Circuits and Systems for High-Throughput Biology
The beginning of this millennium has been marked by some remarkable scientific events, notably the completion of the first objective of the Human Genome Project [HGP], i.e., the decoding of the 3 billion bases that compose the human genome. This success has been made possible by the advancement of bio-engineering, data processing and the collaboration of scientists from academic institutions and private companies in many countries. The availability of biological information through web-accessible open databases has stirred further research and enthusiasm. More interestingly, this has changed the way in which molecular biology is approached today, since the newly available large amount of data require the tight interaction between information technology and life science, in a way not appreciated before. Still much has to be accomplished, to realize the potential impact of using the knowledge that we have acquired. Several grand challenges are still open, such as diagnosing and treatment of a number of diseases, understanding details of the complex mechanisms that regulate life, predicting and controlling the evolution of several biological processes. Nevertheless, there is now unprecendent room to reach these objectives, because the underlying technologies that we master have been exploited only to a limited extent. High-throughput biological data acquisition and processing technologies have shifted the focus of biological research from the realm of traditional experimental science (wet biology) to that of information science (in silico biology). Powerful computation and communication means can be applied to the very large amount of apparently incoherent data coming from biomedical research. The technical challenges that lie ahead include the interfacing between the information in biological samples and information and its abstraction in terms of mathematical models and binary data that computer engineers are used to handle. For example, how can we automate costly, repetitive and time consuming processes for the analysis of data that must cover the information contained in a whole organism genome? How can we design a drug that triggers a specific answer? Anyone wearing the hat of a Circuit and System engineer would immediately realize that one important issue is the interfacing of the biological to the electrical world, which is often realized by microscopic probes, able to capture and manipulate bio-materials at the molecular level. A portion of the costly and time consuming experiments and tests that we used to do in vitro and/or in vivo, can now be done in silico. The concept of Laboratory (Lab) on Chip (LoC) is the natural evolution of System on Chip (SoC) by using an array of heterogeneous technologies. Whether LoCs will be realized on a monolithic chip or as a combination of modules is just a technicality. The revolution brought by Labs on Chips is related to the rationalization of bio-analysis, the drastic reduction of sample quantities, and its portability to various environments. We have witnessed the widespread distribution of complex electronic systems due to their low manufacturing costs. Also in this case, LoC costs will be key to their acceptance. But it is easy to foresee that LoCs may be mass produced, with post-silicon manufacturing technologies, where large production volumes correlate to competitive costs. At the same time, the reduction of size, weight and human intervention will limit operating costs and make LoCs competitive. Labs on Chips at medical points of care will fulfill the desire of fast and more accurate diagnosis. Moreover diagnosis at home and/or at mass transit facilities (e.g., airports) can have a significant impact on the overall population health. LoCs for processing environmental data (e.g., pollution) may be coupled with wireless sensor networks to better monitor the planet. The use of the information produced by the Human Genome Project (marking the beginning of the Genomic Era) and its further refinement and understanding (post-Genomic Era), as well as the consequences related to moral and legal implication for the betterment of society has just started. In fact, the decoding of the Human Genome paved the way to a different approach to molecular biology, in that it is now possible to observe the interrelations among whole bodies of molecules such as genes, proteins, transcripts, metabolites in parallel (the so called omic data like genomes, proteomes, transcriptomes, metabolomes etc.), rather than observe and characterize a single chain of a cascade of events (i.e. perform genomic vs genetic analyses). In other words, molecular biology underwent an important shift in the paradigm of research, from a reductionist to a more systemic approach (systems biology) for which models developed in engineering will be of primary importance.
Record created on 2006-09-06, modified on 2016-08-08