Biology subjects

Zeng, J.

Publications and source records attributed to Zeng, J..

At least 145 records · Page 8Linked to original sources

bioRxiv2020

Prolonged inhibitory effect of repeated period tibial nerve stimulation on the micturition reflex in the rat

BackgroundThe aims of this study was determine if stimulation of tibial nerve afferents could induce a prolonged modulation of the micturition reflex in the rats. MethodsFifteen female Sprague Dawley rats (250-350 g) were fully decorticated and paralysed for the study. Tibial nerve stimulation (TNS) was delivered by inserting two pairs of needle electrodes close to the nerves at the level of the medial malleolus. Constant flow cystometries (0.07 ml/min) at about 10 min interval were performed and the micturition threshold volume (MTV) was recorded and used as the dependent variable. After 4 - 5 stable control recordings, the tibial nerves of both sides were stimulated continuously for 5 min at 10 Hz, 3 times threshold for -motor axons. Six times of same stimulation were applied repeatedly with an interval of 5 min between the stimulations. The mean MTV was compiled from several cystometries in each half hour before the TNS and during, after 6 periods TNS. ResultsDuring the experiment, all the animals survived in a good condition with reasonably stable micturition reflexes, a significant increase in MTV was revealed after TNS. The best effect (mean 178%) occurred during the first 30 min after 6 periods of stimulation. This clear threshold increase remained for at least 5 h. ConclusionsA prolonged increase in MTV was demonstrated by a short periods of TNS repeatedly. This post stimulation modulatory effects of micturition reflex would provide a theoretical explanation for the clinical beneficial effect of TNS in patients with overactive bladder (OAB).

neuroscience↗

bioRxiv2020

Transcription terminator-mediated enhancement in transgene expression in maize: preponderance of the AUGAAU motif overlapping with poly(A) signals

The selection of transcription terminators (TTs) for pairing with high expressing constitutive promoters in chimeric constructs is crucial to deliver optimal transgene expression in plants. In this study, the use of the native combinations of four polyubiquitin gene promoters and corresponding TTs resulted in up to >3-fold increase in transgene expression in maize. Of the eight polyubiquitin promoter and TT regulatory elements utilized, seven were novel and identified from the polyubiquitin genes of Brachypodium distachyon, Setaria italica, and Zea mays. Furthermore, gene expression driven by the Cassava mosaic virus promoter was studied by pairing the promoter with distinct TTs derived from the high expressing genes of Arabidopsis. Of the three TTs studied, the polyubiquitin10 gene TT produced the highest transgene expression in maize. Polyadenylation patterns and mRNA abundance from eight distinct TTs were analyzed using 3-RACE and next-generation sequencing. The results exhibited one to three unique polyadenylation sites in the TTs. The poly(A) site patterns for the StPinII TT were consistent when the same TT was deployed in chimeric constructs irrespective of the reporter gene and promoter used. Distal to the poly(A) sites, putative polyadenylation signals were identified in the near-upstream regions of the TTs based on previously reported mutagenesis and bioinformatics studies in rice and Arabidopsis. The putative polyadenylation signals were 9 to 11 nucleotides in length. Six of the eight TTs contained the putative polyadenylation signals that were overlaps of either canonical AAUAAA or AAUAAA-like polyadenylation signals and AUGAAU, a top-ranking-hexamer of rice and Arabidopsis gene near-upstream regions. Three of the polyubiquitin gene TTs contained the identical 9-nucleotide overlap, AUGAAUAAG, underscoring the functional significance of such overlaps in mRNA 3 end processing. In addition to identifying new combinations of regulatory elements for high constitutive trait gene expression in maize, this study demonstrated the importance of TTs for optimizing gene expression in plants. Learning from this study could be applied to other dicotyledonous and monocotyledonous plant species for transgene expression.

plant biology↗

bioRxiv2020

Effect of storage conditions on peripheral leukocytes transcriptome

IntroductionPeripheral blood leukocytes are essential components of the innate and adaptive immune responses. Their transcriptome reflects an individuals physiological and pathological state, consequently bulk and single-cell RNA sequencing have been used to assess health and disease. As RNA is dynamic and could be affected by ex vivo conditions before RNA stabilization, we have assessed the influence of temporary storage on the transcriptome. MethodsWe collected peripheral blood from six healthy donors and processed it immediately or stored it either at 4{square} or room temperature (RT, 18-22{square}) for 2h, 6h and 24h. Total cellular RNA was extracted from leukocytes after red blood cells lysis and the transcriptome analyzed using RNA sequencing. ResultsWe identified 152 up-regulated and 12 down-regulated coding genes in samples stored at 4{square} for 24h with most of the up-regulated genes related to nucleosome assembly. More coding genes changed expression at RT, with 1218 increased and 1480 decreased. The increased genes were particularly related to mRNA processing and apoptosis, while the decreased genes were associated with neutrophil activation and cytokine production, implying a reduced proportion of neutrophils, which was confirmed by leukocyte subsets analysis. Most house-keeping genes changed expression during storage, but genes such as TUBB and C1orf43 were relatively stable and could serve as reference genes. ConclusionTemporary storage conditions profoundly affect leukocyte gene expression profiles and change leukocyte subset proportions. Blood samples stored at 4{square} for 6h largely maintain their original transcriptome.

molecular biology↗

bioRxiv2020

Microvascular Injury in Mild Traumatic Brain Injury Accelerates Alzheimer-like Pathogenesis in Mice

IntroductionTraumatic brain injury (TBI) is considered as the most robust environmental risk factor for Alzheimers disease (AD). Besides direct neuronal injury and neuroinflammation, vascular impairment is also a hallmark event of the pathological cascade after TBI. However, the vascular connection between TBI and subsequent AD pathogenesis remains underexplored. MethodsWe established a closed-head mild TBI (mTBI) model in mice with controlled cortical impact, and examined the time courses of microvascular injury, blood-brain barrier (BBB) dysfunction, gliosis and motor function impairment in wild type C57BL/6 mice. We also determined the brain clearance of {beta}-amyloid, as well as amyloid pathology and cognitive functions after mTBI in the 5xFAD mouse model of AD. ResultsmTBI induced microvascular injury with BBB breakdown, pericyte loss and cerebral blood flow reduction in mice, which preceded gliosis. mTBI also impaired brain amyloid clearance via the vascular pathways. More importantly, mTBI accelerated amyloid pathology and cognitive impairment in the 5xFAD mice. DiscussionOur data demonstrated that microvascular injury plays a key role in the pathogenesis of AD after mTBI. Therefore, restoring vascular functions might be beneficial for patients with mTBI, and potentially reduce the risk of developing AD.

neuroscience↗

bioRxiv2020

New and improved GRAB fluorescent sensors for monitoring dopaminergic activity in vivo

The monoamine neuromodulator dopamine (DA) plays a critical role in the brain, and the ability to directly measure dopaminergic activity is essential for understanding its physiological functions. We therefore developed the first red fluorescent GPCR-activation-based DA (GRABDA) sensors and optimized versions of green fluorescent GRABDA sensors following our previous studies. In response to extracellular DA, both the red and green GRABDA sensors have a large increase in fluorescence ({Delta}F/F0 values of 150% and 340%, respectively), with subcellular resolution, subsecond kinetics, and nanomolar to submicromolar affinity. Moreover, both the red and green GRABDA sensors readily resolve evoked DA release in mouse brain slices, detect compartmental DA release in live flies with single-cell resolution, and report optogenetically elicited nigrostriatal DA release as well as mesoaccumbens dopaminergic activity during sexual behavior in freely behaving mice. Importantly, co-expressing red GRABDA with either green GRABDA or the calcium indicator GCaMP6s provides a robust tool for simultaneously tracking neuronal activity and dopaminergic signaling in distinct circuits in vivo.

