Analytical biotechnology describes the application of biotechnological tools for the creation of chemical measurement systems. Examples include the creation of sensors from DNA-binding proteins for the detection of trace amounts of arsenic and lead in ground waters, and the development of nanoscale DNA cascade switches that can be used to identify single molecular events. Significant challenges for analytical biotechnology arise in proteomics, glycomics, and lipidomics.
Materials biotechnology entails the use of biotechnological methods for the fabrication of novel materials with unique optical, electronic, rheological, and selective transport properties. Examples include novel polymers created from genetically engineered polypeptide sequences and the formation of nanowires and circuits from metal nanoparticles attached to a DNA backbone.
Computational biotechnology focuses on the potential replacement of silicon devices with nanoscale biomolecular-based computational systems. Examples include the creation of DNA switches from hairpin structures and the programmable self-assembly of DNA tiles for the creation of memory circuits.
A common feature of many of the three new biotechnology application areas is that they all require the production of well-characterized, functional biopolymer nanostructures. The molecular precision and specificity of the enzymatic biochemical pathways employed in biotechnology can often surpass what can be accomplished by other chemical or physical methods—a point that is especially relevant to the problem of nanoscale self-assembly. It is this fine control of nanoscale architecture exhibited in proteins, membranes, and nucleic acids that researchers hope to harness with these applied biotechnologies.
An important enabler of the production of such nanostructures, especially on a large scale, is the availability of increasingly standardized and increasingly automatable fabrication techniques. In some ways, the status of fabrication technologies for these nanostructures is similar to the status of integrated circuit fabrication technology several decades ago, which evolved from a laboratory activity with trial-and-error doping of individual devices to a large-scale automated enterprise driven by design automation software over a period of 20 years beginning in the early 1960s.
Although they draw on biology and computing (along with other disciplines), the tools of these parent disciplines are being applied by researchers in these new biotechnological areas to a different and unrelated set of scientific interests and goals, and these areas often attract scientists with no interests in or ties to traditional biology or computing research. Indeed, these researchers are likely to find intellectual homes in areas such as neuroscience, robotics, and space exploration.
These new areas also have obvious relevance to computing. For example, computational biotechnology is relevant to computing in the same way that lithographic silicon fabrication technologies are today—underpinning these latter technologies are understandings of fundamental physics and well-developed electrical engineering techniques and approaches. Similarly, computational biotechnology will draw on materials science and biochemistry as well as biology as it seeks to create highly regular DNA nanoparticles, mate DNA with submicron electronic structures fabricated in silicon, and create networks of interconnecting nanostructures with unique enzyme communication paths. Analytical and materials biotechnologies are also relevant for enabling MEMS—microelectromechanical systems that interact with the physical world (taking in data through various sensors and affecting the world through various actuators).
The committee believes that the most important barriers today impeding the broader integration of computing and information technology into life sciences research are cultural barriers. Twenty-first century biology will not entail a diminution of the central role that traditional empirical or experimental research plays, but it will call for the whole-hearted embrace of a style of biology that integrates reductionist biology with systems biology research. At the same time, computing and physical science