Article Category: Odyssey Imaging Systems

Create a Customized List of Journal Articles that Reference LI-COR Imaging Systems

Finding out how other researchers have used LI-COR® imaging systems and reagents can really help when you are trying to decide on which system is best for your lab. With over 10,000 journal citations, the Odyssey® Imaging Systems have a long, proven track record in life science research.

There is now a tool that you can use to customize a list of peer-reviewed references specific to your research and application interests. You can access this new Publications Database through pages on our website, such as Products > Imaging System pages (for example, Odyssey CLx > Who’s Using it) and Application pages (for example, Quantitative Western Blots > Publications) or through the link in the footer, which is on the bottom of all web pages.

You can filter results by four categories. Select at least one filter. Each filter you select narrows the search by making the resulting set a combination of all filter parameters.

Let’s go over the various options you can use to create your customized publications list.

You can filter by Research Area. The list of research areas includes 72 different categories. Choose a single, or multiple, area(s). Remember, the more you choose, the narrower your search will be.

You can filter by Instrument.

You can filter by Application.

You can filter by Country. This is the country of the corresponding author’s email address.

For example, if you select “Apoptosis” in Research Area, “Odyssey CLx” in Instrument, and “Germany” in Country, you will receive a list of three publications that specifically reference apoptosis, the Odyssey CLx, and publications where the corresponding author is from Germany.

You can sort the columns in the results by clicking on the corresponding header. You can also show 10, 25, 50, or all entries. If the list does not suit your needs, you can Clear All Filters and start over.

If the number of publications returned is large, you can refine the set using keywords, such as your protein or disease of interest, separated by a space. Results displayed will contain all the terms in the search field. You can also use the digital object identifier (DOI) prefix unique to each publishing group to search for publications in specific journals. For example, use 10.1074 for the Journal of Biological Chemistry and other ASBMB journals.

We regularly add publications to the database, so check back frequently to see who is using LI-COR imaging systems to get published, and how they are using the instrument in their research.

Create your own customized publication list and, if you have feedback on how to improve this tool, please click on the Feedback button and let us know!

Technical and Biological Replicates are Critical for Quantitative Western Blot Success

Replicates improve the reproducibility and accuracy of experimental findings. They are important because they confirm the validity of observed changes in protein levels. Without replication, it is impossible to know if an effect is real or simply an artifact of experimental noise or variation, which can directly affect conclusions made about experimental findings.

There are two types of replicates: biological and technical. Each type addresses different questions1,2,3. Peer-reviewed journals, such as the Journal of Biological Chemistry, have specific guidelines in regards to replicates.

“Authors must state the number of independent samples (biological replications) and the number of replicate samples (technical replicates) and report how many times each experiment was repeated.”
Instructions for Authors. The Journal of Biological Chemistry

Technical vs. Biological Replicates: Which Do You Need to Include?

Technical Replicates

Technical replicates are repeated measurements used to establish the variability of a protocol or assay, and determine if an experimental effect is large enough to be reliably distinguished from the assay noise1. Examples may include loading multiple lanes with each sample on the same blot, running multiple blots in parallel, or repeating the blot with the same samples on different days.

Figure 1. Technical replicates help identify variation in technique. For example, lysate derived from a mouse and treated under a set of experimental conditions (A, B, C), then run and measured independently three times, will help identify variation in technique.

Technical replicates evaluate the precision and reproducibility of an assay, to determine if the observed effect can be reliably measured. When technical replicates are highly variable, it is more difficult to separate the observed effect from the assay variation. You may need to identify and reduce sources of error in your protocol to increase the precision of your assay.

Technical replicates do not address the biological relevance of the results.

Biological Replicates

Biological replicates are parallel measurements of biologically distinct and independently generated samples, used to control for biological variation and determine if the experimental effect is biologically relevant. The effect should be reproducibly observed in independent biological samples. Demonstration of a similar effect in another biological context or system can provide further confirmation. Examples include analysis of samples from multiple mice rather than a single mouse, or from multiple batches of independently cultured and treated cells.

