AmiP from hyperthermophilic Thermus parvatiensis prophage is a thermoactive and ultrathermostable peptidoglycan lytic amidase

Bacteriophages encode a wide variety of cell wall disrupting enzymes that aid the viral escape in the final stages of infection. These lytic enzymes have accumulated notable interest due to their potential as novel antibacterials for infection treatment caused by multiple-drug resistant bacteria. Here, the detailed functional and structural characterization of Thermus parvatiensis prophage peptidoglycan lytic amidase AmiP, a globular Amidase_3 type lytic enzyme adapted to high temperatures is presented. The sequence and structure comparison with homologous lytic amidases reveals the key adaptation traits that ensure the activity and stability of AmiP at high temperatures. The crystal structure determined at a resolution of 1.8 Å displays a compact α/β-fold with multiple secondary structure elements omitted or shortened compared with protein structures of similar proteins. The functional characterization of AmiP demonstrates high efficiency of catalytic activity and broad substrate specificity toward thermophilic and mesophilic bacteria strains containing Orn-type or DAP-type peptidoglycan. The here presented AmiP constitutes the most thermoactive and ultrathermostable Amidase_3 type lytic enzyme biochemically characterized with a temperature optimum at 85°C. The extraordinary high melting temperature T_m 102.6°C confirms fold stability up to approximately 100°C. Furthermore, AmiP is shown to be more active over the alkaline pH range with pH optimum at pH 8.5 and tolerates NaCl up to 300 mM with the activity optimum at 25 mM NaCl. This set of beneficial characteristics suggests that AmiP can be further exploited in biotechnology.

Going to extremes - a metagenomic journey into the dark matter of life

The Virus-X-Viral Metagenomics for Innovation Value-project was a scientific expedition to explore and exploit uncharted territory of genetic diversity in extreme natural environments such as geothermal hot springs and deep-sea ocean ecosystems. Specifically, the project was set to analyse and exploit viral metagenomes with the ultimate goal of developing new gene products with high innovation value for applications in biotechnology, pharmaceutical, medical, and the life science sectors. Viral gene pool analysis is also essential to obtain fundamental insight into ecosystem dynamics and to investigate how viruses influence the evolution of microbes and multicellular organisms. The Virus-X Consortium, established in 2016, included experts from eight European countries. The unique approach based on high throughput bioinformatics technologies combined with structural and functional studies resulted in the development of a biodiscovery pipeline of significant capacity and scale. The activities within the Virus-X consortium cover the entire range from bioprospecting and methods development in bioinformatics to protein production and characterisation, with the final goal of translating our results into new products for the bioeconomy. The significant impact the consortium made in all of these areas was possible due to the successful cooperation between expert teams that worked together to solve a complex scientific problem using state-of-the-art technologies as well as developing novel tools to explore the virosphere, widely considered as the last great frontier of life.

CorNet: Assigning function to networks of co-evolving residues by automated literature mining

CorNet is a web-based tool for the analysis of co-evolving residue positions in protein super-family sequence alignments. CorNet projects external information such as mutation data extracted from literature on interactively displayed groups of co-evolving residue positions to shed light on the functions associated with these groups and the residues in them. We used CorNet to analyse six enzyme super-families and found that groups of strongly co-evolving residues tend to consist of residues involved in a same function such as activity, specificity, co-factor binding, or enantioselectivity. This finding allows to assign a function to residues for which no data is available yet in the literature. A mutant library was designed to mutate residues observed in a group of co-evolving residues predicted to be involved in enantioselectivity, but for which no literature data is available yet. The resulting set of mutations indeed showed many instances of increased enantioselectivity.

Switch in Cofactor Specificity of a Baeyer-Villiger Monooxygenase

Baeyer-Villiger monooxygenases (BVMOs) catalyze the oxidation of ketones to esters or lactones by using molecular oxygen and a cofactor. Type I BVMOs display a strong preference for NADPH. However, for industrial purposes NADH is the preferred cofactor, as it is ten times cheaper and more stable. Thus, we created a variant of the cyclohexanone monooxygenase from Acinetobacter sp. NCIMB 9871 (CHMO_Acineto ); this used NADH 4200-fold better than NADPH. By combining structure analysis, sequence alignment, and literature data, 21 residues in proximity of the cofactor were identified and targeted for mutagenesis. Two combinatorial variants bearing three or four mutations showed higher conversions of cyclohexanone with NADH (79 %) compared to NADPH (58 %) as well as specificity. The structural reasons for this switch in cofactor specificity of a type I BVMO are especially a hydrogen-bond network coordinating the two hydroxy groups of NADH through direct interactions and bridging water molecules.

Simultaneous use of in silico design and a correlated mutation network as a tool to efficiently guide enzyme engineering

In order to improve the efficiency of directed evolution experiments, in silico multiple-substrate clustering was combined with an analysis of the variability of natural enzymes within a protein superfamily. This was applied to a Pseudomonas fluorescens esterase (PFE I) targeting the enantioselective hydrolysis of 3-phenylbutyric acid esters. Data reported in the literature for nine substrates were used for the clustering meta-analysis of the docking conformations in wild-type PFE I, and this highlighted a tryptophan residue (W28) as an interesting target. Exploration of the most frequently, naturally occurring amino acids at this position suggested that the reduced flexibility observed in the case of the W28F variant leads to enhancement of the enantioselectivity. This mutant was subsequently combined with mutations identified in a library based on analysis of a correlated mutation network. By interrogation of <80 variants a mutant with 15-fold improved enantioselectivity was found.

Bioinformatic analysis of a PLP-dependent enzyme superfamily suitable for biocatalytic applications

In this review we analyse structure/sequence-function relationships for the superfamily of PLP-dependent enzymes with special emphasis on class III transaminases. Amine transaminases are highly important for applications in biocatalysis in the synthesis of chiral amines. In addition, other enzyme activities such as racemases or decarboxylases are also discussed. The substrate scope and the ability to accept chemically different types of substrates are shown to be reflected in conserved patterns of amino acids around the active site. These findings are condensed in a sequence-function matrix, which facilitates annotation and identification of biocatalytically relevant enzymes and protein engineering thereof.

Novel tools for extraction and validation of disease-related mutations applied to Fabry disease

Genetic disorders are often caused by nonsynonymous nucleotide changes in one or more genes associated with the disease. Specific amino acid changes, however, can lead to large variability of phenotypic expression. For many genetic disorders this results in an increasing amount of publications describing phenotype-associated mutations in disorder-related genes. Keeping up with this stream of publications is essential for molecular diagnostics and translational research purposes but often impossible due to time constraints: there are simply too many articles to read. To help solve this problem, we have created Mutator, an automated method to extract mutations from full-text articles. Extracted mutations are crossreferenced to sequence data and a scoring method is applied to distinguish false-positives. To analyze stored and new mutation data for their (potential) effect we have developed Validator, a Web-based tool specifically designed for DNA diagnostics. Fabry disease, a monogenetic gene disorder of the GLA gene, was used as a test case. A structure-based sequence alignment of the alpha-amylase superfamily was used to validate results. We have compared our data with existing Fabry mutation data sets obtained from the HGMD and Swiss-Prot databases. Compared to these data sets, Mutator extracted 30% additional mutations from the literature.