genomic.science@science.doe.gov
Office of Biological and Environmental Research
U.S. Department of Energy Office of Science
About BER | BER website
Susan Gregurick
Office of Biological and Environmental Research
U.S. Department of Energy Office of Science
genomic.science@science.doe.gov
Office of Biological and Environmental Research
U.S. Department of Energy Office of Science
Office of Biological and Environmental Research
U.S. Department of Energy Office of Science
Sidebar 1: DOE Genomic Science Program
Sidebar 2: Advances in Genome Engineering
Sidebar 3: Moving Toward Design-Based Biosystem Engineering
Sidebar 4: Molecular Communication Systems for Biodesign
Sidebar 5: Plant Signaling Systems for Biodesign
Sidebar 6: DOE Joint Genome Institute
Sidebar 7: DOE Systems Biology Knowlegebase
Sidebar 8: Visions for the Future of Biodesign
science.energy.gov/ber/research/bssd/genomic-science/
The Department of Energy (DOE) Genomic Science program supports research aimed at identifying the fundamental principles that drive biological systems relevant to DOE missions in energy, climate, and the environment. These principles guide the translation of the genetic code into functional proteins and the metabolic and regulatory networks underlying the systems biology of plants, microbes, and communities. Advancing fundamental knowledge of these systems will enable new solutions to national priorities in sustainable bioenergy production, understanding the fate and transport of environmental contaminants, and developing new approaches to examine the role of biological systems in carbon cycling, biosequestration, and global climate. The major objectives of the Genomic Science program are to:
i.) determine the molecular mechanisms, regulatory elements, and integrated networks needed to understand genome-scale functional properties of microbes, plants, and interactive biological communities,
ii.) develop “omics” experimental capabilities and enabling technologies needed to achieve dynamic, system-level understanding of organism and community function, and
iii.) develop the knowledgebase, computational infrastructure, and modeling capabilities to advance predictive understanding and manipulation of biological systems.
This program is supported by the Office of Biological and Environmental Research within DOE’s Office of Science.
Biosystem design is predicated on the ability to introduce large-scale changes in the genomes of a wide range of organisms. Although improvements are needed in designing and constructing large DNA segments that can be effectively inserted into genomes, recent innovations suggest that a variety of methods for genome engineering may help accelerate the development of synthetic biosystems for useful applications.
One groundbreaking approach for building large DNA molecules was demonstrated in the first complete assembly of a synthetic bacterial genome (Gibson, D. G., et al. 2008. Science 319: 1215–20). Researchers pieced together the 582,970–base pair (bp) genome of Mycoplasma genitalium by assembling smaller DNA segments into larger fragments comprising up to a fourth of the entire genome (~144,000 bp). This impressive achievement serves as a proof-of-principle for more ambitious synthetic genome projects that will be possible as the cost of DNA synthesis continues to decrease.
Several strategies for engineering genomes involve eliminating or reducing expanses of DNA that contain unnecessary regions (e.g., insertion sequence elements and associated effectors) while maintaining genes and regions essential to normal growth and division. Harnessing the natural process of recombination, in which nucleotide sequences are exchanged between similar regions of two DNA molecules, non-essential sequences can be deleted by replacing long segments of intervening sequence with truncated versions of this sequence. This technique was successfully used to reduce the genome of an Escherichia coli strain by roughly 15%. The new strain grew normally, had lower mutation rates, and was easier to transform.
Recombineering—recombination-based genetic engineering—has been automated in a powerful new process called Multiplex Automated Genome Engineering (MAGE). Using single-stranded pieces of synthetic DNA that target many different genomic locations in live cells, MAGE can simultaneously introduce hundreds of specific genetic changes across a population of cells (see figure). In just days, MAGE can generate billions of cells with various combinations of changes in multiple genes or regulatory regions, an effort that could take months or years using traditional genetic engineering methods. This large-scale approach to genomic reprogramming presents many opportunities for rapidly modifying dozens of genes related to synthesizing particular chemical products.
These select examples of innovation in microbial genome engineering provide a substantial foundation for further development and application to a wider range of organisms. The next few years hold tremendous potential for revealing new tools that use genomic engineering to expedite the design and analysis of synthetic biosystems.
