doubt a significant technical accomplishment that adds a new dimension to our under-standing of regeneration. Like all important work, it also leaves us with questions that will probably occupy researchers for the next few years. One question concerns the

contribution of connective-tissue fibroblast cells to the regenerating limb. Fibroblasts are relatively abundant in the limb and are known to contribute significantly to regenerative activ-ities in salamanders8. Are these cells lineage restricted, or can they give rise to other types of tissue? Because there are no reliable mark-ers for identifying connective-tissue fibroblasts yet, Kragl and colleagues could not definitively answer this particularly interesting question.

Is lineage restriction in regenerating cells unique to the axolotl, or can these principles be applied to other commonly studied species of salamander? The animals used for these studies were juveniles, with a skeletal system made up of cartilage rather than bone. Most other studies in salamanders have been done in adult newts, which have ossified skeletons. Also, there are well-documented differences between the regenerative properties of newts and axolotls. For instance, whereas newts can regenerate the lens of the eye after its removal, the axolotl cannot9. These and other issues will have to be resolved before the biological significance of Kragl and colleagues’ findings1 can be fully appreciated. ■

Alejandro Sánchez Alvarado is in the Department

of Neurobiology and Anatomy, Howard Hughes

Medical Institute, University of Utah School of

Medicine, Salt Lake City, Utah 84132, USA.

e-mail: sanchez@neuro.utah.edu

1. Kragl, M. et al. Nature 460, 60–65 (2009).2. Birnbaum, K. D. & Sánchez Alvarado, A. Cell 132, 697–710

(2008).3. Grogg, M. W. et al. Nature 438, 858–862 (2005). 4. Gurley, K. A., Rink, J. C. & Sánchez Alvarado, A. Science 319,

323–327 (2008).5. Kumar, A., Godwin, J. W., Gates, P. B., Garza-Garcia, A. A.

& Brockes, J. P. Science 318, 772–777 (2007). 6. Morrison, J. I., LÖÖf, S., He, P. & Simon, A. J. Cell Biol. 172,

433–440 (2006).7. Reddien, P. W. et al. Dev. Cell 8, 635–649 (2005). 8. Bryant, S. V., Endo, T. & Gardiner, D. M. Int. J. Dev. Biol. 46,

887–896 (2002).9. Tsonis, P. A., Madhavan, M., Tancous, E. E. &

Del Rio-Tsonis, K. Int. J. Dev. Biol. 48, 975–980 (2004).

Dermal cell

Before amputation After regeneration

Cartilage cell

Muscle cell

?

?

Bone cell

Schwann cell

Fibroblast

Epidermal cell

Figure 2 | Lineages are respected during axolotl limb regeneration. Kragl et al.1 find that, with the exception of cells in the dermis, the dedifferentiated cells contributing to limb regeneration largely remain lineage restricted. Because the experiments were carried out in juveniles, in which the bones have not fully ossified, the fate of bone cells after amputation is unknown. Similarly, owing to the paucity of markers, the fate of connective-tissue fibroblasts contributing to limb regeneration remains undefined. The blue arrow indicates that cartilage cells can sometimes contribute to the dermis.

BIOGEOCHEMISTRY

Climatic plant power Yves Goddéris and Yannick Donnadieu

Levels of atmospheric carbon dioxide constrain vegetation types and thus also non-biological uptake during rock weathering. That’s the reasoning used to explain why CO2 levels did not fall below a certain point in the Miocene.

The world is currently at risk of overheating in response to all the carbon dioxide being pumped into the atmosphere from the use of fossil fuels: the current atmospheric concen-tration of CO2 is about 385 parts per million (p.p.m.), compared with a ‘pre-industrial’ level of around 280 p.p.m. But overheating is an atypical menace in the recent history of the Earth. Over most of the past 24 million years, it was the possibility of cooling that posed the

main threat to life. Cooling, however, did not reach the levels of severity that might have been expected, and on page 85 of this issue Pagani et al.1 put forward a thought-provoking case as to why that was so.

Since the end of the Eocene, around 40 million years ago, Earth’s climate has been naturally getting colder. In temporal terms, the cooling has sometimes occurred in dis-crete steps, sometimes as a long-term trend2.

Over the same interval, levels of atmospheric CO2 have fallen from around 1,400 p.p.m. at the end of the Eocene to possibly as low as 200 p.p.m. during the Miocene3 — the geological period between around 24 million and 5 million years ago.

