Analysis of High Throughput Protein Expression in Escherichia coli

Abstract

The ability to efficiently produce hundreds of proteins in parallel is the most basic requirement of many aspects of proteomics. Overcoming the technical and financial barriers associated with high throughput protein production is essential for the development of an experimental platform to query and browse the protein content of a cell (e.g. protein and antibody arrays). Proteins are inherently different one from another in their physicochemical properties; therefore, no single protocol can be expected to successfully express most of the proteins. Instead of optimizing a protocol to express a specific protein, we used sequence analysis tools to estimate the probability of a specific protein to be expressed successfully using a given protocol, thereby avoiding a priori proteins with a low success probability. A set of 547 proteins, to be used for antibody production and selection, was expressed in Escherichia coli using a high throughput protein production pipeline. Protein properties derived from sequence alone were correlated to successful expression, and general guidelines are given to increase the efficiency of similar pipelines. A second set of 68 proteins was expressed to investigate the link between successful protein expression and inclusion body formation. More proteins were expressed in inclusion bodies; however, the formation of inclusion bodies was not a requirement for successful expression. The ability to efficiently produce hundreds of proteins in parallel is the most basic requirement of many aspects of proteomics. Overcoming the technical and financial barriers associated with high throughput protein production is essential for the development of an experimental platform to query and browse the protein content of a cell (e.g. protein and antibody arrays). Proteins are inherently different one from another in their physicochemical properties; therefore, no single protocol can be expected to successfully express most of the proteins. Instead of optimizing a protocol to express a specific protein, we used sequence analysis tools to estimate the probability of a specific protein to be expressed successfully using a given protocol, thereby avoiding a priori proteins with a low success probability. A set of 547 proteins, to be used for antibody production and selection, was expressed in Escherichia coli using a high throughput protein production pipeline. Protein properties derived from sequence alone were correlated to successful expression, and general guidelines are given to increase the efficiency of similar pipelines. A second set of 68 proteins was expressed to investigate the link between successful protein expression and inclusion body formation. More proteins were expressed in inclusion bodies; however, the formation of inclusion bodies was not a requirement for successful expression. The completion of the human genome project and the biotechnical advances in the field of genomics have radically transformed biological and medical research. We now have the ability to monitor the mRNA expression of thousands of genes simultaneously in cells and tissues. However, it is the proteins encoded by these genes that carry out most biological functions. The proteome is much more daunting in size and complexity than the genome, and to understand how cells work we must study which proteins are present, how they interact with each other, and what they do. The difficulty of studying proteins is that they are each distinctively different from the other and are usually present in tissue in very low amounts. In the absence of a PCR equivalent, it has been suggested to call upon affinity ligands, such as monoclonal antibodies, for detection and identification of proteins (1Humphery-Smith I. A human proteome project with a beginning and an end.Proteomics. 2004; 4: 2519-2521Crossref PubMed Scopus (38) Google Scholar). Regardless of the specific affinity ligand used, purified proteins must first be acquired in large quantities f