Volume 4, Issue 27 April 2007
Teaching Biology In the Twenty-First Century
Yeast geneticist Jasper Rine has been named a Howard Hughes Medical Institute Professor and the director of UC Berkeley's Center for Computational Biology.
Since Aristotle's first attempts to classify the animals, biology has been a primarily descriptive pursuit. Even well into the twentieth century, much painstaking work was required to produce precious little biological data. But as researchers have learned to manipulate the genome with ever greater facility, that equation has undergone a fundamental shift.
UC Berkeley Professor of Genetics, Genomics and Developmental Biology and QB3 faculty affiliate Jasper Rine has had a front row seat to this revolution during his thirty-year career as a professional scientist. And he sees the trickle of data biologists once wrested from their experiments exploding into a flood.
While the Human Genome Project required some 13 years and $2.7 billion taxpayer dollars, Rine predicts that within ten years, the average American will be able to have his or her personal genome sequenced for less than $1,000.
Interpreting what those genes do, however, is proving problematic. At present, scientists understand less than one percent of the variations in people's genome sequences. "If we don't do something soon, we'll be at a time when parents will have the sequence of their child, will see that their child is different than 'normal' and we won't be able to interpret 99 percent of the differences between this child and the reference 'normal' human genome sequence. We'll have the key to the kingdom of understanding our individual biology, but not know where the lock is," Rine says.
Berkeley's behemoth introductory biology course enrolls 1,200 undergraduates per year.
Rine and UC Berkeley are acting to channel the information overflow in new and more efficient ways. This fall, Rine was named director of the university's Center for Computational Biology for a three-year term. By bringing together experts in genetics, computer science, mathematics, and other fields, the center will arm a new generation of scientists with the tools to analyze genomes and model complex biological processes. Research so far has included computer programs that help predict protein function by applying principles of evolution to the study of genomes, studies of genome organization and control, and the historical events that led to the evolution of humans from their last common ancestor with other primates.
These innovations have the potential to transform the curiosity of a personalized genome sequence into lifesaving information. Any two people differ in about 6 million letters of the 3 billion letter human genome sequence. Some of these differences are of no importance to us, whereas others play a critical role in our health and well-being. For example, 30 percent of people in the United States carry a gene variant that elevates the amount of a chemical called homocysteine in their blood. High homocysteine levels are associated with a higher risk of cardiovascular problems such as stroke and heart attacks. Those who know they have the defect can compensate by eating more of the vitamin folate – a simple change that could fundamentally improve their health and longevity.
Ironically, the very advances that have opened these new vistas into the life sciences have left a key component of Berkeley's undergraduate biology program lagging behind. More than 1,200 undergraduates per year take the Introductory Biology course, also known as Bio1A. This instructional behemoth includes a laboratory component that runs more like an aircraft carrier with great momentum but one that has difficulty changing course.
"We have lab sections every morning, afternoon, and evening, Tuesday through Friday. Monday, we need all day to set up the labs. The staff have done an amazing job just keeping this course on track. However, over the last few decades, the field has moved more quickly than the labs have been able to adapt," says Rine.
This state of affairs won't last for long. Last April, Rine was awarded $1 million by the Howard Hughes Medical Institute expressly to revamp Bio1A's labs.
Jasper Rine will use a million-dollar grant to inject elements of modern genetics, statistics, and the spark of original experimentation into the venerable Bio1A lab classes.
Most labs conducted on such an industrial scale teach useful laboratory skills, but traditionally ask students to obtain answers to experiments whose results are already known. Rine wants to introduce the element of novel scientific investigation, including having students sequence a segment of their own mitochondrial DNA.
"These genes have an evolutionary clock that ticks faster than the clock in nuclear DNA. Because there will be more differences in each person's mitochondrial genome, it will make it easy to track population evolution," Rine says. The late UC Berkeley biochemist Allan Wilson used the same approach to calculate that the last common maternal ancestor of all humans lived in East Africa about 200,000 years ago. "I want to build on that history and let students see how their sequence fits into the tree of humanity," Rine says.
Other potential experiments include having students analyze algae strains with novel mutations in their photosynthetic machinery, and isolating viruses from bacteria found in the poop of zoo animals. The idea is to inspire students to conduct their own research and potentially join the labs of campus scientists.
