Transformants Produced!

I'll set aside the hack bioinformatics posts for now and give an update on my transformation experiments... We’ve gotten access to a few lanes of Illumina GA2 sequencing for some preliminary studies, and right now I’m drying the genomic DNA samples that we plan to sequence.

The notion is to sequence several independent transformants of Haemophilus influenzae to get some idea of how much donor DNA taken up by cells finds its way into recipient chromosomes. This pilot study will go a long way in informing our planned large-scale experiments and give us a chance to learn how to handle the data.

Here’s what I did to produce the material...
...some transformations, of course!

First, I PCR amplified the gyrA and gyrB alleles from the MAP7 strain (which confer nalidixic acid and novobiocin resistance, respectively). MAP7 is a derivative of our recipient strain KW20 containing several point mutation that confer antibiotic resistances.

I used these PCR products to transform our donor strain 86-028NP to provide two selectable markers in the donor. I’ve been calling this strain 1350NN.


Then I extracted DNA from this strain and used it as the donor DNA to transform KW20 competent cells. By selecting for one or both markers, I can ensure that clones chosen for DNA extraction and sequencing were indeed derived from competent cells that got transformed.


Our baseline expectation is that there will be a large segment (10-50kb) of donor alleles in the transformants at selected sites and 2-3 additional large segments elsewhere in the genome.

Originally, we were going to do this transformation with only a single marker, but we realized that having two would allow us to measure the frequency of co-transformation.

Here’s what the transformation rates looked like:
I used MAP7 DNA as a donor as a control. Since MAP7 is more closely related to KW20 than 86-028NP, it is perhaps unsurprising that transformation rates were higher when using MAP7 as donor.

As for co-transformation, here’s the frequency of double transformants versus expected:
That corresponds to ~25-35% of the cells in the competent cell preparation actually being competent. I’ve been wracking my brain unsuccessfully trying to figure out how to do a back-of-theenvelope calculation as to how many independent molecules we expect to transform any given recipient. I just can’t figure out a concise or reasonable way to do it. Suffice it to say, I estimate a minimum of 20 kb of donor DNA in each transformant (1% of the genome), up to perhaps 100 kb (5% of the genome).

There’s only one way to find out… (continued...)

Mismatch repair versus Segregation

Things have gone swimmingly with my strain construction plans, and indeed today I am extracting DNA that will presumably be sequenced. To recap, I made a couple of clinical isolates (86-028NP and PittGG) resistant to novobiocin (NovR) by transforming them with a bit of left-over NovR allele of the former postdoc. I then isolated the new strains’ DNA, and used these to transform the standard KW20 Rd strain. By selecting for NovR, we can be certain that the clones I pick took up DNA and recombined it into their genomes.

One technical issue arose, however, which required a little bit of thought: Should I have streaked for single colonies? I.e. once I had my transformants, it might be a good idea to streak out individual colonies to make sure I purified them away from any background or broke apart any doublet colonies. No big deal, but after talking it out with Rosie, we decided to skip it. Why? So that we might get lucky and distinguish recombination followed by mismatch repair versus recombination followed by segregation. In the following figures, I illustrate what I mean by this…

In this first one, the donor DNA is shown in red, and the recipient chromsome is shown in two colors, blue and green, to distinguish the strands. The lowercase letters indicate polymorphic sites in the donor genome. Little a is meant to be the selectable marker, in this case an allele of gyrB:
Donor DNA is incubated with competent recipient cells, and recombination of single-stranded DNA leaves patches of heteroduplex in the genome, shown as small red patches on either the blue or green strands.

After this, the cells have a chance to perform mismatch correction to fix any heteroduplex. I select for cells that have little a by plating to novobiocin plates, so only cells that end up a/a will survive an make colonies. (I am not going to show any examples of restoration repair, in which donor alleles are repaired back into recipient alleles… this will be invisible in our analysis.)

In the below example, I show the A/a and B/b heteroduplexes getting mismatch repaired into a/a and b/b, whereas C/c and D/d heteroduplexes remain unrepaired (they escape correction). What will happen in such as case is the generation of a sectored colony, in which (in principle) half the cells would have one genotype and the other half a different genotype:
In the above example, the original transformant segregates the c and d alleles into different cells, while a and b end up in all cells. If the whole resulting colony is grown up and sequenced, the a and b alleles will be the only ones observed, while at the other two loci, there will be a mix of C and c, along with a mix of D and d. We wouldn’t be able to tell “phase”, i.e. whether c and d were on the same or different chromosomes, unless we did streak for singles and the sequenced several clones. But as a first pass, this could be a really interesting analysis. It will also serve as excellent proof-of-principle for our more intense sequencing plans.

There is a caveat, however, which means we need to get a little bit lucky to be able to distinguish these phenomena (mismatch repair versus segregation). We won’t see two different genotypes, if the A/a heteroduplex isn’t mismatch corrected:
The issue isn’t that segregation didn’t happen; the problem is that one of the segregants dies under selection for little a.

Thus, if we see a pure genotype, then either all mismatches were corrected, or our selectable marker didn’t mismatch correct.

When I pre-screen my transformants to make sure they’re not spontaneous mutants, I might be able to pick a colony where I think segregation is occurring. If I get the standard sequencing traces back and see mixed bases in the chromatograms that corresponde to donor and recipient alleles, I’ll pick that kind of clone for sequencing…

One sort of sad note here, in terms of the more distant future, is that mismatch repair mutants, which should be quite useful for understanding transformation, will need to be transformed without selection if we hope to recover isolated segregants from individual transformants. (continued...)

E-Z Strain Construction

As preliminary data for our genome-wide recombination analysis (outlined in this post from Rosie), we want to sequence the whole genome of a single transformed clone in the next couple of months. The idea is to transform our standard KW20 Rd strain with DNA from one of the other completely sequenced strains (probably 86-028NP, possibly PittGG), select a single transformed colony, and sequence its genome.

