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In this chapter, we concentrate on the production of high-quality protein samples for nuclear magnetic resonance (NMR) studies. In particular, we provide an in-depth description of recent advances in the production of NMR samples and their synergistic use with recent advancements in NMR hardware. We describe the protein production platform of the Northeast Structural Genomics Consortium and outline our high-throughput strategies for producing high-quality protein samples for NMR studies. Our strategy is based on the cloning, expression, and purification of 6×-His-tagged proteins using T7-based Escherichia coli systems and isotope enrichment in minimal media. We describe 96-well ligation-independent cloning and analytical expression systems, parallel preparative scale fermentation, and high-throughput purification protocols. The 6×-His affinity tag allows for a similar two-step purification procedure implemented in a parallel high-throughput fashion that routinely results in purity levels sufficient for NMR studies (>97% homogeneity). Using this platform, the protein open reading frames of over 17,500 different targeted proteins (or domains) have been cloned as over 28,000 constructs. Nearly 5000 of these proteins have been purified to homogeneity in tens of milligram quantities (see Summary Statistics, http://nesg.org/statistics.html), resulting in more than 950 new protein structures, including more than 400 NMR structures, deposited in the Protein Data Bank. The Northeast Structural Genomics Consortium pipeline has been effective in producing protein samples of both prokaryotic and eukaryotic origin. Although this chapter describes our entire pipeline for producing isotope-enriched protein samples, it focuses on the major updates introduced during the last 5 years (Phase 2 of the National Institute of General Medical Sciences Protein Structure Initiative). Our advanced automated and/or parallel cloning, expression, purification, and biophysical screening technologies are suitable for implementation in a large individual laboratory or by a small group of collaborating investigators for structural biology, functional proteomics, ligand screening, and structural genomics research.

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RESUMEN

The biochemical and physical factors controlling protein expression level and solubility in vivo remain incompletely characterized. To gain insight into the primary sequence features influencing these outcomes, we performed statistical analyses of results from the high-throughput protein-production pipeline of the Northeast Structural Genomics Consortium. Proteins expressed in E. coli and consistently purified were scored independently for expression and solubility levels. These parameters nonetheless show a very strong positive correlation. We used logistic regressions to determine whether they are systematically influenced by fractional amino acid composition or several bulk sequence parameters including hydrophobicity, sidechain entropy, electrostatic charge, and predicted backbone disorder. Decreasing hydrophobicity correlates with higher expression and solubility levels, but this correlation apparently derives solely from the beneficial effect of three charged amino acids, at least for bacterial proteins. In fact, the three most hydrophobic residues showed very different correlations with solubility level. Leu showed the strongest negative correlation among amino acids, while Ile showed a slightly positive correlation in most data segments. Several other amino acids also had unexpected effects. Notably, Arg correlated with decreased expression and, most surprisingly, solubility of bacterial proteins, an effect only partially attributable to rare codons. However, rare codons did significantly reduce expression despite use of a codon-enhanced strain. Additional analyses suggest that positively but not negatively charged amino acids may reduce translation efficiency in E. coli irrespective of codon usage. While some observed effects may reflect indirect evolutionary correlations, others may reflect basic physicochemical phenomena. We used these results to construct and validate predictors of expression and solubility levels and overall protein usability, and we propose new strategies to be explored for engineering improved protein expression and solubility.

RESUMEN

Crystallization is the most serious bottleneck in high-throughput protein-structure determination by diffraction methods. We have used data mining of the large-scale experimental results of the Northeast Structural Genomics Consortium and experimental folding studies to characterize the biophysical properties that control protein crystallization. This analysis leads to the conclusion that crystallization propensity depends primarily on the prevalence of well-ordered surface epitopes capable of mediating interprotein interactions and is not strongly influenced by overall thermodynamic stability. We identify specific sequence features that correlate with crystallization propensity and that can be used to estimate the crystallization probability of a given construct. Analyses of entire predicted proteomes demonstrate substantial differences in the amino acid-sequence properties of human versus eubacterial proteins, which likely reflect differences in biophysical properties, including crystallization propensity. Our thermodynamic measurements do not generally support previous claims regarding correlations between sequence properties and protein stability.

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