Difference between revisions of "Measurement/Measurement kit"

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<h1>Measurement Resources</h1>
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<p>
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<span class="on_page"></span>
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<b>On this page</b> you will find information on:
 +
<a href="https://2020.igem.org/Measurement/Resources#measuring_fluorescence">Measuring Fluorescence</a>, <a href="https://2020.igem.org/Measurement/Resources#fluor_proteins">Selecting Fluorescent Proteins</a>, <a href="https://2020.igem.org/Measurement/Resources#microscopy">Using Microscopy</a>, and <a href="https://2020.igem.org/Measurement/Resources#plotting_data">Analyzing and Plotting Data</a>
 +
</p>
 +
 
 +
<p>Thinking about how your team might approach measurement? Check out some of the resources below to help get you started, some of which have been developed specifically for iGEM teams. We also encourage you to look at examples from past teams to get inspired.</p>
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<div class="highlight post_item gray">
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<div class="details">
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<span class="icon notice"></span>
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<div class="title">Have a resource to contribute?</div>
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</div>
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<p>Please email the measurement committee at <i> measurement [AT] igem [DOT] org </i> and provide links to material with a short description. We’ll test out the material and if we believe it will be helpful, we’ll add it to this page!</p>
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<div class="clear extra_space" id="measuring_fluorescence"></div>
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<h2>Measuring Fluorescence</h2>
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<p>Below are some tools that can help you transform arbitrary unit (AU) fluorescence measurements into standard comparable units.</p>
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</div>
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<img src="https://static.igem.org/mediawiki/parts/5/59/IGEMHQ_2019_MK.jpg">
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<p class="image_caption">iGEM Measurement Kit</p>
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</div>
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<div class="column two_thirds_size">
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<h3>Plate Reader</h3>
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<p>The <a href="http://parts.igem.org/Help:2020_DNA_Distribution#Measurement_Kit">Measurement Kit </a>is included in your iGEM Distribution Kit and is intended to help your team measure green fluorescent protein (GFP) and red fluorescent protein (RFP) reliably in a plate reader. The kit includes: tubes of Fluorescein Sodium Salt, tubes of Texas Red, and a tube of silica beads.
 +
<br>
 +
<br>
 +
Fluorescein has a similar range of excitation and emission as most GFPs. Because of the overlap of the excitation and emission spectrums, we can utilize fluorescein to create a standard curve to compare GFP measures against in plate readers. The same holds true for Texas Red and many RFPs. The silica beads are a suspension of silica particles in water that can be used for calibrating optical density (OD) measurements.
 +
</p>
 +
 
 +
<ul>
 +
<li>Protocol for using the iGEM Measurement Kit to calibrate fluorescence and OD</li>
 +
<li>iGEM Measurement Kit calculation spreadsheet</li>
 +
</ul>
 +
 
 +
<p><b>Storage</b>: The Measurement Kit should be stored at room temperature or at least higher than 4°C. </p>
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<img src="https://static.igem.org/mediawiki/2019/9/90/Flow_bead_example.png">
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<p class="image_caption">Graph representing peak identification for SPHERO RCP-30-5A beads </p>
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</div>
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<div class="column two_thirds_size">
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<h3>Flow Cytometry</h3>
 +
<p>Flow cytometers allow high-throughput measurement of fluorescence from hundreds of thousands of individual cells. Calibration beads and appropriate controls allow you to turn raw “arbitrary unit” measurements into precise and replicable units.</p>
 +
 
 +
<p>Sources of calibration beads:</p>
 +
<ul>
 +
<li>SpheroTech Rainbow Calibration Particles (Recommended: URCP-38-2K) (<a href="https://www.spherotech.com/CalibrationParticles.htm">Product Link</a>)</li>
 +
<li>ClonTech EGFP and mCherry Calibration Beads (<a href="https://www.clontech.com/US/Products/Fluorescent_Proteins_and_Reporters/Flow_Cytometer_Calibration_Beads/AcGFP_and_mCherry">Product Link</a>)</li>
 +
</ul>
 +
 