This will provide us with all sorts of useful preliminary results:

1. Show that we can indeed handle the type (and amount) of data we’ll be obtaining.
2. Estimate the total amount of donor DNA a single recipient recombines (and fixes) into its genome.
3. Estimate the length of recombination tracts (gene conversions) / the strength of “linkage”.
4. Estimate mosaicism of donor and recipient sequences (mismatch repair).
5. Estimate the transformation rates for different classes of single-nucleotide differences (for example, the number of A->T transformation events observed versus the total A->T differences between the strains)

In particular, item (2) will be crucial for estimating the total amount of sequencing we would need to measure transformation rates per polymorphism across the genome. Simple transformation assays with DNA from the multi-antibiotic resistant MAP7 strain suggest that possibly 20-50kb of DNA may be replaced in a single transformant, but this type of analysis is restricted to only a few different sites in the genome and is very roughly calculated.

The analysis of a single transformed genome will still be preliminary with regards to (3)-(5), for which we will want genome sequences for several independent clones. In the future we are likely to barcode and pool independent transformants, since we expect that a single lane of Illumina sequencing will be overkill for a single Haemophilus genome of less than 2 Mb (250X sequence coverage).

Anyways, one issue with producing the material for this first sequencing experiment is that we need to make sure that the clone we select comes from a cell that was indeed competent and did indeed get transformed. Since only a fraction of cells in a competent culture are competent, we would be wasting a lot of time and money, if we accidentally just re-sequenced our recipient genome.

In order for this to work, we need our donor strain to carry an antibiotic resistance marker. By selecting for recipients that become resistant, we can be sure the clone we select took up DNA that got recombined into the genome. (This may also create a bias for donor alleles near the selected site, due to “linkage”.)

To this end, I am doing the following:

1. Made a couple strains (KW20, 86-028NP, and PittGG) resistant to novobiocin. I just did this. It worked like a charm thanks to the former postdoc having a well-organized lab notebook and a well-organized freezer box containing a tube with a NovR allele of gyrB already prepared for me. This was also my first time doing overnight transformations. I couldn’t believe how easy it was: Add a frozen aliquot of cells and some DNA to some sBHI media, let the cells grow overnight, and plate them the next day. There were plenty of resistant colonies this morning.
2. Prepare DNA from the newly produced 86-028NP NovR and PittGG NovR strains. I’ll do this tomorrow from the overnight cultures I just inoculated.
3. Transform KW20 with this DNA. I’ll use competent cells I already have tomorrow, after my DNA prep.
4. Saturday, assuming I have NovR transformants, I’ll pick and grow up some transformed colonies overnight.
5. Sunday, I can prepare this DNA, and that’ll be what we can send for sequencing!

So if all goes well, we should have our material in a few days! Then we wait. Then the real work begins…

(As a side note, 86-028NP indeed appears to already be resistant to another antibiotic, nalidixic acid. I will check to see if this resistance is transformable when I have the 86-028NP NovR DNA in hand.) (continued...)

The Last Straw

Yesterday, Rosie kindly ran her Perl script over the USS construct I designed. The final thing I was worried about was whether or not my design had any USS or USS-like sequences in it, other than the one it's supposed to have. I'd checked the construct for any core USS motifs (5'-AAGTGCGGT-3'), but since we think that the motif is more complex than this, it was important to make sure that there were no extra sequences that got high scores using the USS position-weight matrix.
Fortunately, the construct looks good, so I can go ahead and order the control oligos and have high expectations that they'll work...

Here's how every 32 base pair window over the 199mer looks when scored with the USS PWM:
There's a single prominent high-scoring site right where it should be, and all of the surrounding area scores near background. The USS in the construct has a score (~10^-8) more than 10 orders of magnitude better than the next best sites. There's a slight increase for windows immediately adjacent to the USS, presumably because the AT-tracts in the USS are still contained in those windows. The rest of the construct only has scores at background.

Just to show that these other sites really do represent background levels of USS score, Rosie also ran a randomized version of the sequence:
Nothing better than 10^-18. Excellent. (continued...)

Reverse engineering

Okay, so now that we’ve exposited all the brilliant experiments we’re planning to do while writing proposals, the actual reality of doing the experiments is starting to sink in. We’ve also managed to put down some fairly concrete goals for the next several months.

One of our experiments involves measuring the specificity of DNA uptake by naturally competent H. influenzae for fragments containing “the genomic USS motif”. The H. influenzae genome contains an abundant sequence motif, and fragments bearing it are taken up better than fragments that don’t. This “uptake signal sequence” was originally defined by its functional role in DNA uptake, but has since been characterized mostly by bioinformatics, with no direct uptake specificity data. The limited data from previous lab members suggests only an imperfect correspondence between the properties of the genomic motif and the specificity of DNA uptake.

The idea, then, is to feed competent cells small DNA fragments bearing a degenerate (highly mutated) version of the USS consensus sequence, recover those that are preferentially taken up, and sequence the resulting pool. USSs are ~32 bases, well within the reach of single-end Illumina reads, if they are positioned properly next to a sequencing primer.

I’ve previously discussed the expected properties of a degenerate USS pool. And though I think we need to consider this more, I will focus this post on the design of other parts of the construct that will allow us to circumvent subsequent sequencing library construction steps. Illumina sequencing uses specific sequences added to the ends of molecules to capture and sequence DNA of interest...

Properties needed for a USS-containing construct, where Illumina sequencing can be directly performed to sequence the USS:

(1) SIZE: ≥200 base pairs, dsDNA. 200 base fragments with USS are efficiently taken up by cells, and the size is sufficient for efficient cluster synthesis and sequencing using Illumina’s Genetic Analyzer.
(2) CAPTURE SEQUENCES: One end of a strand of each fragment needs to be able to anneal to one of the two “Flow Cell Primers” (FP) in the Illumina flow cell, while the other end of the same molecule needs to contain the reverse complement of the other FP.
(3) SEQUENCING PRIMER BINDING SITE: The reverse complement of Illumina’s sequencing primer needs to be immediately downstream of the reverse complement of the USS. (This could work the other way, but getting the “sense” USS directly from the sequencing reads seems optimal).
(4) TAG SEQUENCE: The first few (four) bases of each read should be in non-degenerate fixed sequence to facilitate the alignment of the degenerate USS reads.
(5) CONSTRUCTION: After consulting several oligo makers, we learned that we wouldn’t be able to get our degenerate constructs built into an oligo longer than 130 nt. This means that I will need to anneal two oligos together and extend with polymerase to generate a full-length construct.

