TOP, IRES, Unreg Plasmids
To demonstrate how translational rates will be quantified in our IRE plasmids, Dr. John Albeck provided three plasmids with regulatory sequences in the 5’UTR region. These plasmids are TOP-H2B-DD-YFP, IRES-H2B-DD-YFP, and Unreg-H2B-DD-Cardinal. Each of these plasmids contain reporter genes, which allow easy translational quantification through microscopy, H2B domains which help organize eukaryotic DNA, and a destabilization domain that has a high induction ratio once it is stabilized by its ligand trimethoprim (TMP) (Iwamoto et.al 981). TOP is a 5-15 long sequence that encodes translational regulatory components (Han et.al 86). When exposed to the mTOR inhibitor Torin 2, TOP will downregulate translation rates. However, IRES and Unreg translational rates should be unaffected. TOP will be used as a substitute for our own plasmids with IRE sequences in them as they too should theoretically slow translation rates in the presence of iron regulatory proteins. IRES is an internal ribosome entry site that when exposed to dithiothreitol (DTT) translational rates should increase. TOP and Unreg translational effects are unaffected (Han et.al 87). None of our own plasmids contain regulatory elements that increase translational rates, but IRES will be used to contrast unregulated and downregulated translational rates. Unreg has no regulatory elements in the 5’ UTR region which means its translational rate will be uninhibited. Thus, its use will be to model our control plasmid that has no IRE sequence in its 5’ UTR sequence. To test these translational rates, a 96-well glass bottom plate pretreated with collagen type I was seeded with 10k CHO DG-44 cells in each of the inner 60 wells. All wells received media to ensure that the inner 60 did not dry out. After allowing the cells to proliferate for a day in the 37℃ CO2 incubator, all three plasmids were transfected into thirty wells each. Lipofectamine 3000 Reagent from Invitrogen was used and their transfection protocol was followed. The 96 well plate was set up as follows.
Figure 1: 96 Well Plate Map (2nd Run)
Transfected cells were immediately loaded into a closed 37℃ chamber at 5% CO2 concentration. For the first round of imaging, inhibitors DTT and Torin2 were not added to confirm that translational rates are equal among the three plasmids in the absence of these molecules. Images were collected with a Nikon (Tokyo, Japan) 20/0.75 NA Plan Apo objective on a Nikon Eclipse Ti inverted microscope, equipped with a Lumencor SOLA or Lumencor SPECTRA X light engine. Fluorescence filters used in the experiment are: DAPI (custom ET395/25x - ET460/50 m - T425lpxr, Chroma), YFP (49003, Chroma), Cy5 (49006, Chroma).
Figure 2: Order in which cells were imaged 1-61
Treatment 1
Figure 3: Treatment with TMP at the 5.8 hour mark
Images were taken on a 6 minute interval for 17.5 hrs. At the 5.8 hr mark, TMP was added to each of the inner 60 wells at 2mM and 1mM concentrations and DMSO was added to the first column as shown in Treatment 1. Half of the IRES, TOP, and Unreg transfected cells received 1mM TMP whilst the other half received 2mM TMP. After background subtraction and flat field correction, image data were processed to segment and average pixels within each identified cell’s nucleus and cytoplasm, using a custom procedure written for MATLAB (Pargett et al., 2017), Image data was stored in ND2 files generated by NIS Elements and accessed using the Bio-Formats MATLAB toolbox. Individual cells were tracked over time using uTrack 2.0 (Jaqaman et al., 2008). 175 images were generated for each well and the ones that had the best transfection efficiency were exported as movies. To see the translational rates in graph format, see the Modeling page.
Cell Movies (TMP Added at 5.8 Hours)
Unreg Well #3 0.15 Microliters Lipofectamine
Unreg Well #18 0.3 Microliters Lipofectamine
Top Well #28 0.15 Microliters Lipofectamine
Top Well #40 0.3 Microliters Lipofectamine
IRES Well #50 0.15 Microliters Lipofectamine
IRES Well #52 0.3 Microliters Lipofectamine
The images shown above are an engineering success as we were able to qualitatively and quantitatively measure translational rates. When our own plasmids are constructed we will be able to accurately measure translational rates.
Notes
The first run using the microscope was unsuccessful as the program crashed halfway through. The current data is a second attempt at imaging transfected cells without the addition of Torin2 and DDT. Next steps are to complete two more imaging collections, one in which Torin is added to all wells, and another in which DTT is added to all wells. Results should show an increase in translation in
References
Han, Kyuho, et al. “Parallel Measurement of Dynamic Changes in Translation Rates in Single Cells.” Nature Methods, vol. 11, no. 1, 2013, pp. 86–93. Crossref, doi:10.1038/nmeth.2729. Iwamoto, Mari, et al. “A General Chemical Method to Regulate Protein Stability in the Mammalian Central Nervous System.” Chemistry & Biology, vol. 17, no. 9, 2010, pp. 981–88. Crossref, doi:10.1016/j.chembiol.2010.07.009. Jaqaman, K., Loerke, D., Mettlen, M., Kuwata, H., Grinstein, S., Schmid, S.L., and Danuser, G. (2008). Robust single-particle tracking in live-cell time-lapse sequences. Nat. Methods 5, 695–702. Pargett, M., and Albeck, J.G. (2016). Mapping the spectrum of gene expres- sion responses. Cell Syst. 2, 221–222.