Biology subjects

Xu, C.

Publications and source records attributed to Xu, C..

At least 289 records · Page 16Linked to original sources

bioRxiv2021

Rod-genesis driven by mafba in an nrl knockout zebrafish model with altered photoreceptor compositions and progressive retinal degeneration

The neural retina leucine zipper (NRL) is an essential gene for the fate determination and differentiation of rod photoreceptors in mammals. Mutations in NRL have been associated with autosomal recessive enhanced S-cone syndrome and autosomal dominant retinitis pigmentosa. However, the exact role of Nrl in regulating the development and maintenance of photoreceptors in zebrafish, a popular animal model used for retinal degeneration and regeneration studies, has not been fully determined. In this study, we generated an nrl knockout zebrafish model by CRISPR-Cas9 technology and observed a surprising phenotype characterized by the reduction but not total elimination of rods and the over-grown of green-cones. By tracing the developmental process of rods, we discovered two waves of rod genesis in zebrafish, emerging at the embryonic stage with an nrl-dependent pattern and the post-embryonic stage with an nrl-independent pattern, respectively. Through bulk and single-cell RNA sequencing, we constructed the gene expression profiles for the whole retinal tissues and each of the retinal cell types in WT and nrl knockout zebrafish. We detected the rod/green-cone intermediate photoreceptors in nrl knockout zebrafish, suggesting that there may be a kind of rod/green-cone bipotent precursors and its fate choice between rod and green-cone is controlled by nrl. Besides, we identified the mafba gene as a novel regulator for nrl-independent rods, based on the cell-type-specific expression pattern and the retinal phenotype of nrl/mafba double knockout zebrafish. Furthermore, the altered photoreceptor compositions and abnormal gene expression caused progressive retinal degeneration and subsequent regeneration in nrl knockout zebrafish. Our work revealed a novel function of mafba gene in rod development and established a more suitable model for the developmental processes and regulatory mechanisms of rod and green-cone photoreceptors in zebrafish. Author SummaryVision is mediated by two types of light-sensing cells named rod and cone photoreceptors in animal eyes. Abnormal generation, dysfunction or death of photoreceptor cells can all cause irreversible vision problems. NRL is the most important gene for the occurrence and function of rod cells in mice and humans. Surprisingly, we found that in zebrafish, a popular animal model used for mimicking human diseases and testing treatments, there are two types of rod cells and breaking the function of nrl gene only affects the generation of rod cells at the embryonic stage but not the juvenile and adult stages. The rod cells produced later are proved to be driven by the mafba gene, which has not been reported to play a role in rod cells. In addition to the reduction of rod cells, deletion of nrl also results in the occurrence of rod/green-cone hybrid cells and the increasing number of green-cones. The combination of changes at cellular and molecular levels finally lead to a disease condition named retinal degeneration. These findings add new knowledge to the research field and highlight the conserved and species-specific regulatory mechanisms of photoreceptor development and maintenance.

genetics↗

bioRxiv2021

A Process-Based Model with Temperature, Water, and Lab-derived Data Improves Predictions of Daily Mosquito Density

While the number of human cases of mosquito-borne diseases has increased in North America in the last decade, accurate modeling of mosquito population density has remained a challenge. Longitudinal mosquito trap data over the many years needed for model calibration is relatively rare. In particular, capturing the relative changes in mosquito abundance across seasons is necessary for predicting the risk of disease spread as it varies from year to year. We developed a process-based mosquito population model that captures life-cycle egg, larva, pupa, adult stages, and diapause for Culex pipiens and Culex restuans mosquito populations. Mosquito development through these stages is a function of time, temperature, daylight hours, and aquatic habitat availability. The time-dependent parameters are informed by both laboratory studies and mosquito trap data from the Greater Toronto Area. The model incorporates city-wide water-body gauge and precipitation data as a proxy for aquatic habitat. This approach accounts for the nonlinear interaction of temperature and aquatic habitat variability on the mosquito life stages. We demonstrate that the full model predicts the yearly variations in mosquito populations better than a statistical model using the same data sources. This improvement in modeling mosquito abundance can help guide interventions for reducing mosquito abundance in mitigating mosquito-borne diseases like the West Nile virus.

