Biology subjects

Zheng, K.

Publications and source records attributed to Zheng, K..

71 records · Page 4Linked to original sources

bioRxiv2020

iMDA-BN: Identification of miRNA-Disease Associations based on the Biological Network and Graph Embedding Algorithm

Benefiting from advances in high-throughput experimental techniques, important regulatory roles of miRNAs, lncRNAs, and proteins, as well as biological property information, are gradually being complemented. As the key data support to promote biomedical research, domain knowledge such as intermolecular relationships that are increasingly revealed by molecular genome-wide analysis is often used to guide the discovery of potential associations. However, the method of performing network representation learning from the perspective of the global biological network is scarce. These methods cover a very limited type of molecular associations and are therefore not suitable for more comprehensive analysis of molecular network representation information. In this study, we propose a computational model based on the Biological network for predicting potential associations between miRNAs and diseases called iMDA-BN. The iMDA-BN has three significant advantages: I) It uses a new method to describe disease and miRNA characteristics which analyzes node representation information for disease and miRNA from the perspective of biological networks. II) It can predict unproven associations even if miRNAs and diseases do not appear in the biological network. III) Accurate description of miRNA characteristics from biological properties based on high-throughput sequence information. The iMDA-BN predictor achieves an AUC of 0.9145 and an accuracy of 84.49% on the miRNA-disease association baseline dataset, and it can also achieve an AUC of 0.8765 and an accuracy of 80.96% when predicting unknown diseases and miRNAs in the biological network. Compared to existing miRNA-disease association prediction methods, iMDA-BN has higher accuracy and the advantage of predicting unknown associations. In addition, 45, 49, and 49 of the top 50 miRNA-disease associations with the highest predicted scores were confirmed in the case studies, respectively.

bioinformatics↗

bioRxiv2020

In vivo validation of spray-dried mesoporous bioactive glass microspheres acting as prolonged local release systems for BMP-2 to induce bone regeneration

Despite years of diligent research in fracture healing, an unmet clinical need for safe and effective pharmacological treatments to improve bone regeneration persists with 10 - 20 % of fracture cases exhibiting impaired healing. Bone morphogenetic protein-2 (BMP-2) is a known key mediator of physiological bone regeneration and is clinically approved for selected musculoskeletal interventions. Yet, broad usage of this growth factor is impeded due to side effects that are majorly evoked by high dosages and burst release kinetics. In this study, mesoporous bioactive glass microspheres (MBGs) produced by an aerosol assisted spray-drying, scalable process were found to be biocompatible and to induce a pro-osteogenic response on human MSCs in vitro. Loading of the MBGs with BMP-2 resulted in prolonged, low-dose BMP-2 release without affecting the material features. In a pre-clinical rodent model, BMP-2 loaded MBGs significantly enhanced bone formation and influenced the microarchitecture of newly formed bone. The MBG carriers alone performed equal to the untreated (empty) control in most parameters tested, while additionally exerting mild pro-angiogenic effects. Using MBGs as a biocompatible, pro-regenerative carrier for local and sustained low dose BMP-2 release could limit side effects, thus enabling a safer usage of BMP-2 as a potent pro-osteogenic growth factor.

cell biology↗

bioRxiv2020

A synergistic action of sirtuins directly recognizes DNA breaks and potentiates DNA damage response and repair

The DNA damage response (DDR) is a highly orchestrated process but how double-strand DNA breaks (DSBs) are initially recognized is unclear. Here, we show that polymerized SIRT6 deacetylase recognizes DSBs and potentiates the DDR. First, SIRT1 deacetylates SIRT6 at residue K33, which is important for SIRT6 polymerization and mobilization toward DSBs. Then, K33-deacetylated SIRT6 anchors to {gamma}H2AX, allowing its retention on and subsequent remodeling of local chromatin. We show that a K33R mutation that mimics hypoacetylated SIRT6 can rescue defective DNA repair as a result of SIRT1 deficiency in cultured cells. These data highlight the synergistic action between SIRTs in the spatiotemporal regulation of the DDR and DNA repair.

