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Zhao, Q.

Publications and source records attributed to Zhao, Q..

At least 91 records · Page 5Linked to original sources

Retrieval practice prevents stress-induced inference impairment by restoring rapid memory reactivation

A hallmark of human memory is its ability to form novel inferences by linking discrete but related events. We examined whether acute stress impairs memory inference and if retrieval practice can buffer this effect. Participants were trained on image pairs, AB and BC, to establish interconnected triads (ABC) with a shared bridge element B. Twenty-four hours later, we induced acute stress in half of the participants and then tested their capacity to infer the indirect AC associations. Behavioral results indicated that acute stress-induced memory inference accuracy and speed, and retrieval practice was associated with attenuation of stress-induced impairment in A-C inference accuracy and speed. Using multivariate decoding analysis of human electroencephalogram (EEG) recordings, we found neural evidence that bridge element B is rapidly reactivated during the inferential process, a neural signature predictive of subsequent successful inference. Importantly, stress disrupts this rapid neural reactivation of the bridge element, but retrieval practice buffers the stress effect and enhances the strength of reactivation signals beyond the non-stress condition. Time-frequency analyses of theta oscillations mirrored these effects of stress and retrieval practice on inference performance and neural reactivation. Collectively, our findings pinpoint rapid reactivation of the bridge element as an essential neural mechanism for memory-based inference. Although susceptible to stress, this mechanism can be enhanced through retrieval practice, suggesting that building robust memory traces renders subsequent inferences resilient to stress.

neuroscience↗

Early warning signals of emerging infectious diseases

Establishing early warning systems for infectious disease outbreaks could save millions of lives by enabling rapid response and containment. One promising approach draws on the concept of critical slowing down (CSD)--a phenomenon in which complex systems lose resilience before tipping points--detected using resilience indicators (RIs) derived from the statistical properties of time series. While disease outbreaks may exhibit such early warning signals of critical transitions, most prior applications of CSD theory to global health have been limited to single diseases or locations, without broad assessments of predictive accuracy or lead time--the interval between the detection of warning signals and the onset of an outbreak. To address these limitations, we integrate CSD theory with time-to-event analyses to evaluate the predictive performance of 17 RIs across 31 infectious diseases in 134 regions worldwide. We find that both RIs and time- to-event analyses provide ample time to implement control measures, reliably anticipating outbreaks with a mean lead time of 17-21 days. Lead time was greater for pathogens with longer incubation periods and in regions with higher Human Development Index. Additionally, temperature and precipitation exhibited unimodal effects on lead time predictions for vector-borne and viral diseases. These findings highlight the value of incorporating socio-environmental drivers into outbreak forecasting models and lay the foundation for a local-to-global early warning system capable of guiding proactive public health interventions.

ecology↗

Drug repurposing reveals Posaconazole as a CYP11A1 inhibitor enhancing anti-tumour immunity

Steroid hormones regulate cell physiology and immune function, with dysregulated steroidogenesis promoting cancer progression by supporting tumour growth and suppressing anti-tumour immunity. Targeting CYP11A1, the first and rate-limiting enzyme in steroid biosynthesis, has shown promise in cancer therapy, but safe and effective inhibitors remain an unmet need. Undertaking in silico structure-based drug repurposing approach, we found Posaconazole as an inhibitor of CYP11A1. The docking pose analysis showed that Posaconazole can form multiple hydrogen bonds and hydrophobic interactions with the key residues at the binding site and the cofactor, stabilising the protein-ligand complex. We validated its inhibition efficiency in cell-based assays. In a mouse model of lung metastasis, we demonstrated that Posaconazole restricts metastatic cancer growth by stimulating anti-tumour immunity. These findings highlight Posaconazoles potential as a research tool to study steroidogenesis and as a candidate for further preclinical and clinical evaluation in pathological conditions associated with local steroid production, such as steroidogenic tumours.

immunology↗

Age-Dependent Patterns of Gut Bifidobacterium Microbiome Diversity across child Cohorts in a Multi-Ethnic population, Western China