 +
<p>Free and open data analysis software for calibrated flow cytometry:
 +
<ul>
 +
<li>TASBE Flow Analytics (Matlab/Octave library) (<a href="https://github.com/TASBE">TASBE link</a>)
 +
<br><i>TASBE Flow Analytics is a software tool that analyzes flow cytometry data, including bead-based conversion to standard units.Experiment templates support automated processing, comparison, and plotting of data. TASBE Flow Analytics was developed as Matlab and Octave compatible software.</i></li>
 +
 
 +
<li>CytoFlow (Python library + graphical interface) (<a href="https://bpteague.github.io/cytoflow/">CytoFlow link</a>)
 +
<br><i>CytoFlow is a collection of Python tools for quantitative, reproducible flow cytometry analysis, including bead-based conversion to standard units and a Jupyter notebook interface.</i></li>
 +
 
 +
<li>FlowCal (Python library + Excel interface) (<a href="https://taborlab.github.io/FlowCal/">FlowCal link</a>)
 +
<br><i>FlowCal is a library for reading, analyzing, and calibrating flow cytometry data in Python, including bead-based conversion to standard units and an Excel worksheet interface for simple data entry.</i></li>
 +
</ul>
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<img src="https://static.igem.org/mediawiki/2020/4/4f/Principles_of_fluorescence_microscopy_measurement_committee_2020.jpeg">
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<p class="image_caption">Graph representing fundamental concepts underpinning fluorescence microscopy </p>
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</div>
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 +
<div class="column two_thirds_size">
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 +
<h3>Using Microscopy</h3>
 +
<p>Microscopes are powerful tools to measure fluorescence that produce images rich with spatial information. Absolute calibration for fluorescence microscopy is not straightforward, members of the Measurement Committee are working on a protocol, but there is not one currently available to recommend. Even uncalibrated, fluorescence microscopy is a powerful tool, but there are a number of pitfalls on the path from biological sample to data point. </p> <br>
 +
 
 +
<p>There is a group of microscopy specialists on the Measurement Committee, with experience in widefield and confocal fluorescence microscopy, image processing and analysis, and image data presentation. The article below provides good general practices, if you have specific questions don’t hesitate to email us. Starting an email subject line with ‘Microscopy –‘ will bring it to our attention and likely have a faster response.
 +
</p><br>
 +
<p> <a href="https://doi.org/10.1091/mbc.E17-05-0276">“A beginner’s guide to rigor and reproducibility in fluorescence imaging experiments”</a>
 +
Free and open image visualization, processing and analysis software:
 +
<a href="https://fiji.sc/"> Fiji:</a> Fiji, a distribution of ImageJ, is a powerful, free program that is widely used to explore, process, and analyze fluorescence microscopy data. With a scripting language and a large community of users, plugins exist to meet many image processing and analysis goals, and new extensions of the software can easily be written.
 +
</p>
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<br><br>
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</div>
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<div class="clear extra_space" id="fluor_proteins"></div>
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<div class="column full_size">
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<h2>Selecting Fluorescent Proteins</h2>
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<p>With so many fluorescent proteins to choose, which ones should you use for your project? Fluorescent proteins have revolutionized experiments in synthetic biology. They are so useful that hundreds have been developed for many different uses. The Measurement Committee has recommendations aligned with NIST fluorescence calibration standards. </p>
 +
</div>
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 +
<div class="column half_size">
 +
 
 +
<h3>Features of Fluorescent Proteins (FPs) to consider before starting your experiments</h3>
 +
<p>
 +
It is important to be aware of the properties of the fluorescent proteins you want to use and how these properties could influence results. We recommend that you use fluorescent proteins that are monomers, fold rapidly, and are pH stable.
 +
<ul>
 +
<li>Excitation and emission spectrums</li>
 +
<li>pH stability (pKa) of the protein</li>
 +
<li>Maturation time</li>
 +
</ul>
 +
If using multiple fluorescent proteins, you will need to consider bleed-through, host organism autofluorescence, and signal to background noise.
 +
</p>
 +
 