Figure 2. Biological replicates derived from independent samples help capture random biological variation. For example, lysates derived from 3 mice and treated under the same set of experimental conditions (A, B, C), will help identify variation resulting from the biology.

To demonstrate the same effect in a different experimental context, the experiment might be repeated in multiple cell lines, in related cell types or tissues, or with other biological systems.

An appropriate replication strategy should be developed for each experimental context. Several recent papers discuss considerations for choosing technical and biological replicates1,2,3.

This protocol, Quantitative Western Blot Analysis with Replicates, will guide you in choosing and incorporating technical and biological replicates in your experimental design for reproducible data. It includes calculations for replicate analysis as well as how to interpret the data you obtain.

Additional Resources to Help You Get the Best Data

LI-COR has additional resources that you can use as you plan your quantitative Western blot strategy.


  1. Naegle K, Gough NR, Yaffe MB. Criteria for biological reproducibility: what does “n” mean? Sci Signal. 8 (371): fs7 (2015).
  2. Blainey P, Krzywinski M, Altman N. Replication: quality is often more important than quantity. Nat Meth. 11(9): 879-80 (2014).
  3. Vaux DL, Fidler F, Cumming G. Replicates and repeats – what is the difference and is it significant? EMBO reports 13(4): 291-96 (2012).

Tracing the Footsteps of the Data Reproducibility Crisis

Have you found it challenging to replicate the results of your own or somebody else’s experiments? You are not alone. A member survey conducted by the American Society for Cell Biology (ASCB) revealed that out of 869 respondents, 72% had trouble reproducing the findings of at least one publication1. In a more comprehensive study by the Nature Publishing Group, over 60% and 70% of researchers surveyed in medicine and biology, respectively, reported failure in replicating other researchers’ results2. And out of the 1,576 scientists surveyed in various fields, 90% agreed that there is a reproducibility crisis in scientific literature2.

In case you are wondering, both surveys were conducted between 2014 and 2015, and there is a growing consensus about data reproducibility challenges. But how did we get here?

Beginnings of a Crisis

In 2011, scientists at Bayer HealthCare in Germany published an article in Nature Reviews Drug Discovery, reporting inconsistencies between published data and in-house target validation studies3. Out of the 67 target identification and validation projects they had analyzed for data reproducibility, 43 had shown inconsistencies and had resulted in the termination of projects3. Through this review, the Bayer researchers attempted to raise awareness about the challenges in reproducing published data and called for confirmatory studies prior to investing in downstream drug development projects3.

Close on the heels of Bayer’s report, researchers at Amgen described their attempts at replicating the results of published oncology studies, in a 2012 Nature commentary4. While reporting success at confirming the findings of only 6 out of the 53 landmark publications reviewed, the Amgen scientists outlined recommendations to improve replicability of pre-clinical studies4.

These publications spurred data reproducibility conversations within the biomedical research community, giving way to a wave of initiatives to analyze and address the problem.

Data Reproducibility Gaining Momentum

Reproducibility of research data depends, in part, on the specific materials used in the experiment. But how often are research reagents referenced in sufficient detail? A study found that 54% of resources reported in publications, including model organisms, antibodies, reagents, constructs, and cell lines, were not uniquely identifiable5. In order to promote proper reporting of research materials used, the NIH has recommended that journals expand or eliminate the limits on the length of methods sections17.

When you had challenges reproducing data in your lab, were you able to identify what caused them? In another publication, study design, biological reagents and reference materials, laboratory protocols, and data analysis and reporting were attributed as the four primary causes of experimental irreproducibility6. In effect, an estimated 50% of the U.S. preclinical research budget, or $28 billion a year, was reportedly being spent on data that is not reproducible6.

Based on feedback from researchers in academia, biopharmaceutical companies, journal editors, and funding agency personnel, the Global Biological Standards Institute (GBSI) developed a report highlighting the need for a standards framework in life sciences7.

