Biology subjects

Zhao, H.

Publications and source records attributed to Zhao, H..

At least 433 records · Page 24Linked to original sources

bioRxiv2021

Satellite glia are essential modulators of sympathetic neuron survival, activity, and autonomic function

Satellite glia are the major glial cells in sympathetic ganglia, enveloping neuronal cell bodies. Despite this intimate association, how satellite glia contribute to sympathetic functions remain unclear. Here, we show that satellite glia are critical for metabolism, survival, and activity of sympathetic neurons and modulate autonomic behaviors in mice. Adult ablation of satellite glia results in impaired mTOR signaling, soma atrophy, reduced noradrenergic enzymes, and loss of sympathetic neurons. However, persisting neurons have elevated activity, and satellite glia-ablated mice show increased pupil dilation and heart rate, indicative of enhanced sympathetic tone. Satellite glia-specific deletion of Kir4.1, an inward-rectifying potassium channel, largely recapitulates the cellular defects observed in glia-ablated mice, suggesting that satellite glia act in part via extracellular K+ buffering. These findings highlight neuron-satellite glia as functional units in regulating sympathetic output, with implications for disorders linked to sympathetic hyper-activity such as cardiovascular disease and hypertension.

neuroscience↗

bioRxiv2021

Non-linear Archetypal Analysis of Single-cell RNA-seq Data by Deep Autoencoders

Advances in single-cell RNA sequencing (scRNA-seq) have led to successes in discovering novel cell types and understanding cellular heterogeneity among complex cell populations through cluster analysis. However, cluster analysis is not able to reveal continuous spectrum of states and underlying gene expression programs (GEPs) shared across cell types. We introduce scAAnet, an autoencoder for single-cell non-linear archetypal analysis, to identify GEPs and infer the relative activity of each GEP across cells. We use a count distribution-based loss term to account for the sparsity and overdispersion of the raw count data and add an archetypal constraint to the loss function of scAAnet. We first show that scAAnet outperforms existing methods for archetypal analysis across different metrics through simulations. We then demonstrate the ability of scAAnet to extract biologically meaningful GEPs using publicly available scRNA-seq datasets including a pancreatic islet dataset, a lung idiopathic pulmonary fibrosis dataset and a prefrontal cortex dataset.

bioinformatics↗

bioRxiv2021

Transferrin receptor 1-mediated iron uptake regulates bone mass in mice via osteoclast mitochondria and cytoskeleton

Increased intracellular iron spurs mitochondrial biogenesis and respiration to satisfy high-energy demand during osteoclast differentiation and bone-resorbing activities. Transferrin receptor 1 (TFR1) mediates cellular iron uptake through endocytosis of iron-loaded transferrin and its expression increases during osteoclast differentiation. Nonetheless, the precise functions of TFR1 and TFR1-mediated iron uptake in osteoclast biology and skeletal homeostasis remain incompletely understood. To investigate the role of TFR1 in osteoclast lineage cells, we conditionally deleted Tfr1 gene in myeloid precursors or mature osteoclasts by crossing Tfr1- floxed mice with LysM-Cre and Ctsk-Cre mice, respectively. Skeletal phenotyping by {micro}CT and histology unveiled that loss of Tfr1 in osteoclast progenitor cells resulted in a three-fold increase in trabecular bone mass in the long bones of 10-week old female but not male mice. Although high trabecular bone volume in long bones was seen in both male and female mice with deletion of Tfr1 in mature osteoclasts, this phenotype was more pronounced in female knockout mice. Mechanistically, disruption of Tfr1 expression attenuated mitochondrial metabolism and cytoskeletal organization in mature osteoclasts, leading to decreased bone resorption with no impact on osteoclastogenesis. These results indicate that Tfr1-mediated iron uptake is specifically required for osteoclast function and is indispensable for bone remodeling.

cell biology↗

bioRxiv2021

Large-scale miRNA-Target Data Analysis to Discover miRNA Co-regulation Network of Abiotic Stress Tolerance in Soybeans

