Y (migration distance) = k × log (molecular mass) + b], get the R 2 value, and see how well the equation describes the log-linear relationship. They then calculated the molecular mass of the large subunits of Rubisco for various plant samples by entering into the equation the migration distance of the Rubisco, and solving for the molecular mass. The struggle often occurred at the last step of solving for molecular mass from the equation of log (molecular mass) = known value, the answer of which is obtained by converting to the exponential function (i.e., molecular mass = e raised to the power of the known value). In addition, students showed varied proficiency in data processing with Excel. Many students were preoccupied with using a handheld calculator to process data, until they saw the ease and speed of repetitive calculation in the spreadsheet and learned how to use mathematical functions and create charts in Excel to visually present experimental data. This 3-wk lab module was the last one among a few other labs in which students had an opportunity to learn the use of Excel. Fifty-one percent of students reported that they became more comfortable using a spreadsheet, whereas 26% had a neutral response, and 12% expressed difficulty with Excel (Figure 4). We believe that helping students in applying math to analyze biological data and in the transition from using a calculator to the more sophisticated data-processing software is an added benefit to students' learning experience, an aspect in undergraduate biology education that was recommended by the National Research Council (2003).

The tissue printing module offered an enjoyable lab experience for nearly 60% of students, and 52% of students enjoyed working with plants (Figure 4). Celery, the plant material used for the prints, is readily available and hardy to handle. Each student in a group was encouraged to make a print, with multiple prints made on each piece of nitrocellulose membrane this increased the chance of getting a successful print. The physical mapping and visualization of protein distribution in tissues from tissue prints proved to be exciting for half of all the students.

One potential problem with these procedures was the downtime during the longer steps in the procedure. A strategy we applied to use these incubation times was for students to analyze, interpret, and discuss their data collected in the previous lab module. Students were also encouraged to conduct literature searches on the nutritional value and medicinal use of celery, and required to observe and record the anatomy of celery petioles under a dissecting scope. In one of the instructors' three lab sections, students discussed and debated their prediction on the tissue location of Rubisco, and whether young and mature petioles would differ in Rubisco content. They generally agreed that they would see Rubisco in the green epidermal tissue but were surprised to see its presence in the inner vascular tissue as well. They disagreed over possible differences in Rubisco content between young and older petioles, citing growth rate difference and location of young versus older stalks relative to each other within a bundle and whether the light source could be a contributing factor. Although the tissue prints they generated did not answer all of these questions equally well, they clearly benefited from this inquiry-based approach.

Student learning of the lecture material and their understanding of lab techniques benefited significantly from the hands-on activities in the lab. In addition to the significantly enhanced postlab survey performance on questions specifically related to the three lab modules reported here (Table 2), students scored well on two other lecture topics that were also associated with lab exercises. However, they did not show improvement in knowledge on another photosynthetically important enzyme (i.e., phosphoenolpyruvate carboxylase) that was either addressed in the lecture or included in the text reading assignment, but to which no lab activity was devoted (Table 2, concurrent lecture topics).

The development of a good assessment questionnaire requires much care and skill to avoid potential problems. The survey questions we developed were of multiple-choice format and can be considered to be a generally effective and reliable measurement of student learning overall however, we found it important to exclude inclusive correct answers in the form of “all of the above,” which increased the chance of student guessing the correct answer and risked greater bias in student assessment (Table 2, questions 10 and 17). Still, remedy is possible for more in-depth analysis and insight into student response to questions with such answers by including a follow-up question that probes students' confidence in their response.

In examining students' ability to apply the techniques they learned, we found that although there was improvement in student knowledge on how the techniques might be applied beyond the class studies, it was a relatively small gain compared with understanding the technical details and facts of the particular molecule under study (Table 2, application vs. other categories). Considering that most of our students did not have more advanced knowledge in biochemistry, organic chemistry, or both, we believe that their ability to apply or transfer a technical approach beyond the immediate experience will be improved as they gain more knowledge on the physical and chemical properties of biological molecules from other course work.

In summary, the results of the assessment surveys show that we achieved the stated learning objectives of each of the lab modules, and we believe that they can be applied or modified as a feasible and beneficial introductory cell biology lab exercise for undergraduates in learning important cell biology techniques and their potential applications.


