Vif in ‘permissive’ cell lines. So the infectivityof Vif-deficient HIV-1 seems to depend onthe producer cell type (Fig. 1). Wild-typeHIV-1 with an intact Vif gene is not limitedin this way.

Over the past decade and longer, nu-merous laboratories have tried to explainthese puzzling observations. Studies haveshown8–10 that Vif binds to the genomic RNAof HIV-1. But it is unclear how this mightlead to the unique characteristics of Vif-defi-cient viruses. There is clearly some differencebetween the permissive and non-permissiveproducer cells, and a breakthrough came in 1998 when two groups11,12 proposed thatthere is a factor, present in some human cellsbut not in others, that can inhibit the replica-tion of the mutant HIV-1 but is overcome bythe Vif protein of the unmutated virus. Thiscellular factor seemed to alter Vif-deficientHIV-1 during late stages of its life cycle innon-permissive producer cells11,12. Sheehy etal.3 now have strong evidence that there isindeed a human protein that inhibits HIV-1but whose effects are suppressed by Vif.

Sheehy et al. looked at two geneticallyrelated cell lines, one permissive and onenon-permissive. Using a novel combinationof molecular-biological approaches, theauthors identified a protein — namedCEM15, after the cell line in which it was dis-covered — that was needed for the non-permissive cells to repress the infectivity ofthe Vif-deficient HIV-1. Sheehy et al. havedone a superb job of showing that CEM15 ispresent in all non-permissive cells but not inpermissive cells. They also expressed CEM15in normally permissive cells and found thatthey became non-permissive to the Vif-defi-cient HIV-1 (but not to the wild-type virus).

So there is an unarguable correlationbetween the production of CEM15 and thefailure of Vif-deficient HIV-1 particles toproduce infectious progeny in non-permis-sive cells (Fig. 1). Permissive cells, by con-trast, do not produce CEM15 and thereforeallow the Vif-deficient HIV-1 to replicatefreely. All of this suggests that Vif is needed to overcome the human CEM15 protein and allow effective viral replication in non-permissive human cells. The human proteinseems to represent one host mechanism —perhaps one of many13 — that can inhibit thereplication of retroviruses such as HIV-1.

This paper3 takes us a giant leap forwardin exploring one of the final frontiers of HIV-1’s molecular biology. But it’s not yet clear how CEM15 blocks the replicationof Vif-deficient HIV-1. Nor is it knownwhether this protein binds directly to Vifinside human cells infected with wild-typeHIV-1, or whether Vif operates in anotherway. Perhaps one clue lies in CEM15’s similarity to two other human proteins:APOBEC-1 (the catalytic subunit of anenzyme that ‘edits’ messenger RNA14) andphorbolin-1 (a protein induced by phorbol

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NATURE | VOL 418 | 8 AUGUST 2002 | www.nature.com/nature 595

Obesity

Keeping hunger at bayMichael W. Schwartz and Gregory J. Morton

Many different hormones control our weight and appetite. The discovery ofanother hormone, which suppresses appetite for up to 12 hours, may leadto a better understanding of this complex control system.

esters — compounds that stimulate manyhuman cells). All of these proteins have azinc-coordinating motif, which is importantin cytidine deaminase enzymes (includingAPOBEC-1) in virtually all organisms. It will be interesting to see whether CEM15 isinvolved in RNA editing, especially as Vifclearly binds to viral genomic RNA8–10.

One implication of Sheehy and col-leagues’ results is that our cells have a meansof silencing HIV-1 in some situations, and at a specific stage of the viral life cycle. Thismight not be the only cellular virus-silencingtool. For instance, inactive human T lym-phocytes expressing the CD4 protein (whichHIV-1 uses to latch onto cells) are a key HIV-1 reservoir in vivo, yet are difficult toinfect with the virus in vitro. These cells also have several methods of decreasing thestability and activity of the virus after it has entered host cells but before its genomeintegrates with that of its host. The results oftwo recent studies of ‘RNA interference’ alsosuggest that this mechanism, which inhibitsgene expression, might be used by certainhost cells to decrease HIV-1 infection15–17.