ecology↗

bioRxiv2021

HIV-1 Mutants that Escape the Cytotoxic T-Lymphocytes are Defective in Viral DNA Integration

ABSTRACT HIV-1 replication is durably controlled in certain untreated HIV-1-infected individuals expressing particular human leukocyte antigens (HLA). These HLAs tag infected cells for elimination by presenting specific viral epitopes to CD8+ cytotoxic T-lymphocytes (CTL). In individuals expressing HLA-B27, CTLs primarily target the capsid protein (CA)-derived KK10 epitope. Selection of CA mutation R264K helps HIV-1 escape the CTL response but severely diminishes virus infectivity. Here we report that the R264K mutation-associated infectivity defect arises primarily from impaired viral DNA integration. Strikingly, selection of the compensatory CA mutation S173A or depletion of host cyclophilin A largely rescues the R264K-associated integration and infectivity defects. Collectively, our study reveals novel mechanistic insights into the fitness defect incurred by an HIV-1 variant escaping a CA-directed CTL response.

microbiology↗

bioRxiv2021

Non-Invasive Confocal Fluorescence Imaging of Mice Beyond 1700 nm Using Superconducting Nanowire Single-Photon Detectors

Light scattering by biological tissues sets a limit to the penetration depth of high-resolution optical microscopy imaging of live mammals in vivo. An effective approach to reduce light scattering and increase imaging depth is by extending the excitation and emission wavelengths to the > 1000 nm second near-infrared (NIR-II), also called the short-wavelength infrared (SWIR) window. Here, we developed biocompatible core-shell lead sulfide/cadmium sulfide (PbS/CdS) quantum dots emitting at ~1880 nm and superconducting nanowire single photon detectors (SNSPD) for single-photon detection up to 2000 nm, enabling one-photon fluorescence imaging window in the 1700-2000 nm (NIR-IIc) range. Confocal fluorescence imaging in NIR-IIc reached an imaging depth of ~ 800 m through intact mouse head, and enabled non-invasive imaging of inguinal lymph nodes (LNs) without any surgery. In vivo molecular imaging of high endothelial venules (HEVs) with diameter down to ~ 6.6 m in the lymph nodes was achieved, opening the possibility of non-invasive imaging of immune trafficking in lymph nodes at the single-cell/vessel level longitudinally.

biochemistry↗

bioRxiv2021

Reference genome and resequencing of 305 accessions provide insights into spinach evolution, domestication and genetic basis of agronomic traits

Spinach is a nutritious leafy vegetable belonging to the family Chenopodiaceae. Here we report a chromosome-scale reference genome assembly of spinach, which has a total size of 894.3 Mb and an N50 contig size of 23.8 Mb, with 98.3% anchored and ordered on the six chromosomes. Reconstruction of ancestral Chenopodiaceae karyotype indicates substantial genome rearrangements in spinach after its divergence from ancestral Chenopodiaceae, coinciding with high repeat content in the spinach genome. Resequencing the genomes of 305 cultivated and wild spinach accessions provides insights into spinach genetic diversity and population differentiation. Genome-wide association studies of 20 agronomical traits identify numerous significantly associated regions and candidate genes for these traits. Domestication sweeps in the spinach genome are identified, some of which are associated with important traits (e.g., leaf phenotype, bolting and flowering), demonstrating the role of artificial selection in shaping spinach phenotypic evolution. This study provides not only insights into the spinach evolution and domestication but also valuable resources for facilitating spinach breeding.

plant biology↗

bioRxiv2021

Evolutionary dynamics of indels in SARS-CoV-2 spike glycoprotein

SARS-CoV-2, responsible for the current COVID-19 pandemic that claimed over 4.2 million lives, belongs to a class of enveloped viruses that undergo quick evolutionary adjustments under selection pressure. Numerous variants have emerged in SARS-CoV-2 that are currently posing a serious challenge to the global vaccination effort and COVID-19 management. The evolutionary dynamics of this virus are only beginning to be explored. In this work, we have analysed 1.79 million spike glycoprotein sequences of SARS-CoV-2 and found that the virus is fine-tuning the spike with numerous amino acid insertions and deletions (indels). Indels seem to have a selective advantage as the proportions of sequences with indels were steadily increasing over time, currently at over 89%, with similar trends across countries/variants. There were as many as 420 unique indel positions and 447 unique combinations of indels. Despite their high frequency, indels resulted in only minimal alteration, including both gain and loss, of N-glycosylation sites. As indels and point mutations are positively correlated and sequences with indels have significantly more point mutations, they have implications in the context of evolutionary dynamics of the SARS-CoV-2 spike glycoprotein.

