Difference between revisions of "Team:Carnegie Mellon/Measurement"

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.

Our original goal was to be able to design a fluorimeter solely using the materials available in the Arduino Ultimate Starter Kit. This package came with an Arduino Uno along with several helpful components such as LEDs, buzzers, relays, and a Light Dependent Resistor (LDR). The LDR is a resistor that has resistance inversely proportional to light: it has tiny resistance (100s of ohms) when a lot of light strikes it and very large resistance (10,000s of ohms) when in complete darkness. It soon became apparent, however, that the LDR would not be sufficient for our purposes: the device was not sensitive in low light, the signal was small, and the response time was very slow. Here is a graph of one of our trials where we simply turned the lights off and slowly changed the screen brightness of a computer in the room:

As the graph shows, there was no discernible change between each level of brightness (just a general upward trend), there is an incredible amount of noise making a stable reading impossible, and the response time was in the order of tens of seconds. We decided to tackle these problems individually. First, we tried to smooth out the signal. For those who are not in the field of electrical engineering, this required the use of either an inductor or a capacitor. We decided use capacitors since they were more readily available. A capacitor is a device made up of two parallel metal plates that are not touching each other so that, when a voltage is applied to these plates, an electrical field is created in between them! This field stores energy proportional to its capacitance, so it will store energy when voltage is applied over it and it will give off a voltage when there is no voltage across it. To simplify this thought, a capacitor can almost be thought of as a really small rechargeable battery. Thus, when we place a capacitor in parallel with our LDR, if the signal is high it will store energy and if the signal is low it will raise give off energy! Assuming we are using only a small capacitor, this signal will look smoother with the possible trade off of a small time delay capacitor discharges.

And here we have a much smoother signal! However, the signal is still much too small and is very slow to respond. To tackle both of these problems together, we ordered some new parts: a simple photodiode ($2) and two operational amplifiers (op amps, also roughly $2). Photodiodes are essentially small solar panels and op amps are a complex weave of transistors and capacitors that serve to amplify signals. This lead to the design of our complete circuit:

Two capacitors were used, one to smooth the signal and one to stabilize the voltage source (the Arduino). Our device measures voltage at the V nodes shown in the graph (also done by the Arduino) and the resistors connected to the negative pin of the op amp determine the amplificiation of the signal. The trade off between capacitors of different sizes is always a matter of speed versus smoothness. We tried three different capacitors and found the one that worked best to be the second:

Compare that with the original photodiode circuit unmodified here!

As you can see, things are much better now. Reattempting our original experiment, we closed the doors and turned off the lights to see how well our new circuit could detect us changing a laptop's backlit display from the six feet away facing away from the circuit:

And it worked! It can clearly be seen when the light changes and the response time is around two seconds per change. Our circuit was finally ready to test on cells! We further diminished noise by soldering our components to a PCB board (the shorter the wires, the less the noise), surrounding our circuit board with aluminum (known as a Faraday Cage, this technique prevents outside signals like radio waves from entering), and we added a Bluetooth chip to our circuit so that there was no light in the room at all. For this experiment, we used our Gaussia luciferase and tested it fully saturated to see if we could see anything at that dark. While the biologists added the Coelenterazine in the dark room, the engineers stood outside with laptops to see the results:

It was a success! The point of reaction can clearly be seen, the signal was smooth and fast, and the signal was big (meaning it should work on even diluted solutions). Our luminometer works. Of course, because things can always be improved, we have now been in the process of further amplifying the signal and diminishing noise. We have done this in several ways:
*3D printed a casing for the reaction to take place to further diminish background light
*Bought more enhanced, larger signal photodiodes (approximately $17)
*Changed the resistors so that our op amp gain increased from 4 to 11.

Future directions will also include extending our implementation to a fluorimeter. This simply requires printing a second half to the casing where we will attach an LED to excite the test tube specimens followed by a lens to only allow the wavelengths we want to measure to pass through.