The first trick was to actually find out what the normal Illumina adapter and primer sequences were. They were available on-line, and I think I’ve mostly reverse-engineered what the different bits do. And think I have a reasonable design:

I’ll order two oligos, one 130 nt and the other 106 nt. (At the end of this post, I will list the exact sequences of each part and some notes.) They’ll have 36 bp of reverse complementarity at their 3’-ends, so that I can anneal them and extend to produce full-length construct.
To illustrate what all the different parts of the construct are for, here’s a color-coded version, for which I’ll schematically diagram the Illumina cluster synthesis and sequence priming.
The key features are that the flow cell primers (FP) are on opposite strands on opposite ends and the sequencing primer (SP) sits adjacent to the USS (with the 4-bp tag at the beginning). I am using plasmid sequence present in the lab’s other USS constructs for the Gaps (1 and 2).

To sequence the 200mer (either before or after recovery from competent cell periplasms), the DNA would be melted and annealed to an Illumina flow cell. Below are shown two different parts of a flow cell surface, where the two different strands of a single molecule might anneal.
DNA synthesis from FP1 or FP2 generates a covalently attached version of each strand.
The original molecule is melted off and washed out of the flow cell, and a special in situ PCR method generates clusters of single-strands covalently bound to the flow cell surface. In each cluster, the strands are oriented in both directions.
Sequencing then proceeds from SP binding sites. In this design, the SP binding site will then read the complement of the USS (with the first four fixed bases), so the actual sequence generated would be the USS contained in the construct.
There are several small details to go over to make sure that this design will work. Because the oligos are so expensive, and the degenerate oligo will be precious, I also plan to buy several non-degenerate oligos corresponding to perfect consensus, randomized, and mutant USSs. These will act as controls for the annealing/extension step that generates the uptake substrates and as controls for measuring saturation curves to optimize the appropriate DNA uptake conditions. I will also be able to do PCR to regenerate the control constructs, while I should probably avoid amplifying the degenerate USS construct for fears of strongly biasing the representation of different sequences.

NEXT UP: Uh oh… What about yields? Dimensional analysis…

APPENDIX:

The different parts of the two oligos:

Notes on my reverse engineering:

1. FP1 (25 nt): Composed of putative 20mer FP1 + first 5 bases of one adaptor (calling it A)
2. SP1 (33 nt): Sequencing primer for single-end Illumina runs. Includes the 13 bases of the normal adaptor that normally results in a 13 bp inverted repeat palindrome on either side of adapted DNA fragments.
3. USS (36 nt): Includes 4-base tag (ATGC) upstream of a 32-base genomic Gibbs consensus sequence with a set level of degeneracy at each position.
4. G1 (36 nt): Additional sequence from pGEM7f ,corresponding to the portion of the spacer region where the two oligos are intended to anneal.
5. G2 (46 nt): More sequence from pGEM7f, corresponding to the spacer region only on one of the two oligo.
6. FP2’ (23 nt): Composed of the complement to the 20mer FP2 + first 3 bases of the other adaptor (calling it B).
7. Total length after annealing and extension is 200 bases, where the USS is located from position 63 (after the spacer) to position 94. In the flow cell, the use of SP1 as a sequencing primer should read the complement of the USS sequence, so the actual sequence obtained will correspond to USS (with the first four bases always ATGC).

(continued...)

Eating chromosomal DNA fragments

Haemophilus influenzae cells will take up closely related DNA from the environment quite efficiently, when they are made naturally competent by resource limitation.

Previously, I had done some experiments using sonicated chromosomal DNA of two different size distributions. The take-away lesson was that, for a fixed DNA concentration, larger fragments were taken up better than smaller fragments. This could be due to two non-exclusive reasons:

1. Larger fragments are more likely to contain an uptake signal sequence.
2. The uptake machinery is saturated when I used the smaller fragments, since there are more fragments per unit mass.

I am not certain of the best way to measure the relative contributions of these two factors to the observed disparity in uptake, though I’m pretty sure a saturation curve would be the way to start things off, that is measuring the amount of uptake over a wide range of DNA concentrations.

But first, and more to a practical concern for our sequencing plans...

I repeated this experiment, but also prepared total DNA and periplasmic DNA (by the slick method of Kahn et al) to make sure that I could cleanly recover chromosomal DNA fragments trapped in the periplasm from bulk chromosomes, as I previously showed for a small USS-containing PCR fragment.

Here are the results of that experiment (in which I provided ~0.5 billion competent cells with 200 ng of end-labeled DNA fragments of two different size distributions, either 1-10kb or 200-400 bp, for 30 minutes):
In (a), the % uptake is clearly better for the larger size distribution than the smaller size distribution. In (b) and (c), I show that I can purify periplasmic chromosomal fragments away from the cell’s chromosome. In (b), the results using the larger fragments is shown, while in (c) the results using the smaller fragments are shown. (I ran gels with two different agarose concentrations to optimize the separation for the two different input pools).

One thing to note is that the size-distribution of DNA between the input and periplasmic preparation were effectively indistinguishable. I looked at traces of these lanes in the Molecular Dynamics ImageQuant software, and they looked pretty much exactly the same. This is a little bit confusing, given the two models discussed above and the fact that fewer small fragments were taken up compared with larger fragments. I might have expected that there would be a bias towards the larger fragments in the periplasm compared to the input, but this was not the case.

Another thing to note is that, unlike when I previously did this experiment with USS-containing PCR fragments, there is still evidence of periplasmic DNA in wild type after 30 minutes. I don’t think this is due to poor washing of free DNA away from the cells, but rather reflects that there had been insufficient time to translocate all of the DNA in the periplasm into the cytosol. There is also the possibility that some of the non-chromosomal DNA in the wild-type samples are indeed cytosolic, which I can’t tell without some way to distinguish ssDNA and dsDNA. (continued...)

Uptake and Transformation with "Biorupted" samples

To get an idea of how uptake and transformation would work with different sized donor chromosome fragments, I took MAP7 DNA and sheared it in a “bioruptor”. I ended up with several samples with different size distributions, three of which I used for a pair of experiments:

LARGE: >40 kb (unsonicated)
MEDIUM: 1-10kb (1 X 10 min sonication)
SMALL: 100-400 bp (5 X 10 min sonication)

My naïve assumption was that % uptake would go down as the fragment size decreased, since fewer fragments would contain “uptake signal sequences” (USS), which have an average density in the genome of ~1kb.

