The design of an engineered biological system is the central starting point of each iGEM project and also the point where the engineering cycle starts.
You will pass the DESIGN or REDESIGN stage several times while going to iterations of the Design-Build-Test-Learn (DBTL) cycle. As such, stay open minded and keep your design modular, such that you can easily change and adjust it later on. Modularity is an important criteria for the design but also the implementation of an engineered biological system.
When starting your design, these are important questions to ask:
- What will be the function of your engineered biological system?
- In which organism will you build the function? Bacteria, yeast, maybe a cell-free system?
- Which biological parts will be required to implement your function?
- How well are these functions characterized or described in literature?
- Can you model the performance of these functions and how they work together?
While we are building more information and resources here, get started by watching our 2020 iGEM Measurement Webinar series on topics such as:
- How to get started
- Modeling: ODEs and Hill Functions
- DNA parts and Basic Molecular Biology
- Modeling circuits with ODEs and experimental data
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 Engineering Committee 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. 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.
Quantitative vs. Qualitative Measurements
An important part of designing an experiment is deciding what to measure and how. This section describes the two main types of measurements, quantitative and qualitative, and provides examples of how to use them.
Quantitative Measurement are reported with numerical values. Ideally they will be reported in units that have a physical meaning. In general, you should try and make quantitative measurements whenever possible, particularly if you want other researchers in the future to compare their results to yours.
When making quantitative measurements, you should make sure that:
- You follow the four measurement tips described above: report measurements in standard units, include controls, use appropriate statistics, and present data clearly.
- You should also provide the raw values of your data in a table or spreadsheet.
Example 1 (Quantitative Measurement):
A team is measuring GFP fluorescence in a plate reader. Using the fluorescein standards from the Measurement Kit, the team converts their measurements from arbitrary units to absolute units (molecules of equivalent fluorescein). This way, their results can be compared directly to results from other labs that are reported in the same units.
Once the team obtains their data, they plot their results in a way that shows the important features of the data clearly, with replicates shown. They also post the raw data that they obtained from the plate reader as a spreadsheet on a file-sharing service and provide a link to the data on their wiki. This way, future researchers will be able to incorporate this data into their own analyses.
Qualitative Measurements are typically descriptive, as they measure categorical variables and so do not involve numerical values. Categorical variables have a fixed set of values (such as “true or false” or “low, medium, and high”) which must be defined by the experimenter. Qualitative measurements can also include relative results, such as whether one condition is “more” or “less” than another condition.
When making qualitative measurements, you should make sure that:
- You describe your definitions for your categories clearly and thoroughly. Sometimes this might involve using quantitative values, such as for thresholds between categories. These definitions should be presented alongside your data.
- Your categories are defined unambiguously so that measurements will not fall into more than one category for one variable. For example, if your categories are “low”, “medium”, and “high”, they should be defined so that one measurement cannot be both “medium” and “high” for the same variable.
Example 2 (Qualitative Measurement):
A team is conducting a color-based staining assay on bacterial colonies growing on agar plates to determine the presence of a polymer. Although the team would like to perform a quantitative measurement, they do not have any specialized equipment that would be able to measure numerical values of color.
The team is considering taking pictures of the plates and then calculating the pixel intensities for each colony and reporting the result, hoping that colored colonies will have different intensities than non-colored colonies. However, in this situation it is best for the team to perform a qualitative measurement.
They should create a uniform color standard to compare their colonies against, and use the standard as a threshold to determine if the colonies are colored or not. If the team tried to use pixel intensity as a quantitative value, then they risk introducing extra factors such as lighting conditions in different pictures into their data. As long as the team describes their reference standards and documents this information alongside their results, the qualitative measurement will be better-suited for the situation.
Please email the Engineering Committee at engineering [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!