Friday Feature: Inflammatory behavior

July 16, 2010 § Leave a comment

This video doesn’t exist
This video doesn’t exist

Today’s movies were generously sent to me by Markus Covert (Stanford University).  This is a sampling of a very comprehensive and impressive study of the behavior of NF-κB in single cells, just published in Nature (Tay et al.  2010.  Single-cell NF-kappaB dynamics reveal digital activation and analogue information processing. Nature 466 267-71. PMID: 20581820).  It’s increasingly clear that a number of signaling pathways — calcium, p53, NF-κB  — use spatial and temporal dynamics to deliver complex, nuanced information on the single cell level.  Trying to understand how these pathways are working, or how to manipulate them using drugs, without appreciating that fact is like trying to understand what happened at the World Cup by watching a slice of the action that starts above waist level: you might be able to see when a goal or a near miss happens, but you’d have no idea about what led up to it.

What we’re looking at here is a fluorescent fusion protein of NF-κB being transported into the nucleus in response to the addition of TNF-α, then coming out again.  NF-κB is a transcription factor, so it needs to be in the nucleus to do its job; moving the pre-made protein in and out of the nuclear compartment is a quick way to switch NF-κB-induced genes on and off. NF-κB is usually sequestered in the cytoplasm by a protein called IκB.  When an activating signal, such as TNF-α, comes along, a kinase, IKK, is turned on (I am sweeping a good deal of complexity under the rug here) that phosphorylates IκB, causing it to be degraded by the ubiquitin pathway.  The degradation of IκB releases NF-κB, which then goes into the nucleus and turns on various genes including the one for IκB.

The NF-κB—IκB interaction is thus a negative feedback loop with a fast arm (protein degradation) and a slow arm (protein synthesis), which can lead to oscillations.  (Think about tweaking the taps on your shower when the temperature isn’t right (fast) — and the water taking its sweet time to make its way up the pipe to the shower head and fall onto your alternately shivering and scalded body (slow).  Oscillations, and much swearing, result).  The behavior of these oscillations can determine which downstream genes get activated.  Since NF-κB is a remarkably versatile and important transcription factor — it’s central to the immune response, and implicated in cancer, inflammation, autoimmune disease, learning and memory — the question of exactly how the activation of downstream genes is controlled is really quite important.

Tay et al. set out to look at the details of the oscillatory behavior using a novel microfluidics platform (created by the Quake lab) that allows large numbers of single cells to be studied at a wide range of TNF-α concentrations.  The movies show examples of the dramatically different behavior at different concentrations: the movie at the top is at low concentration, and the movie at the bottom is at a higher concentration.  You can see that the higher dose results in a much more intense pulse, which happens in all of the cells — not just a few of them, as is the case for a lower dose.  Quantitative analysis shows that, remarkably, the area under the curve stays constant (for those cells that show a pulse) no matter what the dose is, although the peak height of the pulse changes with dose (about 4-fold for a change in 4 orders of magnitude in dose).

What determines whether an individual cell responds or not at the lower dose?  Similar to the story from the Sorger lab on the apoptosis pathway, it seems that some individual cells just happen to be better at triggering pulses than others, presumably because they have more of the relevant pathway members (or less of an inhibitor).  Lower doses lead to a delay in activation, while higher doses lead to more oscillations.  Just as for p53, if you look at the population average you get a picture that entirely fails to represent the behavior of any single cell.  The differences between doses, and between cells, are consequential: at low doses, if an NF-κB pulse gets set off at all, only a subset of the genes controlled by NF-κB are induced (the “early” genes, including IκB), whereas at high doses, as the oscillations continue, you start to get expression of the intermediate and late sets of genes as well.

Although models of NF-κB activation have been proposed before, they were built on the basis of data from experiments using only high concentrations of TNF-α.  Tay et al. set out to adjust these models to account for the “digital” behavior (you either get a pulse, or you don’t) at low concentrations.  To get the model to behave appropriately, they had to invoke a new idea: that IKK, the kinase that phosphorylates IκB leading to its degradation, is activated in a non-linear fashion by its upstream regulator. Although this idea has yet to be confirmed, there is already a possible biochemical explanation: IKK has to be phosphorylated twice to become active, which one could imagine would lead to non-linear activation.  With this key modification, Tay et al. were able to get their model to show behavior that is almost identical to the real data, except for some differences at intermediate TNF-α doses. Once again, this story shows why looking at single cells can be crucial in understanding how signaling networks actually work.

Reading this paper, I was struck by the similarities between NF-κB and p53.  Both seem to use a combination of digital and analog behavior to control the expression of downstream genes.  Both seem to have a dual negative feedback: p53 has one negative feedback loop with Mdm2, and another through Wip1 to the kinase ATM, while NF-κB has one with IκB and another through A20 to the kinase IKK.  A recent collaboration between the Lahav lab and Uri Alon’s group showed that this type of dual negative feedback system is important for generating the dynamics observed for p53. And both have non-linearity in the activity of the upstream kinases (in the case of p53, the Lahav lab used a Hill function to model the non-linearity in p53 stabilization).  The similarities could be more apparent than real, but it seems that a careful comparison of the two systems might well come up with interesting principles.  No doubt someone will make this comparison in the not-too-distant future; we’ll watch out for it and let you know.

Incidentally, Markus Covert gave a great talk on this work at the recent Systems Biology of Human Disease conference organized by the Council for Systems Biology in Boston (CSB2).  He also received the CSB2 Boehringer Ingelheim Prize in Computational Biology.  Congratulations, Markus!

Tay S, Hughey JJ, Lee TK, Lipniacki T, Quake SR, & Covert MW (2010). Single-cell NF-kappaB dynamics reveal digital activation and analogue information processing. Nature, 466 (7303), 267-71 PMID: 20581820

Tagged: , , , ,

Leave a Reply

Fill in your details below or click an icon to log in: Logo

You are commenting using your account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s

What’s this?

You are currently reading Friday Feature: Inflammatory behavior at It Takes 30.


%d bloggers like this: