Team:Carnegie Mellon/Measurement
Measurement.
Simple, low cost flourometers & luminometers.
Measurement is an important facet of synthetic biology. In order for experiments to run smoothly, measurements should be consistent across different research teams. One standing goal for iGEM is to characterize biological parts using precise measurements so that new systems can be created. Our Carnegie Mellon iGEM team chose to participate in the measurement track to lay a foundation for future measurement activities in iGEM.
In being part of this track, there are a few requirements we needed to fulfill. We took part in the international iGEM collaboration called the interlab study where we measured the same property of known samples to see if we could quantify the calculated measurements across different teams. Each team was recommended a protocol but was free to do any of their choosing. Our team decided to use the classical cloning protocol due to the versatility of this protocol and the supplies we had. In addition to the Interlab study, we needed to register our team, make a wiki page describing our project, and present a poster at the Jamboree. Being part of the measurement track has allowed us to focus our skills on making several biological and triplicate replicates to make sure our data was consistent across the board. We also learned how to problem solve and analyze our results based on the values we obtained.
Our team wants to emphasize that simple, reliable measurement is key to progressing scientific knowledge. Fluorescent proteins have revolutionized measurement of protein amounts and allow kinetic measurements to be made in live cells. However, measurements are of a relative qualitative nature, instead of a universal unit or SI measure, so that it is difficult to standardize across labs and data is not suitable for accurate modeling of cellular processes influenced by amounts of protein. The major reason for this is because measuring light at this scale deals more with converting an analog signal to a digital output, rather than finding luminous intensity over a given cone (i.e. the lumen rating one would find on a light bulb). The way luminescence is read is through a sensor that is activated when it gets struck with individual photons. These photons are then translated to a varied amount of electrical signal that is heavily related to submicroscopic interference, the variability of digital output (low level computational issues), and perhaps most importantly the drastically different sensitivities of the chain of sensors and controllers involved in relaying a digital signal. It is not as simple as saying that one “digital count” (or relative luminescence unit (RLU)) is one photon.
Even more difficulties arise when trying to quantitatively measure fluorescence. As fluorescence only releases photons after absorbing photons of higher energy, the only way of getting a sustained signal is through bombarding a sample with photons. The number of photons of appropriate wavelength striking a sample leading in photon signal emission becomes nearly even more impossible to count with electrical inconsistencies compounding on the analog signal-digital count problem. Thus in constructing an affordable machine and better quantifying and characterizing the light output of our proteins, we are attacking the problem of comparing data by allowing incredibly similar relative measurements to be taken across iGEM teams and more. By eliminating at least one of the major problems with relative measurements (drastically different access to hardware and the expensive nature of normalizing this type of signal) we can ensure the reproducibility of our specific reads. Reproducibility is key to building accurate and accountable biotechnologies.
In being part of this track, there are a few requirements we needed to fulfill. We took part in the international iGEM collaboration called the interlab study where we measured the same property of known samples to see if we could quantify the calculated measurements across different teams. Each team was recommended a protocol but was free to do any of their choosing. Our team decided to use the classical cloning protocol due to the versatility of this protocol and the supplies we had. In addition to the Interlab study, we needed to register our team, make a wiki page describing our project, and present a poster at the Jamboree. Being part of the measurement track has allowed us to focus our skills on making several biological and triplicate replicates to make sure our data was consistent across the board. We also learned how to problem solve and analyze our results based on the values we obtained.
Our team wants to emphasize that simple, reliable measurement is key to progressing scientific knowledge. Fluorescent proteins have revolutionized measurement of protein amounts and allow kinetic measurements to be made in live cells. However, measurements are of a relative qualitative nature, instead of a universal unit or SI measure, so that it is difficult to standardize across labs and data is not suitable for accurate modeling of cellular processes influenced by amounts of protein. The major reason for this is because measuring light at this scale deals more with converting an analog signal to a digital output, rather than finding luminous intensity over a given cone (i.e. the lumen rating one would find on a light bulb). The way luminescence is read is through a sensor that is activated when it gets struck with individual photons. These photons are then translated to a varied amount of electrical signal that is heavily related to submicroscopic interference, the variability of digital output (low level computational issues), and perhaps most importantly the drastically different sensitivities of the chain of sensors and controllers involved in relaying a digital signal. It is not as simple as saying that one “digital count” (or relative luminescence unit (RLU)) is one photon.
Even more difficulties arise when trying to quantitatively measure fluorescence. As fluorescence only releases photons after absorbing photons of higher energy, the only way of getting a sustained signal is through bombarding a sample with photons. The number of photons of appropriate wavelength striking a sample leading in photon signal emission becomes nearly even more impossible to count with electrical inconsistencies compounding on the analog signal-digital count problem. Thus in constructing an affordable machine and better quantifying and characterizing the light output of our proteins, we are attacking the problem of comparing data by allowing incredibly similar relative measurements to be taken across iGEM teams and more. By eliminating at least one of the major problems with relative measurements (drastically different access to hardware and the expensive nature of normalizing this type of signal) we can ensure the reproducibility of our specific reads. Reproducibility is key to building accurate and accountable biotechnologies.