Biology subjects

Jiang, Y.

Publications and source records attributed to Jiang, Y..

At least 505 records · Page 28Linked to original sources

bioRxiv2020

Selective increase of functional network connectivity in Arc-positive neuronal engrams after long-term potentiation

New tools in optogenetics and molecular biology have culminated in recent studies which mark immediate-early gene (IEG)-expressing neurons as memory traces or engrams. Although the activity-dependent expression of IEGs has been successfully utilised to label memory traces, their roles in engram specification is incompletely understood. Outstanding questions remain as to whether expression of IEGs can interplay with network properties such as functional connectivity and also if neurons expressing different IEGs are functionally distinct. We investigated the expression of Arc and c-Fos, two commonly utilised IEGs in memory engram specification, in cultured hippocampal neurons. After pharmacological induction of long-term potentiation (LTP) in the network, we noted an emergent network property of refinement in functional connectivity between neurons, characterized by a global down-regulation of network connectivity, together with strengthening of specific connections. Subsequently, we show that Arc expression correlates with the effects of network refinement, with Arc-positive neurons being selectively strengthened. Arc positive neurons were also found to be located in closer physical proximity to each other in the network. While the expression pattern of IEGs c-Fos and Arc strongly overlaps, Arc was more selectively expressed than c-Fos. These IEGs also act together in coding information about connection strength pruning. These results demonstrate important links between IEG expression and network connectivity, which serve to bridge the gap between cellular correlates and network effects in learning and memory.

neuroscience↗

bioRxiv2020

Three-dimensional ATUM-SEM reconstruction and analysis of hepatic endoplasmic reticulum-organelle interactions

The endoplasmic reticulum (ER) is a contiguous and complicated membrane network in eukaryotic cells, and membrane contact sites (MCSs) between the ER and other organelles perform vital cellular functions, including lipid homeostasis, metabolite exchange, calcium level regulation, and organelle division. Here, we establish a whole pipeline to reconstruct all ER, mitochondria, lipid droplets, lysosomes, peroxisomes, and nuclei by automated tape-collecting ultramicrotome scanning electron microscopy (ATUM-SEM) and deep-learning techniques, which generates an unprecedented 3D model for mapping liver samples. Furthermore, the morphology of various organelles is systematically analyzed. We found that the ER presents with predominantly flat cisternae and is knitted tightly all throughout the intracellular space and around other organelles. In addition, the ER has a smaller volume-to-membrane surface area ratio than other organelles, which suggests that the ER could be more suited for functions that require a large membrane surface area. Moreover, the MCSs between the ER and other organelles are explored. Our data indicate that ER-mitochondrial contacts are particularly abundant, especially for branched mitochondria. In addition, ER contacts with lipid droplets, lysosomes, and peroxisomes are also plentiful. In summary, we design an efficient method for obtaining a 3D reconstruction of biological structures at a nanometer resolution. Our study also provides the first 3D reconstruction of various organelles in liver samples together with important information fundamental for biochemical and functional studies in the liver.

cell biology↗

bioRxiv2020

DrugOrchestra: Jointly predicting drug response, targets, and side effects via deep multi-task learning

Massively accumulated pharmacogenomics, chemogenomics, and side effect datasets offer an unprecedented opportunity for drug response prediction, drug target identification and drug side effect prediction. Existing computational approaches limit their scope to only one of these three tasks, inevitably overlooking the rich connection among them. Here, we propose DrugOrchestra, a deep multi-task learning framework that jointly predicts drug response, targets and side effects. DrugOrchestra leverages pre-trained molecular structure-based drug representation to bridge these three tasks. Instead of directly fine-tuning on an individual task, DrugOrchestra uses deep multi-task learning to obtain a phenotype-based drug representation by simultaneously fine-tuning on drug response, target and side effect prediction. By coupling these three tasks together, DrugOrchestra is able to make predictions for unseen drugs by only knowing their molecular structures. We constructed a heterogeneous drug discovery dataset of over 21k drugs by integrating 8 datasets across three tasks. Our method obtained significant improvement in comparison to methods that were trained on a single task or a single dataset. We further revealed the transferability across 8 datasets and 3 tasks, providing novel insights for understanding drug mechanisms. Availabilityhttps://github.com/jiangdada1221/DrugOrchestra

bioinformatics↗

bioRxiv2020

WEVar: a novel statistical learning framework for predicting noncoding regulatory variants

