Biology subjects

Zhao, N.

Publications and source records attributed to Zhao, N..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Adenosine triggers astrocyte reactivity to drive the pathogenesis of sepsis-associated encephalopathy

Molecular pathways mediating systemic inflammation entering the brain parenchyma to induce sepsis-associated encephalopathy (SAE) remain elusive. Here, we report that in mice during the first 6 hours of peripheral lipopolysaccharide (LPS)-evoked systemic inflammation (6 hpi), the plasma level of adenosine quickly increased and enhanced the tone of central extracellular adenosine which then provoked neuroinflammation by triggering early astrocyte reactivity. Specific ablation of astrocytic A1 adenosine receptors (A1ARs) prevented this early reactivity and reduced the levels of inflammatory factors (e.g., CCL2, CCL5, and CXCL1) in astrocytes, thereby alleviating microglial activation, ameliorating blood-brain barrier disruption, neuronal dysfunction, and depression-like behaviour in the mice. Chemogenetic stimulation of Gi signaling in A1AR-deficent astrocytes at 2 and 4 hpi of LPS injection could restore neuroinflammation and depression-like behaviour, highlighting astrocytes rather than microglia as early drivers of neuroinflammation. Our results identify early astrocyte reactivity towards peripheral and central levels of adenosine as a novel pathway driving SAE.

neuroscience↗

bioRxiv2023

Disruption of Epithelium Integrity by Inflammation-Associated Fibroblasts through Prostaglandin Signaling

Inflammation-associated fibroblasts (IAFs) are associated with the progression and drug resistance of chronic inflammatory diseases such as inflammatory bowel disease (IBD), but their direct impact on epithelial function and architecture is unknown. In this study, we developed an in vitro model whereby human colon fibroblasts are induced to become IAFs by specific cytokines and recapitulate key features of IAFs in vivo. When co-cultured with patient-derived colon organoids (colonoids), IAFs induced rapid colonoid swelling and barrier disruption due to swelling and rupture of individual epithelial cells. Epithelial cells co-cultured with IAFs also exhibit increased DNA damage, mitotic errors, and proliferation arrest. These IAF-induced epithelial defects are mediated through a paracrine pathway involving prostaglandin E2 (PGE2) and the PGE2 receptor EP4, leading to PKA-dependent activation of the CFTR chloride channel. Importantly, EP4-specific chemical inhibitors effectively prevented colonoid swelling and restored normal proliferation and genome stability of IAF-exposed epithelial cells. These findings reveal a mechanism by which IAFs could promote and perpetuate IBD and suggest a potential treatment to mitigate inflammation-associated epithelial injury. TeaserInflammation-associated fibroblasts compromise colon epithelial barrier integrity and genome stability via PGE2-EP4 signaling.

cell biology↗

bioRxiv2023

Voluntary wheel running mitigates disease in an Orai1 gain-of-function mouse model of tubular aggregate myopathy

Tubular aggregate myopathy (TAM) is an inherited skeletal muscle disease associated with progressive muscle weakness, cramps, and myalgia. Tubular aggregates (TAs) are regular arrays of highly ordered and densely packed SR straight-tubes in muscle biopsies; the extensive presence of TAs represent a key histopathological hallmark of this disease in TAM patients. TAM is caused by gain-of-function mutations in proteins that coordinate store-operated Ca2+ entry (SOCE): STIM1 Ca2+ sensor proteins in the sarcoplasmic reticulum (SR) and Ca2+-permeable ORAI1 channels in the surface membrane. We have previously shown that voluntary wheel running (VWR) prevents formation of TAs in aging mice. Here, we assessed the therapeutic potential of endurance exercise (in the form of VWR) in mitigating the functional and structural alterations in a knock-in mouse model of TAM (Orai1G100S/+ or GS mice) based on a gain-of-function mutation in the ORAI1 pore. WT and GS mice were singly-housed for six months (from two to eight months of age) with either free-spinning or locked low profile wheels. Six months of VWR exercise significantly increased soleus peak tetanic specific force production, normalized FDB fiber Ca2+ store content, and markedly reduced TAs in EDL muscle from GS mice. Six months of VWR exercise normalized the expression of mitochondrial proteins found to be altered in soleus muscle of sedentary GS mice in conjunction with a signature of increased protein translation and biosynthetic processes. Parallel proteomic analyses of EDL muscles from sedentary WT and GS mice revealed changes in a tight network of pathways involved in formation of supramolecular complexes, which were also normalized following six months of VWR. In summary, sustained voluntary endurance exercise improved slow twitch muscle function, reduced the presence of TAs in fast twitch muscle, and normalized the muscle proteome of GS mice consistent with protective adaptions in proteostasis, mitochondrial structure/function, and formation of supramolecular complexes.

