Structural insights into leucine-rich repeat-containing synaptic cleft molecules

LRRC superfamily expression in stromal cells predicts the clinical prognosis and platinum resistance of ovarian cancer

BACKGROUND

Leucine-rich repeat sequence domains are known to mediate protein‒protein interactions. Recently, some studies showed that members of the leucine rich repeat containing (LRRC) protein superfamily may become new targets for the diagnosis and treatment of tumours. However, it is not known whether any of the LRRC superfamily genes is expressed in the stroma of ovarian cancer (OC) and is associated with prognosis.

METHODS

The clinical data and transcriptional profiles of OC patients from the public databases TCGA (n = 427), GTEx (n = 88) and GEO (GSE40266 and GSE40595) were analysed by R software. A nomogram model was also generated through R. An online public database was used for auxiliary analysis of prognosis, immune infiltration and protein‒protein interaction (PPI) networks. Immunohistochemistry and qPCR were performed to determine the protein and mRNA levels of genes in high-grade serous ovarian cancer (HGSC) tissues of participants and the MRC-5 cell line induced by TGF-β.

RESULTS

LRRC15 and LRRC32 were identified as differentially expressed genes from the LRRC superfamily by GEO transcriptome analysis. PPI network analysis suggested that they were most enriched in TGF-β signalling. The TCGA-GTEx analysis results showed that only LRRC15 was highly expressed in both cancer-associated fibroblasts (CAFs) and the tumour stroma of OC and was related to clinical prognosis. Based on this, we developed a nomogram model to predict the incidence of adverse outcomes in OC. Moreover, LRRC15 was positively correlated with CAF infiltration and negatively correlated with CD8 + T-cell infiltration. As a single indicator, LRRC15 had the highest accuracy (AUC = 0.920) in predicting the outcome of primary platinum resistance.

CONCLUSIONS

The LRRC superfamily is related to the TGF-β pathway in the microenvironment of OC. LRRC15, as a stromal biomarker, can predict the clinical prognosis of HGSC and promote the immunosuppressive microenvironment. LRRC15 may be a potential therapeutic target for reversing primary resistance in OC.

Deep learning-based synapse counting and synaptic ultrastructure analysis of electron microscopy images

BACKGROUND

Synapses are the connections between neurons in the central nervous system (CNS) or between neurons and other excitable cells in the peripheral nervous system (PNS), where electrical or chemical signals rapidly travel through one cell to another with high spatial precision. Synaptic analysis, based on synapse numbers and fine morphology, is the basis for understanding neurological functions and diseases. Manual analysis of synaptic structures in electron microscopy (EM) images is often limited by low efficiency and subjective bias.

NEW METHOD

We developed a multifunctional synaptic analysis system based on several advanced deep learning (DL) models. The system achieved synapse counting in low-magnification EM images and synaptic ultrastructure analysis in high-magnification EM images.

RESULTS

The synapse counting system based on ResNet18 and a Faster R-CNN model had a mean average precision (mAP) of 92.55%. For synaptic ultrastructure analysis, the Faster R-CNN model based on ResNet50 achieved a mAP of 91.60%, the DeepLab v3 + model based on ResNet50 enabled high performance in presynaptic and postsynaptic membrane segmentation with a global accuracy of 0.9811, and the Faster R-CNN model based on ResNet18 achieved a mAP of 91.41% for synaptic vesicle detection.

CONCLUSIONS

The proposed multifunctional synaptic analysis system may help to overcome the experimental bias inherent in manual analysis, thereby facilitating EM image-based synaptic function studies.

Trans-synaptic assemblies link synaptic vesicles and neuroreceptors

Synaptic transmission is characterized by fast, tightly coupled processes and complex signaling pathways that require a precise protein organization, such as the previously reported nanodomain colocalization of pre- and postsynaptic proteins. Here, we used cryo-electron tomography to visualize synaptic complexes together with their native environment comprising interacting proteins and lipids on a 2- to 4-nm scale. Using template-free detection and classification, we showed that tripartite trans-synaptic assemblies (subcolumns) link synaptic vesicles to postsynaptic receptors and established that a particular displacement between directly interacting complexes characterizes subcolumns. Furthermore, we obtained de novo average structures of ionotropic glutamate receptors in their physiological composition, embedded in plasma membrane. These data support the hypothesis that synaptic function is carried by precisely organized trans-synaptic units. It provides a framework for further exploration of synaptic and other large molecular assemblies that link different cells or cellular regions and may require weak or transient interactions to exert their function.

Structural basis of SALM3 dimerization and synaptic adhesion complex formation with PTPσ

Synaptic adhesion molecules play an important role in the formation, maintenance and refinement of neuronal connectivity. Recently, several leucine rich repeat (LRR) domain containing neuronal adhesion molecules have been characterized including netrin G-ligands, SLITRKs and the synaptic adhesion-like molecules (SALMs). Dysregulation of these adhesion molecules have been genetically and functionally linked to various neurological disorders. Here we investigated the molecular structure and mechanism of ligand interactions for the postsynaptic SALM3 adhesion protein with its presynaptic ligand, receptor protein tyrosine phosphatase σ (PTPσ). We solved the crystal structure of the dimerized LRR domain of SALM3, revealing the conserved structural features and mechanism of dimerization. Furthermore, we determined the complex structure of SALM3 with PTPσ using small angle X-ray scattering, revealing a 2:2 complex similar to that observed for SALM5. Solution studies unraveled additional flexibility for the complex structure, but validated the uniform mode of action for SALM3 and SALM5 to promote synapse formation. The relevance of the key interface residues was further confirmed by mutational analysis with cellular binding assays and artificial synapse formation assays. Collectively, our results suggest that SALM3 dimerization is a pre-requisite for the SALM3-PTPσ complex to exert synaptogenic activity.