Multiplex Automated Genome Engineering (MAGE). This process enables the rapid and continuous generation of sequence diversity at many targeted chromosomal locations across a large population of cells through the repeated introduction of synthetic DNA. [Credit: Wang, H. H., et al. 2009. Nature 460: 894–98.]
For traditional engineering fields, such as mechanical, electrical, or chemical engineering, the design-based construction of a device (e.g., electric circuit, engine) directly from a plan is possible, because this engineering is based on a complete mathematical understanding of the physics controlling the device components. Engineering biological systems is more challenging, because our knowledge of the principles that govern these living systems is largely incomplete.
To design a microbial system that produces a desired product, for example, researchers typically modify existing organisms based on models that are limited in their predictive capabilities. As a result, the engineering of microbial systems follows an iterative cycling of modeling, implementation, and analysis (see figure). Researchers design a strategy (e.g., introducing new enzymes or knocking out competing pathways) for engineering a microbial system based on genome-scale knowledge and models. Available models of microbial systems do not encompass all activities of a cell, so insights from the "omic" analyses of the engineered microbial system are used to revise the genome-scale models and improve predictability.
Transitioning biosystem engineering from an iterative process to a linear, design-based approach requires a synergy between biodesign and systems biology. Biosystems design can help reveal how the addition or elimination of different pathways (or other biological components) can influence the dynamic behavior of the complete system. By providing a comprehensive view of how all biological components work together, systems biology enables the discovery of organizing principles needed to assemble different components into a functional system. Building synthetic biosystems based on these principles provides an important mechanism for testing and validating biological design strategies. Other key requirements for making biosystem engineering faster and more predictable include increasing the number of well-characterized biological modules that are available to the research community, enhancing interoperability of those modules, and standardizing the tools and strategies for assembling them.
Tyo, K., K. Kocharin, and J. Nielsen. 2010. “Toward Design-Based Engineering of Industrial Microbes.” Current Opinion in Microbiology 13: 255–62.
Smolke, C. D., and P. A. Silver. 2011. “Informing Biological Design by Integration of Systems and Synthetic Biology.” Cell 144: 855–59.
Engineering Microbial Systems. As the tools for engineering microbial systems improve, and the predictive capabilities of genome-scale models become more reliable, engineering microbes will transition from an iterative cycle (a) to a linear, design-based process (b). [Credit: Tyo, Kocharin, and Nielsen 2010.]
Communication among organisms is crucial for developing synchronized behaviors that benefit the community (see figure). Molecular communication systems, which have been found in even the simplest bacteria, are used to sense dense populations and trigger responses at the genetic level to adapt to new environmental conditions. The small-molecule chemical signals (called autoinducers) used in bacterial communication are synthesized in cells and secreted into the surrounding environment where their concentration increases with increasing cell density. They can be internalized by neighboring organisms and recognized by intracellular receptors to regulate the transcription of genes that stimulate more autoinducer production and initiate a biological response to the changing environment. One of the earliest and most-studied examples of bacterial communication is quorum sensing in the Gram-negative marine bacterium Vibrio fischeri. In high population density environments where nutrient concentrations are typically greatest, these bacteria use acyl-homoserine lactone autoinducers to activate genes that control bioluminescence. Interestingly, bacterial communication systems are widespread, though autoinducers differ between species. Some bacteria, such as Pseudomonas aeruginosa use multiple quorum sensing systems to regulate many complex cellular functions related to virulence.
Molecular communication systems have been an attractive target for biosystems design given their important role in bacterial growth and physiology and the relative ease of building and manipulating genetic circuits consisting of autoinducer synthases and receptors. A number of interesting bacterial systems have been designed to have controlled and predictable behavior. One example is the construction of biological “logic” circuits in which one organism synthesizes an autoinducer, and another organism receives the signal and executes a functional response. These systems have been adapted to control bacterial population density, controlled pattern formation, and synthetic predator-prey systems. Importantly, the communication principles developed in these bacterial designs have been extended to engineer communication systems in other higher organisms and even between different organisms such as yeast and plants.
Early results using bacterial communication systems have helped develop computational approaches that account for simple behaviors and predict outcomes of more complex designs. However, continued advances in genome engineering and computational modeling of increasingly complex behaviors will be needed to reach the long-term goal of de novo design of synthetic biosystems for diverse biotech applications.
