Western Blot - Accurate, Reproducible Data Integrity
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Consistent Data to Address Reproducibility Challenges

In the face of changing data reporting guidelines, publish your results with confidence. LI-COR near-infrared imaging solutions will help you minimize variation in detection, chemistry, and data analysis, for accurate and reproducible Western blot results.

BRC, We Have a Problem

And it affects all of us in the Biomedical Research Community (BRC); academia, industry, journal publishers, funding agencies, and government.

Published Data is Not Consistent with Replicated Studies

Among other findings…

Pile of 67 pills

43 out of 67 Studies

showed inconsistencies between published and in-house data when replicated by researchers at Bayer1

Pile of 53 pills

6 out of 53 Findings

from landmark preclinical cancer papers could be confirmed by researchers at Amgen2

Variability in Materials and Methods at Fault

Among other sources...

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54% of Materials

used in research, including antibodies, model organisms, and reagents are not uniquely identifiable in publications3

11%

papers graph 11%

Lab Protocols

25%

papers graph 25%

Data Analysis and Reporting

28%

papers graph 28%

Study Design

36%

papers graph 36%

Biological Reagents and Reference Materials

4 Major Factors

contribute to irreproducibility in preclinical research4

The Bottom Line Hit Hard

Among other costs...

$

28 Billion Spent Annually

on research that cannot be replicated, in the United States alone4

$

500,000 - 2 Million Per Study

investment needed to replicate academic research with potential clinical applications within the pharmaceutical industry4

Your Peers Agree

Among other surveys...

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90% of Respondents

surveyed by Nature from various scientific disciplines agreed that there is a reproducibility crisis in scientific literature5

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At least 60% of Respondents

in the fields of biology and medicine from Nature and American Society for Cell Biology (ASCB) surveys reported failure in replicating someone else’s experiments5,6

Change is Coming Soon to a Lab near You

2014

December

The National Science Foundation (NSF)

Reported its ongoing and future activities to improve reproducibility, replicability, and robustness in funded research7

2015

June

The National Institutes of Health (NIH)

Issued revisions to grant application instructions in an effort to enhance reproducibility in preclinical research8

October

The Academy of Medical Sciences (UK)

Developed an action plan for improving reproducibility and reliability of biomedical research9

2016

January

The Federation of American Societies For Experimental Biology (FASEB)

Drafted recommendations regarding the use of mouse models and antibodies towards enhancing research reproducibility10

September

The InterAcademy Partnership (IAP) for Health

Issued a statement, endorsed by 46 of its member academies in Europe, Asia, the Americas, and Africa, to improve reproducibility of biomedical research11,12

2017

January

The American Statistical Association (ASA)

Provided recommendations on statistical analysis to funding agencies for supporting reproducible research13

April

The German Research Foundation (DFG)

Published a statement on replicability of research results and identified activities for research funding and scientific self-governance14

Ongoing Efforts to Enhance Reproducibility

Revision of Publication Guidelines

Journals groups including AAAS, ASCB, Biomed Central, F1000, Frontiers, Nature, PLOS, Springer, and Wiley, among others, have signed up to tighten publication guidelines17

Validation of Research Materials

A number of non-profit groups in partnership with academia and industry are developing standards, practices, and validation guidelines for research reagents16

Training in Rigor and Reproducibility

Training programs are being developed for researchers in study design, meeting funding and publication policies, data analysis, and more15

Global Biological Standards Institute (GBSI)

Established the Reproducibility2020 initiative to significantly improve the quality of preclinical biological research15,16

Strengthen Your Findings with Reproducible Data

Unraveling the complex interplay between biochemical pathways and understanding how therapeutic agents affect them often requires reliance on protein expression data. Results from Western blots and cell-based biochemical assays help measure therapeutic outcomes and guide preclinical development of potential drug compounds.

When a lot counts on accurate assessment of protein expression changes, you cannot let variability in detection methods, techniques, reagent chemistry, and image analysis programs affect your results. Minimize error and variation using standardized protocols, robust detection, validated reagents, and secured data analysis software. Maximize the accuracy of your results and publish your data with confidence.

Take your research forward with the LI-COR Data Integrity Bundle.

