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Liu, W.

Publications and source records attributed to Liu, W..

At least 361 records · Page 20Linked to original sources

SRSF10 is essential for progenitor spermatogonia expansion by regulating alternative splicing

Alternative splicing expands the transcriptome and proteome complexity and plays essential roles in tissue development and human diseases. However, how alternative splicing regulates spermatogenesis remains largely unknown. Here, using germ cell-specific knockout mouse model, we demonstrated that the splicing factor Srsf10 is essential for spermatogenesis and male fertility. Depletion of Srsf10 in germ cells had little effect on the formation of SSCs but impeded the expansion of progenitor spermatogonia, leading to the failure of spermatogonia differentiation and meiosis initiation. This was further evidenced by the decreased expression of progenitor cell markers in bulk RNA-seq, and much less progenitor and differentiating spermatogonia in single-cell RNA-seq data. Furthermore, the expression of genes involved in cell cycle was abnormal in all subtypes of spermatogonia identified in single-cell RNA-seq data. Notably, using isolated spermatogonia, we found that Srsf10 depletion disturbed the alternative splicing of hundreds of genes, which were preferentially associated with cell cycle, mitotic cell cycle checkpoint and germ cell development, including Dazl, Kit, Ret, Sycp1, Nasp and Bora. These data suggest that SRSF10 is critical for the expansion of progenitor spermatogonia by regulating alternative splicing, expanding our understanding of the mechanism underlying spermatogenesis.

developmental biology↗

Temporal and spatial dynamics mapping reveals follicle development regulated by different stromal cell populations

Follicle development is a complex dynamic process. The follicles are encapsulated in the stroma, and once the follicle develops, the follicle moves from the cortex to the medulla and finally to the cortex to ovulate in the process of continuous growth. Many of these processes cannot be explained with the follicle alone. Through single-cell and spatial transcriptome sequencing at key time points of follicular development in mice after birth, we found that ovarian stromal cells are not only one of the main cell groups that make up the ovary but that their cell population and spatial location are also closely related to follicular development. Through analysis of cell communication, it was found that ovarian stromal cells were the main transmitters of intercellular communication, and many of the signals they sent were received by granulosa cells and oocytes to participate in follicle development. Ovarian stromal cells are not a homogeneous cell population. We combined single cell types with their spatial location information to divide ovarian stromal cells into four types, namely, structural stromal cells, perifollicular stromal cells, stromal progenitor cells, and steroidogenic stromal cells, each of which plays a different function in follicle development. Indepth studies of the different spatial locations and different types of stromal cells will expand our understanding of follicle development dynamics, leading to new targets and novel approaches for the treatment of ovarian-related diseases.

developmental biology↗

A high-performance genetically encoded fluorescent indicator for in vivo cAMP imaging

cAMP is a key second messenger that regulates diverse cellular functions including neural plasticity. However, the spatiotemporal dynamics of intracellular cAMP in intact organisms are largely unknown due to low sensitivity and/or brightness of current genetically encoded fluorescent cAMP indicators. Here, we report the development of the new circularly permuted GFP (cpGFP)-based cAMP indicator G-Flamp1, which exhibits a large fluorescence increase (a maximum {Delta}F/F0 of 1100% in HEK293T cells), relatively high brightness, appropriate affinity (a Kd of 2.17 {micro}M) and fast response kinetics (an association and dissociation half-time of 0.20 s and 0.087 s, respectively). Furthermore, the crystal structure of the cAMP-bound G-Flamp1 reveals one linker connecting the cAMP-binding domain to cpGFP adopts a distorted {beta}-strand conformation that may serve as a fluorescence modulation switch. We demonstrate that G-Flamp1 enables sensitive monitoring of endogenous cAMP signals in brain regions that are implicated in learning and motor control in living organisms such as fruit flies and mice.