Bacterial Communication. Bacteria, such as these Shewanella putrefaciens cells growing on iron oxide particles, use chemical signals to coordinate biofilm formation and other community-level behaviors. [Credit: DOE Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory.]
Redesigning gene products, pathways, and systems in plants represents a significant opportunity for developing novel, important applications. An interesting multidisciplinary approach combining computational protein design, synthetic biology, and plant biology has recently led to the generation of plants that could detect trace levels of virtually any small molecule.
The design of these synthetic phytodetectors is based on a two-component signaling system derived from bacterial and plant proteins. In its simplest form, this system consists of a membrane-spanning receptor and a response regulator. Upon effector binding, the receptor is activated, resulting in dimerization and autophosphorylation. After accepting the phosphate from the receptor, the response regulator activates a latent DNA binding domain to regulate transcription. Once the modular system components were initially constructed and evaluated in bacteria, the signaling system was successfully transferred to plants for in situ functional analyses.
Three key attributes were required for the construction of a synthetic plant signaling system: (1) an appropriate receptor to initiate the signal, (2) a mechanism to transmit an external signal into the cell, and (3) a suitable output result to indicate the presence of the effector of interest. The receptor component of the signaling system was a bacterial periplasmic binding protein that was computationally redesigned to recognize a new chemical instead of its normal effector, ribose. One part of the transmission component is a hybrid transmembrane receptor consisting of extracellular and intracellular domains from two different bacterial systems. This hybrid receptor was also modified to enable its expression at the plant plasma membrane. The other part of the transmission component, the response regulator, was a fusion between bacterial and viral proteins designed to accept phosphorylation and activate transcription in eukaryotic systems. Once phosphorylated, the response regulator is translocated to the nucleus where it initiates the transcription of specific genes. By linking this synthetic signal recognition system to the activation of genes that rapidly produce an observable phenotype, plants can be used to detect minute quantities of particular chemicals relevant to many different application areas. For example, a hybrid signaling system has been used in plants to turn on degreening genes, which trigger a pale color in leaves that is observable within hours after exposure to a selected effector.
This research illustrates the need for multidisciplinary approaches that can combine complementary components from plants and bacteria to construct new designs, test functional attributes of new hybrid systems in simpler bacterial organisms, and then transfer these constructs to plants for in vivo analysis. Although a quantitative model has not yet been developed to describe the system’s performance, these achievements mark a breakthrough in the development of complex, synthetic signaling systems in higher organisms.
Chemical-Detecting Plants. A synthetic signal transduction pathway activates degreening genes, causing a plant to change color over 48 hours after detecting minute amounts of a chemical. [Credit: Colorado State University.]
The U.S. Department of Energy (DOE) Joint Genome Institute (JGI) is the only federally-funded high-throughput genome sequencing and analysis facility dedicated to genomes of nonmedical microbes, microbial communities, plants, fungi, and other targets for DOE missions in energy, climate, and environment. Located in Walnut Creek, California, JGI annually provides more than 1800 users worldwide with access to massive-scale DNA sequencing capabilities that underpin biosystems design and modern systems biology research. High-quality sequencing data and annotations from JGI are needed to continue to improve comparative genomics approaches, transcriptional regulatory network inferences, and predictions of how gene expression is controlled at the transcriptional level. As a leader in analyzing the genomes of organisms with novel capabilities discovered through bioprospecting in diverse environments, JGI is expanding the range of biological components and metabolic functions that can be used to design new DOE-relevant biological systems. By enabling the publication of project results in more than 150 peer-reviewed journal articles each year and depositing data in public databases, JGI ensures that the larger scientific community can access and benefit from its contributions to genome science. Supported by the DOE Office of Biological and Environmental Research, JGI is managed by Lawrence Berkeley National Laboratory.
DOE Joint Genome Institute (JGI). With advanced capabilities for sequencing and analyzing genomes, JGI supports projects around the world investigating the genomes of microbes, microbial communities, and plants relevant to U.S. Department of Energy missions. [Credit: DOE JGI.]