High-throughput sequencing has provided unprecedented opportunities to elucidate the role of human gut microbiota. However, current studies have primarily focused on infant and adult cohorts, leaving biomarkers associated with the development of transitional children unclear, particularly in revealing geographic, multi-ethnic group underrepresented. Here, we analyzed fecal samples from 776 infants and children aged 0 to 15 years with amplicon sequencing of the 16S rRNA and groEL gene, representing multi-ethnic groups from different residential locations in the Yining region of Xinjiang. First, we systematically characterized the gut microbiota Spectrum of children in the Ili region. As age increases, the diversity and functional composition of the microbiota become richer and more stable, with Bifidobacterium consistently dominating the community. Utilizing Bayesian regression models, we identified a cluster of microbiota strongly associated with growth and development in children, which phylogenetically corresponds to Bifidobacterium breve. Finally, we included another similar study in the species-level of Bifidobacterium, and metrics of the age-related effect sizes showed heterogeneity across ethnic groups (Uyghur vs Han: {beta}Deming = 4.40 and Kazakh vs Han: {beta}Deming = 4.33). In conclusion, this study provides novel insights into the developmental trajectories of the gut microbiome in children and its relationship with health. IMPORTANCEThe intestinal microbial markers associated with the development of geographically diverse, multi-ethnic children, particularly those represented by Bifidobacterium species, have been elucidated in this study. Through the application of Bayesian regression models, we identified a microbiome profile closely linked to childhood growth and development, specifically phylogenetically aligned with Bifidobacterium breve. When incorporating a comparable study conducted at the species level of another Bifidobacterium, it was observed that age-related effect sizes varied among different ethnic groups, offering novel insights into the developmental trajectory of childrens gut microbiota and its implications for health.

microbiology↗

High-throughput Single-Virion DNA-PAINT Reveals Structural Diversity, Cooperativity and Flexibility during Selective Packaging in Influenza

Influenza A, a negative-sense RNA virus, has a genome that consists of eight single-stranded RNA segments. Influenza co-infections can result in re-assortant viruses that contain gene segments from multiple strains, causing pandemic outbreaks with severe consequences for human health. The outcome of re-assortment is likely influenced by a selective sequence-specific genome packaging mechanism. To uncover the contributions of individual segment pairings to selective packaging, we set out to statistically analyse packaging defects and inter-segment distances in individual A/Puerto Rico/8/34 (H1N1) (PR8) virus particles. To enable such analysis, we developed a multiplexed DNA-PAINT approach capable of assessing the segment stoichiometry of more than 10,000 individual virus particles in one experiment; our approach can also spatially resolve the individual segments inside complete virus particles with a localisation precision of ~10 nm. Our results show the influenza genome can be assembled through multiple pathways in a redundant and cooperative process guided by preferentially interacting segment pairs and aided by synergistic effects that enhance genome assembly, driving it to completion. Our structural evidence indicates that the interaction strength of segment pairs affects the spatial configuration of the gene segments, which appears to be preserved in mature virions. As our method quantified the interactions of whole influenza segments instead of identifying individual sequence-based interactions, our results can serve as a template to quantify the contributions of individual sequence motifs to selective packaging.

microbiology↗

Primitive steroidogenesis in mast cells: A novel regulatory mechanism for mast cell function

Mast cells, ancient immune sentinels, are crucial in immune responses, tissue homeostasis and inflammatory pathologies. This study unveils a previously unknown regulatory mechanism in mast cell biology: de novo steroidogenesis. Through comprehensive multi-omics analysis and functional assays, we demonstrate that mast cells express Cyp11a1 and produce pregnenolone, representing a primitive form of steroidogenesis. This cell-intrinsic steroidogenic pathway is essential for mast cell development, survival, and functional regulation. Genetic abrogation of mast cell steroidogenesis leads to exaggerated inflammatory and anaphylactic responses in vivo. Our integrative approach reveals extensive transcriptional and proteomic remodelling during mast cell regranulation, with steroidogenesis playing a pivotal role in coordinating recovery and tissue repair processes. We uncover significant sexual dimorphism in mast cell proteomes and a global uncoupling of transcriptional and translational programmes. These findings advance our understanding of mast cell physiology and provide a foundation for developing targeted therapies for mast cell-associated pathologies.

immunology↗

Tunable fluorogenic DNA probes drive fast and high-resolution single-molecule fluorescence imaging

