Biology subjects

Zhu, J.

Publications and source records attributed to Zhu, J..

At least 541 records · Page 30Linked to original sources

bioRxiv2020

Phenotype Prediction using a Tensor Representation and Deep Learning from Data Independent Acquisition Mass Spectrometry

A novel approach for phenotype prediction is developed for mass spectrometric data. First, the data-independent acquisition (DIA) mass spectrometric data is converted into a novel file format called "DIA tensor" (DIAT) which contains all the peptide precursors and fragments information and can be used for convenient DIA visualization. The DIAT format is fed directly into a deep neural network to predict phenotypes without the need to identify peptides or proteins. We applied this strategy to a collection of 102 hepatocellular carcinoma samples and achieved an accuracy of 96.8% in classifying malignant from benign samples. We further applied refined model to 492 samples of thyroid nodules to predict thyroid cancer; and achieved a predictive accuracy of 91.7% in an independent cohort of 216 test samples. In conclusion, DIA tensor enables facile 2D visualization of DIA proteomics data as well as being a new approach for phenotype prediction directly from DIA-MS data.

bioinformatics↗

bioRxiv2020

Profiling the immune vulnerability landscape of the 2019 Novel Coronavirus

The outbreak of the 2019 Novel Coronavirus (SARS-CoV-2) rapidly spread from Wuhan, China to more than 150 countries, areas, or territories, causing staggering numbers of infections and deaths. In this study, bioinformatics analyses were performed on 5,568 complete genomes of SARS-CoV-2 virus to predict the T cell and B cell immunogenic epitopes of all viral proteins, which formed a systematic immune vulnerability landscape of SARS-CoV-2. The immune vulnerability and genetic variation profiles of SARS-CoV were compared with those of SARS-CoV and MERS-CoV. In addition, a web portal was developed to broadly share the data and results as a resource for the research community. Using this resource, we showed that genetic variations in SARS-CoV-2 are associated with loss of B cell immunogenicity, an increase in CD4+ T cell immunogenicity, and a minimum loss in CD8+ T cell immunogenicity, indicating the existence of a curious correlation between SARS-CoV-2 genetic evolutions and the immunity pressure from the host. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic/vaccine development and mechanistic research.

bioinformatics↗

bioRxiv2020

Integrated profiling of single cell epigenomic and transcriptomic landscape of Parkinson's disease mouse brain

Parkinsons disease (PD) is a neurodegenerative disease leading to the impairment of execution of movement. PD pathogenesis has been largely investigated, but either restricted in bulk level or at certain cell types, which failed to capture cellular heterogeneity and intrinsic interplays among distinct cell types. To overcome this, we applied single-nucleus RNA-seq and single cell ATAC-seq on cerebellum, midbrain and striatum of PD mouse and matched control. With 74,493 cells in total, we comprehensively depicted the dysfunctions under PD pathology covering proteostasis, neuroinflammation, calcium homeostasis and extracellular neurotransmitter homeostasis. Besides, by multi-omics approach, we identified putative biomarkers for early stage of PD, based on the relationships between transcriptomic and epigenetic profiles. We located certain cell types that primarily contribute to PD early pathology, narrowing the gap between genotypes and phenotypes. Taken together, our study provides a valuable resource to dissect the molecular mechanism of PD pathogenesis at single cell level, which could facilitate the development of novel methods regarding diagnosis, monitoring and practical therapies against PD at early stage.

cell biology↗

bioRxiv2020

Molecular and cellular heterogeneity of gastric cancer explained by methylation-driven key regulators

