Synthetic Biology: Engineering Life To Examine It

Synthetic biology is an area of science devoted to engineering novel biological circuits, devices, systems, genomes or even whole organisms. This rather broad description of what "synthetic biology" encompasses reflects the multidisciplinary nature of this field which integrates ideas derived from biology, engineering, chemistry and mathematical modeling as well as a vast arsenal of experimental tools developed in each of these disciplines. Specific examples of "synthetic biology" include the engineering of microbial organisms that are able to mass produce fuels or other valuable raw materials, synthesizing large chunks of DNA to replace whole chromosomes or even the complete genome in certain cells, assembling synthetic cells or introducing groups of genes into cells so that these genes can form functional circuits by interacting with each other. Synthesis in the context of synthetic biology can signify the engineering of artificial genes or biological systems that do not exist in nature (i.e. synthetic = artificial or unnatural), but synthesis can also stand for integration and composition, a meaning which is closer to the Greek origin of the word. It is this latter aspect of synthetic biology which makes it an attractive area for basic scientists who are trying to understand the complexity of biological organisms. Instead of the traditional molecular biology focus on studying just one single gene and its function, synthetic biology is engineering biological composites that consist of multiple genes and regulatory elements of each gene. This enables scientists to interrogate the interactions of these genes, their regulatory elements and the proteins encoded by the genes with each other. Synthesis serves as a path to analysis.

One goal of synthetic biologists is to create complex circuits in cells to facilitate biocomputing, building biological computers that are as powerful or even more powerful that traditional computers. While such gene circuits and cells that have been engineered have some degree of memory and computing power, they are no match for the comparatively gigantic computing power of even small digital computers. Nevertheless, we have to keep in mind that the field is very young and advances are progressing at a rapid pace.

One of the major recent advances in synthetic biology occurred in 2013 when an MIT research team led by Rahul Sarpeshkar and Timothy Lu at MIT created analog computing circuits in cells. Most synthetic biology groups that engineer gene circuits in cells to create biological computers have taken their cues from contemporary computer technology. Nearly all of the computers we use are digital computers, which process data using discrete values such as 0's and 1's. Analog data processing on the other hand uses a continuous range of values instead of 0's and 1's. Digital computers have supplanted analog computing in nearly all areas of life because they are easy to program, highly efficient and process analog signals by converting them into digital data. Nature, on the other hand, processes data and information using both analog and digital approaches. Some biological states are indeed discrete, such as heart cells which are electrically depolarized and then repolarized in periodical intervals in order to keep the heart beating. Such discrete states of cells (polarized / depolarized) can be modeled using the ON and OFF states in the biological circuit described earlier. However, many biological processes, such as inflammation, occur on a continuous scale. Cells do not just exist in uninflamed and inflamed states; instead there is a continuum of inflammation from minimal inflammatory activation of cells to massive inflammation. Environmental signals that are critical for cell behavior such as temperature, tension or shear stress occur on a continuous scale and there is little evidence to indicate that cells convert these analog signals into digital data.

Most of the attempts to create synthetic gene circuits and study information processing in cells have been based on a digital computing paradigm. Sarpeshkar and Lu instead wondered whether one could construct analog computation circuits and take advantage of the analog information processing systems that may be intrinsic to cells.

by Jalees Rehman, 3Quarks Daily | Read more:

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