A main limitation of single-molecule fluorescence (SMF) measurements is the "high concentration barrier", describing the maximum concentration of fluorescent species tolerable for sufficient signal-to-noise ratio (SNR). To address this barrier in several SMF applications, we design fluorogenic probes based on short ssDNAs, fluorescing only upon hybridising to their complementary target sequence. We engineer the quenching efficiency and fluorescence enhancement upon duplex formation through screening several fluorophore-quencher combinations, label lengths, and sequence motifs, which we utilise as tuning screws to adapt our labels to different experimental designs. Using these fluorogenic probes, we can perform SMF experiments at concentrations of 10 {micro}M fluorescent labels; this concentration is 100-fold higher than the operational limit for standard TIRF experiments. We demonstrate the ease of implementing these probes into existing protocols by performing super-resolution imaging with DNA-PAINT, employing a fluorogenic 6 nt-long imager; through the faster acquisition of binding events, the imaging of viral genome segments could be sped up significantly to achieve extraction of 20-nm structural features with only [~]150 s of imaging. The exceptional tunability of our probe design will overcome concentration barriers in SMF experiments and unlock new possibilities in super-resolution imaging, molecular tracking, and smFRET. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/634148v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@1d51a20org.highwire.dtl.DTLVardef@1a64fb7org.highwire.dtl.DTLVardef@1bbb4bforg.highwire.dtl.DTLVardef@578c63_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

Omics-based insights into human liver reveal GTPase-driven mechanisms of MASLD progression in obesity

Metabolic dysfunction-associated steatotic liver disease (MASLD) is often asymptomatic early on but can progress to irreversible conditions like cirrhosis. Due to limited access to human liver biopsies, systematic and integrative molecular resources remain scarce. In this study, we performed transcriptomic analyses on liver and metabolomic analyses on liver and plasma samples from morbidly obese individuals without liver pathology or at early-stage MASLD. While, the plasma metabolomic profile did not fully mirror liver histological features, dual-omics integration of liver samples revealed significantly remodeled lipid and amino acid metabolism pathways. Integrative network analysis uncoupled metabolic remodeling and gene expression as independent features of hepatic steatosis and fibrosis progression, respectively. Notably, GTPases and their regulators emerged as a novel class of genes linked to early liver fibrosis. This study offers a detailed molecular landscape of early MASLD in obesity and highlights potential targets of obesity-linked liver fibrosis. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=136 SRC="FIGDIR/small/632747v3_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1188eborg.highwire.dtl.DTLVardef@1340070org.highwire.dtl.DTLVardef@108d560org.highwire.dtl.DTLVardef@f0adda_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

Single-cell RNA sequencing analysis reveals new insights for intersex gonad initiation and early sex differentiation of goats

Polled intersex syndrome in goats severely impacts productivity and economic benefits, serving as a potential model for human reproductive defects. However, its specific molecular and cellular regulatory mechanisms remain unclear. This study combined single-cell RNA-sequencing (scRNA-seq) with tissue morphology and immunofluorescence detection to investigate the cellular heterogeneity, pseudo-time differentiation trajectory, differentially expressed genes, and regulatory networks of female, intersex, and male gonads during the 55-65 days embryonic stage of goats. The results indicated significant heterogeneity and cell fate transition in the somatic and germ cells of female, intersex, and male gonads at different developmental stages. Stromal cells may initiate female and intersexual gonad development, and epithelial cells may be the source of gonad cells in male fetuses. The abnormal expression of FOXL2, SOX9, AMH, DMRT1, RSPO1, INSL3, TCF21 and CSF1R may cause female-to-male sex reversal. The new candidate genes like PHLDB2, ZNRF3 and TEAD1 may contribute to the gender differentiation. Additionally, TREM2+ macrophages analogous to those in humans were identified in male gonads, while genes such as CSF1R and TYROBP potentially regulate macrophage immune privilege mechanisms. Early gonadal development in goats may also be regulated by circadian rhythm mechanisms similar to humans, with genes such as NR1D1, LGR4, and ATG5 involved in granulosa cell development, while genes such as ATG5, NRIP1, and FBXW11 may affect intersex trait development. In general, this study provided an important reference for exploring molecular and cellular mechanisms of intersex initiation during early embryonic development in goats and also for modelling human reproductive defects. Author summaryIn this study, we investigated the cell fate trajectory and key gene expression profile of goat fetus gonads using scRNA-seq. The analysis revealed cellular heterogeneity among normal male, normal female, and intersex gonadal somatic and germ cells, alongside their dynamic fate transitions across various developmental states. Pseudo-time trajectory analysis suggested that stromal cells might act as the initiation signal for female and intersexual gonad development, while epithelial cells could serve as the primary source of gonadal cells in male fetal goats. GO functional enrichment and KEGG analyses confirmed that abnormal expression of FOXL2, SOX9, AMH, DMRT1 and RSPO1 was linked to the emergence of intersexual gonads. Newly identified candidate genes including LRP2, PITX2, ARX, LHX9, PHLDB2, ZNRF3 and TEAD1 may contribute to sex-specific differences, while INSL3 and TCF21 could be linked to intersexual gonads. We identified TREM2+ macrophages analogous to those in humans, which could regulate immune privilege mechanisms. Circadian rhythmic changes were observed during early goat gonadal development.

