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Lee Makowski from the Argonne National Laboratory outlined the U.S. Department of Energy's ambitious plans for determining the three-dimensional "folding" of all proteins The shapes of proteins is how they work. In the past, it took years to figure out these shapes. The academic mantra used to be, one graduate student, one protein, one Ph.D., one career. According to Makowski, getting the three-dimensional structure of a protein used to measured in man-years. The record now at the Argonne Lab is six hours.
In the afternoon, I dropped by a symposium that asked the provocative question, "How Long Can Humans Live?" The dour Leonard Hayflick, from the University of California-San Francisco, kicked off the session. Hayflick made his reputation by discovering that animal cells divide only a set number of times before they senesce and die. Hayflick insists on a useful distinction between lifespan and life expectancy. Lifespan is the longest that any member of species has ever lived. In the case of humans, this appears to be the Frenchwoman Jeanne Calment who lived to be 122 years old. Life expectancy is the age at which 50 percent of any given population cohort has died. Life expectancy in the U.S. is around 76 years today.
Hayflick made the point that if deaths from cancer, heart disease, stroke, and the like were all eliminated, that would increase life expectancy by only 15 years. Hayflick also insisted on a distinction between research on aging and geriatric medicine. Hardly anyone is researching aging; instead they're focusing on diseases that appear in old age, he complained. For example, half of the budget of the National Institute on Aging is spent on Alzheimer's research, claimed Hayflick. Yet if one eliminated Alzheimer's entirely, one would add only 19 days to average life expectancy in the U.S.
Hayflick believes that aging is the result of increasing molecular disorder in cells. Cellular repair mechanisms do a good job of fixing damage until after we pass our reproductive period. Once humans have successfully reproduced, then natural selection has no reason to worry about whether their cells get repaired or not. Thus we age, because from the point of view of natural selection, there's no reason for us to hang around after we've produced progeny.
Hayflick claims that aging is a phenomenon unique to humans and the animals we choose to protect. In the wild, humans and animals died well before they experienced aging. He says that prehistoric remains of humans have not revealed that our ancestors lived beyond age 50. Hayflick doesn't hold out much hope that scientists will be able to conquer ageing any time soon. Which is just fine by him, since he believes that neither individuals nor society would benefit from the prevention of ageing.
Demographer Jay Olshansky from the University of Chicago was not much cheerier. He agreed that if all cancer, cardiovascular disease, diabetes, and the like were eliminated, average life expectancy in the U.S. might reach 90 years, up from 76 now. He pointed out that if every cause of death before age 50 were removed in the U.S., that would boost average life expectancy by only 3.5 years. Mathematically, in order to boost the average life expectancy of a particular cohort to 100 years, 18 percent of that cohort must live to be over 122. So far, that's been achieved by only one person. The only way to really raise life expectancy is to retard or eliminate aging.
George Martin from the University of Washington was a bit more upbeat. It is theoretically possible that as few as 300 genes may be involved with aging and among them a very few might have a big effect. But he agreed with the Hayflick's evolutionary point that deleterious genes that express themselves after age 45 have no effect on reproductive success therefore natural selection doesn't bother to eliminate them. He illustrated this point by looking at the ApoE genes that are involved with Alzheimer's disease. It is now known that carriers of theApoE4 variant of the gene tend to have early-onset dementia. It has not been eliminated by natural selection because dementia begins after 45. Even more interestingly, the ApoE4 variant is far more prevalent among Africans and people descended from Africans. The ApoE4 gene is not very good at delivering lipids to membranes. This is important because the endemic African organism that causes sleeping sickness needs lipids to survive, so the ApoE4 gene protects carriers from sleeping sickness at the expense of causing dementia and cardiovascular disease after their reproductive years are passed.
What evolution grants, it can take away.
San Francisco, CA, Feb. 18 - "I live in Washington, D.C.," confessed Science senior editor Barbara Jasny as she opened the "Beyond the Human Genome" seminar at yesterday's session of the Association for the Advancement of American Science's annual meeting in San Francisco. "In Washington, you get used to hype and spin, but this is one time when all the words--landmark, milestone, revolutionary--really do apply."
Jasny's right. But then she showed herself a true denizen of D.C. when she indulged in what is rapidly becoming a standard ritual whenever scientists speak of the human genome. She claimed that "the discovery that it takes far fewer genes than we thought to make a human being is causing people to re-evaluate our relationship to other species." In strict biological terms that is certainly true, but Jasny's utterance is supposed to take us arrogant humans down a peg or two since, after all, it takes only a few thousand more genes to make us than it takes to make a nematode. Rubbish. When a nematode can devise a culture capable of sequencing its own genes, then I'll eat humble pie. But not before.
Most of the morning session of the Genome seminar was devoted to discussing where scientists plan to go from here. That means that there were few new findings to report since the announcement of the publication of the draft sequences of the human genome in Science and Nature earlier this week.
The first presenter was Mark Adams, who is Vice President for Genome Programs at Celera Genomics, the private company that raced the publicly financed International Genome Project consortium to the finish line. Adams gave a quick overview of how Celera had sequenced all 3.2 billion DNA base pairs of the human genome in only 9 months. Adams told the audience that Celera has now sequenced the genomes of 3 different strains of mice and despite the fact that mice and men last shared an ancestor 80 million years ago, they are genetically very similar. "The mouse genome is going to be a tremendous resource for learning about the human genome," said Adams. For example, Adams said that "there are many genome regions that are conserved between mouse and human that do not code for protein." Generally speaking, if a lot of different species share similar segments of DNA, that means that those segments must be important or else natural selection would have eliminated them is some species. Adams thinks that these conserved regions in mice and men probably exercise some sort of regulatory control over other genes. If scientists were unable to compare different animal genomes, these regions would likely not have been found so quickly.
Next up was Eric Green, who works at the National Human Genome Research Institute. He made some suggestions for which animal genomes should be sequenced next. Having other genomes to compare will help uncover the functions of the third of human genes whose functions are currently unknown. "Virtually all mammals have genomes that are roughly 3 billion base pairs," said Green. Why not sequence a lot of different genomes? Cost. Right now it costs between $10 to $15 million to sequence a genome once and one should really do it at least 4 times to make sure that it's accurate, so the costs run to around $50 million per completed animal genome. "Of course, if sequencing technology dramatically improves, then all bets are off," said Green. After the mouse genome, the next one is rat. Sequencing work is going on with various other animal species including chimpanzees, baboons, cows, cats, dogs, chickens, zebrafish and pufferfish. At the end of Green's presentation, a scientist from the audience complained about how hard it is to use the government's gene data banks compared to Celera's much easier system, and asked "Why can't the government do better than government work?"
The afternoon session began with Michael Eisen from Lawrence Berkeley National Laboratory and University of California at Berkeley. "It shouldn't surprise anybody that you can have lots of different things come out of the nearly the same sets of gene repertoires," said Eisen. "After all, you already have very different things stemming from the same set of genes inside yourself now. For example, neural cells don't look very much liver cells." The DNA may be similar, "but the differences come from regulation, and everything in a cell is regulated."