Although growing evidence shows that microRNA (miRNA) regulates plant growth and development, miRNA regulatory networks in plants are not well understood. Current experimental studies cannot characterize miRNA regulatory networks on a large scale. This information gap provides a good opportunity to employ computational methods for global analysis and to generate useful models and hypotheses. To address this opportunity, we collected miRNA-target interactions (MTIs) and used MTIs from Arabidopsis thaliana and Medicago truncatula to predict homologous MTIs in soybeans, resulting in 80,235 soybean MTIs in total. A multi-level iterative bi-clustering method was developed to identify 483 soybean miRNA-target regulatory modules (MTRMs). Furthermore, we collected soybean miRNA expression data and corresponding gene expression data in response to abiotic stresses. By clustering these data, 37 MTRMs related to abiotic stresses were identified including stress-specific MTRMs and shared MTRMs. These MTRMs have gene ontology (GO) enrichment in resistance response, iron transport, positive growth regulation, etc. Our study predicts soybean miRNA-target regulatory modules with high confidence under different stresses, constructs miRNA-GO regulatory networks for MTRMs under different stresses and provides miRNA targeting hypotheses for experimental study. The method can be applied to other biological processes and other plants to elucidate miRNA co-regulation mechanisms.

plant biology↗

bioRxiv2021

Capturing large genomic contexts for accurately predicting enhancer-promoter interactions

Accurately identifying enhancer-promoter interactions (EPIs) is challenging because enhancers usually act on the promoters of distant target genes. Although a variety of machine learning and deep learning models have been developed, many of them are not designed to or could not be well applied to predict EPIs in cell types different from the training data. In this study, we develop the TransEPI model for EPI prediction based on datasets derived from Hi-C and ChIA-PET data. TransEPI compiles genomic features from large intervals harboring the enhancer-promoter pair and adopts a Transformer-based architecture to capture the long-range dependencies. Thus, TransEPI could achieve more accurate prediction by addressing the impact of other genomic loci that may competitively interact with the enhancer-promoter pair. We evaluate TransEPI in a challenging scenario, where the independent test samples are predicted by models trained on the data from different cell types and chromosomes. TransEPI robustly predicts cross-cell-type EPI prediction by achieving comparable performance in cross-validation and independent test. More importantly, TransEPI significantly outperforms the state-of-the-art EPI models on the independent test datasets, with the Area Under Precision-Recall Curve (auPRC) score increasing by 48.84 % on average. Hence, TransEPI is applicable for accurate EPI prediction in cell types without chromatin structure data. Moreover, we find the TransEPI framework could also be extended to identify the target gene of non-coding mutations, which may facilitate studying pathogenic non-coding mutations.

bioinformatics↗

bioRxiv2021

Hippo pathway and Bonus control developmental cell fate decisions in the Drosophila eye

The canonical function of the Hippo signaling pathway is regulation of organ growth. How this pathway controls cell fate determination is less well understood. Here, we uncover a function of the Hippo pathway in developmental cell fate decisions in the Drosophila eye-antennal disc exerted through the interaction of Yorkie (Yki) with the transcriptional regulator Bonus (Bon), an ortholog of mammalian Transcriptional Intermediary Factor 1/tripartite motif (TIF1/TRIM) family proteins. Instead of controlling tissue growth, Yki and Bon promote epidermal and antennal fates at the expense of the eye fate. Proteomic, transcriptomic, and genetic analyses reveal that Yki and Bon control these cell fate decisions by recruiting transcriptional and post-transcriptional co-regulators, and by activating epidermal differentiation genes and repressing Notch target genes. Our work expands the range of functions and regulatory mechanisms under Hippo pathway control.

developmental biology↗

bioRxiv2021

Dynamics of poly(A) tail length and non-A residues during the human oocyte-to-embryo transition

Poly(A) tail-mediated post-transcriptional regulation of maternal mRNA has been shown to be vital in the oocyte-to-embryo transition (OET) in flies, fish, frogs, and mice1-8. However, nothing is known about poly(A) tail dynamics for even a single gene during the human OET, because of the limited availability of human oocytes and embryos in combination with the low sensitivity of previous methods. Here, we systematically profiled the transcriptome-wide mRNA poly(A) tails in human oocytes at the germ-vesicle (GV), metaphase I (MI), and metaphase II (MII) stages, as well as pre-implantation embryos at the 1-cell (1C), 2-cell (2C), 4-cell (4C), 8-cell (8C), morula (MO), and blastocyst (BL) stages using single-oocyte/embryo PAIso-seq1 and PAIso-seq2 methods. We show that poly(A) tail length is highly dynamic during the OET, with BTG4 responsible for global deadenylation. Moreover, we reveal that non-A residues occur primarily in poly(A) tails of maternal RNA, which begin to increase at the MI stage, become highly abundant after fertilization (with U residues occurring in about two thirds, G residues in about one third, and C residues in about one fifth of mRNAs), and decline at the 8C stage. Importantly, we reveal that TUT4/7 can add U residues to deadenylated mRNA, which can then be re- polyadenylated to produce 5'-end and internal U residues. In addition, the re- polyadenylated mRNA can be stabilized through the addition of G residues by TENT4A/B. Finally, we demonstrate that U residues in poly(A) tails mark the maternal transcripts for quicker degradation in 8C human embryos compared to those without U residues. Together, our results not only reveal the dynamics of poly(A) tail length and non-A residues, but also provide mechanistic insights into the regulation of the length and the role of non-A residues during human OET. These findings further scientific understanding and open a new door for studying the human OET.

developmental biology↗

bioRxiv2021

Mapping of single-cell landscape of acral melanoma and analysis of molecular regulatory network of tumor microenvironment

Melanoma is a type of skin malignant tumor with high invasiveness, high metastasis, and poor prognosis. The incidence of melanoma continues to increase. Among them, the subtype of acral melanoma (AM) is more common in Asian populations. AM has higher degree, low immunotherapy response rate. With the help of single-cell sequencing technology provides new technical means for tumor microenvironment research, so that we can more easily explore specific tumor types suitable immunotherapy targets. However, no complete single-cell level differentiation map exists for the AM tumor microenvironment (TME). In this study, we used AM related sample and used the 10x Genomics single-cell transcriptome platform to draw a specific single-cell map of AM, understand the cell composition of AM, and analyze the interaction and molecular regulation of AM TME. Nine cell types were identified, of which malignant cells accounted for the largest proportion, followed by fibroblasts. And the cell interaction network shows that malignant cells, macrophages, B, T and fibroblasts play an important role in AM TME. Our research provides systematic theoretical guidance for the diagnosis and treatment of acral melanoma.

genomics↗

bioRxiv2021

AlphaFold-aware prediction of protein-DNA binding sites using graph transformer

Protein-DNA interactions play crucial roles in the biological systems, and identifying protein-DNA binding sites is the first step for mechanistic understanding of various biological activities (such as transcription and repair) and designing novel drugs. How to accurately identify DNA-binding residues from only protein sequence remains a challenging task. Currently, most existing sequence-based methods only consider contextual features of the sequential neighbors, which are limited to capture spatial information. Based on the recent breakthrough in protein structure prediction by AlphaFold2, we propose an accurate predictor, GraphSite, for identifying DNA-binding residues based on the structural models predicted by AlphaFold2. Here, we convert the binding site prediction problem into a graph node classification task and employ a transformer-based variant model to take the protein structural information into account. By leveraging predicted protein structures and graph transformer, GraphSite substantially improves over the latest sequence-based and structure-based methods. The algorithm is further confirmed on the independent test set of 181 proteins, where GraphSite surpasses the state-of-the-art structure-based method by 16.4% in AUPR and 11.2% in MCC, respectively. We provide the datasets, the predicted structures, and the source codes along with the pre-trained models of GraphSite at https://github.com/biomed-AI/GraphSite. The GraphSite web server is freely available at https://biomed.nscc-gz.cn/apps/GraphSite.

