A Deep Dive Into DNA Binding

How do transcription regulators bind DNA, and how does this binding in the test tube compare with binding in cells?

There has been a lot of speculation about special conditions inside cells that affect searching and binding by DNA-binding regulators. The fundamental sequence-specific affinity of a protein can be recapitulated in a test tube, (that is to say, "in vitro", even though test tubes are all plastic these days, not vitreous), but the cytoplasm / nucleoplasm is a different environment. The highly crowded nature of the environment is one issue. Another are specific factors like nucleosomes, chromatin structure, and the many other proteins that might compete with the binding protein on the DNA or alter the DNA shape, such as with twisting, bending, or chemical modifications. There are a lot of possible variables, and it has also been difficult to even assess quantitatively how well binding in the test tube compares with binding in cells.

A recent paper tries to delve into these issues in great detail, with rather confounding, if interesting results. I should say right off that this is a poorly written paper, with the kind of florid over-indulgence of figures that reminds me of my first poster. Anyhow, there were a few interesting points.

The regulator (or "transcription factor" as is historical / customary in the field) that they choose for this work is KLF1. This a hugely influential regulator that orchestrates the maturation of erythrocytes from their progenitor cells, among other tasks. Knockouts of this gene leave mouse embryos dead at around 14 days, with profound lack of hemoglobin. Red blood cells undergo amazing development, ramping up hemoglobin production while they cut production of everything else, and finally eject their nuclei to become the streamlined and shapely pucks of oxygen-carrying goodness we are familiar with. KLF1 is part of a large family of proteins (that is to say, proteins that originated by accidental duplication from one long-ago parent through the history of life) that bind to DNA via three zinc fingers, shown as the gray bars in the diagram below. Zinc fingers are a structure that is small, binds to about three bases of DNA, and, as its name suggests, contains a zinc ion that organizes its compact structure. For a 3D look at a representative zinc finger structure in detail, go to the protein data bank.

Diagram of the protein domains found in SP/KLF family members, in humans. While these regulators all share a highly similar DNA-binding core of three zinc fingers, (gray bars at right), they are otherwise a riot of ancillary protein domains, which are generally involved in contacting other proteins of the transcription apparatus, forming cooperative complexes to either activate or repress transcription.

So KLF1 binds to a site of about nine informative bases, though these authors go on to show that a couple of extra bases on the sides are also significant to binding affinity. They do a thorough in vitro scan of all the sequence variations of KLF1's target sequence, coming up with a quantitative presentation of its "consensus", or ideal binding sequence, shown below. This sequence is rich in C's obviously, and heavily biased against G bases. 

KLF1 binds to this "consensus" sequence, via its three zinc fingers, as noted at the top. Each position of the binding sequence has its preferred and non-preferred bases, as indicated by the colored letters and their heights. 

They find that KLF1 has a pretty short residence time on its site, of about 2 minutes, thus is easily competed off by other DNA or other KLF1 proteins. Additionally, they look over the flanking DNA and find that not only do the two bases on each side of the consensus DNA sequence carry a lot of weight (presumably by directly binding KLF1 at its edges), but more distant flanking DNA has influential effects as well. These effects have a strong 10.5 base periodicity, indicating that they occur on one side of the DNA- the same side as the target binding site. But the preferred sequences at these distant positions are the *=opposite of the binding consensus, tending toward A and T. After considering a few hypotheses, the authors settle on a model where KLF1 searches for its binding site by hopping around on and near the DNA. The more semi-similar sites there are nearby, the more time this search takes, so it is better to bias the nearest locations against the consensus sequence.

But the main question they are asking is.. do all these in vitro parameters reflect also what is going on in vivo, in relevant erythroid human cells? For this, they use artificial DNA constructs with multiple KLF1 binding sites, and a methylation-protection technique where the bound protein physically "protects" its DNA site from methylation by an introduced enzyme (not to be confused with traditional DNA footprinting). These methylation sites are then read out by a complicated sequencing method, and displayed horizontally as shown below. Since the residence time of KLF1 is so short, the experiment was run as quickly as possible, with two minutes the minimum time point. Each of the KLF1 consensus sites (teal blocks, at top) were clearly protected from the methylase, while portions/lanes in between (15 bases long) were not, showing that these sites appear to have been specifically bound by KLF1 or one of its very close family members. This effect wore off quickly as KLF1 dropped off the DNA, (likely due to death of the cells/system they were working with, due to the methylation technique), and was hard to discern at fifteen minutes. So they conclude that the residence time of KLF1 is very similar between laboratory and in-cell settings. Incidentally, they show also that the consensus, flanking and distant flanking effects are also operative in cells, and thus the raw sequence-specificity of KLF1 binding to DNA is similar in both settings. 

"Footprinting" of KLF1 sites in cells. The DNA region is spread horizontally in these depictions, on the X axis, and white marks note methylation events, or non-protection from the methylase. The 15 bp borders between the KLF1 consensus DNA binding sites are white, while the sites themselves are dark or protected. In F, the control with mutated consensus KLF1 sites, there is protection all over the DNA, which the researchers interpret as a stable nucleosome plopped on this site instead of the specifically bound KLF1.

But suppose fewer KLF1 sites are used, instead of seven sites? What then? In vitro, binding of KLF1 is strictly linear with motif number (below). In vivo, on the other hand, binding is very poor to one or two sites, and only rises once three or more are available. The authors interpret this as showing competition against other binding proteins, principally nucleosomes (as above, right). And they also argue that this is not due to direct binding by the multiple KLF1 proteins vs the nucleosome, but is mediated by some other proteins (aka factors, in green, below), that bind to KLF1 and help to budge off local nucleosomes. KLF1 is a so-called "pioneer" factor which has this power, doubtless due not to its own structure alone, but due to the goons it can call in to help, such as nucleosome-displacing SWI/SNF complexes. 

In the test tube, affinity of KLF1 to its site is linear with the number of sites.

On the other hand, in cells, KLF1 has little occupancy until there are three or more sites available to bind (B, C). In D is shown the author's explanation, which suggests that large nucleosomes typically block the site and can only be evicted if several KLF1 binding sites and proteins cooperate to bring in some extra machinery (green).

Lastly, does all this work allow these researchers to predict where KLF1 binds within cells on its own? Not at all. They publish a fascinating analysis of the correlation between observed locations of KLF1 binding at its normal sites in normal cells (via the ChIP method) versus predicted sites in the genome from their in vitro analysis. And the correlation is pretty much zero (below). So KLF1 is only one actor, if an important one, in a flurry of activity going on in the nucleus, many aspects of which can supervene over its raw DNA binding preferences. Trying to predict all this, with an AI or other model, remains, as yet, quite out of reach.

Correlation between actual binding locations of KLF1 in normal cells (Y axis) vs predicted binding sites (X axis). Note the lack of correlation.

• Maybe things aren't so bad.