Biology subjects

Xu, Y.

Publications and source records attributed to Xu, Y..

At least 973 records · Page 54Linked to original sources

bioRxiv2018

Autophagy Decreases Alveolar Epithelial Cell Injury by Suppressing the NF-κB Signaling Pathway and Regulating the Release of Inflammatory Mediators

To research the impact of autophagy on alveolar epithelial cell inflammation and its possible mechanism in early stages of hypoxia, we established a cell hypoxia-reoxygenation model and orthotopic left lung ischemia-reperfusion model. Rat alveolar epithelial cells stably expressing GFP-LC3 were treated with an autophagy inhibitor (3-methyladenine, 3-MA) or autophagy promoter (rapamycin), followed by hypoxia-reoxygenation treatment at 2, 4 and 6h in vitro. In vivo, twenty-four male Sprague-Dawley rats were randomly divided into four groups (model group: no blocking of hilum in the left lung; control group: blocking of hilum in the left lung for 1h with DMSO lavage; 3-MA group: blocking of hilum in the left lung for 1h with 100ml/kg of 3-MA (5mol/L) solution lavage; rapamycin group: blocking of hilum in the left lung for 1h with 100ml/kg of rapamycin (250nmol/L) solution lavage) to establish an orthotopic left lung ischemia model. This study demonstrated that rapamycin significantly suppressed the NF-{kappa}B signaling pathway, restrained the expression of pro-inflammatory factors. A contrary result was confirmed by 3-MA pretreatment. These findings indicate that autophagy reduces ischemia-reperfusion injury by repressing inflammatory signaling pathways in the early stage of hypoxia in vitro and in vivo. This could be a new protective method for lung ischemia-reperfusion injury.

cell biology↗

bioRxiv2018

U1 snRNP regulates chromatin retention of noncoding RNAs

Thousands of noncoding transcripts exist in mammalian genomes, and they preferentially localize to chromatin. Here, to identify cis-regulatory elements that control RNA-chromatin association, we developed a high-throughput method named RNA element for subcellular localization by sequencing (REL-seq). Coupling REL-seq with random mutagenesis (mutREL-seq), we discovered a key 7-nt U1 recognition motif in chromatin-enriched RNA elements. Reporter assays indicated a direct role for U1 snRNP recognition in regulating RNA-chromatin localization. Globally, U1 motifs and U1 binding are strongly enriched in long noncoding RNA (lncRNA) transcripts. Inhibition of U1 snRNA, and of U2 to a lesser degree, led to global reduction in chromatin association of hundreds of lncRNAs. For promoter- and enhancer-associated noncoding RNAs, U1 binds to their genomic neighborhoods, and their chromatin association depends on both U1 and U2 snRNAs. These findings reveal that U1 snRNP, perhaps together with the splicing machinery, acts widely to promote the chromatin association of noncoding transcripts.

molecular biology↗

bioRxiv2018

Detection of viral pathogens with multiplex Nanopore MinION sequencing: be careful with cross-talk

Metagenomic sequencing with the Oxford Nanopore MinION sequencer offers potential for point-of-care testing of infectious diseases in clinical settings. To improve cost-effectiveness, multiplexing of several, barcoded samples upon a single flow cell will be required during sequencing. We generated a unique sequencing dataset to assess the extent and source of cross barcode contamination caused by multiplex MinION sequencing. Sequencing libraries for three different viruses, including influenza A, dengue and chikungunya, were prepared separately and sequenced on individual flow cells. We also pooled the respective libraries and performed multiplex sequencing. We identified 0.056% of total reads in the multiplex sequencing data that were assigned to incorrect barcodes. Chimeric reads were the predominant source of this error. Our findings highlight the need for careful filtering of multiplex sequencing data before downstream analysis, and the trade-off between sensitivity and specificity that applies to the barcode demultiplexing methods.