neuroscience↗

bioRxiv2020

Identification of key candidate genes and pathways in axial Spondyloarthritis through integrated bioinformatics analysis

BackgroundRadiographic axial Spondyloarthritis (r-axSpA) is the prototypic form of seronegative spondyloarthritis (SpA). In the present study, we evaluated the key genes related with r-axSpA, and then elucidated the possible molecular mechanisms of r-axSpA. Material/MethodsThe gene expression GSE13782 was downloaded from the GEO database contained five proteoglycan-induced spondylitis mice and three naive controls. The differentially expressed genes (DEGs) were identified with the Bioconductor affy package in R. Gene Ontology (GO) enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were built with the DAVID program followed by construction of a protein-protein interaction (PPI) network performed with Cytoscape. WebGestalt was performed to construct transcriptional regulatory network and microRNAs-target regulatory networks. RT-PCR and immunohistochemical staining were performed to testify the expression of hub genes, transcription factors (TFs) and microRNAs. ResultsA total of 230 DEGs were identified. PPI networks were constructed by mapping DEGs into STRING, in which 20 hub proteins were identified. KEGG pathway analyses revealed that the chemokine, NOD-like receptor, IL-17, and TNF signalling pathways were altered. GO analyses revealed that DEGs were extensively involved in the regulation of cytokine production, the immune response, the external side of the plasma membrane, and G-protein coupled chemoattractant receptor activity. The results of RT-PCR and immunohistochemical staining demonstrated that the expression of DEGs, TFs and microRNAs in our experiment were basically consistent with the predictions. ConclusionsThe results of this study offer insight into the pathomechanisms of r-axSpA and provide potential research directions.

molecular biology↗

bioRxiv2020

A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

The global spread of SARS-CoV-2 requires an urgent need to find effective therapeutics for the treatment of COVID-19. We developed a data-driven drug repositioning framework, which applies both machine learning and statistical analysis approaches to systematically integrate and mine large-scale knowledge graph, literature and transcriptome data to discover the potential drug candidates against SARS-CoV-2. The retrospective study using the past SARS-CoV and MERS-CoV data demonstrated that our machine learning based method can successfully predict effective drug candidates against a specific coronavirus. Our in silico screening followed by wet-lab validation indicated that a poly-ADP-ribose polymerase 1 (PARP1) inhibitor, CVL218, currently in Phase I clinical trial, may be repurposed to treat COVID-19. Our in vitro assays revealed that CVL218 can exhibit effective inhibitory activity against SARS-CoV-2 replication without obvious cytopathic effect. In addition, we showed that CVL218 is able to suppress the CpG-induced IL-6 production in peripheral blood mononuclear cells, suggesting that it may also have anti-inflammatory effect that is highly relevant to the prevention immunopathology induced by SARS-CoV-2 infection. Further pharmacokinetic and toxicokinetic evaluation in rats and monkeys showed a high concentration of CVL218 in lung and observed no apparent signs of toxicity, indicating the appealing potential of this drug for the treatment of the pneumonia caused by SARS-CoV-2 infection. Moreover, molecular docking simulation suggested that CVL218 may bind to the N-terminal domain of nucleocapsid (N) protein of SARS-CoV-2, providing a possible model to explain its antiviral action. We also proposed several possible mechanisms to explain the antiviral activities of PARP1 inhibitors against SARS-CoV-2, based on the data present in this study and previous evidences reported in the literature. In summary, the PARP1 inhibitor CVL218 discovered by our data-driven drug repositioning framework can serve as a potential therapeutic agent for the treatment of COVID-19.

systems biology↗

bioRxiv2020

A genetically encoded GRAB sensor for measuring serotonin dynamics in vivo

Serotonin (5-HT) is a phylogenetically conserved monoamine neurotransmitter modulating a variety of processes in the brain. To directly visualize the dynamics of 5-HT, we developed a genetically encoded GPCR-Activation-Based 5-HT (GRAB5-HT) sensor with high sensitivity, selectivity, and spatiotemporal resolution. GRAB5-HT, detected 5-HT release in multiple physiological and pathological conditions in both flies and mice, and thus provides new insights into the dynamics and mechanisms of 5-HT signaling.

neuroscience↗

bioRxiv2020

Crowdsourced mapping of unexplored target space of kinase inhibitors

Despite decades of intensive search for compounds that modulate the activity of particular targets, there are currently small-molecules available only for a small proportion of the human proteome. Effective approaches are therefore required to map the massive space of unexplored compound-target interactions for novel and potent activities. Here, we carried out a crowdsourced benchmarking of predictive models for kinase inhibitor potencies across multiple kinase families using unpublished bioactivity data. The top-performing predictions were based on kernel learning, gradient boosting and deep learning, and their ensemble resulted in predictive accuracy exceeding that of kinase activity assays. We then made new experiments based on the model predictions, which further improved the accuracy of experimental mapping efforts and identified unexpected potencies even for under-studied kinases. The open-source algorithms together with the novel bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking new prediction algorithms and for extending the druggable kinome.

biochemistry↗

bioRxiv2019

MONN: a Multi-Objective Neural Network for Predicting Pairwise Non-Covalent Interactions and Binding Affinities between Compounds and Proteins

Computational approaches for inferring the mechanisms of compound-protein interactions (CPIs) can greatly facilitate drug development. Recently, although a number of deep learning based methods have been proposed to predict binding affinities and attempt to capture local interaction sites in compounds and proteins through neural attentions, they still lack a systematic evaluation on the interpretability of the identified local features. In addition, in these previous approaches, the exact matchings between interaction sites from compounds and proteins, which are generally important for understanding drug mechanisms of action, still remain unknown. Here, we compiled the first benchmark dataset containing the inter-molecular non-covalent interactions for more than 10,000 compound-protein pairs, and used it to systematically evaluate the interpretability of neural attentions in existing prediction models. We developed a multi-objective neural network, called MONN, to predict both non-covalent interactions and binding affinity for a given compound-protein pair. MONN uses convolution neural networks on molecular graphs of compounds and primary sequences of proteins to effectively capture the intrinsic features from both inputs, and also takes advantage of the predicted non-covalent interactions to further boost the accuracy of binding affinity prediction. Comprehensive evaluation demonstrated that while the previous neural attention based approaches fail to exhibit satisfactory interpretability results without extra supervision, MONN can successfully predict non-covalent interactions on our benchmark dataset as well as another independent dataset derived from the Protein Data Bank (PDB). Moreover, MONN can outperform other state-of-the-art methods in predicting compound-protein binding affinities. In addition, the pairwise interactions predicted by MONN displayed compatible and accordant patterns in chemical properties, which provided another evidence to support the strong predictive power of MONN. These results suggested that MONN can offer a powerful tool in predicting binding affinities of compound-protein pairs and also provide useful insights into understanding the molecular mechanisms of compound-protein interactions, which thus can greatly advance the drug discovery process. The source code of the MONN model and the dataset creation process can be downloaded from https://github.com/lishuya17/MONN.

bioinformatics↗

bioRxiv2019

Genome-wide association study identifies 143 loci associated with 25 hydroxyvitamin D concentration.