biochemistry↗

bioRxiv2020

Inferring Disease-Associated Piwi-Interacting RNAs via Graph Attention Networks

MotivationPIWI proteins and Piwi-Interacting RNAs (piRNAs) are commonly detected in human cancers, especially in germline and somatic tissues, and correlates with poorer clinical outcomes, suggesting that they play a functional role in cancer. As the problem of combinatorial explosions between ncRNA and disease exposes out gradually, new bioinformatics methods for large-scale identification and prioritization of potential associations are therefore of interest. However, in the real world, the network of interactions between molecules is enormously intricate and noisy, which poses a problem for efficient graph mining. This study aims to make preliminary attempts on bionetwork based graph mining. ResultsIn this study, we present a method based on graph attention network to identify potential and biologically significant piRNA-disease associations (PDAs), called GAPDA. The attention mechanism can calculate a hidden representation of an association in the network based on neighbor nodes and assign weights to the input to make decisions. In particular, we introduced the attention-based Graph Neural Networks to the field of bio-association prediction for the first time, and proposed an abstract network topology suitable for small samples. Specifically, we combined piRNA sequence information and disease semantic similarity with piRNA-disease association network to construct a new attribute network. In the experiment, GAPDA performed excellently in five-fold cross-validation with the AUC of 0.9038. Not only that, but it still has superior performance compared to methods based on collaborative filtering and attribute features. The experimental results show that GAPDA ensures the prospect of the graph neural network on such problems and can be an excellent supplement for future biomedical research. Contactzhuhongyou@ms.xjb.ac.cn;leiwang@ms.xjb.ac.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2019

GCNCDA: A New Method for Predicting CircRNA-Disease Associations Based on Graph Convolutional Network Algorithm

Numerous evidences indicate that Circular RNAs (circRNAs) are widely involved in the occurrence and development of diseases. Identifying the association between circRNAs and diseases plays a crucial role in exploring the pathogenesis of complex diseases and improving the diagnosis and treatment of diseases. However, due to the complex mechanisms between circRNAs and diseases, it is expensive and time-consuming to discover the new circRNA-disease associations by biological experiment. Therefore, there is increasingly urgent need for utilizing the computational methods to predict novel circRNA-disease associations. In this study, we propose a computational method called GCNCDA based on the deep learning Fast learning with Graph Convolutional Networks (FastGCN) algorithm to predict the potential disease-associated circRNAs. Specifically, the method first forms the unified descriptor by fusing disease semantic similarity information, disease and circRNA Gaussian Interaction Profile (GIP) kernel similarity information based on known circRNA-disease associations. The FastGCN algorithm is then used to objectively extract the high-level features contained in the fusion descriptor. Finally, the new circRNA-disease associations are accurately predicted by the Forest by Penalizing Attributes (Forest PA) classifier. The 5-fold cross-validation experiment of GCNCDA achieved 91.2% accuracy with 92.78% sensitivity at the AUC of 90.90% on circR2Disease benchmark dataset. In comparison with different classifier models, feature extraction models and other state-of-the-art methods, GCNCDA shows strong competitiveness. Furthermore, 10 of the top 15 circRNA-disease association candidates with the highest prediction scores were confirmed by recently published literature. These results suggest that GCNCDA can effectively predict potential circRNA-disease associations and provide highly credible candidates for biological experiments. Author SummaryThe recognition of circRNA-disease association is the key of disease diagnosis and treatment, and it is of great significance for exploring the pathogenesis of complex diseases. Computational methods can predicte the potential disease-related circRNAs quickly and accurately. Based on the hypothesis that circRNA with similar function tends to associate with similar disease, GCNCDA model is proposed to effectively predict the potential association between circRNAs and diseases by combining FastGCN algorithm. The performance of the model was verified by cross-validation experiments, different feature extraction algorithm and classifier models comparison experiments. Furthermore, 10 of the top 15 disease-associated circRNAs with the highest prediction scores were confirmed by recently published literature. It is anticipated that GCNCDA model can give priority to the most promising circRNA-disease associations on a large scale to provide reliable candidates for further biological experiment.

bioinformatics↗

bioRxiv2019

MeSHHeading2vec: A new method for representing MeSH headings as feature vectors based on graph embedding algorithm