bioinformatics↗

bioRxiv2018

Co-regulation of alternative splicing by hnRNPM and ESRP1 during EMT

The epithelial-mesenchymal transition (EMT) is a fundamental developmental process that is abnormally activated in cancer metastasis. Dynamic changes in alternative splicing occur during EMT. ESRP1 and hnRNPM are splicing regulators that promote an epithelial splicing program and a mesenchymal splicing program, respectively. The functional relationships between these splicing factors in the genome-scale remain elusive. Comparing alternative splicing targets of hnRNPM and ESRP1 revealed that they co-regulate a set of cassette exon events, with the majority showing discordant splicing regulation. hnRNPM discordantly regulated splicing events show a positive correlation with splicing during EMT while concordant splicing events do not, highlighting the antagonistic role of hnRNPM and ESRP1 during EMT. Motif enrichment analysis near co-regulated exons identifies guanine-uridine rich motifs downstream of hnRNPM-repressed and ESRP1-enhanced exons, supporting a model of competitive binding to these cis-elements to antagonize alternative splicing. The set of co-regulated exons are enriched in genes associated with cell-migration and cytoskeletal reorganization, which are pathways associated with EMT. Splicing levels of co-regulated exons are associated with breast cancer patient survival and correlate with gene sets involved in EMT and breast cancer subtypes. These data identify complex modes of interaction between hnRNPM and ESRP1 in regulation of splicing in disease-relevant contexts.

molecular biology↗

bioRxiv2018

Pathological Oxidation of PTPN12 Underlies ABL1 Phosphorylation in HLRCC

Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC) is an inherited cancer syndrome associated with a highly aggressive form of type 2 papillary renal cell carcinoma (PRCC). Germ line inactivating alterations in Fumarate Hydratase (FH) cause HLRCC, and result in elevated levels of reactive oxygen species (ROS). Recent work indicates that FH -/-PRCC cells have increased ABL1 activation, which promotes tumor growth, but how ABL1 is activated remained unclear. Oxidation can regulate protein-tyrosine phosphatase (PTP) catalytic activity; conceivably, ROS-catalyzed inactivation of an ABL-directed PTP might account for ABL1 activation in this malignancy. Previously, our group developed \"q-oxPTPome,\" a method that can globally monitor the oxidation of classical PTPs. We have now refined the q-oxPTPome approach, increasing its sensitivity by >10X. Applying q-oxPTPome to FH-deficient cell models shows that multiple PTPs are either highly oxidized (including PTPN12) or overexpressed. In general, highly oxidized PTPs were those that have relatively high sensitivity to exogenous H2O2. Most PTP oxidation in FH-deficient cells is reversible, although nearly 40% of PTPN13 is oxidized irreversibly to the sulfonic acid state. Using \"substrate-trapping mutants\", we mapped PTPs to their putative substrates, and found that only PTPN12 could target ABL1. Furthermore, knockdown experiments identify PTPN12 as the major ABL1 phosphatase in HLRCC. Overall, our results show that ROS-induced PTPN12 oxidation accounts for ABL1 phosphorylation in HLRCC-associated PRCC, reveal a novel mechanism for inactivating a tumor suppressor gene product, and establish a direct link between pathological PTP oxidation and neoplastic disease.

cancer biology↗

bioRxiv2018

Preclinical Study: Sunitinib-suppressed MiR-452-5p Facilitates Renal Cancer Cell Invasion and Metastasis Through Modulating SMAD4/SMAD7/EMT Signals

Although microRNAs (miRNAs) have been revealed as crucial modulators in tumor metastasis and target therapy, our understanding of their roles in metastatic renal cell carcinoma (mRCC) and Sunitinib treatment is limited. Here, We focused on 2 published microarray data to select out our anchored miRNA which was downregulated after Sunitinib treatment while upregulated in metastasis RCC tissues. Then we discovered that treating with Sunitinib, the targeted receptor tyrosine kinase inhibitor (TKI), inhibited renal cell migration and invasion via attenuating the expression of miR-452-5p. The novel identified miR-452-5p was upregulated and associated with poor prognosis in RCC. Preclinical studies using multiple RCC cells and xenografts model illustrated that miR-452-5p could promote RCC cell migration and invasion in vitro and in vivo. Mechanistically, P65 could directly bind to the miR-452-5p promoter and thus transcriptionally induce miR-452-5p expression, which led to post-transcriptionally abrogate SMAD4 expression, thus inhibition of its downstream signals including SMAD7 and EMT (Epithelial-Mesenchymal Transition) associated genes. Our study presented a road map for targeting this newly identified miR-452-5p and its SMAD4/SMAD7/EMT signals pathway, which imparted a new potential therapeutic strategy for mRCC treatment.