The Design of a Quantitative Western Blot Experiment

Western blotting is a technique that has been in practice for more than three decades that began as a means of detecting a protein target in a complex sample. Although there have been significant advances in both the imaging and reagent technologies to improve sensitivity, dynamic range of detection, and the applicability of multiplexed target detection, the basic technique has remained essentially unchanged. In the past, western blotting was used simply to detect a specific target protein in a complex mixture, but now journal editors and reviewers are requesting the quantitative interpretation of western blot data in terms of fold changes in protein expression between samples. The calculations are based on the differential densitometry of the associated chemiluminescent and/or fluorescent signals from the blots and this now requires a fundamental shift in the experimental methodology, acquisition, and interpretation of the data. We have recently published an updated approach to produce quantitative densitometric data from western blots (Taylor et al., 2013) and here we summarize the complete western blot workflow with a focus on sample preparation and data analysis for quantitative western blotting.

1. Introduction

Proteomic technologies such as two-dimensional electrophoresis and mass spectrometry are valuable tools in semiquantitative protein profiling studies in order to identify broad expression patterns enabling a better understanding of molecular events, signaling pathways and mechanisms [1]. The resulting data are typically confirmed by a second, independent method such as western blotting. Western blotting was introduced by Towbin et al. [2] in 1979 and has since become a common technique used in research laboratories globally for the immunodetection and quantitation of specific proteins in complex cell homogenates. Over the past three decades, the sensitivity, robustness, and flexibility of the corresponding indicator systems have increased significantly [3, 4]. In addition, the ongoing development of detection media and reagents has provided the scientific community with ultrasensitive imaging systems giving broad dynamic range of detection enabling precise and accurate quantitation of signals from both low and high expressing proteins from the same blot. Although labs have been quick to purchase the latest detection technologies and reagents for western blotting, the associated techniques used to produce the densitometric data have not evolved leading to published data that are difficult or impossible to interpret or reproduce [5–7].

In order to obtain quantitative data from western blots, a rigorous methodology must be used as previously described [8]. Briefly, the validation of antibodies (Ab) is critical both to assure that the Ab/antigen interaction is specific and correct and to determine the dilution factor of samples that is required for protein loading in the quantitative linear dynamic range for each antibody. Furthermore, the appropriate selection of normalization method (based on reference signals obtained either by housekeeping proteins (HKPs) after immunochemical staining or total protein (TP) intensity on blotting membranes after total protein staining) must be considered to assure that the reported fold changes of the target protein are not an artifact of reference signal. Thus, data normalization is crucial to identify and correct experimental errors where reference instability becomes increasingly important with the measurement of smaller differences in target protein expression between samples [9]. The direct effect of poor normalization is evident when sample loading above 10 μg of a total protein lysate per lane is required because traditional loading HKPs such as GAPDH, actin, and tubulin are grossly overloaded and therefore not serving the purpose of data normalization [8, 9]. Also, these HKPs can be affected by the treatment conditions of the experiment giving skewed results for target protein expression that do not reflect the biology of the tested samples [10–15]. Alternatively, normalization by total, blot-transferred protein has recently been shown to give excellent data for typical total protein lysates [16].

Here, we describe some general techniques to produce good quality protein samples with minimal degradation for improved reproducibility between experiments. Also summarized are the basic steps of quantitative western blotting and a standardized approach to calculating the associated densitometric data from multiple blots.

2. Careful Experimental Design Produces Reliable and Reproducible Data

Unlike DNA-based assays that measure a predictable type of molecule that is typically stable in a variety of conditions, proteins can vary significantly in their expression, stability, conformation, and activity under different buffer and experimental conditions. Furthermore, the presence of contaminating proteins in a homogenate can greatly affect the integrity and activity of target proteins [17]. Care must therefore be taken in the design of any protein-based assay to ensure that the apparent differences between case and control samples are not an artifact of the experimental conditions or sample handling. Factors that can have a major influence on the proteome include incubation time and temperature, as well as the parameters for processing samples such as the amount of time between tissue collection and subsequent freezing or even the conditions and timing for thawing tissue or cell pellets (Table 1).

Experiment procedureControl groupsReplicatesExperiment conditionsSample handling
Disease or treatment groupsTime course study (i.e.,

3. Sample Preparation

There are several pitfalls associated with sample preparation that can directly affect the density of bands on a western blot including: (1) improper handling of tissue or cell specimens resulting in variable degradation and/or expression of proteins between samples, (2) inadequate detergents, salts, and protease inhibitors in the lysis buffer, (3) poor homogenization technique.

