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20.109(F20): Laboratory Fundamentals of Biological Engineering

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Fall 2020 schedule        FYI        Assignments        Homework        Communication |        Accessibility

       M1: Genomic instability        M2: Drug discovery        M3: Metabolic engineering       


Today is the culminating day of Module 2 and hopefully you will identify 'hits' from your SMM screen! Though you may be able to qualitatively visualize the spots that appear to emit more fluorescence, it is important to complete quantitative analysis that supports your observations. During our previous laboratory session, you learned that a microarrayer was used to read the fluorescence signals emitted from the surface of the SMM slide at two excitation wavelengths. As noted previously, the 532 nm wavelength was used to excite fluorescein, which was printed in an 'X' pattern to assist with alignment. The 635 nm wavelength was used to excite Alexa Fluor 647-conjugated anti-His antibody; which would be associated with PF3D7_1351100 bound to a small molecule on the slide. A hit denotes a spot on the slide that emits a red fluorescence signal significantly higher than the background fluorescence level. In terms of protein binding, a hit denotes that the PF3D7_1351100 protein is bound to a small molecule and is therefore localized to a specific position on the slide. You will analyze the fluorescence signal collected by the microarray scanner using a value termed the robust z-score.

The robust z-score differentiates signal from noise by providing a value that represents the intensity of a signal above background. In the case of the SMM experiment, the intensity of a fluorescent signal above the background fluorescence is calculated. To do this the fluorescence emitted across the entire slide is grouped to define the Median Absolute Deviation (MAD), which is is a measure of the variability of a univariate dataset. Though beyond the scope of this class, the equation for calculating the robust z-score assigns a value for how much more intense the fluroescent signal at a spot is over background. The higher the value, the more different the signal from background.

Sp20 M1D6 background, foreground.png
When the SMM slides were imaged, the microarrayer also produced a GAL file, or GenePix Array List. The GAL file contains information about where each spot was printed, and what compound was printed there. However, the relationship between the GAL file and the actual contact of the print head is very imprecise. Instead, we will use the fluorescein guide spots to align the array in the GAL file to the true print location for each pin. Following the alignment, we will compare the fluorescence at 635nm within the deposition region of each spot (foreground) to the fluorescence immediately outside of this region, where nothing was printed (background) as illustrated in the image to the left. These values will be used to calculate the robust z-score. From the robust z-score, you can determine the associated probability that the observed fluorescence occurred by chance, and if this probability is sufficiently low, we call the small molecule a hit.


Part 1: Participate in Comm Lab workshop

Our communication instructors, Dr. Prerna Bhargava and Dr. Sean Clarke, will join us today for a discussion on preparing a Research article.

Part 2: Identify hits from SMM results

To complete the data analysis steps outlined, you will use a Jupyter notebook generated by Rob Wilson, a researcher in the Koehler Laboratory. Though the code is provided to you, it is important to critically think through the data analysis steps!

  1. If you do not have Anaconda installed on your computer, please do so. Anaconda Installation Site.
  2. Download SMM files from Dropbox link here: SMM Files
  3. Open a terminal.
  4. In Terminal type: "conda env create --name 20109_SMM" and answer yes when asked to proceed.
  5. Activate the environment by entering: "conda activate 20109_SMM" and press the enter key.
    • This command indicates which Python environment should be used.
  6. Type "jupyter notebook" and press the enter key. Keep this terminal open.
    • This command opens Jupyter.
    • Please note: if you had not previously installed Anaconda or a Jupyter notebook, this may give an error message. The Jupyter notebook can also be installed in the SMM environment through the Anaconda navigator.
  7. The Jupyter notebook directory should open in a new window.
  8. To select the Jupyter notebook location, select "Desktop", select 'F20_SMM_PF3D7_1351100', then select the notebook '20109_F20_SMM_Analysis.ipynb.
  9. The notebook should look like the image below:
    Sp20 M1D6 Jupyter screen capture.png
  10. The text provides details on what the code below (in boxes) is accomplishing. As you work through the data analysis, make notes in your laboratory notebook regarding the steps. Specifically, include the purpose for each step. You will also generate several figures as you complete the analysis, these should also be included in your laboratory notebook with some description of what is shown.
  11. To correctly run the notebook, several widgets must be installed in the SMM environment. This can be done in the original terminal or a new terminal window within the 20109_SMM environment using the following commands:
    • conda install -c conda-forge ipywidgets
    • conda install pandas
    • conda install scipy
    • conda install plotly
    • conda install -c conda-forge pillow
    • conda install -c anaconda qgrid
    • conda install -c conda-forge rdkit

In your laboratory notebook, complete the following:

  • For each step in the code used to analyze the SMM data, provide a brief description of the purpose (ie what is the code doing?).
    • If a figure was generated at the step, include it!
  • Attach a list of the 'hits' you identified.

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