Genetic regulation of human brain proteome reveals proteins implicated in psychiatric disorders.

Psychiatric disorders are highly heritable yet polygenic, potentially involving hundreds of risk genes. Genome-wide association studies have identified hundreds of genomic susceptibility loci with susceptibility to psychiatric disorders; however, the contribution of these loci to the underlying psychopathology and etiology remains elusive. Here we generated deep human brain proteomics data by quantifying 11,608 proteins across 268 subjects using 11-plex tandem mass tag coupled with two-dimensional liquid chromatography-tandem mass spectrometry. Our analysis revealed 788 cis-acting protein quantitative trait loci associated with the expression of 883 proteins at a genome-wide false discovery rate <5%. In contrast to expression at the transcript level and complex diseases that are found to be mainly influenced by noncoding variants, we found protein expression level tends to be regulated by non-synonymous variants. We also provided evidence of 76 shared regulatory signals between gene expression and protein abundance. Mediation analysis revealed that for most (88%) of the colocalized genes, the expression levels of their corresponding proteins are regulated by cis-pQTLs via gene transcription. Using summary data-based Mendelian randomization analysis, we identified 4 proteins and 19 genes that are causally associated with schizophrenia. We further integrated multiple omics data with network analysis to prioritize candidate genes for schizophrenia risk loci. Collectively, our findings underscore the potential of proteome-wide linkage analysis in gaining mechanistic insights into the pathogenesis of psychiatric disorders.

Single-cell genomics and regulatory networks for 388 human brains.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Validation of Enhancer Regions in Primary Human Neural Progenitor Cells using Capture STARR-seq.

Genome-wide association studies (GWAS) and expression analyses implicate noncoding regulatory regions as harboring risk factors for psychiatric disease, but functional characterization of these regions remains limited. We performed capture STARR-sequencing of over 78,000 candidate regions to identify active enhancers in primary human neural progenitor cells (phNPCs). We selected candidate regions by integrating data from NPCs, prefrontal cortex, developmental timepoints, and GWAS. Over 8,000 regions demonstrated enhancer activity in the phNPCs, and we linked these regions to over 2,200 predicted target genes. These genes are involved in neuronal and psychiatric disease-associated pathways, including dopaminergic synapse, axon guidance, and schizophrenia. We functionally validated a subset of these enhancers using mutation STARR-sequencing and CRISPR deletions, demonstrating the effects of genetic variation on enhancer activity and enhancer deletion on gene expression. Overall, we identified thousands of highly active enhancers and functionally validated a subset of these enhancers, improving our understanding of regulatory networks underlying brain function and disease.

SLKB: synthetic lethality knowledge base.

Emerging CRISPR-Cas9 technology permits synthetic lethality (SL) screening of large number of gene pairs from gene combination double knockout (CDKO) experiments. However, the poor integration and annotation of CDKO SL data in current SL databases limit their utility, and diverse methods of calculating SL scores prohibit their comparison. To overcome these shortcomings, we have developed SL knowledge base (SLKB) that incorporates data of 11 CDKO experiments in 22 cell lines, 16,059 SL gene pairs and 264,424 non-SL gene pairs. Additionally, within SLKB, we have implemented five SL calculation methods: median score with and without background control normalization (Median-B/NB), sgRNA-derived score (sgRNA-B/NB), Horlbeck score, GEMINI score and MAGeCK score. The five scores have demonstrated a mere 1.21% overlap among their top 10% SL gene pairs, reflecting high diversity. Users can browse SL networks and assess the impact of scoring methods using Venn diagrams. The SL network generated from all data in SLKB shows a greater likelihood of SL gene pair connectivity with other SL gene pairs than non-SL pairs. Comparison of SL networks between two cell lines demonstrated greater likelihood to share SL hub genes than SL gene pairs. SLKB website and pipeline can be freely accessed at https://slkb.osubmi.org and https://slkb.docs.osubmi.org/, respectively.

Proteomic sequencing analysis in a rat model of atrial fibrosis caused by chronic intermittent hypoxia.

Background: Atrial fibrosis caused by long-term atrial fibrillation influences the outcomes of clinical treatment. An improved understanding of the mechanisms underlying atrial fibrillation may reveal new therapeutic targets. This study was conducted to analyze the changes in protein levels in the atrial tissue of a rat model of atrial fibrillation based on proteome sequencing. Methods: Sprague-Dawley rats were used to develop a model of atrial fibrillation induced by chronic intermittent hypoxia (CIH). Histopathological changes were detected using hematoxylin and eosin staining and Masson's staining, and immunohistochemistry and western blotting for the levels of fibrosis biomarkers. Atrial fibrosis tissue samples were also evaluated by proteome sequencing. Differentially expressed proteins (DEPs) between the CIH and control groups were evaluated in functional assay. The expression levels of several key proteins were validated using western blotting. Results: CIH resulted in atrial fibrosis and induced atrial fibrillation. We identified 145 DEPs between the CIH and control groups. These included Myh7, Myl2, Myl3, and Atpla3, which are involved in signaling pathways related to hypertrophic cardiomyopathy, glycerolipid metabolism, and cardiac muscle contraction. Western blotting revealed the upregulation of Myh7, Myl2, and Myl3 and the downregulation of Atpla3 in the CIH group compared with the control group. These results were consistent with the sequencing results. Conclusions: Myh7, Myl2, Myl3, and Atpla3 may play key roles in the progression of atrial fibrillation through their involvement in cardiovascular-disease-related signaling pathways.

Molecular Systematics and Taxonomic Analyses of Three New Wood-Inhabiting Fungi of Hyphoderma (Hyphodermataceae, Basidiomycota).

In this present study, three new wood-inhabiting fungal taxa, Hyphoderma niveomarginatum, H. sordidum and H. weishanense, are proposed. Hyphoderma niveomarginatum is characterized by the ceraceous basidiomata having a smooth, cracking hymenial surface and the presence of the moniliform cystidia and ellipsoid basidiospores (7-9 × 3.5-5 µm). Hyphoderma sordidum is characterized by its resupinate basidiomata with a smooth hymenial surface with the fimbriate margin, the presence of the tubular cystidia and ellipsoid basidiospores (3-4.5 × 2-3 µm). Hyphoderma weishanense differs in its membranous basidiomata with a slightly buff to buff hymenial surface and the presence of broadly ellipsoid basidiospores (4.5-8.5 × 4-7 µm). Sequences of ITS+nLSU+mt-SSU+RPB1+RPB2 genes were used for the phylogenetic analyses using three methods. The ITS+nLSU+mt-SSU+RPB1+RPB2 analysis of the genus Hyphoderma indicated that the 3 new species of Hyphoderma were nested into genus Hyphoderma, in which H. niveomarginatum formed a single group and then grouped with H. membranaceum and H. sinense; H. sordidum was a sister to H. nudicephalum; and H. weishanense closely grouped with H. crystallinum.

Osteosarcoma Multi-Omics Landscape and Subtypes.

Osteosarcoma (OS) is the most common primary bone malignancy that exhibits remarkable histologic diversity and genetic heterogeneity. The complex nature of osteosarcoma has confounded precise molecular categorization, prognosis, and prediction for this disease. In this study, we performed a comprehensive multiplatform analysis on 86 osteosarcoma tumors, including somatic copy-number alteration, gene expression and methylation, and identified three molecularly distinct and clinically relevant subtypes of osteosarcoma. The subgrouping criteria was validated on another cohort of osteosarcoma tumors. Previously unappreciated osteosarcoma-type-specific changes in specific genes' copy number, expression and methylation were revealed based on the subgrouping. The subgrouping and novel gene signatures provide insights into refining osteosarcoma therapy and relationships to other types of cancer.

The impact of common variants on gene expression in the human brain: from RNA to protein to schizophrenia risk.

Background: The impact of genetic variants on gene expression has been intensely studied at the transcription level, yielding in valuable insights into the association between genes and the risk of complex disorders, such as schizophrenia (SCZ). However, the downstream impact of these variants and the molecular mechanisms connecting transcription variation to disease risk are not well understood. Results: We quantitated ribosome occupancy in prefrontal cortex samples of the BrainGVEX cohort. Together with transcriptomics and proteomics data from the same cohort, we performed cis-Quantitative Trait Locus (QTL) mapping and identified 3,253 expression QTLs (eQTLs), 1,344 ribosome occupancy QTLs (rQTLs), and 657 protein QTLs (pQTLs) out of 7,458 genes quantitated in all three omics types from 185 samples. Of the eQTLs identified, only 34% have their effects propagated to the protein level. Further analysis on the effect size of prefrontal cortex eQTLs identified from an independent dataset showed clear post-transcriptional attenuation of eQTL effects. To investigate the biological relevance of the attenuated eQTLs, we identified 70 expression-specific QTLs (esQTLs), 51 ribosome-occupancy-specific QTLs (rsQTLs), and 107 protein-specific QTLs (psQTLs). Five of these omics-specific QTLs showed strong colocalization with SCZ GWAS signals, three of them are esQTLs. The limited number of GWAS colocalization discoveries from omics-specific QTLs and the apparent prevalence of eQTL attenuation prompted us to take a complementary approach to investigate the functional relevance of attenuated eQTLs. Using S-PrediXcan we identified 74 SCZ risk genes, 34% of which were novel, and 67% of these risk genes were replicated in a MR-Egger test. Notably, 52 out of 74 risk genes were identified using eQTL data and 70% of these SCZ-risk-gene-driving eQTLs show little to no evidence of driving corresponding variations at the protein level. Conclusion: The effect of eQTLs on gene expression in the prefrontal cortex is commonly attenuated post-transcriptionally. Many of the attenuated eQTLs still correlate with SCZ GWAS signal. Further investigation is needed to elucidate a mechanistic link between attenuated eQTLs and SCZ disease risk.

A novel alcohol steamed preparation from Gastrodia elata Blume: Pharmacological assessment of a functional food.

Rhizoma Gastrodia (Orchidaceae; Gastrodia elata Blume), the rhizome of Gastrodia elata Blume (GE), is traditionally used as both a medicinal and functional food, with proven efficacy in treating mental disorders. In traditional processing, GE is washed, steamed with water, dried, and sliced. In this study, a novel processing technology-alcohol steamed GE (AGE) was proposed as an alternative. Totally, 17 compounds were identified in fresh GE and AGE. Compared with fresh GE, the relative content of parishin A and parishin E decreased after alcohol steaming, whereas gastrodin (GAS), p-hydroxylbenzyl alcohol (HBA), Parishin B, and Parishin C were increased. Additionally, the pentobarbital-induced sleep mice model and Chronic Restraint Stress (CRS) model were applied to evaluate the pharmacological effects of fresh GE and steamed GE, and both fresh and steamed GE showed an intensive hypnotic and anti-anxiety effect. Furthermore, the anti-anxiety mechanism based on serum metabolic was investigated and the tryptophan metabolic pathway was considered the response to the anti-anxiety effect of GE. Although the optimization of the processing technology of AGE still needs to be further explored, the current results have provided new thoughts for the processing technology and clinical application of GE.

Investigation of underlying links between nitrogen transformation and microorganisms' network modularity in the novel static aerobic composting of dairy manure by "stepwise verification interaction analysis".

Conventional composting is a viable method treating agricultural solid waste, and microorganisms and nitrogen transformation are the two major components of this proces. Unfortunately, conventional composting is time-consuming and laborious, and limited efforts have been made to mitigate these problems. Herein, a novel static aerobic composting technology (NSACT) was developed and employed for the composting of cow manure and rice straw mixtures. During the composting process, physicochemical parameters were analyzed to evaluate the quality of compost products, and microbial abundance dynamics were determined using high-throughput sequencing technique. The results showed that NSACT achieved compost maturity within 17 days as the thermophilic stage (≥55 °C) lasted for 11 days. GI, pH, and C/N were 98.71 %, 8.38, and 19.67 in the top layer, 92.32 %, 8.24, and 22.38 in the middle layer, 102.08 %, 8.33, and 19.95 in the bottom layer. These observations indicate compost products maturated and met the requirements of current legislation. Compared with fungi, bacterial communities dominated NSACT composting system. Based on the stepwise verification interaction analysis (SVIA), the novel combination utilization of multiple statistical analyses (Spearman, RDA/CCA, Network modularity, and Path analyses), bacterial genera Norank Anaerolineaceae (-0.9279*), norank Gemmatimonadetes (1.1959*), norank Acidobacteria (0.6137**) and unclassified Proteobacteria (-0.7998*), and fungi genera Myriococcum thermophilum (-0.0445), unclassified Sordariales (-0.0828*), unclassified Lasiosphaeriaceae (-0.4174**), and Coprinopsis calospora (-0.3453*) were the identified key microbial taxa affecting NH4+-N, NO3--N, TKN and C/N transformation in the NSACT composting matrix respectively. This work revealed that NSACT successfully managed cow manure-rice straw wastes and significantly shorten the composting period. Interestingly, most microorganisms observed in this composting matrix acted in a synergistic manner, promoting nitrogen transformation.

At-Home COVID-19 Rapid Antigen Test Down to 0.03 pg mL-1 of Nucleocapsid Protein.

Rapid and ultra-sensitive detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical for early screening and management of COVID-19. Currently, the real-time reverse transcription polymerase chain reaction (rRT-PCR) is the primary laboratory method for diagnosing SARS-CoV-2. It is not suitable for at-home COVID-19 diagnostic test due to the long operating time, specific equipment, and professional procedures. Here an all-printed photonic crystal (PC) microarray with portable device for at-home COVID-19 rapid antigen test is reported. The fluorescence-enhanced effect of PC amplifies the fluorescence intensity of the labeled probe, achieving detection of nucleocapsid (N-) protein down to 0.03 pg mL-1 . A portable fluorescence intensity measurement instrument gives the result (negative or positive) by the color of the indicator within 5 s after inserting the reacted PC microarray test card. The N protein in inactivated virus samples (with cycle threshold values of 26.6-40.0) can be detected. The PC microarray provides a general and easy-to-use method for the timely monitoring and eventual control of the global coronavirus pandemic.

Fast and Sensitive Detection of Protein Markers Using an All-Printing Photonic Crystal Microarray via Fingertip Blood.

With the demand for point-of-care testing (POCT) in cardiovascular diseases, the detection of biomarkers in trace blood samples is of great significance in emergency medicine settings. Here, we demonstrated an all-printed photonic crystal microarray for POCT of protein markers (named "P4 microarray"). The paired nanobodies were printed as probes to target the soluble suppression of tumorigenicity 2 (sST2) as a certified cardiovascular protein marker. Benefiting from photonic crystal-enhanced fluorescence and integrated microarrays, quantitative detection of sST2 is 2 orders of magnitude lower than that of a traditional fluorescent immunoassay. The limit of detection is down to 10 pg/mL with the coefficient of variation being less than 8%. Detection of sST2 via fingertip blood is achieved in 10 min. Moreover, the P4 microarray after 180 days of storage at room temperature showed excellent stability for detection. This P4 microarray, as a convenient and reliable immunoassay for rapid and quantitative detection of protein markers in trace blood samples, has high sensitivity and strong storage stability, which hold great potential to advance cardiovascular precision medicine.

Ticagrelor Can Regulate the Ion Channel Characteristics of Superior Cervical Ganglion Neurons after Myocardial Infarction.

BACKGROUND: The superior cervical ganglion (SCG) plays a key role in cardiovascular diseases. The aim of this study was to determine the changes in the ion channel characteristics of the SCG following myocardial infarction (MI) and the role of pretreatment with the P2Y12 receptor antagonist ticagrelor (TIC). METHODS: A total of 18 male rabbits were randomly divided into a control group, MI group, and P2Y12 receptor antagonist (TIC) group (abbreviated as the TIC group). Rabbit MI was performed via two abdominal subcutaneous injections of 150 mg·kg-1·d-1 of isoproterenol (ISO) with an interval of 24 h. TIC pretreatment at 20 mg·kg-1·d-1 was administered via gavage for two consecutive days. The cardiac function of each group was evaluated with echocardiography. ADP receptor P2Y12 expressions in SCGs were determined using RT-PCR and immunofluorescence staining. Ion channel characteristics of SCG neurons were measured using a whole-cell patch clamp. Intracellular calcium concentrations for SCG neurons were measured using confocal microscopy. RESULTS: Cardiac function was reduced in the rabbits of the MI group, the sympathetic nerve activity of SCGs was increased, and the current amplitude of the neuron ion channel was increased. MI led to alterations in the activation and inactivation characteristics of INa channels accompanied by increased expression of P2Y12 in SCGs. Most of these abnormalities were prevented by TIC pretreatment in the TIC group. CONCLUSIONS: TIC pretreatment could attenuate the increase in P2Y12 expression in SCGs and the changes to the ion channel characteristics of SCG neurons after MI. This may be the mechanism underlying the cardiac protective effects of TIC.

Single-neuron whole genome sequencing identifies increased somatic mutation burden in Alzheimer's disease related genes.

Accumulation of somatic mutations in human neurons is associated with aging and neurodegeneration. To shed light on the somatic mutational burden in Alzheimer's disease (AD) neurons and get more insight into the role of somatic mutations in AD pathogenesis, we performed single-neuron whole genome sequencing to detect genome-wide somatic mutations (single nucleotide variants (SNVs) and Indels) in 96 single prefrontal cortex neurons from 8 AD patients and 8 elderly controls. We found that the mutational burden is ∼3000 somatic mutations per neuron genome in elderly subjects. AD patients have increased somatic mutation burden in AD-related annotation categories, including AD risk genes and differentially expressed genes in AD neurons. Mutational signature analysis showed somatic SNVs (sSNVs) primarily caused by aging and oxidative DNA damage processes but no significant difference was detected between AD and controls. Additionally, functional somatic mutations identified in AD patients showed significant enrichment in several AD-related pathways, including AD pathway, Notch-signaling pathway and Calcium-signaling pathway. These findings provide genetic insights into how somatic mutations may alter the function of single neurons and exert their potential roles in the pathogenesis of AD.

Synthetic lethal gene pairs: Experimental approaches and predictive models.

Synthetic lethality (SL) refers to a genetic interaction in which the simultaneous perturbation of two genes leads to cell or organism death, whereas viability is maintained when only one of the pair is altered. The experimental exploration of these pairs and predictive modeling in computational biology contribute to our understanding of cancer biology and the development of cancer therapies. We extensively reviewed experimental technologies, public data sources, and predictive models in the study of synthetic lethal gene pairs and herein detail biological assumptions, experimental data, statistical models, and computational schemes of various predictive models, speculate regarding their influence on individual sample- and population-based synthetic lethal interactions, discuss the pros and cons of existing SL data and models, and highlight potential research directions in SL discovery.

Bi-EB: Empirical Bayesian Biclustering for Multi-Omics Data Integration Pattern Identification among Species.

Although several biclustering algorithms have been studied, few are used for cross-pattern identification across species using multi-omics data mining. A fast empirical Bayesian biclustering (Bi-EB) algorithm is developed to detect the patterns shared from both integrated omics data and between species. The Bi-EB algorithm addresses the clinical critical translational question using the bioinformatics strategy, which addresses how modules of genotype variation associated with phenotype from cancer cell screening data can be identified and how these findings can be directly translated to a cancer patient subpopulation. Empirical Bayesian probabilistic interpretation and ratio strategy are proposed in Bi-EB for the first time to detect the pairwise regulation patterns among species and variations in multiple omics on a gene level, such as proteins and mRNA. An expectation-maximization (EM) optimal algorithm is used to extract the foreground co-current variations out of its background noise data by adjusting parameters with bicluster membership probability threshold Ac; and the bicluster average probability p. Three simulation experiments and two real biology mRNA and protein data analyses conducted on the well-known Cancer Genomics Atlas (TCGA) and The Cancer Cell Line Encyclopedia (CCLE) verify that the proposed Bi-EB algorithm can significantly improve the clustering recovery and relevance accuracy, outperforming the other seven biclustering methods-Cheng and Church (CC), xMOTIFs, BiMax, Plaid, Spectral, FABIA, and QUBIC-with a recovery score of 0.98 and a relevance score of 0.99. At the same time, the Bi-EB algorithm is used to determine shared the causality patterns of mRNA to the protein between patients and cancer cells in TCGA and CCLE breast cancer. The clinically well-known treatment target protein module estrogen receptor (ER), ER (p118), AR, BCL2, cyclin E1, and IGFBP2 are identified in accordance with their mRNA expression variations in the luminal-like subtype. Ten genes, including CCNB1, CDH1, KDR, RAB25, PRKCA, etc., found which can maintain the high accordance of mRNA-protein for both breast cancer patients and cell lines in basal-like subtypes for the first time. Bi-EB provides a useful biclustering analysis tool to discover the cross patterns hidden both in multiple data matrixes (omics) and species. The implementation of the Bi-EB method in the clinical setting will have a direct impact on administrating translational research based on the cancer cell screening guidance.

Subpathway Analysis of Transcriptome Profiles Reveals New Molecular Mechanisms of Acquired Chemotherapy Resistance in Breast Cancer.

Chemoresistance has been a major challenge in the treatment of patients with breast cancer. The diverse omics platforms and small sample sizes reported in the current studies of chemoresistance in breast cancer limit the consensus regarding the underlying molecular mechanisms of chemoresistance and the applicability of these study findings. Therefore, we built two transcriptome datasets for patients with chemotherapy-resistant breast cancers­one comprising paired transcriptome samples from 40 patients before and after chemotherapy and the second including unpaired samples from 690 patients before and 45 patients after chemotherapy. Subsequent conventional pathway analysis and new subpathway analysis using these cohorts uncovered 56 overlapping upregulated genes (false discovery rate [FDR], 0.018) and 36 downregulated genes (FDR, 0.016). Pathway analysis revealed the activation of several pathways in the chemotherapy-resistant tumors, including those of drug metabolism, MAPK, ErbB, calcium, cGMP-PKG, sphingolipid, and PI3K-Akt, as well as those activated by Cushing's syndrome, human papillomavirus (HPV) infection, and proteoglycans in cancers, and subpathway analysis identified the activation of several more, including fluid shear stress, Wnt, FoxO, ECM-receptor interaction, RAS signaling, Rap1, mTOR focal adhesion, and cellular senescence (FDR < 0.20). Among these pathways, those associated with Cushing's syndrome, HPV infection, proteoglycans in cancer, fluid shear stress, and focal adhesion have not yet been reported in breast cancer chemoresistance. Pathway and subpathway analysis of a subset of triple-negative breast cancers from the two cohorts revealed activation of the identical chemoresistance pathways.

CEDA: integrating gene expression data with CRISPR-pooled screen data identifies essential genes with higher expression.

MOTIVATION: Clustered regularly interspaced short palindromic repeats (CRISPR)-based genetic perturbation screen is a powerful tool to probe gene function. However, experimental noises, especially for the lowly expressed genes, need to be accounted for to maintain proper control of false positive rate. METHODS: We develop a statistical method, named CRISPR screen with Expression Data Analysis (CEDA), to integrate gene expression profiles and CRISPR screen data for identifying essential genes. CEDA stratifies genes based on expression level and adopts a three-component mixture model for the log-fold change of single-guide RNAs (sgRNAs). Empirical Bayesian prior and expectation-maximization algorithm are used for parameter estimation and false discovery rate inference. RESULTS: Taking advantage of gene expression data, CEDA identifies essential genes with higher expression. Compared to existing methods, CEDA shows comparable reliability but higher sensitivity in detecting essential genes with moderate sgRNA fold change. Therefore, using the same CRISPR data, CEDA generates an additional hit gene list. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Generation of dual-gRNA library for combinatorial CRISPR screening of synthetic lethal gene pairs.

Combinatorial CRISPR screening is useful for investigating synthetic lethality (SL) gene pairs. Here, we detail the steps for dual-gRNA library construction, with the introduction of two backbones, LentiGuide_DKO and LentiCRISPR_DKO. We describe steps for in vitro screening with 22Rv1-Cas9 and SaOS2-Cas9 cells followed by sequencing and data analysis. By introducing two backbones, we optimized the library construction process, facilitated standard pair-end sequencing, and provided options of screening on cells with or without modification of Cas9 expression.

Sodium-glucose cotransporter-2 inhibitor alleviated atrial remodeling in STZ-induced diabetic rats by targeting TLR4 pathway.

Purpose: The mechanism of sodium-glucose cotransporter-2 inhibitor (SGLT-2i) reducing the incidence of atrial fibrillation remains unclear. We hypothesize that sodium-glucose cotransporter-2 inhibitor alleviated atrial remodeling in STZ-induced diabetic rats by targeting TLR4 pathway. Methods: A total of 42 rats were randomly assigned into three groups: control group (CON group); diabetes group (DM group): diabetes mellitus rats were established by 65 mg/kg streptozotocin (STZ) intraperitoneal injection; and diabetes + dapagliflozin group (DM + DAPA group): diabetic rats were given DAPA gavage administration (DAPA 2mg/kg/d for 4 weeks by gavage administration), 14 rats in each group. Epicardial multiple-lead recording and intracardiac electrophysiology studies were performed to investigate the electrical remodeling in the heart and the atrial fibrillation inducibility in each group. Western blot analysis and real-time PCR were used to determine the protein and mRNA expression of toll-like receptor 4 (TLR4), interleukin receptor-associated kinase 1 (IRAK1), tumor necrosis factor receptor-associated factor 6 (TRAF6), nuclear factor-kappa B (NF-κB), and type I collagen (collagen I). Results: Compared with rats in CON group, rats in DM group showed marked myocardial fibrosis, ectopic pacing excitement, reduced conduction velocity, decreased cardiac function. TLR4/IRAK1/TRAF6/NF-κB, collagen I proteins expressions and incidence of atrial fibrillation (27.3%) were increased in DM group. Parts of these changes were reversed by treatment of DAPA. Incidence of atrial fibrillation was decreased in DM + DAPA group (2.8%). Conclusions: SGLT-2i dapagliflozin may prevent diabetic rats' atrial remodeling and reduce the inducibility of atrial fibrillation partly by targeting TLR4/IRAK1/TRAF6/NF-κB inflammatory pathway.