Another implication is that the HIV-1 Vifprotein and its interactions with CEM15 —whether direct or indirect — provide us witha unique drug target. It might be possible todevelop small-molecule drugs that target Vifin the major cell types in which HIV-1 lurksin vivo. Another approach could be to inhibitthe aggregation of Vif proteins into multi-mers18, a process that is required for Vif tofunction in non-permissive cells. Under-standing how CEM15 inhibits HIV-1 repli-cation, and how this inhibition is overcomeby Vif, will be crucial in designing drugs tocombat this viral accessory protein.

The work of Sheehy et al.3 shows that even

the hardest viral nut can be cracked by combining the perseverance of molecularvirology laboratories with new moleculartechniques. Nevertheless, the story will sure-ly not end here. I predict that this paper willspur the hunt for cellular antiviral moleculesand will lead to a heightened understandingof the molecular mechanisms of HIV-1. Italso reveals an HIV-1 accessory protein thatis a good target for future antiviral drugs —more of which are urgently needed in bothdeveloped and developing countries. ■

Roger J. Pomerantz is at the Center for HumanVirology, Thomas Jefferson University, 1020 Locust Street, Suite 329, Philadelphia,Pennsylvania 19107, USA.e-mail: roger.j.pomerantz@mail.tju.edu

1. Fisher, A. G. et al. Science 237, 888–893 (1987).

2. Strebel, K. et al. Nature 328, 728–773 (1987).

3. Sheehy, A. M., Gaddis, N. C., Choi, J. D. & Malim, M. H. Nature

418, 646–650 (2002); advance online publication, 14 July 2002

(doi:10.1038/nature00939).

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4945–4955 (1993).

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8701–8709 (1996).

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74, 8252–8261 (2000).

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J. Virol. 74, 8938–8945 (2000).

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M. H. Nature Med. 4, 1397–1400 (1998).

13.Pryciak, P. M. & Varmus, H. E. J. Virol. 66, 5959–5966 (1992).

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Taylor, W. R. Trends Biochem. Sci. 19, 105–106 (1994).

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(2002); advance online publication, 26 June 2002

(doi:10.1038/nature00896).

17.Pomerantz, R. J. Nature Med. 8, 659–660 (2002).

18.Yang, S. C., Sun, Y. & Zhang, H. J. Biol. Chem. 276, 4889–4893

(2001).

Spurred on both by a series of remark-able discoveries and by the emergenceof obesity as a world health problem,

research into how our bodies control ourappetite and weight continues at an unpara-lleled pace. The result is an increasingly clearinsight into the workings of a fascinating but complex neuroendocrine system, inwhich circulating hormones convey infor-mation about energy balance (the differencebetween energy intake and expenditure) tobrain pathways that control eating and energy output. The process of discovery hasbeen rather like peeling back the layers of an

onion, as new molecules involved in the sys-tem continue to be uncovered — although insome instances it is not the molecule itselfbut its role in controlling food intake that isdiscovered. Such is the case for the hormonepeptide YY3-36 (PYY3-36), as Batterham andcolleagues1 report on page 650 of this issue.

Hormones that regulate food intake can be separated into those that act rapidly to influence individual meals, and those that act more slowly to promote the stabilityof body fat stores. Long-term regulatorsinclude insulin and leptin, which are releasedinto the blood in proportion to the amount

© 2002 Nature Publishing Group

of body fat2,3 and exert sustained inhibitoryeffects on food intake while increasing ener-gy expenditure4,5. When body fat stores fall,declining levels of these hormones are sensedby the brain and are transduced into increas-es in appetite and metabolic efficiency thatpersist until the lost weight is recovered.

Such long-term regulators can be distin-guished from short-duration, meal-related‘satiety’ signals, such as cholecystokinin, thatare released from the gastrointestinal tractduring eating6. These peptides promote asense of ‘fullness’ that encourages an end tothe meal. Yet another type of hormonal signal is the gastric peptide ghrelin. Levels ofthis appetite-stimulating hormone rise pre-cipitously in the blood before meals (whenthe stomach is empty), then fall just as quick-ly after food is consumed7. So ghrelin andcholecystokinin are implicated as factorsthat respectively trigger the onset and termi-nation of eating, participating in a meal-to-meal control system that is itself sensitive to changes in insulin and leptin levels. In thisway, the size and frequency of individualmeals can be adjusted so as to minimizechanges in body fat content. Defects in this control system appear to be common,

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however, and the global obesity epidemicdemands a better understanding of its basicoperation. It is a high priority to clarify howPYY3-36 and other molecules influence thedecision to eat.

