You have five main responses to this:
1) Necrosis/Lysis (cell dies due to malfunction)
2) Apotosis (cell kills itself)
3) Senescence (cell doesn't die but stops dividing)
4) Non-homologous end joining (NHEJ, the free ends of the damaged DNA are just pasted back together by the cells repair machinery)
5) Homology-directed repair (HDR, other DNA around that has a similar sequence to the free ends gets used by the cells repair machinery to paste something in between; eg you have two of each chromosome so use the corresponding sequence on the other one to fill in the gap)
The second thing to realize is that cells containing the targeted DNA sequence will be more likely to have damaged DNA than those without. So once a cell is "mutated" (either because it just existed beforehand, or because it survived the crispr/cas9 treatment), it will have a survival advantage.
The third thing to realize is that often these cells they use can divide multiple times per day, I've seen as high as 12 times a day for activated T-cells. That means in two days a single mutant cell could possibly produce 2^24 = 16,777,216 offspring cells containing the mutation.
Anyway, I think the efficiency of this procedure may have been far overstated. There may be only a very few cells in each experiment that actually get edited, but a few days later when they check, those (already mutated) cells dominate the population due to their resistance to the crispr/cas9 treatment.
Eg, look at extended data fig 1h from this recent paper: https://www.nature.com/articles/s41586-018-0326-5/figures/5
The more cells that die, the higher percent of "edited" cells later.
I wanted to elide the details, but this is what I was referring to when I discussed CRISPR applications that try to change a nucleotide sequence.
This of course leaves discussions of base-editing aside[1]
1. http://www.sciencemag.org/news/2017/10/novel-crispr-derived-...
EDIT:
I really mean that I think in some of these experiments, where they only try to cause NHEJ, they just already had mutants in the population and selected for them. Its possible not a single cell was successfully edited but you still have so many cells with indels at the targeted sequence afterward.
I'll go find some refs on it if you ask.
Reference:
GAATTC
Variants:
Cell 1: TAATTC
Cell 2: GTATTC
Cell 3: GATTTC
Cell 4: GAAGTC
Cell 5: GAATGC
Cell 6: GAATTT
Cell 7: GAATTC
Cell 8: GAATTC
For six cells, 1/6 nucleotides differ from the reference sequence (16.7% per base indel rate). For two cells, there is no difference (0 % per base indel rate).
Even though 12.5% of cells contain an indel at any given site, no single cell contains 12.5% indels. There is no reason the two values should be the same.
1) There are no indels in your example, only nucleotide substitutions.
2) There are six substitutions in 48 bases, for a per-base substitution rate of 12.5%. The fact that none of the individual cells contains 12.5% substitutions is totally irrelevant.
It works perfectly fine as an example. A single nucleotide change could be due to an indel:
"Indel is a molecular biology term for an insertion or deletion of bases in the genome of an organism. It is classified among small genetic variations, measuring from 1 to 10 000 base pairs in length,[1][2][3][4][5][6][7]" https://en.wikipedia.org/wiki/Indel
>"There are six substitutions in 48 bases, for a per-base substitution rate of 12.5%. The fact that none of the individual cells contains 12.5% substitutions is totally irrelevant."
In the experiments they are counting how many cells contain a mutant (eg via GFP expression or not). Thus the number you want is percent of cells that contain a mutation at a given site.
You are the one calculating some other number... Remember what we are discussing? Its percent of cells with a given mutation and mutations per cell, the numbers I calculated:
>"There's no way cells survive with indels at 10% of their base positions, that's not possible."
>"You clearly have no idea what you are talking about."
There seems to be some heavy dunning-kruger going on with your post.
You posted an example purporting to disprove this, but instead, illustrated that you don't know what an indel is, and that the two statements are indeed equivalent -- at any given site, 12.5% of cells are mutant, and that the per-base mutation rate is 12.5%.
The only one with Dunning-Kruger is you.
> "There's no way cells survive with indels at 10% of their base positions, that's not possible."
> "How is the per-base indel rate not 10% if 10% of cells carry an indel at any given locus?"
I figured you were referring to per base within each cell. Your overall "per base" rate is getting the average (across cells) number of mutated sites. The survival of a cell is determined by its own genome, not the average of the population its been grouped into.