bioinformatics↗

bioRxiv2021

Machine learning enables discovery of DNA-carbon nanotube sensors for serotonin

DNA-wrapped single walled carbon nanotube (SWNT) conjugates have remarkable optical properties leading to their use in biosensing and imaging applications. A critical limitation in the development of DNA-SWNT sensors is the current inability to predict unique DNA sequences that confer a strong analyte-specific optical response to these sensors. Here, near-infrared (nIR) fluorescence response datasets for ~100 DNA-SWNT conjugates, narrowed down by a selective evolution protocol starting from a pool of ~1010 unique DNA-SWNT candidates, are used to train machine learning (ML) models to predict new unique DNA sequences with strong optical response to neurotransmitter serotonin. First, classifier models based on convolutional neural networks (CNN) are trained on sequence features to classify DNA ligands as either high response or low response to serotonin. Second, support vector machine (SVM) regression models are trained to predict relative optical response values for DNA sequences. Finally, we demonstrate with validation experiments that integrating the predictions of ensembles of the highest quality CNN classifiers and SVM regression models leads to the best predictions of both high and low response sequences. With our ML approaches, we discovered five new DNA-SWNT sensors with higher fluorescence intensity response to serotonin than obtained previously. Overall, the explored ML approaches introduce an important new tool to predict useful DNA sequences, which can be used for discovery of new DNA-based sensors and nanobiotechnologies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/457145v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@9e1a2corg.highwire.dtl.DTLVardef@1c84e68org.highwire.dtl.DTLVardef@1939d1eorg.highwire.dtl.DTLVardef@30424e_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2021

Estimating genetic correlation jointly using individual-level and summary-level GWAS data

With the increasing accessibility of individual-level data from genome wide association studies, it is now common for researchers to have individual-level data of some traits in one specific population. For some traits, we can only access public released summary-level data due to privacy and safety concerns. The current methods to estimate genetic correlation can only be applied when the input data type of the two traits of interest is either both individual-level or both summary-level. When researchers have access to individual-level data for one trait and summary-level data for the other, they have to transform the individual-level data to summary-level data first and then apply summary data-based methods to estimate the genetic correlation. This procedure is computationally and statistically inefficient and introduces information loss. We introduce GENJI (Genetic correlation EstimatioN Jointly using Individual-level and summary data), a method that can estimate within-population or transethnic genetic correlation based on individual-level data for one trait and summary-level data for another trait. Through extensive simulations and analyses of real data on within-population and transethnic genetic correlation estimation, we show that GENJI produces more reliable and efficient estimation than summary data-based methods. Besides, when individual-level data are available for both traits, GENJI can achieve comparable performance than individual-level data-based methods. Downstream applications of genetic correlation can benefit from more accurate estimates. In particular, we show that more accurate genetic correlation estimation facilitates the predictability of cross-population polygenic risk scores.

genetics↗

bioRxiv2021

Construction of competing endogenous RNA interaction networks as prognostic markers in metastatic melanoma

Malignant melanoma (MM) is a highly aggressive, metastatic cancer originating from melanocytes. These tumors have an extremely poor prognosis. MM accounts for 4% of skin cancers with an 80% mortality rate. The median survival of patients with metastatic melanoma is approximately six months, with a five-year survival rate of less than 10%. In recent years, the incidence of melanoma has gradually increased and has become one of the deadliest cancers. Competitive endogenous RNA (ceRNA) models the mechanism by which long chain non-coding RNAs (lncRNAs) play a regulatory role in the disease. LncRNAs can act as a sponge, competitively attracting small RNAs (micoRNAs; miRNAs) and interfering with miRNA function. This can affect the expression of target gene messenger RNAs (mRNAs), ultimately promoting tumorigenesis and tumor progression. Bioinformatics analysis may identify potentially prognostic and therapeutically-relevant differentially expressed genes in MM, as well as lncRNAs, miRNAs and mRNAs that are interconnected through the ceRNA network. This may provide further insight into gene regulation and the prognosis of metastatic melanoma. Weighted co-expression networks were used to identify lncRNA and mRNA modules associated with the metastatic phenotype, as well as the co-expression genes contained in the modules. We used 17 lncRNAs, six miRNAs, and 11 mRNAs to construct a ceRNA interaction network with a regulatory role in patients with metastatic melanoma. The prognostic risk model was used as a sorter to classify the survival prognosis of melanoma patients. Four groups of ceRNA interaction triplets were obtained, and miR-3662 may be used in the treatment of metastatic melanoma patients. Experiments confirmed the regulating relationship and phenotype of this assumption. This study provides new targets to regulate the metastatic process, predict metastatic potential and determine that miR-3662 may be used in the treatment of melanoma.