Changes Instituted by Granting Agencies and Policy Makers

In the face of data reproducibility challenges, government agencies that fund research, including the National Institutes of Health (NIH) and National Science Foundation (NSF) developed action plans to improve the reproducibility of research8,9. The NIH also revised criteria for grant applications8. That means researchers will need to report details of experimental design, biological variables, and authenticate research materials when applying for grants8.

The Academy of Medical Sciences (UK), the German Research Foundation (DFG), and the InterAcademy Partnership for Health (IAP for Health) identified specific activities to improve reproducibility of published data10,11,12.

Recommendations on Use of Standards, Best Practices, and Reagent Validation

Among the organizations championing the development of standards and best practices to improve the reproducibility of biomedical research are:

  • Federation of American Societies for Experimental Biology (FASEB) with recommendations regarding the use of mouse models and antibodies13
  • American Statistical Association’s (ASA) report on statistical analysis best practices when publishing data14
  • Global Biological Standards Institute with recommendations regarding the additional standards in life science research; antibody validation and cell line authentication groups in partnership with life science vendors, academia, industry, and journal publishers15
  • Science Exchange’s efforts at validation of experimental results16

Changes to Publication Guidelines

Journal groups have been revising author instructions and publication policies to encourage scientists to publish data that is robust and replicable. That means important changes regarding reporting of study design, replicates, statistical analyses, reagent identification and validation, are coming your way.

  • The NIH and journal publishing groups including Nature, Science, Cell, Journal of Biological Chemistry, Journal of Cell Biology, and Public Library of Science (PLOS), among others, have developed and endorsed principles and guidelines for reporting preclinical research. These guidelines include statistical analysis, transparency in reporting, data and material sharing, refutations, screening for image-based data (e.g. Western blots) and unique identification of research resources (antibodies, cell lines, animals)17
  • The Center for Open Science (COS) developed Transparency and Openness Promotion (TOP) guidelines framework for journal publishers. Signatories include journal publication groups like AAAS, ASCB, Biomed Central, F1000, Frontiers, Nature, PLOS, Springer, and Wiley, among others18

Emphasis on Training

To train scientists in proper study design and data analysis, the NIH has developed training courses and modules19. A number of universities also offer courses in study design and statistics20.

In the face of revisions to grant applications and publication guidelines, use of standards, reagent validation, and need for consistent training in methods and technique, changes are coming your way. Is your lab prepared? Let us help you get there. See what has changed for publishing Western blot data and get your entire lab trained to generate consistent and reproducible Western blot data at Lambda U™.


