Synthetic Biology needs great measurement approaches for characterizing parts, and efficient new methods for characterizing many parts at once. Describe your measurement approaches on this page.
Measurements are critical to scientific communication and advancement. Well-reported measurements are the only way to show whether hardware is functioning correctly, whether data are reliable and whether a result is actually important. There is high value in identifying appropriate targets for measurement, collecting precise measurements, and reporting results clearly and with appropriate units. Document your careful measurement efforts and you could win this award!
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project 1: quantifying how blood effects reporter strength
research question: how does blood effect reporter strength? how well can we detect reporter (i.e. chromoproteins or fluorescent proteins) signals within diluted blood?
run 2: voetir dark fake blood, 1-1, 1-3, 1-7, 1-9, water (in order fromof left to right) (left number is blood, right number is water)
initial fluorescence experiments: a potential end product for tnbc patients utilizes a fluorescence measurement of mirna’s 21 and 155 circulating in blood to provide a quantitative result via the minipcr “biobits” kit. we wanted to test what the lowest dilution level with blood added that fluorescence is clearly visible. for samples one through three, the addition of blood renders the fluorescence undetectable or close to it. the small quantity of what appears like fluorescence is caused by a reflection of the light coming from below. proof will be provided later on. there is slight fluorescence detectable in the 1-3 sample, too slight to be distinguishable from basal levels in blood. based on these results, we must use a minimum a 1-7 dilution. importantly, this means we need to lower the detectable threshold of our measurement target (mirnas 21 and 155) to a value lower than our target in standard whole blood.
distilled water on the left, water sample from run 1 on right.
explanation of glare: when we initially ran the test for fluorescence penetration in blood, we had a concern that the water sample fluoresced at a lower intensity than our two most dilute blood samples. in theory, water fluoresces at the highest rate. as such, we hypothesized that the inducer for the biobits was simply never added to the water sample in run 1. to test our hypothesis we simply prepared an identical biobits tube, and purposefully left out the iptg inducer. as pictured above, the two samples were in fact identical. therefore, we created a new run (run 2) and ensured the inducer was added. thankfully, we had the expected results for our water sample in this run. you will notice that even in the samples without the inducer, we still see fluorescence, however this is actually glare caused by the light shining from below the tube.
depiction of blue-based chromoprotein samples before + after addition of 20 ul blood sample
blue toned chromoproteins blood addition writeup: the goal of this experiment was to see if we could see a color change when there is a combination of chromoprotein and blood. we wanted to avoid a green chromoprotein, which would produce a brown mixture with blood, as a brown color in blood can be caused by other health factors naturally. we chose a blue chromoprotein to create a purple mixture when mixed with blood. this unique, unnatural color would then be used to distinguish between positive or negative target mirna quantity test results. we added a pink chromoprotein as a form of negative control, as a pink and red mixture are similar enough colors that they wouldn’t result in a detectable change (assuming we have performed the procedure correctly). however, we were unable to produce distinguishable results after adding the blood sample. we suspect this is due to adding too much blood to a too-dilute chromoprotein sample. additionally, cells have a tendency to settle back into pellets out of solution after roughly a minute or two. we have made several attempts to create colorful chromoprotein-producing liquid culture of engineered bacteria, however we have only been able to see color on plates. this makes it hard to standardize the amount of bacteria added, and generate consistent color patterns.
nanodrop od measurement for blue chromoproteins
the readings pictured above were taken at the beginning of our experimental process.
potential for future measurement: due to the challenges we’ve had in our lab trying to develop meaningful results with too low quantities of chromoprotein-rich cultures, we’ve decided to put this experimental series on the sidelines. however, we believe this testing method and process has extensive potential for future igem teams, or future iterations of this project to take advantage of. linked below is a document containing an in-depth experimental plan/protocol for the development of a od based chromoprotein standard, and an ideal experimental pathway to generate meaningful positive results. https://docs.google.com/document/d/1d4kzdrjftvufigwzswkpbrbjizxgfznlqdutxuso8ic/edit?usp=drivesdk
sfgfp as a chromoprotein: considering our
difficulties with aeblue, we wanted to use a different chromoprotein,
and we landed on sfgfp. we originally avoided gfp, thinking it would be
green when exposed to natural light (meaning when mixed with red, it
would turn brown). however, when spun down and rehydrated according to
the same guidelines as aeblue, we found it to be yellow. this yellow
color could produce an orange instead, which matches our criteria of an
unnatural color. our primary research question here is: what is the
amount of standardized dilute blood it takes to result in a noticeable
color change? to answer this question, we first made simple a dilution
curve of od to dilution of sfgfp samples, so that our experiment can be
repeated. as outlined in the protocol below, we identified our “most
dilute sample that is indistinguishably yellow” (or mdsiy), which was
our ¼ dilution. then, to actually test for the color change, we set
yeast producing b-carotene as the “orange” target. what we mean by
target is the rgb values of something known to be orange, whose color
our cells would then try to match as we added diluted blood. we chose
this as our target, as b-carotene is responsible for orange color in
carotene, which is universally considered orange. we wanted to use these
yeast as our target instead of a carrot itself for both uniformity of
color, and so that any possible influence our test tubes or lighting may
have on rgb values are the same between target and sample. we chose to
add diluted blood (1 part blood to 7 parts water) to our samples 1 ul at
a time. we chose this specific dilution because, as defined in our
initial fluorescence experiments, this dilution is the most concentrated
with the least amount of dampening effect on fluorescence. this is
important, so that we can match fluorescence of our sample’s color in
another experiment. we found that 1ul of 1-7 fake blood alone was enough
to cause a color change to a pink-red color whose rgb values far
exceeded the targets. we moved forward with the remaining stock sample,
and our ½ dilution. we found 2 ul were enough to cause a match in the ½
dilution, and 3 ul were enough to cause a change in our stock sample.