Since protein lysates are highly complex with contaminants such as cellular or tissue debris, fats, hydrophobic protein aggregates, nucleic acids, and proteases that can directly and negatively affect the results from western blots, it is important to use cell lysis buffers and homogenization techniques that eliminate their effects [17]. In general, homogenization buffers containing nonionic detergents such as NP-40 and Triton X-100 are less harsh than ionic detergents, such as SDS and sodium deoxycholate. Salts such as NaCl or KCl are typically added to a concentration of 100 to 150 mM to prevent protein aggregation. RIPA buffer (1% NP-40 or Triton X-100, 1% sodium deoxycholate, 0.1% SDS, 150 mM NaCl, 50 mM Tris-HCl, pH 7.8, 1 mM EDTA) and complete mini protease inhibitor cocktail tablets (Roche Applied Science) in combination with either mechanical or manual homogenization instruments have been used to produce homogenates that give solid data for western blot assays.

The proper choice of tissue homogenization technique is a prerequisite for a successful western blot assay and the method employed entirely depends on the sample type (i.e., brain versus muscle versus liver tissue as opposed to plated or suspended cells) [18, 19]. A good example of a tissue lysis protocol is as follows: (1) Snap-freeze the tissue in liquid nitrogen and then dice tissue into 1 mm pieces with a scalpel in a mortar on dry ice. Ensure that the scalpel or grinder is also frozen on dry ice to keep the cut or ground tissue close to the temperature of dry ice throughout the procedure. (2) Add the diced/ground tissue to ice-cold RIPA buffer. (3) Transfer the tissue preparation to an ice-cold Dounce tissue homogenizer (Wheaton) and Dounce 25x on ice. (4) Sonicate (Tekmar Sonic Disrupter) the Dounce-homogenized tissue on ice for

seconds at 50% power and clear the extracts by centrifugation at 34,000 ×g at 4°C for 30 minutes. (5) Transfer the supernatant to a new tube and perform protein assay (see below). (6) Store the supernatants at −80°C or in liquid nitrogen for long term storage.

For cell lysis, add the pelleted cells (in the case of cell suspensions) to ice-cold RIPA buffer or for plated cells, add the ice-cold RIPA buffer directly to the plate after washing the cells, and scrape and pipette the cells up and down. Continue with step (3) above.

The total protein concentration of the homogenate from either cell or tissue lysates should be measured using a detergent compatible protein assay such as the RC DC protein assay from Bio-Rad. Ideally, the homogenates would be diluted to a concentration of at least 2 mg/mL which would permit loading between 10 μg and 80 μg per lane of a 1 mm thick mini polyacrylamide SDS-gel.

4. Determine the Linear Dynamic Range of Protein Loading

Most labs load a random amount of protein in each lane of a gel for western blotting that is typically between 10 μg and 100 μg of total lysate and there is typically no scientific basis for choosing this amount. This often results in the overloading of highly expressed, target proteins and particularly the loading controls that are used to normalize the data. This typically gives uniform band densities between lanes for the housekeeping proteins which is not due to consistent protein loading but rather from overloading the membrane with the target protein (Figure 1). To alleviate the effect of membrane saturation, a standard curve of protein load versus band density should be produced for each target protein. This can be accomplished by making a 1/2 dilution series of a pooled sample from all the lysates in the study group starting from 100 μg protein load over at least 12 dilutions on a TGX stain-free SDS-gel (Bio-Rad). Stain-free detection on the ChemiDoc MP (Bio-Rad) camera system can be used to verify the loading, quality, and separation of the homogenate followed by transfer to a low fluorescent PVDF membrane using the Trans Blot Turbo (Bio-Rad) protein transfer system [8].


Reliable western blot data can only be generated when the proper sample amount of protein is used. Loading too much protein leads to signal saturation in western blots, yet too little produces weak signals. Once the experimental setup and conditions are established for the assay, do not change the sample load, transfer method, transfer time, antibody dilution, antibody incubation time, or temperature in subsequent experiments as these factors may significantly change the detection signals.

