Hello all,
My name is Matt, and I am a 2nd year PhD student whose work currently focuses on intestinal gene expression. In brief, to collect intestinal tissue samples, we harvest sections of the intestine, flush the lumen with ice-cold 1X PBS, and remove as much fat from the outside of the intestine as we can. Finally, we "open up" the sections by cutting down the length of the sections, flatten them out on plastic Petri dish covers on ice, and scrape up the mucosa layer using glass cover slips. So, we don't collect the muscular layer of the intestines (besides any cells that may be incidentally scraped up), and do collect all cells of the mucosal layer (enterocytes, goblet cell, stem cells, resident immune cells) and any bacteria still adhered to the mucus layer.
The specific cells I am interested in, the stem and immune cells, represent a small fraction of the overall cell population, and I worry their low number means that when I isolate mRNA and perform RT-qPCR, changes in gene expression will get lost in the "noise" of all the the other cells' mRNA. I know that isolating cells of interest would be the best way to reduce noise, but right now a lot of my work is exploratory and as such faster/cheaper methods to generate pilot data is best. Here are my specific questions:
1) Besides following MIQE guidelines, are there any other helpful guidelines people could point me towards for primer design and optimization?
2) Our lab uses 18S as the reporter gene, and we use the ΔΔCT method for calculating relative expression. In previous experiments I confirmed 18S is actually the most stably-expressed reporter gene in a panel of 10 other genes I tried out, but should I use a second reporter gene and use the geometric mean method for calculating expression?
3) Any other general RT-qPCR tips/advice?
Thank you!
Hello, Matt. You should use second reference gene. Your deltaCt should be less than 10, preferably even less, for each pair "gene-of-interest"-"reference-gene". If you expect very low amount of mRNA of interest you could add some carrier for nucleic acids to reverse transcription reaction and RT-PCR. We use yeast tRNA as a carrier, but other polymers could be also used: linear polyacrylamide, for example. The main criteria: it must be inert with respect to reaction components.
You'll need a standard curve that includes very low copy number samples. You don't have to do a 10x change for each dilution step either (or even do the same dilution for each step). The key is that you CAN'T extrapolate (go beyond the data on the curve).
Your standards have to show 95-105% primer efficiency using DNA with concentrations that you see in your samples. You'll need to have excellent and careful pipetting skills to create your standards. Pre-aliquot them into strip tubes & freeze. Take out one at a time, use once, and then toss.
Most pairs of primers simply are not efficient enough to use for qPCR. Design several for each locus of interest, test them all, and be prepared to reject them all and design more. "Don't trust, verify before use" ALL primers that you get from a publication.
Good luck!
Are you looking for genes being exclusively expressed in yourtarget cells? Then you could measure only these genes. If you measure genes that are expressed in the other cells, too, then it is extremely important that the cell composition in your samples is identical under all experimental conditions.
I don't think that this approach will be very successful. Even if you find something, it will remain unclear if the apparent gene regulation is due to a biological response of your target cells, or of the non-target cells, or due to changes in the cell composition.
Have you ever considered single-cell NGS? This might looks a bit expensive at the first sight, but if you count the time and the effort to design and validate qPCR assays and what all you will have to do to get data that is interpretable at least in some limited way, NGS may eventually be cheaper.
Elena V Filatova these experiments are a new direction for our lab, so we actually aren't sure if the mRNA for the genes of interest will be lowly or highly expressed. But, if we do run into issues with very low mRNA quantity and poor amplification, that's good to know using nucleotide carriers can help improve results.
Jochen (not sure why I can't tag you), this qPCR work is intended to be exploratory, confirm our RNASeq results, and inform later cell-sorting experiments. It is good to know that our results should be taken with a grain of salt; naturally any positive results would need more rigorous experiments for confirmation, but negative results should not be taken as a sign to abandon this line of inquiry.
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