[need to perform again with more replicates] protocol: https://docs.google.com/document/d/1d4kzdrjftvufigwzswkpbrbjizxgfznlqdutxuso8ic/edit?usp=drivesdk project 2: determining if mirna 21 can cross the cell
membrane research question: how much mirna makes it into
bacteria cells that express toehold switches? how does that relate to
reporter output from the toehold switches? ct values of ivt mirna with splicer probes:
the goal of this experiment is to generate a ct value curve with mirna’s
21, 155, 159, and the probes for each, to be used as a standard for our
cell membrane recovery experiments, detailed later on. https://docs.google.com/document/d/1mskvyfjeerfodp5qwye6hzjfi0hthmms42lgfyhlyek/edit?usp=drivesdk after analyzing the data, we saw that ct values were very high for
all concentrations and with a slight trend towards lower ct values the
higher the concentration as expected. exp 2: given the high ct values from exp 1, we decided to try higher
concentrations to see if we can get any signal differences between the
concentrations. we also found a paper that uses 10 nm concentrations of
mirna when adding to e. coli cultures [cite]. we
are now re-running the experiment using concentrations of 1 um, 100 nm,
10 nm, and 1 nm mirna and hope to create a more effective ct curve. protocol: https://docs.google.com/document/d/1rxxuyuph1yw8lqt5avycvfkf2lt4mj7ydxwzblx0wv4/edit?usp=drivesdk ct values were lower for some samples than for exp 1. we also once
again noticed a slight trend towards lower ct values as the
concentration of mirna added increased. the rest (very work in progress!!!!!! not meant to be used in
wiki until finished) depiction of serial dilutions before vs after adding 20ul samples of
aeblue cells spun from tsb culture then resuspended in water. fluorescence curve in fake blood: the purpose of
this experiment is to benchmark cell-based fluorescence against biobits
in fake blood. [im just writing, will compress thoughts to be wiki
worthy later: we will use the blood serial dilutions, and replace the
water in the biobits kit with them. then we will get the fluorescence
values at those different levels. what’s important here is that this
allows us to measure how much the blood itself is actually affecting the
fluorescence. if our cells can’t reach equivalent fluorescence in the
same dilution, or exceed it for whatever reason, that will influence our
test design. the complexity of cells introduces so many more variables,
so if the overall purpose of our blood experiments as a whole is to see
how blood affects the fluorescence, we need the biobits as a reference
to see how much of a change is because of fake blood itself, and not
because of some other biological issue. if someone were to repeat our
experiment exactly, and didn’t have the biobits standard, if they
encountered an issue they have no “next step” to figure out what’s
causing the difference. if they repeat the biobits experiment, firstly
they know for sure whether it’s organic (a difference in our cells), or
inorganic (a difference in environment, product, etc).] can mirna-21 cross the cell membrane?: during our
literature review, while we were able to confirm mirna-155 was able to
cross the cell membrane of e.coli, there is no
equivalent for mirna-21. if the mirna was unable to cross the membrane,
we would be unable to use a possible cell-based test. the purpose of the
following experiment is to see whether mirna-21 can cross the cell
membrane. the method we used to test this was by adding a known
concentration of mirna into a culture of e.coli, isolating the
mirna using a technique called splicer, and then use qpcr to quantify
the amount of mirna recovered. splicer is a technique which uses
partially complementary nucleic acid probes, which bind to different
parts of the mirna. after these probes attach, they are joined together
by splintr ligase. at the base of one of the probes is biotin, which is
a substance that binds to streptavidin coated magnetic beads. these
beads can be pulled out of solution, which is how we isolate the mirna
from the cell contents. rate of cell membrane crossing: the purpose of this
experiment is to determine how fast the mirna molecules cross a cell
membrane. this is important for our math modeling team to figure out how
much time our test would need to fluoresce. If you've done excellent work in measurement, you should consider nominating your team for this special prize. Synthetic Biology needs great measurement approaches for characterizing parts, and efficient new methods for characterizing many parts at once. If you've done something exciting in the area of Measurement, describe it here!
exp 1: we used a set of 3 dilutions for each mirna, specifically 1 nm,
1pm, and 1 fm concentrations, reflecting a range of values found in the
splicer paper [cite] and literature on concentrations of mirna in
circulating blood [cite]. when performing qpcr we generated the
following graphs linked below.