Synthetic Biology: Engineering Biological Systems

On June 26, 2000, President Bill Clinton and Prime Minister Tony Blair, along with Francis Collins, director of the Human Genome Project at the NIH, and Craig Venter, president of Celera Genomics, announced the arrival of the genomic era with the sequencing of the first draft sequence of the human genome. With this wealth of information, scientists and policy-makers alike were eager to welcome in the genomic era of genetics. Doctors dreamed of personalized medicine, where genomic information can be used to diagnose individual predispositions to cancer and disease. Politicians pondered the implications of genetic profiling, where insurance companies can potentially use genetic information to screen policyholders. The genomic era is bright with promise and unprecedented potential but also rife with social implications and practical applications. While a sequenced genome provides a boon of new information and the scientific community is quick to emphasize the potential of this plethora of information, there are still many challenges in its interpretation and analysis. The interpretation of genomic data requires both high throughput techniques, such as microarray analysis, and heuristic algorithms in bioinformatics to analyze large amounts of data. Microarray analysis allows researchers to understand differential expression of many different proteins between different species, ages, and diseases states. With more than four billion base-pairs in the human genome and over thirty thousand open reading frames, the sheer size of the human genome requires the use of ad hoc analytical methods. The status quo approach in analyzing individual enzymes and molecules is complemented by a recent desire to understand entire systems, regulatory networks, and gene families. Exponentially increasing information on biological organisms and increasing computational power has broadened the perspective of current biological research. Although genomic sequences provide insight into the enzymes that make up an organism, understanding of how these parts work together to produce complex phenotypes is the focus of current research. Understanding the regulation of gene expression and multicellular development will require a deeper analysis of how transcription and stability of mRNA is regulated in response to the environmental stimuli. Despite the age old debate between nature vs. nurture, it is the interplay of the environment and gene products that determine disease states and merge to create the fascinating output of life. Greater understanding of the regulation of gene products is required in determining their effects on physiology and development. Synthetic biology seeks to understand and apply understanding of biological regulation to tackle general problems. Recombinant DNA technology laid the foundation for manipulation of biological systems on a molecular level, but recent advances in DNA sequencing and synthesis technology have greatly expanded the potential of biological engineering projects. The decreasing cost of oligonucleotide synthesis as well as improved techniques of combining oligonucleotides allows unparalleled flexibility in synthesizing long DNA sequences. From traditional methods of subcloning using restriction endonucleases and ligases to polymerase-based techniques such as gene Splicing by Overlap Extension (gene SOEing), researchers have unprecedented power in their ability to alter and characterize DNA. We can now identify new genes or regulatory sequences in diverse systems and recombine them into novel networks that attempt to recreate our understanding of existing biological systems. The rapidly expanding molecular biologist’s toolkit broadens the scope of manipulation to whole genetic systems instead of individual genes. The current state of molecular biology has improved our understanding of the networks of biomolecular interactions that give rise to complex phenotypes and allows for unprecedented control of biological systems through clear characterization and synthetic Abstract