Ionic liquids (ILs) are attractive (co-)solvents for biocatalysis. However, in high concentration (>10 % IL), enzymes usually show decreased activity. No general principles have been discovered to improve IL resistance of enzymes by protein engineering. We present a systematic study to elucidate general engineering principles by site saturation mutagenesis on the complete gene bsla. Screening in presence of four [BMIM]-based ILs revealed two unexpected lessons on directed evolution: 1) resistance improvement was obtainable at 50-69 % of all amino acid positions, thus explaining the success of small sized random mutant libraries; 2) 6-13 % of substitutions led to improved resistance. Among these, 66-95 % were substitutions by chemically different amino acids (e.g., aromatic to polar/aliphatic/charged amino acids), thus indicating that mutagenesis methods introducing such changes should, at least for lipases like BSLA, be favored to improve IL resistance.

BackgroundEscherichia coli is commonly used in academia and industry for expressing recombinant proteins because of its well-characterized molecular genetics and the availability of numerous expression vectors and strains. One important issue during recombinant protein production is the so-called ‘metabolic burden’: the material and energy normally reserved for microbial metabolism which is sapped from the bacterium to produce the recombinant protein. This material and energy drain harms biomass formation and modifies respiration. To the best of our knowledge, no research has investigated so far whether a single amino acid exchange in a recombinant protein affects the metabolic burden phenomenon. Thus, in this study, 15 E. coli BL21(DE3) clones expressing either the fusion tags, a recombinant wild type lipase, or 13 different lipase variants are investigated to quantitatively analyze the respective effects of single amino acid exchanges at different positions on respiration, biomass and protein production of each clone. Therefore, two small-scale online monitoring systems, namely a Respiration Activity MOnitoring System (RAMOS) and a microtiter plate based cultivation system (BioLector) are applied.ResultsUpon expression of all enzyme variants, strong variations were found in the Oxygen Transfer Rate (OTR), biomass and protein (lipase) production of the respective E. coli clones. Two distinct patterns of respiration behavior were observed and, so, the clones could be classified into two groups (Type A and B). Potential factors to explain these patterns were evaluated (e.g. plasmid copy number, inclusion body formation). However, no decisive factor could yet be identified. Five distinct cultivation phases could be determined from OTR curves which give real-time information about carbon source consumption, biomass and protein production. In general, it was found that the quantity of product increased with the duration of active respiration.ConclusionsThis work demonstrates that single amino acid exchanges in a recombinant protein influence the metabolic burden during protein production. The small-scale online monitoring devices RAMOS and BioLector enable the real-time detection of even smallest differences in respiration behavior, biomass and protein production in the E. coli clones investigated. Hence, this study underscores the importance of parallel online monitoring systems to unveil the relevance of single amino acid exchanges for the recombinant protein production.Electronic supplementary materialThe online version of this article (doi:10.1186/s12934-015-0191-y) contains supplementary material, which is available to authorized users.

Protein thermostability is a crucial factor for biotechnological enzyme applications. Protein engineering studies aimed at improving thermostability have successfully applied both directed evolution and rational design. However, for rational approaches, the major challenge remains the prediction of mutation sites and optimal amino acid substitutions. Recently, we showed that such mutation sites can be identified as structural weak spots by rigidity theory-based thermal unfolding simulations of proteins. Here, we describe and validate a unique, ensemble-based, yet highly efficient strategy to predict optimal amino acid substitutions at structural weak spots for improving a protein’s thermostability. For this, we exploit the fact that in the majority of cases an increased structural rigidity of the folded state has been found as the cause for thermostability. When applied prospectively to lipase A from Bacillus subtilis, we achieved both a high success rate (25% over all experimentally tested mutations, which raises to 60% if small-to-large residue mutations and mutations in the active site are excluded) in predicting significantly thermostabilized lipase variants and a remarkably large increase in those variants’ thermostability (up to 6.6°C) based on single amino acid mutations. When considering negative controls in addition and evaluating the performance of our approach as a binary classifier, the accuracy is 63% and increases to 83% if small-to-large residue mutations and mutations in the active site are excluded. The gain in precision (predictive value for increased thermostability) over random classification is 1.6-fold (2.4-fold). Furthermore, an increase in thermostability predicted by our approach significantly points to increased experimental thermostability (p < 0.05). These results suggest that our strategy is a valuable complement to existing methods for rational protein design aimed at improving thermostability.

A systematic study was conducted with Bacillus subtilis lipase A (BSLA) to determine the effect of every single amino acid substitution on detergent tolerance. BSLA is a minimal α/β-hydrolase of 181 amino acids with a known crystal structure. It can be expressed in Escherichia coli and is biochemically well characterized. Site saturation mutagenesis resulted in a library of 3439 variants, each with a single amino acid exchange as confirmed by DNA sequencing. The library was tested against four detergents, namely SDS, CTAB, Tween 80, and sulfobetaine. Surface remodeling emerged as an effective engineering strategy to increase tolerance towards detergents. Amino acid residues that significantly affect the tolerance for each of the four detergents were identified. In summary, this systematic analysis provides an experimental dataset to help derive novel protein engineering strategies as well as to direct modeling efforts.