MotivationEffectively representing the MeSH headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify. ResultsIn this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships) which can be constructed by the rule of tree num. Then, five graph embedding algorithms including DeepWalk (DW), LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed method, we carried out the node classification and relationship prediction tasks. The experimental results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the distinguishable ability of vectors. Thus, it can act as input and continue to play a significant role in any disease-, drug-, microbe- and etc.-related computational models. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network perspective. Contactzhuhongyou@ms.xjb.ac.cn

bioinformatics↗

bioRxiv2019

A mutation in Hnrnph1 that decreases methamphetamine-induced reinforcement, reward, and dopamine release and increases synaptosomal hnRNP H and mitochondrial proteins

Individual variation in the addiction liability of amphetamines has a heritable genetic component. We previously identified Hnrnph1 (heterogeneous nuclear ribonucleoprotein H1) as a quantitative trait gene underlying decreased methamphetamine-induced locomotor activity in mice. Here, mice (both male and female) with a heterozygous mutation in the first coding exon of Hnrnph1 (H1+/-) showed reduced methamphetamine reinforcement and intake and dose-dependent changes in methamphetamine reward as measured via conditioned place preference. Furthermore, H1+/- mice showed a robust decrease in methamphetamine-induced dopamine release in the nucleus accumbens with no change in baseline extracellular dopamine, striatal whole tissue dopamine, dopamine transporter protein, or dopamine uptake. Immunohistochemical and immunoblot staining of midbrain dopaminergic neurons and their forebrain projections for tyrosine hydroxylase did not reveal any major changes in staining intensity, cell number, or in the number of forebrain puncta. Surprisingly, there was a two-fold increase in hnRNP H protein in the striatal synaptosome of H1+/- mice with no change in whole tissue levels. To gain insight into the molecular mechanisms linking increased synaptic hnRNP H with decreased methamphetamine-induced dopamine release and behaviors, synaptosomal proteomic analysis identified an increased baseline abundance of several mitochondrial complex I and V proteins that rapidly decreased at 30 min post-methamphetamine administration in H1+/- mice. In contrast, the much lower level of basal synaptosomal mitochondrial proteins in wild-type mice showed a rapid increase in response to methamphetamine. We conclude that H1+/- decreases methamphetamine-induced dopamine release, reward, and reinforcement and induces dynamic changes in basal and methamphetamine-induced synaptic mitochondrial function.\n\nSIGNIFICANCE STATEMENTMethamphetamine dependence is a significant public health concern with no FDA-approved treatment. We discovered a role for the RNA binding protein hnRNP H in methamphetamine reward and reinforcement. Hnrnph1 mutation also blunted methamphetamine-induced dopamine release in the nucleus accumbens - a key neurochemical event contributing to methamphetamine addiction liability. Finally, Hnrnph1 mutants showed a marked increase in basal level of synaptosomal hnRNP H and mitochondrial proteins that decreased in response to methamphetamine whereas wild-type mice showed a methamphetamine-induced increase in synaptosomal mitochondrial proteins. Thus, we identified a potential role for hnRNP H in basal and dynamic mitochondrial function that informs methamphetamine-induced cellular adaptations associated with reduced addiction liability.

neuroscience↗

bioRxiv2019

Noncanonical scaffolding of Gαi and β-arrestin by G protein-coupled receptors

G-protein-coupled receptors (GPCRs) enable cells to sense and respond appropriately to hormonal and environmental signals, and are a target of ~30% of all FDA-approved medications. Canonically, each GPCR couples to distinct G proteins, such as Gs, Gi, Gq or G12/13, as well as {beta}-arrestins. These transducer proteins translate and integrate extracellular stimuli sensed by GPCRs into intracellular signals through what are broadly considered separable signalling pathways. However, the ability of G proteins to directly interact with {beta}-arrestins to integrate signalling has not previously been appreciated. Here we show a novel interaction between Gi protein family members and {beta}-arrestin. Gi:{beta}-arrestin complexes were formed by all GPCRs tested, regardless of their canonical G protein isoform coupling, and could bind both GPCRs as well as the extracellular signal-regulated kinase (ERK). This novel paradigm of Gi:{beta}-arrestin scaffolds enhances our understanding of GPCR signalling.

