20.109(F13): Mod 2 Day 7 HTS and Analysis

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#*Don't forget to also organize your EGF stimulated data!
#*Don't forget to also organize your EGF stimulated data!
#*Take note of the positive control wells -- these are the ''true'' zeros (after background subtraction). However, we will calculate the IC50 today, so we won't use these values in our calculations.
#*Take note of the positive control wells -- these are the ''true'' zeros (after background subtraction). However, we will calculate the IC50 today, so we won't use these values in our calculations.
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#Following the steps in the [[media:Example_datafilesetup.xls|datafilesetup.xls]] file, you will create an excel file with the name 'data'.
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#Following the steps in the [[media:Example_datafilesetup.xls|datafilesetup.xls]] file, you will create an excel file with the name 'data'. Here is an example of a Matlab-importable xls file with CellTiter-Glo data included: [[media:Data_example_F1320109.xls|example]].
#*<font color = purple> <font size = 3>'''Stop now and upload your data set-up file to the M2D7 talk page. Make sure to add your team color and day to the name of the file when you upload it!</font color></font size>'''
#*<font color = purple> <font size = 3>'''Stop now and upload your data set-up file to the M2D7 talk page. Make sure to add your team color and day to the name of the file when you upload it!</font color></font size>'''

Current revision

20.109(F13): Laboratory Fundamentals of Biological Engineering

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Contents

Introduction

Last time you set up a cell viability screen to evaluate the combination of an EGFR inhibitor and an inhibitor targeting a downstream pathway (PI3K/Akt, Ras/ErK, or STAT3). Today we will use a luminescence-based assay to quantify the viability of the cells within your culture. If the robot in the Koch Institute is cooperating (oh the perils of cutting edge technology!) we will depend on it to do all the work for us! Otherwise, we will employ a 96-well multichannel pipette to significantly cut down on our work -- giving us a different method to minimize our pipetting steps.

The cell viability assay that we will use is from Promega, Inc., and is called the CellTiter-Glo assay. The CellTiter-Glo reagent contains a recombinantly produced Luciferase that catalyzes the mono-oxygenation of beetle luciferan to oxyluciferan + light. The reaction requires Mg2+ and ATP -- and the source of ATP for the reaction is from your cells. Therefore, the extent of reaction (i.e. light generation) is related to the number of live cells within the culture. Promega reports that the reaction proceeds linearly within the range of 15 and about 50,000 cells. The doubling time of our SKOV3 cells is approximately 30 hrs, therefore our experiment will be safely within this range.
CellTiter-Glo mechanism of action. Image and caption from CellTiter-Glo product manual, Promega, Inc (Madison, WI).
CellTiter-Glo mechanism of action. Image and caption from CellTiter-Glo product manual, Promega, Inc (Madison, WI).

After completing the CellTiter-Glo assay you can utilize the Matlab code below to calculate IC50 values for your Eroltinib + Inhibitor X combinations. You will pre-process the data using Excel and then import a properly formatted spreadsheet into Matlab for visualization and calculation.

Cell viability high throughput screen

The CellTiter-Glo reaction proceeds most effectively at room temperature. Therefore, your experimental plates were removed from the tissue culture incubator and allowed to equilibrate to room temperature at the beginning of class. The CellTiter-Glo reagents have also warmed to room temp.

The following steps are written for completing the assay on the benchtop. All of the steps are done in the same way when using the robot in the HTS facility -- but you don't have to do the pipetting!

  1. Use the Liquidator 96-well multi-channel pipettor to add 100 μL of CellTiter-Glo reagent to every well in your experimental assay plate.
  2. Place the plate on the rotating platform in the chemical hood for 2 min.
  3. Remove the plate and place on your benchtop for 18 min.
  4. Obtain a black-walled, white well 96-well assay plate from the front bench.
  5. After 20 min (total), use a multi-channel pipettor to first mix and then transfer 100 μL of each well to the black plate.
    • Change your pipette tips with each addition -- perform this transfer column-wise. This will make for 12 distinct pipetting steps -- you will need one box of pipette tips for this step.
  6. Measure the luminescent output from each well using the SpectraMax L luminometer collecting light from each well for 1 sec.
    • The teaching staff will go upstairs with you to use the luminometer.

