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Protein engineering for metabolic engineering: current and next-generation tools.

ABSTRACT: Protein engineering in the context of metabolic engineering is increasingly important to the field of industrial biotechnology. As the demand for biologically produced food, fuels, chemicals, food additives, and pharmaceuticals continues to grow, the ability to design and modify proteins to accomplish new functions will be required to meet the high productivity demands for the metabolism of engineered organisms. We review advances in selecting, modeling, and engineering proteins to improve or alter their activity. Some of the methods have only recently been developed for general use and are just beginning to find greater application in the metabolic engineering community. We also discuss methods of generating random and targeted diversity in proteins to generate mutant libraries for analysis. Recent uses of these techniques to alter cofactor use; produce non-natural amino acids, alcohols, and carboxylic acids; and alter organism phenotypes are presented and discussed as examples of the successful engineering of proteins for metabolic engineering purposes.

SUBMITTER: Marcheschi RJ

PROVIDER: S-EPMC4134947 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Protein engineering for metabolic engineering: current and next-generation tools.

Marcheschi Ryan J RJ Gronenberg Luisa S LS Liao James C JC

Biotechnology journal 20130416 5

Protein engineering in the context of metabolic engineering is increasingly important to the field of industrial biotechnology. As the demand for biologically produced food, fuels, chemicals, food additives, and pharmaceuticals continues to grow, the ability to design and modify proteins to accomplish new functions will be required to meet the high productivity demands for the metabolism of engineered organisms. We review advances in selecting, modeling, and engineering proteins to improve or al ...[more]

PMID: 23589443

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Project description:MotivationOver the last decades, vast numbers of sequences were deposited in public databases. Bioinformatics tools allow homology and consequently functional inference for these sequences. New profile-based homology search tools have been introduced, allowing reliable detection of remote homologs, but have not been systematically benchmarked. To provide such a comparison, which can guide bioinformatics workflows, we extend and apply our previously developed benchmark approach to evaluate the 'next generation' of profile-based approaches, including CS-BLAST, HHSEARCH and PHMMER, in comparison with the non-profile based search tools NCBI-BLAST, USEARCH, UBLAST and FASTA.MethodWe generated challenging benchmark datasets based on protein domain architectures within either the PFAM + Clan, SCOP/Superfamily or CATH/Gene3D domain definition schemes. From each dataset, homologous and non-homologous protein pairs were aligned using each tool, and standard performance metrics calculated. We further measured congruence of domain architecture assignments in the three domain databases.ResultsCSBLAST and PHMMER had overall highest accuracy. FASTA, UBLAST and USEARCH showed large trade-offs of accuracy for speed optimization.ConclusionProfile methods are superior at inferring remote homologs but the difference in accuracy between methods is relatively small. PHMMER and CSBLAST stand out with the highest accuracy, yet still at a reasonable computational cost. Additionally, we show that less than 0.1% of Swiss-Prot protein pairs considered homologous by one database are considered non-homologous by another, implying that these classifications represent equivalent underlying biological phenomena, differing mostly in coverage and granularity.Availability and implementationBenchmark datasets and all scripts are placed at (http://sonnhammer.org/download/Homology_benchmark).Contactforslund@embl.deSupplementary informationSupplementary data are available at Bioinformatics online.

Project description:BackgroundThe isopentenols, including isoprenol and prenol, are excellent alternative fuels. However, they are not compounds largely accumulated in natural organism. The need for the next generation of biofuels with better physical and chemical properties impels us to develop biosynthetic routes for the production of isoprenol and prenol from renewable sugar. In this study, we use the heterogenous mevalonate-dependent (MVA) isoprenoid pathway for the synthesis of isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP) intermediates, and then convert IPP and DMAPP to isoprenol and prenol, respectively.ResultsA mevalonate titer of 1.7 g/L was obtained by constructing an efficient MVA upper pathway in engineered E. coli. Different phosphatases and pyrophosphatases were investigated for their abilities in hydrolyzing the IPP and DMAPP. Consequently, ADP-ribose pyrophosphatase was found to be an efficient IPP and DMAPP hydrolase. Moreover, ADP-ribose pyrophosphatase from Bacillus subtilis (BsNudF) exhibited a equivalent substrate specificity towards IPP and DMAPP, while ADP-ribose pyrophosphatase from E. coli (EcNudF) presented a high substrate preference for DMAPP. Without the expression of any phosphatases or pyrophosphatases, a background level of isopentenols was synthesized. When the endogenous pyrophosphatase genes (EcNudF and yggV) that were capable of enhancing the hydrolyzation of the IPP and DMAPP were knocked out, the background level of isopentenols was still obtained. Maybe the synthesized IPP and DMAPP were hydrolyzed by some unknown hydrolases of E. coli. Finally, 1.3 g/L single isoprenol was obtained by blocking the conversion of IPP to DMAPP and employing the BsNudF, and 0.2 g/L ~80% prenol was produced by employing the EcNudF. A maximal yield of 12% was achieved in both isoprenol and prenol producing strains.ConclusionsTo the best of our knowledge, this is the first successful report on high-specificity production of isoprenol and prenol by microbial fermentation. Over 1.3 g/L isoprenol achieved in shake-flask experiments represents a quite encouraging titer of higher alcohols. In addition, the substrate specificities of ADP-ribose pyrophosphatases were determined and successfully applied for the high-specificity synthesis of isoprenol and prenol. Altogether, this work presents a promising strategy for high-specificity production of two excellent biofuels, isoprenol and prenol.

Dataset Information

Protein engineering for metabolic engineering: current and next-generation tools.

Publications

Protein engineering for metabolic engineering: current and next-generation tools.

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