PYY3-36, a member of the neuropeptide Y(NPY) protein family, was already known tobe secreted by endocrine cells lining the distal small bowel and colon in response tofood, such that its levels in the blood remainhigh between meals. Batterham et al.1 nowfind that, in both humans and rodents, dosesof PYY3-36 that produce such levels inhibiteating for up to 12 hours — a time intervalthat is intermediate between that of thequickly acting peptides that control individ-ual meals and the more slowly working hor-mones that control body weight. Moreover,like insulin, leptin and ghrelin, PYY3-36

activity seems to involve a key brain area —the arcuate nucleus in the hypothalamus. Inaddition to identifying a new role for PYY3-36,Batterham et al.’s work helps clarify how thearcuate nucleus translates input from diversehormonal signals into behavioural andmetabolic responses that powerfully influ-ence the energy-balance equation.

The arcuate nucleus contains two distinct

subsets of neurons that control food intake,one that acts as an accelerator and the other as a brake. The ‘accelerator’ neuronsproduce NPY, which acts in the brain to stimulate feeding8 (paradoxically, this effectis opposite to that of the NPY-family memberPYY3-36). An adjacent neuronal subset pro-duces melanocortin peptides, which act onthe same brain areas as NPY but inhibit eating9. Typically, when one of these subsets is activated the other is inhibited. Duringweight loss, for example, NPY-expressingneurons are activated10 and melanocortin-producing neurons are inhibited11 — re-sponses that stimulate eating and promotethe recovery of depleted fuel stores when sufficient food becomes available. The NPY-expressing neurons also produceagouti-related peptide (AgRP)12, whichblocks neuronal melanocortin receptors.Activating these NPY/AgRP-expressing neurons during weight loss can therebyincrease food intake in two ways: by increasing the release of the appetite-inducing NPY and by blocking the appetite-reducing melanocortin receptors.

Changes in weight are communicated tothe brain by hormones such as leptin andinsulin, which inhibit the NPY/AgRP-expressing neurons (Fig. 1). So the activationof these neurons (and consequent release ofNPY and AgRP) during weight loss is, at leastin part, a consequence of combined insulinand leptin deficiency. Ghrelin can also stim-ulate food intake by activating theseneurons13. Interestingly, this effect of ghrelinis opposed not only by insulin and leptin butalso by NPY itself, which can inhibit the very neurons that produce it (and so inhibitfood intake) by binding to a subtype of the NPY receptor, the Y2 receptor (Y2R), on theNPY/AgRP-expressing neurons. Like otherNPY receptors, the Y2 receptor is coupled toG proteins — common molecular switches— such that its activation blocks an intra-cellular signalling pathway that involves themessenger molecule cyclic AMP.

The idea that activating the Y2 receptorinhibits NPY/AgRP-expressing neurons iskey to understanding the newly discoveredrole of PYY3-36 as an appetite regulator. Thispeptide is a truncated form of a larger peptide that recognizes all NPY-receptorsubtypes. But PYY3-36 binds specifically tothe Y2 receptor14, and Batterham et al.’s data1

suggest that the inhibition of food intake byPYY3-36 requires this receptor, as mice lackingthe receptor are insensitive to the peptide’sappetite-decreasing effects.

In normal mice, intricate neuronal cir-cuitry within the arcuate nucleus amplifiesthese appetite-decreasing effects of PYY3-36.Melanocortin-producing neurons are inhib-ited by adjacent NPY/AgRP-expressing neurons15. So, inhibiting the NPY/AgRP-expressing neurons (for example by insulin,leptin or PYY3-36) lifts the inhibition of the

Figure 1 Hormones that control eating. Leptin and insulin (lower part of the figure) circulate in theblood at concentrations proportionate to body-fat mass. They decrease appetite by inhibiting neurons(centre) that produce the molecules NPY and AgRP, while stimulating melanocortin-producingneurons in the arcuate-nucleus region of the hypothalamus, near the third ventricle of the brain. NPYand AgRP stimulate eating, and melanocortins inhibit eating, via other neurons (top). Activation ofNPY/AgRP-expressing neurons inhibits melanocortin-producing neurons. The gastric hormoneghrelin stimulates appetite by activating the NPY/AgRP-expressing neurons. Batterham et al.1 havenow shown that PYY3-36, released from the colon, inhibits these neurons and thereby decreases appetitefor up to 12 hours. PYY3-36 works in part through the autoinhibitory NPY receptor Y2R.