  1. How Can Scientists Enhance Rigor in Conducting Basic Research and Reporting Research Results? American Society for Cell Biology. Web. Accessed October 6, 2017.
  2. Baker M. 1,500 scientists lift the lid on reproducibility. Nature (News Feature) 533, 452-454.
  3. Prinz F, Schlange T, Asadullah K. 2011. Believe it or not: how much can we rely on published data on potential drug targets? Nat Rev Drug Discov 10, 712-713. doi:10.1038/nrd3439-c1
  4. Begley GC, Ellis LM. 2012. Drug development: Raise standards for preclinical cancer research. Nature 483, 531-533. doi:10.1038/483531a
  5. Vasilevsky NA, Brush MH, Paddock H, et al. On the reproducibility of science: unique identification of research resources in the biomedical literature. Abdullah J, ed. PeerJ. 2013;1:e148. doi:10.7717/peerj.148.
  6. Freedman LP, Cockburn IM, Simcoe TS (2015). The Economics of Reproducibility in Preclinical Research. PLOS Biology 13(6): e1002165.
  7. The Case for Standards in Life Science Research – Seizing Opportunities at a Time of Critical Need. The Global Biological Standards Institute. Web. Accessed November 16, 2017.
  8. Enhancing Reproducibility through Rigor and Transparency. National Institutes of Health. Web. Accessed October 6, 2017.
  9. A Framework for Ongoing and Future National Science Foundation Activities to Improve Reproducibility, Replicability, and Robustness in Funded Research. December 2014. National Science Foundation. Web. Accessed October 6, 2017.
  10. Reproducibility and Reliability of Biomedical Research. The Academy of Medical Sciences (UK). Web. Accessed October 6, 2017.
  11. DFG Statement on the Replicability of Research Results. The Deutsche Forschungsgemeinschaft (DFG – German Research Foundation). Web. Accessed October 6, 2017.
  12. A Call for Action to Improve the Reproducibility of Biomedical Research. The InterAcademy Partnership for Health. Accessed October 6, 2017.
  13. Enhancing Research Reproducibility: Recommendations from the Federation of American Societies for Experimental Biology. Federation of American Societies for Experimental Biology. Web. Accessed October 6, 2017.
  14. Recommendations to Funding Agencies for Supporting Reproducible Research. American Statistical Association. Web. Accessed October 6, 2017.
  15. Reproducibility2020. The Global Biological Standards Institute™. Web. Accessed October 6, 2017.
  16. Validation by the Science Exchange network. Science Exchange. Web. Accessed November 16, 2017.
  17. Principles and Guidelines for Reporting Preclinical Research. Rigor and Reproducibility. National Institutes of Health. Web. Accessed November 16, 2017.
  18. Transparency and Openness Promotion (TOP). Center for Open Science. Web. Accessed October 6, 2017.
  19. Training. Rigor and Reproducibility. National Institutes of Health. Web. Accessed November 16, 2017.
  20. Freedman LP, Venugopalan G and Wisman R. Reproducibility2020: Progress and priorities [version 1; referees: 2 approved]. F1000Research 2017, 6:604 (doi:10.12688/ f1000research.11334.1)

10 Tips for Reproducible Odyssey® Western Blots

When your results depend upon reproducible measurements of protein expression changes, minimize error and variation to maximize the accuracy of your data. Get the most out of your Odyssey Imaging System with these 10 tips for robust and replicable analysis of Western blots.

1. Use the Right Membrane

It is important that you consider a few factors before choosing the appropriate membrane for your experiment. Both PVDF and nitrocellulose membranes are available in two different pore sizes, 0.2 µm for proteins less than 20 kDa, and 0.45 µm for most Western blotting applications.

Consider other experimental conditions, as well, such as:

Condition PVDF Membranes Nitrocellulose
150-200 µg of protein/cm2 which
might result in increased background signal
80-100 µg of protein/cm2
Less fragile and a better choice for
experiments that require stripping and re-probing
of membrane
PVDF membranes must be pre-wetted with
methanol, but can be used with methanol-free
transfer buffer
Transfer buffer must contain methanol
Detection Low-fluorescence PVDF must be used
for near-infrared fluorescence detection to
avoid high background resulting from
autofluorescence of standard PVDF membranes.
It is recommended that you cut a small sample
of membrane and image it both wet and dry,
to check for autofluorescence and background.
All nitrocellulose membranes are
suitable for near-infrared detection

LI-COR has evaluated and compared different transfer membranes types, and overall, nitrocellulose membranes offer the lowest membrane autofluorescence.

Figure 1. Membrane autofluorescence from PVDF affects Western blot performance. Transferrin was detected by Western blotting, using various vendors and brands of PVDF membrane. Blots were imaged with the Odyssey Classic Infrared Imaging System in both the 700 and 800 nm channels.

2. Dry Membrane after Transfer

Once the transfer of proteins from the gel to membrane has been completed, it is recommended that you air-dry the membrane, before proceeding to the blocking step. By letting the membrane air-dry, you are essentially allowing the protein to get “fixed” in place. This helps ensure that proteins are not lost from the membrane during the subsequent processing steps like washes, blocking, and probing. It will also help retain low abundance proteins, giving you better sensitivity. Also, proteins at higher concentrations will not smear when the membrane is allowed to air-dry.

3. Optimize Blocking Conditions

The right blocking buffer can greatly enhance sensitivity of near-infrared Western blots by reducing background interference, promoting specific binding of primary antibody to target, and yielding high signal-to-noise ratios with minimal non-specific signals. However, there isn’t a universal blocking buffer suitable for all experimental conditions, so optimization is important.

