Experimental validation of computerised models of clustering of platelet glycoprotein receptors that signal via tandem SH2 domain proteins

The clustering of platelet glycoprotein receptors with cytosolic YxxL and YxxM motifs, including GPVI, CLEC-2 and PEAR1, triggers activation via phosphorylation of the conserved tyrosine residues and recruitment of the tandem SH2 (Src homology 2) domain effector proteins, Syk and PI 3-kinase. We have modelled the clustering of these receptors with monovalent, divalent and tetravalent soluble ligands and with transmembrane ligands based on the law of mass action using ordinary differential equations and agent-based modelling. The models were experimentally evaluated in platelets and transfected cell lines using monovalent and multivalent ligands, including novel nanobody-based divalent and tetravalent ligands, by fluorescence correlation spectroscopy. Ligand valency, receptor number, receptor dimerisation, receptor phosphorylation and a cytosolic tandem SH2 domain protein act in synergy to drive receptor clustering. Threshold concentrations of a CLEC-2-blocking antibody and Syk inhibitor act in synergy to block platelet aggregation. This offers a strategy for countering the effect of avidity of multivalent ligands and in limiting off-target effects

Experimental validation of computerised models of clustering of platelet glycoprotein receptors that signal via tandem SH2 domain proteins

The clustering of platelet glycoprotein receptors with cytosolic YxxL and YxxM motifs, including GPVI, CLEC-2 and PEAR1, triggers activation via phosphorylation of the conserved tyrosine residues and recruitment of the tandem SH2 (Src homology 2) domain effector proteins, Syk and PI 3-kinase. We have modelled the clustering of these receptors with monovalent, divalent and tetravalent soluble ligands and with transmembrane ligands based on the law of mass action using ordinary differential equations and agent-based modelling. The models were experimentally evaluated in platelets and transfected cell lines using monovalent and multivalent ligands, including novel nanobody-based divalent and tetravalent ligands, by fluorescence correlation spectroscopy. Ligand valency, receptor number, receptor dimerisation, receptor phosphorylation and a cytosolic tandem SH2 domain protein act in synergy to drive receptor clustering. Threshold concentrations of a CLEC-2-blocking antibody and Syk inhibitor act in synergy to block platelet aggregation. This offers a strategy for countering the effect of avidity of multivalent ligands and in limiting off-target effects

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock

Models of Models: A Translational Route for Cancer Treatment and Drug Development

Every patient and every disease is different. Each patient therefore requires a personalized treatment approach. For technical reasons, a personalized approach is feasible for treatment strategies such as surgery, but not for drug-based therapy or drug development. The development of individual mechanistic models of the disease process in every patient offers the possibility of attaining truly personalized drug-based therapy and prevention. The concept of virtual clinical trials and the integrated use of in silico, in vitro, and in vivo models in preclinical development could lead to significant gains in efficiency and order of magnitude increases in the cost effectiveness of drug development and approval. We have developed mechanistic computational models of large-scale cellular signal transduction networks for prediction of drug effects and functional responses, based on patient-specific multi-level omics profiles. However, a major barrier to the use of such models in a clinical and developmental context is the reliability of predictions. Here we detail how the approach of using “models of models” has the potential to impact cancer treatment and drug development. We describe the iterative refinement process that leverages the flexibility of experimental systems to generate highly dimensional data, which can be used to train and validate computational model parameters and improve model predictions. In this way, highly optimized computational models with robust predictive capacity can be generated. Such models open up a number of opportunities for cancer drug treatment and development, from enhancing the design of experimental studies, reducing costs, and improving animal welfare, to increasing the translational value of results generated

Functional Analysis of Centrosomal Kinase Substrates in Drosophila melanogaster Reveals a New Function of the Nuclear Envelope Component Otefin in Cell Cycle Progression

Phosphorylation is one of the key mechanisms that regulate centrosome biogenesis, spindle assembly, and cell cycle progression. However, little is known about centrosome-specific phosphorylation sites and their functional relevance. Here, we identified phosphoproteins of intact Drosophila melanogaster centrosomes and found previously unknown phosphorylation sites in known and unexpected centrosomal components. We functionally characterized phosphoproteins and integrated them into regulatory signaling networks with the 3 important mitotic kinases, cdc2, polo, and aur, as well as the kinase CkIIβ. Using a combinatorial RNA interference (RNAi) strategy, we demonstrated novel functions for P granule, nuclear envelope (NE), and nuclear proteins in centrosome duplication, maturation, and separation. Peptide microarrays confirmed phosphorylation of identified residues by centrosome-associated kinases. For a subset of phosphoproteins, we identified previously unknown centrosome and/or spindle localization via expression of tagged fusion proteins in Drosophila SL2 cells. Among those was otefin (Ote), an NE protein that we found to localize to centrosomes. Furthermore, we provide evidence that it is phosphorylated in vitro at threonine 63 (T63) through Aurora-A kinase. We propose that phosphorylation of this site plays a dual role in controlling mitotic exit when phosphorylated while dephosphorylation promotes G2/M transition in Drosophila SL2 cells

Gene ontology analysis of the centrosome proteomes of Drosophila and human

The centrosome is a complex cell organelle in higher eukaryotic cells that functions in microtubule organization and is integrated into major cellular signaling pathways.1–3 For example, a tight link exists between cell cycle regulation and centrosome duplication, as centrosome numbers must be precisely controlled to ensure high fidelity of chromosome segregation.4 The analysis of the centrosome's protein composition provides the opportunity for a better understanding of centrosome function and to identify possible links to cellular signaling pathways.5,6 Our proteomics study of the Drosophila centrosome recently identified 251 centrosome candidate proteins that we subsequently characterized by RNAi in Drosophila SL2 cells and classified according to their function in centrosome duplication/segregation, structure maintenance and cell cycle regulation.7 Interestingly, functional characterization of their human orthologous proteins revealed the highest functional conservation in the process of centrosome duplication and separation. To analyze functional and biochemical interdependencies further, we carried out an analysis of the gene ontology (GO) annotation of the identified Drosophila centrosome proteins, as well as of the human centrosome proteome.5 The GO analysis of the group of proteins that did not show a centrosome, chromosome segregation or cell cycle related phenotype in our RNAi assays suggests that these molecules may constitute linker proteins to other cellular signaling pathways. Furthermore, the results of our GO analysis of components of the human and of the Drosophila centrosome reflect the somatic and embryonic origin, respectively, of the isolated centrosomes, implicating the Drosophila centrosome proteins in developmental signaling and cell differentiation

Experimental validation of computerised models of clustering of platelet glycoprotein receptors that signal via tandem SH2 domain proteins

The clustering of platelet glycoprotein receptors with cytosolic YxxL and YxxM motifs, including GPVI, CLEC-2 and PEAR1, triggers activation via phosphorylation of the conserved tyrosine residues and recruitment of the tandem SH2 (Src homology 2) domain effector proteins, Syk and PI 3-kinase. We have modelled the clustering of these receptors with monovalent, divalent and tetravalent soluble ligands and with transmembrane ligands based on the law of mass action using ordinary differential equations and agent-based modelling. The models were experimentally evaluated in platelets and transfected cell lines using monovalent and multivalent ligands, including novel nanobody-based divalent and tetravalent ligands, by fluorescence correlation spectroscopy. Ligand valency, receptor number, receptor dimerisation, receptor phosphorylation and a cytosolic tandem SH2 domain protein act in synergy to drive receptor clustering. Threshold concentrations of a CLEC-2-blocking antibody and Syk inhibitor act in synergy to block platelet aggregation. This offers a strategy for countering the effect of avidity of multivalent ligands and in limiting off-target effects