developmental biology↗

GlioME: A Novel Organoid Model Retaining the Glioma Mi-croenvironment for Personalized Drug Screening and Thera-peutic Evaluation

Glioma is an aggressive brain tumor with a poor prognosis. Establishing an in vitro culture model that closely replicates the cellular composition and microenvironment of the original tumor has been challenging, limiting its clinical applications. Here, we present a novel approach to generate glioma organoids with a microenvironment (GlioME) from patient-derived glioma tissue. These organoids maintain the genetic and epigenetic characteristics of the primary tumor and preserve cell-to-cell interactions within the tumor microenvironment, including resident immune cells. Bulk RNA sequencing, whole exome sequencing, and DNA methylation analysis were used to confirm the molecular similarities between the organoids and primary glioma tissues. Immunofluorescence and flow cytometry were used to assess immune cell viability, comparing GlioME with floating glioma organoids. GlioME exhibited high responsiveness to chemotherapy and targeted therapy, demonstrating its potential for therapeutic screening applications. Notably, GlioME accurately predicted patient response to the recently approved MET inhibitor, vebreltinib. Thus, this organoid model provides a reliable in vitro platform for glioma microenvironment-related research and clinical drug screening.

cancer biology↗

Guidelines for alternative polyadenylation identification tools using single-cell and spatial transcriptomics data

BackgroundMany popular single-cell and spatial transcriptomics platforms exhibit 3 bias, making it challenging to resolve all transcripts but potentially more feasible to resolve alternative polyadenylation (APA) events. Despite the development of several tools for identifying APA events in scRNA-seq data, a neutral benchmark is lacking, complicating the choice for biologists. ResultsWe categorized existing APA analysis tools into three main classes, with the alignment-based class being the largest and we further divided this category into four sub-types. We compared the performance of methods from each algorithmic subtype in terms of site identification, quantification, and differential expression analysis across four single-cell and spatial transcriptomic datasets, using matched nanopore data as ground truth. No single method showed absolute superiority in all comparisons. Therefore, we selected representative methods (Sierra, scAPAtrap, and SCAPE) to deeply analyze the impact of different algorithmic choices on performance. SCAPE which is based on the distance estimation demonstrated less sensitivity to changes in read length and sequencing depth. It identified the most sites and achieved high recall but does not account for the impact of alternative splicing on site identification, leading to a loss in precision. Sierra that fits a coverage distribution is sensitive to changes in sequencing depth and identifies relatively fewer sites, but it considers the impact of junction reads on site identification and this results in relatively high precision. scAPAtrap combines peak calling and soft clipping, both of which are sensitive to sequencing depth. Moreover, soft clipping is particularly sensitive to read length, with increased read length leading to more false positive sites. Quantification consistency was affected by Cell Ranger versions and parameters, influencing downstream analysis but having less effect on differential expression between cell types. ConclusionsEach method has unique strengths. SCAPE is recommended for low-coverage data, scAPAtrap for moderate read lengths including intergenic sites, and Sierra for high-depth data with alternative splicing considerations. Filtering low-confidence sites, choosing appropriate mapping tools, and optimizing window size can improve performance.