Gastric cancer (GC) is a heterogeneous disease of diverse genetic, genomic, and epigenetic alterations. Tumor microenvironment (TME) also contributes to the heterogeneity of GC. To investigate GC heterogeneity, we developed an Integrative Sequential Causality Test (ISCT) to identify key regulators of GC by integrating DNA methylation, copy number variation, and transcriptomic data. Applying ISCT to three GC cohorts containing methylation, CNV and transcriptomic data, 11 common methylation-driven key regulators (ADHFE1, CDO1, CRYAB, FSTL1, GPT, PKP3, PTPRCAP, RAB25, RHOH, SFN, and SORD) were identified. Based on these 11 genes, gastric tumors were clustered into 3 clusters which were associated with known molecular subtypes, Lauren classification, tumor stage, and patient survival, suggesting significance of the methylation-driven key regulators in molecular and histological heterogeneity of GC. We further showed that chemotherapy benefit was different in the 3 GC clusters and varied depending on the tumor stage. Both immune/stromal proportions in TME and tumor cell genomic variations contributed to expression variations of the 11 methylation-driven key regulators and to the GC heterogeneity.

genomics↗

bioRxiv2020

Single cell atlas of trisomy 21 cerebral cortex

Down syndrome (DS) is one of the most common human birth defects caused by trisomy 21 (T21), leading to a variety of cognitive impairments. The cellular composition of human brain has been explored using single cell RNA sequencing in both physiological and pathological conditions. However, the cellular heterogeneity of human brain with chromosome aneuploidy is largely unknown. Here, we profiled the transcriptome of 36046 cells in cerebral cortex of T21 human fetus, covering frontal lobe, parietal lobe, occipital lobe and temporal lobe. Intriguingly, we detected several genes positively associated with neurons maturation was dysregulated in T21 frontal cortex (HIC2, POU2F2, ZGLP1 and FOXK1). To share, explore and utilized the data resources of T21 cerebral cortex, we developed a comprehensive platform named T21atlas, composing of two functional modules (T21cluster and T21talk). Overall, our study provides, as far as we know, the first single cell atlas for T21 cerebral cortex, which could promote our understanding of the molecular mechanism of DS at an unprecedented resolution and could potentially facilitate the development of novel clinical therapeutics against T21.

neuroscience↗

bioRxiv2020

Overcoming Genetic Drop-outs in Variants-based Lineage Tracing from Single-cell RNA Sequencing Data

Lineage tracing provides key insights into the fates of individual cells in complex tissues. Recent works on lineage reconstruction based on the single-cell expression data are suitable for short time frames while tracing lineage based on more stable genetic markers is needed for studies that span time scales over months or years. However, variant calling from the single-cell RNA sequencing (scRNA-Seq) data suffers from "genetic drop-outs", including low coverage and allelic bias, which presents significant obstacles for lineage reconstruction. Prior studies focused only on mitochondrial (chrM) variants and need to be expanded to the whole genome to capture more variants with clearer physiological meaning. However, non-chrM variants suffer even more severe drop-outs than chrM variants, although drop-outs affect all variants. We developed strategies to overcome genetic drop-outs in scRNA-Seq-derived whole genomic variants for accurate lineage tracing, and we developed SClineger, a Bayesian Hierarchical model, to implement our approach. Our validation analyses on a series of sequencing protocols demonstrated the necessity of correction for genetic drop-outs and consideration of variants in the whole genome, and also showed the improvement that our approach provided. We showed that genetic-based lineage tracing is applicable for single-cell studies of both tumors and non-tumor tissues using our approach, and can reveal novel biological insights not afforded by expressional analyses. Interestingly, we showed that cells of various lineages grew under the spatial constraints of their respective organs during the developmental process. Overall, our work provides a powerful tool that can be applied to the large amounts of already existing scRNA-Seq data to construct the lineage histories of cells and derive new knowledge.

bioinformatics↗

bioRxiv2019

Phase separation-mediated formation of condensed GIT/PIX enzyme complex module for compartmentalized signaling

Cells compartmentalize enzymes for broad physiological functions such as efficient metabolic reactions and spatiotemporally controlled signaling. A given enzyme or enzyme complex can participate in multiple cellular processes in response to different signal inputs by forming different cellular compartments. Here, we demonstrate that association of GIT1 and {beta}-Pix, a pair of GTPase regulatory enzymes involved in diverse cellular processes, leads to autonomous condensation of the complex via phase separation without additional scaffolding molecules. The atomic structure of the GIT/PIX complex reveals the molecular basis governing the phase separation-mediated condensation of the GIT1/{beta}-Pix complex. Importantly, the GIT1/{beta}-Pix condensates can function as a versatile modular membrane-less organelle- like structure for distinct cellular compartmentalization by binding to upstream proteins such as Paxillin in focal adhesions, Shank3 in neuronal synapses, and Scribble in cellular junctions. Thus, phase separation-mediated formation of condensed enzyme complexes provides a powerful way of dynamically concentrating limited amounts of cooperating enzymes to specific cellular compartments for optimal signaling.

