Termination of TCR-mediated activation signals is regulated by CrkII-dependent Cbl-mediated ubiquitination and degradation of C3G

Crk adaptor proteins are key players in signal transduction from multiple cell surface receptors, including the T cell antigen receptor (TCR). The involvement of CrkII in the early stages of T cell activation is well documented, but little is known about its role during the termination of the activation response. We substantiated findings showing that CrkII utilizes its SH3N and SH2 domains to constitutively associate with C3G and transiently with Cbl in resting and TCR/CD3-stimulated T cells, respectively. Association of CrkII with Cbl peaks within 1 min post-TCR/CD3 stimulation, and involves the formation of multiple CrkII-containing complexes of different molecular mass. Ubiquitination of C3G commences at ～5 min post TCR/CD3 stimulation concomitantly with its degradation. This entire process conversely correlates with the levels of expression of CrkII and is dependent on the presence of the CrkII-bound Cbl protein. The data suggest that CrkII functions as a scaffold that brings Cbl into close proximity with C3G in TCR/CD3-stimulated T cells and that tyrosine phosphorylation and activation of Cbl promotes C3G ubiquitination and degradation. We suggest that this mechanism contributes to the termination of the TCR/CD3-induced activation signal and helps tune the length and intensity of T cell-mediated immune responses.     

Effect of gut flora mediated-bile acid metabolism on intestinal immune microenvironment

According to reports, gut microbiota and metabolites regulate the intestinal immune microenvironment. In recent years, an increasing number of studies reported that bile acids (BAs) of intestinal flora origin affect T helper cells and regulatory T cells (Treg cells). Th17 cells play a pro-inflammatory role and Treg cells usually act in an immunosuppressive role. In this review, we emphatically summarised the influence and corresponding mechanism of different configurations of lithocholic acid (LCA) and deoxycholic acid (DCA) on intestinal Th17 cells, Treg cells and intestinal immune microenvironment. The regulation of BAs receptors G protein-coupled bile acid receptor 1 (GPBAR1/TGR5) and farnesoid X receptor (FXR) on immune cells and intestinal environment are elaborated. Furthermore, the potential clinical applications above were also concluded in three aspects. The above will help researchers better understand the effects of gut flora on the intestinal immune microenvironment via BAs and contribute to the development of new targeted drugs.     

Increased copy number of 23S ribosomal RNA gene with point mutation in MRSA associated with linezolid resistance in a patient treated with long-term linezolid

BackgroundMethicillin-resistant Staphylococcus aureus (MRSA) infection is one of the most difficult infections we have to treat. Linezolid is one of the effective treatment options for refractory MRSA infections. There are cases where we are forced to use long-term linezolid treatment for refractory MRSA infections.ObjectiveTo discuss the evolution of Linezolid resistance factors in clinical isolates of MRSA.MethodsWe investigated 16 MRSA isolated from a patient treated with linezolid for a long period of 75 days. We performed antibiotic susceptibility test, 23S rRNA genes sequencing analysis, Pulsed-field gel electrophoresis.ResultsMRSA isolates were susceptible to linezolid before the start of treatment, but became less susceptible by prolonged treatment. The 23S rRNA sequencing analysis of linezolid-resistant strains that appeared 17 days after the start of treatment with linezolid revealed that all resistant MRSA had the G2576T substitution (Escherichia coli 23S rRNA gene number). The number of copies of this mutation increased with the use of linezolid.ConclusionLong-term use of linezolid in a patient or reuse of linezolid in a patient who has been previously treated with linezolid can lead to the emerging of linezolid-resistant MRSA in the host.     

Endocannabinoid signaling in glioma

High-grade gliomas constitute the most frequent and aggressive form of primary brain cancer in adults. These tumors express cannabinoid CB₁ and CB₂ receptors, as well as other elements of the endocannabinoid system. Accruing preclinical evidence supports that pharmacological activation of cannabinoid receptors located on glioma cells exerts overt anti-tumoral effects by modulating key intracellular signaling pathways. The mechanism of this cannabinoid receptor-evoked anti-tumoral activity in experimental models of glioma is intricate and may involve an inhibition not only of cancer cell survival/proliferation, but also of invasiveness, angiogenesis, and the stem cell-like properties of cancer cells, thereby affecting the complex tumor microenvironment. However, the precise biological role of the endocannabinoid system in the generation and progression of glioma seems very context-dependent and remains largely unknown. Increasing our basic knowledge on how (endo)cannabinoids act on glioma cells could help to optimize experimental cannabinoid-based anti-tumoral therapies, as well as the preliminary clinical testing that is currently underway.     

Gene–environment interaction analysis via deep learning

Gene–environment (G–E) interaction analysis plays an important role in studying complex diseases. Extensive methodological research has been conducted on G–E interaction analysis, and the existing methods are mostly based on regression techniques. In many fields including biomedicine and omics, it has been increasingly recognized that deep learning may outperform regression with its unique flexibility (e.g., in accommodating unspecified nonlinear effects) and superior prediction performance. However, there has been a lack of development in deep learning for G–E interaction analysis. In this article, we fill this important knowledge gap and develop a new analysis approach based on deep neural network in conjunction with penalization. The proposed approach can simultaneously conduct model estimation and selection (of important main G effects and G–E interactions), while uniquely respecting the “main effects, interactions” variable selection hierarchy. Simulation shows that it has superior prediction and feature selection performance. The analysis of data on lung adenocarcinoma and skin cutaneous melanoma overall survival further establishes its practical utility. Overall, this study can advance G–E interaction analysis by delivering a powerful new analysis approach based on modern deep learning.     

Spatiotemporal GPCR signaling illuminated by genetically encoded fluorescent biosensors

G protein-coupled receptors (GPCRs) are ligand-activated cell membrane proteins and represent the most important class of drug targets. GPCRs adopt several active conformations that stimulate different intracellular G proteins (and other transducers) and thereby modulate second messenger levels, eventually resulting in receptor-specific cell responses. It is increasingly accepted that not only the type of active signaling protein but also the duration of its stimulation and the subcellular location from where receptors signal distinctly contribute to the overall cell response. However, the molecular principles governing such spatiotemporal GPCR signaling and their role in disease are incompletely understood. Genetically encoded, fluorescent biosensors—in particular for the GPCR/cAMP signaling axis—have been pivotal to the discovery and molecular understanding of novel concepts in spatiotemporal GPCR signaling. These include GPCR priming, location bias, and receptor-associated independent cAMP nanodomains. Here, we review such technologies that we believe will illuminate the spatiotemporal organization of other GPCR signaling pathways that define the complex signaling architecture of the cell.