cancer biology↗

bioRxiv2018

Large-scale gene losses underlie the genome evolution of parasitic plant Cuscuta australis

Dodders (Cuscuta spp., Convolvulaceae) are globally distributed root- and leafless parasitic plants that parasitize a wide range of hosts. The physiology, ecology, and evolution of these obligate parasites are still poorly understood. A high-quality reference genome (size 266.74 Mb and contig N50 of 3.63 Mb) of Cuscuta australis was assembled. Our analyses reveal that Cuscuta experienced accelerated evolution, and Cuscuta and the convolvulaceous morning glory (Ipomoea) shared a common whole-genome triplication event before their divergence. Importantly, C. australis genome harbors only 19805 protein-coding genes, and 11.7% of the conserved orthologs in autotrophic plants are lost in C. australis. Many of these gene loss events likely result from the plants parasitic lifestyle and large changes in its body plan. Moreover, comparison of the gene expression patterns in Cuscuta prehaustoria/haustoria and various tissues of closely related autotrophic plants suggests that Cuscuta haustorium genes largely evolved from roots. The C. australis genome provides important resources for studying the evolution of parasitism, regressive evolution, and evo-devo in plant parasites.

genomics↗

bioRxiv2018

Down-regulated Long Noncoding RNA HOXA11-AS affects trophoblast cell proliferation and migration by regulating RND3 and HOXA7 expression in preeclampsia

The long noncoding RNA HOXA11-AS reveals abnormal expression in numerous human diseases. However, its function and biological mechanisms remain unclear in Preeclampsia (PE). In this study, we report that HOXA11-AS was significantly downregulated in preeclampsic placental tissues and could contribute to the occurrence and development of Preeclampsia. Silencing of HOXA11-AS expression could significantly suppress trophoblast cell growth and migration, whereas HOXA11-AS overexpression facilitated cell growth in HTR-8/SVneo, JEG3 and JAR cell lines. RNA-seq analysis also indicated that HOXA11-AS silencing preferentially regulated numerous genes associated with cell proliferation and cell migration. Mechanistic analyses showed that HOXA11-AS could recruit Ezh2 and Lsd1 protein, and regulate RND3 mRNA expression in nucleus. In cytoplasm, HOXA11-AS modulate HOXA7 expression by sponged miR-15b-5p, thus affecting trophoblast cell proliferation. Together, these resulting data confirm that aberrant expression of HOXA11-AS is involved in the occurrence and development of Preeclampsia, and may act as a prospective diagnosis and therapeutic target in PE.

molecular biology↗

bioRxiv2018

The interplay of immune components and ECM in oral cancer

We report that in Oral Squamous Cell Carcinoma (OSCC), extracellular matrix (ECM) plays a vitally important role in defining the characteristics of cancer vs. normal, as it is a compartment with significant enrichment of known OSCC biomarkers, and the number of genes constituting ECM are more prominently upregulated in OSCC than almost all the rest of the cancer types. This is probably due to the constant exposure of oral cavity to external stimuli, resulting in the ECM remodeling, which further is a key player in tumor invasion. While we showed ECM molecules alone could well distinguish oral cancer from normal tissue samples, a significant portion of these predictive ECM molecules, share the same transcriptional regulator, NFKB1, a master regulator of immune response. We further studied the level of involvement of the immune system in OSCC, and found that the immune composition in OSCC is distinctly different from the other cancer types. OSCC has a higher level of infiltration of adaptive immune cells, including B cell, T cell and neutrophil, compared with other cancer types, while a lower level of infiltration of innate immune, including macrophage and monocyte. Previous studies have revealed the roles of ECM and immune system in OSCC development, and our study showed that ECM plays a very prominent role in OSCC, subject to the complex microenvironment in oral cavity, particularly the immune system profile, and our association analysis revealed it is likely the interactions between ECM and immune cells that define the highly invasive property of OSCC.

bioinformatics↗

bioRxiv2018

ClusterMine: a Knowledge-integrated Clustering Approach based on Expression Profiles of Gene Sets