cell biology↗

bioRxiv2019

Mechanics of multi-centrosomal clustering in bipolar mitotic spindles

To segregate chromosomes in mitosis, cells assemble mitotic spindle, a molecular machine with centrosomes at two opposing cell poles and chromosomes at the equator. Microtubules and molecular motors connect the poles to kinetochores, specialized protein assemblies on the centromere regions of the chromosomes. Bipolarity of the spindle is crucial for the proper cell division, and two centrosomes in animal cells naturally become two spindle poles. Cancer cells are often multi-centrosomal, yet they are able to assemble bipolar spindles by clustering centrosomes into two spindle poles. Mechanisms of this clustering are debated. In this study, we computationally screen effective forces between a) centrosomes, b) centrosomes and kineto-chores, c) centrosomes and chromosome arms, d) centrosomes and cell cortex, to understand mechanics that determines three-dimensional spindle architecture. To do this, we use stochastic Monte Carlo search for stable mechanical equilibria in effective energy landscape of the spindle. We find that the following conditions have to be met to robustly assemble the bipolar spindle in a multi-centrosomal cell: 1) strengths of centrosomes attraction to each other and to the cell cortex have to be proportional to each other; 2) strengths of centrosomes attraction to kinetochores and repulsion from the chromosome arms have to be proportional to each other. We also find that three other spindle configurations emerge if these conditions are not met: a) collapsed, b) monopolar, c) multipolar spindles, and the computational screen reveal mechanical conditions for these abnormal spindles. Significance statementTo segregate chromosomes, cells assemble bipolar mitotic spindle. Multiple mechanical forces generated by microtubules and molecular motors in the spindle govern the spindle architecture, but it is unclear what force balances support the bipolarity of the spindle. This problem is especially difficult and important in cancer cells, which often have multiple centrosomes that somehow are able to cluster into two spindle poles. By using stochastic energy minimization in an effective energy landscape of the spindle and computationally screening forces, we find mechanical conditions for mono-, multi- and bi-polar spindles. We predict how microtubule and motor parameters have to be regulated in mitosis in multi-centrosomal cells.

cell biology↗

bioRxiv2019

Inositol pyrophosphates promote the interaction of SPX domains with the coiled-coil motif of PHR transcription factors to regulate plant phosphate homeostasis.

Phosphorus is an essential nutrient taken up by organisms in the form of inorganic phosphate (Pi). Eukaryotes have evolved sophisticated Pi sensing and signalling cascades, enabling them to maintain cellular Pi concentrations. Pi homeostasis is regulated by inositol pyrophosphate signalling molecules (PP-InsPs), which are sensed by SPX-domain containing proteins. In plants, PP-InsP bound SPX receptors inactivate Myb coiled-coil (MYB-CC) Pi starvation response transcription factors (PHRs) by an unknown mechanism. Here we report that a InsP8 - SPX complex targets the plant-unique CC domain of PHRs. Crystal structures of the CC domain reveal an unusual four-stranded anti-parallel arrangement. Interface mutations in the CC domain yield monomeric PHR1, which is no longer able to bind DNA with high affinity. Mutation of conserved basic residues located at the surface of the CC domain disrupt interaction with the SPX receptor in vitro and in planta, resulting in constitutive Pi starvation responses. Together, our findings suggest that InsP8 regulates plant Pi homeostasis by controlling the oligomeric state and hence the promoter binding capability of PHRs via their SPX receptors. (173 words)

plant biology↗

bioRxiv2019

Single cell atlas of domestic pig brain illuminates the conservation and divergence of cell types at spatial and species levels