molecular biology↗

Structural basis for receptor selectivity and inverse agonism in S1P5 receptors

The bioactive lysophospholipid sphingosine-1-phosphate (S1P) acts via five different subtypes of S1P receptors (S1PR) - S1P1-5. S1P5 is predominantly expressed in nervous and immune systems, regulating the egress of natural killer cells from lymph nodes and playing a role in immune and neurodegenerative disorders, as well as carcinogenesis. Several S1PR therapeutic drugs have been developed to treat these diseases; however, they lack receptor subtype selectivity, which leads to side effects. In this article, we describe a 2.2 [A] resolution room temperature crystal structure of the human S1P5 receptor in complex with a selective inverse agonist determined by serial femtosecond crystallography (SFX) at the Pohang Accelerator Laboratory X-Ray Free Electron Laser (PAL-XFEL) and analyze its structure-activity relationship data. The structure demonstrates a unique ligand-binding mode, involving an allosteric subpocket, which clarifies the receptor subtype selectivity and provides a template for structure-based drug design. Together with previously published S1PR structures in complex with antagonists and agonists, the new S1P5-inverse agonist structure sheds light on the activation mechanism and reveals structural determinants of the inverse agonism in the S1PR-family.

biophysics↗

The circ_0002538/miR-138-5p/PLLP axis regulates Schwann cell migration and myelination in diabetic peripheral neuropathy

Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes, but the underlying molecular pathogenesis remains unclear. Accumulating evidence indicates that circular RNAs (circRNAs) play vital roles in DPN, while their expressions and functions in Schwann cell (SC) are rarely reported. Here, we performed protein profiling and circRNA sequencing on the peripheral nerves of patients with or without DPN. A total of 265 differentially expressed proteins were identified in DPN by protein profiling, which mainly enrich in myelination according to Gene Ontology analysis. Further, 15637 circRNAs were identified by circRNA sequencing, of which 11 were verified to be dysregulated. Among them, circ_0002538 was found to be downregulated in DPN and chosen for further investigation. Functional experiments revealed that circ_0002538 overexpression promoted SC migration and relieved demyelination in DPN. Mechanistic studies revealed that circ_0002538 could promote PLLP expression by sponging miR-138-5p, while lack of circ_0002538 led to PLLP deficiency, which further suppressed SC migration and caused demyelination. The present research provided novel insights into the pathogenesis of DPN, in which the circ_0002538/miR-138-5p/PLLP axis was suppressed in SCs and hence caused demyelination. These findings expanded the role of circRNAs in DPN and provided potential therapeutic targets for DPN.

neuroscience↗

ABIOTIC STRESS GENE 1 mediates aroma volatiles accumulation by activating MdLOX1a in apple

Fruit aroma is an important organoleptic quality, which influences consumer preference and market competitiveness. Aroma compound synthesis pathways in plants have been widely identified of which the lipoxygenase pathway is crucial for fatty acid catabolism to form esters in apple. However, the regulatory mechanism of this pathway remains elusive. In this study, linear regression analysis and transgene verification revealed that the lipoxygenase MdLOX1a participates in ester biosynthesis. Yeast one-hybrid library screening indicated that a novel abiotic stress gene, MdASG1 (ABIOTIC STRESS GENE 1), was a positive regulator of the MdLOX1a promoter and ester production based on yeast one-hybrid and dual-luciferase assays, and correlation analysis among eight apple cultivars. Overexpression of MdASG1 in apple and tomato stimulated the lipoxygenase pathway and increased the fatty acid-derived volatile content, whereas the latter was decreased by MdASG1 silencing. Furthermore, MdASG1 overexpression enhanced the salt-stress tolerance of tomato and apple Orin calli accompanied by a higher content of fatty acid-derived volatiles compared with that of non-stressed transgenic tomato fruit. Collectively, these findings indicate that MdASG1 activates MdLOX1a expression and participates in the lipoxygenase pathway, subsequently increasing the accumulation of aroma compounds especially under moderate salt stress treatment. The results also provide insight into the regulation of aroma production, and the potential strategy of prudent development and utilization of saline-alkali land to produce high-quality fruit, thereby reducing pressure on arable land and ensuring national food security. One-sentence SummaryMdASG1 directly activates MdLOX1a expression to promote aroma volatiles accumulation especially under moderate salt stress.

molecular biology↗

A comprehensive comparison on cell type composition inference for spatial transcriptomics data