physiology↗

bioRxiv2023

Targeting EIF4A triggers an interferon response to synergize with chemotherapy and suppress triple-negative breast cancer

Protein synthesis is frequently dysregulated in cancer and selective inhibition of mRNA translation represents an attractive cancer therapy. Here, we show that therapeutically targeting the RNA helicase eIF4A by Zotatifin, the first-in-class eIF4A inhibitor, exerts pleiotropic effects on both tumor cells and the tumor immune microenvironment in a diverse cohort of syngeneic triple-negative breast cancer (TNBC) mouse models. Zotatifin not only suppresses tumor cell proliferation but also directly repolarizes macrophages towards an M1-like phenotype and inhibits neutrophil infiltration, which sensitizes tumors to immune checkpoint blockade. Mechanistic studies revealed that Zotatifin reprograms the tumor translational landscape, inhibits the translation of Sox4 and Fgfr1, and induces an interferon response uniformly across models. The induction of an interferon response is partially due to the inhibition of Sox4 translation by Zotatifin. A similar induction of interferon-stimulated genes was observed in breast cancer patient biopsies following Zotatifin treatment. Surprisingly, Zotatifin significantly synergizes with carboplatin to trigger DNA damage and an even heightened interferon response resulting in T cell-dependent tumor suppression. These studies identified a vulnerability of eIF4A in TNBC, potential pharmacodynamic biomarkers for Zotatifin, and provide a rationale for new combination regimens comprising Zotatifin and chemotherapy or immunotherapy as treatments for TNBC. One Sentence SummaryTargeting EIF4A sensitizes TNBC to immune therapy and chemotherapy by suppressing Sox4, inducing an interferon response, and reprograming the tumor immune microenvironment.

cancer biology↗

bioRxiv2023

Organ-specific prioritization and annotation of non-coding regulatory variants in the human genome

Identifying non-coding regulatory variants in the human genome remains a challenging task in genomics. Recently, we released the second version of our leading regulatory variant database, RegulomeDB. Building upon this comprehensive database, we developed a novel machine-learning architecture, TLand, which utilizes RegulomeDB-derived features to predict regulatory variants at the cell- or organ-specific level. In our holdout benchmarking, TLand consistently outperformed state-of-the-art models, demonstrating its ability to generalize to new cell lines or organs. We trained three types of organ-specific TLand models to overcome the common model bias toward high data availability cell lines or organs. These models accurately prioritize relevant organs for 2 million GWAS SNPs associated with GWAS traits. Moreover, our analysis of top-scoring variants in specific organ models showed a high enrichment of relevant GWAS traits. We expect that TLand and RegulomeDB will further advance our ability to understand human regulatory variants genome-wide.

bioinformatics↗

bioRxiv2023

Population genomic analyses reveal extensive genomic regions within selective sweeps associated with adaptation and demographic history of a wheat fungal pathogen