cell biology↗

bioRxiv2019

Long noncoding RNAs sustain high expression of exogenous Oct4 by sponging miRNA during reprogramming

Long noncoding RNAs (lncRNAs) modulate gene expression as competing endogenous RNAs (ceRNAs) via sponging microRNAs (miRNAs). However, the extent and functional consequences of ceRNAs in diverse cellular context still need to be proven. Using a doxycycline inducible expression of Yamanaka four factors to generate induced pluripotent stem cells (iPSCs) from mouse embryonic fibroblasts (MEFs), we found the miRNAs from MEFs remained highly expressed from day 0 to day 6 after doxycycline induction; unexpectedly, many genes targeted by these miRNAs were actually up-regulated; meanwhile, long intergenic noncoding RNAs (lincRNAs) and circular RNAs (circRNAs) which have complementary binding sites with the miRNAs were highly expressed, indicating lincRNAs and circRNAs (linc/circRNAs) may serve as sponges for miRNAs to block their activities during reprogramming. Intriguingly, the knockdown of the linc/circRNAs sponging the miRNAs targeting Oct4 mRNA resulted in down-regulation of exogenous Oct4 expression, decrease of reprogramming efficiency, and low-grade chimera forming iPSCs. Our results suggest that the ceRNA network plays an important role in reprogramming somatic cells to pluripotent stem cells.

cell biology↗

bioRxiv2019

The gut microbiota regulates mouse biliary regenerative responses

Injury to the biliary epithelium triggers cholangiopathies. However, factors involved in regulating the pathogenesis remains incompletely understood. Here, we report that the gut microbiota is important in regulating hepatobiliary fibroproliferative regenerative process. In helminth Clonorchis sinensis-induced bile duct injury model, wild-type mice showed more extensive peribiliary fibroproliferative responses than non-littermate IL-33-deficient mice. However, these reactions could be attenuated by co-housing of the animals together. In the meantime, the relatively fibroproliferative-resistant IL-33-deficient mice could become fibroproliferative-responsive especially in large intrahepatic bile duct by antibiotics treatment. Furthermore, microbiota-derived metabolite butyrate was able to inhibit biliary organoid expansion in vitro and temper 3,5-diethoxycarbonyl-1,4-dihydrocollidine-induced biliary fibrosis in vivo. Together, our data implies a potential way of management of hepatobiliary diseases by modulating gut microbiota.

microbiology↗

bioRxiv2018

Osteoblastic PLEKHO1 contributes to joint inflammation in rheumatoid arthritis

Osteoblasts participating in the inflammation regulation gradually obtain concerns. However, its role in joint inflammation of rheumatoid arthritis (RA) is largely unknown. Pleckstrin homology domain-containing family O member 1 (PLEKHO1) was previously identified as a negative regulator of osteogenic lineage activity. Here we demonstrated that PLEKHO1 was highly expressed in osteoblasts of articular specimens from RA patients and inflammatory arthritis mice. Genetic deletion of osteoblastic Plekho1 ameliorated joint inflammation in mice with collagen-induced arthritis (CIA) and K/BxN serum-transfer arthritis (STA), whereas overexpressing Plekho1 only within osteoblasts in CIA and STA mice demonstrated exacerbated local inflammation. Further in vitro studies indicated that PLEKHO1 was required for TRAF2-mediated RIP1 ubiquitination to activate NF-kB for inducing inflammatory cytokines production in osteoblasts. Moreover, osteoblastic PLEKHO1 inhibition improved joint inflammation and attenuated bone formation reduction in CIA mice and non-human primate arthritis model. These data strongly suggest that highly expressed PLEKHO1 in osteoblast mediates joint inflammation in RA. Targeting osteoblastic PLEKHO1 may exert dual therapeutic action of alleviating joint inflammation and promoting bone formation in RA.