 +
</div>
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 +
<div class="column half_size">
 +
<h3>Instrumentation Properties</h3>
 +
<p>
 +
It is also very important to be aware of the properties of your instrumentation so you can determine the types of measurements you can take during your experiments. You should know this type of instrumentation when working with fluorescent measurements:
 +
<ul>
 +
<li>Excitation light source - laser, LED</li>
 +
<li>Emission detectors - PMTs, sensitivity</li>
 +
<li>Filter sets (if applicable)</li>
 +
</ul>
 +
</p>
 +
</div>
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 +
<div class="clear"></div>
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<div class="column full_size">
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<h3>Fluorescent Protein Database</h3>
 +
<p>FPbase is a free and open-source, community-editable database for fluorescent proteins (FPs) and their properties. FPbase was designed and created in 2018 by Talley Lambert at Harvard Medical School.</p>
 +
<div class="button"> <a href="https://www.fpbase.org/about/"> FPbase.org </a> </div>
 +
</div>
 +
 
 +
<div class="clear"></div>
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<div class="column full_size">
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<h3>Specific Fluorescent Protein Recommendations</h3>
 +
<p>As a general recommendation from iGEM for a fluorescent reporter protein, it is important that the protein is a monomer, folds rapidly (min vs hours), is bright, and does not possess acid sensitivity.
 +
</p>
 +
 
 +
<p><b>Green Fluorescent Proteins</b>
 +
<br>
 +
<ul>
 +
<li><a href="http://parts.igem.org/Part:BBa_E0040">BBa_E0040</a>: GFPmut3 (500/513, brightness 35, maturation time 4.1 min, weak dimer) - more information can be found on <a href="https://www.fpbase.org/protein/gfpmut3/">FPBase</a></li>
 +
</ul>
 +
<br>
 +
<b>Red Fluorescent Proteins</b>
 +
<br>
 +
<ul>
 +
<li><a href="http://parts.igem.org/Part:BBa_J06504">BBa_J06504</a>: mCherry (587/610, brightness 16, maturation time 15 min, pKa 4.5 ) - more information can be found on <a href="https://www.fpbase.org/protein/mcherry/">FPbase</a></li>
 +
<li>mKate2 (588/633, brightness 25, maturation time 20 min, pKa 5.4) - more information can be found on <a href="https://www.fpbase.org/protein/mkate2/">FPbase</a></li>
 +
</ul>
 +
 
 +
<p>If a slow maturation time is acceptable, then we recommend these:
 +
<ul>
 +
<li><a href="http://parts.igem.org/Part:BBa_E1010">BBa_E1010</a>: mRFP1 (584/607, brightness 12.5, maturation time 60 min, pKa4.5) - more information can be found on <a href="https://www.fpbase.org/protein/mrfp1/">FPbase</a></li>
 +
<li>mScarlet (569/594, brightness 70, maturation time 174 min, pKa 5.3) - more information can be found on <a href="https://www.fpbase.org/protein/mscarlet/">FPbase</a></li>
 +
</ul>
 +
<br>
 +
 
 +
<b>Red Organic Dyes</b>
 +
<br>
 +
The major organic dyes in this range include:
 +
<ul>
 +
<li>Nile Red (549/628) (part of the NIST fluorescence standards)</li>
 +
<li>Texas Red (596/620)</li>
 +
</ul>
 +
<br><br>
 +
 
 +
<p>
 +
<b>Blue Fluorescent Proteins</b>
 +
<br>
 +
Another consideration for blue fluorescent proteins can be damage from shorter wavelength light so moving to a cyan may be preferable depending on the experiment.
 +
 
 +
<ul>
 +
<li><a href="http://parts.igem.org/Part:BBa_K592100">BBa_K592100</a>: TagBFP (402/457, brightness 33, maturation time 13 min, pKa 2.7) - more information can be found on  <a href="https://www.fpbase.org/protein/tagbfp/">FPbase</a></li>
 +
</ul>
 +
 
 +
<p>
 +
If a cyan is required with a longer maturation time then:
 +
 
 +
<ul>
 +
<li>mCerulean3 (433/475, brightness 35, maturation time 70 min, pKa 3.2) - more information can be found on <a href="https://www.fpbase.org/protein/mcerulean3/">FPbase</a></li>
 +
</ul>
 +
 