Understanding the functional consequence of noncoding variants is of great interest. Though genome-wide association studies (GWAS) or quantitative trait locus (QTL) analyses have identified variants associated with traits or molecular phenotypes, most of them are located in the noncoding regions, making the identification of causal variants a particular challenge. Existing computational approaches developed for for prioritizing non-coding variants produce inconsistent and even conflicting results. To address these challenges, we propose a novel statistical learning framework, which directly integrates the precomputed functional scores from representative scoring methods. It will maximize the usage of integrated methods by automatically learning the relative contribution of each method and produce an ensemble score as the final prediction. The framework consists of two modes. The first "context-free" mode is trained using curated causal regulatory variants from a wide range of context and is applicable to predict noncoding variants of unknown and diverse context. The second "context-dependent" mode further improves the prediction when the training and testing variants are from the same context. By evaluating the framework via both simulation and empirical studies, we demonstrate that it outperforms integrated scoring methods and the ensemble score successfully prioritizes experimentally validated regulatory variants in multiple risk loci.

bioinformatics↗

bioRxiv2020

Neuronal Activity-Dependent Accumulation of Arc in Astrocytes

The immediate-early gene Arc is a master regulator of synaptic plasticity and plays a critical role in memory consolidation. However, there has not been a comprehensive analysis of the itinerary of Arc protein, linking its function at different subcellular locations with corresponding time points after neuronal network activation. When cultured hippocampal neurons are treated with a combination of pharmacological agents to induce long term potentiation, they express high levels of Arc, allowing to study its spatiotemporal distribution. Our experiments show that neuronal activity-induced Arc expression was not restricted to neurons, but that its spatiotemporal dynamics involved a shift to astrocytes at a later timepoint. Specifically, astrocytic Arc is not due to endogenous transcription, but is dependent on the production of neuronal Arc and accumulates potentially via the recently reported intercellular transfer mechanism through Arc capsids. In conclusion, we found that Arc accumulates within astrocytes in a neuronal activity-dependent manner, which is independent of endogenous astrocytic Arc transcription, therefore highlighting the need to study the purpose of this pool of Arc, especially in learning and memory.

neuroscience↗

bioRxiv2020

A new duck genome reveals conserved and convergently evolved chromosome architectures of birds and mammals

BackgroundDucks have a typical avian karyotype that consists of macro- and microchromosomes, but a pair of much less differentiated ZW sex chromosomes compared to chicken. To elucidate the evolution of chromosome architectures between duck and chicken, and between birds and mammals, we produced a nearly complete chromosomal assembly of a female Pekin duck by combining long-read sequencing and multiplatform scaffolding techniques. ResultsThe major improvement of genome assembly and annotation quality resulted from successful resolution of lineage-specific propagated repeats that fragmented the previous Illumina-based assembly. We found that the duck topologically associated domains (TAD) are demarcated by putative binding sites of the insulator protein CTCF, housekeeping genes, or transitions of active/inactive chromatin compartments, indicating the conserved mechanisms of spatial chromosome folding with mammals. There are extensive overlaps of TAD boundaries between duck and chicken, and also between the TAD boundaries and chromosome inversion breakpoints. This suggests strong natural selection on maintaining regulatory domain integrity, or vulnerability of TAD boundaries to DNA double-strand breaks. The duck W chromosome retains 2.5-fold more genes relative to chicken. Similar to the independently evolved human Y chromosome, the duck W evolved massive dispersed palindromic structures, and a pattern of sequence divergence with the Z chromosome that reflects stepwise suppression of homologous recombination. ConclusionsOur results provide novel insights into the conserved and convergently evolved chromosome features of birds and mammals, and also importantly add to the genomic resources for poultry studies.

genomics↗

bioRxiv2020

Structural basis for repurpose and design of nucleoside drugs for treating COVID-19

SARS-CoV-2 has caused a global pandemic of COVID-19 that urgently needs an effective treatment. Nucleoside analog drugs including favipiravir have been repurposed for COVID-19 despite of unclear mechanism of their inhibition of the viral RNA polymerase (RdRp). Here we report the cryo-EM structures of the viral RdRp in complex with favipiravir and two other nucleoside inhibitor drugs ribavirin and penciclovir. Ribavirin and the ribosylated form of favipiravir share a similar ribose scaffold that is distinct from penciclovir. However, the structures reveal that all three inhibitors are covalently linked to the primer strand in a monophosphate form despite the different chemical scaffolds between favipiravir and penciclovir. Surprisingly, the base moieties of these inhibitors can form mismatched pairs with the template strand. Moreover, in view of the clinical disadvantages of remdesivir mainly associated with its prodrug form, we designed several orally-available remdesivir parent nucleoside derivatives, including VV16 that showed 5-fold more potent than remdesivir in inhibition of viral replication. Together, these results demonstrate an unexpected promiscuity of the viral RNA polymerase and provide a basis for repurpose and design of nucleotide analog drugs for COVID-19. One Sentence SummaryCryo-EM structures of the RNA polymerase of SARS-CoV-2 reveals the basis for repurposing of old nucleotide drugs to treat COVID-19.

biophysics↗

bioRxiv2020

Cell group analysis reveals changes in upper-layer neurons associated with schizophrenia

Genome-wide association studies (GWAS) of schizophrenia (SCZ) have revealed over 100 risk loci. We investigated whether these SCZ-associated variants regulate gene expression by cell type. Using a fully unsupervised deconvolution method, we calculated gene expression by clusters of estimated cell types (cell-groups, CGs). Five CGs emerged in the dorsolateral prefrontal cortices (DLPFC) of 341 donors with and without SCZ. By mapping expression quantitative trait loci (eQTL) per CG, we partitioned the heritability of SCZ risk in GWAS by CGs. CG-specific expressions and eQTLs were replicated in both a deconvoluted bulk tissue data set with a different method and also in sorted-cell expression data. Further, we characterized CG-specific gene differential expression and cell proportion changes in SCZ brains. We found upper-layer neurons in the DLPFC to be associated with SCZ based on enrichment of SCZ heritability in eQTLs, disease-related transcriptional signatures, and decreased cell proportion. Our study suggests that neurons and related anomalous circuits in the upper layers of the DLPFC may have a major contribution to SCZ risk.

genomics↗

bioRxiv2020

Through-scalp deep-brain stimulation in tether-free, naturally-behaving mice with widefield NIR-II illumination

Neural modulation techniques with electricity, light and other forms of energy have enabled the deconstruction of neural circuitry. One major challenge of existing neural modulation techniques is the invasive brain implants and the permanent skull attachment of an optical fiber for modulating neural activity in the deep brain. Here we report an implant-free and tether-free optical neuromodulation technique in deep-brain regions through the intact scalp with brain-penetrant second near-infrared (NIR-II) illumination. Macromolecular infrared nanotransducers for deep-brain stimulation (MINDS) demonstrate exceptional photothermal conversion efficiency of 71% at 1064 nm, the wavelength that minimizes light attenuation by the brain in the entire 400-1700 nm spectrum. Upon widefield 1064-nm illumination >50 cm above the mouse head at a low incident power density of 10 mW/mm2, deep-brain neurons are activated by MINDS-sensitized TRPV1 channels with minimal thermal damage. Our approach could open opportunities for simultaneous neuromodulation of multiple socially interacting animals by remotely irradiating NIR-II light to stimulate each subject individually.

neuroscience↗

bioRxiv2020

LPA/PKD-1 signaling promotes development of arteriolar niche that supports self-renewal of breast cancer stem cells and stemness