Blocking reagents can influence antibody binding and specificity. For example, milk-based blockers can cause high background when using anti-goat antibodies, streptavidin-biotin based detection, or when probing phosphorylated target proteins.

Also consider the buffering system used in the experiment. Washing, blocking, and antibody dilutions must be performed using either Phosphate Buffered Saline (PBS) or Tris Buffered Saline (TBS) consistently throughout the protocol.

Additionally, exposure to detergent should be avoided until the blocking step is complete, as it may cause high membrane background.

Figure 2. Effect of various blocking agents on detection of pAkt and total Akt in Jurkat lysate after stimulation by calyculin A. Total and phosphorylated Akt were detected in calyculin A-stimulated (+) and non-stimulated (-) Jurkat lysate at 10 µg; 5 µg; and 2.5 µg/well. Blots were probed with pAkt Rabbit mAb (Santa Cruz P/N sc-135650) and Akt mAb (CST P/N 2967) and detected with IRDye® 800CW Goat anti-Rabbit IgG (LI-COR P/N 926-32211) and IRDye 680RD Goat anti-Mouse IgG (LI-COR P/N 926-68070); scanned on Odyssey® CLx (auto scan 700 & 800). pAkt (green) is only detected with Odyssey Blocking Buffer (TBS).

For more optimization tips, see the Odyssey Blocking Buffer optimization protocol.

4. Optimize the Dilution of Secondary Antibodies

Using secondary antibodies at the right concentration is critical to Western blotting success. Higher dilutions provide lower membrane background and fewer background bands. On the other hand, too much secondary antibody can result in strong bands and signal saturation. Therefore, it is recommended that you optimize the dilution range for your IRDye® 800CW and IRDye 680RD conjugated secondary antibodies within 1:10,000 to 1:40,000. Ideally, begin with a 1:20,000 dilution and then optimize according to primary antibody and preferred appearance of the blot.

5. Validate Primary Antibodies

As primary antibodies bind directly to the molecule of interest to enable detection, it is critical to ensure that the antibodies are specific and bind with high affinity to the target (and isoform) of interest. A positive and negative control sample can identify non-specific interactions of the antibody. In addition, you may want to knockout the expression of your target to see if the antibody binds to any other proteins within the sample. Treating cells with growth factors that induce or inhibit expression of the target, or using a blocking peptide to inhibit binding of the antibody to the target protein are some of the other methods used to confirm antibody specificity.

When performing validation assays, do not use purified or overexpressed target protein. Also, examine different cell lines or tissues with known levels of expression of the target protein.

6. Determine the Combined Linear Range of Detection

For accurate quantitation of Western blots, it is essential that both the target protein and the internal loading control (whether total protein, housekeeping protein, or modified form of the target) are measured within the combined linear range of detection.

First, the linear range for target and internal loading control need to be determined separately. This can be performed using a dilution series of the sample and the appropriate internal loading control. The individual loading ranges obtained can then be combined to identify a loading amount within the combined linear range of detection. See the complete step-by-step protocol.

7. Use Proper Experimental Controls

Control samples are essential for generating reliable and reproducible data. Including both a positive and a negative control in your experimental design will serve as helpful checkpoints for accurate target detection. A positive control will help you confirm your antibody specificity to target within the experimental conditions. On the other hand, a negative control will help you identify any non-specific binding. Most journals recommend including a molecular size marker in Western blot data images submitted for publication. Markers aid in identifying and confirming the target within the expected molecular weight range.

“Positive and negative controls, as well as molecular size markers, should be included on each gel and blot…”
– Image Integrity, Authors and Referees, Nature; Author Guidelines, EMBO Molecular Medicine

8. Normalize Data to Internal Loading Controls

Normalization corrects for sample-to-sample and lane-to-lane variation by measuring data with reference to internal loading controls. If you do not normalize your samples, any observed changes in band intensity could be a result of error in sample preparation, loading, transfer, or actual experimental conditions.