Vitamin D deficiency is a candidate risk factor for a range of adverse health outcomes. In a genome-wide association study of 25 hydroxyvitamin D (25OHD) concentration in 417,580 Europeans we identified 143 independent loci in 112 1-Mb regions providing new insights into the physiology of vitamin D and implicating genes involved in (a) lipid and lipoprotein metabolism, (b) dermal tissue properties, and (c) the sulphonation and glucuronidation of 25OHD. Mendelian randomization models found no robust evidence that 25OHD concentration had causal effects on candidate phenotypes (e.g. BMI, psychiatric disorders), but many phenotypes had (direct or indirect) causal effects on 25OHD concentration, clarifying the relationship between 25OHD status and health.

genetics↗

bioRxiv2019

An optimized acetylcholine sensor for monitoring in vivo cholinergic activity

The ability to directly measure acetylcholine (ACh) release is an essential first step towards understanding its physiological function. Here we optimized the GRABACh (GPCR-Activation-Based-ACh) sensor with significantly improved sensitivity and minimal downstream coupling. Using this sensor, we measured in-vivo cholinergic activity in both Drosophila and mice, revealing compartmental ACh signals in fly olfactory center and single-trial ACh dynamics in multiple regions of the mice brain under a variety of different behaviors

neuroscience↗

bioRxiv2019

Myt1 kinase promotes mitotic cell cycle exit in Drosophila intestinal progenitor cells

Inhibitory phosphorylation of Cdk1 is a well-established mechanism for gating mitotic entry during development. However, failure to inhibit Cdk1 in adult organs causes ectopic cell division and tissue dysplasia, indicating that Cdk1 inhibition is also required for cell cycle exit. Two types of progenitor cells populate the adult Drosophila midgut: intestinal stem cells (ISCs) and post-mitotic enteroblasts (EBs). ISCs are the only mitotic cells under homeostatic conditions, dividing asymmetrically to produce quiescent EB daughter cells. We show here that Myt1, the membrane associated Cdk1 inhibitory kinase, is required for EB quiescence and subsequent differentiation. Loss of Myt1 disrupts EB cell cycle dynamics, promoting Cyclin A-dependent mitosis and accumulation of smaller progenitor-like cells that fail to differentiate. Thus, Myt1 inhibition of Cyclin A/Cdk1 functions as a mechanism for coupling cell cycle arrest with terminal cell differentiation in this developmental context.

developmental biology↗

bioRxiv2019

Bayesian analysis of GWAS summary data reveals differential signatures of natural selection across human complex traits and functional genomic categories

Understanding how natural selection has shaped the genetic architecture of complex traits and diseases is of importance in medical and evolutionary genetics. Bayesian methods have been developed using individual-level data to estimate multiple features of genetic architecture, including signatures of natural selection. Here, we present an enhanced method (SBayesS) that only requires GWAS summary statistics and incorporates functional genomic annotations. We analysed GWAS data with large sample sizes for 155 complex traits and detected pervasive signatures of negative selection with diverse estimates of SNP-based heritability and polygenicity. Projecting these estimates onto a map of genetic architecture obtained from evolutionary simulations revealed relatively strong natural selection on genetic variants associated with cardiorespiratory and cognitive traits and relatively small number of mutational targets for diseases. Averaging across traits, the joint distribution of SNP effect size and MAF varied across functional genomic regions (likely to be a consequence of natural selection), with enrichment in both the number of associated variants and the magnitude of effect sizes in regions such as transcriptional start sites, coding regions and 5- and 3-UTRs.

genetics↗

bioRxiv2019

Generation and quality control of maternal plasma lipidomics data associated with preterm birth

Preterm birth is not only one of the most common causes of infant deaths but also a great risk for them to have severe subsequent health problems. The causes of preterm birth may be due to a combination of genetic and environmental factors, however, it remains largely unknown. Here we report an untargeted lipidomics dataset of plasma specimens from 258 pregnant women at the stage of twelve to twenty-five gestational weeks. Among them, 44 had extremely to very preterm births, 54 had moderate preterm births, 71 had late preterm births and 89 had full-term deliveries. The metabolomic profiling was generated with an UPLC-MS in both the positive and negative mode, and putative identification of all the metabolites was provided by searching against online databases. The quality assessment performed on quality control samples showed that the data is reproducible, robust and reliable. Both the raw data files, the raw and processed data matrix were available on MetaboLights, which may be used as a valuable validation dataset for new findings and a test dataset for novel algorithms.