Domestic pig (Sus scrofa domesticus) has drawn much attention from researchers worldwide due to its implications in evolutionary biology, regenerative medicine and agriculture. The brain atlas of Homo sapiens (primate), Mus musculus (rodent), Danio rerio (fish) and Drosophila melanogaster (insect) have been constructed at single cell resolution, however, the cellular compositions of pig brain remain largely unexplored. In this study, we investigated the single-cell transcriptomic profiles of five distinct regions of domestic pig brain, from which we identified 21 clusters corresponding to six major cell types, characterized by unique spectrum of gene expression. By spatial comparison, we identified cell types enriched or depleted in certain brain regions. Inter-species comparison revealed cell-type similarities and divergences in hypothalamus between mouse and pig, providing invaluable resources for the evolutionary exploration of brain functions at single cell level. Besides, our study revealed cell types and molecular pathways closely associated with several diseases (obesity, anorexia, bulimia, epilepsy, intellectual disability, and autism spectrum disorder), bridging the gap between gene mutations and pathological phenotypes, which might be of great use to the development precise therapies against neural system disorders. Taken together, we reported, so far as we know, the first single cell brain atlas of Sus scrofa domesticus, followed by comprehensive comparisons across brain region and species, which could throw light upon future evo-devo, regenerative medicine, and agricultural studies.

bioinformatics↗

bioRxiv2019

Integrative genomic and epigenomic analyses identify a distinct role of c-Myc and L-Myc for lineage determination in small cell lung cancer

Comprehensive genomic analyses of small cell lung cancer (SCLC), the most aggressive form of lung cancer, have revealed near universal loss of tumor suppressors (RB1 and TP53) and frequent genomic amplification of all three MYC family members. The amplification of each Myc family member is mutually exclusive; hence it had been long suggested that they are functionally equivalent. However, their expression has more recently been associated with specific neuroendocrine markers and distinct histopathology. In this study, we explored a novel role of c-Myc and L-Myc as lineage determining factors contributing to SCLC molecular subtypes and histology. Integrated analyses of a gene regulatory network generated from mRNA expression of primary SCLC tumor and chromatin state profiling of SCLC cell lines showed that Myc family members impart distinct transcriptional programs associated with lineage state; wherein the L-Myc signature was enriched for neuronal pathways while the c-Myc signature was enriched for Notch signaling and epithelial-to-mesenchymal transition. We investigated the functional redundancy and distinction of c-Myc and L-Myc, and noted the insufficiency of L-Myc to induce lineage switch in contrast to the potential of c-Myc to induce trans-differentiation. c-Myc rewires the Myc-accessible landscape and activates neuron al repressor, Rest to mediate transition from ASCL1-SCLC to NeuroD1-SCLC characterized by distinct LCNEC-like histopathology. Collectively, our findings reveal a previously undescribed role of historically defined general oncogenes, c-Myc and L-Myc, for regulating lineage plasticity across molecular subtypes as well as histological subclasses.

cancer biology↗

bioRxiv2019

Mapping Human Pluripotent Stem Cell Derived Erythroid Differentiation by Single-Cell Transcriptome Analysis

There is an imbalance between the supply and demand of functional red blood cells (RBCs) in clinical applications. This imbalance can be addressed by regenerating RBCs using several in vitro methods. Induced pluripotent stem cells (iPSCs) can handle the low supply of cord blood and the ethical issues in embryonic stem cell research and provide a promising strategy to eliminate immune rejection. However, no complete single-cell level differentiation pathway exists for the iPSC-derived RBC differentiation system. In this study, we used iPSC line BC1 to establish a RBCs regeneration system. The 10x genomics single-cell transcriptome platform was used to map the cell lineage and differentiation trajectories on day 14 of the regeneration system. We observed that iPSCs differentiation was not synchronized during embryoid body (EB) culture. The cells (day 14) mainly consisted of mesodermal and various blood cells, similar to the yolk sac hematopoiesis. We identified six cell classifications and characterized the regulatory transcription factors (TFs) networks and cell-cell contacts underlying the system. iPSCs undergo two transformations during the differentiation trajectory, accompanied by the dynamic expression of cell adhesion molecules and estrogen-responsive genes. We identified different stages of erythroid cells such as burst-forming unit erythroid (BFU-E) and orthochromatic erythroblasts (ortho-E) and found that the regulation of TFs (e.g., TFDP1 and FOXO3) is erythroid-stage specific. Immune erythroid cells were identified in our system. This study provides systematic theoretical guidance for optimizing the iPSCs-derived RBCs differentiation system, and this system is a useful model for simulating in vivo hematopoietic development and differentiation.

