Once again, there are more great papers out there than I can write about. Below are two that will show up on the site in a few days. (Nature Reports web production schedule requires a week). Also check out Tom Zwaka’s paper that finds another, powerful control over Nanog; Sheng Ding shows that small molecules can substitute for two of the four Yamanaka factors, inching closer to reprogramming without viruses; in a high-throughput screen, Lorenz Studer shows us how known drugs affect human embryonic stem cells, a technique that might reveal unwanted side effects. (Those are all in the most recent Cell Stem Cell; see our Q&A with Sheng Ding on the potential of small molecules.)
See below for these papers along with links to less specialized articles.
A metasignalling network makes muscles age (Irina Conboy on skeletal muscle)
Two networks of pluripotency (Chia-Lin Wei and Huck-Hui Ng map transcription factor binding sites to find ‘stemness hotspots’)
A metasignalling network makes muscles age
(This gets pretty technical; a lay explanation is here. )
Regeneration is actively repressed in a metasignalling network between TGF-beta and Notch
Old bodies weaken partly because aged muscles are less able to repair themselves. Reporting in Nature, Irina Conboy and colleagues at the University of California, Berkeley finger a new molecular culprit for this phenomenon and show that, at least in skeletal muscle, tissue stem and progenitor cells do not so much lose their ability to repair damage as actively inhibit this potential.
In previous work, Conboy had shown that young satellite cells exposed to old differentiated myofibers are less able to regenerate. These old myofibers secrete factors that increase the activity of a common cell-signalling molecule known as transforming growth factor-beta (TGF-beta), and older satellite cells have elevated levels of phosphorylated Smad3, a transcription factor activated by TGF-beta signalling.
The TGF-beta pathway is not the only one implicated in satellite cell aging. Previous work had shown that loss of the ability to regenerate accompanied the decline of an important signalling pathway known as the Notch pathway. If Notch activity is artificially boosted, old muscle cells become better able to repair themselves after injury.
Conboy’s work suggests that either the decline of Notch or the activation of TGF-beta would suffice to explain old muscle’s inability to heal. However, the pathways are connected. Notch and TGF-beta pathways exert opposing effects on the activation of proteins that stall a cell’s division cycle and are known as cyclin-dependent kinase (CDK) inhibitors. When TGF-beta activates pSmad3, pSMAD3 induces CDK inhibitors and thus prevents satellite cell proliferation.
In contrast, Notch prevents pSmad3 from activating CDK inhibitors, which promotes satellite cell division. Conboy’s team established that Notch, Smad3 and RNA polymerase are found together in a complex on promoter regions of several CDK inhibitors, suggesting that Notch physically blocks the effects of pSmad3. Thus, as Notch declines and TGF-beta and pSmad3 rise, the balance between pathways that regulate muscle stem cell proliferation shifts in a way that hinders muscle repair. Knocking down Smad3 expression in vivo downregulated levels of CDK inhibitors in satellite cells residing in old muscle and restored efficient tissue repair.
“They’ve closed the loop on that pathway,” says Mike Rudnicki, who notes that satellite stem cells are a heterogeneous population, so the analysis might miss differences between cells that can self-renew and those destined for differentiation into muscle.
On the other hand, the components in the metasignalling network are ubiquitous in cell regulation. Rudnicki believes this metasignalling network could be “a general mechanism that explains loss of stem cell rigor as we age,” he says. “That’s a reasonable hypothesis.”
Reference
Carlson, M. E., Hsu, M. & Conboy, I. M. Imbalance between pSmad3 and Notch induces CDK inhibitors in old muscle stem cells. Nature advance online publication, doi:doi: 10.1038/nature07034 (15 June 2008).
Two networks of pluripotency
Monya Baker
Pluripotency transcription factors bind DNA in clusters
(GenomeWeb did a nice job summarizing this one)
An analysis of transcription factor binding sitesfinds clusters that clarify cooperative binding
The list of factors that contribute to pluripotency is long and growing, but the diagram of how these proteins interact with the genome and with each other is far from complete. Publishing in Cell, researchers led by Chia-Lin Wei and Huck-Hui Ng at the Genome Institute of Singapore probed these interactions by analyzing where and how a baker’s dozen of transcription factors bind in the genome.
To conduct their investigation, the researchers applied a recently reported technique called ChIP-seq to transcription factors well known for their roles in mouse embryonic stem (ES) cells. ChIP-seq combines a technique that collects the DNA fragments to which transcription factors bind (chromatin immunoprecipitation) with ultra-high-throughput sequencing. This method can search out genetic sites to which particular transcription factors bind in particular cell types. Michael Teitell, an ES scientist at the University of California, Los Angeles, says more labs are adopting this method, partly because other techniques can be biased to particular segments of the genome. “The main reason to be excited is that there is no limitation to the areas of the genome that can be interrogated and the depth to which it can be covered by sequencing.”
Wei and Ng’s analysis describes the transcription factors as “wired into the genome” in two clusters whose binding sites often overlap extensively. The first cluster contains an all-star cast including Nanog, Oct4, Sox2, Smad1 and Stat3. The second, smaller cluster consists of c-Myc (an oncogene that boosts reprogramming efficiency), n-Myc, Zfx and E2f1.
The analysis also sheds light on how the factors bind cooperatively. For example, the binding sequences for Sox2 and Oct4 often occurred together as a motif, supporting the idea that a heterodimer of those proteins is the functional binding unit. In another experiment to explore cooperative binding, the researchers found that depleting Oct4 lowered the binding rates for Smad1 and Stat3, but Oct4 binding was undisturbed by disruptions to these pathways. [Binding rates of Smad1 and Stat3 were lowered by perturbing their chief signaling pathways (BMP (bone morphogenic protein) for Smad1; LIF (leukaemia inhibitory factor) for Stat3)]. Researchers also found regions of the genome that were co-occupied by multiple transcription factors within ES cells, providing both further evidence of their interaction and insights.
Earlier this year, a study led by Stuart Orkin used a different technique to analyze the binding sites of a slightly different set of nine transcription factors. Ng and Wei speculate that future work integrating these data sets will prove useful in identifying the essentials of gene-regulatory networks necessary to the ES-cell state.
References
Chen, X. et al. Integration of external signaling pathways with the core transcriptional network in embryonic stem cells. Cell 133, 1106–1117 (2008). | Article
Kim, J. et al. An extended transcriptional network for pluripotency of embryonic stem cells. Cell 132, 1049–1061 (2008).