Housekeeping proteins that have been validated for stable expression, total protein loading amounts, or modified forms of target proteins (e.g., phosphorylated and total) can all be used as internal loading controls. Housekeeping proteins or modified forms of target protein use a single or a few endogenous proteins as reference. On the other hand, total protein control takes into account the sum total of all proteins loaded within the lane. Learn more about Western blot normalization.

9. Perform Measurements in Replicates

Taking replicate measurements of experimental data are necessary for accurate, reliable results. Both technical and biological replicates help address different questions about data reproducibility.

Technical replicates are repeated measurements of the same sample that represent independent measures of the noise associated with protocols or equipment1. For example, by loading replicate lanes for each sample on a blot or repeating blots with same samples on different days, you can address the reproducibility of the technique.

Biological replicates are parallel measurements of biologically distinct samples that capture biological variation within the system1. For example, using samples derived from different cell types, tissue types, or organisms, you can evaluate if similar results can be observed, or whether your finding is an anomaly. This protocol – Quantitative Western Blot Analysis with Replicate Samples – will help you define and design your experimental replicate strategy.

10. Use Software That Does Not Modify Raw Data

Accurate data measurement and analysis is the foundation of your research findings. Image file modifications using unsupported image editing and analysis software programs can compromise the integrity of your data. Ensure that you are using a software program designed to analyze the results of your Western blot experiments that is compatible with your detection system, like Image Studio Software.

Image Studio only affects how raw data pixels are mapped to the screen, leaving your original experimental results secure. With data capture and analysis integrated in a single interface, you can keep variability from file transfers and digital adjustments from affecting your data.

Keep these ten tips for near-infrared fluorescent Western blots handy. Download this wallpaper for your computer or this flyer for quick references.

1. Blainey P, Krzywinski M, and Altman N. (2014) Points of Significance: Replication. Nature Methods 11(9): 879-880. doi:10.1038/nmeth.30

Are You Experiencing Detection System Saturation?

Normalization Webinar InvitationFor more information on Western blot normalization, watch these webinars:

An effective loading control will display a linear relationship between signal intensity and sample concentration. Saturation can often prevent this linear response, especially for highly abundant proteins. A quick recap: saturation is when strong band intensities appear different, but relative signal intensity plateaus. Check out a previous blog post on how saturation limits accurate Western blot normalization.

Linear range is the region over which signals are directly proportional to the amount of protein present. A wider dynamic range makes it easier to get data within the linear range today, as well as next year – increasing reproducibility.

Film Exposure of Chemiluminescent Blots

While film might be the method of choice for some researchers, it has fundamental limitations that affect the analysis and reproducibility of your data. It provides an extremely narrow linear range of detection, roughly 4-10 fold. Also, rapid saturation of strong signals makes it difficult to accurately determine the upper limit of detection. Film exaggerates small differences in abundance and masks sample-to-sample changes in strong bands.

Western Blot - fig1-detection
Figure 1. Odyssey® data are linear across a much wider range than ECL and film. Pure recombinant p53, Hdm2, and Hdmx protein of known concentration were serially diluted and run in duplicate, followed by Western blot analysis. Proteins were detected by IR fluorescence or standard ECL. Signal intensities were quantified with Odyssey software or, for ECL, densitometry of developed films. Reprinted from Wang, YV et al. Proc Natl Acad Sci USA. 104(30): 12365-70 (2007). Copyright (2007) National Academy of Sciences, U.S.A.

CCD Imaging of Chemiluminescent Blots

Digital imaging of chemiluminescent blots typically offers a wider linear range of detection than film. Many CCD systems are able to detect faint signals without saturating strong signals. Sensitivity and linear range depend on which CCD system you choose.

Even with a digital imager, chemiluminescent Western blot signals are still the result of an enzymatic reaction. The time-dependent enzymatic reaction may still lead to saturation and inaccurate results.