Breast cancer stem cells (BCSCs) are essential for cancer growth, metastasis and recurrence. However, the regulatory mechanisms of self-renewal and interactions with the vascular niche within tumor microenvironment are currently under investigation. Here, we demonstrate that BCSCs are enriched within arteriolar niche within the tumor microenvironment of estrogen receptor positive (ER+) BC and bi-directionally interact with arteriolar endothelial cells (ECs). Mechanistically, this interaction is driven by the LPA/PKD-1 signaling pathway, which promotes arteriolar differentiation and self-renewal. Furthermore, this pathway directly promotes stemness features. These findings suggest that targeting LPA/PKD-1 signaling may disrupt the arteriolar niche within the tumor microenvironment and concomitantly eradicate BCSCs, thereby attenuating BC progression.

cancer biology↗

bioRxiv2020

ATF6 aggravates angiogenesis-osteogenesis coupling during ankylosing spondylitis by mediating FGF2 expression in chondrocytes

Although angiogenesis-osteogenesis coupling is important in ankylosing spondylitis (AS), therapeutic agents targeting the vasculature remain elusive. Here, we identified activating transcription factor 6 (ATF6) as an important regulator of angiogenesis in AS patients. Firstly, we found that ATF6 and fibroblast growth factor 2 (FGF2) levels were higher in SKG mice and AS patient cartilage. The pro-angiogenic ability of human chondrocytes was enhanced through activated ATF6-FGF2 axis following long-term stimulation with inflammatory factors, e.g. TNF-, IFN-{gamma} or IL-17. Mechanistically, ATF6 interacted with the FGF2 promotor and promoted its transcription. Treatment with the ATF6 inhibitor Ceapin-A7 inhibited angiogenesis in vitro and angiogenesis-osteogenesis coupling in vivo. ATF6 may aggravate angiogenesis-osteogenesis coupling during AS by mediating FGF2 transcription in chondrocytes, implying that ATF6 represents a promising therapeutic target for AS.

molecular biology↗

bioRxiv2020

Sub-second heat inactivation of coronavirus

Heat treatment denatures viral proteins that comprise the virion, making virus incapable of infecting a host. Coronavirus (CoV) virions contain single-stranded RNA genomes with a lipid envelope and 4 proteins, 3 of which are associated with the lipid envelope and thus are thought to be easily denatured by heat or surfactant-type chemicals. Prior studies have shown that a temperature of as low as 75 {degrees}C and treatment duration of 15 min can effectively inactivate CoV. The applicability of a CoV heat inactivation method greatly depends on the length of time of a heat treatment and the temperature needed to inactivate the virus. With the goal of finding conditions where sub-second heat exposure of CoV can sufficiently inactivate CoV, we designed and developed a simple system that can measure sub-second heat inactivation of CoV. The system is composed of capillary stainless-steel tubing immersed in a temperature-controlled oil bath followed by an ice bath, through which virus solution can be flowed at various speeds. Flowing virus solution at different speeds, along with a real-time temperature monitoring system, allows the virus to be accurately exposed to a desired temperature for various durations of time. Using mouse hepatitis virus (MHV), a beta-coronavirus, as a model system, we identified that 85.2 {degrees}C for 0.48 s exposure is sufficient to obtain > 5 Log10 reduction in viral titer (starting titer: 5 x 107 PFU/mL), and that when exposed to 83.4 {degrees}C for 0.95 s, the virus was completely inactivated (zero titer, > 6 Log10 reduction). IMPORTANCEThree coronaviruses (CoVs) have now caused global outbreaks within the past 20 years, with the COVID19 pandemic caused by SARS-CoV-2 still ongoing. Methods that can rapidly inactivate viruses, especially CoVs, can play critical roles in ensuring public safety and safeguarding personal health. Heat treatment of viruses to inactive them can be an efficient and inexpensive method, with the potential to be incorporated into various human-occupied spaces. In this work, a simple system that can heat-treat viruses for extremely short period was developed and utilized to show that sub-second exposure of CoV to heat is sufficient to inactivate CoV. This opens up the possibility of developing instruments and methods of disinfecting CoV in diverse settings, including rapid liquid disinfection and airborne virus disinfection. The developed method can also be broadly utilized to assess heat sensitivity of viruses other viral pathogens of interest and develop sub-second rapid heat inactivation approaches.