developmental biology↗

bioRxiv2019

Active monomer RTR-1 derived from the root of Rhodomyrtus tomentosa induces apoptosis in gastric carcinoma cells by inducing ER stress and inhibiting the STAT3 signalling pathway

ObjectiveRhodomyrtus tomentosa, a flowering plant belonging to the Myrtaceae family, is considered an antitumour substance with versatile biological and pharmacological activities. And RTR-1 is an active monomer purified from the root of Rhodomyrtus tomentosa. However, the detail of the mechanisms of anti-cancer activity of RTR-1 remains to be elucidated and the effect on gastric cancer cells is unknown. MethodsCell proliferation was determined by MTT and clone formation assay. The effect of RTR-1 on cell cycle and apoptosis was analyzed utilizing flow cytometry, respectively. Moreover, western blotting was used to detect the expression of cell cycle- and apoptosis-related protein. ResultsBased on MTT and clone formation assay, we noticed that RTR-1 inhibited the proliferation of gastric carcinoma (BGC823 and SGC7901) cells in a dose- and time-dependent manner. Furthermore, the results of flow cytometry and western blotting showed that RTR-1 induced cell cycle arrest in the G2/M phase through the ATM-Chk2-p53-p21 signalling pathway and induced cell apoptosis by inhibiting the signal transducers and activators of transcription 3 (STAT3) pathway and activating the endoplasmic reticulum stress (ER stress) pathway. ConclusionTaken together, these results demonstrate that RTR-1 induces cell cycle arrest and promotes apoptosis in gastric carcinoma, indicating its potential application for gastric cancer therapy.

cancer biology↗

bioRxiv2019

Secure data storage on DNA hard drives

DNA is emerging as a novel material for digital data storage. The two main challenges are efficient encoding and data security. Here, we develop an approach that allows for writing and erasing data by relying solely on Watson-Crick base pairing of short oligonucleotides to single-stranded DNA overhangs located along a long double-stranded DNA hard drive (DNA-HD). Our enzyme-free system enables fast synthesis-free data writing with predetermined building blocks. The use of DNA base pairing allows for secure encryption on DNA-HDs that requires a physical key and nanopore sensing for decoding. The system is suitable for miniature integration for an end-to-end DNA storage device. Our study opens a novel pathway for rewritable and secure data storage with DNA. One Sentence SummaryStoring digital information on molecules along DNA hard drives for rewritable and secure data storage.

biophysics↗

bioRxiv2019

MACS: Rapid aqueous clearing system for three-dimensional mapping of intact organs

Tissue optical clearing techniques have provided important tools for large-volume imaging. Aqueous-based clearing methods are known for good fluorescence preservation and scalable size maintenance, but are limited by either long incubation time, or insufficient clearing performance, or requirements for specialized devices. Additionally, due to the use of high concentration organic solvents or detergents, few clearing methods are compatible with lipophilic dyes while maintaining high clearing performance. To address these issues, we developed a rapid, highly efficient aqueous clearing method with robust compatibility, termed m-xylylenediamine (MXDA)-based Aqueous Clearing System (MACS). MACS can render intact organs highly transparent in a fairly short time and possesses ideal compatibility with multiple probes, especially for lipophilic dyes. Using MACS, we cleared the adult mouse brains within only 2.5 days for three-dimensional (3D) imaging of the neural structures labelled by various techniques. Combining MACS with DiI labelling, we visualized the vascular structures of various organs. MACS provides a useful tool for 3D mapping of intact tissues and is expected to facilitate morphological, physiological and pathological studies of various organs.