Digital Imaging of Fluorescent Blots

Fluorescent immunoblotting is best performed with near-infrared fluorescent dyes and imaging systems. Background autofluorescence of membranes and biological samples is low in the near-infrared region, enabling high sensitivity. To detect faint signals without saturating strong signals, use an imaging system with a wide linear dynamic range.

Are you experiencing detection system saturation? Find more information about saturation in this full review article:
Western Blot Normalization: Challenges and Considerations for Quantitative Analysis

Is Your Chemiluminescent Western Blot Imaging Method a Source of Error and Variability?

Chemiluminescence is a dynamic, enzymatic process that introduces variability and error in your Western blot experiments. It’s often difficult to find the “best” exposure, and the need for multiple exposures limits the reproducibility of your results.

Variability and error are introduced because:

  • Chemiluminescent reaction changes constantly.
    The “best” exposure time is a moving target, so you must optimize and double-check every experiment.
  • Multiple exposures are required.
    Common detection methods cannot accurately capture both faint and strong signals at once, without signal saturation.


Usable Data for Each Detection Method

Film Imager B Odyssey® Fc Imager
film usable range imager b usable range odyssey fc usable range
RESULT: Exposure time dramatically affects data output. Multiple exposures are required to detect strong and faint signals. Signal saturation cannot be determined visually. RESULT: Multiple exposures are required to capture the full range of data. Strong signals are saturated (shown in blue). RESULT: Multiple exposures are not required, because all exposure times yield consistent results. All data are captured in a single exposure without saturation.

In the figure above, film was compared with a conventional, commercially-available CCD imager (Imager B), and the Odyssey Fc imager. To eliminate variability introduced by blotting and chemiluminescent detection chemistry, a Harta luminometer reference plate (standardized light source) was used in place of a Western blot.

The Odyssey Fc imager outperformed both film and Imager B. All signals, from faintest to strongest, were detected – regardless of exposure time in a single exposure. No signal saturation occurred and all signals could be quantified. With film and Imager B, however, longer exposures are needed to detect faint signals. In addition, stronger signals become saturated and cannot be quantified.

Choosing the Odyssey Fc Imaging System as your imaging method reduces variability and error in chemiluminescent Western blotting by giving you:

  • All your data in a single exposure
  • More reproducible results
  • Simplified data analysis

Read the full study to learn:

  • How chemiluminescence detection introduces variability and error
  • How you can improve the reproducibility of your Western blot data

Film and CCD Imaging of Western Blots: Exposure Time, Signal Saturation, and Linear Dynamic Range

Is Research Funding an Issue in Your Lab?

Note: Currently, the SURG program is available in Austria, Canada, Denmark, Finland, France, Germany, Iceland, Ireland, Norway, Puerto Rico, Sweden, Switzerland, the United Kingdom, and the United States.

NIH Funding Graph smallerIs research funding a main concern at your institution? In a study of 3700 researchers by the American Society for Biochemistry and Molecular Biology, “68% of respondents do not have the funds to expand their research operations.” Furthermore, “65% of respondents have had difficulties receiving funding.” This is an alarming number for the research community today.

Funding has been on the decline for some time now (see chart below), especially after the 2008 recession and the NIH sequester in 2013. In 2013, the NIH handed out “approximately 640 fewer research project grants compared to FY 2012.”

As budgets are tightened across the board, funding in general may be an issue in your lab. Besides funding to back research projects, faculty and researchers need reliable instrumentation in their labs to ensure reproducible, consistent results.

How will your institution remain equipped in an ever-increasing competitive environment? The LI-COR SURG Program** could help. The SURG – Science Undergraduate Research Grant – Program is designed for faculty researchers and their students to gain access to cutting edge life science technology. If students are learning Western blotting or gel imaging techniques, this grant program could be a perfect fit.

Odyssey Fc smallerLI-COR SURG grants are a 40% match from LI-COR. The process takes ten minutes to apply.

There’s no guarantee funding will increase in the future. This program could help ensure your research is supported by superior digital imaging technology. Check out the SURG Program** offered by LI-COR Biosciences if you’re interested in learning more. Here’s more information on the Odyssey® Fc Imaging System – LI-COR’s digital imaging solution offered through the SURG program.