Plant pathogens can quickly evolve in response to the changing host and environment, resulting in destructive epidemics. The fungus Puccinia striiformis f. sp. tritici (Pst), causing wheat stripe rust disease worldwide, is one such pathogen. In the arms race between pathogens and hosts, changes in host populations exerted continuous selective forces on the dynamics of pathogens. However, the footprints of these selection forces and the demography of Pst remain poorly explored, limited our understanding the evolutionary processes that shape the spread and evolution of pathogens. In this study, we revealed several features of worldwide Pst populations through population genomic analyses. There might be limited gene flow between Pst populations from China and other countries. A slower rate of linkage disequilibrium decay was detected comparing to rust fungi with known sexual reproduction. Furthermore, we detected extensive hard and soft sweeps associated with Pst adaptation. Genes within the selective sweeps were enriched in secreted proteins and effectors and showed functions related to pathogenicity or virulence, temperature tolerance, and fungicide resistance implying that Chinese Pst populations suffered positive selection pressures from host and abiotic factors. Moreover, demographic history indicated Pst populations experienced strong bottlenecks at the beginning of the wheat domestication around 10,000 years ago and during modern agriculture around 100 years ago, suggesting that the crop domestication and breeding programs could continuously contribute to the decline of pathogen effective population sizes. Our results provided insights into the evolution of the Pst genome and highlighted the role of modern agriculture on pathogen demography. Author SummaryWheat stripe rust, as a pathogen of wheat, is capable of inducing significant yield reduction on a global scale. Traditional epidemiological investigations have elucidated the causative agent behind this disease, the wheat stripe rust pathogen, as an organism exhibiting swift adaptive evolution in response to its environment. However, the precise mechanisms underpinning its adaptive strategies and the ensuing alterations in population dynamics remain relatively unexplored. In our research, we have undertaken an analysis encompassing wheat stripe rust samples throughout the world. Employing population genomics methods, we have sought to discern the genomic footprints corresponding to the adaptive process within the pathogen. These genomic footprints have illuminated the operation of positive selection pressures caused by both the host plant and the ecological context. Concurrently, it have provided insights into the population size that the wheat stripe rust pathogen has undergone over millennia. Notably, its change in population size revealed the demographic history associated with wheat domestication.

microbiology↗

bioRxiv2023

Mesenchymal stem cells ameliorate inflammation in an experimental model of Crohn's disease via the mesentery

ObjectiveMesenchymal stem cells (MSCs) are novel therapeutics for treatment of Crohns disease. However, their mechanism of action is unclear, especially in disease-relevant chronic models of inflammation. Thus, we used SAMP-1/YitFc, a chronic and spontaneous murine model of small intestinal inflammation, to study the therapeutic effect and mechanism of human bone marrow-derived MSCs (hMSC). DesignhMSC immunosuppressive potential was evaluated through in vitro mixed lymphocyte reaction, ELISA, macrophage co-culture, and RT-qPCR. Therapeutic efficacy and mechanism in SAMP were studied by stereomicroscopy, histopathology, MRI radiomics, flow cytometry, RT-qPCR, small animal imaging, and single-cell RNA sequencing (Sc-RNAseq). ResultshMSC dose-dependently inhibited naive T lymphocyte proliferation in MLR via PGE2 secretion and reprogrammed macrophages to an anti-inflammatory phenotype. hMSC promoted mucosal healing and immunologic response early after administration in SAMP model of chronic small intestinal inflammation when live hMSCs are present (until day 9) and resulted in complete response characterized by mucosal, histological, immunologic, and radiological healing by day 28 when no live hMSCs are present. hMSC mediate their effect via modulation of T cells and macrophages in the mesentery and mesenteric lymph nodes (mLN). Sc-RNAseq confirmed the anti-inflammatory phenotype of macrophages and identified macrophage efferocytosis of apoptotic hMSCs as a mechanism of action that explains their long-term efficacy. ConclusionhMSCs result in healing and tissue regeneration in a chronic model of small intestinal inflammation. Despite being short-lived, exert long-term effects via macrophage reprogramming to an anti-inflammatory phenotype. Data Transparency StatementSingle-cell RNA transcriptome datasets are deposited in an online open access repository Figshare (DOI: https://doi.org/10.6084/m9.figshare.21453936.v1)

immunology↗

bioRxiv2023

MIDAS: a fast and simple simulator for realistic microbiome data

BackgroundAdvances in sequencing technology has led to the discovery of associations between the human microbiota and many diseases, conditions, and traits. With the increasing availability of microbiome data, many statistical methods have been developed for studying these associations. The growing number of newly developed methods highlights the need for simple, rapid, and reliable methods to simulate realistic microbiome data, which is essential for validating and evaluating the performance of these methods. However, generating realistic microbiome data is challenging due to the complex nature of microbiome data, which feature correlation between taxa, sparsity, overdispersion, and compositionality. Current methods for simulating microbiome data are deficient in their ability to capture these important features of microbiome data, or can require exorbitant computational time. MethodsWe develop MIDASim (MIcrobiome DAta Simulator), a fast and simple approach for simulating realistic microbiome data that reproduces the distributional and correlation structure of a template microbiome dataset. MIDASim is a two-step approach. The first step generates correlated binary indicators that represent the presence-absence status of all taxa, and the second step generates relative abundances and counts for the taxa that are considered to be present in step 1, utilizing a Gaussian copula to account for the taxon-taxon correlations. In the second step, MIDASim can operate in both a nonparametric and parametric mode. In the nonparametric mode, the Gaussian copula uses the empirical distribution of relative abundances for the marginal distributions. In the parametric mode, an inverse generalized gamma distribution is used in place of the empirical distribution. ResultsWe demonstrate improved performance of MIDASim relative to other existing methods using gut and vaginal data. MIDASim showed superior performance by PER-MANOVA and in terms of alpha diversity and beta dispersion in either parametric or nonparametric mode. We also show how MIDASim in parametric mode can be used to assess the performance of methods for finding differentially abundant taxa in a compositional model. ConclusionsMIDASim is easy to implement, flexible and suitable for most microbiome data simulation situations. MIDASim has three major advantages. First, MIDASim performs better in reproducing the distributional features of real data compared to other methods at both presence-absence level and relative-abundance level. MIDASim-simulated data are more similar to the template data than competing methods, as quantified using a variety of measures. Second, MIDASim makes few distributional assumptions for the relative abundances, and thus can easily accommodate complex distributional features in real data. Third, MIDASim is computationally efficient and can be used to simulate large microbiome datasets.

bioinformatics↗

bioRxiv2023

Explain-seq: an end-to-end pipeline from training to interpretation of sequence-based deep learning models

Interpreting predictive machine learning models to derive biological knowledge is the ultimate goal of developing models in the era of genomic data exploding. Recently, sequence-based deep learning models have greatly outperformed other machine learning models such as SVM in genome-wide prediction tasks. However, deep learning models, which are black-box models, are challenging to interpret their predictions. Here we represented an end-to-end computational pipeline, Explain-seq, to automate the process of developing and interpreting deep learning models in the context of genomics. Explain-seq takes input as genomic sequences and outputs predictive motifs derived from the model trained on sequences. We demonstrated Explain-seq with a public STARR-seq dataset of the A549 human lung cancer cell line released by ENCODE. We found our deep learning model outperformed gkm-SVM model in predicting A549 enhancer activities. By interpreting our well-performed model, we identified 47 TF motifs matched with known TF PWMs, including ZEB1, SP1, YY1, and INSM1. They are associated with epithelial-mesenchymal transition and lung cancer proliferation and metagenesis. In addition, there were motifs that were not matched in the JASPAR database and may be considered as de novo enhancer motifs in the A549 cell line. Availabilityhttps://github.com/nsamzhao/Explain-seq Contactapboyle@umich.edu Supplementary informationSupplementary data are available as attachment.

bioinformatics↗

bioRxiv2022

Deep RNA-seq of male and female murine sensory neuron subtypes after nerve injury