A typical methodology for determination of the appropriate loading for protein samples follows: (1) Transfer and blot accordingly by incubating the target protein primary antibody and associated secondary to each blot with at least four, 3-minute wash steps between each incubation. (2) Add an imager-compatible, chemiluminescence substrate such as Clarity (Bio-Rad) to develop the immunochemical signal and capture the signal using a CCD-camera-based imager such as the ChemiDoc MP (Bio-Rad). (3) Image the blots using software that provides accurate, background-subtracted densitometric tools such as Image Lab (Bio-Rad) and produce a plot of relative density versus fold dilution for each primary antibody. (4) Validate the antibodies by determining their linear dynamic range (i.e., the range in which a consistent, 1/2 decrease in density is obtained). (5) Select the protein load for each antibody that corresponds to the middle of the linear dynamic range.

Dilution of the individual samples in the study group to the middle point in the linear dynamic range of the pooled sample for each antibody may mean that the individual protein samples require widely different dilutions for each antibody. This will assure that the densitometric data for each target protein will be within the linear dynamic (quantitative) range to give accurate and reproducible results reflecting the true biology between samples in the study set (Figure 2). Inappropriate loading of samples may result in no quantifiable difference between the samples for a given target simply due to overloading the membrane.


(From [9] with permission from the authors and Bio-Rad.) Linearity comparison of stain-free total protein measurement and immunodetection of three housekeeping proteins in 10–50 μg of HeLa cell lysate. On the left are representative images of (a), stain-free blot and the chemi blots for (b), β-actin (c), β-tubulin and (d), GAPDH. Lane labels correspond to total protein load (μg). Although the actin and tubulin signals appear linear, the densitometric ratio was far below the predicted “quantitative response” of actual loading whereas the stain-free signal correlated to the expected result (e).

5. Determine the Appropriate Reference Signal for Data Normalization

A good reference signal or “loading control” is one that is coexpressed with the target protein within the same sample and consistently expressed between samples. HKPs such as tubulin, β-actin, and GAPDH have traditionally served as loading controls, but there are three potential drawbacks to using such controls. (1) HKPs may not be expressed in a uniform manner between the experimental conditions which will give erroneous results [10–15]. The same issue has been found with reference genes used for qPCR where the selection of unstable targets has led to opposite results when contrasted with stable targets [20, 21]. (2) HKPs are highly abundant in lysates and have typically saturated the membrane for samples loaded in excess of about 4 μg per lane (see previous section) (Figure 2). This would give these proteins the “appearance” of good normalization controls because the densities of the associated bands would all be similar between lanes as an “artifact” of membrane saturation. (3) Data normalization with HKPs relies only on one data point and provides a poor reflection of possible process inconsistencies.

Given the problems that arise with HKP controls, alternative methods for normalization have been sought out by the scientific community and we propose that an excellent loading control (LC) should meet the following criteria. (1) It has good responsiveness (1 : 1) to changes in total protein amount of individual samples. (2) It is insensitive to the influence of various physiological conditions and treatments and therefore must be quantified from the membrane itself to take into account the effect of transfer efficiency [22, 23]. (3) Acquisition of the LC would ideally be possible at all phases of the western blot process (i.e., visualization of protein on the pretransfer gel lanes, posttransfer blot, and posttransfer gel lanes) thus enabling a consistent process control. (4) Acquisition of the LC must be fast, easy, and highly reproducible. (5) No lengthy process should be required for the optimization and establishment of LC. (6) The method for LC detection should be compatible with immunochemical staining.

To address these issues, the scientific community is now adopting the use of total lane density from the blot-transferred protein as a means of data normalization [24–26]. There are a number of stains that can be used to visualize, image, and quantify the transferred protein on the blot including Ponceau S, Coomassie R-350, Amido Black, MemCode, and Deep Purple. However, each of these stains has individual issues of being poorly reproducible on a day-to-day basis, limited dynamic range, and restricted compatibility with blotting membranes and immunochemical staining [25]. More recently the Stain-Free technology (Bio-Rad) has been introduced [24–26] and meets all six of the criteria mentioned above for a good LC with a linear dynamic range between about 10 and 80 μg of total protein load from a typical cell or tissue lysate [8, 9]. This permits the use of total lane density from the stain-free blot for normalization between lanes for most western blot studies.

The technique for total lane normalization using the stain-free assay technology has been well-described but briefly it is as follows: (a) The quality of the electrophoretic separation can be verified within a couple of minutes. After UV-activation, the protein bands are visible in the gel and can be recorded with a camera system. The generated fluorescent signal remains stable over a couple of hours. (b) The blot is imaged immediately after transfer to verify the transfer of protein from each lane. (c) The image data from the total density of all the blot-transferred protein bands per lane is then recorded using Image Lab software by selecting a single band in each lane and stretching the band width to cover all the volume peaks in the lane profile. (d) The background rolling disc is adjusted to a low value (between 1 and 5) for all the lanes to assure that only the total background subtracted density from the sum of all the bands per lane is acquired for normalization.