I also thought that transformation rates would also go down for smaller fragments, but would not necessarily correlate that well with uptake, since additional steps of translocation and recombination could also potentially influence the efficiency of transformation. So for example, transformation might drop off more quickly than uptake, if degradation would affect smaller fragments more than larger fragments. (This seemed to be the case in Pifer and Smith, 1985.)

Keeping in mind that these are just one-off experiments and need to be repeated (like pretty much every experiment I’ve reported in this blog), the above predictions look like they’re true, but I’m not certain if my reasons are necessarily correct...

First, I’ll show the uptake data. I end-labeled the MEDIUM and SMALL donor fragments using Klenow and did a simple uptake experiment (comparing total radiolabel to that in cell pellets after 30 min of uptake) using wild type cells and as donors, either MEDIUM or SMALL chromosome fragments, and either saturating (500 ng) or sub-saturating (100 ng) amounts of input DNA per 0.5 ml of wild-type competent cells. Here’s the data:
So clearly, several-fold less chromosomal DNA is taken up when smaller fragments (100-400 bp) are used than when larger fragments (1kb-10kb) are used. As explained above, one reasonable explanation for this is that fewer fragments in the SMALL sample contain USS, so maybe only 1/10 to 1/2 will have a USS, whereas in the MEDIUM sample most fragments will contain at least 1 USS.

But there is an alternative explanation that I’d like to be able to distinguish (but am pretty sure I can’t with this one experiment). It could be that a given competent cell only takes up a fixed number of DNA fragments, independent of fragment size. So since the SMALL sample is composed of ~10-100X more fragments per unit mass, it could be that I’ve simply saturated the system with fragments in the case of SMALL, but not in the case of MEDIUM. This issue was addressed by Deich and Smith, 1980, and they concluded that indeed this was the case (that the number of molecules taken up was independent of fragment size), but while they do mention USS, they do not bring up USS density as a potential reason for their data.

I’d hoped that by doing a second DNA concentration (100 ng) that I might get hints as to which of the two above models is correct (or if they are both correct and both contribute to the observation), but I don’t really think I can say too much without repeating this several times and getting some error bars on that graph. Furthermore, I’m not really entirely sure what the expectations are for the two models. I’ll have to think on this some more....
-----
Okay, what about transformation rates using my “biorupted” fragments? Below are two graphs reporting the transformation rates of the KanR and NovR alleles from MAP7 to KW20 for the three different DNA pools (LARGE, MEDIUM, and SMALL):
(Note: In the case of the NovR/CFU SMALL sample, the number reported is actually the limit of detection, so NovR/CFU(small) is less than 4.4e-6. I didn't observe any NovR transformants for the SMALL fragments, despite having a decent limit of detection.)

First, I'll look at the difference between the LARGE and MEDIUM fragments. Both markers showed ~6-fold decrease in transformation rate in the briefly sonicated sample, compared to the large intact fragments. Possible explanations:

1. Less USS per fragment: I doubt this is a major reason for the difference. While a larger percentage of fragments are expected to contain no USS in the MEDIUM sample, it shouldn’t be that large of a difference, since the mean density of USS motifs is ~1kb.
2. Degradation by translocation or cytosolic nucleases: This seems to be a reasonable explanation. From an old set of experiments using a defined plasmid donor, Pifer and Smith, 1985 estimated that an average of ~1.5 kb of a leading 3’ end is degraded during translocation. Maybe the medium-sized fragments simply don’t survive translocation as well as large taken up fragments.
3. Recombination efficiency: Maybe both the LARGE and MEDIUM fragments make it into the cytosol, but homology search and recombination are much better for larger fragments.

Things look a little more interesting when looking at the change between MEDIUM and SMALL fragments: While the KanR rate only changed modestly (less than 2-fold), the NovR rate went down below my limit of detection. Possible explanations:

1. Distance to USS: The nearest USS to the NovR allele is more than 4oo bp away, but less than 400 bp for the KanR allele: I like this explanation. I really really need to figure out the identity of these antibiotic resistance alleles. We’re pretty sure it’s a mutation in the gyrB gene, but I don’t know the actual change. I looked at gyrB and it does contain a USS core motif and two other core motifs a few hundred bases before the start codon, but the gene is ~2.5 kb, so the actual gyrB mutation could easily be too far away from these USS. When I looked at the putative gene responsible for KanR (the ribosomal S7 gene), there was a single USS near the start, but none within. Again, without knowing the causative lesion, I can’t tell whether this is within the size distribution of the SMALL fragments.
   
2. Differences in degradation rates at the two loci: This is possible. The other thing these data suggest is that, despite the ~1.5 kb average degradation reported by Pifer and Smith, 1985, there’s still plenty of small fragments that can recombine, since the KanR rates between MEDIUM and SMALL are not really dramatically different.
   
3. Recombination signals: Also possible. And probably the hardest to tell, since the other effects need to be canceled out.

The main take-away (assuming that the results replicate) is that not only do different markers transform at different rates, the change in transformation rate for different sized-fragments also varies for different markers. The underlying reasons for this are probably interesting. So what next? I need to repeat this, but next time I’d like to:

1. Extend this to additional markers to see if this variability also applies to other loci.
2. Measure linkage between Kan and Nov. I’ve previously seen the known linkage between Kan and Nov using large fragments, but would expect linkage to vanish for small fragments when the KanR and NovR alleles never share the same fragment.

And again, I really need to know what the lesions are that are responsible for the MAP7 antibiotic resistances. I’ve looked around a fair amount, but it seems that many antibiotic resistances can be produced by mutations in more than one different gene, so narrowing it down isn’t that straightforward. (continued...)

Dose Response

How hungry are competent cells for DNA? I know that about a billion cells will consume ~65% of 20 nanograms tasty USS-1 fragment, but what if I offer the cells different amounts of USS-1?

To get a better hands-on feel for the DNA uptake process in wild-type and rec-2 mutant competent cells, I did a dose response experiment, where I incubated competent cells with different amounts of USS-1 DNA.

