Teneurin C-Terminal Associated Peptide (TCAP)-1 and Latrophilin Interaction in HEK293 Cells: Evidence for Modulation of Intercellular Adhesion

The teneurins are a family of four transmembrane proteins essential to intercellular adhesion processes, and are required for the development and maintenance of tissues. The Adhesion G protein-coupled receptor (GPCR) subclass latrophilins (ADGRL), or simply the latrophilins (LPHN), are putative receptors of the teneurins and act, in part, to mediate intercellular adhesion via binding with the teneurin extracellular region. At the distal tip of the extracellular region of each teneurin lies a peptide sequence termed the teneurin C-terminal associated peptide (TCAP). TCAP-1, associated with teneurin-1, is itself bioactive, suggesting that TCAP is a critical functional region of teneurin. However, the role of TCAP-1 has not been established with respect to its ability to interact with LPHN to induce downstream effects. To establish that TCAP-1 binds to LPHN1, a FLAG-tagged hormone binding domain (HBD) of LPHN1 and a GFP-tagged TCAP-1 peptide were co-expressed in HEK293 cells. Both immunoreactive epitopes were co-localized as a single band after immunoprecipitation, indicating an association between the two proteins. Moreover, fluorescent co-labeling occurred at the plasma membrane of LPHN1 over-expressing cells when treated with a FITC-tagged TCAP-1 variant. Expression of LPHN1 and treatment with TCAP-1 modulated the actin-based cytoskeleton in these cells in a manner consistent with previously reported actions of TCAP-1 and affected the overall morphology and aggregation of the cells. This study indicates that TCAP-1 may associate directly with LPHN1 and could play a role in the modulation of cytoskeletal organization and intercellular adhesion and aggregation via this interaction

Correction to: Phenotate: crowdsourcing phenotype annotations as exercises in undergraduate classes (Genetics in Medicine, (2020), 22, 8, (1391-1400), 10.1038/s41436-020-0812-7)

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Binding, Activation and Cellular Actions of Teneurin C-terminal Associated Peptide (TCAP)-1 with its Putative Receptor, Latrophilin-1 (ADGRL1), in Immortalized Cell Lines

Teneurins are multifunctional type II transmembrane proteins that bind the Adhesion G-protein coupled receptor subfamily L/Latrophilin (ADGRL) in the only intermolecular synaptic adhesion unit conserved between invertebrates and vertebrates. However, the specific interaction between teneurin and ADGRL is not well understood. The distal extracellular region of teneurin possesses a potentially cleavable bioactive peptide termed the ‘teneurin C-terminal associated peptide’ (TCAP). A synthetic version of TCAP-1 is highly active in cells, causing increased expression of cytoskeletal components and actin re-arrangement. Yet the mechanism by which TCAP-1 induces these effects remains unclear. HCT116 cells over-expressing ADGRL1 have increased uptake of TCAP-1 compared to wild-type cells. ADGRL1 expression causes increased adhesion between cells and reduces their expression of f-actin. TCAP-1 treatment induces f-actin polymerization and modulation of cellular morphology only in ADGRL1-expressing cells. These data are the first to establish TCAP-1 as an endogenous ADGRL1 ligand, and further elucidate its mode of action.M.Sc

Phenotate: crowdsourcing phenotype annotations as exercises in undergraduate classes.

PURPOSE: Computational documentation of genetic disorders is highly reliant on structured data for differential diagnosis, pathogenic variant identification, and patient matchmaking. However, most information on rare diseases (RDs) exists in freeform text, such as academic literature. To increase availability of structured RD data, we developed a crowdsourcing approach for collecting phenotype information using student assignments. METHODS: We developed Phenotate, a web application for crowdsourcing disease phenotype annotations through assignments for undergraduate genetics students. Using student-collected data, we generated composite annotations for each disease through a machine learning approach. These annotations were compared with those from clinical practitioners and gold standard curated data. RESULTS: Deploying Phenotate in five undergraduate genetics courses, we collected annotations for 22 diseases. Student-sourced annotations showed strong similarity to gold standards, with F-measures ranging from 0.584 to 0.868. Furthermore, clinicians used Phenotate annotations to identify diseases with comparable accuracy to other annotation sources and gold standards. For six disorders, no gold standards were available, allowing us to create some of the first structured annotations for them, while students demonstrated ability to research RDs. CONCLUSION: Phenotate enables crowdsourcing RD phenotypic annotations through educational assignments. Presented as an intuitive web-based tool, it offers pedagogical benefits and augments the computable RD knowledgebase

CReSCENT: Cancer single cell expressioN toolkit

CReSCENT: CanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of singlecell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires highperformance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users