MotivationClustering analysis is essential for understanding complex biological data. In widely used methods such as hierarchical clustering (HC) and consensus clustering (CC), expression profiles of all genes are often used to assess similarity between samples for clustering. These methods output sample clusters, but are not able to provide information about which gene sets (functions) contribute most to the clustering. So interpretability of their results is limited. We hypothesized that integrating prior knowledge of annotated biological processes would not only achieve satisfying clustering performance but also, more importantly, enable potential biological interpretation of clusters.\n\nResultsHere we report ClusterMine, a novel approach that identifies clusters by assessing functional similarity between samples through integrating known annotated gene sets, e.g., in Gene Ontology. In addition to outputting cluster membership of each sample as conventional approaches do, it outputs gene sets that are most likely to contribute to the clustering, a feature facilitating biological interpretation. Using three cancer datasets, two single cell RNA-sequencing based cell differentiation datasets, one cell cycle dataset and two datasets of cells of different tissue origins, we found that ClusterMine achieved similar or better clustering performance and that top-scored gene sets prioritized by ClusterMine are biologically relevant.\n\nImplementation and availabilityClusterMine is implemented as an R package and is freely available at: www.genemine.org/clustermine.php\n\nContactjxwang@csu.edu.cn\n\nSupplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2017

Human iPSC-derived RPE and retinal organoids reveal impaired alternative splicing of genes involved in pre-mRNA splicing in PRPF31 autosomal dominant retinitis pigmentosa

Mutations in pre-mRNA processing factors (PRPFs) cause 40% of autosomal dominant retinitis pigmentosa (RP), but it is unclear why mutations in ubiquitously expressed PRPFs cause retinal disease. To understand the molecular basis of this phenotype, we have generated RP type 11 (PRPF31-mutated) patient-specific retinal organoids and retinal pigment epithelium (RPE) from induced pluripotent stem cells (iPSC). Impaired alternative splicing of genes encoding pre-mRNA splicing proteins occurred in patient-specific retinal cells and Prpf31+/- mouse retinae, but not fibroblasts and iPSCs, providing mechanistic insights into retinal-specific phenotypes of PRPFs. RPE was the most affected, characterised by loss of apical-basal polarity, reduced trans-epithelial resistance, phagocytic capacity, microvilli, and cilia length and incidence. Disrupted cilia morphology was observed in patient-derived-photoreceptors that displayed progressive features associated with degeneration and cell stress. In situ gene-editing of a pathogenic mutation rescued key structural and functional phenotypes in RPE and photoreceptors, providing proof-of-concept for future therapeutic strategies.\n\neTOCPRPF31 is a ubiquitously expressed pre-mRNA processing factor that when mutated causes autosomal dominant RP. Using a patient-specific iPSC approach, Buskin and Zhu et al. show that retinal-specific defects result from altered splicing of genes involved in the splicing process itself, leading to impaired splicing, loss of RPE polarity and diminished phagocytic ability as well as reduced cilia incidence and length in both photoreceptors and RPE.\n\nHighlightsO_LISuccessful generation of iPSC-derived RPE and photoreceptors from four RP type 11 patients\nC_LIO_LIRPE cells express the mutant PRPF31 protein and show the lowest expression of wildtype protein\nC_LIO_LIPRPF31 mutations result in altered splicing of genes involved in pre-mRNA splicing in RPE and retinal organoids\nC_LIO_LIPrpf31 haploinsufficiency results in altered splicing of genes involved in pre-mRNA splicing in mouse retina\nC_LIO_LIRPE cells display loss of polarity, reduced barrier function and phagocytosis\nC_LIO_LIPhotoreceptors display shorter and fewer cilia and degenerative features\nC_LIO_LIRPE cells display most abnormalities suggesting they might be the primary site of pathogenesis\nC_LIO_LIIn situ gene editing corrects the mutation and rescues key phenotypes\nC_LI

genetics↗

bioRxiv2017

quanTIseq: quantifying immune contexture of human tumors

The immune contexture has a prognostic value in several cancers and the study of its pharmacological modulation could identify drugs acting synergistically with immune checkpoint blockers. However, the quantification of the immune contexture is hampered by the lack of simple and efficient methods. We developed quanTIseq, a deconvolution method that quantifies the densities of ten immune cell types from bulk RNA sequencing data and tissue imaging data. We performed extensive validation using simulated data, flow cytometry data, and immunohistochemistry data from three cancer cohorts.\n\nAnalysis of 8,000 samples showed that the activation of the CXCR3/CXCL9 axis, rather than the mutational load is associated with cytotoxic T cell infiltration. We also show the prognostic value of deconvolution-based immunoscore and T cell/B cell score in several solid cancers. Finally, we used quanTIseq to show how kinase inhibitors modulate the immune contexture, and we suggest that it might have predictive value for immunotherapy.