For this first experiment, I used 0.5 ml of competent cell cultures for each sample and did 6 different amounts of USS-1 DNA (12 samples total for wt and rec-2). I didn’t have enough radiolabeled fragment for all of my desired concentration, so I mixed in some cold USS-1 DNA to make up the difference. I let the DNA and cells incubate for 30 mins, then I washed the cells several times and determined the total radioactive counts in the cell pellet and washes to determine the % uptake and total uptake.

Here’s the results:

Total Uptake:

Percent uptake:

Interestingly, rec-2 does better at low concentrations of DNA than wild-type, but worse with high concentrations. The latter could be due to the periplasm getting too clogged with DNA, such that the outer membrane uptake machinery has to work too hard to get more DNA through, while in wild-type translocation of DNA frees up space in the periplasm. But the former (higher uptake in rec-2 at low DNA concentrations) doesn't really make much sense to me. Maybe not all free nucleotides created during degradation at the inner membrane remain in the cell, so that at low concentrations, rec-2 simply holds more label?
(continued...)

Standing upon the shoulders of giants

It really is gratifying to have things work the way they're supposed to. Some kind of bug bit me on Saturday and I came in to see if the periplasmic DNA preparation reported by Kahn et al 1983 would work in my hands. And sure enough it did!

The experiment was much the same as before. I added radiolabeled USS-1 fragments to either wild-type or rec-2 competent cell preps, incubated for 5 minutes, and then either prepared total DNA or did the periplasmic extraction (TE/1.5M CsCl + phenol/acetone, 1:1).

Since wild-type cells will take up the fragment, but also incorporate labeled subunits from degradation of taken up DNA, I can tell if the periplasmic DNA prep managed to exclude chromosomal DNA. But first, I counted the radiolabel present in the different cellular fractions...

This time, about a quarter of the USS-1 fragment added was taken up within five minutes (wild-type: 26%; rec-2: 28%). I suspect these numbers are lower than the last time I did it, because my five minutes was really five minutes (whereas the first time, I think I was 2-3 minutes late).

The extraction: When I collected the aqueous phase, I also collected the organic phase, and the interface between the phases (which should contain the cells minus their outer membranes). I counted the radiolabel in these different fractions as before:
Wild-type cells had label in both the aqueous extract, as well as in the interface containing the cells, while rec-2 had nearly all the label in the aqueous extract. The organic phase had less than 1% rec-2.

But here's the important bit:
Lane 1: Input (1/3, or 4 ng)
Lane 2: Total DNA, wild-type + USS-1 for 5 min.
Lane 3: Total DNA, rec-2 +USS-1 for 5 min.
Lane 4: Peri DNA, wild-type + USS-1 for 5 min.
Lane 5: Peri DNA, rec-2 +USS-1 for 5 min.

The important point here is that in the total DNA extract of wild-type, both intact donor USS-1 and chromosomal labeling are evident, while in the peri-extract of wild-type, there is no chromosomal label.

This means that the extraction I did successfully purified periplasmic DNA over chromosomal DNA. Fabulous!

Now I need to scale this protocol up, and get cleaner DNA (i.e. use RNase), so hopfully I can see this without using radiolabel. If I can really get clean periplasmic DNA with little or no chromosomal contamination, I will move onto doing the "real" experiment with donor DNA made up from sheared genomic DNA of another isolate.

Yay! (continued...)

Building a periplasm prep...

After my failed attempts at doing a large-scale periplasm prep right off the bat, I decided to spend this week going a bit more slowly. I repeated what others have already done successfully using radio-labeled DNA fragments as donors. This means that I can do smaller scale experiments and don't need particularly pure DNA.

And this time the experiments all worked. Here's what I did:

(1) I made competent cells of KW20 (RR722) and KW20 rec-2 (RR622). I confirmed that the wild-type strain transformed normally and the rec-2 strain not at all (or at least below my limit of detection). This confirmed that my competent cell preps were okay, and that the rec-2 strain seems to be correct.

(2) Following the DNA uptake assay protocol of Maughan and Redfield, 2009, I showed that USS-1 is taken up very well, but USS-R is only poorly taken up. To do this, I simply incubated ~12 ng of either radio-labeled USS-1 or USS-R with 0.5 ml of competent cells for 20 minutes, and then compared the radioactive counts in a washed cell pellet compared to the total counts:
Wild type and rec-2 both take up USS-1 well, but USS-R poorly, as expected. But rec-2 seems to take up USS-1 slightly better than wild type. This is also true in the next experiment. This may be significant but could also reflect slight differences in the competent cell prep of the two strains.

Possibly the coolest part of this for me was that I got numbers that were spot-on the former post-doc's numbers (found in her notebook) and older papers describing % uptake. That is: ~65% uptake for ~20 ng / ml of cells. This was very encouraging to me.

(3) I repeated the uptake assay described above using ~12 ng USS-1 donor DNA and incubated wild-type and rec-2 cells for either 5 or 60 minutes. This gave results similar to those shown above:
Most uptake was finished after only 5 mins, though additional incubation increased the level of uptake. The results were nearly identical for 60 min incubation as for 20 min incubation, so I don't need to do it for so long.. The rec-2 strain again showed slightly more uptake at all time points.

After this, I took it a step further: I also extracted the DNA from the cell pellets and ran them out on a gel. I also included the input donor DNA as a control. I dried down the gel and exposed it to a phosphor screen. This is what the gel looked like:


Lane 1: Donor DNA (50% of input; ~6 ng)
Lane 2: Wild-type + USS-1 for 5 min. Total DNA.
Lane 3: Wild-type + USS-1 for 60 min. Total DNA.
Lane 4: rec-2 + USS-1 for 5 min. Total DNA.
Lane 5: rec-2 + USS-1 for 60 min. Total DNA.

Alright! That's exactly what I hoped for! (Well, not quantitatively between lanes: this was a sloppy first experiment.) The gel shows that the natural competence phenotypes of the two strains: wild-type and rec-2.

Intact uptake DNA is the smaller (lower) band, while chromosomal DNA is the high molecular weight species. In wild type, donor DNA gets degraded and nucleotides can be incorporated into the chromosome over time. (Importantly, the labeling of the chromosome is NOT from transformation, but from incorporation of degraded nucleotides into the genome by DNA replication.) In rec-2, the radio-labeled donor DNA is trapped in the periplasm and isn't degraded. So there is no chromosomal labeling in this case.