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Accurate Detection
Odyssey® CLx and Fc Imaging Systems

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Stable Chemistry
IRDye® infrared dye products and Western blotting reagents

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Reliable Analysis
Image Studio data analysis software

You'll also get:

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Comprehensive Learning
Personalized training and educational resources

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Accessible Expertise
Unparallelled technical support just a call away

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Close Collaboration
Western blotting assay and validation services

Accurate Western Blot Detection

Get the true picture of protein expression changes. Detect and quantitate targets and internal reference proteins within the combined linear range of the assay, wherein signals captured by the imaging system are proportional to protein amounts.

Is Your Detection System Showing You All Data?

Protein targets of varying abundance (say, a low-abundance target and a high-abundance housekeeping protein) can have very different linear ranges of detection. An imaging system with a limited dynamic range of detection makes data capture within the combined linear ranges of targets challenging. This is because strong signals can saturate the detector; at saturation, strong signals are no longer linear, and therefore are not directly proportional to the target signals at lower abundances. Because the actual protein amounts (low-abundance target and high-abundance HKP) are not proportional, normalization of the target is not possible. Moreover, signals acquired at different exposures or detected on separate blots cannot be compared for quantitative analysis.

Take one step towards enhancing data reproducibility by minimizing variation in detection.

Widen Your Detection Capabilities

A wide dynamic range of detection on Odyssey® Imaging Systems enables you to capture data over the entire linear range of your assay in a single image. This means you can see both strong and faint signals, without saturation, and accurately compare data.

Normalizing target proteins to high-abundance housekeeping proteins or total protein loading? With a wide dynamic range of detection, you can get the most accurate data using either method. Conveniently assess the combined linear range for targets and internal loading controls, and confidently quantitate your results.

target protein linear range
Detect your target protein and internal loading control in the combined linear range. Low abundance targets and high abundance internal loading controls may have very different linear ranges of detection. A serial dilution will help you find their combined linear range.

“Quantification of gel or blot intensities must be performed with data obtained within a linear range of exposure.”

- Instructions for Authors, Journal of Biological Chemistry

“For quantitative comparisons, appropriate reagents, controls and imaging methods with linear signal ranges should be used.”

– Image Integrity, Authors and Referees, Nature

Extend Your Possibilities

Detecting multiple targets with similar molecular weights, or looking at modified forms of proteins? Near-infrared (NIR) fluorescence detection on Odyssey® Imaging Systems lets you detect two or more targets and controls simultaneously, using 700 nm and 800 nm channels. This means you can compare signals across several samples in a single scan for coherent data analysis.

Background autofluorescence from blotting membranes is low in the NIR imaging spectrum. So, you get improved sensitivity and high signal-to-noise ratios for detecting low-abundance or poorly expressed targets.

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700nm
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800nm
700nm and 800nm Western Blot

Multiplex to detect two different protein targets in each sample lane. Use secondary antibodies labeled with spectrally-distinct NIR fluorescent dyes to get more data from your blot. View, adjust, and analyze your results as a merged image, or as separate 700 nm and 800 nm channel images in pseudo-color or grayscale.

Visible region (Vy3) High autofluorescence Neasr-infrared region (700nm) Low autofluorescence

NIR fluorescence imaging gives you low membrane fluorescence and high sensitivity. Visible fluorescent dyes like Cy3 have poor sensitivity, because membrane autofluorescence is so strong. Blots show detection of phospho-ERK with NIR fluorescence (700 nm) and with ECL Plex reagents.

““The image should include all relevant controls, and controls should be run on the same blot or gel as the samples.”

- Submission Guidelines, PLOS ONE”

Optimized Western Blot Assay Chemistry

Turn your rigorous study designs into measurable experiments. Stabilize your detection chemistry and expand options for consistent, reproducible results.

Is Detection Chemistry Affecting Your Results?

For quantitative protein expression analysis, you need to compare and relate data from targets, standards, controls, markers, and more. Enzymatic detection is difficult to control and optimize. Changes in substrate type, incubation time, volume, temperature, and other factors can cause results to vary greatly. Additionally, optimization of the enzymatic reaction to detect more than one target at a time is difficult, which limits throughput, efficiency and consistency.

Adapt your workflow with near-infrared fluorescence detection and get more data out of each blot.

Reduce Variables, Multiply Options

“Positive and negative controls, as well as molecular size markers, should be included on each gel and blot...”

