Genomes to Life Contractor-Grantee Workshop III
February 6-9, 2005, Washington, D.C.
Technology Development and Use
Protein Production and Molecular Tags
106 Development of Genome-Scale Expression Methods
Sarah Fey, Elizabeth Landorf, Yuri Londer, Terese Peppler, andFrank Collart* (fcollart@anl.gov)
Argonne National Laboratory, Argonne, IL
Protein diversity suggests multiple expression strategies will be required to insure production of the highest possible proportion of cellular proteins. We are developing novel cellular and cell-free technologies to optimize the expression of cytoplasmic, periplasmic/secreted proteins and protein domains. These molecular tools contain elements that enable localization to appropriate cellular or extracellular compartments coupled with regulatory elements to permit control and coordination of protein expression. They also incorporate specific fusion components that promote protein stability and solubility or that facilitate detection, purification and/or protein characterization. Specific focus areas for in vivo expression in E. coli are as follows:
- Evaluation of various fusion tag cassettes to maximize the generation of soluble proteins or protein domains for downstream analysis.
- Development of a periplasmic expression system compatible with current standard high throughput cytoplasmic cloning strategies. This process has been implemented in a 96-well plate format and is being used for analysis of expression and solubility for Shewanella and Geobacter proteins directed to the cytoplasm or periplasm.
- Evaluation of a domain-based cloning and expression strategy for simple architecture membrane proteins. Proteins were analyzed for periplasmic signal sequences by sequence analysis using the signalP algorithm (1, 2) or for transmembrane regions by application of the TMHMM program (3). This approach is being applied to a set of two-component sensor and methyl accepting chemotaxis proteins from Shewanella and Geobacter.
- Generation of several constructs intended to facilitate cloning and expression of genes coding for c-type cytochromes. These constructs and host strains are being evaluated for implementation in a high throughput environment.
Our studies indicate a large fraction of proteins of highest interest are difficult to express using standard expression systems. Our novel expression methods extend the boundaries of current high throughput technology and provide strategies for expression of challenging proteins that can be implemented by the general scientific community. We are attempting to optimize distribution of purified proteins or clones that express soluble protein for characterization in detail and elucidation of biological function.
References
- Nielsen, H., and Krogh, A. (1998) Prediction of signal peptides and signal anchors by a hidden Markov model. Proc Int Conf Intell Syst Mol Biol 6, 122-30.
- Nielsen, H., Brunak, S., and von Heijne, G. (1999) Machine learning approaches for the prediction of signal peptides and other protein sorting signals. Protein Eng 12, 3-9.
- Sonnhammer, E. L., von Heijne, G., and Krogh, A. (1998) A hidden Markov model for predicting transmembrane helices in protein sequences. Proc Int Conf Intell Syst Mol Biol 6, 175-82.
* Presenting author