bioengineering↗

bioRxiv2019

Over 50000 metagenomically assembled draft genomes for the human oral microbiome reveal new taxa

The oral cavity of each person is home for hundreds of bacterial species. While taxa for oral diseases have been well studied using culture-based as well as amplicon sequencing methods, metagenomic and genomic information remain scarce compared to the fecal microbiome. Here we provide metagenomic shotgun data for 3346 oral metagenomics samples, and together with 808 published samples, assemble 56,213 metagenome-assembled genomes (MAGs). 64% of the 3,589 species-level genome bins contained no publicly available genomes, others with only a handful. The resulting genome collection is representative of samples around the world and across physiological conditions, contained many genomes from Candidate phyla radiation (CPR) which lack monoculture, and enabled discovery of new taxa such as a family within the Acholeplasmataceae order. New biomarkers were identified for rheumatoid arthritis or colorectal cancer, which would be more convenient than fecal samples. The large number of metagenomic samples also allowed assembly of many strains from important oral taxa such as Porphyromonas and Neisseria. Predicted functions enrich in drug metabolism and small molecule synthesis. Thus, these data lay down a genomic framework for future inquiries of the human oral microbiome.

microbiology↗

bioRxiv2019

In-Depth Characterization and Validation in BRG1-Mutant Lung Cancers Define Novel Catalytic Inhibitors of SWI/SNF Chromatin Remodeling

Members of the ATP-dependent SWI/SNF chromatin remodeling complexes are among the most frequently mutated genes in cancer, suggesting their dysregulation plays a critical role. The synthetic lethality between SWI/SNF catalytic subunits BRM/SMARCA2 and BRG1/SMARCA4 has instigated great interest in targeting BRM. Here we have performed a critical and in-depth investigation of novel dual inhibitors (BRM011 and BRM014) of BRM and BRG1 in order to validate their utility as chemical probes of SWI/SNF catalytic function, while obtaining insights into the therapeutic potential of SWI/SNF inhibition. In corroboration of on-target activity, we discovered compound resistant mutations through pooled screening of BRM variants in BRG1-mut cancer cells. Strikingly, genome-wide transcriptional and chromatin profiling (ATAC-Seq) provided further evidence of pharmacological perturbation of SWI/SNF chromatin remodeling as BRM011 treatment induced specific changes in chromatin accessibility and gene expression similar to genetic depletion of BRM. Finally, these compounds have the capacity to inhibit the growth of tumor-xenografts, yielding important insights into the feasibility of developing BRM/BRG1 ATPase inhibitors for the treatment of BRG1-mut lung cancers. Overall, our studies not only establish the feasibility of inhibiting SWI/SNF catalytic function, providing a framework for SWI/SNF therapeutic targeting, but have also yielded successful elucidation of small-molecule inhibitors that will be of importance in probing SWI/SNF function in various disease contexts.

cancer biology↗

bioRxiv2019

Statistical Analysis of Spatial Expression Pattern for Spatially Resolved Transcriptomic Studies

Recent development of various spatially resolved transcriptomic techniques has enabled gene expression profiling on complex tissues with spatial localization information. Identifying genes that display spatial expression pattern in these studies is an important first step towards characterizing the spatial transcriptomic landscape. Detecting spatially expressed genes requires the development of statistical methods that can properly model spatial count data, provide effective type I error control, have sufficient statistical power, and are computationally efficient. Here, we developed such a method, SPARK. SPARK directly models count data generated from various spatial resolved transcriptomic techniques through generalized linear spatial models. With a new efficient penalized quasi-likelihood based algorithm, SPARK is scalable to data sets with tens of thousands of genes measured on tens of thousands of samples. Importantly, SPARK relies on newly developed statistical formulas for hypothesis testing, producing well-calibrated p-values and yielding high statistical power. We illustrate the benefits of SPARK through extensive simulations and in-depth analysis of four published spatially resolved transcriptomic data sets. In the real data applications, SPARK is up to ten times more powerful than existing approaches. The high power of SPARK allows us to identify new genes and pathways that reveal new biology in the data that otherwise cannot be revealed by existing approaches.

genomics↗