cancer biology↗

bioRxiv2021

ASER: Animal Sex Reversal database

Sex reversal, representing extraordinary sexual plasticity during the life cycle, not only triggers reproduction in animals but also affects reproductive and endocrine system-related diseases and cancers in humans. Sex reversal has been broadly reported in animals, however, an integrated resource hub of sex reversal information is still lacking. Here, we constructed a comprehensive database named ASER by integrating sex reversal-related data of 18 species from Teleostei to Mammals. We systematically collected 40,018 published papers and mined the Sex Reversal-associated Genes (SRGs), including their regulatory networks, from 1,611 core papers. We annotated homologous genes and computed conservation scores for whole genomes across the 18 species. Furthermore, we collected 206 available RNA-seq data and investigated the expression dynamics of SRGs during sex reversal or sex determination processes. In addition, we manually annotated 551 ISH images of SRGs from the literature and described their spatial expression in the gonads. Collectively, ASER provides a unique and integrated resource for researchers to query and reuse organized data to explore the mechanisms and applications of SRGs in animal breeding and human health. The ASER database is publicly available at http://aser.ihb.ac.cn/.

zoology↗

bioRxiv2021

Vitamin D modulation of mitochondrial oxidative metabolism and mTOR enforces stress tolerance and anti-cancer responses

The relationship between vitamin D and reactive oxygen species (ROS), two integral signaling and damaging molecules of the cell, is poorly understood. This is striking, given that both factors are involved in cancer cell regulation and metabolism. Mitochondria (mt) dysfunction is one of the main drivers of cancer, producing higher cellular energy and ROS that can enhance oxidative stress and stress tolerance responses. To study the effects of vitamin D on metabolic and mt dysfunction, we used the vitamin D receptor (VDR)-sensitive MG-63 osteosarcoma cell model. Using biochemical approaches, active vitamin D (1,25-dihydroxyvitamin D, 1,25(OH)2D3) decreased mt ROS levels, membrane potential ({Delta}{Psi}mt), biogenesis, and translation, while enforcing endoplasmic reticulum/mitohormetic stress tolerance responses. Using a mitochondria-focused transcriptomic approach, gene set enrichment and pathway analyses show that 1,25(OH)2D3 lowered mt fusion/fission and oxidative phosphorylation (OXPHOS). By contrast, mitophagy, ROS defense, and epigenetic gene regulation were enhanced after 1,25(OH)2D3 treatment, as well as key metabolic enzymes that regulate fluxes of substrates for cellular architecture and a shift toward non-oxidative energy metabolism. ATACseq revealed putative oxi-sensitive and tumor-suppressing transcription factors that may regulate important mt functional genes such as the mTORC1 inhibitor, DDIT4/REDD1. DDIT4/REDD1 was predominantly localized to the outer mt membrane in untreated MG-63 cells yet sequestered in the cytoplasm after 1,25(OH)2D3 and rotenone treatments, suggesting a level of control by membrane depolarization to facilitate its cytoplasmic mTORC1 inhibitory function. The results show that vitamin D activates distinct adaptive metabolic responses involving mitochondria to regain redox balance and control the growth of cancer cells.

cancer biology↗

bioRxiv2021

CBX4 regulates long-form thymic stromal lymphopoietin-mediated airway inflammation through SUMOylation in HDM-induced asthma

RationaleThymic stromal lymphopoietin (TSLP) is present in two distinct isoforms, short-form (sfTSLP) and long-form (lfTSLP). lfTSLP promotes inflammation while sfTSLP inhibits inflammation in allergic asthma. However, little is known about the regulation of lfTSLP and sfTSLP during allergic attack in asthma airway epithelium. Methods and ResultsHere, we report that SUMOylation was enhanced in HDM-induced allergic asthma airway epithelium. Inhibition of SUMOylation significantly alleviated airway Th2 inflammation and lfTSLP expression. Mechanistically, CBX4, a SUMOylation E3 ligase, enhanced lfTSLP, but not sfTSLP, mRNA translation through the RNA binding protein, MEX-3B. MEX-3B promoted lfTSLP translation through binding of its KH domains to the lfTSLP mRNA. Furthermore, CBX4 regulated MEX-3B transcription in HBE through enhancing SUMOylation levels of the transcription factor, TFII-I. ConclusionWe demonstrate an important mechanism whereby CBX4 promotes MEX-3B transcription through enhancing TFII-I SUMOylation, and MEX-3B enhances the expression of lfTSLP through binding to the lfTSLP mRNA and promoting its translation. Our findings uncover a novel target of CBX4 for therapeutic agents to lfTSLP-mediated asthma.

