Systems biology

New views of life

"One long-term goal of this research is to develop targeted drugs that are effective for a specific disease," says Michelle Buchanan, director of ORNL's Chemical and Analytical Sciences Division. "To design these therapeutic drugs, you need detailed knowledge about the many molecular-level processes that occur within a cell." Acquiring such knowledge is not an easy task.

"We frequently hear about new human genes that play a role in cancer and diseases of the heart, central nervous system, and other organs," says Reinhold Mann, director of ORNL's Life Sciences Division. "Some diseases can be traced to one altered DNA base pair in a particular gene. However, genome characteristics or changes that make some people more likely to get sick involve complex, intricately timed, and balanced interactions among a variety of genes and other signals encoded in the genome. Our current state of knowledge of how the genome is interpreted to provide the diversity of life is extremely limited."

ORNL researchers use various technologies to characterize DNA and proteins. This image shows the order of chemical bases in a strand of DNA. The bases are labeled with dyes that fluoresce in different colors when exposed to laser light. The sequence was obtained by gel electrophoresis in a PE Biosystems DNA-sequencing machine at ORNL.

"The next step," says Buchanan, "is to identify which genes turn on to make particular proteins. Then we must identify the protein complexes, or protein machines, in which proteins work together in the cell to carry out specific roles and help perform life's most essential functions. These protein complexes are involved in signaling pathways that tell cells what to do and allow them to communicate with each other."

Characterizing the roles of protein machines in cells is the objective of DOE's "Genomes to Life" initiative. This knowledge will help scientists predict how cells and their genes will respond to changes in the environment, such as exposure to a toxin.

Some of this knowledge will be obtained at DOE's Center for Structural and Molecular Biology at ORNL. Scientists at this user center directed by Buchanan will obtain information about protein interactions through mass spectrometry, computational biology, and small-angle neutron scattering (SANS). SANS will be conducted using the planned Bio-SANS instrument that is to be completed at ORNL's High Flux Isotope Reactor in 2003. Various studies of proteins and other biological materials are also planned. These studies will be conducted using biological instruments at the Spallation Neutron Source, to be completed in 2006 at ORNL.

Research by Oak Ridge biological scientists is aimed at learning which genes are expressed when certain microrganisms are exposed to environmental toxins or radiation. DOE is interested in funding microbial research partly because microbes can help remediate mixed waste sites by converting toxic metals from the soluble to the insoluble state to help keep them on-site.

In addition, there is great interest in learning about the proteins that are expressed by microbes under various conditions. ORNL's experts in mass spectrometry can identify proteins by determining their molecular weight and amino-acid sequence and comparing this information with that in a protein database. In this way, they can find protein signatures and then work backwards to determine the gene sequence coding for that protein, thus identifying the gene that was expressed, say, as a result of exposure to a pollutant.

A protein can have as many as 200 modifications in response to the actions of other proteins or environmental influences. These post-translational modifications (PTM), such as the addition of a phosphate or carbohydrate to a protein, can change the protein's activity. For example, if a PTM is present on a regulatory protein A, it becomes a misshapen key that no longer fits into Protein B, preventing it from turning on a downstream gene, possibly causing miscommunication between cells. Mass spectrometry is an excellent tool for identifying proteins that have been modified.

ORNL researchers seek to understand complex biological systems at the organism as well as the molecular and cellular levels, says Mann. To understand how hormone-mimicking chemicals can affect development, ORNL researchers are studying gene and protein expression in see-through embryos of zebrafish. They are also trying to identify the genes that enable trees to produce better wood products and fuels and store more carbon from the air. To understand the functions of genes in mammals, ORNL researchers are determining which genes are expressed in the skin of mice and which mouse genes in their mutant form cause maladies also found in humans, such as polycystic kidney disease, obesity, chronic hereditary tyrosinemia, and epilepsy. Researchers use microarrays (gene chips) and computational tools for these expression studies. For example, our experimental researchers collaborate with our computational biology experts, who make sense out of gene ex-pression data using super-computers. They are practicing the discipline of bioinformatics, the study of genetic and other biological information using computational and statistical techniques.

Yun You examines the image of a mouse embryo magnified in an optical microscope. The image is captured by a difital camera and then transferred to a computer.

"Knowing functions of all genes in the genome, by itself, will not lead to understanding the processes of a living organism," Mann says. "The reason is the biological system's complexity. Expression of genes can be regulated in a virtually unlimited number of ways, depending on location in the body, time in the development of the organism, and environmental conditions and exposures.

"Certain protein complexes can bind to specific locations in an organism's genome, thereby controlling the expression of a gene sometimes far away from these binding sites. The number of these regulatory protein complexes is finite, perhaps some 10,000, but taken together with the number of genes and regulatory binding sites in the genome, there is a combinatorial explosion that works against any brute force approach solely based on experimental research. That is why collaborations between experimenters and computational biologists are so important. They are a hallmark of biological investigations at ORNL."

Computational biology researchers in ORNL's Life Sciences Division have identified many genes in bacterial, mouse, and human genomes and have computationally analyzed the human genome using an ORNL-developed gene-finding computer program. They have written and used assembly programs and analysis tools to produce draft sequences of the 300 million DNA base pairs in chromosomes 19, 16, and 5 for DOE's Joint Genome Institute (JGI). They have also analyzed 25 complete microbial genomes (52,000 genes) and many JGI draft microbial genomes (1000 genes/day). They have predicted the structures of proteins (100 proteins/day) from amino-acid sequences using an ORNL-developed, protein-threading computer program.

The section's programmers have written algorithms and developed other tools to make it easier for biologists to use computers to find genes and make sense out of the rising flood of biological data. These data are produced in studies of biochemical pathways and processes, cellular and developmental processes, tissue and organism physiology, and ecological processes and populations. Through ORNL's user-friendly Genome Channel Web site, its Genomic Integrated Supercomputing Toolkit, and the IBM super-computer at DOE's Center for Computational Sciences, the international biology community, including pharmaceutical industry researchers and academics, have easily obtained genetically meaningful interpretations of their DNA sequences and other data. ORNL's Web site is popular in the biological community (150,000 sessions per month).

Thanks to ORNL's interdisciplinary approach to complex biology using state-of-the-art technologies, we believe we have the right stuff to better understand the stuff of life.