Driven by the ever-increasing wealth of data resulting from new generations of genomics-based technologies, research on biological systems is demanding a computational environment for comparing and integrating large, heterogeneous datasets and using this information to develop predictive models. To provide the research community with such a resource, the Genomic Science program is developing the DOE Systems Biology Knowledgebase (Kbase), led by the Lawrence Berkeley National Laboratory, in partnership with the Argonne, Brookhaven, and Oak Ridge National Laboratories. A knowledgebase is a cyberinfrastructure consisting of a collection of data, organizational methods, standards, analysis tools, and interfaces representing a dynamic body of knowledge. The fully functional Kbase will support free and open access to data, analysis tools, resources for modeling and simulation, and information for the research community. Kbase differs from current informatics efforts by bringing together research products from many different projects and laboratories to create a comprehensive computational environment focused on DOE scientific objectives in microbial, plant, and metacommunity (complex communities of organisms) research. By democratizing access to data and computational resources, Kbase will enable any laboratory or project, regardless of size, to participate in a transformative community-wide effort for advancing systems biology and accelerating the pace toward predictive biology.
Some of the Kbase computational development efforts that are relevant to biosystems design should be leveraged, including the integration of heterogeneous data (e.g., genome sequencing, gene expression, protein expression, and metabolite concentration data), and the development of improved automated tools for annotation using multiple lines of evidence. Such approaches could be used to generate hypotheses about the mechanisms underlying complex traits (e.g., tolerance to biofuels or pH) or to identify candidate enzymes with desired metabolic activities. Advancing computational tools for biosystems design requires open source capabilities (so that tools can be maintained or modified by the community as needed), accessibility to both the biological and computational communities in a timely and verifiable manner, and interoperability with other computational tools and databases. These accessibility and usage criteria are consistent with the Kbase goals and implementation requirements.
One strategy to expand biomass production while potentially benefiting the environment is to create energy crops that grow in marginal or degraded land that is not currently useful for agriculture. Such crops can be engineered so that they not only yield biomass for biofuel production, but they may also help to reclaim degraded environments. For example, expected progress in plant engineering could lead to new crops that express their own nitrogen-fixing enzymes without the need for bacterial symbionts. Such advances in biosystem engineering that enhance nitrogen utilization or water-use efficiency in plants would enable the development of new, sustainable energy crops. In addition to making plant cell walls more amenable to sugar extraction, lignin can be engineered to create useful products, such as high-value carbon fiber. In this approach, the fuel would become a byproduct, and the enhanced value of plant-based materials would facilitate economic sustainability.
Other biodesign strategies could improve energy crops by increasing carbon fixation efficiency or transferring the beneficial properties of perennial plants to annual crops. To enhance carbon fixation and sugar formation in crops that use the C3 pathway of photosynthesis, components from the more efficient C4 pathway of some crops such as maize and sugarcane could be engineered into C3 plants. To increase the sustainability of energy crops, annual crops could be reengineered to acquire the advantages of perennial crops, which are less harmful to the environment as they do not need tillage, and use nutrients more efficiently by storing them in underground tissues after the growing season, leaving mostly the carbohydrates above ground to harvest for biofuel production.
With continued progress in structural biology, enzymology, membrane biology, and genome engineering, components of photosynthesis could be bundled into functional modules and introduced into nonphotosynthetic organisms. Successfully reconstructing and incorporating photosynthesis as a modular process into an organism would enhance our fundamental understanding of this process, define the minimum set of components needed to carry out photosynthesis, and reveal new combinations of components that can maximize photosynthetic efficiency.
Understanding stress in microbes is another critical issue. Almost every fermentation process is currently limited by the tolerance of the microbe to the final product. One way to overcome this problem is to modify cell membrane composition by introducing genes to synthesize new membrane lipids. For example, the lipids that make up Archaea membranes are very different from those of bacteria. Thus, moving the pathways for lipid biosynthesis from Archaea to other microbes could create engineered organisms that are more alcohol-tolerant and thus more resilient to the stress of biofuel production.
Harnessing the wealth of information obtained from metagenomic sequencing of microbial communities in diverse environments is limited by the inability to culture and study many of the identified organisms in the laboratory. Advances in computer modeling are helping researchers study the metabolism of novel organisms in silico and identify nutrients, cofactors, and physicochemical conditions needed to grow and characterize these microbes in vitro.