Abstract

INTRODUCTION Functional Genomics and the mapping program of the human genome (HUGO) will revolutionize the future of Life Sciences. One of the key issues will be to link gene sequences to protein expression. Proteomics is fueling the fast development of functional protein analysis and aims at analyzing biologically relevant biopolymers at defined states. High capacity throughput technologies that are able to identify the expression of proteins are currently a research area with enormous attention. This is due to the fact that the DNA-coding and “the Holy Grail” of human life is no further away than the nearest computer with an internet connection. Almost the entire genome can be searched. However, these gene sequences hold only a limited percentage of the entire proteome that is present in cells. The reason is that upon transcription and translation, proteins in many cases undergo a post translational modifying step. This is often associated with an enzymatic transformation whereby the protein is modified. These modifications, e.g., phosphorylation, methylation, and glycosylation, are often linked to biological activity. It is assumed that close to one million structurally different proteins are present in human cells. Currently there is no single technology that is able to map even close to the majority of all these proteins. Two-dimensional gelelectrophoresis in combination with mass spectrometry (MS) is the method of choice to study the expression of proteins. The combination of these techniques has been the propelling force of proteomics that allows the separation of several thousands of proteins and identification of their corresponding peptide maps by high-resolution MS. The need for ever decreasing sample volumes and concentrations has been the driving force in the emerging field of microfluidics and chemical microsystems. Miniaturized separation techniques such as microcolumn liquid chromatography and capillary electrophoresis has entered into the field of Proteomics 3 offering high separation efficiency with subsequent peptide mass fingerprint identities. In this paper we describe a chip technology based workstation interfacing capillary liquid chromatography to MALDI-TOF mass spectrometry which can be operated in an unattended and fully automated mode.

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