Saturday, January 15, 2011

IRS Serine Phosphorylation and Insulin Sensitivity?

This is part of my last year in science series. Click here for the rationale.

Insulin signalling passes through a cascade of signaling proteins starting with the recruitment of the Insulin Receptor Substrate (IRS) to the Insulin Receptor.  Insulin resistance, or impaired insulin signaling is a hallmark of obesity and diabetes.  One of the ways in which was thought to happen was through phosphorylation of Serine 307 on IRS, a phosphorylation event which has been proposed to be inhibitory to insulin signaling.  As an example, it has been proposed that inflammation (via JNK or IKKbeta), overnutrition (via S6K) or several other factors can lead to the phosphorylation of this protein.  Since several of these factors correlate with reduced insulin signaling, and the ablation of these factors leads to both increased insulin signaling and reduced serine phosphorylation, the obvious hypothesis was that serine phosphorylation of IRS is causative of insulin signaling.

Correlation does not equal causation, so in order to test this hypothesis in vivo, Morris White's group at Harvard Medical School generated knockin mice, in which Serine 307 of IRS1 is mutated to an alanine (and is therefore unable to be phosphorylated).  The idea would be that these mice would be unable to phosphorylated IRS1 on Serine 307, and therefore would be resistant to the deleterious effects of this phosphorylation.  This serine to alanine knockin model is considered the gold standard for translating an observational protein phosphorylation site into an in vivo phenotype.  Unfortunately for the prevailing hypothesis, the opposite was true.

The paper, from Copps et al. published in January of 2010 show that on a normal diet S307A mice showed modest reductions in insulin sensitivity, and increased fasted insulin levels.  Both of these effects were amplified by high fat diet, and were associated with a reduction in weight gain, in contradiction to the previous hypothesis, that these effects would be ameliorated.  Mechanistically, when on a high fat diet (or coupled with liver specific IRS2 knockout) the S307A mouse had decreased tyrosine phosphorylation of IRS, but no effect of the downstream insulin targets Akt and S6K. Therefore it is unclear exactly how the insulin intolerance is propagated into effects on glucose homeostasis.

In the past year this article has been cited 10 times (according to Google Scholar), mostly in review articles, but the major upshot here, is that the models which showed effects on IRS Serine 307 phosphorylation and insulin resistance, and concluded that insulin resistance was mediated by increased phosphorylation may need re-interpretation.  IRS is phosphorylated on several other sites, so the general hypothesis that serine phosphorylation of IRS causes insulin resistance could still be true, but that again might need to wait until such a knockin model can be generated.  This work also points out the risks of correlating phenotypes with incompletely characterized phosphorylation sites.

Copps KD, Hancer NJ, Opare-Ado L, Qiu W, Walsh C, & White MF (2010). Irs1 serine 307 promotes insulin sensitivity in mice. Cell metabolism, 11 (1), 84-92 PMID: 20074531 DOI

Last Year in Science

I hope to put together a series of posts on papers from about a year ago. Quite often the context of a paper can get lost in the flurry surrounding the initial release of a paper. My hope is that I can provide a little bit of insight on these papers with a little bit more since publication. If you have any ideas for things that might be interesting to go over (again) just let me know. For now I'll try to read some of the glamor mags in my field (Cell, Cell Metabolism, Nature Cell Biology, Nature and Science) and see if anything strikes my interest.

Wednesday, January 12, 2011

Inositol Phosphates and Insulin Signaling

When most people think of the role of inositols in Akt signaling, they immediately think about the role of PIP3 in the PDK1-Akt signaling axis.  A recent paper published in Cell by Solomon Snyder's group at John's Hopkins highlights the role of soluble inositol phosphates in insulin signaling.

Soluble Inositol Phosphates

Inositol is best known as a lipid head group, that can be phosphorylated to form 8 potential phosphorylated phosphatidylinositols. These membrane bound signaling lipids have many important roles in cell biology, including in signal transduction. In addition to these 8 membrane bound lipids, the inositol headgroup can be solubilized from the lipid tails by phospholipases.  This leads to the important second messenger IP3, which can then be further phosphorylated to yield IP4, IP5 and IP6.  Adding even more to the complexity, these rings can be pyrophosphorylated to yield even more species including IP7 and IP8 among others. The functions of these phosphorylated inositol rings are largely unknown.

Role of IP7 in Akt Activation

The IP6-Kinase 1 phosphorylates IP6 to form IP7 (pyrophospho-IP5). The current paper, Chakraborty et al. (2010), describes insulin signaling in cells in which IP6 is knocked out. As expected, IP7 concentrations are reduced in these cells, but the major finding is that Akt phosphorylation and activation is increased. The proposed mechanism for this effect is that IP7 acts as an endogenous, physiological inhibitor of Akt, likely by competitively inhibiting the ability of PIP3 to bind to the same site in its PH domain. Once IP7 is reduced, this inhibition is released, and Akt can be activated more easily.

Consistent with hyperactivation of Akt, these knockout mice exhibit increased insulin sensitivity and a reduction in diet-induced obesity. Akt and its downstream targets are known to be major mediators of insulin signaling, and so increased insulin signaling through the Akt pathway leads to increased glucose disposal and a resistance to diet-induced weight gain, insulin resistance, hyperinsulinemia and hyperglycemia. These data are consistent with a role of IP7 as a negative regulator of insulin signaling and the authors propose that IP6K1 may be a novel potential therapeutic target to improve insulin sensitivity.