bioengineering↗

bioRxiv2020

Structural basis for repurposing a 100-years-old drug suramin for treating COVID-19

The COVID-19 pandemic by non-stop infections of SARS-CoV-2 has continued to ravage many countries worldwide. Here we report the discovery of suramin, a 100-year-old drug, as a potent inhibitor of the SARS-CoV-2 RNA dependent RNA polymerase (RdRp) through blocking the binding of RNA to the enzyme. In biochemical assays, suramin and its derivatives are at least 20-fold more potent than remdesivir, the currently approved nucleotide drug for COVID-19. The 2.6 [A] cryo-EM structure of the viral RdRp bound to suramin reveals two binding sites of suramin, with one site directly blocking the binding of the RNA template strand and the other site clash with the RNA primer strand near the RdRp catalytic active site, therefore inhibiting the viral RNA replication. Furthermore, suramin potently inhibits SARS-CoV-2 duplication in Vero E6 cells. These results provide a structural mechanism for the first non-nucleotide inhibitor of the SARS-CoV-2 RdRp and a rationale for repurposing suramin for treating COVID-19. One Sentence SummaryDiscovery and mechanism of suramin as potent SARS-CoV-2 RNA polymerase inhibitor and its repurposing for treating COVID-19.

molecular biology↗

bioRxiv2020

MetaFusion: A high-confidence metacaller for filtering and prioritizing RNA-seq gene fusion candidates.

MotivationCurrent fusion detection tools use diverse calling approaches and provide varying results, making selection of the appropriate tool challenging. Ensemble fusion calling techniques appear promising; however, current options have limited accessibility and function. ResultsMetaFusion is a flexible meta-calling tool that amalgamates outputs from any number of fusion callers. Individual caller results are standardized by conversion into the new file type Common Fusion Format (CFF). Calls are annotated, merged using graph clustering, filtered, and ranked to provide a final output of high confidence candidates. MetaFusion consistently achieves higher precision and recall than individual callers on real and simulated datasets, and reaches up to 100% precision, indicating that ensemble calling is imperative for high confidence results. MetaFusion uses FusionAnnotator to annotate calls with information from cancer fusion databases, and is provided with a benchmarking toolkit to calibrate new callers. AvailabilityMetaFusion is freely available at https://github.com/ccmbioinfo/MetaFusion Contactarun.ramani@sickkids.ca Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

In vitro transcription using psychrophilic phage VSW-3 RNA polymerase

RNA research and applications were underpinned by in vitro transcription (IVT), while the RNA impurity resulted from the enzymatic reagents severely impede downstream applications. To improve the stability and purity of synthesized RNA we had characterized a novel single-subunit RNA polymerase (RNAP) encoded by a psychrophilic phage VSW-3 from plateau lake to produce RNA at low temperature. The VSW-3 RNAP is capable of carrying out in vitro RNA synthesis at low temperature (4-25{degrees}C) to reduce RNA degradation and alleviate the need of costly RNase inhibitor. Compared to routinely used T7 RNAP, VSW-3 RNAP provides comparable yield of transcripts, but is insensitive to class II transcription terminators and synthesizes RNA without redundant 3 -cis extension. More importantly, through dot-blot detection with the J2 monoclonal antibody, we found that the RNA products synthesized by VSW-3 RNAP contain much lower amount of or virtually no double-stranded RNA (dsRNA) by-products, which are significant in most T7 RNAP products and may cause severe cellular immune response. Combining these advantages, the VSW-3 RNAP is an advantageous enzyme for IVT, especially to produce RNA for in vivo use.

molecular biology↗

bioRxiv2020

Single-vessel cerebral blood flow fMRI to map blood velocity by phase-contrast imaging