Thirdventricle

Colon

PYY3-36

Ghrelin

Stomach

Fat tissue

Pancreas

Melanocortin

Foodintake

Energyexpenditure

+–

–

Ghrelin receptor

Leptin receptoror insulin receptor

NPY receptor Y1R

NPY/PYY3-36receptor Y2R

NPY/AgRP

Neuron

Insulin

–

Leptin

+

Arcuatenucleus

Melanocortinreceptor (MC4R)(blocked by AgRP)

Melanocortinreceptor (MC3R)

© 2002 Nature Publishing Group

melanocortin-producing neurons1, therebyreducing food intake. The suppression offeeding induced by PYY3-36 — like thatinduced by leptin or insulin — can thereforebe predicted to require intact neuronalmelanocortin signalling.

These new insights provide a usefulframework for understanding how obesityoccurs and how it might be treated. Butmany questions remain to be answered. Forinstance, does PYY3-36 participate in thelong-term control of body fat stores, theshort-term control of individual meals, orboth? Are factors that control its secretionlinked to weight changes? At the cellularlevel, the hypothesis that PYY3-36 inhibitsNPY/AgRP-expressing neurons through theY2 receptor implies that signalling involvingcyclic AMP is a major determinant of theactivity of these neurons (as it is this signalthat is blocked by PYY3-36). Yet we have no idea what inputs normally drive such signalling in these neurons.

From the clinical perspective, analoguesof PYY3-36 and other molecules that reducefood consumption by activating the Y2receptor will no doubt generate interest fortheir potential in treating obesity. The use of such drugs — perhaps in combinationwith interventions that reduce signalling by

ghrelin or increase signalling at the neuronalmelanocortin, leptin or insulin receptors —may improve obesity treatments to theextent that significant weight loss can beachieved and maintained indefinitely. If weare to combat the global obesity epidemic,such breakthroughs are urgently needed. ■

Michael W. Schwartz and Gregory J. Morton are inthe Division of Metabolism, Endocrinology andNutrition, University of Washington andHarborview Medical Center, 325 9th Avenue,Seattle, Washington 98104-2499, USA.e-mail: mschwart@u.washington.edu

1. Batterham, R. L. et al. Nature 418, 650–654 (2002).

2. Considine, R. V. et al. J. Clin. Invest. 95, 2986–2988 (1995).

3. Bagdade, J. D., Bierman, E. L. & Porte, D. Jr J. Clin. Invest. 46,

1549–1557 (1967).

4. Zhang, Y. et al. Nature 372, 425–432 (1994).

5. Woods, S. C., Lotter, E. C., McKay, L. D. & Porte, D. Jr Nature

282, 503–505 (1979).

6. Gibbs, J., Young, R. C. & Smith, G. P. J. Comp. Physiol. Psychol.

84, 488–495 (1973).

7. Cummings, D. E. et al. Diabetes 50, 1714–1719 (2001).

8. Stanley, B. G., Kyrkouli, S. E., Lampert, S. & Leibowitz, S. F.

Peptides 7, 1189–1192 (1986).

9. Fan, W. et al. Nature 385, 165–168 (1997).

10.Sahu, A., Kalra, P. S. & Kalra, S. P. Peptides 9, 83–86 (1988).

11.Schwartz, M. W. et al. Diabetes 46, 2119–2123 (1997).

12.Hahn, T. M., Breininger, J. F., Baskin, D. G. & Schwartz, M. W.

Nature Neurosci. 1, 271–272 (1998).

13.Nakazato, M. et al. Nature 409, 194–198 (2001).

14.Gobbi, M., Mennini, T. & Vezzani, A. J. Neurochem. 72,

1663–1670 (1999).

15.Cowley, M. A. Nature 411, 480–484 (2001).

(or both). One such two-level system is acoupled electron–hole pair — an exciton.The absence (equivalent to the state |0>) andpresence (state |1>) of an exciton in a semi-conductor quantum dot could represent thetwo levels of a quantum bit.