Dorsal root ganglia (DRG) neurons have been well described for their role in driving both acute and pain. Although nerve injury is known to cause transcriptional dysregulation, how this differs across neuronal subtypes and the impact of sex is unclear. Here, we study the deep transcriptional profiles of multiple murine DRG populations in early and late pain states while considering sex. We have exploited currently available transgenics to label numerous subpopulations for fluorescent activated cell sorting (FACS) and subsequent transcriptomic analysis. Using bulk tissue samples, we are able to circumvent the issues of low transcript coverage and drop-outs seen with single cell datasets. This increases our power to detect novel and even subtle changes in gene expression within neuronal subtypes and discuss sexual dimorphism at the neuronal subtype level. We have curated this resource into an accessible database for other researchers (https://livedataoxford.shinyapps.io/drg-directory/). We see both stereotyped and unique subtype signatures in injured states after nerve injury at both an early and late timepoint. While all populations contribute to a general injury signature, subtype enrichment changes can also be seen. Within populations, there is not a strong intersection of sex and injury, but previously unknown sex differences in naive states-particularly in A{beta}-RA + A{delta}-LTMRs - still contribute to differences in injured neurons.

neuroscience↗

bioRxiv2022

Profiling of chimeric RNAs in human retinal development with retinal organoids

Chimeric RNAs have been found in both cancer and healthy human cells. They have regulatory effects on human stem/progenitor cell differentiation, stemness maintenance and central nervous system (CNS) development. However, their physiological functions in the retinal development remain unknown. Based on the human embryonic stem cells (hESC)-derived retinal organoids (ROs) spanning from day 0 to day 120, we present the expression atlas of chimeric RNAs throughout the developing ROs. We confirmed the existence of some common chimeric RNAs and also discovered many novel chimeric RNAs during retinal development. We focused on CTNNBIP1-CLSTN1 (CTCL) whose downregulation causes precocious neuronal differentiation and a marked reduction of neural progenitors in human cerebral organoids. Our study found that CTCL also plays a key role in human retinogenesis, CTCL loss-of-function obstructed RO differentiation but prompted the retinal pigment epithelial (RPE) differentiation. Together, this work provides a landscape of chimeric RNAs and reveals evidence for their crucial roles in human retina development.

neuroscience↗

bioRxiv2022

SUMOylation regulates Lem2 function in centromere clustering and silencing

Regulation by the small modifier SUMO is heavily dependent on spatial control of enzymes that mediate the attachment and removal of SUMO on substrate proteins. Here we show that in fission yeast, delocalisation of the SUMO protease Ulp1 from the nuclear envelope results in centromeric defects that can be attributed to hyper-SUMOylation at the nuclear periphery. Unexpectedly, we find that while this localised hyper-SUMOylation impairs centromeric silencing, it can also enhance centromere clustering. Moreover, both effects are at least partially dependent on SUMOylation of the inner nuclear membrane protein Lem2. Lem2 has previously been implicated in diverse biological processes, including the promotion of both centromere clustering and silencing, but how these distinct activities are coordinated was unclear; our observations suggest a model whereby SUMOylation may serve as a regulatory switch, modulating Lem2 interactions with competing partner proteins to balance its roles in alternative pathways. Our findings also reveal a previously unappreciated role for SUMOylation in promoting centromere clustering.

cell biology↗

bioRxiv2022

Annotating and prioritizing human non-coding variants with RegulomeDB

Nearly 90% of the disease risk-associated variants identified from genome-wide association studies (GWAS) are in non-coding regions of the genome. The annotations obtained from analyzing functional genomics assays can provide additional information to pinpoint causal variants, which are often not the lead variants identified from association studies. However, the lack of available annotation tools limits the use of such data. To address the challenge, we have previously built the RegulomeDB database for prioritizing and annotating variants in non-coding regions1, which has been a highly utilized resource for the research community (Supplementary Fig. 1). RegulomeDB annotates a variant by intersecting its position with genomic intervals identified from functional genomic assays and computational approaches. It also incorporates those hits of a variant into a heuristic ranking score, representing its potential to be functional in regulatory elements. Here we present a newer version of the RegulomeDB web server, RegulomeDB v2.1 (http://regulomedb.org). We improve and boost annotation power by incorporating thousands of newly processed data from functional genomic assays in GRCh38 assembly, and now include probabilistic scores from the SURF algorithm that was the top performing non-coding variant predictor in CAGI 52. We also provide interactive charts and genome browser views to allow users an easy way to perform exploratory analyses in different tissue contexts.