bioinformatics↗

bioRxiv2021

Functional connectomics spanning multiple areas of mouse visual cortex

To understand the brain we must relate neurons functional responses to the circuit architecture that shapes them. Here, we present a large functional connectomics dataset with dense calcium imaging of a millimeter scale volume. We recorded activity from approximately 75,000 neurons in primary visual cortex (VISp) and three higher visual areas (VISrl, VISal and VISlm) in an awake mouse viewing natural movies and synthetic stimuli. The functional data were co-registered with a volumetric electron microscopy (EM) reconstruction containing more than 200,000 cells and 0.5 billion synapses. Subsequent proofreading of a subset of neurons in this volume yielded reconstructions that include complete dendritic trees as well the local and inter-areal axonal projections that map up to thousands of cell-to-cell connections per neuron. Here, we release this dataset as an open-access resource to the scientific community including a set of tools that facilitate data retrieval and downstream analysis. In accompanying papers we describe our findings using the dataset to provide a comprehensive structural characterization of cortical cell types1-3 and the most detailed synaptic level connectivity diagram of a cortical column to date2, uncovering unique cell-type specific inhibitory motifs that can be linked to gene expression data4. Functionally, we identify new computational principles of how information is integrated across visual space5, characterize novel types of neuronal invariances6 and bring structure and function together to decipher a general principle that wires excitatory neurons within and across areas7, 8.

neuroscience↗

bioRxiv2021

Comprehensive multi-omics single-cell data integration reveals greater heterogeneity in the human immune system

Single-cell transcriptomics enables the definition of diverse human immune cell types across multiple tissues and disease contexts. Still, deeper biological understanding requires comprehensive integration of multiple single-cell omics (transcriptomic, proteomic, and cell-receptor repertoire). To improve the identification of diverse cell types and the accuracy of cell-type classification in multi-omics single-cell datasets, we developed SuPERR-seq, a novel analysis workflow to increase the resolution and accuracy of clustering and allow for the discovery of previously hidden cell subsets. In addition, SuPERR-seq accurately removes cell doublets and prevents widespread cell-type misclassification by incorporating information from cell-surface proteins and immunoglobulin transcript counts. This approach uniquely improves the identification of heterogeneous cell types in the human immune system, including a novel subset of antibody-secreting cells in the bone marrow.

systems biology↗

bioRxiv2021

ASXL3 controls cortical neuron fate specification through extrinsic self-renewal pathways

During corticogenesis, transcription plasticity is fundamental to the restriction of neural progenitor cell (NPC) multipotency and production of cortical neuron heterogeneity. Human and mouse genetic studies have highlighted the role of Polycomb transcriptional regulation in this process. ASXL3, which encodes a component of the Polycomb repressive deubiquitination (PR-DUB) complex, has been identified as a high confidence autism spectrum disorder (ASD) risk gene. Genetic inactivation of Asxl3, in a mouse model that carries a clinically relevant ASXL3 frameshift (Asxl3fs) variant, disrupts lateral expansion of NPCs and delays cortical neuron differentiation. Single-cell RNA sequencing analysis implicates Notch signaling, which alters the composition of excitatory neurons and fidelity of cortical layer deposition. Our data provides a new link between extrinsic signaling cues and intrinsic epigenetic regulation that together control the timing of cell fate programs. Furthermore, transcriptomic analysis revealed dysregulation of other known ASD risk genes indicating that a convergent developmental pathway is affected. Collectively our work provides important insights about developmental mechanisms that contribute to ASD neuropathology.

