Some Expected Yields

Here is some real-world data describing expected yields we may expect from some of these routine lab procedures or services.

Obviously the above plot is about how much total plasmid DNA we get from the miniprep kit we use in the lab.
The plot above show the expected total yields of DNA based on the extraction type / method
And this is the pretty wide range of reads we’ve gotten from submitting plasmids to plasmidsaurus
The above graph shows how many (raw) reads we’ve gotten from Azenta / Genewiz Amplicon-EZ.

Oh, and this is a good one:

How well my determination of flask “confluency” actually correlated with cell counts. I mean, sure, there must be some error being imparted by the actual measurement of the cells when counting, but I think we all know it’s mostly that my estimate really isn’t precisely informative.

When iCasp9 doesn’t kill

iCasp9 as a negative selection cassette is amazing. Targeted protein dimerization with AP1903 / Rimiducid is super clean and potent, and the speed of its effect is a cell culturist’s dream (cells floating off the plate in 2 hrs!). It really works.

But when there are enough datapoints, sometimes it doesn’t. I have three recorded instances of email discussions with people that have mentioned it not working in their cells. First was Jeff in Nov 2020 with MEFs. Then Ben in June 2021 with K562s. And Vahid in July 2021 with different MEFs. Very well possible there’s one or two more in there I missed with my search terms.

Reading those emails, it’s clear that I had already put some thought into this (even if I can’t remember doing so), so I may as well copy-paste what some them were:

1) Could iCasp9 not work in murine cells, due to the potential species-based sequence differences in downstream targets? Answer seems to be no, as a quick google search yields a paper that says “Moreover, recent studies demonstrated that iPSCs of various origin including murine, non-human primate and human cells, effectively undergo apoptosis upon the induction of iCasp9 by [Rimiducid]. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7177583/

Separately, after the K562s (human-derived cells) came into the picture:

This is actually the second time this subject has come up for me this week; earlier, I had a collaborator working in MEF cells note that they were seeing slightly increased but still quite incomplete cell death. That really made me start thinking about the mechanism of iCasp9-based killing, which is chemical dimerization and activation of caspase 9, which then presumably cleaves caspases 3 and 7 to then start cleaving the actual targets actually causing apoptosis. So this is really starting to make me think / realize that perhaps those downstream switches aren’t always available to be turned on, depending on the cellular context. In their case, I wondered whether the human caspase 9 may not recognize the binding / substrate motif in murine caspase 3 or 7. In yours, perhaps K562’s are deficient in one (or both?) of those downstream caspases?

Now for the most recent time, which happened in the lab rather than by email: It was recently brought up that there is a particular landing pad line (HEK293T G417A1) which we sometimes use, that apparently has poor negative selection. John and another student each separately noticed it. Just so I could see it in a controlled, side-by-side experiment, I asked John if he’d be willing to do that experiment, and the effect was convincing.

So after enough attempts and inadvertently collecting datapoints, we see the cases where things did not go the way we expected. Perhaps all of these cases share a common underlying mechanism, or perhaps they all have unique ones; we probably won’t ever know. But there are also some potentially interesting perspective shifts (eg. a tool existing only for a singular practical purpose morphing into a potential biological readout), along with the practical implications (ie. if you are having issues with negative selection, you are not alone).

This is the post I will refer people to when they ask about this phenomenon (or what cell types they may wish to avoid if they want to use this feature).

Submitted DNA amounts and reads returned

In this previous post, I showed how many reads we’ve gotten from our Plasmidsaurus and AMP-EZ submissions. Well, now’s also time to see whether the amount of DNA that we gave correlated with the number of reads we got back.

Submissions to Plasmidsaurus. Red vertical line denotes the minimum value asked for submission (>= 10uL at 30 ng/uL). Blue line is a linear model based on the datapoints.

As you can see above, since this is miniprepped DNA, it’s usually quite easy to reach the 300 ng needed for submission. One time, when we submitted closer to 200ng, it worked perfectly fine. One other time, when we submitted ~ 100ng, it did not, albeit this was not plasmid DNA and instead was a PCR product, so it’s an outlier for that reason as well.

Submissions to Genewiz / Azenta AMP-EZ. Red vertical line is the minimum amount of DNA asked for, while the horizontal red line is the number of reads they “guarantee” returned. Blue line is a linear model based on the data.

This is the more important graph though, since all of our AMP-EZ submissions are from gel extracted PCR amplifications, and it can be quite difficult to do it in such a way that we have the 500 ng of total qubitted DNA available for submission. Well, turns out that it’s probably not all that important for us to hit 500 ng of DNA, since it’s worked perfectly fine in our attempts between 200 and 500 ng. I imagine people in my lab will simultaneously be happy (knowing they don’t have to hit 500 ng) and sad (knowing they had spent a bunch of extra effort in the past unnecessarily trying to reach that number) seeing the above data, but hey, it’s good to finally know this and better late than never!

Terrific for lentivector growth?

At some point, I was chatting with Melissa Chiasson about plasmid DNA yields, and she mentioned that her current boss had suggested using terrific broth instead of Luria broth for growing transformed bacteria. I think both of us were skeptical at first, but she later shared data with me showing that DNA from e.coli grown in TB had actually given her better yield. I thus decided it was worth trying myself to see if I could reproduce it in my lab.

There are two general types of plasmids we tend to propagate a lot in my lab. attB recombination vectors, for expressing transgenes within the landing pad, and also lentiviral vectors of the “pLenti” variety, which play a number of different roles including new landing pad cell line generation and pseudovirus reporter assays.

I first did side-by-side preps of the same attB plasmids grown in TB or LB, and TB-grown cultures yielded attB plasmid DNA concentrations that were slightly, albeit consistently worse. But I eventually I tested some lentiviral vector plasmids and finally saw the increase in yield from TB that I had been hoping for. Relaying this to Melissa, she noted she had been doing transformations with (presumably unrelated sets of) lentiviral vectors herself, so these observations had been consistent after all.

Thus, if you get any attB or pLenti plasmids from me, you should probably grow them in LB (attB plasmids) and TB (pLenti plasmids), respectively, to maximize the amount of DNA yields you get back for your efforts.