 +
The Coumarin 30 beads in the <a href="https://spherotech.com/Ultra%20Rainbow%20Quantitative%20Particle%20Kit.pdf">Spherotech Ultra Rainbow Quantitative Particle Kit</a> can be used to standardize the quantitation (these are the beads used by NIST and the previous iGEM InterLab studies).
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</p>
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<h2>Analyzing and Plotting Data</h2>
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<p>Below are some tools that can help you analyze your data and create useful plots to explain your results.</p>
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</div>
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<div class="clear extra_space"></div>
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<div class="column third_size">
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<img src="https://static.igem.org/mediawiki/2019/a/a0/DNAPlotLib.jpg">
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<p class="image_caption">Image from DNAplotlib</p>
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</div>
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<div class="column two_thirds_size">
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<a href="https://github.com/VoigtLab/dnaplotlib"><h3>DNAplotlib</h3></a>
 +
 
 +
<p>Visually integrating graphs of your data with a schematic representation of the parts and circuits which generated that data is an important aspect of scientific communication in synthetic biology. There are many ways to achieve this goal, but for teams with proficiency in the Python programming language, DNAplotlib is an excellent tool developed by the authors of Der and Glassey et al., 2016, <i>ACS Synthetic Biology</i> for this purpose. Even for teams without coding experience, we recommend looking at some of DNAplotlib’s sample graphs as an example of good data visualization practices in synthetic biology.</p>
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<img src="https://static.igem.org/mediawiki/2020/3/30/R_Logo.jpeg">
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</div>
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 +
<div class="column two_thirds_size">
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<a href="https://rstudio.com/"><h3>R and R Studio</h3></a>
 +
 
 +
<p>R studio is a free set of tools designed to let you use the programming language R in an easy and effective way. R is a programming language for statistical computing which can be used to analyse data from your experiments, and plot graphs for use on your wiki. As R is an opensource platform, scripts written to analyse and plot your data can be uploaded to iGEM wikis, which helps others better understand your data and hence more likely to use aspects of your project. A beginners tutorial for R can be found <a href="https://www.rforbiologists.org/">here</a>. </p>
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<img src="https://static.igem.org/mediawiki/2019/5/5b/WebPlot.jpg">
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<p class="image_caption">Image from WebPlotDigitizer</p>
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</div>
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<div class="column two_thirds_size">
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 +
<a href="https://automeris.io/WebPlotDigitizer/"><h3>WebPlotDigitizer</h3></a>
 +
 
 +
<p>Often, published data (whether in scientific papers or in the BioBrick Registry) exists only in graphical form, which prevents you from being able to make quantitative comparisons between your results and existing work. WebPlotDigitizer, developed by Ankit Rohatgi, is an open-source web-based tool that solves this problem by allowing you to input an image of a graph or plot and returning numerical values for the data depicted in the image. No coding experience is required-- just upload an image, define values along the axes, and click on points within the graph to generate a table of data that you can analyze!</p>
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Revision as of 15:35, 26 March 2020

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Measurement Resources

On this page you will find information on: Measuring Fluorescence, Selecting Fluorescent Proteins, Using Microscopy, and Analyzing and Plotting Data

Thinking about how your team might approach measurement? Check out some of the resources below to help get you started, some of which have been developed specifically for iGEM teams. We also encourage you to look at examples from past teams to get inspired.

Have a resource to contribute?

Please email the measurement committee at measurement [AT] igem [DOT] org and provide links to material with a short description. We’ll test out the material and if we believe it will be helpful, we’ll add it to this page!

Measuring Fluorescence

Below are some tools that can help you transform arbitrary unit (AU) fluorescence measurements into standard comparable units.

iGEM Measurement Kit

Plate Reader

The Measurement Kit is included in your iGEM Distribution Kit and is intended to help your team measure green fluorescent protein (GFP) and red fluorescent protein (RFP) reliably in a plate reader. The kit includes: tubes of Fluorescein Sodium Salt, tubes of Texas Red, and a tube of silica beads.