In addition, Stain-Free technology is compatible with both nitrocellulose and PVDF membranes and data normalization with SF blot images is based on many data points which is superior to HKPs.

6. Data Analysis: The Background Subtraction Problem

Background subtraction is a common reason to obtain variable or incorrect data from western blots [27]. Using traditional densitometric analysis methods such as volume analysis from boxed bands and background, variations in background-subtracted data can arise since the background is not subtracted from the same box in which the band resides. Furthermore, the box in which a band is selected always contains density from both the band and the associated background which becomes more prevalent with low density bands [8]. The combination of these factors can result in highly variable data when testing samples with a differentially expressed target protein using a nonspecific antibody with high background. A good alternative to volume analysis using boxes is a rolling disc background subtraction algorithm coupled with a lane profile tool (Figure 3). Image Lab software is designed with both of these tools that can be used simultaneously to ensure that the appropriate band width and lane background is selected for each lane (Figure 3).


(From [8] with permission from the authors and Bio-Rad.) Image acquisition and densitometric analysis. Image Lab software version 5.0 (Bio-Rad) was used for image acquisition and densitometric analysis of the gels, blots, and film in this study. The software interprets the raw data in three dimensions with the length and width of the band defined by the “Lanes and Bands” tool in concert with the “Lane Profile” tool such that the chemiluminescent signal emitted from the blot is registered in the third dimension as a peak rising out of the blot surface. The density of a given band was measured as the total volume under the three-dimensional peak, which could be viewed in two dimensions using the “Lane Profile” tool to adjust the precise width of the band to account for the area under the shaded peak of interest. Background subtraction was set by using the rolling disc setting in the “Lanes” tool. The rolling disc values were set such that the background was subtracted under the band (i.e., peak) of interest in a uniform manner between the lanes of a given blot. In this case, the rolling disc for the two lanes analyzed was set to 18 and 25, respectively, such that the peaks of interest were cut at a consistent level between the markers shown with an “X”.

7. Computational Analysis of Densitometric Data

There are numerous calculations from densitometric data using formulas buried in EXCEL spreadsheets spanning multiple worksheets and files to obtain quantitative data from western blots. It is often difficult to follow the basis of the calculations and we have found that when lab members are faced with the direct question of how to work up the raw data obtained from western blots to publishable results, there is often confusion. The analysis of western blot data can be accomplished using a very similar methodology to qPCR by calculating relative, normalized protein expression as described in the following steps (Tables 2 and 3). (1) For each blot, multiply the background subtracted density (volume in Image Lab software) of the target protein (TP) in each lane by the ratio of density of the loading control (LC) (either housekeeping protein or total lane density) from a control sample loaded into lane 1 of all the study blots to the other lanes in the gel. This will give the normalized density to the loading control (NDL) (Table 2). The control sample is typically a pooled homogenate from all of the samples in a given study aliquoted into multiple tubes to permit the loading of a fresh control sample in lane 1 of each study blot. (2) Calculate the fold difference (FD) for each biological/technical replicate by dividing NDL from each lane by the NDL from the control sample in lane 1 (Table 2). (3) Determine the average FD and associated

values for the biological replicates by importing the FD from step (2) above into a statistical analysis software package such a PRISM or Analyze IT (Table 3).


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  • No fixing, microwaving, or washing
  • Aqueous-based and non-toxic for drain disposal
One-Step Blue® is an alternative to time consuming Coomassie® staining, for fast and easy visible staining (left) or near-infrared imaging in the LI-COR® Odyssey® 800 channel (right). Red fluorescent One-Step Lumitein™ is an alternative to time-consuming and expensive SYPRO® Ruby protein gel stain, and it can be imaged on a UV box or fluorescence gel scanner Red fluorescent One-Step Lumitein™ UV Protein Gel Stain is designed for imaging using a UV transilluminator. Unlike Oriole™ Gel Stain it does not contain hazardous solvents and does not cause gel shrinkage.

