High throughput biology

High throughput cell biology is the use of automation equipment with classical cell biology techniques to address biological questions that are otherwise unattainable using conventional methods. It may incorporate techniques from optics, chemistry, biology or image analysis to permit rapid, highly parallel research into how cells function, interact with each other and how pathogens exploit them in disease.

High-throughput biology serves as one facet of what has also been called "omics research" - the interface between large scale biology (genome, proteome, transcriptome), technology and researchers. High throughput cell biology has a definite focus on the cell, and methods accessing the cell such as imaging, gene expression microarrays, or genome wide screening. The basic idea is to take methods normally performed on their own and do a very large number of them without impacting their quality.

High throughput research can be defined as the automation of experiments such that large scale repetition becomes feasible. This is important because many of the questions faced by life science researchers now involve large numbers. For example, the Human Genome contains at least 21,000 genes,^[1] all of which can potentially contribute to cell function, or disease. To be able to capture an idea of how these genes interact with one another, which genes are involved in and where they are, methods that encompass from the cell to the genome are of interest.

Use of robotics

Classical High throughput screening robotics are now being tied closer to cell biology, principally using technologies such as High-content screening. High throughput cell biology dictates methods that can take routine cell biology from low scale research to the speed and scale necessary to investigate complex systems, achieve high sample size, or efficiently screen through a collection.

It has a greater emphasis on function rather than discovery, and will have its most significant impact in exploring biology as we progress toward models of the cell as a system rather than isolated pathways.^[2]

Use of microscopy and cytometry

High-content screening technology is mainly based on automated digital microscopy and flow cytometry, in combination with IT-systems for the analysis and storage of the data. "High-content" or visual biology technology has two purposes, first to acquire spatially or temporally resolved information on an event and second to automatically quantify it. Spatially resolved instruments are typically automated microscopes, and temporal resolution still requires some form of fluorescence measurement in most cases.This means that a lot of HCS instruments are (fluorescence) microscopes that are connected to some form of image analysis package. These take care of all the steps in taking fluorescent images of cells and provide rapid, automated and unbiased assessment of experiments.

Development of technology

The technology can be defined as being at the same development point as the first automated DNA sequencers in the early 1990s. Automated DNA sequencing was a disruptive technology when it became practical and -even if early devices had shortcomings- it enabled genome scale sequencing projects and created the field of bioinformatics. The impact of a similarly disruptive and powerful technology on molecular cell biology and translational research is hard to predict but what is clear is that it will cause a profound change in the way cell biologists research and medicines are discovered.

See also

• Drug discovery
• High-throughput screening
• Drug discovery hit to lead
• High-content screening

References

1. "How Many Genes Are There?". Human Genome Project Information. U.S. Department of Energy Office of Science. 2008-09-19.
2. Ritter, R. (2002). The Oxford Style Manual. Oxford University Press. ISBN 0-19-860564-1

Further reading

• Abraham VC, Taylor DL, Haskins JR (January 2004). "High content screening applied to large-scale cell biology". Trends Biotechnol. 22 (1): 15–22. doi:10.1016/j.tibtech.2003.10.012. PMID 14690618.
• Bleicher KH, Böhm HJ, Müller K, Alanine AI (May 2003). "Hit and lead generation: beyond high-throughput screening". Nat Rev Drug Discov. 2 (5): 369–78. doi:10.1038/nrd1086. PMID 12750740.
• Burdine L, Kodadek T (May 2004). "Target identification in chemical genetics: the (often) missing link". Chem. Biol. 11 (5): 593–7. doi:10.1016/j.chembiol.2004.05.001. PMID 15157870.
• Carpenter AE, Sabatini DM (January 2004). "Systematic genome-wide screens of gene function". Nat. Rev. Genet. 5 (1): 11–22. doi:10.1038/nrg1248. PMID 14708012.
• Edwards BS, Oprea T, Prossnitz ER, Sklar LA (August 2004). "Flow cytometry for high-throughput, high-content screening". Curr Opin Chem Biol. 8 (4): 392–8. doi:10.1016/j.cbpa.2004.06.007. PMID 15288249.
• Eggert US, Mitchison TJ (June 2006). "Small molecule screening by imaging". Curr Opin Chem Biol. 10 (3): 232–7. doi:10.1016/j.cbpa.2006.04.010. PMID 16682248.
• Giuliano KA, Haskins JR, Taylor DL (August 2003). "Advances in high content screening for drug discovery". Assay Drug Dev Technol. 1 (4): 565–77. doi:10.1089/154065803322302826. PMID 15090253.
• Milligan G (July 2003). "High-content assays for ligand regulation of G-protein-coupled receptors". Drug Discov. Today. 8 (13): 579–85. doi:10.1016/S1359-6446(03)02738-7. PMID 12850333.

External links

• Yale Center for High Throughput Cell Biology
• The Advanced Cell Classifier project (ETH Zurich)