bioinformatics↗

Accurate de novo design of high-affinity protein binding macrocycles using deep learning

The development of macrocyclic binders to therapeutic proteins typically relies on large-scale screening methods that are resource-intensive and provide little control over binding mode. Despite considerable progress in physics-based methods for peptide design and deep-learning methods for protein design, there are currently no robust approaches for de novo design of protein-binding macrocycles. Here, we introduce RFpeptides, a denoising diffusion-based pipeline for designing macrocyclic peptide binders against protein targets of interest. We test 20 or fewer designed macrocycles against each of four diverse proteins and obtain medium to high-affinity binders against all selected targets. Designs against MCL1 and MDM2 demonstrate KD between 1-10 M, and the best anti-GABARAP macrocycle binds with a KD of 6 nM and a sub-nanomolar IC50 in vitro. For one of the targets, RbtA, we obtain a high-affinity binder with KD < 10 nM despite starting from the target sequence alone due to the lack of an experimentally determined target structure. X-ray structures determined for macrocycle-bound MCL1, GABARAP, and RbtA complexes match very closely with the computational design models, with three out of the four structures demonstrating Ca RMSD of less than 1.5 [A] to the design models. In contrast to library screening approaches for which determining binding mode can be a major bottleneck, the binding modes of RFpeptides-generated macrocycles are known by design, which should greatly facilitate downstream optimization. RFpeptides thus provides a powerful framework for rapid and custom design of macrocyclic peptides for diagnostic and therapeutic applications.

biochemistry↗

Early-life antibiotic exposure leads to gut microbial dysbiosis associated with neurodevelopment and neuroregeneration

Early-life is a critical period for neurodevelopment and establishment of gut microbiota, which are highly susceptible to antibiotic exposure. Here, we aimed to investigate association between gut microbiota and metabolites with neurodevelopment and neuroregeneration in early-life after antibiotic exposure. To induce microbial dysbiosis in offspring, a broad-spectrum antibiotic cocktail was administered to mice dams. The prefrontal lobe, spinal cord tissues and gut sample of offspring were collected at different time with or without spinal cord crush injury. 16S rRNA sequencing and metabolomics were performed to analyze the gut microbiota and metabolites. NG2 glia were cultured and treated by mitochondrial fusion and fission compounds and metabolites. Maternal antibiotic exposure significantly affected neuronal maturation, NG2 glia proliferation, prefrontal cortex myelination and injured spinal cord neuroregeneration of offspring. Mice in antibiotic exposure group exhibited disruption of gut microbiota and metabolites, along with lower Ace, Chao and Shannon indexes, higher relative abundance of Enterobacter and Escherichia_Shigella, lower lactobacillus and Streptococcus genus, and downregulated Cyclo(Arg-Gly-Asp-D-Phe-Val), Ampicilloyl, DG(8:0/i-19:0/0:0), Petasinine and 6-Hydroxymelatonin glucuronide. These metabolites were enriched in alpha-Linolenic acid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, linoleic acid metabolism. 6-Hydroxymelatonin glucuronide, PC(20:3/0:0), PC(20:2/0:0), Ameltolide, DG(8:0/i-19:0/0:0), Inproquone, and Chorismate were the cores of networks between gut microbiota and metabolites and negatively associated with neurodevelopment and neuroregeneration. Additionally, gut microbiota metabolites promoted NG2 glia differentiation, partly through reversing the effects of mitochondrial fusion/fission compounds. Totally, antibiotic exposure in early-life changed the composition, abundance, and metabolites of gut microbiota in offspring, which was associated with neurodevelopment and neuroregeneration.

microbiology↗

A unified framework for drug-target interaction prediction by semantic-guided meta-path method