Note: We WILL use the robot in the Koch Institute for our assay!

  • Special thanks to Ian Tay (BE 3rd year PhD student and former 20.109 TA) for helping to make this possible!

Here is how the assay will run in the Koch High Throughput Facility:

  1. Half of the class at a time will walk their plates to the Koch Institute. The HTS facility is located in the basement of the building.
  2. Up to five experimental plates will be loaded onto the HighRes Bio Ambistore instrument. The Ambitstore will serve as the 'home base' for your plates.
  3. After all of the plates are loaded, the plates will receive 100 μL of CellTiter-Glo reagent per well:
    • First, each plate will move to the HighRes Bio Lid Valet to remove the lid of the plate.
    • After removing the lid, the plate will move to the Tecan EVO liquid handling system.
    • Once placed in the EVO, 100 μL will be dispensed simultaneously into each well.
  4. After visiting the Lid Valet once more, the plate will be moved by the robot arm to the BioTek plate washer where it will shake for 1 min to lyse the cells.
  5. After agitation, the plate will be returned to the Ambistore rack for 19 min.
  6. Now things get interesting --
    • First, a black plate with white wells is moved from the Ambistore to the EVO liquid handler.
    • Second, the experimental plate (now containing lysed cells + CellTiter-Glo reagent) stops by the Lid Valet on its way to the EVO.
    • Once at the EVO, 100 μL of cells/CellTiter-Glo is moved from the experimental plate to the measurement (black) plate.
    • Note: We are moving only 100 μL instead of the full volume (approx. 200 μL) to avoid air bubbles. The pipette tips will be changed between each plate to avoid cross-contamination.
  7. Finally, the measurement plate is moved directly to the Tecan M1000 microplate reader to obtain the luminescence measurement.

Data analysis

Once your plate has been read on the luminometer upstairs or in the Koch Institue, you will have a .csv file that contains your viability measurements that can be imported into Excel.

Follow these general guidelines to pre-process your data and get it ready for Matlab analysis:

  1. First, begin by locating the wells with no cells. These values represent the background luminescence signal from media alone.
    • Average these values and subtract the average value from all of the other wells.
  2. Next organize your data so that you have duplicates next to one another. For our analysis, it will be convenient to organize the data with respect to Erlotinib. Use this spreadsheet as a guide.
    • Don't forget to also organize your EGF stimulated data!
    • Take note of the positive control wells -- these are the true zeros (after background subtraction). However, we will calculate the IC50 today, so we won't use these values in our calculations.
  3. Following the steps in the datafilesetup.xls file, you will create an excel file with the name 'data'. Here is an example of a Matlab-importable xls file with CellTiter-Glo data included: example.
    • Stop now and upload your data set-up file to the M2D7 talk page. Make sure to add your team color and day to the name of the file when you upload it!

Download these three Matlab m-files:

Use the m-files to estimate the IC50 values for:

  1. Erlotinib's effect on the phosphorylation of EGFR and downstream components.
  2. The effect of adding Inhibitor X on the IC50 value for Erlotinib with respect to cell viability.
    • Note: See your lecture notes for some ideas about how to group and analyze all of the data available to you.
  3. Visualization of your viability experiment in HeatMap format.
    • Note: A HeatMap is not very quantitative -- it instead helps to identify any 'hot spots' in your data that might be worth pursuing (or at the very least, forming hypotheses and plans to pursue).
    • Note 2: You may find that a different mode of plotting the data seems more intuitive and informative to you -- think of the plots we talked about in lecture.

Remember that you are trying to determine if the addition of your Inhibitor X increased the efficacy of Erlotinib. Or, did your inhibitor do a fine job alone? Alternatively, did you find that your inhibitor did not have an effect at all? These are all questions that can be answered with the aid of statistics -- specifically, comparison of the various IC50 values using t-tests (or other appropriate methods) would be a good start.

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