neuroscience↗

bioRxiv2021

Repression of Hypoxia-Inducible Factor-1 Contributes to Increased Mitochondrial Reactive Oxygen Species Production in Diabetes

BackgroundExcessive production of mitochondrial reactive oxygen species (ROS) is a central mechanism for the development of diabetes complications. Recently, hypoxia has been identified to play an additional pathogenic role in diabetes. In this study, we hypothesized that ROS overproduction was secondary to the impaired responses to hypoxia due to the inhibition of hypoxia-inducible factor-1 (HIF-1) by hyperglycemia. MethodsThe dynamic of ROS levels was analysed in the blood of healthy subjects and individuals with type 1 diabetes after exposure to hypoxia (ClinicalTrials.gov registration no. NCT02629406). The relation between HIF-1, glucose levels, ROS production and its functional consequences were analyzed in renal mIMCD-3 cells and in kidneys of mouse models of diabetes. ResultsExposure to hypoxia increased circulating ROS in subjects with diabetes, but not in subjects without diabetes. High glucose concentrations repressed HIF-1 both in hypoxic cells and in kidneys of animals with diabetes, through a HIF prolyl-hydroxylase (PHD) - dependent mechanism. The impaired HIF-1 signaling contributed to excess production of mitochondrial ROS through increased mitochondrial respiration that was mediated by Pyruvate dehydrogenase kinase 1 (PDK1) and was followed by functional consequences. The restoration of HIF-1 function attenuated ROS overproduction despite persistent hyperglycemia, and conferred protection against apoptosis and renal injury in diabetes. ConclusionsWe conclude that the repression of HIF-1 plays a central role in mitochondrial ROS overproduction in diabetes and is a potential therapeutic target for diabetic complications. These findings are highly significant and timely since the first PHD inhibitor that can activate HIF-1 has been newly approved for clinical use.

cell biology↗

bioRxiv2021

Evolution of Selective RNA Processing and Stabilization operons in cellulosome-harboring Clostridium spp.

In selective RNA processing and stabilization (SRPS) operons, the stoichiometry of encoded proteins is determined by their respective 3-end stem-loops (SLs), yet the evolution of this mechanism remains elusive. In cellulosomal operons of Clostridium spp., we show that the SLs and their associated genes form a monogamy companionship during the operon evolution. Based on {Delta}G of such SLs, we propose CoSLOE (Composite SL-based Operon Evolution) model with evolutionary ratio (ER) >1 or <1 for positive or negative selection of SRPS operons. In the composite SL-{Delta}G-based tree (CoSL-tree) of cellulosomal operons, when traversing from leafs to the root nodes, ERs reveal diversifying/positive selection towards a less efficient cellulosomal system, consistent with glycoside-hydrolase gene variation both in-operon and genome-wide. A similar pattern is followed by the ATPase operon and the majority of orthologous SRPS operons genome-wide, suggesting conservation among operons in such selection. Thus SRPS operons via their transcript-stabilizing non-coding elements are highlighting a link between operon stoichiometry and operon evolution.

evolutionary biology↗

bioRxiv2021

Integrative Epigenomic and High-Throughput Functional Enhancer Profiling Reveals Determinants of Enhancer Heterogeneity in Gastric Cancer

BackgroundEnhancers are distal cis-regulatory elements required for cell-specific gene expression and cell fate determination. In cancer, enhancer variation has been proposed as a major cause of inter-patient heterogeneity - however, most predicted enhancer regions remain to be functionally tested. ResultsAnalyzing 128 epigenomic histone modification profiles of primary GC samples, normal gastric tissues, and GC cell lines, we report a comprehensive catalog of 75,730 recurrent predicted enhancers, the majority of which are tumor-associated in vivo (>50,000) and associated with lower somatic mutation rates inferred by whole-genome sequencing. Applying Capture-based Self-Transcribing Active Regulatory Region sequencing (CapSTARR-seq) to the enhancer catalog, we observed significant correlations between CapSTARR-seq functional activity and H3K27ac/H3K4me1 levels. Super-enhancer regions exhibited increased CapSTARR-seq signals compared to regular enhancers even when decoupled from native chromatin contexture. We show that combining histone modification and CapSTARR-seq functional enhancer data improves the prediction of enhancer-promoter interactions and pinpointing of germline single nucleotide polymorphisms (SNPs), somatic copy number alterations (SCNAs), and trans-acting TFs involved in GC expression. Specifically, we identified cancer-relevant genes (e.g. ING1, ARL4C) whose expression between patients is influenced by enhancer differences in genomic copy number and germline SNPs, and HNF4 as a master trans-acting factor associated with GC enhancer heterogeneity. ConclusionsOur study indicates that combining histone modification and functional assay data may provide a more accurate metric to assess enhancer activity than either platform individually, and provides insights into the relative contribution of genetic (cis) and regulatory (trans) mechanisms to GC enhancer functional heterogeneity.