Drug-target interaction (DTI) prediction plays a crucial role in drug development, impacting areas such as virtual screening, drug repurposing, and the identification of potential drug side effects. Despite significant efforts dedicated to improving DTI prediction, existing methods still struggle with the challenges posed by the high sparsity of DTI datasets and the complexity of capturing heterogeneous information in biological networks. To address these challenges, we propose a unified framework for DTI prediction based on a semantics-guided meta-path walk. Specifically, we first pre-train drug and protein embeddings to capture their semantic information. This semantic information is then leveraged to guide a meta-path-based random walk on the biological heterogeneous network, generating sequences of interactions. These sequences are used to compute embedding features via a heterogeneous skip-gram model, which are subsequently fed into downstream tasks to predict DTIs. SGMDTI achieves substantial performance improvement over other state-of-the-art methods for drug-target interaction prediction. Moreover, it excels in the cold-start scenario, which is often a challenging case in DTI prediction. These results indicate the effectiveness of our approach in predicting drug-target interactions.Experimental datasets and experimental codes can be found in https://github.com/HYLPRC/SGMDTI

bioinformatics↗

Synaptic targets and cellular sources of CB1 cannabinoid receptor and vesicular glutamate transporter-3 expressing nerve terminals in relation to GABAergic neurons in the human cerebral cortex

Cannabinoid receptor 1 (CB1) regulates synaptic transmission through presynaptic receptors in nerve terminals, and its physiological roles are of clinical relevance. The cellular sources and synaptic targets of CB1-expressing terminals in the human cerebral cortex are undefined. We demonstrate a variable laminar pattern of CB1-immunorective axons and electron microscopically show that CB1-positive GABAergic terminals make type-2 synapses innervating dendritic shafts (69%), dendritic spines (20%) and somata (11%) in neocortical layers 2-3. Of the CB1-immunopositive GABAergic terminals, 25% were vesicular-glutamate-transporter-3 (VGLUT3)-immunoreactive, suggesting GABAergic/glutamatergic co-transmission on dendritic shafts. In vitro recorded and labelled VGLUT3 or CB1-positive GABAergic interneurons expressed cholecystokinin, vasoactive-intestinal-polypeptide and calretinin, had diverse firing, axons and dendrites, and included rosehip, neurogliaform and basket cells, but not double bouquet or axo-axonic cells. CB1-positive interneurons innervated pyramidal cells and GABAergic interneurons. Most glutamatergic synaptic terminals formed type-1 synapses and some were positive for CB1 receptor concentrated in the presynaptic active zone, unlike in GABAergic terminals. From the sampled VGLUT3-positive terminals, 60% formed type-1 synapses with dendritic spines (80%) or shafts (20%) and 52% were also positive for VGLUT1, suggesting intracortical origin. Some VGLUT3-positive terminals were immunopositive for vesicular-monoamine-transporter-2, suggesting 5-HT/glutamate co-transmission. Overall, the results show that CB1 regulates GABA release mainly to dendritic shafts of both pyramidal cells and interneurons, and predict CB1-regulated co-release of GABA and glutamate from single cortical interneurons. We also demonstrate the co-existence of multiple vesicular glutamate transporters in a select population of terminals probably originating from cortical neurons and innervating dendritic spines in the human cerebral cortex.

neuroscience↗

Spatial Single-Cell Mapping of Transcriptional Differences Across Genetic Backgrounds in Mouse Brains

Genetic variation can alter organ structure and, in turn, function. Comparative statistical analysis of organs across genetic backgrounds requires spatial, single-cell, atlas-scale data in replicates, which current technologies do not provide at scale. We introduce Atlas-scale Transcriptome Localization using Aggregate Signatures (ATLAS), a scalable tissue mapping method. ATLAS learns transcriptional signatures from scRNAseq data, encodes them in situ with tens of thousands of oligonucleotide probes, and decodes them to infer cell types and imputed transcriptomes. We validated ATLAS in the mouse brain by comparing its cell type inferences with direct MERFISH measurements of marker genes and quantitative comparisons to four other technologies. Using ATLAS, we mapped the central brains of five male and five female C57BL/6J (B6) mice and five male BTBR T+ tf/J (BTBR) mice, an idiopathic model of autism, collectively profiling over 40 million cells across over 400 coronal sections. Our analysis revealed over 40 significant differences in cell type distributions and identified 16 regional composition changes across male-female and B6-BTBR comparisons. ATLAS thus enables systematic comparative studies, facilitating organ-level structure-function analysis of disease models.

genomics↗

TYK2 inhibition enhances Treg differentiation and function while preventing Th1 and Th17 differnetiation