This is effectively a repeat of an experiment from Barouki and Smith, 1985.

Next, I'll try exactly the same thing, but I'll also try the extraction from Kahn et al., 1983. If this successfully yields pure periplasmic DNA, then I expect that the extraction will not yield radiolabeled chromosome, even for the wild type sample. If that works, I can work on scaling the protocol up to do a real purification of uptake DNA.

Onward! (continued...)

Imagine it exists, and maybe it does!

Our proposed experiments involve capturing DNA molecules at the different stages of natural transformation. One of the technical challenges we face will be producing a library of DNA molecules that have been translocated into the cytosol. We have some schemes for how we’ll do the purification of donor DNA from the cytosol, but even assuming that this works wonderfully, we still need to turn these into double-stranded DNA. We can’t use a specific primer to the 3’ends of translocated ssDNAs, because (a) we don’t know the exact 3’ ends and (b) it will be a complex mixture.

What to do?

Until now the only thing that had occurred to me is to use random priming of our ssDNA to convert cytosolic ssDNA into dsDNA (shown schematically above), but this approach has several limitations. The biggest problem is that we would only be able to accurately identify the 5’-end of translocated DNA. The 3’-end of the final dsDNA we produce would not represent the 3’-ends of the original ssDNA molecules using random primers. Furthermore, we would not know which end of our dsDNA was the original ssDNA’s 5’ or 3’ end. And finally, we would end up with a highly heterogeneous size distribution, which might complicate sequencing.

How can I circumvent this, get both ends, and know which is which? I need a strategy like RACE. I decided to imagine that a certain enzyme existed that might help me in this endeavor and then see if it actually existed and was already was commercially available. This strategy has worked for me in the past: Once, I’d wanted to know if there were restriction enzymes that only nicked at their recognition sites, so I typed “nickase neb” into Google, and sure enough NEB carries nickases! Go biotechnologists!

This time, I want to tack some type of single-stranded adaptor sequence onto the 3’ ends of my putative cytosolic ssDNAs, so I typed “ssDNA ligase” into Google, and Presto!... Epicentre produces a single-stranded ligase that they call CircLigase. Sweet!

This doesn’t fully solve the problem, since the ligase will normally take an ssDNA and circularize it (since the intra-molecular ligation will usually be favored). This is useful to plenty of folks who are interested in doing rolling circle amplification and rolling circle transcription, but I would rather not circularize my ssDNAs, but would like to favor ligation of an ssDNA adaptor specifically to the 3’-end. This will require a couple of bells and whistles.

If we take our ssDNA and then treat it with a phosphatase, we can rid the 5’-end of its terminal phosphate and both block circular ligation, as well as ligation of our adaptor to the 5’end. If our adaptor oligonucleotide also has a protected 3’end (not sure how to do this... an oligo with a terminal dideoxy nucleotide?), then we’d block the ligation of the adaptors to each other and force ligation only in the orientation we want (5’ of the adaptor to 3’ of the target).

Then, using a primer complementary to the adaptor, we can convert full-length ssDNA into dsDNA. Furthermore, the adaptor marks the original 3’ end of the fragment, so we can give a polarity to our cytosolic fragments. Here’s the scheme:

Afterwards, of course, we’d need to either amplify this product or de-protect both ends, so that we could ligate sequencing adaptors to the mixture.

This plan just might work, and I could make sure it works using defined substrates, rather than precious (as well as non-existent) cytosolic DNA fractions. The main thing I can’t think of off the top of my head is getting a hold of an oligo with a protected 3’-end (preferably reversibly so).

UPDATE: Looks like at least some oligo companies can include dideoxy bases in oligos. Awesome. This is not quite as ideal as a reversible protection of the 3' end...

UPDATE 2: Uh oh. How to amplify the product? There's no primer sequence at one end... This could involve a phosphorylation step and a ligation of a normal adaptor to that end? That's an extra unfortunate step. Also, the adaptor sequences will eat into the sequence read length, but that should be acceptable, since we only need to get tag sequences.
(continued...)

Happy (Belated) Canada Day!

(Image: The Canadian-built robot arm attaching the space shuttle docked to the Hubble Space Telescope with the Earth in the background.)

Oh yeah, and my second attempt at preparing periplasm DNA was... inconclusive. But it was pretty interesting to try out. In particular, the TE/CsCl/phenol/acetone extraction was quite compelling visually, involving small bubbles breaking up and reforming. I need to start these experiments out at a smaller scale.

And luckily, we've received radiolabeled dATP, so I can do some more sensitive and controlled experiments next week. The use of radiolabeled uptake fragments will be significantly more sensitive and allow me to use small cultures and follow small amounts of uptake DNA.

Once I've got a functioning uptake assay, I can work out the best purification method and scale up from there.
(continued...)

Periplasm Prep Planning II

I tried a modification of a periplasmic protein prep to try and purify uptake DNA, which didn't work. There are several possible reasons why the experiment might not have worked, but one simple reason could be that I failed to dissociate DNA from the membranes and cells when I did the chloroform extraction.

I know! Maybe I should try an extraction that has already been used for purifying uptake DNA...

Kahn, Barany, and Smith (1983) PNAS 80:6927. Rather than describe the paper at length here, I just want to show Table 1 and Figure 4b, which relate to my extraction plans:

The first two columns describe the extraction conditions (rows 1-5). Competent cell cultures were incubated with a radiolabeled plasmid and pelleted after DNA uptake (5 or 60 min). Cell pellets were then resuspended in the indicated aqueous and organic solutions (columns A and B) in a 1:1 mixture, gently mixed, centrifuged to separate the phases, and radioactive counts in each fraction were measured.

The remaining columns indicate the relative amount of uptake in the different fractions and the identity of the radiolabeled DNA, either transformed into the chromosome (C) or still a double-stranded donor DNA molecule (D).

In the fourth condition (row 4), the aqueous phase consists of mostly donor DNA! So chromosomal contamination is in the pellet, and the desired donor molecules are in the aqueous phase. Sounds like a scheme. That’s what I’ll proceed with tomorrow.