molecular biology↗

bioRxiv2021

Phase separation on cell surface: a mechanism of basic fibroblast growth factor signal transduction with heparan sulphate

Liquid-liquid phase separation (LLPS) driven by weak, multivalent interactions among biomolecules is an important means of cellular compartmentation and plays a central role in cellular processes including stress resistance, RNA processing and other cellular activities. Coordination of the condensates and inner membrane was recently revealed, mediating intracellular processes like cell signalling and cargo trafficking. Intracellular LLPS has been observed extensively in vivo, whereas LLPS in extracellular compartments has not been reported under physiological conditions. Here we show, for the first time, that basic fibroblast growth factor (bFGF) undergoes LLPS on the cell surface by interacting with heparan sulphate proteoglycans (HSPG) and the phase transition is required for effective downstream signalling. The condensation is driven by multivalent interactions between bFGF and sulpho-groups on heparan sulphate (HS), and dimerization and oligomerization of bFGF promote the LLPS process. Compared with free bFGF, phase separated bFGF with HS showed higher thermo stability, providing a potential mechanism for the preservation of bFGF activity. Furthermore, we have found that downstream signalling is triggered by phase separation of a ternary complex formed by bFGF, HSPGs and FGFR on cell surface. Our results revealed a molecular mechanism that HS can serve as a platform to promote extracellular proteins like bFGF to condensate on outer membrane, consequently coordinating the signal transduction activities. This novel finding expands the horizons of phase separation in vivo, providing a new dimension on how HSPG may regulate extracellular protein behaviour and cell signalling.

biochemistry↗

bioRxiv2021

Diversity of satellite glia in sympathetic and sensory ganglia

Satellite glia are the major glial type found in ganglia of the peripheral nervous system and wrap around cell bodies of sympathetic and sensory neurons that are very diverse. Other than their close physical association with peripheral neurons, little is known about this glial population. Here, we performed single cell RNA sequencing analysis and identified five different populations of satellite glia from sympathetic and sensory ganglia. We identified three shared populations of satellite glia enriched in immune-response genes, immediate-early genes and ion channels/ECM-interactors, respectively. Sensory- and sympathetic-specific satellite glia are differentially enriched for modulators of lipid synthesis and metabolism. Sensory glia are also specifically enriched for genes involved in glutamate turnover. Further, satellite glia and Schwann cells can be distinguished by unique transcriptional signatures. This study reveals remarkable heterogeneity of satellite glia in the peripheral nervous system.

neuroscience↗

bioRxiv2021

Complex introgression among three diverged largemouth bass lineages

Hybrid zones between diverged lineages offer an unique opportunity to study evolutionary processes related to speciation. Natural and anthropogenic hybridization in the black basses (Micropterus spp.) is well documented, including an extensive intergrade zone between the widespread northern Largemouth Bass (M. salmoides) and the Florida Bass (M. floridanus). Phenotypic surveys have identified an estuarine population of Largemouth Bass (M. salmoides) in the Mobile-Tensaw Delta, with larger relative weight and smaller adult size compared to inland populations, suggesting a potential third lineage of largemouth bass. To determine the evolutionary relationships between these Mobile Delta bass populations, M. salmoides, and M. floridanus, putative pure and intergrade populations of all three groups were sampled across the eastern United States. Phylogenetic analyses of 8,582 nuclear SNPs derived from genotype-by-sequencing and the ND2 mitochondrial gene determined that Delta bass populations stem from a recently diverged lineage of Largemouth Bass. Using a novel quantitative pipeline, a panel of 73 diagnostic SNPs was developed for the three lineages, evaluated for accuracy, and then used to screen 881 samples from 52 sites for genetic integrity and hybridization on the Agena MassARRAY platform. These results strongly support a redrawing of native ranges for both the intergrade zone and M. floridanus, which has significant implications for current fisheries management. Furthermore, Delta bass ancestry was shown to contribute significantly to the previously described intergrade zone between northern Largemouth Bass and Florida Bass, suggesting a more complex pattern of secondary contact and introgression among these diverged Micropterus lineages.

evolutionary biology↗