systems biology↗

bioRxiv2019

Evaluation of five cell-free DNA isolation kits for plasma

Cell-free DNA (cfDNA) has been widely used in prenatal test and cancer diagnosis nowadays. The cost- and time-effective isolation kits are needed especially in large-scale clinical application. Here, we compared three domestic kits: VAHTS Serum/Plasma Circulating DNA kit (VZ), MagPure Gel Pure DNA mini kit (MG) and Serum/Plasma Circulating DNA Kit (TG), together with QIAamp Circulating Nucleic Acid Kit (QC) and QIAamp DNA Blood Mini Kit (QD) in cfDNA isolation. cfDNA was isolated from the pooled samples with spike-in fragments, qPCR was conducted to quantify the spike-in fragments recovery. The results indicated that all of the five kits could isolate cfDNA with different efficiency. The VZ kit had an efficiency as high as 90 percent, which is comparable to QC kit. The libraries were constructed using the isolated cfDNAs, quantified by Qubit and analyzed by 2100 bioanalyzer. Both showed the libraries were qualified. Finally, cffDNAs were detected by qPCR targeting SRY gene using libraries from pregnant women bearing male fetuses. All five kits could isolate cffDNAs that could be detected by qPCR. Our results provided more choices in wide-scale clinical application of cfDNA-based non-invasive genetic tests.

molecular biology↗

bioRxiv2019

PALM-Seq: simultaneous sequencing of cell-free long RNA and small RNA

Cell-free RNA, including both long RNA and small RNA, has been considered important for its biological functions and potential clinical usage, but the major challenge is to effectively sequence them at the same time. Here we present PolyAdenylation Ligation Mediated-Seq (PALM-Seq), an integrated sequencing method for cell-free long and small RNA. Through terminal modification and addition of 3 polyadenylation and 5 adaptor, we could get mRNA, long non-coding RNA, microRNA, tRNA, piRNA and other RNAs in a single library. With target RNA depletion, all these RNAs could be sequenced with relatively low depth. Using PALM-Seq, we identified pregnant-related mRNAs, long non-coding RNAs and microRNAs in female plasma. We also applied PALM-Seq to sequence RNA from amniotic fluids, leukocytes and placentas, and could find RNA signatures associated with specific sample type. PALM-Seq provides an integrated, cost-effective and simple method to characterize the landscape of cell-free RNA, and can stimulate further progress in cell-free RNA study and usage.

molecular biology↗

bioRxiv2019

Assessment of the gene expression profiles of leukocytes from different isolations

BACKGROUNDResearch on peripheral leukocyte gene expression in human health and disease is growing rapidly. However, how to process sample efficiently, simply and stably, and how to reflect human physiological state preferably remains critical issues in large cohort studies.\n\nMETHODSWe used RNA-seq to explore the differences of gene expression profiles among whole blood (WB) and three groups of leukocytes from buffy coat (BC) extraction, red blood cell (RBC) lysis and peripheral blood mononuclear cell (PBMC) isolation.\n\nRESULTSThe residual globin mRNA in leukocytes from RBC lysis (1.00% {+/-}1.23%) and PBMC isolation (0.06% {+/-} 0.03%) was much less than that in leukocytes from BC extraction (17.48% {+/-} 6.95%) and WB (24.46% {+/-} 6.43%), resulting in higher transcriptome mapping rates and larger numbers of detected genes. The expression of 616 genes associated with leukocyte function was slightly higher in leukocytes from RBC lysis than that from BC extraction and WB, but barely detected in leukocytes from PBMC isolation.\n\nCONCLUSIONSWe suggest that sample processing based on RBC lysis could allow better applications of gene expression profiling of peripheral leukocytes in large cohort studies.

molecular biology↗