Why not condition 1, just TE and phenol? Looks good, right? Because of Figure 4B:

The bottom line is that the phenol condition degraded the donor molecules (lane D), whereas the phenol/acetone condition did not (lane I). Here’s the gory details:

Lanes A-D describe phenol extraction of intact donor DNA molecules (Table 1, row 1):
A: input plasmid donor molecule.
B: total DNA from cells 4 min into uptake.
C: DNA extracted and dialyzed out of the pellet.
D: DNA extracted into the aqueous layer (TE).

Lanes E-J describe the phenol/acetone extraction of intact donor DNA molecules:
E: input again.
F: input cut with HindIII.
G: total DNA after 8 min uptake.
H: same as G, but digested with HindIII.
I: phenol/acetone extracted DNA after 8 mins.
J: same as I, but digested with HindIII.

The point of the HindIII digestion was as an additional test for whether molecules were donor or chromosomal. Chromosomal DNA is resistant to HindIII (this being Haemophilus influenzae after all), while donor DNA is not. Also, the HindIII digests show that the recovered DNA is double-stranded, since ssDNA won’t get cut.

Condition 4 it is, then:
Aqueous: TE/1.5 M CsCl
Organic: phenol/acetone, 1:1

That's what I'll try next.

Hmm, I’ll have to remember how to clean the DNA of CsCl after the extraction...I seem to remember doing something in particular at one point... (continued...)

Periplasm Prep

UPDATED BELOW

Experimental plan for the day: Medium-scale periplasm prep test-- to purify double-stranded DNA in the “protected state” (the periplasm).

I have two PCR products: (1) a “good” uptake sequence USS-1, and (2) a “bad” uptake sequence, USS-R . I want to compare their uptake into rec-2 cells, which can bring DNA through the outer membrane, but not the inner membrane. This means that if I can specifically enrich USS-1, but not USS-R--and can see the difference in a gel-- then I’ve got a functioning periplasmic DNA prep. Naturally, it’ll probably take several attempts to get working...

I will use a modification of this paper and see if it nets some DNA where it should be. In outline, I’ll: Add chloroform to washed cell pellets. Soak. Extract periplasm with TE. Clean and concentrate. Run on a gel.

Based on other studies with radiolabeled USS-1 uptake, I expect that for 20 ng added to a 1 ml culture, ~50% will be taken up. To see uptake DNA without radiolabel on a gel and for reasonable controls, I will need larger cultures of competent cells than I aliquoted and froze last week.

Here’s my protocol so far:
1) Defrost two tubes of rec-2 (0.3 OD/ml aliquot) into fresh sBHI@37 (2X25 ml); wait ~2-2.5 hrs.
2) At OD600=0.3 / ml, transfer cells to M-IV by filtration.
3) Incubate 100 min @37 to induce natural competence. (negative control: frozen tube of rec-2 (0.1 OD/ml) into fresh sBHI (25 ml).)
4) Split cultures 2X and incubate with 20ng 222bp PCR fragments (USS-1, USS-R, none) / 1 ml M-IV culture (~10^9 cells) for 15-30 min @37, DNase I, EDTA to kill DNase I and other nucleases. Also add USS-1 to non-competents.
5) Spin, wash pellet 3X PBS, chloroform (20-40ul), incubate 20 min @RT (chloroform pellet DNA extraction?, save washes).
6) Extract with 100-200ul cold TE, proteinase? RNase?, p/c extraction, PCR clean-up column (or ppt?) to concentrate.
7) 1.2% agarose gel. Lanes:

Size standard
USS-1 input (2X dilution)
USS-R input (2X dilution)
rec-2 + USS-1 -> chloroform extract
rec-2 + USS-R -> chloroform extract
rec-2 + no dna -> chloroform extract
non-competent rec-2 + USS-1 -> chloroform extract

UPDATE:

Didn't work. A few little mishaps aside (mainly that the chloroform and cells really didn't mix well), I got no USS out of the prep, but did have a fair amount of chromosomal contamination. So clearly, I didn't really get the periplasm specifically, but since I didn't see any USS come through, it may also be that my competent cells weren't really.

I'll try to go through this again tomorrow, but instead of going straight for the periplasm preparation, I'll just lyse the cells, extract the DNA, run it over a mini-prep column, and run it on a gel. I'm not going to worry about the periplasm specifically, but simply that the cells are taking up DNA. When the radiolabel shows up, I can repeat the uptake assay the lab has typically done.

(continued...)

Plan for the next few weeks

One proposal down, one to go... The next one isn’t due until August 8th, so I’ve got just over a month to get it done. This time, however, I am going to manage my time better, since I need to get some preliminary data and still keep learning how to use a computer.

So here’s my plan for the next several weeks:

(1) Work on the proposal for a limited time each day (~1-2 hrs). I’ll start by developing a detailed outline of what I want to say and the order I want to say it, rather than leaping straight into writing. Based on my experience with this last one and in the past, I find I am an extremely inefficient writer (both with my time and with my words), so hopefully I can improve by having more focused daily goals.

(2) Work on the computational stuff only 1-2 hrs per day. Still need to fix the browser to display the Hin genome. Still want to work out the best way to align the genomes and report differences... particularly enumerating structural variation (non-SNPs). I also need to keep a mind towards what file formats I expect to get from sequencing. It might be particularly useful to try and simulate the kinds of results I might expect from sequencing periplasmic uptake DNA, etc.

(3) The rest of the time will be dedicated to lab work. The priority is to use defined fragments (USS-1 and USS-R) to work out a periplasmic DNA purification protocol. I’ve got cleaned amplified USS-1 and USS-R fragments, and I’m making competent cells of wild-type and rec-2 today. I tried to grow up a pilA mutant to use as a no uptake control, but something was wonky with the strain. All I need now is label. And a calibrated Geiger counter. I’ll get these things done today.

(The image above was made using the Mac-specific application GenomeMatcher. It represents a BLAST alignment between KW20 and 086-28NP across an interval containing several inversions. It also has a bunch of useful-seeming utilities that I'd like to figure out. Now if I could just get it to use my MUMmer program, like it’s supposed to...) (continued...)

As easy as that? Nahh...