Spatial transcriptomic (ST) technologies allow researchers to examine high-quality RNA-sequencing data along with maintained two-dimensional positional information as well as a co-registered histology image. A popular use of ST omics data is to provide insights about tissue structure and spatially unique features. However, due to the technical nature unique to most ST data, the resolution varies from a diameter of 2-10m to 50-100m instead of single-cell resolution, which brings uncertainty into cell number and cell mixture within each ST spot. Motivated by the important role for spatial arrangement of cell types within a tissue in physiology and disease pathogenesis, several ST deconvolution methods have been developed and are being used to explore gene expression variation and identification of spatial domains. The aim of this work is to review state-of-the-art methods for ST deconvolution, while comparing their strengths and weaknesses. Specifically, we use four real datasets to examine the performance of eight methods across different tissues and technological platforms. Key PointsO_LICell mixture inference is a critical step in the analysis of spatial transcriptomics (ST) data to prevent downstream analysis suffering from confounding factors at the spot level. C_LIO_LIExisting ST deconvolution methods can be classified into three groups: probabilistic-based, non-negative matrix factorization and non-negative least squares based, and other deep learning framework-based methods. C_LIO_LIWe compared eight ST deconvolution methods by using two single cell level resolution datasets and two spot level resolution ST datasets. We provided practical guidelines for the choice of method under different scenarios as well as the optimal subsets of genes to use for each method. C_LI

genetics↗

A Model-Based Clustering via Mixture of Bayesian Hierarchical Models with Covariate Adjustment for Detecting Differentially Expressed Genes from Paired Design

The causes of many complex human diseases are still largely unknown. Genetics plays an important role in uncovering the molecular mechanisms of complex human diseases. A key step to characterize the genetics of a complex human disease is to unbiasedly identify disease-associated gene transcripts in whole-genome scale. Confounding factors could cause false positives. Paired design, such as measuring gene expression before and after treatment for the same subject, can reduce the effect of known confounding factors. Model-based clustering, such as mixtures of Bayesian hierarchical models, has been proposed to detect gene transcripts differentially expressed between paired samples. However, not all known confounding factors can be controlled in a paired/match design. To the best of our knowledge, no clustering methods have the capacity to adjust for the effects of covariates yet. In this article, we proposed a novel mixture of Bayesian hierarchical models with covariate adjustment in identifying differentially expressed transcripts using high-throughput whole-genome data from paired design. Both simulation study and real data analysis show the good performance of the proposed method

genomics↗

Reduced Hippocampal-Cortical Connectivity During Memory Suppression Predicts the Ability to Forget Unwanted Memories

The ability to suppress unwelcome memories is important for productivity and well-being. Successful memory suppression is associated with hippocampal deactivations and a concomitant disruption of this regions functionality. Much of the previous neuroimaging literature exploring such suppression-related hippocampal modulations has focused on the regions negative coupling with the prefrontal cortex. In contrast, task-based changes in functional connectivity between the hippocampus and other brain regions have remained relatively underexplored. Here, we utilize psychophysiological interactions and seed connectome-based predictive modeling (seed-CPM) to investigate the relationship between the hippocampus and the rest of the brain as 134 participants attempted to suppress unwanted memories during the Think/No-Think task. The results show that during retrieval suppression, the right hippocampus exhibited decreased functional connectivity with visual cortical areas (bilateral intracalcarine cortex, right cuneal cortex, left lingual gyrus, right supracalcarine cortex, right occipital pole), left nucleus accumbens and the brain-stem that predicted superior forgetting of unwanted memories on later memory tests. Validation tests verified that prediction performance was not an artifact of head motion or prediction method and that the negative features remained consistent across different brain parcellations. These findings suggest that systemic memory suppression involves more than the modulation of hippocampal activity--it alters functional connectivity patterns between the hippocampus and visual cortex, leading to successful forgetting.