- Image Integrity, Author and Referees Nature; Author Guidelines, EMBO Molecular Medicine

Get sensitive detection and multiplexing options with IRDye® Infrared Dye fluorophores and dye conjugated products. Two-color detection of targets, controls, and molecular weight markers let you analyze expression changes consistently across samples.

“Normalization of signal intensity to total protein loading (assessed by staining membranes using Coomassie blue, Ponceau S or other protein stains) is preferred. “House-keeping” proteins should not be used for normalization without evidence that experimental manipulations do not affect their expression.”

- Instructions for Authors, Journal of Biological Chemistry

Whether you normalize targets using total protein staining or a housekeeping protein, you have options. Before normalizing to a housekeeping protein, check for stable expression using loading indicators.

Minimize non-specific interactions and enhance signal-to-noise ratios with reagents optimized for near-infrared detection.

Reliable Western Blot Data Analysis

Process experimental observations into conclusive outcomes. Secure your experimental results with software designed for Western blot analysis.

Keep Unknowns Out of Your Data

Image Studio Screenshot

Not all image editing software programs are designed to analyze your Western blot data. Features in unsupported programs can result in non-linear adjustments, compromising the integrity of your results. Software that bins or modifies images during digital transfer and analysis can also introduce unwanted variability.

Minimize uncertainty in data analysis and transfer, and safeguard your results.

Simplify Data Analysis

Image Studio software integrates data acquisition, analysis, and archiving within a simple interface, so you can eliminate variability in digital transfers, while securing your original data for future reference.

Image Studio only affects the display of raw data pixels mapped to the screen. So, variables in binning and non-uniform adjustments are left out of the equation while you adjust, normalize, quantitate, and chart data.

 

“All images submitted to The Journal of Immunology must accurately represent the original data. Original data (digital files, autoradiographs, films, etc.) for all experiments should be fully annotated, secured, and retrievable.”

– Information for Authors, The Journal of Immunology

“Our screening process examines…whether adjustments of brightness, contrast, or color balance have been applied to the entire image and that adjustments do not enhance, erase, or misrepresent any information present in the original, including the background.”

- Editorial Policies, Journal of Cell Biology

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Your information has been sent to our Product Support Team who will be following up with you.

If you do not receive a response within 2 business days, please contact: biosales@licor.com

What steps can you take today to improve your Western blot results?

LI-COR provides products, protocols, and support for Western blotting and a range of other protein assays. Let us know how we can help you.

Get In Touch

Consistent training is key to reproducible results. Sign up for Lambda U and get your lab members trained with standardized Western blotting protocols, video tutorials, and technical resources.

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References

  1. 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
  2. Begley GC, Ellis LM. 2012. Drug development: Raise standards for preclinical cancer research. Nature 483, 531-533. doi:10.1038/483531a
  3. Vasilevsky NA, Brush MH, Paddock H, et al. On the reproducibility of science: unique identi cation of research resources in the biomedical literature. Abdullah J, ed. PeerJ. 2013;1:e148. doi:10.7717/peerj.148.
  4. Freedman LP, Cockburn IM, Simcoe TS (2015). The Economics of Reproducibility in Preclinical Research. PLOS Biology 13(6): e1002165.
  5. Baker M. 1,500 scientists lift the lid on reproducibility. Nature (News Feature) 533, 452-454.
  6. How Can Scientists Enhance Rigor in Conducting Basic Research and Reporting Research Results? American Society for Cell Biology. Web. Accessed October 6, 2017.
  7. 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.
  8. Enhancing Reproducibility through Rigor and Transparency. National Institutes of Health. Web. Accessed October 6, 2017.
  9. Reproducibility and Reliability of Biomedical Research. The Academy of Medical Sciences (UK). Web. Accessed October 6, 2017.
  10. 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.
  11. Improving the reproducibility of biomedical research: a call for action. The Interacademy Partnership for Health. 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. Recommendations to Funding Agencies for Supporting Reproducible Research. American Statistical Association. Web. Accessed October 6, 2017.
  14. DFG Statement on the Replicability of Research Results. The Deutsche Forschungsgemeinschaft (DFG - German Research Foundation). Web. Accessed October 6, 2017.
  15. 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)
  16. Reproducibility2020. The Global Biological Standards Institute. Web. Accessed October 6, 2017.
  17. Transparency and Openness Promotion (TOP). Center for Open Science. Web. Accessed October 6, 2017.
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