This long-term history of atmospheric CO2 is the result of the interplay between several pro cesses. The degassing of the Earth through magmatic activity (for instance volcanic eruptions) is the main source of CO2, and the dissolution of continental rocks captures atmospheric CO2, which is eventually stored as marine carbonate sediments4. The effi-ciency of the dissolution process — chemical weathering — is heavily dependent on climate, but also depends on vegetation and physical erosion. The last two parameters boost CO2 uptake by rock weathering. In particular, land plants promote rock dissolution through the mechanical action of roots, and by acidifying the water in contact with rocks5. Acidification occurs through the release of organic acids and the large-scale accumulation of CO2 in soil through root respiration. Removing plants, particularly trees, may strongly decrease the dissolution rate of rocks and the ability of this process to consume atmospheric CO2.

In their paper, Pagani and colleagues1 consider the potential role of the rise of many mountain-ous regions (orogens) over the past 40 million years, especially in the warm and humid low-latitude areas. In these mountain ranges, physical erosion would break down rocks and expose them to intense chemical weathering. The uptake of atmospheric CO2 would conse-quently increase, as indicated by the levels of CO2 measured, which could have declined to the lowest levels since multicellular life evolved on Earth some 500 million years ago.

But what could stop this CO2 uptake pump? Degassing through magmatic activity was probably declining at the same time (at best it remained constant), and tectonic activity accel-erated mountain uplift over the past 24 million years. According to this line of evidence, CO2 levels should have plunged to below 200 p.p.m., with ice ultimately covering large surfaces of the Earth as a consequence. But that was not the case. Earth even experienced a warm spell between 18 million and 14 million years ago2.

Pagani et al.1 propose an exciting hypoth-esis to explain why, 24 million years ago, CO2 might have levelled off at about 200 p.p.m., and then stuck there. They suggest that, when CO2 levels became too low, forests became starved and were progressively replaced by grasslands, particularly in the low-latitude orogens. Grass-lands exert a much less vigorous effect on rocks than do trees. In consequence, runs the think-ing, CO2 consumption due to weathering declined because of changing terrestrial eco-systems, which in turn stabilized atmospheric CO2 at around 200 p.p.m.

Overall, the authors’ model provides an elegant twist on several ideas about the Earth system that emphasize the role of vegetation

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in dynamically regulating and fixing the lower limit of atmospheric CO2. But it also raises con-tentious issues.

First, in the model1, forest starvation is trig-gered by the low level of atmospheric CO2, and by elevated temperature. But do proxy estimates of conditions at that time confirm this paradoxical combination? Proxy measure-ments of CO2 levels include marine carbon-ate boron isotopes6, carbon-isotope values of alkenones produced by oceanic algae3 and the density of stomata — a measure of gas exchange — in fossil leaves7. Unlike the geo-chemical proxy records3,6, the more recent estimates based on the stomatal index7 depict a highly variable CO2 trend over the Miocene (in good agreement with climatic fluctuations), rather than a CO2 level stuck at 200 p.p.m. Furthermore, the estimates show that CO2 concentrations are above the forest-starvation level most of the time, oscillating between 300 and 500 p.p.m.

Second, in their model Pagani et al. assume that rock weathering generated by mountain uplift would have continuously consumed atmospheric CO2 until it reached the forest-starvation level. But there is evidence that the extra consumption of CO2 due to the Hima-layan uplift, the most important orogeny of the recent past, occurred mainly through the burial of organic matter in the Bengal fan, and not through rock weathering8,9. In addi-tion, the tectonic history of the past 24 million years is still subject to debate, and the timing of the uplift of the main mountain ranges, such as the Himalaya and Andes, is far from fully constrained10.

Finally, the link between weathering and continental vegetation is well recognized. But it is complex. Apart from acidifying water and mechanical effects, land plants also control the hydrology of soils. In humid tropical environ-ments, about 70% of the rainfall is absorbed by land plants and then evaporates through their leaves. This effect should inhibit weathering reactions by limiting the amount of water avail-able for rock dissolution. Also, in equatorial uplifted areas, intense erosion occurs through landslides triggered by heavy rainfall11. These landslides bring fresh rock material in contact with water by removing the soil mantle, pro-moting weathering and CO2 consumption. The role of vegetation cover in these systems might not be as significant as Pagani et al. suggest.

The authors themselves acknowledge some of these limitations, and all in all have put forward a bold and provocative hypothesis. But accounting for all of the processes and constraints involved is probably beyond the capabilities of the first-order global models that Pagani et al. used, and more-complex and process-based modelling12,13 will be required to test their conclusions. Whatever the outcome, that should prove to be a fruitful exercise for carbon-cycle modellers intent on understand-ing the processes that drove climate and CO2 oscillations during the Miocene. ■

Yves Goddéris is at the LMTG-Observatoire

Midi-Pyrénées, CNRS, Université de Toulouse III,

Toulouse F-31400, France. Yannick Donnadieu

is at LSCE, CNRS-CEA, Gif-sur-Yvette F-91191,

France.

e-mails: godderis@lmtg.obs-mip.fr;

yannick.donnadieu@lsce.ipsl.fr

1. Pagani, M., Caldeira, K., Berner, R. & Beerling, D. J. Nature

460, 85–88 (2009).