neuroscience↗

6S RNA-dependent antibiotic susceptibility

Bacterial small RNAs (sRNAs) contribute to a variety of regulatory mechanisms that modulate wide ranging pathways, including metabolism, virulence, and antibiotic resistance. We investigated the involvement of sRNAs in rifampicin resistance in the opportunistic pathogen Staphylococcus aureus. Using a competition assay with an sRNA mutant library, we identified 6S RNA as being required for protection against low concentrations of rifampicin, an RNA polymerase (RNAP) inhibitor. This effect applied to rifabutin and fidaxomicin, two other RNAP-targeting antibiotics. 6S RNA is highly conserved in bacteria and its absence in two other major pathogens, Salmonella enterica and Clostridioides difficile, also impaired susceptibility to RNAP inhibitors. In S. aureus, 6S RNA is produced from an autonomous gene and accumulates in stationary phase. In contrast to what was reported in Escherichia coli, S. aureus 6S RNA does not appear to play a critical role in the transition from exponential to stationary phase, but affects {sigma}B-regulated expression in prolonged stationary phase. Nevertheless, its protective effect against rifampicin is independent of alternative sigma factor {sigma}B activity. Our results suggest that 6S RNA helps maintain RNAP-{sigma}A integrity in S. aureus, which could in turn help bacteria withstand low concentrations of RNAP inhibitors.

microbiology↗

PIMT suppresses endothelial activation and vascular inflammation through methylation of TRAF6

As a repair enzyme, protein L-isoaspartyl O-methyltransferase (PIMT) methylates and converts isoaspartyl residues (isoAsp) back to conventional forms to avoid protein damage during aging and stress responses. This study aims to investigate the pathological significance of PIMT in vascular inflammation. Herein, we show that PIMT is highly expressed in lung endothelial cells (ECs), and its reduction significantly exacerbates pulmonary inflammation in a murine model of acute lung injury (ALI). Mechanistically, we identify tumor necrosis factor receptor-associated factor 6 (TRAF6) as a substrate of PIMT. PIMT-mediated methylation of TRAF6 inhibits TRAF6 oligomerization, autoubiquitination, and LPS-induced NF-{kappa}B transactivation in ECs. Importantly, in addition to transcriptionally attenuating expression of adhesion molecules, PIMT post-translationally impedes site specific N-glycosylation of intercellular adhesion molecule-1 (ICAM-1), which leads to an increased protein degradation of ICAM-1 and a subsequent inhibition of EC interaction with immune cells during inflammatory process. Our results for the first time identify PIMT-mediated protein O-methylation as a key post-translational mechanism in controlling vascular inflammation, and suggest that PIMT may represent a novel therapeutic target in inflammatory vascular diseases.

physiology↗

Structural basis for Nirmatrelvir in vitro efficacy against the Omicron variant of SARS-CoV-2

The COVID-19 pandemic continues to be a public health threat with emerging variants of SARS-CoV-2. Nirmatrelvir (PF-07321332) is a reversible, covalent inhibitor targeting the main protease (Mpro) of SARS-CoV-2 and the active protease inhibitor in PAXLOVID (nirmatrelvir tablets and ritonavir tablets). We evaluated the in vitro catalytic activity and in vitro potency of nirmatrelvir against the main protease (Mpro) of prevalent variants of concern (VOC) or variants of interest (VOI): Alpha (, B.1.1.7), Beta ({beta}, B.1.351), Delta ({delta}, B1.617.2), Gamma ({gamma}, P.1), Lambda ({lambda}, B.1.1.1.37/C37), Omicron (o, B.1.1.529) as well as the original Washington or wildtype strain. These VOC/VOI carry prevalent mutations at varying frequencies in the Mpro specifically for: , {beta},{gamma} (K90R), {lambda} (G15S) and o (P132H). In vitro biochemical enzymatic assay characterization of the enzyme kinetics of the mutant Mpros demonstrate that they are catalytically comparable to wildtype. Nirmatrelvir has similar potency against each mutant Mpro including P132H that is observed in the Omicron variant with a Ki of 0.635 nM as compared to a Ki of 0.933nM for wildtype. The molecular basis for these observations were provided by solution-phase structural dynamics and structural determination of nirmatrelvir bound to the o, {lambda} and {beta} Mpro at 1.63 - 2.09 [A] resolution. These in vitro data suggest that PAXLOVID has the potential to maintain plasma concentrations of nirmatrelvir many-fold times higher than the amount required to stop the SARS-CoV-2 VOC/VOI, including Omicron, from replicating in cells (1).