bioinformatics↗

bioRxiv2017

A Rice Dual-localized Pentatricopeptide Repeat Protein is involved in Organellar RNA Editing with MORFs

Flowering plants engage in diverse RNA editing events in mitochondrion and chloroplast on post-transcriptional process. Although several PPRs and MORFs were identified as RNA editing factors, the underlying mechanism of PPRs and the cooperation among them are still obscure. Here, we identified a rice dual-localized PPR mutant Ospgl1. Loss-of-function of OsPGLl resulted in defect of chloroplast RNA editing at ndhD-878 and mitochondrial RNA editing at ccmFc-543, which can be restored via complementary validation. Despite the synonymous editing on ccmFc-543, loss of editing at ndhD-878 caused failure of conversion from serine to leucine, leading to the dysfunction of chloroplast and defective in photosynthetic complex, further studies demonstrated OsPGL1 directly bound to both two transcripts. The interaction between three MORFs (MORF2/8/9) and OsPGL1 were confirmed in vitro and in vivo, implied OsPGL1 functioned on RNA editing via an editosome. It also suggested MORFs assisted and contributed to the flexible PPR-RNA recognition model during RNA editing through the cooperation with PPRs. These results provide new insight into the relationship between RNA editing and plant development on chloroplast.\n\nHighlightWe firstly characterized a dual-localized PPR protein which is required for RNA editing in mitochondrion and chloroplast simultaneously. OsPGL1 binds to two distinguish target transcripts directly and cooperated with MORFs.

molecular biology↗

bioRxiv2017

BayCount: A Bayesian Decomposition Method for Inferring Tumor Heterogeneity using RNA-Seq Counts

Tumors are heterogeneous - a tumor sample usually consists of a set of subclones with distinct transcriptional profiles and potentially different degrees of aggressiveness and responses to drugs. Understanding tumor heterogeneity is therefore critical for precise cancer prognosis and treatment. In this paper, we introduce BayCount, a Bayesian decomposition method to infer tumor heterogeneity with highly over-dispersed RNA sequencing count data. Using negative binomial factor analysis, BayCount takes into account both the between-sample and gene-specific random effects on raw counts of sequencing reads mapped to each gene. For the posterior inference, we develop an efficient compound Poisson based blocked Gibbs sampler. Simulation studies show that BayCount is able to accurately estimate the subclonal inference, including number of subclones, the proportions of these subclones in each tumor sample, and the gene expression profiles in each subclone. For real-world data examples, we apply BayCount to The Cancer Genome Atlas lung cancer and kidney cancer RNA sequencing count data and obtain biologically interpretable results. Our method represents the first effort in characterizing tumor heterogeneity using RNA sequencing count data that simultaneously removes the need of normalizing the counts, achieves statistical robustness, and obtains biologically/clinically meaningful insights. The R package BayCount implementing our model and algorithm is available for download.

bioinformatics↗

bioRxiv2017

A Model Mechanism Based Explanation of an In Vitro-In Vivo Disconnect for Improving Extrapolation and Translation

