Digenic inheritance involving a muscle-specific protein kinase and the giant titin protein causes a skeletal muscle myopathy.

In digenic inheritance, pathogenic variants in two genes must be inherited together to cause disease. Only very few examples of digenic inheritance have been described in the neuromuscular disease field. Here we show that predicted deleterious variants in SRPK3, encoding the X-linked serine/argenine protein kinase 3, lead to a progressive early onset skeletal muscle myopathy only when in combination with heterozygous variants in the TTN gene. The co-occurrence of predicted deleterious SRPK3/TTN variants was not seen among 76,702 healthy male individuals, and statistical modeling strongly supported digenic inheritance as the best-fitting model. Furthermore, double-mutant zebrafish (srpk3-/-; ttn.1+/-) replicated the myopathic phenotype and showed myofibrillar disorganization. Transcriptome data suggest that the interaction of srpk3 and ttn.1 in zebrafish occurs at a post-transcriptional level. We propose that digenic inheritance of deleterious changes impacting both the protein kinase SRPK3 and the giant muscle protein titin causes a skeletal myopathy and might serve as a model for other genetic diseases.

Beyond rational-biosensor-guided isolation of 100 independently evolved bacterial strain variants and comparative analysis of their genomes.

BACKGROUND: In contrast to modern rational metabolic engineering, classical strain development strongly relies on random mutagenesis and screening for the desired production phenotype. Nowadays, with the availability of biosensor-based FACS screening strategies, these random approaches are coming back into fashion. In this study, we employ this technology in combination with comparative genome analyses to identify novel mutations contributing to product formation in the genome of a Corynebacterium glutamicum L-histidine producer. Since all known genetic targets contributing to L-histidine production have been already rationally engineered in this strain, identification of novel beneficial mutations can be regarded as challenging, as they might not be intuitively linkable to L-histidine biosynthesis. RESULTS: In order to identify 100 improved strain variants that had each arisen independently, we performed > 600 chemical mutagenesis experiments, > 200 biosensor-based FACS screenings, isolated > 50,000 variants with increased fluorescence, and characterized > 4500 variants with regard to biomass formation and L-histidine production. Based on comparative genome analyses of these 100 variants accumulating 10-80% more L-histidine, we discovered several beneficial mutations. Combination of selected genetic modifications allowed for the construction of a strain variant characterized by a doubled L-histidine titer (29 mM) and product yield (0.13 C-mol C-mol-1) in comparison to the starting variant. CONCLUSIONS: This study may serve as a blueprint for the identification of novel beneficial mutations in microbial producers in a more systematic manner. This way, also previously unexplored genes or genes with previously unknown contribution to the respective production phenotype can be identified. We believe that this technology has a great potential to push industrial production strains towards maximum performance.

Understanding structure-guided variant effect predictions using 3D convolutional neural networks.

Predicting pathogenicity of missense variants in molecular diagnostics remains a challenge despite the available wealth of data, such as evolutionary information, and the wealth of tools to integrate that data. We describe DeepRank-Mut, a configurable framework designed to extract and learn from physicochemically relevant features of amino acids surrounding missense variants in 3D space. For each variant, various atomic and residue-level features are extracted from its structural environment, including sequence conservation scores of the surrounding amino acids, and stored in multi-channel 3D voxel grids which are then used to train a 3D convolutional neural network (3D-CNN). The resultant model gives a probabilistic estimate of whether a given input variant is disease-causing or benign. We find that the performance of our 3D-CNN model, on independent test datasets, is comparable to other widely used resources which also combine sequence and structural features. Based on the 10-fold cross-validation experiments, we achieve an average accuracy of 0.77 on the independent test datasets. We discuss the contribution of the variant neighborhood in the model's predictive power, in addition to the impact of individual features on the model's performance. Two key features: evolutionary information of residues in the variant neighborhood and their solvent accessibilities were observed to influence the predictions. We also highlight how predictions are impacted by the underlying disease mechanisms of missense mutations and offer insights into understanding these to improve pathogenicity predictions. Our study presents aspects to take into consideration when adopting deep learning approaches for protein structure-guided pathogenicity predictions.

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/ß-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 Tm 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.

Functional Analysis Identifies Damaging CHEK2 Missense Variants Associated with Increased Cancer Risk.

Heterozygous carriers of germline loss-of-function variants in the tumor suppressor gene checkpoint kinase 2 (CHEK2) are at an increased risk for developing breast and other cancers. While truncating variants in CHEK2 are known to be pathogenic, the interpretation of missense variants of uncertain significance (VUS) is challenging. Consequently, many VUS remain unclassified both functionally and clinically. Here we describe a mouse embryonic stem (mES) cell-based system to quantitatively determine the functional impact of 50 missense VUS in human CHEK2. By assessing the activity of human CHK2 to phosphorylate one of its main targets, Kap1, in Chek2 knockout mES cells, 31 missense VUS in CHEK2 were found to impair protein function to a similar extent as truncating variants, while 9 CHEK2 missense VUS resulted in intermediate functional defects. Mechanistically, most VUS impaired CHK2 kinase function by causing protein instability or by impairing activation through (auto)phosphorylation. Quantitative results showed that the degree of CHK2 kinase dysfunction correlates with an increased risk for breast cancer. Both damaging CHEK2 variants as a group [OR 2.23; 95% confidence interval (CI), 1.62-3.07; P < 0.0001] and intermediate variants (OR 1.63; 95% CI, 1.21-2.20; P = 0.0014) were associated with an increased breast cancer risk, while functional variants did not show this association (OR 1.13; 95% CI, 0.87-1.46; P = 0.378). Finally, a damaging VUS in CHEK2, c.486A>G/p.D162G, was also identified, which cosegregated with familial prostate cancer. Altogether, these functional assays efficiently and reliably identified VUS in CHEK2 that associate with cancer. SIGNIFICANCE: Quantitative assessment of the functional consequences of CHEK2 variants of uncertain significance identifies damaging variants associated with increased cancer risk, which may aid in the clinical management of patients and carriers.

Functional analysis of genetic variants in the high-risk breast cancer susceptibility gene PALB2.

Heterozygous carriers of germ-line loss-of-function variants in the DNA repair gene PALB2 are at a highly increased lifetime risk for developing breast cancer. While truncating variants in PALB2 are known to increase cancer risk, the interpretation of missense variants of uncertain significance (VUS) is in its infancy. Here we describe the development of a relatively fast and easy cDNA-based system for the semi high-throughput functional analysis of 48 VUS in human PALB2. By assessing the ability of PALB2 VUS to rescue the DNA repair and checkpoint defects in Palb2 knockout mouse embryonic stem (mES) cells, we identify various VUS in PALB2 that impair its function. Three VUS in the coiled-coil domain of PALB2 abrogate the interaction with BRCA1, whereas several VUS in the WD40 domain dramatically reduce protein stability. Thus, our functional assays identify damaging VUS in PALB2 that may increase cancer risk.

Recessive variants of MuSK are associated with late onset CMS and predominant limb girdle weakness.

Congenital myasthenic syndrome (CMS) is a heterogeneous disorder that causes fatigable muscle weakness. CMS has been associated with variants in the MuSK gene and, to date, 16 patients have been reported. MuSK-CMS patients present a different phenotypic pattern of limb girdle weakness. Here, we describe four additional patients and discuss the phenotypic and clinical relationship with those previously reported. Two novel damaging missense variants are described: c.1742T > A; p.I581N found in homozygosis, and c.1634T > C; p.L545P found in compound heterozygosis with p.R166*. The reported patients had predominant limb girdle weakness with symptom onset at 12, 17, 18, and 30 years of age, and the majority exhibited a good clinical response to Salbutamol therapy, but not to esterase inhibitors. Meta-analysis including previously reported variants revealed an increased likelihood of a severe, respiratory phenotype with null alleles. Missense variants exclusively affecting the kinase domain, but not the catalytic site, are associated with late onset. These data refine the phenotype associated with MuSK-related CMS.

Complex phenotypes associated with STIM1 mutations in both coiled coil and EF-hand domains.

Dominant mutations in STIM1 are a cause of three allelic conditions: tubular aggregate myopathy, Stormorken syndrome (a complex phenotype including myopathy, hyposplenism, hypocalcaemia and bleeding diathesis), and a platelet dysfunction disorder, York platelet syndrome. Previous reports have suggested a genotype-phenotype correlation with mutations in the N-terminal EF-hand domain associated with tubular aggregate myopathy, and a common mutation at p.R304W in a coiled coil domain associated with Stormorken syndrome. In this study individuals with STIM1 variants were identified by exome sequencing or STIM1 direct sequencing, and assessed for neuromuscular, haematological and biochemical evidence of the allelic disorders of STIM1. STIM1 mutations were investigated by fibroblast calcium imaging and 3D modelling. Six individuals with STIM1 mutations, including two novel mutations (c.262A>G (p.S88G) and c.911G>A (p.R304Q)), were identified. Extra-neuromuscular symptoms including thrombocytopenia, platelet dysfunction, hypocalcaemia or hyposplenism were present in 5/6 patients with mutations in both the EF-hand and CC domains. 3/6 patients had psychiatric disorders, not previously reported in STIM1 disease. Review of published STIM1 patients (n = 49) confirmed that neuromuscular symptoms are present in most patients. We conclude that the phenotype associated with activating STIM1 mutations frequently includes extra-neuromuscular features such as hypocalcaemia, hypo-/asplenia and platelet dysfunction regardless of mutation domain.

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.

GPCRdb: an information system for G protein-coupled receptors.

Recent developments in G protein-coupled receptor (GPCR) structural biology and pharmacology have greatly enhanced our knowledge of receptor structure-function relations, and have helped improve the scientific foundation for drug design studies. The GPCR database, GPCRdb, serves a dual role in disseminating and enabling new scientific developments by providing reference data, analysis tools and interactive diagrams. This paper highlights new features in the fifth major GPCRdb release: (i) GPCR crystal structure browsing, superposition and display of ligand interactions; (ii) direct deposition by users of point mutations and their effects on ligand binding; (iii) refined snake and helix box residue diagram looks; and (iii) phylogenetic trees with receptor classification colour schemes. Under the hood, the entire GPCRdb front- and back-ends have been re-coded within one infrastructure, ensuring a smooth browsing experience and development. GPCRdb is available at http://www.gpcrdb.org/ and it's open source code at https://bitbucket.org/gpcr/protwis.

GPCRDB: an information system for G protein-coupled receptors.

For the past 20 years, the GPCRDB (G protein-coupled receptors database; http://www.gpcr.org/7tm/) has been a 'one-stop shop' for G protein-coupled receptor (GPCR)-related data. The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data, such as multiple sequence alignments and homology models. The GPCRDB also provides visualization and analysis tools, plus a number of query systems. In the latest GPCRDB release, all multiple sequence alignments, and >65,000 homology models, have been significantly improved, thanks to a recent flurry of GPCR X-ray structure data. Tools were introduced to browse X-ray structures, compare binding sites, profile similar receptors and generate amino acid conservation statistics. Snake plots and helix box diagrams can now be custom coloured (e.g. by chemical properties or mutation data) and saved as figures. A series of sequence alignment visualization tools has been added, and sequence alignments can now be created for subsets of sequences and sequence positions, and alignment statistics can be produced for any of these subsets.

NucleaRDB: information system for nuclear receptors.

The NucleaRDB is a Molecular Class-Specific Information System that collects, combines, validates and disseminates large amounts of heterogeneous data on nuclear hormone receptors. It contains both experimental and computationally derived data. The data and knowledge present in the NucleaRDB can be accessed using a number of different interactive and programmatic methods and query systems. A nuclear hormone receptor-specific PDF reader interface is available that can integrate the contents of the NucleaRDB with full-text scientific articles. The NucleaRDB is freely available at http://www.receptors.org/nucleardb.

Integrating GPCR-specific information with full text articles.