cancer biology↗

bioRxiv2021

Chronic opioid treatment arrests neurodevelopment and alters synaptic activity in human midbrain organoids

The impact of long-term opioid exposure on the embryonic brain is crucial to healthcare due to the surging number of pregnant mothers with an opioid dependency. Current studies on the neuronal effects are limited due to human brain inaccessibility and cross-species differences among animal models. Here, we report a model to assess cell-type specific responses to acute and chronic fentanyl treatment, as well as fentanyl withdrawal, using human induced pluripotent stem cell (hiPSC)-derived midbrain organoids. Single cell mRNA sequencing (25,510 single cells in total) results suggest that chronic fentanyl treatment arrests neuronal subtype specification during early midbrain development and alters the pathways associated with synaptic activities and neuron projection. Acute fentanyl treatment, however, increases dopamine release but does not induce significant changes in gene expressions of cell lineage development. To date, our study is the first unbiased examination of midbrain transcriptomics with synthetic opioid treatment at the single cell level.

neuroscience↗

bioRxiv2021

Distinct allosteric mechanisms of first-generation MsbA inhibitors

Present in all kingdoms of life, ATP-binding cassette (ABC) transporters couple ATP hydrolysis to mechanical force and facilitate trafficking of diverse substrates across biological membranes. Although many ABC transporters are promising drug targets, their mechanisms of regulation by small molecule inhibitors remain largely unknown. Herein, we used the lipopolysaccharide (LPS) flippase MsbA, a prototypical ABC exporter, as a model system to probe mechanisms of allosteric modulation by compounds binding to the transmembrane domains (TMDs). Recent chemical screens have identified intriguing LPS transport inhibitors targeting MsbA: the ATPase stimulator TBT1 and the ATPase inhibitor G247. Despite preliminary biochemical and structural data, it is unclear how TBT1 and G247 bind to the MsbA TMDs yet induce opposite allosteric effect in the nucleotide-binding domains (NBDs). Through single-particle EM, mutagenesis and activity assay, we show that TBT1 and G247 bind adjacent yet separate locations in the TMDs, inducing drastic changes in TMD conformation and NBD positioning. Two TBT1 molecules asymmetrically occupy the LPS binding site to break the symmetry of MsbA, resulting in disordered transmembrane helices and decreased NBD distance. In this novel inhibited ABC transporter state, decreased distance between the NBDs causes stimulation of ATP hydrolysis yet LPS transport blockage. In contrast, G247 acts as a TMDs wedge, symmetrically increasing NBD separation and preventing conformational transition of MsbA. Our study uncovers the distinct mechanisms of the first-generation MsbA-specific inhibitors and demonstrates that rational design of substrate-mimicking compounds can be exploited to develop useful ABC transporter modulators.

biochemistry↗

bioRxiv2021

Molecular basis for PICS-mediated piRNA biogenesis and cell division

By incorporating two mutually exclusive factors, PID-1 and TOST-1, C. elegans PICS complex plays important roles in piRNA biogenesis, chromosome segregation and cell division, respectively. We firstly mapped the interaction network between PICS subunits. By solving the several complex structures, including those of TOFU-6/PICS-1, ERH-2/PICS-1, and ERH-2/TOST-1, we uncover the mechanisms underlying the interactions between PICS subunits. Our biochemical experiment demonstrates that PICS exists as an octamer consisting of two copies of each subunits. Combining structural analyses with mutagenesis experiments, we identified residues of PICS subunits that are critical for maintaining intact PICS complex in vitro. Furthermore, using genetics, cell biology and imaging experiments, we found that those mutants impairing the in vitro interaction network within PICS, also lead to abnormal dysfunction PICS in vivo, including mislocalization of PICS, and reduced levels of piRNAs or abnormal chromosome segregation and cell division. Therefore, our work provides structural insights into understanding the PICS-mediated piRNA biogenesis and cell division.