cell biology↗

bioRxiv2018

Astroglia withdraw from potentiated synapses boosting inter-synaptic cross-talk

Extrasynaptic actions of glutamate are limited by high-affinity transporters on perisynaptic astroglial processes (PAPs), which helps to maintain point-to-point transmission in excitatory circuits. Memory formation in the brain is associated with synaptic remodelling, but how this remodelling affects PAPs and therefore extrasynaptic glutamate actions is poorly understood. Here we used advanced imaging methods, in situ and in vivo, to find that a classical synaptic memory mechanism, long-term potentiation (LTP), triggers withdrawal of PAPs from potentiated synapses. Optical glutamate sensors combined with patch-clamp and 3D molecular localisation reveal that LTP induction thus prompts a spatial retreat of glial glutamate transporters, boosting glutamate spillover and NMDA receptor-mediated inter-synaptic cross-talk. The LTP-triggered PAP withdrawal involves NKCC1 transporters and the actin-controlling protein cofilin but does not depend on major Ca2+-dependent cascades in astrocytes. We have therefore uncovered a mechanism by which synaptic potentiation could alter signal handling by multiple nearby connections.

neuroscience↗

bioRxiv2018

Multiplexed calcium imaging of single-synapse activity and astroglial responses in the intact brain

All-optical registration of neuronal and astrocytic activities within the intact mammalian brain has improved significantly with recent advances in optical sensors and biophotonics. However, relating single-synapse release events and local astroglial responses to sensory stimuli in an intact animal has not hitherto been feasible. Here, we present a multiplexed multiphoton excitation imaging approach for assessing the relationship between presynaptic Ca2+ entry at thalamocortical axonal boutons and perisynaptic astrocytic Ca2+ elevations, induced by whisker stimulation in the barrel cortex of C57BL/6 mice. We find that, unexpectedly, Ca2+ elevations in the perisynaptic astrocytic regions consistently precede local presynaptic Ca2+ signals during spontaneous brain activity associated with anaesthesia. The methods described here can be adapted to a variety of optical sensors and are compatible with experimental designs that might necessitate repeated sampling of single synapses over a longitudinal behavioural paradigm.\n\nHighlightsO_LIWe applied multiplexed multiphoton imaging to optically assess activity of individual synapses and the surrounding astroglia in the intact brain\nC_LIO_LIPerisynaptic astrocytic regions display localiased, context-dependent Ca2+ elevations in vivo\nC_LIO_LISuch elevations may precede spontaneous Ca2+ entry at presynaptic boutons\nC_LIO_LIThis method paves the way for optical investigation of glutamate release probability in vivo\nC_LI

neuroscience↗

bioRxiv2018

Multiplex imaging of quantal glutamate release and presynaptic Ca2+ at multiple synapses in situ

Information processing by brain circuits depends on Ca2+-dependent, stochastic release of the excitatory neurotransmitter glutamate. Recently developed optical sensors have enabled detection of evoked and spontaneous release at common glutamatergic synapses. However, monitoring synaptic release probability, its use-dependent changes, and its underpinning presynaptic machinery in situ requires concurrent, intensity-independent readout of presynaptic Ca2+ and glutamate release. Here, we find that the red-shifted Ca2+ indicator Cal-590 shows Ca2+-sensitive fluorescence lifetime, and employ it in combination with the novel green glutamate sensor SF-iGluSnFR variant to document quantal release of glutamate together with presynaptic Ca2+ concentration, in multiple synapses in an identified neural circuit. At the level of individual presynaptic boutons, we use multi-exposure and stochastic reconstruction procedures to reveal nanoscopic co-localisation of presynaptic Ca2+ entry and glutamate release, a fundamental unknown in modern neurobiology. This approach opens a new horizon in the quest to understand release machinery of central synapses.

neuroscience↗

bioRxiv2018

Changes in neuronal immunofluorescence in the C- versus N-terminal domains of hnRNP H following D1 dopamine receptor activation

