Is there DNA in oreos?

I have to weigh in on this.

I spend a lot of time discussing the idea that bacteria can use DNA as a source of nutrients, and audiences are always surprised when I show this graphic and point out that DNA is ubiquitous in our foods.  And these are scientifically sophisticated molecular biologists and microbiologists.

So it's not at all surprising to me that 80% of the general public would check 'Yes' when asked, in a set of survey questions about food labelling and regulation, whether foods containing DNA should be labelled as such.  Instead of laughing at their ignorance we should think about how much expert knowledge is needed to evaluate this issue.

Many people, if guided by a series of prompting questions, could figure out that there's probably some DNA in at least some natural foods. But would you expect someone who hadn't taken high-school biology, or took it a long time ago, to know the answers to any of these questions?

• Is there DNA in meat?
• Is there DNA in leaves?
• Is there DNA in potatoes?  In rice?  In noodles?
• Is there DNA in fruit?  What if you don't eat the seeds?  In fruit juice?
• Is there DNA in beer?  In wine?  In scotch? 
• Is there DNA in flour?  In butter?  In olive oil?  In oreos?
• Is DNA destroyed by being cooked?
• Does DNA break down (like some vitamins) when food is stored?
• Does DNA dissolve in water?

RNAseq success!

The sequences are back for our big RNAseq project, and the big good news is that the RNA preps were of good enough quality to give useful sequences for all the samples!  Thos was very much in doubt, because the Bioanalyzer characterization of the RNA samples showed almost no detectable mRNA-sized molecules in the samples we tested.

Now we have all this data, we need to decide how to analyze it.  It's not just a big dataset but a very rich one since the samples differed in what can be considered to be three independent directions, all of which are underlain by rich sets of biological information about phenotypes and molecular events.

1. Each sample was in one of two different culture media, either rich growth medium (supplemented brain-heart infusion, sBHI) or the competence-inducing starvation medium M-IV.
2. Each sample is part of a time course, either three different cell densities in sBHI or four time points of a culture transferred to M-IV.
3. Each sample has a specific genotype: wildtype, knockout mutations in well characterized competence-regulating genes (sxy or crp or cya), mutations that cause hypercompetence (sxy-1, murE747 or rpoD753), and other mutations that affect competence by unknown mechanisms (knockouts of hfq and of one or both members of the mysterious toxin/antitoxin system
4. Most samples have one or two replicates, from independent cultures usually on different days.

Ideally we would first characterize the data quality of each sample, and decide if we need to apply any constraints to its use.  Then we'd do a very meticulous analysis of the wildtype cultures to identify the genes that change when cells become competent, followed by analysis of the sxy and crp/cya knockouts to identify the genes that are specifically responding to these regulators.  This would let us identify all the genes we know we should pay attention to when looking at the effects of the other mutations.

But I don't have a regimented team of minions to do exactly what I tell them.  There will be several of us working on this data set, with different skill levels and research goals.  So here's my tentative plan to keep us at least informed about what each other is doing.

Group blog: I've set up a group blog on Blogger, called The Sense Strand (great name, right?).  Each of us needs to post there to tell the others what we've done and what we've learned.  These posts should be in plain English, this is not a place for data files or code.

Gene-info: We have a big table of information about the known competence genes, and I'm going to convert this into a Google Docs spreadsheet that we all can edit, adding new genes and new information as we develop it.

Shared data files: We've created a shared folder on Google Drive, where we all will post copies of the useful data files we generate.

Code repository:  Finally, I've just learned how to create a shared code repository on GitHub (I'm doing the short Coursera course A Data Scientist's Toolbox, in preparation for their short R Programming course.)  We'll all use this to archive copies of the code we use to do our analyses.

Transformations with dirty DNA

The previous post considers ways to test the effects on transformation of chromosomal proteins bound to donor DNA, by gently lysing donor cells and transforming recipient cells with the crude lysate.  We've now done one experiment trying out some methods.

We used donor cells resistant to novobiocin.  We tried freezing the cells without adding the usual 16% glycerol as cryoprotectant, vortexing them with a drop of chloroform or in 0.0001% SDS to disrupt the membranes, with or without pretreatment with EDTA and lysozyme (0.1 mg/ml, 1/10 the normal concentration) to break down the cell walls.

One question was how efficiently different methods would kill all the donor cells.  If some donor cells remain alive they will form colonies on the selective plates used to isolate transformants, confounding measurements of transformation.  Freezing was surprisingly effective.  Many aliquots of a single 'late-log' culture (OD600 = 1.0) were originally frozen at -80 °C in their normal growth medium.  After thawing, 20-40% of the cells were still viable.  All the treatments (listed below) decreased viability, but most left 10,000 or more viable cells per ml.  But after the various treatments we froze the cells again, this time at -20 °C, and when these were thawed there were no viable cells.  This is good, because freezing/thawing is very easy and we don't expect it to disrupt the associations of chromosomal proteins with DNA.

We had 5 treatments:

1. just chloroform
2. just SDS
3. lysozyme then chloroform
4. lysozyme then SDS
5. just lysozyme

After the various treatments we pelletted the remaining cells and/or debris, and used 10 µl and 100 µl of each sample as 'donor DNA' in transformations of sensitive wildtype cells.  We got LOTS of transformants from all the treated samples, sometimes as many or more than from an equivalent amount of purified DNA.  There were differences between samples but the causes are unclear.

Next steps:

Freezing/thawing:  try just -20 °C with no other treatment.  Does this kill all the cells?  Does it liberate transforming DNA?

Try less SDS plus lysozyme, and try a milder detergent.

To characterize the DNA, try running the treated samples in an agarose gel, say 0.5% agarose so that large DNA enters the gel.  Run samples ± lots of SDS, to see what difference bound proteins might be making.