Rine's plans to renovate all twelve lab modules over four years. He'll be developing and testing three new modules at a time over the summers with the assistance of undergraduates, staff, and HHMI teaching fellows such as geneticist and postdoctoral student Jacob Mayfield. "A million dollars sounds like a lot of money, but over four years, with supplies and the price of equipment—like the two $30,000 spectrophotometers we'll need—it goes quickly." But to produce the biologists of the twenty-first century, it's money well spent.
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The Protein Machine
Building a protein, like assembling a car, is a complicated business. It requires reading blueprints, finding parts, and attaching each component in the right order. Automakers rely on a combination of sophisticated robots and trained human workers to get these jobs done. Cells, however, are more efficient. They use a single organelle called a ribosome to perform all of these functions simultaneously.
Ribosome researcher Jamie Cate is now enlisting the aid of microbes to produce biofuels as an energy alternative to petroleum. Photo credit: courtesy Jamie Cate
"The ribosome is in some respects the prototypical nanomachine," says Jamie Cate, a UC Berkeley professor of biochemistry, molecular biology, and chemistry and QB3 faculty affiliate.
Cate is among the leaders in the current effort to map the ribosome's structure. Since its discovery in the 1950s, the ribosome has largely rebuffed scientists' attempts to study its structure in detail. What it looked like—and therefore how its parts operated—remained in frustratingly soft focus. Cate's work has provided some of the clearest images of the ribosome to date. His results are not only unveiling new aspects of this critical cellular component, but could eventually lead to designs for an entirely new generation of antibiotics.
The ribosome is about as complex as cellular machinery gets. Its job is known as translation: deciphering a genetic transcript known as messenger RNA (mRNA) into the amino acid sequence of a protein. The ribosome plays many roles. It holds both the mRNA and the growing protein chain, regulating which amino acid should be added next. It serves as a platform where helper molecules can land. It forms a bond between the protein chain and each new amino acid. Finally, it ratchets the growing protein forward so that the process can repeat and the chain can lengthen, a step called translocation.
The Escherichia coli bacterium ribosome caught in the act of protein synthesis. This ribosome (shown in grey, blues, and purples) is complexed to a DNA transcript called messenger RNA (mRNA). Also bound to the ribosome is a portion of transfer RNA (labeled ASL); its job is to deliver an amino acid. The ribosome slides along the mRNA, "reading" each segment to determine which amino acid is needed next to assemble the protein. Image credit: Veysel Berk and Jamie Cate
"It's the universal translator; it converts the four-letter code of mRNA into the 20-letter code of proteins," Cate says.
Though large for an enzyme, the ribosome is far too tiny to produce clear images under a conventional microscope. Instead, Cate uses a technique called x-ray crystallography, which provides the most detailed information about protein and RNA structure. It requires arranging trillions of copies of a ribosome into the ordered lattice of a crystal. When hit by x-rays, this repeating unit scatters the radiation in a distinctive pattern. Cate can then use computers and the intuition that comes of long scientific experience to decipher its structure.
The need to freeze this active biomolecule in order to study it has long been the bottleneck in ribosome studies. "It functions as a moving machine, with moving parts. It makes proteins at a clip of about 20 amino acids per second. But growing crystals – that takes weeks. We're slowing it down to try to isolate snapshots of all the things going on as it adds each amino acid," Cate says.
Despite these obstacles, and Cate and colleagues have been able to grow crystals that diffract well enough to provide high quality images. Bombarding the crystals with powerful x-rays from the Advanced Light Source at Lawrence Berkeley National Laboratory enabled the researchers to produce images so detailed they pinpoint the position of virtually every atom.
"It's the difference between knowing the car has an engine and knowing how that engine actually works," Cate says.
This past fall, the group was able to characterize a ribosome gripping both an mRNA transcript and part of a tRNA helper molecule delivering the first amino acid of a protein. These crystals contain copies of the ribosome in different poses, or conformations.
Though the ribosome they analyzed comes from the gut bacterium Escherichia coli, it provides plenty of insight into the ribosomes of humans and other animals. Because ribosomes are so vital to cell survival, they are among the most conserved, or unchanged, organelles in the tree of life. "You can take ribosomes from just about any organism and at some level translate mRNAs from any other," Cate says.