biochemistry↗

TGFβ receptor inhibition unleashes interferon-β production by tumor-associated macrophages and enhances radiotherapy efficacy

BackgroundTransforming growth factor-beta (TGF{beta}) can limit the efficacy of cancer treatments, including radiotherapy (RT), by inducing an immunosuppressive tumor environment. The association of TGF{beta} with impaired T cell infiltration and antitumor immunity is known, but the mechanisms by which TGF{beta} participates in immune cell exclusion and limits the efficacy of antitumor therapies warrant further investigations. MethodsWe used the clinically relevant TGF{beta} receptor 2 (TGF{beta}R2)-neutralizing antibody MT1 and the small molecule TGF{beta}R1 inhibitor LY3200882 and evaluated their efficacy in combination with RT against murine orthotopic models of head and neck and lung cancer. ResultsWe demonstrated that TGF{beta} pathway inhibition strongly increased the efficacy of RT. TGF{beta}R2 antibody upregulated interferon beta (IFN{beta}) expression in tumor-associated macrophages (TAMs) within the irradiated tumors and favored T cell infiltration at the periphery and within the core of the tumor lesions. We highlighted that both the antitumor efficacy and inhibition of immune exclusion observed with the combination of MT1 and RT were dependent on type I interferon signaling. ConclusionsThese data shed new light on the role of TGF{beta} in limiting the efficacy of RT, identifying a novel mechanism involving the inhibition of macrophage-derived type I interferon production, and fostering the use of TGF{beta}R inhibition in combination with RT in therapeutic strategies for the management of head and neck and lung cancer.

cancer biology↗

Crystal Structure of Caskin1/CASK complex reveals the molecular basis of the binding specificity of CASK_CAMK domain and its binding partners

CASK is a unique scaffold protein in the synapse system. It links numerous proteins to the pre- or post-synaptic region and is critical to the homeostasis of synaptic vesicles. The N-terminus of CASK is a calcium/calmodulin-dependent protein kinase (CAMK) domain, which has diverse functions and interacts with downstream proteins to form a scaffold platform. Caskin1 is one of the brain-specific adaptor proteins of CASK. Previous studies showed that CASK_CAMK domain interacts with Caskin1 CID domain with relatively low affinity. In this study, we re-visit this interaction by remapping the interaction boundary and solving their complex structure. Based on the structure, we systematically compared the interactions between CASK_CAMK and other binding partners. Our results showed that CAMK domain occupies the CID peptide by using its C-lobe groove (between the 1 and 2) and there is a highly conserved signature motif ({zeta}-x-{psi}-W-{psi}-x-R) in the CID domain, where {zeta} is acidic side chain containing residues, x is any amino acid residue, {psi} is hydrophobic residues, W is for tryptophan, and R is arginine. These findings allowed us to identify several new potential cytoplasmic binding partners for CASK_CAMK.

biochemistry↗

Lipid nanoparticles delivering constitutively active STING mRNA as a novel anti-cancer therapeutic approach

Treating immunosuppressive tumors represents a major challenge in cancer therapies. Activation of STING signaling has shown remarkable potential to invigorate the immunologically cold tumor microenvironment (TME). However, we and others have shown that STING is silenced in many cancers, including pancreatic ductal adenocarcinoma (PDAC) and Merkel cell carcinoma (MCC), both of which are associated with an immune-dampened TME. In this study, we applied mRNA lipid nanoparticles (LNP) to deliver a permanently active gain-of-function STINGR284S mutant into PDAC and MCC cells. Expression of STINGR284S induces cytokines and chemokines crucial for promoting intratumoral infiltration of CD8+ T cells and, importantly, also leads to robust cancer cell death while avoiding T cell entry and toxicity. Our studies demonstrated that mRNA-LNP delivery of STINGR284S could be explored as a novel therapeutic tool to reactivate antitumor response in an array of STING-deficient cancers while overcoming the toxicity and limitations of conventional STING agonists.

