A high-throughput protein refolding screen in 96-well format combined with design of experiments to optimize the refolding conditions.

Production of correctly folded and biologically active proteins in Escherichiacoli can be a challenging process. Frequently, proteins are recovered as insoluble inclusion bodies and need to be denatured and refolded into the correct structure. To address this, a refolding screening process based on a 96-well assay format supported by design of experiments (DOE) was developed for identification of optimal refolding conditions. After a first generic screen of 96 different refolding conditions the parameters that produced the best yield were further explored in a focused DOE-based screen. The refolding efficiency and the quality of the refolded protein were analyzed by RP-HPLC and SDS-PAGE. The results were analyzed by the DOE software to identify the optimal concentrations of the critical additives. The optimal refolding conditions suggested by DOE were verified in medium-scale refolding tests, which confirmed the reliability of the predictions. Finally, the refolded protein was purified and its biological activity was tested in vitro. The screen was applied for the refolding of Interleukin 17F (IL-17F), stromal-cell-derived factor-1 (SDF-1α/CXCL12), B cell-attracting chemokine 1 (BCA-1/CXCL13), granulocyte macrophage colony stimulating factor (GM-CSF) and the complement factor C5a. This procedure identified refolding conditions for all the tested proteins. For the proteins where refolding conditions were already available, the optimized conditions identified in the screening process increased the yields between 50% and 100%. Thus, the method described herein is a useful tool to determine the feasibility of refolding and to identify high-yield scalable refolding conditions optimized for each individual protein.

In vitro and in silico processes to identify differentially expressed proteins.

We present an integrated proteomics platform designed for performing differential analyses. Since reproducible results are essential for comparative studies, we explain how we improved reproducibility at every step of our laboratory processes, e.g. by taking advantage of the powerful laboratory information management system we developed. The differential capacity of our platform is validated by detecting known markers in a real sample and by a spiking experiment. We introduce an innovative two-dimensional (2-D) plot for displaying identification results combined with chromatographic data. This 2-D plot is very convenient for detecting differential proteins. We also adapt standard multivariate statistical techniques to show that peptide identification scores can be used for reliable and sensitive differential studies. The interest of the protein separation approach we generally apply is justified by numerous statistics, complemented by a comparison with a simple shotgun analysis performed on a small volume sample. By introducing an automatic integration step after mass spectrometry data identification, we are able to search numerous databases systematically, including the human genome and expressed sequence tags. Finally, we explain how rigorous data processing can be combined with the work of human experts to set high quality standards, and hence obtain reliable (false positive < 0.35%) and nonredundant protein identifications.