Possible Cause 10 for Weak Chemiluminescent Western Blot Signals: Diluting Substrates

westernsure-premium-926-95000Okay, I know, research budget money is tight and you want to make your reagents stretch as far as possible, but it really not a good idea to dilute your chemiluminescent Western blotting substrate.

Why? It’s because the rate of reaction is determined by the ratio of enzyme to substrate. Diluting substrates will dramatically impact the overall generation of light. Then, you will have to repeat the experiment, and you end up using more substrate anyway!

Optimal Blot Unsatisfactory Blot
Images Optimal Western Blot - Substrate Not Diluted Unsatisfactory Chemiluminescent Western Blot - Substrate Diluted
Substrate SuperSignal® West Dura1 SuperSignal® West Dura1
Substrate NOT diluted. Substrate diluted 1:1 (in water)
Performance LOD – 1.25 µg LOD – 2.5 µg

1Comparable to WesternSure® PREMIUM Chemiluminescent Substrate

So don’t skimp – use the substrate full strength the first time to ensure that you are seeing all of your protein bands. Or you might just have to repeat the experiment (and that will just cost you more time and money. . .)!

Here are the other nine possible causes of weak chemiluminescent Western blot signals:

Don’t Rush Substrate Incubation Time for Chemiluminescent Western Blots

Substrate Incubation Time is Important!Five minutes can seem like a long time, especially when you are waiting to image your chemiluminescent Western blot. But it is really important that you follow the manufacturer’s recommendation for incubation time. Typically, this is five (5) minutes for optimal photon emission – for both film and digital imaging.

So, set the timer for 5 minutes, grab your iPhone® or iPod® – or the crossword, and relax until the buzzer goes off.

To test this, we imaged a chemiluminescent Western blot immediately after adding the chemiluminescent substrate and then imaged a blot where we waited 5 minutes – answered a few emails, looked at the news, and downloaded a new app – and THEN imaged the Western blot. As you can see, incubating allowed us to see more bands and gave much better Western blotting results.

Optimal Blot Unsatisfactory Blot
Images Optimal Blot - 5 Min Substrate Incubation Unsatisfactory Blot - No Incubation
Substrate SuperSignal® West Pico SuperSignal® West Pico
Incubated for 5 minutes No incubation
Substrate at room temperature Substrate at room temperature
Performance LOD – 2.5 µg LOD – 5 µg

So slow down, take a breath, and wait for your chemiluminescent Western blot substrate to incubate on your Western blot before imaging.

Here are some other blog posts on possible causes of weak chemiluminescent Western blot signals:

iPhone and iPod are all registered trademarks of Apple Inc.

Chemiluminescent Western Blot Substrate Temperature Affects Signal Strength on Western Blots

The temperature at which a chemiluminescent Western blot substrate is used can affect the strength of the signal that is captured from Western blot images. Really?? Absolutely! This is because enzyme activity is greatly reduced when it is cold. The substrate needs to be equilibrated to room temperature for digital imaging. This is true with film as well, but there may be a period of time after adding substrate and exposing to film during which the substrate has had a chance to equilibrate to room temperature.

In the table below, we show data from an experiment in which we tested the affect of temperature on Western blotting signal. For one blot, SuperSignal® West Pico chemiluminescent substrate was used right out of the refrigerator – cold, 4 °C. For the other blot, the chemiluminescent Western blot substrate was allowed to come to room temperature before digital imaging. As you can see the signal difference is quite large.

Optimal Blot Unsatisfactory Blot
Images Optimal Blot when Substrate is at Room Temperature Unsatisfactory Blot when Substrate is Cold
Substrate SuperSignal® West Pico SuperSignal® West Pico
Substrate at room temperature Substrate cold
Sensitivity Standard Standard
Performance Signal – 1,740 Signal – 200

So make sure your substrate is at room temperature before using, especially when you are imaging with a digital imager!

Here are some other blog posts on possible causes of weak chemiluminescent Western blot signals: