Systems biology holds tremendous promise for the future of science and medicine, but some have criticized the field's lack of practical solutions. Experts counsel patience, saying progress has been strong and is accelerating.
Ten years after the successful completion of the Human Genome Project, biologists and chemists are working together to form a comprehensive model of biological systems. This is a daunting task, dwarfing efforts to decode a genome and testing the limits of analytical science and computational resources. Genes are only one piece of the puzzle. Researchers must understand the mechanics of genetic transcription, the dynamics of protein folding, how enzymes work, and how cells communicate. Due to the complexity of the "system", it is difficult to gauge progress. R&D Magazine recently spoke to former Scientists of the Year Dr. Leroy Hood of the Institute of Systems Biology, and Dr. Richard D. Smith of Pacific Northwest National Laboratory (PNNL) to find out where systems biology stands today.
Systems biology progress report
When Leroy Hood founded the Institute of Systems Biology (ISB) in 2000, the term "systems biology" had only recently been coined; the term is still not well-defined as the field constantly changes. But, according to Hood, the concept can be distilled to the following definition: The study of the dynamics and functions of all the key informational levels in a system to explain its emergent properties.
"There are a lot of alternative definitions. There are people who think 'omic' analysis is systems biology, and by itself it certainly is not. There are people who think that top-down modeling is systems biology, but it's not that either. Systems biology is really an integration of all of these different things," says Hood.
Philosophically, Hood's view of progress in systems biology research is broken down into three distinct components. First, scientists must assemble a toolkit of all the biological parts that make up the system. Second, they must understand how those parts interact. And lastly, they must understand how those interactions add up to the whole organism. This framework helps shape the research approach at ISB, which has grown to include more than 240 scientists.
"Up to now, we've done massive work on the parts list. We've made great progress in being able to quantify RNA and being able to use microarrays and DNA sequencing to measure RNA," says Hood. "For the future, the whole focus is going to be getting from quantifying biological functions to learning about the dynamics and to correlate those functions. The use of microfluidics and nanotechnology is going to be important, and I think it is going to be absolutely essential to extend the computational techniques we have now to include multiscale integrations."
This is a critical area for Hood, who is a believer in the ability of computer modeling to achieve a better comprehension of small-scale biology. Scale is only part of the equation—with multiscale analysis researchers can draw correlations between activity at the cellular and systems level. Although still in its infancy, this type of modeling, he believes, will be among the first applications to leverage exascale computing power.
At ISB, Hood has identified specific goals for systems biologists in the next decade. One pressing need is the ability to decipher the logic of promoters, a section of about 100 to 1,000 base pairs in a region of DNA that initiates gene transcription. They are an important part of the gene regulatory system that includes silencers and enhancers that work in concert to manage genes.
At the cellular level, he says, the methods of cell-to-cell communication are still poorly understood and need deciphering before computer models of cellular systems can be effective. Finally, he would like to see the emergence of omics for small-molecule mediators within the next decade.
"We have to do omics at the single-cell level. If we are able to use single-cell biology, we can determine how discrete populations interact both in vivo and in vitro. I think that we can use nanotechnology to integrate and automate chemical procedures at the cellular level, such as using protein capture agents that can hold antibodies. One of the most exciting advances for me is the ability to use systems biology approaches to identify blood diagnostic parameters," says Hood. A broad analysis of blood for biomarkers is a powerful way to facilitate early diagnosis and progression of many types of diseases, and even psychological phenomena such as post-traumatic stress.
"The second area that I'm really excited about is the whole family of genome sequencing techniques. We are getting really good at sequencing and can even modify disease sequences," says Hood.
The importance of analytical science
According to PNNL's Richard Smith, one of the most highly cited biochemists in history, successful progression in biological science has a lot to do with the molecular basis for modern biological research. The key, he says, is the ability to make accurate measurements at the molecular level and having the ability to apply computational resources to arrive at a conclusion regarding the data.
"Those are the key components of systems biology. You have to measure the pieces that are there and identify the gross biological perturbations," say Smith. Despite this progress, he believes systems biology research is still in its nascent stages. "I think systems biology has a bright future, but the techniques and capabilities are still developing. The development of experimental genomics has been rapid, but the computational side of things has a long way to go."
What's exciting to him is the progression in analytical tools that have allowed great progress in genomics and building a clear picture of the transcriptome. These capabilities have come a "tremendous distance", he says, but other omics, such as metabolomics, proteomics, and others, are less mature.
"Our understanding of what is needed is really quite sophisticated. In studies of simpler microbial systems, the capabilities we have are really quite advanced and have improved remarkably in a relatively short period of time," says Smith.
For Smith, the real driver of systems biology in recent years has been technical advancement in mass spectrometry and separations science. Genomics benefited first. Now, spectrometry techniques are moving to other omics disciplines, contributing to broad understanding of the proteome through targeted measurements.
The ability to make these measurements in a quantitative fashion is important, but it also manages to avoid the missing data problem that currently plagues analyses in these omics fields.
Because data collection is accelerating at a breakneck pace, automation is another essential component to successful systems biology research.
"A hot area of work at present is integrated measurement. This represents a different pipeline for each omics fields. If we can integrate those pipelines, we can greatly increase the rate of data collection," says Smith. Such advances will also improve the quality of data because it can be cross-referenced, or corroborated, against data collected simultaneously from the same sample.
Looking further ahead, Smith sees another potential breakthrough on the horizon. Currently, mass spectrometry exists as standalone systems that can cost up to $500,000 or more. The "holy grail" in this area of technology is a way to achieve massive parallel measurement capability. Smith anticipates someday having the ability to take any sample, and use chromatography to fracture it into a hundred samples for simultaneous spectroscopic analysis.
"This could help solve one of the failings right now, which is the incomplete measurements of the proteome," says Smith.
So far, Smith's research group can only dream of such capabilities. But his team has been successful in pathogen modeling work in recent years, collaborating with several organizations to describe how the Salmonella pathogen operates. Their techniques include capillary liquid chromatography with mass spectrometry to extensively characterize proteins present in both wild and mutant strains. Concurrently, parallel whole-genome microarray analysis has determined the transcriptome in matched samples. They hope to discover the consequences of mutations in the expression of proteins by the pathogen.
According to Smith, the core goals of his work at PNNL, which require broad but targeted measurement techniques, is difficult to do in an industrial setting simply because of its wide focus. It typically lacks immediate return on investment.
"This kind of research has largely disappeared from industry, and it's hard to do in a university environment. It requires a large team and a collaborative environment," says Smith.
But down the road, he says, as the payoffs increase, so will interest from private corporations, which are closely watching progress in systems biology.