2. Zachos, J. C., Dickens, G. R. & Zeebe, R. E. Nature 451, 279–283 (2008).

3. Pagani, M. et al. Science 309, 600–603 (2005).

4. Walker, J. C. G., Hays, P. B. & Kasting, J. F.

IMMUNOLOGY

A metabolic switch to memory Martin Prlic and Michael J. Bevan

Two therapeutic drugs have been found to enhance memory in immune cells called T cells, apparently by altering cellular metabolism. Are changes in T-cell metabolism the key to generating long-lived immune memory?

T lymphocytes respond to an acute infection with a massive burst of proliferation, generating effector T cells that counteract the pathogen. When the infection is cleared, most of these effector T cells die (the contraction phase of the immune response), but a minority lives on and changes into resting memory T cells that rapidly respond to future encounters with the same pathogen1. In this issue, Pearce et al.2 (page 103) and Araki et al.3 (page 108) report that two drugs, one used to control diabetes and the other to prevent organ-transplant rejection, markedly enhance memory T-cell development. Through their actions on major metabolic pathways in the cell, these drugs seem to promote the switch from growth to quiescent survival.

While investigating the role of a protein called TRAF6, which is a negative regulator of T-cell signalling, Pearce et al.2 noted that, although T cells in which TRAF6 was knocked out mounted a normal effector response to a pathogen, they left behind few if any memory cells. The authors performed a microarray analysis comparing the genes expressed by normal and TRAF6-deficient T cells at the time they change from effector to memory cells. In a eureka moment, they realized that TRAF6-knockout T cells display defects in the expression of genes involved in several metabolic pathways, including the fatty-acid oxidation pathway, implying that a metabolic switch in T cells might be affecting memory-cell generation.

Pearce et al. followed up on this clue, and showed that the inability of TRAF6-deficient T cells to spawn long-lived memory T cells could be reversed by treatment with either the antidiabetes drug metformin or the immuno-suppressant rapamycin. Both drugs are known

to affect cellular metabolism, and treatment with either drug not only restored the mem-ory T-cell response in TRAF6-deficient cells, but also greatly enhanced memory T-cell formation in normal cells, resulting in a superior recall response to a second infection.

In an independent study, Araki et al.3 examined the effect of treating mice with rapamycin during the various phases of a T-cell response to viral infection. Giving rapamycin during the first 8 days after infec-tion (the proliferative phase) markedly increased the number of memory T cells 5 weeks later. This was due to an enhanced commitment of effector T cells to become memory precursor cells. When the authors administered rapamycin during the contrac-tion phase of the T-cell response (days 8–35 after infection), the number of memory T cells did not increase, but there was a speeding up of the conversion of effector T cells to long-lived memory T cells with superior recall ability.

Rapamycin inhibits mTOR (‘mammalian target of rapamycin’), a protein-kinase enzyme found in at least two multiprotein complexes — mTORC1, which is rapamycin sensitive, and mTORC2, which is largely resistant to inhibition by rapamycin4. To pinpoint the cellular target of rapamycin in their studies, Araki et al.3 used RNA-interference knock-down techniques to demonstrate that the mTORC1 complex, acting intrinsically in T cells, regulates memory-cell differentiation.

So both rapamycin and metformin seem to enhance T-cell memory formation. But do both drugs affect the same pathway(s), are the pathways interconnected, or do two differ-ent mechanisms lead to a similar outcome? Metformin activates AMPK, an enzyme that can inhibit mTOR activity in several ways,

J. Geophys. Res. 86, 9776–9782 (1981).

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(2000).

7. Kürschner, W. M., Kvaček, Z. & Dilcher, D. L. Proc. Natl

Acad. Sci. USA 105, 449–453 (2008).

8. Galy, V. et al. Nature 450, 407–410 (2007).

9. France-Lanord, C. & Derry, L. A. Nature 390, 65–67 (1997).

10. Sempere, T., Hartley, A. & Roperch, P. Science 314, 760

(2006).

11. Bhatt, M. P. & McDowell, W. H. Water Resour. Res. 43, doi:10.1029/2007WR005915 (2007).

12. Donnadieu, Y. et al. Geochem. Geophys. Geosyst. 7, doi:10.1029/2006GC001278 (2006).

13. Donnadieu, Y., Goddéris, Y. & Bouttes, N. Climate Past 5, 85–96 (2009).

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