BACKGROUND: With the continued growth in the volume both of experimental G protein-coupled receptor (GPCR) data and of the related peer-reviewed literature, the ability of GPCR researchers to keep up-to-date is becoming increasingly curtailed. RESULTS: We present work that integrates the biological data and annotations in the GPCR information system (GPCRDB) with next-generation methods for intelligently exploring, visualising and interacting with the scientific articles used to disseminate them. This solution automatically retrieves relevant information from GPCRDB and displays it both within and as an adjunct to an article. CONCLUSIONS: This approach allows researchers to extract more knowledge more swiftly from literature. Importantly, it allows reinterpretation of data in articles published before GPCR structure data became widely available, thereby rescuing these valuable data from long-dormant sources.

Snooker: a structure-based pharmacophore generation tool applied to class A GPCRs.

G-protein coupled receptors (GPCRs) are important drug targets for various diseases and of major interest to pharmaceutical companies. The function of individual members of this protein family can be modulated by the binding of small molecules at the extracellular side of the structurally conserved transmembrane (TM) domain. Here, we present Snooker, a structure-based approach to generate pharmacophore hypotheses for compounds binding to this extracellular side of the TM domain. Snooker does not require knowledge of ligands, is therefore suitable for apo-proteins, and can be applied to all receptors of the GPCR protein family. The method comprises the construction of a homology model of the TM domains and prioritization of residues on the probability of being ligand binding. Subsequently, protein properties are converted to ligand space, and pharmacophore features are generated at positions where protein ligand interactions are likely. Using this semiautomated knowledge-driven bioinformatics approach we have created pharmacophore hypotheses for 15 different GPCRs from several different subfamilies. For the beta-2-adrenergic receptor we show that ligand poses predicted by Snooker pharmacophore hypotheses reproduce literature supported binding modes for ∼75% of compounds fulfilling pharmacophore constraints. All 15 pharmacophore hypotheses represent interactions with essential residues for ligand binding as observed in mutagenesis experiments and compound selections based on these hypotheses are shown to be target specific. For 8 out of 15 targets enrichment factors above 10-fold are observed in the top 0.5% ranked compounds in a virtual screen. Additionally, prospectively predicted ligand binding poses in the human dopamine D3 receptor based on Snooker pharmacophores were ranked among the best models in the community wide GPCR dock 2010.

GPCRDB: information system for G protein-coupled receptors.

The GPCRDB is a Molecular Class-Specific Information System (MCSIS) that collects, combines, validates and disseminates large amounts of heterogeneous data on G protein-coupled receptors (GPCRs). The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data such as multiple sequence alignments and homology models. The GPCRDB provides access to the data via a number of different access methods. It offers visualization and analysis tools, and a number of query systems. The data is updated automatically on a monthly basis. The GPCRDB can be found online at http://www.gpcr.org/7tm/.

GPCR-OKB: the G Protein Coupled Receptor Oligomer Knowledge Base.

SUMMARY: Rapid expansion of available data about G Protein Coupled Receptor (GPCR) dimers/oligomers over the past few years requires an effective system to organize this information electronically. Based on an ontology derived from a community dialog involving colleagues using experimental and computational methodologies, we developed the GPCR-Oligomerization Knowledge Base (GPCR-OKB). GPCR-OKB is a system that supports browsing and searching for GPCR oligomer data. Such data were manually derived from the literature. While focused on GPCR oligomers, GPCR-OKB is seamlessly connected to GPCRDB, facilitating the correlation of information about GPCR protomers and oligomers. AVAILABILITY AND IMPLEMENTATION: The GPCR-OKB web application is freely available at http://www.gpcr-okb.org

Homology modelling and spectroscopy, a never-ending love story.

Homology modelling is normally the technique of choice when experimental structure data are not available but three-dimensional coordinates are needed, for example, to aid with detailed interpretation of results of spectroscopic studies. Herein, the state of the art of homology modelling will be described in the light of a series of recent developments, and an overview will be given of the problems and opportunities encountered in this field. The major topic, the accuracy and precision of homology models, will be discussed extensively due to its influence on the reliability of conclusions drawn from the combination of homology models and spectroscopic data. Three real-world examples will illustrate how both homology modelling and spectroscopy can be beneficial for (bio)medical research.