However, it is the case that if x% of cells have a mutation at any given site then there must be at least some cells in this group that contain x% or greater mutated sites. Is that what you meant? Because that's not a bad point. I don't know where that 10% value came from and have no attachment to it, just assume that one is measurement noise for now, but even cells with 0.1% of sites mutated seems like a lot.
There doesn't seem to be many whole genome single cell sequencing results available yet, which is what I think is needed here. Here is one that reports ~ 15k SNVs, 50-100 "micro-CNVs" (ie 10-100 kb copy number variants, fig S4), and 290 indels:
>"We call an SNV if there is a called NR allele and: (a) the total read depth in the bulk sample is above 15; (b) no bulk read has the NR allele; (c) if two SNVs are within 100bp from each other, both are discarded. With this procedure, we called 15,940 SNVs on the autosome of sample BJ1...We called 294 putative INDELs from the BJ1-BJ2 pair, the negative control" https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538131/
So taking the smallest and biggest numbers of possible here gives:
100%*(15e3 + 50*10e3 + 290*1)/3e9 = 0.02% of bases affected
100%*(15e3 + 100*100e3 + 290*10e3)/3e9 = 0.4% of bases affected
I wrote this before I added the "smallest" calculation. So only the very large structural changes are ignored (> 100 kb).
Fig 1b: 0.31%
Fig 3b: 1.12%
Fig 4b: 0.18%>"You could call that noise of course, at the very least they can't detect rates below those using current methods."
>"Either that or the methods used to measure this are too noisy to detect mutants that exist at those rates."
Yes, for the HDR case it is usually extremely unlikely (barring contamination) that the mutant already existed. If you reread my other post I specifically refer to the NHEJ case when discussing pre-existing mutants.
However, a single T-cell could (T-cells can divide up to 12 times a day[1]) expand to as many as 2^48 = 2.81475e+14 daughter cells in the 4 days of that study (see panel A of the same figure). They started with only 1e6 cells in the culture. Therefore these results could be explained by editing a single cell that then proliferates to make up the 30% of the population (300k cells) they see.
[1] http://journals.plos.org/plosone/article?id=10.1371/journal....
So, on average, only one cell division happened before measurement, unless you want to claim GFP stimulates T-cells to hyperproliferate. My intuition is that cells with the transgene will actually be slower than their competitors, since they have to waste energy to make GFP.
The PLoS One paper you've linked is about in-vivo hyperproliferation of T-cells in response to an ongoing infection, not about in-vitro primary culture in minimal media.
No, the claim is that double stranded breaks lead to cell death and senescence amongst the non-mutated cells thus selecting for the cells that lack the target sequence (because they were just "edited" or otherwise). We don't know how many cells survived the treatment, or how fast the different populations were dividing, or the rate at which these cells were dying. From extended fig 1a just see that 2 days after treatment there were ~500k total cells from an original ~1 million and ~100k of those expressing GFP. Then four days after treatment there were ~1 million total cells with ~ 300k of them expressing GFP.
Are T-cells capable of dividing quick enough so a single cell can generate 100k in 2 days and 300k in 4 days? The literature says yes. Maybe there was an initial thousand edited cells that divided on average ~3 times each day for two days and then once the last two days as the surviving non-GFP+ cells recovered. Is that what happened? I don't know. They didnt report the details of what happened immediately after the treatment.
>"The PLoS One paper you've linked is about in-vivo hyperproliferation of T-cells in response to an ongoing infection, not about in-vitro primary culture in minimal media."
Yes, it only demonstrates how fast they could be dividing, setting an upper bound. We don't know under the conditions in this paper.
As often covered in the news, CRISPR-mediated gene editing can be used to edit a DNA sequence to another, desired sequence. In these applications, it's very important that no other mutations besides the desired mutation are introduced. Such additional mutations would be 'off-target' mutations.
In a second kind of experimental approach, researchers can use CRISPR technology to make arbitrary mutations at a desired site in the genome. This approach cares less about the resulting damage; the goal is simply to destroy the existing gene.
The referenced article[1] seems to characterize the types of mutations that arise when people use CRISPR to ablate a gene (i.e., the second approach). It would be interesting to see if the range of DNA damage is restricted when CRISPR is instead used to change the sequence of a targeted DNA segment into another, desired sequence.
[1] https://www.nature.com/articles/Nbt.4192