Precise measurements lie at the foundation of every scientific discipline, including synthetic biology. The limits of our knowledge are set by how well we can connect observations to reproducible quantities that give insight. Measurement is also an act of communication, allowing researchers to make meaningful comparisons between their observations. The science and technology of measurement are easily overlooked, because measuring devices are so familiar to us, but behind even the simplest devices lies an elaborate infrastructure. Consider a laboratory pipette. How accurate are the volumes it dispenses? How similar is it to other pipettes? How do you know? The answers to these questions are a complex story involving everything from the speed to light in vacuum to the atomic properties of cesium.
In synthetic biology, measurement is a critical challenge that is receiving an increasing amount of attention each year. For example, one of the long-standing goals of both iGEM and synthetic biology at large, is to characterize biological parts, so that they can be more easily used for designing new systems. The aim of the iGEM Measurement Track is to get students informed and excited about these problems, and to highlight the successes that teams are able to achieve in the area of measurement. The Measurement Track also aims to find out what measurement assays teams have available and to lay groundwork for future more complex measurement activities in iGEM.
Measurement Challenges in Synthetic Biology
With all the instruments in our laboratories, why isn't measurement a solved problem in synthetic biology? Part of the problem is knowing what to measure and in what context. One way to think about the impact of measurements is in terms of four levels, each building upon the last:
- Measurement quantifies a phenomenon that has been experimentally
- Quantitative measurements may be used to create a model of how the
phenomenon was produced.
- Models may be applied to predict what quantitative phenomena will be
observed in a new context.
- Predictions may be used to inform choices about how to engineer
towards desired phenomena.
Instruments, by themselves, only address the first level. In
synthetic biology, many models are constructed, often post-facto.
Quantitative predictions, however, are still extremely difficult: an
important part of the problem is determining how measurement relates to
context, so that we can understand what sorts of things a model can be
reasonably expected to predict.
Even when we know what we wish to quantify, it may be impractical to
obtain with our current instruments. For example, many
quantitative models describe how the concentration of chemicals in a
single cell changes over time. Behaviors often vary greatly from
cell to cell, so it is often desirable to collect data from a large
number of individual cells. Most current instruments, however,
cannot readily measure this. Instead we end up having to make
tradeoffs like these:
A mass spectrometer can measure the amount of particular chemicals in a sample, but any cell measured is destroyed, it is difficult to obtain measurement from individual cells, and often difficult to interpret the massive pattern of data produced to quantify particular chemicals of interest.
A flow cytometer can take vast numbers of individual cell measuremements, but the measurements are of a proxy fluorescent protein rather than the actual chemical of interest and the cells may still be disrupted by running them through the instrument. Unless calibration controls are run with an experiment, the measurements are relative and non-reproducible.
A fluorimeter is less invasive than a flow cytometer and can measure changing fluorescence over time with little impact on the cells, but still uses a fluorescent proxy. Its measurements are also of the whole sample rather than individual cells, and also relative to the number of cells in the sample.
A microscope can track and quantify fluorescence from individual cells, but not very many of them, and often needs human help on tracking.
Figure 1: No generally available instrument can measure chemical concentrations in large number of single cells over time.
Relative measurements are a major problem, because they cannot be
compared. If you build models of biological devices using
different relative measurements, then you cannot combine the models to
predict what will happen when you combine the devices. If units
are relative to a batch of samples or to a laboratory, then you cannot
reproduce experimental results: even if two experiments produce the
same numbers in a new experiment, if the units are relative you cannot
tell whether the results are actually the same or whether they have
been uniformly shifted (which might be very important!).
Figure 2: Models using different relative units cannot be compared or connected. How many "Blue" in the output characterized for Repressor #1 are equal to a "Red" in the input characterized for Repressor #2?
Beyond these core scientific concerns, there are pragmatic problems
as well. Instruments are also often very expensive to buy and to
operate. This is an especially big problem for DIY groups and
researchers in smaller institutions or developing nations.
Cheaper instruments are sometimes available, but usually produce much
less accurate or precise data. Once you've got the data, you also
need to be able to share it effectively, so that everybody can benefit
from the information that is being learned. The community will
thus likely also need new tools and data exchange standards to allow
for simpler and more effective sharing of measurements and models.
Additional Reading on Measurement and Synthetic Biology
Here are some additional resources that may be interesting and can
help you learn more about the lay of the land for measurement in
Plans for the Measurement Track in 2015
The 2015 event expands on iGEM's long-running inclusion of measurement as a focus area (a measurement award has been given since 2006), and on the great success of teams in the 2014 Measurement Track.
Teams participating in the Measurement Track in 2015 can also earn a Measurement Prize by taking part in a group measurement project (the Interlab Study), in which each team measures the same properties of several known samples. We will provide some recommendations for experimental and measurement protocols, but teams are encouraged to use whatever approach will provide the most reliable and accurate measurements with the resources available to them. All of the results will be collected together and later shared, which will allow people to see the tradeoffs between different approaches.
The measurement track offers two separate opportunities for teams:
- Earning a Measurement Prize: any team may do this, including teams that compete in other tracks
- Competing for awards within the Measurement Track
Earning a Measurement Prize:
Last year, the Measurement Track ran the biggest ever synthetic biology interlab study, with 45 teams around the world signing up to participate, and collectively produce highly valuable information on the reproducibility of fluorescent expression from BioBricks. Can you help us make it even bigger and more successful this year?
In iGEM 2015, the Measurement Track will once again feature an Interlab Study, in which teams around the world will measure the same genetic devices in order to determine the amount of variation and reliability of various properties and approaches to measurement. This is not restricted to the Measurement Track teams - any team from any track that participates in the interlab study will earn a Measurement Prize!
Your team does not have to compete in the Measurement Track to participate: teams in any track can participate in the interlab study and earn a Measurement Prize. All teams that compete in the Measurement Track, however, are required to participate in the interlab study.
Any team that participates in the interlab study will receive a Measurement Prize!
Competing in the Measurement Track:
To compete for an award in the measurement track, your team must:
- Register your team, make a wiki page describing your project, and present a poster and talk at the Jamboree
- Qualify by participating in the interlab study.
- Interlab Measurement Study:
Details for the interlab study can be found here.
All iGEM teams are invited and encouraged to participate in the first international inter-lab measurement study in synthetic biology. We’re hoping this study will get you excited for iGEM and help prepare you for the summer!
Please note: All Measurement Track teams are required to participate in the inter-lab study.
All teams who participate in the inter-lab study will be acknowledged at the Giant Jamboree with a Measurement Prize!
For any questions, email measurement (at) igem (dot) org.
Please see the track medal criteria page for more information.
We have a great committee to help coordinate the Measurement track in 2015. To contact them email: measurement (at) igem (dot) org.
- Jacob Beal (BBN Technologies) (chair)
- Markus Gershater (Synthace) (co-chair)
- Alistair Elfick (Edinburgh)
- Jim Hollenhorst (Agilent)
- Deepak Mishra (MIT)
- Sarah Munro (NIST)