molecular biology↗

bioRxiv2021

Homogeneous environmental selection overturns distance-decay relationship of soil prokaryotic community

Though being fundamental to global diversity distribution, little is known about the geographic pattern of soil microorganisms across different biomes on a large scale. Here, we investigated soil prokaryotic communities from Chinese northern grasslands on a scale up to 4,000 km in both alpine and temperate biomes. Surprisingly, prokaryotic similarities increased with geographic distance after tipping points of 1,760 - 1,920 km, overturning the well-accepted distance-decay relationship and generating a significant U-shape pattern. Such U-shape pattern was likely due to decreased disparities in environmental heterogeneity along with geographic distance when across biomes, as homogeneous environmental selection dominated prokaryotic assembly based on {beta}NTI analysis. Consistently, short-term environmental heterogeneity also followed the U-shape pattern spatially, mainly attributed to dissolved nutrients. In sum, these results demonstrate that homogeneous environmental selection via dissolved nutrients overwhelmed the "distance" effect when across biomes, subverting the previously well-accepted geographic pattern for microbes on a large scale.

ecology↗

bioRxiv2021

AutoGGN: A Gene Graph Network AutoML tool for Multi-Omics Research

Omics data identifies biological characteristics from genetic to phenotypic levels during the life span. Molecular interaction networks have a fundamental impact on life activities. Integrating omics data and molecular interaction networks will help researchers delve into comprehensive information underlying the data. Here, we proposed a new multimodal method called AutoGGN to aggregate multi-omics data and molecular interaction networks based on graph convolutional neural networks. We evaluated AutoGGN using two different tasks: cancer type classification and single-cell stage classification. On both tasks, AutoGGN showed better performance compared to other methods, the trend is relevant to the ability of utilizing much more information from biological data. The phenomenon indicated AutoGGN has the potential to incorporate valuable information from molecular interaction networks and multi-omics data effectively. Furthermore, in order to provide a better understanding of the mechanism of prediction results, we assessed the explanation using SHAP module and identified the key genes contributing to the prediction of classification, which will provide insights for the downstream design of biological experiments.

bioinformatics↗

bioRxiv2021

scvi-tools: a library for deep probabilistic analysis of single-cell omics data

AO_SCPLOWBSTRACTC_SCPLOWProbabilistic models have provided the underpinnings for state-of-the-art performance in many single-cell omics data analysis tasks, including dimensionality reduction, clustering, differential expression, annotation, removal of unwanted variation, and integration across modalities. Many of the models being deployed are amenable to scalable stochastic inference techniques, and accordingly they are able to process single-cell datasets of realistic and growing sizes. However, the community-wide adoption of probabilistic approaches is hindered by a fractured software ecosystem resulting in an array of packages with distinct, and often complex interfaces. To address this issue, we developed scvi-tools (https://scvi-tools.org), a Python package that implements a variety of leading probabilistic methods. These methods, which cover many fundamental analysis tasks, are accessible through a standardized, easy-to-use interface with direct links to Scanpy, Seurat, and Bioconductor workflows. By standardizing the implementations, we were able to develop and reuse novel functionalities across different models, such as support for complex study designs through nonlinear removal of unwanted variation due to multiple covariates and reference-query integration via scArches. The extensible software building blocks that underlie scvi-tools also enable a developer environment in which new probabilistic models for single cell omics can be efficiently developed, benchmarked, and deployed. We demonstrate this through a code-efficient reimplementation of Stereoscope for deconvolution of spatial transcriptomics profiles. By catering to both the end user and developer audiences, we expect scvi-tools to become an essential software dependency and serve to formulate a community standard for probabilistic modeling of single cell omics.

bioinformatics↗