The past decade has seen dramatic developments in studies of the genetics of ageing and longevity, mostly involving model organisms such as the nematode worm Caenorhabditis elegans, baker's yeast, fruitflies and mice1. This has created considerable optimism that an understanding of the biology of ageing is within reach. So far, scores of ageing-related genes have been identified, in which altered activity increases longevity or accelerates ageing. But simply identifying these 'gerontogenes' often sheds no light on the real question at stake — what are the actual biochemical processes that determine lifespan? The findings reported by Murphy et al. on page 277 of this issue2 represent an important step towards the answer. Using DNA microarray technology, these authors have identified a large set of genes whose activity is linked to lifespan, and they provide evidence that many of these genes act in concert to control longevity and ageing.
A prime example of an interesting gerontogene that had, until now, provided little insight into the mechanics of ageing is daf-16. This gene encodes a transcription factor, DAF-16 — a protein that modifies the activity of other genes — which is a powerful regulator of C. elegans lifespan3, 4. DAF-16 is switched off by a hormonal signalling pathway akin to that activated by the mammalian insulin and insulin-like growth factor 1 (IGF-1) proteins5. Reduced activity of this pathway can greatly increase adult life span not only in C. elegans6, but also in fruitflies7 and mice8. Even ten years ago, it was clear that to understand ageing thoroughly we would need to identify the genes regulated by DAF-16 (ref. 6). Yet screening for mutants failed to identify any of these 'downstream' genes.
Fortunately, a new technology has emerged that is well suited to addressing this question: DNA microarrays. Using microarrays, researchers can take a snapshot of the activity of most of the genes in the fully sequenced C. elegans genome. By comparing the snapshots from normal animals to similar snapshots from animals in which a particular gene is mutated, it is possible to work out which other genes in the mutants are activated or repressed as a result of that mutation. Murphy et al. used this technology to identify two classes of genes that are activated or repressed by DAF-16. Class 1 genes are switched on by DAF-16 and are associated with increased lifespan, whereas class 2 genes are repressed by DAF-16, and are associated with reduced lifespan. Using these analytical approaches, the authors found 189 class 1 and 122 class 2 genes.
But do any of these genes actually have a role in determining lifespan? To test this, Murphy et al. analysed the genes' functions, using an elegant methodology called RNA interference. If C. elegans are fed bacteria that produce pieces of RNA matching a given worm gene, the activity of that gene is reduced, or silenced. The expectation was that in some cases, silencing the genes in class 1 would reduce lifespan, whereas silencing class 2 genes would increase lifespan. As it turned out, a surprisingly high proportion of genes behaved as predicted.
This is an important finding. The previous failure to identify genes that act downstream of DAF-16 had raised the gloomy prospect that this protein might regulate numerous genes that act in concert, such that inactivation of any single gene would have no perceptible effect. Instead, it appears that the increased longevity resulting from DAF-16 activation is due to the additive effects of many genes, which individually exert a small effect on lifespan. This is a satisfying discovery, because if individual downstream gerontogenes had little effect on ageing, it would be difficult to see how longevity could evolve.
So does the identity of DAF-16-regulated genes explain the biochemistry of ageing, or is it just another big list of gerontogenes? The list certainly gives a few inklings. One influential theory of the biochemistry of ageing is the oxidative-damage theory: over time, oxidative by-products of metabolism cause molecular damage, which accumulates and eventually causes ageing and death9. Consistent with another recent microarray study involving daf-16 (ref. 10), Murphy et al.2 found that some of the genes that are upregulated by DAF-16 do encode enzymes that protect against or repair oxidative damage (Fig. 1).
Figure 1: Ageing versus long life: the molecules involved.
Murphy et al.2 have found that the transcription factor DAF-16 controls the expression of a battery of genes, many of which have small effects on lifespan — promoting either ageing or longevity — in Caenorhabditis elegans. Consistent with earlier studies, the pro-longevity genes include some that encode antioxidant enzymes and others encoding heat-shock proteins, which can restore misfolded proteins to their active conformations. Genes that promote ageing include some that encode yolk proteins, consistent with a link between ageing and reproduction. Another pro-ageing protein is the insulin-like INS-7, which, by binding to the insulin/IGF-1 receptor (DAF-2), may repress DAF-16 on the same and other cells. This suggests the presence of a positive feedback loop that regulates DAF-2 activity. There are also many other proteins whose mechanistic links to ageing are as unclear as they are intriguing. Arrows indicate activation; T-bars indicate inhibition.
High resolution image and legend (49K)But numerous other biochemical processes are implicated; DAF-16 also regulates genes involved in antimicrobial responses, genes for several protein-digesting enzymes, metabolic genes, and many genes of unknown function. Finally, several signalling molecules seem to influence longevity, including an insulin-like protein encoded by ins-7 — one of the bewildering multiplicity of 39 such genes in the C. elegans genome. Potentially, the most important proteins identified are among the many whose mechanistic link to ageing is mysterious. It is tantalizing to think that among these proteins could be some that determine the differences in longevity between animal species, and control human ageing.
Seeking insight into the biochemistry of ageing, Murphy et al. panned their mine of microarray data for genes that fit existing expectations — an approach sometimes referred to as 'fishing'. But the drawback with fishing is that it is all too tempting to fit your data to the hypothesis, rather than the other way around. What is needed now is an unbiased and statistically rigorous analysis of which functional classes of genes are controlling lifespan. Such an approach would be better able to identify processes not previously known to be involved in ageing. The raw microarray data generated by Murphy et al. are publicly available, so other researchers should be able to analyse the data further and fully realize the value of this information.
Understanding the function of the impressive list of genes identified here2, and their role in ageing, must be the next major task — one likely to take years of painstaking analysis. This will mean much hard work at the molecular-biology coalface, after the heady interlude of microarray analysis.