Product Information

ProductReplacement forCatalog numberUnit sizeProduct protocolSafety report
One-Step Blue®
Coomassie stain21003-1L1LPI-21003
One-Step Gel Stains Safety Report
One-Step Lumitein™SYPRO® Ruby Protein Gel Stain21004-1L1LPI-21004
21004-4L4L
One-Step Lumitein™ UVOriole™ and Flamingo™ Protein Gel Stains21005-1L1LPI-21005
21005-4L4L

Lumitein and its related technologies are covered by US and international patents. SYPRO is a registered trademark of Molecular Probes, Inc. Oriole is a trademark of Bio-Rad Laboratories. Coomassie is a registered trademark of Imperial Chemical Industries.

VersaBlot™ Total Protein Normalization Kits

VersaBlot™ Total Protein Normalization Kits allow simple, sensitive and highly linear protein quantitation on SDS-PAGE gels and western blot membranes. The kits allow you to label purified proteins or cell lysates with our near-infrared CF® dyes before running the samples on SDS-PAGE. Proteins can then be visualized on a gel or membrane using a fluorescent gel scanner, allowing detection of as little as 1 ng protein per band. If desired, the prestain can be reversed after scanning, facilitating downstream multi-color western blot analysis. The staining demonstrates excellent linearity for quantitation of total protein over a wide dynamic range, outperforming traditional western blot normalization based on housekeeping protein detection.

VersaBlot™ Total Protein Prestain Features

  • Reversible prestain for downstream multi-color western blot analysis
  • Superior linearity for western normalization compared to housekeeping proteins
  • Highly sensitive protein quantitation on PAGE gels or western membranes
  • Fast and simple labeling of proteins or lysates, no purification required
  • Detect as little as 1 ng protein and 10% difference in protein content
In-gel fluorescence image of bovine serum albumin (BSA) labeled with the VersaBlot™ total protein normalization kit on SDS-PAGE gel. Protein content for each lane ranges from 10 ug to 1 ng, from left to right. The bands above and below the major bands are from impurity proteins in the BSA sample. The excess dye runs to the very bottom of the gel. Inset: part of the image with enhanced brightness to visualize the bands with 10, 5, and 1 ng of BSA. VersaBlot™ total protein normalization kits for western blot normalization. HeLa cell lysate in serial dilution was labeled with (A) the CF®770T total protein prestain before SDS-PAGE and transfer to PVDF, or (B) mouse anti-tubulin primary antibody and CF®770T goat anti-mouse secondary antibody after transfer to PVDF. (C) Plots of band intensity vs protein content for CF®770T labeled lysate (shown in A), CF®680T labeled lysate (membrane not shown), and tubulin WB (shown in B). The VersaBlot™ total protein normalization kits show better linearity compared to housekeeping protein detection.

Product Information

ProductCatalog numberSizeAbs/EmImaging Systems / Detection channels
VersaBlot™ CF®680T Total Protein Normalization Kit
33025-T100 labelings681 / 698 nmAmersham Typhoon™ Trio Cy®5 channel
Amersham Typhoon™ 5 IR short channel
LI-COR® Odyssey® 700 channel
33025500 labelings
VersaBlot™ CF®770T Total Protein Normalization Kit33026-T100 labelings764 / 787 nmAmersham Typhoon™ 5 IR long channel
LI-COR® Odyssey® 800 channel
33026500 labelings

Typhoon is a trademark and Cy dye is a registered trademark of GE Healthcare Odyssey is a registered trademark of LI-COR Biosciences.

GloMelt™ Protein Thermal Stability Assay

Thermal shift assay for protein stability

The thermal shift assay, also called Protein Thermal Shift™, differential scanning fluorimetry, or Thermofluor assay, is a simple technique for measuring protein denaturation temperature. It can be used to screen conditions that affect protein thermal stability, such as mutations, ligand binding, and buffer formulations. The assay is rapid and is performed on a quantitative PCR system. Thermal shift is compatible with high throughput screening and requires much less protein than methods like circular dichroism and differential scanning calorimetry.

Environmentally sensitive fluorescent dyes can be used to monitor the temperature dependent unfolding of a protein. The protein’s melting temperature (Tm) is a reporter of the protein’s thermal stability.

GloMelt™ Dye for protein thermal stability

GloMelt™ dye undergoes fluorescence enhancement upon binding to hydrophobic regions of denatured proteins, and can be used to detect protein unfolding in thermal shift assay. GloMelt™ dye is optimized for detection in the SYBR® Green channel, so it generates much stronger signal than SYPRO® Orange and PROTEOSTAT® TS dyes, which have spectra that are not well-matched to common qPCR fluorescence channels. Because GloMelt™ has green fluorescence, it also can be used with ROX normalization for improved replicate consistency.