But to work as a quantum bit, it is essentialthat the quantum states of this exciton can beprepared, controlled and measured with highaccuracy. Zrenner et al.2 have taken a remark-able step forward by showing that coherentmanipulation of an exciton quantum bit ispossible by applying short laser pulses to a sin-gle quantum dot. Further, they demonstratethat the quantum-bit state can be measuredwith extremely high efficiency, through itstransformation into an electric current.

Optical excitation using a picosecond laserpulse creates an exciton in the quantum dot, asan electron is lifted from the valence band intothe conduction band of the semiconductor:the electron is coupled to the ‘hole’ it leftbehind in the valence band, forming an exciton. In a simplified model, the exciton canbe considered as a harmonic oscillator — likethe membrane of a loudspeaker — that is driven by the laser field. On the shorttimescales of the laser pulse, damping of theoscillator does not occur. As the laser intensityincreases, equivalent to pushing the loud-speaker membrane harder, the amplitude ofthe oscillator increases to a maximum value, then decreases. Increasing the laser intensity further sets up a periodic repetition of thisexcitation and de-excitation process — thecreation and annihilation of excitons in thequantum dot, an effect called Rabi oscillation.

Exciton Rabi oscillations in single quan-tum dots are a recently demonstrated phen-omenon3–5, relying on optical detections. Aphoton may be released as the electron andhole recombine and the exciton is destroyed.But this kind of measurement is rather ineffi-cient, and so photon detection would be oflimited use as a measurement protocol forquantum-information processing. However,Zrenner et al. have developed a more effectivemethod for detecting the quantum state thatinvolves mapping the quantum state onto acurrent. Whereas photons can easily just getlost en route to a detector, this current can bemeasured with high precision because chargemust be conserved in a circuit. The quantumdot is placed between two electrodes to whichvoltage is applied, and the electron and thehole of the exciton tunnel out of the dot, generating a current that reflects the Rabioscillations taking place.

The situation becomes especially inter-esting when the laser intensity is such that theexciton oscillator reaches its maximumamplitude. This corresponds to ‘full inver-sion’: the prepared quantum state is wholly|1>, with no state |0> mixed in. Each laserpulse creates exactly one exciton, subse-quently causing a single elementary chargeto flow through the detection circuit. Thus,

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NATURE | VOL 418 | 8 AUGUST 2002 | www.nature.com/nature 597

Semiconductor physics

One at a time, pleaseManfred Bayer

Semiconductor quantum dots could become the basis of the much-talked-about quantum computer. A single-electron ‘turnstile’ device is a promising way to read out the information being processed.

Physicists are actively seeking to transferthe weird phenomena of the quantumworld from their laboratories to the real

world. In particular, the prospect of quan-tum-information processing has attractedconsiderable attention for its potential toimprove the speed and reliability of datahandling1. Information would be encoded in‘quantum bits’, and the search is on for aphysical system that could form a reliable,controllable quantum bit: on page 612 of this issue, Zrenner et al.2 report theirprogress with a candidate from solid-statephysics, the ‘exciton’.

In contrast to classical bits, which can bein either state 0 or state 1, quantum bits existas a combination (a linear superposition) oftwo quantum logic states, represented as |0>and |1>. In a quantum computer, the quan-tum bits first have to be controlled individu-ally in order to initialize the quantum registerin which information is stored. Then a con-trollable interaction between the quantumbits must be established so that the quantumstates become entangled. It is this ‘entangle-

ment’ that is the key to a quantum computer’spower: in effect, a rigid coupling is intro-duced between the quantum bits, which canthen no longer be considered individually butare affected simultaneously by a calculationaloperation. It is thanks to this capacity for parallel processing that a quantum computershould be able to perform calculations muchfaster than a classical computer.

The original proposals for quantumcomputers were based on atomic systems1,such as atoms held in traps, where the quan-tum bit is formed by two energy levelsbetween which an atomic electron can maketransitions. Now that semiconductor quan-tum dots have been synthesized, it opens upthe possibility of mimicking these approach-es in a solid-state environment. Quantumdots, tiny clusters of semiconductor materi-al, are often called ‘artificial atoms’, becausethe charge carriers in these systems (elec-trons or holes) can only occupy a restrictedset of energy levels, just like the electrons inan atom. In fact, quantum dots offer a varietyof two-level systems, based on charge or spin

© 2002 Nature Publishing Group