Looking for the best way to make your measurements, process your data and present your results? 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 the Exemplary Projects page for good examples from past teams to get inspired.
Selecting the Right Fluorescent Protein(s)
With so many fluorescent proteins to choose from, 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.
Here are some Measurement Committee recommendations, aligned with NIST fluorescence calibration standards.
Already know which proteins you’re going to use? Head to the Measuring Fluorescence section below.
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. Here are some of the properties you should consider:
- Excitation and emission spectrums
- pH stability (pKa) of the protein
- Maturation time
We recommend that you use fluorescent proteins that are monomers, fold rapidly, and are pH stable. You should consider host organism autofluorescence (especially with plants) and signal to background noise.
Also, if you are using multiple fluorescent proteins, think about selecting the right combination of proteins to avoid or minimize bleed-through. You can find more information about selecting the right properties for your project in this article by Addgene: A Practical Approach to Choosing the B(right)est Fluorescent Protein
It is also important to be aware of the capabilities of your instruments when choosing what fluorescent protein to use. We recommend teams familiarise themselves with the capabilities of their instruments generally when planning their projects so you can determine the types of
measurements you can take during your experiments.
You should know this about your instruments when planning your fluorescence measurements:
- Excitation light source (e.g.laser, LED) and the wavelengths your instrument can excite at
- Emission detector (e.g. PMT), its sensitivity and the wavelengths you can measure emission at
- Filter sets (if applicable). These can determine the wavelengths you can excite at and/or the emission wavelengths you can measure
Where to find the right fluorescent protein
There are several fluorescent protein databases to help you find the right ones to use. 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. ThermoFischer also hosts a tool called SpectraViewer, which lets you look up and compare the excitation and emission wavelengths of fluorophores including proteins, antibodies and chemical dyes. It’s great for checking compatibility between multiple sources of fluorescence.
Specific Fluorescent Protein Recommendations
For fluorescent reporter proteins, iGEM’s general recommendation is 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 (Excit. 500 / Emiss. 513, brightness 35, maturation time 4.1 min, weak dimer). See FPBase for more information.
- BBa_K864100: sYFP2 (Excit. 515 / Emiss. 527, brightness 68, maturation time 4.1 min). See FPBase for more information.
Red Fluorescent Proteins
- BBa_J06504: mCherry (Excit. 587 / Emiss. 610, brightness 16, maturation time 15 min, pKa 4.5). See FPbase for more information.
- mKate2 (Excit. 588 / Emiss. 633, brightness 25, maturation time 20 min, pKa 5.4). See FPbase for more information.
If a slow maturation time is acceptable, then we recommend these:
- BBa_E1010: mRFP1 (Excit. 584 / Emiss. 607, brightness 12.5, maturation time 60 min, pKa 4.5). See FPbase for more information.
- mScarlet (Excit. 569 / Emiss. 594, brightness 70, maturation time 174 min, pKa 5.3). See FPbase for more information.
Red Organic Dyes
These can be used for calibration of red FPs. Major organic dyes in this range include:
- Nile Red (549/628) (part of the NIST fluorescence standards)
- Texas Red (596/620)
Blue Fluorescent Proteins
These can be useful if you need excitation or emission wavelengths that do not overlap with blue or red fluorescence. Damage from shorter wavelength light is however a consideration with blue fluorescent proteins. To avoid this, using a cyan fluorescent protein may be preferable depending on the experiment.
- BBa_K592100: TagBFP (Excit. 402 / Emiss. 457, brightness 33, maturation time 13 min, pKa 2.7). See FPbase for more information.
If a cyan fluorescent protein is required with a longer maturation time then we recommend:
- mCerulean3 (Excit. 433 / Emiss. 475, brightness 35, maturation time 70 min, pKa 3.2). See FPbase for more information.
Note the Coumarin 30 beads in the Spherotech Ultra Rainbow Quantitative Particle Kit can be used to calibration the quantification of some blue and cyan fluorescent proteins. These are the beads used by NIST and the previous iGEM InterLab studies.
Fluorescent proteins are great tools for lots of measurements and used every year by many iGEM teams. If you’re going to use fluorescence measurements in your project, here are some great resources to check out.
Plate Readers and the iGEM Measurement Kit
iGEM sends all teams a Measurement Kit which lets you calibrate your plate reader fluorescence measurements. This makes them more powerful because calibrated fluorescence measurements can be directly compared between different iGEM teams. We recommend all teams using plate readers for fluorescence measurements calibrate their instrument. For more details about the Measurement Kit and how to use it, please see our dedicated Measurement Kit page.
Flow cytometers allow high-throughput measurement of fluorescence from hundreds of thousands of individual cells. Like plate readers, your flow cytometry machine can be calibrated so that your results can be directly compared to those of other teams who have also calibrated their instruments. iGEM does not currently include the materials to do this in the Measurement Kit. However, for teams interested in calibrating their flow cytometry we recommend checking out these products.
- SpheroTech Rainbow Calibration Particles (Recommended: URCP-38-2K) (Product Link)
- ClonTech EGFP and mCherry Calibration Beads (Product Link)
We also recommend several free and open source 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.
Microscopes are powerful tools to measure fluorescence that produce images rich with spatial information. Absolute calibration for fluorescence microscopy can be challenging and iGEM currently does not have a calibration protocol to recommend. However, even uncalibrated, fluorescence microscopy is a powerful tool.
For teams considering it, we recommend this article which provides good general practices: “A beginner’s guide to rigor and reproducibility in fluorescence imaging experiments”. Please also see the software Fiji below which can help you analyse your microscopy data.
Analyzing and Plotting Data
Presenting your data correctly and well is just as important as good measurement. Below are some tools that can help you analyze your data and create useful plots to explain your results. There is an older but still very pertinent article here on things to consider when plotting your data: "Some Helpful Hints in Preparing Scientific-Quality Plots for Reports by hand or by using Excel." We also recommend teams look at our Exemplary Projects page to see good past iGEM examples. This also has examples of many common graphs and figures, presented in published scientific articles.
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.
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.
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!
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.
Please email the measurement committee at measurement [AT] igem [DOT] org and provide links to material with a short description. We’ll check it out and if we believe it will be helpful, we’ll add it to this page!