Janus kinase (JAK) inhibitors are widely use to inhibit inflammatory cytokine signalling in autoimmune and inflammatory diseases but their effect on regulatory T cells (Tregs) is poorly characterized. We investigated the effect of JAK inhibition on human Treg differentiation, phenotype, and function using a JAK inhibitor, upadacitinib, in comparison to BMS-986202, a selective Tyrosine kinase 2 (TYK2) inhibitor. Both upadacitinib and BMS-986202 blocked the differentiation of naive CD4+ T cells into Th1 and Th17 cells, but only BMS-986202 spared IL-2 signalling and Treg differentiation. BMS-986202 also increased Treg suppressive function and stability under Th1- and Th17-polarizing conditions, whereas upadacitinib significantly impaired the phenotype and viability of ex vivo Tregs. Analysis of lamina propria mononuclear cells from patients with inflammatory bowel disease revealed that, under Th17 polarizing conditions, BMS-986202 redirected CD4+ T cells towards a Treg phenotype. The Treg-sparing and enhancing properties of TYK2 inhibition suggest that TYK2 inhibitors are a promising pharmacological approach for tolerance induction. eTOC SUMMARYTuomela et al. report that TYK2 inhibition does not affect human Treg induction from naive CD4+ T cells, promotes Treg differentiation in lamina propria-derived T cells, and increases blood-derived Treg stability/function. In contrast, JAK inhibition strongly impairs Treg function.

immunology↗

Aryl-hydrocarbon receptor in smooth muscle cells protect against dioxin induced adverse remodeling of atherosclerosis

IntroductionEnvironmental exposure to dioxin has been linked to increased myocardial infarction. Smooth muscle cells (SMC) in the coronary vasculature play a critical role in atherosclerotic plaque remodeling due to their phenotypic plasticity, however, the detailed mechanism linking dioxin exposure to adverse SMC modulation is not well understood. MethodsSingle-cell RNA and ATAC sequencing and histological analyses were performed on the aorta from mouse models of atherosclerosis exposed to 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) or control. Primary human coronary artery SMC (HCASMC) treated in culture with TCDD were used to perform RNA-Seq, ATAC-Seq, and functional phenotypic assays. ChIP-Seq was performed with antibodies against Aryl-hydrocarbon receptor (AHR) and TCF21, two of known SMC modulating transcription factors. ResultsModulated SMC were the most transcriptionally responsive cell type to dioxin in the atherosclerotic aorta. Dioxin accelerated disease phenotype by promoting a modulated SMC phenotype early, resulting in increased lesion size, migration of SMC, and macrophage recruitment to the lesion. We found C3 expressing modulated SMCs to be likely contributing to the increased macrophage recruitment and inflammation. Analysis of the RNA-Seq data from HCASMC treated with TCDD showed differential enrichment of biological pathways related to cell migration, localization, and inflammation. Furthermore, ATAC-Seq data showed a significant activation for pathways regulating vascular development, cell migration, inflammation, and apoptosis. With TCDD treatment, there was also enrichment of AHR ChIP-Seq peaks, while the TCF21 enrichment decreased significantly. The SMC-specific Ahr knockout resulted in increased oxidative stress in SMC, increased lesion size and macrophage content, and loss of SMC lineage cells in the lesion cap when exposed to TCDD, consistent with a more vulnerable plaque phenotype. ConclusionDioxin adversely remodels atherosclerotic plaque by accelerating the SMC- phenotypic modulation, and increasing inflammation and oxidative stress resulting in increased macrophage recruitment and lesion size. Dioxin may adversely affect the SMC phenotype and disease state by affecting the TCF21 occupancy in the open chromatin regions. Furthermore, we observed that SMC-specific deletion of Ahr in mice resulted in worsening of dioxin mediated SMC modulation and atherosclerosis, suggesting that Ahr in SMC confers protection against dioxin by promoting a stable plaque phenotype and reducing dioxin induced oxidative stress. SummaryO_LIExposure to dioxin, an environmental pollutant present in tobacco smoke and air pollution, accelerates smooth muscle cell modulation, and atherosclerosis. C_LIO_LIDioxin exposure leads to inflammatory smooth muscle cell phenotype characterized by complement pathway activation and increased macrophage recruitment to plaque C_LIO_LIAryl-hydrocarbon receptor in SMC protects against oxidative stress, and promotes a stable plaque phenotype C_LI

molecular biology↗