RNA binding proteins are a diverse class of proteins that regulate all aspects of RNA metabolism. Accumulating studies indicate that heterogeneous nuclear ribonucleoproteins are associated with cellular adaptations in response to drugs of abuse. We recently mapped and validated heterogeneous nuclear ribonucleoprotein H1 (Hnrnph1) as a quantitative trait gene underlying differential behavioral sensitivity to methamphetamine. The molecular mechanisms by which hnRNP H1 alters methamphetamine behaviors are unknown but could involve preand/or post-synaptic changes in protein localization and function. Methamphetamine initiates post-synaptic D1 dopamine receptor signaling indirectly by binding to pre-synaptic dopamine transporters and vesicular monoamine transporters of midbrain dopaminergic neurons which triggers revers e transport and accumulation of dopamine at the synapse. Here, we examined changes in neuronal localization of hnRNP H in primary rat cortical neurons that express dopamine receptors that can be modulated by the D1 or D2 dopamine receptor agonists SKF38393 and (-)-Quinpirole HCl, respectively. Basal immunostaining of hnRNP H was localized primarily to the nucleus. D1 dopamine receptor activation induced an increase in hnRNP H nuclear immunostaining as detected by immunocytochemistry with a C-domain directed antibody containing epitope near the glycine-rich domain but not with an N-domain specific antibody. Although there was no change in hnRNP H protein in the nucleus or cytoplasm, there was a decrease in Hnrnph1 transcript following D1 receptor stimulation. Taken together, these results suggest that D1 receptor activation increases availability of the hnRNP H C-terminal epitope, which could potentially reflect changes in protein-protein interactions. Thus, D1 receptor signaling could represent a key molecular post-synaptic event linking Hnrnph1 polymorphisms to drug-induced behavior.\n\nHighlightsO_LIWe investigated immunofluorescence and localization of hnRNP H following dopamine receptor activation in primary rat cortical neurons.\nC_LIO_LIActivation of D1 dopamine receptor increased nuclear immunofluorescence of the C-terminal domain but not the N-terminal domain of hnRNP H with no change in either nuclear or cytoplasmic levels of hnRNP H protein.\nC_LIO_LID1 dopamine signaling could alter interaction of hnRNP H with other proteins.\nC_LI

neuroscience↗

bioRxiv2017

Rice TSV3 Encoding Obg-like GTPase Protein is Essential for Chloroplast Development during the Early Leaf Stage under Cold Stress

The Spo0B-associated GTP-binding (Obg) proteins occupy a wide variety of roles in the viability of nearly all bacteria. Its detailed roles in higher plants have not yet been elucidated. A novel rice thermo-sensitive virescent mutant tsv3 was identified in this study that displayed albino phenotype at 20{degrees}C before the 3-leaf stage while being normal green at 32{degrees}C or even at 20{degrees}C after the 4-leaf stage. The mutant phenotype was aligned with altered chlorophyll (Chl) content and chloroplast development. Map-based cloning and complementation test showed that TSV3 encoded a kind of small GTP binding protein. Subcellular localization revealed that TSV3 was in chloroplast. TSV3 transcripts were highly expressed in leaves and weak or undetectable in other tissues, suggesting the tissue-specific expression. In tsv3 mutant, the transcriptional levels of certain genes associated with biogenesis of chloroplast ribosomes 50S subunit were severely decreased at the 3-leaf-stage under cold stress, but could be recovered to normal levels at a higher temperature (32{degrees}C). The observations from this study indicated that the rice nuclear-encoded TSV3 plays important roles in chloroplast development at early leaf stage under cold stress.

plant biology↗

bioRxiv2016

Cas13b is a Type VI-B CRISPR-associated RNA-Guided RNase differentially regulated by accessory proteins Csx27 and Csx28

CRISPR-Cas adaptive immune systems defend microbes against foreign nucleic acids via RNA-guided endonucleases. Using a computational sequence database mining approach, we identify two Class 2 CRISPR-Cas systems (subtype VI-B) that lack Cas1 and Cas2 and encompass a single large effector protein, Cas13b, along with one of two previously uncharacterized associated proteins, Csx27 or Csx28. We establish that these CRISPR-Cas systems can achieve RNA interference when heterologously expressed. Through a combination of biochemical and genetic experiments, we show that Cas13b processes its own CRISPR array with short and long direct repeats, cleaves target RNA, and exhibits collateral RNase activity. Using an E. coli essential gene screen, we demonstrate that Cas13b has a double-sided protospacer-flanking sequence and elucidate RNA secondary structure requirements for targeting. We also find that Csx27 represses, whereas Csx28 enhances, Cas13b-mediated RNA interference. Characterization of these CRISPR systems creates opportunities to develop tools to manipulate and monitor cellular transcripts.

microbiology↗