GloMelt™ tolerates a wide variety of common stabilizers and destabilizers, and unlike SYPRO® Orange, it performs well in the presence of detergents. SYPRO® Orange and PROTEOSTAT® TS dyes are highly hydrophobic, so after dilution in buffer the dyes must be used immediately. In contrast, GloMelt™ has excellent water solubility, allowing storage of diluted dye solutions for greater convenience and less wasted dye.

GloMelt™ Features

  • Green fluorescence optimal for qPCR instruments and ROX normalization
  • Compatible with high detergent concentrations
  • Compatible with wide pH range, reducing agents, and common buffers/excipients
  • Great for high throughput assays, low reaction volumes and low protein concentrations
  • Highly soluble and stable in aqueous buffers
GloMelt™ has much better detergent tolerance than SYPRO® Orange. IgG melt curve plots in the presence of detergent. A thermal shift assay was performed on 20 ug IgG in the presence of 5X SYPRO® Orange or 1X GloMelt™ dye, using a QuantStudio™ 5 qPCR system. The presence of detergent inhibited the SYPRO® Orange assay, but had little affect on the GloMelt™ curve. GloMelt™ tolerates reducing agents, unlike PROTEOSTAT® TS. IgG melt curve plots in the presence of DTT. A thermal shift assay was performed on 25 ug IgG in the presence of 1X PROTEOSTAT® TS dye or 1X GloMelt™ dye, using a QuantStudio™ 5 qPCR system. The presence of DTT drastically reduced the sensitivity of the PROTEOSTAT® assay, but had little affect on the GloMelt™ dye. As expected, DTT reduced IgG thermal stability. Normalization of GloMelt™ signal to ROX reference dye can improve results by increasing replicate consistency. A thermal shift assay was performed on 20 ug IgG in the presence 1X GloMelt™ dye and 50 nM ROX. After ROX normalization the standard deviation was reduced more than 5-fold.

Product Information

ProductKit contentsCatalog numberSize*
GloMelt™ Kit&bull GloMelt™ Dye
&bull Goat IgG Control
33021-T200 reactions
33021-12000 reactions
GloMelt™ Kit with ROX&bull GloMelt™ Dye
&bull Goat IgG Control
&bull ROX Reference Dye
33022-T200 reactions
33022-12000 reactions
* Size based on 20 uL reaction volume

SYPRO is a registered trademark of Thermo Fisher Scientific Protein Thermal Shift and QuantStudio are trademarks of Thermo Fisher Scientific PROTEOSTAT is a registered trademark of Enzo Life Sciences.

AccuOrange™ Fluorescent Protein Quantitation Assay

AccuOrange™ Protein Quantitation Kit is a highly sensitive fluorescence-based assay for quantitating purified protein or antibody samples in 96-well format. The detection range of the assay is 0.1-15 ug/mL protein. AccuOrange™ is much more sensitive than traditional protein quantitation assays such as BCA, Bradford and Lowry, and is more linearity and reproducible compared to the NanoOrange® protein quantitation assay. The assay shows minimal variability between different proteins, and has stable fluorescence signal for up to 16 hours. The AccuOrange™ assay has low tolerance for detergents, and is not recommended for use with cell lysates.

The AccuOrange™ fluorescent protein quantitation assay is more linear and less variable than the NanoOrange® assay.

AssayDetection RangeComments
AccuOrange™0.1-15 ug/mLFluorescence-based (480/598 nm)
Highly linear
Signal stable for at least 16 hours
Compatible with reducing agents
Not compatible with detergents
NanoOrange®0.1-10 ug/mLFluorescence-based (470/570 nm)
Non-linear
Fluorescence stable for 6 hours
Compatible with reducing agents
Not compatible with detergents
Modified Lowry1-1500 ug/mLAbsorbance-based (750 nm)
Non-linear
Not compatible with reducing agents or detergents
BCA20-2000 ug/mLAbsorbance-based (562 nm)
Highly linear
Signal not stable over time
Not compatible with reducing agents
Compatible with detergents
Bradford (Coomassie®)50-500 ug/mLAbsorbance-based (595 nm)
Signal not stable over time
Non-linear
Compatible with reducing agents
Not compatible with detergents
Pierce® 660 nm50-2000 ug/mLAbsorbance-based (660 nm)
Non-linear
Compatible with reducing agents & detergents
A28050-2000 ug/mLAbsorbance-based (280 nm)
High protein-protein variability
Contaminants and detergents can affect results