Close-ups of mRNA (gold) and tRNA (green) molecules within the ribosome (light blue). The three nucleotides of this mRNA code for a specific amino acid. By forming hydrogen bonds with the mRNA, the tRNA can put its amino acid in position to be added to the protein. Image credit: Veysel Berk and Jamie Cate
A large percentage of known antibiotics target bacterial ribosomes, including tetracycline, erythromycin, and streptomycin. Many of these antibiotics have been isolated from microbes themselves. "It's a byproduct of the chemical warfare that's been going on among bacteria for hundreds of millions of years," Cate says. "We want to understand how these natural products inhibit translation. Then, based on what we understand about the ribosome mechanism, we should be able to come up with new ways to stop bacterial translation based on the old compounds."
Cate's latest project involves helping to make biofuel production a reality. The project will contribute to the Energy Biosciences Institute collaboration UC Berkeley has developed with petroleum producer BP and several other research institutions. Cate's plan is to engineer bacteria to produce proteins capable of breaking down plant cell walls into simple sugars. Those sugars can then be used to feed other organisms that would then produce ethanol or other fuels. Says Cate, "It's not a substitute for conservation or other measures, but it is one piece of the puzzle."
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Self-Tuning Genes
Rachel Brem studies yeast genes in hopes of finding ways to easily locate and analyze potentially harmful gene variations in humans. Image credit: Courtesy Rachel Brem
When scientists first began studying the human genome, they thought its 3 billion base pairs of DNA might harbor as many as 100,000 genes. Less than ten years later, in 2004, they revised that number sharply downward to between 20,000 and 25,000—just a third more than the lowly roundworm. How can a creature as complex as Homo sapiens have so few instructions? One answer is that we make the most of the DNA we have by carefully regulating how those genes are used.
For example, in some cases, proteins are responsible for regulating their own production. This can happen directly, as when a protein stops its gene from being read; or indirectly, as when a protein interacts with other cell factors to amplify its gene's expression. Researchers don't yet know how many genes self-regulate. If the mechanism is widespread, it could be useful in tracking down mutations responsible for cardiovascular disease, diabetes, schizophrenia, and other disorders controlled by multiple genes.
Rachel Brem, QB3 faculty affiliate aand professor of genetics and development who joined the UC Berkeley faculty just last spring, studies such regulatory networks in the context of entire genomes. She hopes to find characteristics that will make it easier to identify self-regulatory genes, and home in on the mutations most likely to cause disease.
Brem uses yeast as her model organism. This member of the fungus family offers many advantages in the lab, Brem says. "We can address questions like how the genome is organized, and how genes work together, in a lot more depth because so much is already known about yeast and the experiments are easy to do."
Brem's first order of business, after setting up her lab, will be to assay each of the roughly 6,200 genes in yeast to see if their expression is controlled by a feedback mechanism. She'll insert a jellyfish gene known as green fluorescent protein (GFP) into each stretch of yeast DNA that codes for a protein. Then she'll grow these yeast on Petri dishes. In the dark, these modified colonies will glow like miniature stars. She'll compare their glow against colonies where she's deleted the yeast portion of the marked gene. If the deleted strain gets brighter or dimmer, Brem can conclude that the gene is involved in a regulatory feedback network.
Yeast colonies genetically engineered to produce a protein that glows green. Rachel Brem is analyzing how brightly these colonies grow in order to find genes that regulate their own expression. Gene feedback networks are implicated in complex diseases such as diabetes and heart disease. Image credit: Courtesy Edward Marcotte's laboratory, CSSB, University of Texas at Austin
"We're looking for patterns," Brem says. "Are there certain functions or classes of genes associated with regulatory feedback? How frequent are they in the genome and why?" Because the number of genes Brem must process are so large, she'll be fishing for commonalities among regulatory genes using computer algorithms of her own devising.
Researchers such as UC Berkeley's Adam Arkin have found that regulatory feedback is associated with chance fluctuations in mRNA or protein levels—a phenomenon called expression noise. "Even though they're all genetically identical, and grown under the same conditions, yeast clones don't express certain proteins at exactly the same level," Brem says. "Some genes are noisier than others. That makes people think the cell is actively tuning the distribution around an expression level set by the regulatory network." Noise may ensure that a few individuals can handle abrupt changes in their environment. In other words, if a colony is suddenly assaulted by toxic chemicals or high heat, a few individuals will already have expression levels suited to those conditions.
As for Brem's ultimate goal? "We'd like to have a computer program smart enough to make a prediction about which would be disease-linked without doing any other experiments," Brem says. "But we haven't seen enough of those mutations so far, so we don't know how to recognize them yet." With her perseverance and prowess at computational analysis, that lack of data should be replaced with new insight into the organizing principles of our DNA.
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