bioinformatics↗

bioRxiv2022

Dynamics of Borrelia Burgdorferi Invasion and Intravasation in a Tissue Engineered Dermal Microvessel Model

Lyme disease is a tick-borne disease prevalent in North America, Europe, and Asia. Dissemination of vector-borne pathogens, such as Borrelia burgdorferi (Bb), results in infection of distant tissues and is the main contributor to poor outcomes. Despite the accumulated knowledge from epidemiological, in vitro, and in animal studies, the understanding of dissemination remains incomplete with several important knowledge gaps, especially related to invasion and intravasation at the site of a tick bite, which cannot be readily studied in animal models or humans. To elucidate the mechanistic details of these processes we developed a tissue-engineered human dermal microvessel model. Fluorescently-labeled Bb (B31 strain) were injected into the extracellular matrix (ECM) of the model to mimic tick inoculation. High resolution, confocal imaging was performed to visualize Bb migration in the ECM and intravasation into circulation. From analysis of migration paths we found no evidence to support adhesin-mediated interactions between Bb and components of the ECM or basement membrane, suggesting that collagen fibers serve as inert obstacles to migration. Transendothelial migration occurred at cell-cell junctions and was relatively fast, consistent with Bb swimming in ECM. In addition, we found that Bb alone can induce endothelium activation, resulting in increased immune cell adhesion but no changes in global or local permeability. Together these results provide new insight into the minimum requirements for dissemination of Bb at the site of a tick bite, and highlight how tissue-engineered models are complementary to animal models in visualizing dynamic processes associated with vector-borne pathogens. Significance StatementUsing a tissue-engineered human dermal microvessel model we reveal new insight into the invasion and intravasation of Borrelia burgdorferi (Bb), a causative agent of Lyme disease in North America, following a tick bite. These results show how tissue-engineered models enable imaging of dynamic processes that are challenging in animal models or human subjects.

bioengineering↗

bioRxiv2022

Genome-wide association study of brain biochemical phenotypes reveals distinct genetic architecture of Alzheimer's Disease related proteins

Alzheimers disease (AD) is neuropathologically characterized by amyloid-beta (A{beta}) plaques and neurofibrillary tangles. Main protein components of these hallmarks include A{beta}40, A{beta}42, tau, phospho-tau and APOE. With the exception of the APOE-{varepsilon}4 variant, genetic risk factors associated with brain biochemical measures of these proteins have yet to be characterized. We performed a genome-wide association study in brains of 441 AD patients for quantitative levels of these proteins collected from three distinct fractions reflecting soluble, membrane-bound and insoluble biochemical states. We identified 123 genome-wide significant associations at seven novel loci and the APOE locus. Genes and variants at these loci also associate with multiple AD- related measures, regulate gene expression, have cell-type specific enrichment, and roles in brain health and other neuropsychiatric diseases. Pathway analysis identified significant enrichment of shared and distinct biological pathways. Although all biochemical measures tested reflect proteins core to AD pathology, our results strongly suggest that each have unique genetic architecture and biological pathways that influence their specific biochemical states in the brain. Our novel approach of deep brain biochemical endophenotype GWAS has implications for pathophysiology of proteostasis in AD that can guide therapeutic discovery efforts focused on these proteins.