An improved understanding of in vivo-to-in vitro hepatocyte changes is crucial to interpreting in vitro data correctly and further improving hepatocyte-based in vitro-to-in vivo extrapolations to human targets. We demonstrate using virtual experiments as a means to help untangle plausible causes of inaccurate extrapolations. We start with virtual mice that have biomimetic software livers. Earlier, using those mice, we discovered model mechanisms that enabled achieving quantitative validation targets while also providing plausible causal explanations for temporal characteristics of acetaminophen hepatotoxicity. We isolated virtual hepatocytes, created a virtual culture, and then conducted dose-response experiments in both culture and mice. We expected the two dose-response curves to be displaced. We were surprised that they crossed because it evidenced that simulated acetaminophen metabolism and toxicity are different for virtual culture and mouse contexts even though individual hepatocyte mechanisms were unchanged. Crossing dose-response curves is a virtual example of an in vivo-to-in vitro disconnect. We use detailed results of experiments to explain the disconnect. Individual hepatocytes contribute differently to system level phenomena. In liver, hepatocytes are exposed to acetaminophen sequentially. Relative production of the reactive acetaminophen metabolite is largest (smallest) in pericentral (periportal) hepatocytes. Because that sequential exposure is absent in culture, hepatocytes from different lobular locations do not respond the same. A virtual Culture-to-Mouse translation can stand as a scientifically challengeable theory explaining an in vitro-in vivo disconnect. It provides a framework to develop more reliable interpretations of in vitro observations, which then may be used to improve extrapolations.\n\nAbbreviations

pharmacology and toxicology↗

bioRxiv2017

TCGA-Assembler 2: Software Pipeline for Retrieval and Processing of TCGA/CPTAC Data

MotivationThe Cancer Genome Atlas (TCGA) program has produced huge amounts of cancer genomics data providing unprecedented opportunities for research. In 2014, we developed TCGA-Assembler (Zhu et al, 2014), a software pipeline for retrieval and processing of public TCGA data. In 2016, TCGA data were transferred from the TCGA data portal to the Genomic Data Commons (GDC), which is supported by a different set of data storage and retrieval mechanisms. In addition, new proteomics data of TCGA samples have been generated by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) program, which were not available for downloading through TCGA-Assembler. It is desirable to acquire and integrate data from both GDC and CPTAC.\n\nResultsWe develop TCGA-Assembler 2 (TA2) to automatically download and integrate data from GDC and CPTAC. We make substantial improvement on the functionality of TA2 to enhance user experience and software performance. TA2 together with its previous version have helped more than 2,000 researchers from 64 countries to access and utilize TCGA and CPTAC data in their research. Availability of TA2 will continue to allow existing and new users to conduct reproducible research based on TCGA and CPTAC data.\n\nAvailabilityhttp://www.compgenome.org/TCGA-Assembler/\n\nContactkoaeraser@gmail.com or zhuyitan@gmail.com

bioinformatics↗

bioRxiv2017

Two distinct DNA sequences recognized by transcription factors represent enthalpy and entropy optima

Most transcription factors (TFs) can bind to a population of sequences closely related to a single optimal site. However, some TFs can bind to two distinct sequences that represent two local optima in the Gibbs free energy of binding ({Delta}G). To determine the molecular mechanism behind this effect, we solved the structures of human HOXB13 and CDX2 bound to their two optimal DNA sequences, CAATAAA and TCGTAAA. Thermodynamic analyses by isothermal titration calorimetry revealed that both sites were bound with similar {Delta}G. However, the interaction with the CAA sequence was driven by change in enthalpy ({Delta}H), whereas the TCG site was bound with similar affinity due to smaller loss of entropy ({Delta}S). The common presence of at least two local optima is general to all macromolecular interactions, as {Delta}G depends on two partially independent variables {Delta}H and {Delta}S according to the central equation of thermodynamics, {Delta}G = {Delta}H - T{Delta}S.

biochemistry↗

bioRxiv2017

Enter the matrix: Interpreting unsupervised feature learning with matrix decomposition to discover hidden knowledge in high-throughput omics data

Omics data contains signal from the molecular, physical, and kinetic inter- and intra-cellular interactions that control biological systems. Matrix factorization techniques can reveal low-dimensional structure from high-dimensional data that reflect these interactions. These techniques can uncover new biological knowledge from diverse high-throughput omics data in topics ranging from pathway discovery to time course analysis. We review exemplary applications of matrix factorization for systems-level analyses. We discuss appropriate application of these methods, their limitations, and focus on analysis of results to facilitate optimal biological interpretation. The inference of biologically relevant features with matrix factorization enables discovery from high-throughput data beyond the limits of current biological knowledge--answering questions from high-dimensional data that we have not yet thought to ask.

systems biology↗