Current approaches to high-field fMRI provide two means to map hemodynamics at the level of single vessels in the brain. One is through changes in deoxyhemoglobin in venules, i.e., blood oxygenation level-dependent (BOLD) fMRI, while the second is through changes in arteriole diameter, i.e., cerebral blood volume (CBV) fMRI. Here we introduce cerebral blood flow (CBF)-fMRI, which uses high-resolution phase-contrast MRI to form velocity measurements of flow and demonstrate CBF-fMRI in single penetrating microvessels across rat parietal cortex. In contrast to the venule-dominated BOLD and arteriole-dominated CBV fMRI signal, the phase-contrast -based CBF signal changes are highly comparable from both arterioles and venules. Thus, we have developed a single-vessel fMRI platform to map the BOLD, CBV, and CBF from penetrating microvessels throughout the cortex. This high-resolution single-vessel fMRI mapping scheme not only enables the vessel-specific hemodynamic mapping in diseased animal models but also presents a translational potential to map vascular dementia in diseased or injured human brains with ultra-high field fMRI. SummaryWe established a high-resolution PC-based single-vessel velocity mapping method using the high field MRI. This PC-based micro-vessel velocity measurement enables the development of the single-vessel CBF-fMRI method. In particular, in contrast to the arteriole-dominated CBV and venule-dominated BOLD responses, the CBF-fMRI shows similar velocity changes in penetrating arterioles and venules in activated brain regions. Thus, we have built a noninvasive single-vessel fMRI mapping scheme for BOLD, CBV, and CBF hemodynamic parameter measurements in animals.

neuroscience↗

bioRxiv2020

scGNN: a novel graph neural network framework for single-cell RNA-Seq analyses

Single-cell RNA-sequencing (scRNA-Seq) is widely used to reveal the heterogeneity and dynamics of tissues, organisms, and complex diseases, but its analyses still suffer from multiple grand challenges, including the sequencing sparsity and complex differential patterns in gene expression. We introduce the scGNN (single-cell graph neural network) to provide a hypothesis-free deep learning framework for scRNA-Seq analyses. This framework formulates and aggregates cell-cell relationships with graph neural networks and models heterogeneous gene expression patterns using a left-truncated mixture Gaussian model. scGNN integrates three iterative multi-modal autoencoders and outperforms existing tools for gene imputation and cell clustering on four benchmark scRNA-Seq datasets. In an Alzheimers disease study with 13,214 single nuclei from postmortem brain tissues, scGNN successfully illustrated disease-related neural development and the differential mechanism. scGNN provides an effective representation of gene expression and cell-cell relationships. It is also a novel and powerful framework that can be applied to scRNA-Seq analyses.

bioinformatics↗

bioRxiv2020

Repopulating Kupffer Cells Originate Directly from Hematopoietic Stem Cells

Kupffer cells (KCs) originate from yolk sac progenitors before birth. Throughout adulthood, they self-maintain independently from the input of circulating monocytes (MOs) at stead state, and are replenished within 2 weeks after having been depleted, but the origin of repopulating KCs in adult remains unclear. The current paradigm dictates that repopulating KCs originate from preexisting KCs or monocytes, but there remains a lack of fate-mapping evidence. In current study, we firstly traced the fate of preexisting KCs and that of monocytic cells with tissue-resident macrophage-specific and monocytic cell-specific fate mapping mouse models, respectively, and found no evidences that repopulating KCs originate from preexisting KCs or MOs. Secondly, we performed genetic lineage tracing to determine the type of progenitor cells involved in response to KC depletion in mice, and found that in response to KC depletion, hematopoietic stem cells (HSCs) proliferated in the bone marrow, mobilized into the blood, adoptively transferred into the liver and differentiated into KCs. Finally, we traced the fate of HSCs in a HSC-specific fate-mapping mouse model, in context of chronic liver inflammation induced by repeated carbon tetrachloride treatment, and confirmed that repopulating KCs originated directly from HSCs. Taken together, these findings provided strong in vivo fate-mapping evidences that repopulating KCs originate directly from Hematopoietic stem cells not from preexisting KCs or from MOs. SignificanceThere is a standing controversy in the field regarding the cellular origin of repopulating macrophages. This paper provides strong in vivo fate-mapping evidences that repopulating KCs originate directly from hematopoietic stem cells not from preexisting KCs or from MOs, which presenting a completely novel understanding of the cellular origin of repopulating Kupffer Cells and shedding light on the divergent roles of KCs in liver homeostasis and diseases.

cell biology↗