MTT Assays: Part 3 - Analysis & Presentation

welcome to part three of our video on mtt assays in this video we're going to talk about how to analyze the mtt data and present it appropriately so let's start by reviewing some sample data and start specifically by looking at a sample experimental setup here we discussed this in the previous videos if you haven't watched it yet you can go back and look at the part two but this is essentially a basic setup for a drug dose response mtt assay so you can see that across the top we have these drug concentrations that are doubling

for each column and then we have our no cell control our zero drug control and our very high drug control all of which are important we have our eight replicates and we've made sure to plate the exact same number of cells for every single well so this is the base setup that we're starting with and when we run this assay we're going to get a certain set of absorbance readings so here is the sample data that we would get when we put that plate in for the absorbance readings so you can see here that we

still have our eight replicates going down the side we have our range of drug concentrations coming across the top and we have our important negative control at the very end so i always like to start by just calculating some key averages of our controls so we want the average of the zero micromolar we want our positive control 1000 micromolar and we want the dmso control and then our goal is really to calculate our percent viability for every single well in this chart and the way we can do that is with a simple formula so percent

viability is going to be equal to some quantity over some quantity multiplied by 100 and so on the top we're going to put the value we want to calculate against and we're going to subtract out the average of the dmso control which is the background reading and then we're going to take the average of our control because that's what we're normalizing against and again we're going to subtract out that background reading and that average that we're normalizing against in this case is our zero drug control because we want that to come out as our 100

percent viable condition because that is basically we're saying that we have treated these cells with no drug and so they should be at 100 viability and we want to know what all the other drug concentrations do relative to that zero micro molar control and so that's important to keep in mind because you may be doing different setups where you actually want to normalize against different things so for example if you were doing conditions over time you might want to normalize everything to your day zero control and so actually you would normalize every single plate to

that day zero control average or you might be doing something where you want to look at proliferation over time and so you might actually want to normalize against each cell line at its own day zero and so you can see how each cell line changes relative to its stay zero condition as you just want to think very carefully about what you're normalizing against but in this case if you were doing this kind of setup you would normalize against the zero micro molar average control so here we have the exact same data that we just looked

at and i like to start in excel by just calculating the averages across all of the columns because this gives you a basic sense of whether or not the assay worked and it allows you to see those key controls that i'm highlighting which you will need to do the actual analysis i then like to copy over this table so that i have a place to put the percent viability and i still preserve the raw data and then we can just start filling in our formula so we're going to do exactly what i just said which

is we'll take our value we'll subtract out the negative control and then we'll divide by our positive control with again the negative control subtracted out so this is the control that we're normalizing against which is our zero drug control and the dollar signs you see in the formula just make it so that it is always locked to that box every time you run the formula and so here we pull down to spread the formula across and then we can pull across to put the formula across the whole table and there you go those are all

of our percent viabilities so you see that the zero is about a hundred and then as we go down our concentration gradient we see that there is less and less viability across the board so now that we've walked through all of the analysis let's talk a little bit about how to actually present this data and analyze the graphs that you get at the end so this is a great figure from a paper that i referenced down below at the bottom of the slide you can check it out and here i think this is just a

really good example of how to present your data so you can see here that they used two different cell lines and then they did three different time points and so this is a great example of how you can mix both looking at different drug concentrations and looking at different time points and they've labeled their x and y axes which is of course really important you always want to make sure you have a clear label with the units of the drug concentration used and then you want to also label your y-axis with either normalized proliferation or

cell viability in percent as i did here you also want to make sure that you have a clear legend and that you're using colors that are easy to separate so here they have both colors and shapes that separate and define their conditions you want to make sure you include those error bars and then you also want to make sure that you talk about significance so in this case these are likely not significant but for example this condition may be significant as you'd want to add those stars to indicate significance and then possibly the most important

thing to look at is to identify the ic50 from these graphs and that is where 50 of your cells are no longer alive and so if we take the 50 mark on this graph and carry it out we can see for the blue line that it's about 100 micromolar whereas if we look for the green or the red it's about 50 micromolar and so that tells us that the longer we treat these cells the lower the ic50 is that is the more sensitive they are to our drug of interest and you can see that they've

actually made this graph of the ic50s and they're showing that as you go over time the ic50s decrease and that there's a difference between the cell lines in the ic50s and so that's the thing that you'll get asked most about when you do mtt assays what is the ic50 and then finally i just wanted to talk about if you don't have a continuous condition so if you're not doing this over time or you're not doing it over drug concentration and instead you actually just have two conditions maybe a control condition and a gene knock down

condition and you just want to show that when i knock down my gene i get less viability in that case you probably present it as a bar graph as i've drawn here rather than as align plots so in this next segment let's talk a little bit about how to actually make these graphs so to make these graphs i like to use a software called prism which as you can see has a lot of different options for graph types but here we're going to use the x y type we're going to say that x is numbers

which is our concentrations and y we're going to enter 8 replicates for each assay we'll fill in our doses here under x so 0 1 2 and so on for all the doses that we did and then we can copy over our excel table into the software to do the analysis and make the graph so here you can label your groups if you do different conditions you can label them by different conditions but here since we just did one cell line or one condition we'll just call it cell line and then you can pull over

the data i like to use a keyboard shortcut command shift t which allows you to transpose the data and you can do it one column at a time or you can actually take the entire data set and just copy it all over with command shift t and so now that we have our data in prism it will actually just generate the graph for us so here we can see we have our graph and then you can change the type to make sure that there's a line connecting it and then we can go ahead and relabel

our axes the way we want to so you should always put the drug name and then the unit of dosing you should percent viability or in this case more correctly it would be a normalized percent viability and then we can change the axes if we want to so sometimes people like to present these in log scales and so here i'm just showing you if you put it in log 10 what that might look like or if you put it in a log 2 scale what that might look like but it's also perfectly appropriate to leave

it in a linear scale if that is your preference and then of course you want to re-label with a title that's appropriate and so you would put the cell line and then you would put dose response or viability whatever this is and you can always change your axes to reflect more what you want them to because of course this is not going to go up to 150 so maybe you want to make it a little bit tighter so i'm just showing you how to do that and then you can also change the colors and so

if you have different conditions on your graph you would want to make each line a different color you would want to put in a legend right where i boxed right there and you would want to add any significance and so you can do that by using this analyze function in prism and choose an appropriate analysis there's a lot of them but there is a multiple t-test if you're trying to compare across the rows for differences but of course we can't run right now but you could run if you had multiple conditions and then you would

want to use the text function to add in stars for wherever there is a difference in significance but again of course here there is not and so we're just going to remove it so this brings us to the end of our series on mtt asses thanks so much for watching if you want to see more content like this feel free to subscribe on the youtube channel and then again there's always expanded content including protocols templates etc that you can access at the website if you need a little bit more information on mtt essays you can

definitely check out the parts one and 2 which cover the theory behind the asset and the actual protocol which you can get the links in the description below and then feel free to contact me with any questions or concerns thanks again