Gordon hopes to eventually answer much broader questions about humans’ microbial inhabitants. How does the makeup of these communities contribute to a person’s health? What is the origin of each person’s distinctive microbial menagerie? Are a person’s microbes determined mostly by her diet, or by where she lives, or by some other aspect of her lifestyle? How do our microbial populations change over time? And perhaps most important, can we tinker with an individual’s microbial profile to improve his or her health? Ultimately, says Gordon, “we’ll get a much more transcendent view of ourselves as a supraorganism, with traits encoded by our human genes and by those in the genomes of our microbial partners.”
Sequencing Microbial Complexity
One floor below Gordon’s lab is Washington University’s Genome Sequencing Center, one of the primary sites of the Human Genome Project. The center houses more than 130 “traditional” sequencing machines, capable of reading five to six billion letters of DNA every month. During a recent tour of the facility, Gordon whizzed past these genomic workhorses and down a hall to the room that houses the center’s newest acquisitions: two sequencing machines made by 454 Life Sciences of Branford, CT. The machines are among the world’s fastest gene sequencers, each reading an impressive 100 million DNA letters during a seven-hour run (see “Sequencing in a Flash,” May/June 2007).
The 454 sequencers are at the heart of Gordon’s next project. Researchers hope to learn how to manipulate the way microbes affect energy storage and metabolism–to predict and perhaps reduce the risk of obesity, or to aid people who are undernourished. To understand these effects, Gordon plans to compare the microbial profiles of family members–obese and lean siblings and their mothers–in unprecedented depth. That’s possible thanks to the new machines, which can sequence hundreds of thousands of pieces of DNA in a single experiment; older machines can handle just a few hundred. Only after researchers have generated microbial profiles of many different people will they be able to gauge the normal variability of microbial profiles in people of different ages and origins. That, in turn, will help them determine which specific microbial changes can be linked to illnesses or other health issues.
A comprehensive effort to catalogue human microbial populations is far too large for a single lab to undertake. The National Institutes of Health acknowledged that in May by designating the human microbiome a “Roadmap initiative.” That means that significant funding will be available to support research in this area over the next five years. Scientists hope the initiative will ultimately blossom into a microbial version of the Human Genome Project. The project will be challenging. “Even though a microbial genome is one-thousandth the size of the human genome,” says Baylor’s Weinstock, “the total number of microbial genes in [the human] body is much greater than [the number of] human genes, because you have so many different species.”
The success of the project will depend not just on ever-faster sequencing technologies but on new techniques for analyzing all that data. Scientists can examine a metagenomic sequence in two ways: by studying microbial species separately and by studying the community of different species as a whole. The first approach involves piecing together individual genomes to deduce the roles that different species play in the gut. Most genomic-analysis tools, however, have trouble with the genetic soup that constitutes a metagenomic DNA sample. The second approach is to look at the genes from an entire microbial community at once, without trying to analyze how they fit together into genomes. This approach gives a better picture of how bacterial communities may have evolved to function as a group, but it has its own limitations. Metagenomic studies of the ocean and other ecosystems have already revealed an unexpected bounty of genetic diversity; many of the genes uncovered are entirely novel and their functions entirely unknown. So scientists will also need better ways to predict these genes’ functions.