Chakraborty, A., Koldobskiy, M., Bello, N., Maxwell, M., Potter, J., Juluri, K., Maag, D., Kim, S., Huang, A., & Dailey, M. (2010). Inositol Pyrophosphates Inhibit Akt Signaling, Thereby Regulating Insulin Sensitivity and Weight Gain Cell, 143 (6), 897-910 DOI: 10.1016/j.cell.2010.11.032

Sunday, January 9, 2011

The Web of Data and Experimental Observations

A few things this week got me thinking about the idealized best way to think of experimental data.  One was a technical problem I had been pondering.  If i wanted to publish some experimental observation (not a paper just a single observation) what is the best way to do this.  It got me thinking a little about the Semantic Web (or the Web of Data) and how it could related to 'wet' biology. I am far from an expert on any of these things, so feel free to make public your thoughts

The Web of Data and Ontologies

One of the new things the architechts of the internet have been concerning themselves lately is the semantic web. Some authoritative links are herehere and here.   The idea is that there are lots of things out there which are data but the web considers mostly things that are documents.  The world will be a better place when computers can make connections between these things.  This involves two concepts, one of which is the thing and the other of which is the connection

Things on the Web

Not everything is on the web.  I for example, am sitting in my living room and am definately not on the web.  Therefore to locate me, I need some kind of identifier.  These are called Uniform Resource Identifiers (URI).  Mine could be something like  URI's need to be unique and they need to be available on the internet.  Anything could have a URI, and something could have several URI's. The key is that a URI should not belong to more than one thing.  Things which have multiple URI's can be crossreferenced with specific vocabularies (ie owl:sameAs).

Connections (Ontologies)

Once things are on the internet, the basis of linked data is how these things relate to one another.  For example, this blog post was created by me.  So if there was some kind of explicit statement connecting this, any computer could figure out that I wrote this post, or inversely that this post was written by me.  The connections are defined by specific vocabularies or ontologies.  For example dublincore is a vocabulary about documents, and includes a term "creator".  Therefore one could create a link between me and this post by writing something like this:

This Blog Post has a Creator named Dave Bridges

The important thing is that the ontology specifically defines the relationship between two URI's.  Given this knowledge, a computer could generate the creator of the page, or all pages created by me.

How Would This Work in Science

What got me thinking about this was how it would be great to have defined vocabularies to describe experimental results.  For example if there was an ontology that described a protein-protein interaction (there is, its at, one could use, for example two PubMed links as URI's to could indicate a molecular interaction and the two proteins.  Given a large enough catalog of these it would be possible to get a list of all molecular interactions for a particular protein.

What About Non-Cannonical Findings

I might talk about this later, but one thing important would be to not just be able to obtain a list of interactions, but also links to the specific data supporting (or refuting that point).  Ideally this would go deeper than just a link to the paper, but maybe a link to a separate URI describing a particular experiment.

The things that got me thinking about this were a question i posted on BioStar, a blog post on MolBio Research Highlights and a paper at Nature Preceedings

Plans and Ethics

This is my first post here and my second stab at blogging.  I am still not sure what sorts of things that will go here so bear with me.  Some guidelines that I will try to stick to are below:

Journalistic-like Ethics

  • Posts will not be deleted.  I said it, I cant unsay it.
  • Comments will left to stand, unless they are obviously unrelated sales pitches.  I reserve the right to eventually approve comments, but lets hope not.
  • Minor changes and typos will be made without notification.  If you see a typo just email me or leave a comment.
  • Major changes, corrections and omissions will be made in a separate post and both posts will be linked.
  • Assertions and generalizations about individuals will be made very carefully and with thoughts of consequences.  If I say something less than positive about a model, result, or datum it is not personal.
  • All posts regarding published materials will be tagged with a symbol and DOI resolvable links (preferably) or PubMed links to source materials.  Summaries of research blogging materials can be found here
  • Unpublished and/or confidential materials, thoughts or ideas will be not used unless permission is obtained from the scientists involved.
  • Disclosures will be made if I have collaborated with or obtained reagents with a group in the past. Also if I am worried that I am allowing my personal feelings affect my interpretation.

Web Community Ethics

  • I will link to all material that leads to a post, and will amend posts with relevant discussions.  Even if I am linking to someone just to say I am agree.  If I don't, its an accidental omission and please let me know.
  • I will quote portions of, but rarely all of other posts, but will provide links to the full post.
  • If you email me directly, and I forget to respond, please keep at me.  Chances are I have forgotten to get back to you.  Any information provided in confidence will remain in confidence unless explicit permission is obtained.
  • If I promised to do something and didn't, I absolutely forgot.  My bad, just remind me.
  • Until I find a voice on this thing, I am totally open to ideas.  Drop me a comment or an email.

General Rules

  • I will not discuss politics, and will discourage others from talking about it.  There is no doubt that there is an intersection between science (and especially science funding) and politics, but there are thousands of other people who would rather talk about that.
  • I will try to keep discussion of personal lives and trials and tribulations of my current career to a minimum.
  • I will try to keep a positive tone wherever possible.  Its too easy to be negative and critical all the time.

These are based on the code of conduct of the fantastic mgoblog.  Any further suggestions are welcome.