Fluorescein has a similar range of excitation and emission as most GFPs. Because of the overlap of the excitation and emission spectrums, we can utilize fluorescein to create a standard curve to compare GFP measures against in plate readers. The same holds true for Texas Red and many RFPs. The silica beads are a suspension of silica particles in water that can be used for calibrating optical density (OD) measurements.

  • Protocol for using the iGEM Measurement Kit to calibrate fluorescence and OD
  • iGEM Measurement Kit calculation spreadsheet

Storage: The Measurement Kit should be stored at room temperature or at least higher than 4°C.

Graph representing peak identification for SPHERO RCP-30-5A beads

Flow Cytometry

Flow cytometers allow high-throughput measurement of fluorescence from hundreds of thousands of individual cells. Calibration beads and appropriate controls allow you to turn raw “arbitrary unit” measurements into precise and replicable units.

Sources of calibration beads:

  • SpheroTech Rainbow Calibration Particles (Recommended: URCP-38-2K) (Product Link)
  • ClonTech EGFP and mCherry Calibration Beads (Product Link)

Free and open data analysis software for calibrated flow cytometry:

  • TASBE Flow Analytics (Matlab/Octave library) (TASBE link)
    TASBE Flow Analytics is a software tool that analyzes flow cytometry data, including bead-based conversion to standard units.Experiment templates support automated processing, comparison, and plotting of data. TASBE Flow Analytics was developed as Matlab and Octave compatible software.
  • CytoFlow (Python library + graphical interface) (CytoFlow link)
    CytoFlow is a collection of Python tools for quantitative, reproducible flow cytometry analysis, including bead-based conversion to standard units and a Jupyter notebook interface.
  • FlowCal (Python library + Excel interface) (FlowCal link)
    FlowCal is a library for reading, analyzing, and calibrating flow cytometry data in Python, including bead-based conversion to standard units and an Excel worksheet interface for simple data entry.

Graph representing fundamental concepts underpinning fluorescence microscopy

Using Microscopy

Microscopes are powerful tools to measure fluorescence that produce images rich with spatial information. Absolute calibration for fluorescence microscopy is not straightforward, members of the Measurement Committee are working on a protocol, but there is not one currently available to recommend. Even uncalibrated, fluorescence microscopy is a powerful tool, but there are a number of pitfalls on the path from biological sample to data point.


There is a group of microscopy specialists on the Measurement Committee, with experience in widefield and confocal fluorescence microscopy, image processing and analysis, and image data presentation. The article below provides good general practices, if you have specific questions don’t hesitate to email us. Starting an email subject line with ‘Microscopy –‘ will bring it to our attention and likely have a faster response.


“A beginner’s guide to rigor and reproducibility in fluorescence imaging experiments” Free and open image visualization, processing and analysis software: Fiji: Fiji, a distribution of ImageJ, is a powerful, free program that is widely used to explore, process, and analyze fluorescence microscopy data. With a scripting language and a large community of users, plugins exist to meet many image processing and analysis goals, and new extensions of the software can easily be written.



Selecting Fluorescent Proteins

With so many fluorescent proteins to choose, which ones should you use for your project? Fluorescent proteins have revolutionized experiments in synthetic biology. They are so useful that hundreds have been developed for many different uses. The Measurement Committee has recommendations aligned with NIST fluorescence calibration standards.

Features of Fluorescent Proteins (FPs) to consider before starting your experiments

It is important to be aware of the properties of the fluorescent proteins you want to use and how these properties could influence results. We recommend that you use fluorescent proteins that are monomers, fold rapidly, and are pH stable.

  • Excitation and emission spectrums
  • pH stability (pKa) of the protein
  • Maturation time
If using multiple fluorescent proteins, you will need to consider bleed-through, host organism autofluorescence, and signal to background noise.

Instrumentation Properties

It is also very important to be aware of the properties of your instrumentation so you can determine the types of measurements you can take during your experiments. You should know this type of instrumentation when working with fluorescent measurements:

  • Excitation light source - laser, LED
  • Emission detectors - PMTs, sensitivity
  • Filter sets (if applicable)

Fluorescent Protein Database

FPbase is a free and open-source, community-editable database for fluorescent proteins (FPs) and their properties. FPbase was designed and created in 2018 by Talley Lambert at Harvard Medical School.

FPbase.org

Specific Fluorescent Protein Recommendations

As a general recommendation from iGEM for a fluorescent reporter protein, it is important that the protein is a monomer, folds rapidly (min vs hours), is bright, and does not possess acid sensitivity.

Green Fluorescent Proteins

  • BBa_E0040: GFPmut3 (500/513, brightness 35, maturation time 4.1 min, weak dimer) - more information can be found on FPBase

Red Fluorescent Proteins
  • BBa_J06504: mCherry (587/610, brightness 16, maturation time 15 min, pKa 4.5 ) - more information can be found on FPbase
  • mKate2 (588/633, brightness 25, maturation time 20 min, pKa 5.4) - more information can be found on FPbase

If a slow maturation time is acceptable, then we recommend these:

  • BBa_E1010: mRFP1 (584/607, brightness 12.5, maturation time 60 min, pKa4.5) - more information can be found on FPbase
  • mScarlet (569/594, brightness 70, maturation time 174 min, pKa 5.3) - more information can be found on FPbase

Red Organic Dyes
The major organic dyes in this range include:
  • Nile Red (549/628) (part of the NIST fluorescence standards)
  • Texas Red (596/620)


Blue Fluorescent Proteins
Another consideration for blue fluorescent proteins can be damage from shorter wavelength light so moving to a cyan may be preferable depending on the experiment.

  • BBa_K592100: TagBFP (402/457, brightness 33, maturation time 13 min, pKa 2.7) - more information can be found on FPbase

If a cyan is required with a longer maturation time then:

  • mCerulean3 (433/475, brightness 35, maturation time 70 min, pKa 3.2) - more information can be found on FPbase
The Coumarin 30 beads in the Spherotech Ultra Rainbow Quantitative Particle Kit can be used to standardize the quantitation (these are the beads used by NIST and the previous iGEM InterLab studies).

Analyzing and Plotting Data

Below are some tools that can help you analyze your data and create useful plots to explain your results.

Image from DNAplotlib

DNAplotlib

Visually integrating graphs of your data with a schematic representation of the parts and circuits which generated that data is an important aspect of scientific communication in synthetic biology. There are many ways to achieve this goal, but for teams with proficiency in the Python programming language, DNAplotlib is an excellent tool developed by the authors of Der and Glassey et al., 2016, ACS Synthetic Biology for this purpose. Even for teams without coding experience, we recommend looking at some of DNAplotlib’s sample graphs as an example of good data visualization practices in synthetic biology.

R and R Studio

R studio is a free set of tools designed to let you use the programming language R in an easy and effective way. R is a programming language for statistical computing which can be used to analyse data from your experiments, and plot graphs for use on your wiki. As R is an opensource platform, scripts written to analyse and plot your data can be uploaded to iGEM wikis, which helps others better understand your data and hence more likely to use aspects of your project. A beginners tutorial for R can be found here.

Image from WebPlotDigitizer

WebPlotDigitizer

Often, published data (whether in scientific papers or in the BioBrick Registry) exists only in graphical form, which prevents you from being able to make quantitative comparisons between your results and existing work. WebPlotDigitizer, developed by Ankit Rohatgi, is an open-source web-based tool that solves this problem by allowing you to input an image of a graph or plot and returning numerical values for the data depicted in the image. No coding experience is required-- just upload an image, define values along the axes, and click on points within the graph to generate a table of data that you can analyze!

iGEM Foundation

The International Genetically Engineered Machine (iGEM) Foundation is an independent, non-profit organization dedicated to the advancement of synthetic biology, education and competition, and the development of an open community and collaboration. Visit us at igem.org

Contact


hq AT igem DOT org


45 Prospect Street
Cambridge, MA 02139


Due to COVID-19, iGEM staff are working remotely and cannot receive phone calls.
Please contact us by email.

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