bioengineering↗

Joint dimension reduction and clustering analysis for single-cell RNA-seq and spatial transcriptomics data

Dimension reduction and (spatial) clustering is usually performed sequentially; however, the low-dimensional embeddings estimated in the dimension-reduction step may not be relevant to the class labels inferred in the clustering step. We therefore developed a computation method, Dimension-Reduction Spatial-Clustering (DR-SC), that can simultaneously perform dimension reduction and (spatial) clustering within a unified framework. Joint analysis by DR-SC produces accurate (spatial) clustering results and ensures the effective extraction of biologically informative low-dimensional features. DR-SC is applicable to spatial clustering in spatial transcriptomics that characterizes the spatial organization of the tissue by segregating it into multiple tissue structures. Here, DR-SC relies on a latent hidden Markov random field model to encourage the spatial smoothness of the detected spatial cluster boundaries. Underlying DR-SC is an efficient expectation-maximization algorithm based on an iterative conditional mode. As such, DR-SC is scalable to large sample sizes and can optimize the spatial smoothness parameter in a data-driven manner. With comprehensive simulations and real data applications, we show that DR-SC outperforms existing clustering and spatial clustering methods: it extracts more biologically relevant features than conventional dimension reduction methods, improves clustering performance, and offers improved trajectory inference and visualization for downstream trajectory inference analyses.

genomics↗

Leveraging TOPMed Imputation Server and Constructing a Cohort-Specific Imputation Reference Panel to Enhance Genotype Imputation among Cystic Fibrosis Patients

Cystic fibrosis (CF) is a severe genetic disorder that can cause multiple comorbidities affecting the lungs, the pancreas, the luminal digestive system and beyond. In our previous genome-wide association studies (GWAS), we genotyped [~]8,000 CF samples using a mixture of different genotyping platforms. More recently, the Cystic Fibrosis Genome Project (CFGP) performed deep ([~]30x) whole genome sequencing (WGS) of 5,095 samples to better understand the genetic mechanisms underlying clinical heterogeneity among CF patients. For mixtures of GWAS array and WGS data, genotype imputation has proven effective in increasing effective sample size. Therefore, we first performed imputation for the [~]8,000 CF samples with GWAS array genotype using the TOPMed freeze 8 reference panel. Our results demonstrate that TOPMed can provide high-quality imputation for CF patients, boosting genomic coverage from [~]0.3 - 4.2 million genotyped markers to [~]11 - 43 million well-imputed markers, and significantly improving Polygenic Risk Score (PRS) prediction accuracy. Furthermore, we built a CF-specific CFGP reference panel based on WGS data of CF patients. We demonstrate that despite having [~]3% the sample size of TOPMed, our CFGP reference panel can still outperform TOPMed when imputing some CF disease-causing variants, likely due to allele and haplotype differences between CF patients and general populations. We anticipate our imputed data for 4,656 samples without WGS data will benefit our subsequent genetic association studies, and the CFGP reference panel built from CF WGS samples will benefit other investigators studying CF.

genetics↗

Isolation disrupts social interactions and destabilizes brain development in bumblebees

Social isolation, particularly in early life, leads to deleterious physiological and behavioral outcomes. Few studies, if any, have been able to capture the behavioral and neurogenomic consequences of early life social isolation together in a single social animal system. Here, we leverage new high-throughput tools to comprehensively investigate the impact of isolation in the bumblebee (Bombus impatiens) from behavioral, molecular, and neuroanatomical perspectives. We reared newly emerged bumblebees either in complete isolation, small groups, or in their natal colony, and then analyzed their behaviors while alone or paired with another bee. We find that when alone, individuals of each rearing condition show distinct behavioral signatures. When paired with a conspecific, bees reared in small groups or in the natal colony express similar behavioral profiles. Isolated bees, however, showed increased social interactions. To identify the neurobiological correlates of these differences, we quantified brain gene expression and measured the volumes of key brain regions for a subset of individuals from each rearing condition. Overall, we find that isolation increases social interactions and disrupts gene expression and brain development. Limited social experience in small groups is sufficient to preserve typical patterns of brain development and social behavior.

animal behavior and cognition↗