So this week I was pretty busy at the lab, a bit more than usual. What happened was that the HepG2 cells in both my 12-well plates (The Stage 1 culture-wares) became over-confluent, which means that the cells have divided too much and are stacking on top of each other. This is NOT helpful when you want to count cells, and it would skew treatment results. The color of the nutrient media was shifting towards light orange or yellow instead of its healthy red or light red. If you remember what I said a few weeks ago, these cells grow very fast and I have to subculture them every 2 days. I subcultured them on Saturday and intending to do it again on Monday, which I did many times before. But SURPRISE!! The over-confluent nature of my cells delayed this trial by a day and a half. I might be exaggerating this just a bit, but it was pretty annoying. I think this happened because I didn’t count the cells correctly or I diluted by the wrong volume, which can really cause a significant difference. There’s only one way to fix it and that’s subculturing the overconfluent cells, which I did carefully and I ended up doing it right this time.
In the next part of this post I’m going to be responding to some of the comments in my previous posts, because it’s easier this way.
- First up, Arjun asked about whether the cells might have become resistant to the drugs. My answer is no, because firstly it didn’t happen before, and secondly it would’ve shown a proportional resistance in the other conditions, because the treatment only happens once per well in each trial.
- Arjun also asked about how I will be analyzing my data. For the FACS data, I’ve already technically analyzed the raw data because I was able to determine the live/dead percentages and cell cycle for all the trials. The further analysis is basically comparisons of trends among the 3 treatment types (Dox alone, Dox + Pac, Dox pretreat then Pac) and among each treatment concentrations. As for the Western Blot analysis, I find the ROI (rate of intensity) values of the p53, p21, SOD2, Noxa, and Puma proteins in each sample. Then I normalize the values based on the B-Actin levels, and then I plot the normalized values on separate bar graphs. Further analysis would be basically evaluating trends and checking the difference in expression levels per sample.
- As for Sahi’s question about running the FACS test multiple times, I will be running one FACS test per trial. There’s no need for more than one per trial, because it’s highly accurate and would take far too long (each new test would add another 2 days to my trial), but considering the consistency of my results, I don’t think it’s necessary.
I hope you got your questions answered, and you can definitely also ask me in person if you have more! 🙂