For one of our planned experiments, I want to purify periplasmic uptake DNA away from chromosomal DNA in a clean efficient manner. There are likely several good ways to do this, some of which may be relatively complicated. But purity will be very important for our downstream sequencing plans, so complications are okay.

Nevertheless I did a silly little experiment today to see what kind of size bias our in-house GenElute columns from Sigma have...

The columns are based on DNA adsorption to silica under high salt conditions and elution under low salt. However, larger DNAs will have a difficult time eluting off of the column, even under low salt. That’s why the manufacturer states that the columns are only good up for up to 10 kb fragments.

The DNA I’ll feed to cells will be of a discrete size distribution much smaller than chromosomal DNA, so I simply mixed genomic DNA with DNA size standards and ran them over the column. Here’s the results on a 0.6% gel:
Lane 1: 1-kb ladder alone.
Lane 2: INPUT: MAP7 + 1-kb ladder.
Lane 3: OUTPUT: the input run over a silica column with high salt.

Lane 4: lambda ladder alone.
Lane 5: INPUT: MAP7 + lambda ladder.
Lane 6: OUTPUT: the input run over a silica column with high salt.

Lane 7: MAP7 DNA alone.

It looks like the large genomic DNA fragments were pretty efficiently cleaned away from the smaller ladder fragments. The largest Lambda fragment is ~23-kb, and it seems to have been depleted quite a bit as well. Some smaller sheared genomic is clearly coming through, though, as can be seen when comparing lanes 1 to 3 and lanes 4 to 6.

I don’t think this is really enough size bias for our purposes, but I’m really quite surprised at how well it worked, so maybe I’m just being pessimistic.

I wonder how well this will work in real life. Assuming all our ladder fragments were efficiently taken up by cells into the periplasm, the association of the uptake DNA with the membranes is a major concern. If the uptake DNA is only loosely associated with the membranes, then a standard plasmid mini-prep may very well work quite nicely. Since most of the chromosomal DNA will pellet with the other cellular debris and lysed membranes, the column would then take care of most of the contaminating large molecular weight DNA.

Hmmm... I need some real uptake fragments, so I can try this with cells... (continued...)

Congression versus linkage

Yet again, I did a transformation of Haemophilus influenzae cells with slightly variant H. influenzae genomic DNA. I fed MAP7 DNA-- containing several antibiotic resistance-conferring mutations-- to KW20 competent cells (RR722). I used my third competent cell prep for the third time (experiment 3-3), using frozen stocks. Things looked pretty good, and now I’ve got some real co-transformation numbers to play with to distinguish “congression” from “linkage”...

This time, I selected for four different markers: Resistance to Kan, Nov, Spc, and Nal. As expected, last week’s failure with Spc was due to a mistaken antibiotic concentration. Here’s what the transformation frequencies for each independent marker looked like:

Apparently, all four mutations in MAP7 are point mutations. The good news is that there is indeed variation in transformation rates (~4-fold); the bad news is that the rates I’m getting will require much greater than 10,000X sequence coverage in our planned genome-wide experiment. I may very well need to turn to older methods involving blood in the media to see if I can get rates substantially higher... Or possibly a hyper-rec mutation in the recipient strain.

While Kan and Nov are tightly linked, the other two are unlinked. I should be able to distinguish “congression” from “linkage” by looking at co-transformation rates. I decided to look at co-transformation of the Kan marker relative to the other three, rather than make every possible kind of antibiotic plate for the four markers (which would be 24 kinds of plates).

Here’s what the observed and expected rates of co-transformation looked like (where “expected” was calculated as the product of the independent transformation rates and the ratio of obs/exp is indicated by the number above each pair of bars):
Indeed the co-transformation rate of Kan and Nov dramatically exceeded the expected rate, relative to that of Kan versus Spc or Nal. This is what we expect for linked markers. So the obs/exp ratio I’m seeing for KanSpc and KanNal are presumably due to “congression” rather than “linkage”. That is, not all cells are equally competent in a culture, so I see excess co-transformation as an artifact.

However, if we use the measure Cf to calculate the fraction of competent cells in a culture, we arrive at different answers depending on whether we use the KanSpc or Kan Nal rates.

So, for some definitions (as per Goodgal and Herriot 1961 and others):

If markers behave totally independently:
f(ab) = f(a) * f(b).

Since they don’t, we can calculate the fraction of competent cells as:
Cf = f(a) * f(b) / f(ab).

But then, for two different pairs of unlinked markers:
Cf (KanSpc) = 41%
Cf (KanNal) = 18%

So something more is going on here, since we’re getting different fractions of competent cells, despite it being only a single culture. Thus the assumptions required for the Cf value to work are not entirely valid.

One explanation for this was put forward by Erickson and Copeland 1973, who observed differences in congression for different sets of unlinked markers in B. subtilis. They showed a relationship between co-transformation rates and the position of markers relative to the origin of replication. Thus, co-transformation rates may be influenced by whether or not the transforming markers are recombining into the recipient chromosome before or after the replication fork.

I’ll need more information about the exact identity of the markers I’m using to examine this model with these data. It also would’ve been nice in this case to have SpcNal co-transformation rates.

As an aside, if competence is maximal during DNA replication, this lends support to a conflated DNA repair/food hypothesis for natural competence. Nucleotides are needed during DNA replication, and DNA that’s taken up during this period could serve to faciliate DNA replication, or maybe DNA repair...

-------
A couple other notes:

Now that I’ve done three experiments with the same competent cells, I can look at how reproducible I am. For exp3-3 and exp3-2, I used frozen stocks, while exp3-1 used fresh cells:
Not stellar, but it looks to me that fresh is better than frozen.

Another note: I might be able to increase relative transformation rate for the genome-wide experiment by selecting for a marker right away. This creates some problems, but it allows me to remove “incompetent” cells from the population and focus only on those cells that were actually able to take up DNA and be transformed, possibly significantly improving observed transformation rates:
Of course, tightly linked markers will look artificially high, but I’d get 2X the Spc transformants and 6X the Nal transformants under this regime. I’ll definitely need to understand congression better, as well as the problem of dead cells before seriously considering this for the bulk transformation experiments.

Another (probably better) possibility would be to somehow fractionate transformable cells from others in a competent culture as has been done with renografin gradients in B. subtilis. (continued...)