Product Information

ProductCatalog numberSizeFeatures
AccuOrange™ Protein Quantitation Kit30071-T200 assays&bull Highly sensitive: detect 0.1-15 ug/mL protein
&bull Excellent linearity and low variability
&bull Stable fluorescence signal
&bull Compatible with reducing agents and other additivies
&bull For use with purified protein or antibody samples
300711000 assays

NanoOrange is a registered trademark and Pierce is a trademark of Thermo Fisher Scientific Coomassie is a registered trademark of Imperial Chemical Industries.

Conjugates and accessories for western blotting

Near-infrared (near-IR) western detection is highly sensitive, and offers advantages of wider linear range and multiplexing capability compared to chemiluminscence detection (see our webinar to learn more). Biotium’s near-IR CF® dyes are the brightest and most photostable available. Learn more about CF®680 and CF®770 dyes for near-IR western, In Cell Western®, and other applications.

We offer wide selection of primary and secondary antibodies conjugated to our exceptional near-IR CF® dyes for western blot, as well as HRP conjugates for chemiluminescence detection. Also see below for our selection of protein markers, buffers, blocking agents, and more for western blotting.

CF® dye conjugates are brighter than IRDye® conjugates for near-infrared western blotting. A dilution series of HeLa cell lysate (from 2 ug to 0.125 ug) was transferred to PVDF membranes. Mouse anti-tubulin and rabbit anti-COX IV antibodies were detected using CF®680 anti-mouse and CF®770 anti-rabbit, or the corresponding IRDye® conjugates, and scanned on LI-COR® Odyssey®. Band quantitation showed

50% brighter signal with CF® dyes. M: marker.

Peacock™ and Peacock™ Plus Prestained Protein Markers on 10% Bis-Tris MES gels, labeled with apparent molecular weights of the bands.

Principle

Western blotting (protein blotting or immunoblotting) is a rapid and sensitive assay for detection and characterization of proteins. It is based on the principle of immunochromatography where proteins are separated into polyacrylamide gel according to their molecular weight.

The protein thus separated are then transferred or electrotransferred onto nitrocellulose membrane and are detected using specific primary antibody and secondary enzyme labeled antibody and substrate.


References

Alexander SPH, Roberts RE, Broughton BRS, Sobey CG, George CH, Stanford SC, et al. Goals and practicalities of immunoblotting and immunohistochemistry: a guide for submission to the British. Br J Pharmacol. 2018175:407–11.

Uhlen M, Bandrowski A, Carr S, Edwards A, Ellenberg J, Lundberg E, et al. A proposal for validation of antibodies. Nat Methods. 201613:823–7.

Vigelso A, Dybboe R, Hansen CN, Dela F, Helge JW, Guadalupe Grau A. GAPDH and beta-actin protein decreases with aging, making stain-free technology a superior loading control in Western blotting of human skeletal muscle. J Appl Physiol. 2015118:386–94.

Greer S, Honeywell R, Geletu M, Arulanandam R, Raptis L. Housekeeping genes expression levels may change with density of cultured cells. J Immunol Methods. 2010355:76–9.

Thacker JS, Yeung DH, Staines WR, Mielke JG. Total protein or high-abundance protein: which offers the best loading control for Western blotting? Anal Biochem. 2016496:76–8.

Luo S, Wehr NB, Levine RL. Quantitation of protein on gels and blots by infrared fluorescence of coomassie blue and fast green. Anal Biochem. 2006350:233–8.

Liu X, Fagotto F. A method to separate nuclear, cytosolic, and membrane-associated signaling molecules in cultured cells. Sci Signal. 20114:pl2.


Acknowledgments

The authors thank Dr. Nicole Davis for implementing this laboratory exercise in her biochemistry laboratory course. The authors also thank the Armstrong State University College of Science and Technology for their support through Summer Research Session Grants. This work was further supported by the National Science Foundation's STEP Program under Award No. DUE-0856593. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Additional Supporting Information may be found in the online version of this article.

Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.


Watch the video: Western Blot. Protein Immunoblot explained (August 2022).