genetics↗

bioRxiv2022

Two Competing Guilds as a Core Microbiome Signature for Chronic Diseases

Summary ParagraphOver eons of co-evolution, the gut microbiota has become an essential organ for humans1,2. However, it is unclear what core members and their ecological organization ensures the stable provision of this organs essential health-relevant functions to the host. With high quality metagenome-assembled genomes as network nodes, here we identified two competing guilds3 of the most stably and highly connected bacteria that together correlate with a wide range of host health conditions. Genomes in these two guilds kept their ecological relationship unchanged despite experiencing profound abundance changes during a 3-month high fiber intervention and 1-year follow-up in patients with type 2 diabetes (T2DM). The genomes of one guild harbored more genes for plant polysaccharide degradation and butyrate production, while the other guild had more genes for virulence or antibiotic resistance. A Random Forest regression model showed that the abundance distributions of these genomes were associated with 41 out of 43 bio-clinical parameters in the study cohort. With these genomes as reference, Random Forest modeling successfully classified case and control of T2DM, atherosclerotic cardiovascular disease, liver cirrhosis, inflammatory bowel diseases, colorectal cancer, ankylosing spondylitis, schizophrenia, and Parkinsons disease in 12 independent metagenomic datasets from 1,816 participants across ethnicity and geography. This core microbiome signature may serve as a common target for health recovery.

microbiology↗

bioRxiv2021

Activation of transient receptor potential vanilloid 4 is involved in pressure overload-induced cardiac hypertrophy

Previous studies, including our own, have demonstrated that transient receptor potential vanilloid 4 (TRPV4) is expressed in hearts and implicated in cardiac remodeling and cardiac dysfunction. However, the effects of TRPV4 on pressure overload-induced cardiac hypertrophy remain unclear. In this study, we found that TRPV4 expression was significantly increased in mouse hypertrophic hearts, human failing hearts, and neurohormone-induced hypertrophic cardiomyocytes. Deletion of TRPV4 attenuated transverse aortic constriction (TAC)-induced cardiac hypertrophy, cardiac dysfunction, fibrosis, inflammation, and the activation of NF{kappa}B - NOD-like receptor pyrin domain-containing protein 3 (NLRP3) in mice. In vitro, TRPV4 inhibition decreased the neurohormone-induced cardiomyocyte hypertrophy and the increase of intracellular Ca2+ concentration. TRPV4 agonist triggered Ca2+ influx and evoked the phosphorylation of Ca2+/calmodulin-dependent protein kinase II (CaMKII) but these effects were abolished by removing extracellular Ca2+ or TRPV4 inhibition. More importantly, TAC or neurohormone stimulation-induced CaMKII phosphorylation was significantly blocked by TRPV4 inhibition. Finally, we showed that CaMKII inhibition significantly inhibited the phosphorylation of NF{kappa}B induced by TRPV4 activation. Our results suggest that TRPV4 activation contributed to pressure overload-induced cardiac hypertrophy. This effect was associated with upregulated Ca2+/ CaMKII mediated the activation of NF{kappa}B-NLRP3. Thus, TRPV4 may represent a potential therapeutic drug target for cardiac hypertrophy.

cell biology↗

bioRxiv2021

Kernel-based genetic association analysis for microbiome phenotypes identifies host genetic drivers of beta-diversity

Understanding human genetic influences on the gut microbiota helps elucidate the mechanisms by which genetics affects health outcomes. We propose a novel approach, the covariate-adjusted kernel RV (KRV) framework, to map genetic variants associated with microbiome beta-diversity, which focuses on overall shifts in the microbiota. The proposed KRV framework improves statistical power by capturing intrinsic structure within the genetic and microbiome data while reducing the multiple-testing burden. We apply the covariate-adjusted KRV test to the Hispanic Community Health Study/Study of Latinos in a genome-wide association analysis (first gene-level, then variant-level) for microbiome beta-diversity. We have identified an immunity-related gene, IL23R, reported in previous association studies and discovered 3 other novel genes, 2 of which are involved in immune functions or autoimmune disorders. Our findings highlight the value of the KRV as a powerful microbiome GWAS approach and support an important role of immunity-related genes in shaping the gut microbiome composition.

genomics↗