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Biology subjects

Zhu, Q.

Publications and source records attributed to Zhu, Q..

At least 199 records · Page 11Linked to original sources

Visualizing synaptic plasticity in vivo by large-scale imaging of endogenous AMPA receptors

Elucidating how synaptic molecules such as AMPA receptors mediate neuronal communication and tracking their dynamic expression during behavior is crucial to understand cognition and disease, but current technological barriers preclude large-scale exploration of molecular dynamics in vivo. We have developed a suite of innovative methodologies that break through these barriers: a new knockin mouse line with fluorescently tagged endogenous AMPA receptors, two-photon imaging of hundreds of thousands of labeled synapses in behaving mice, and computer-vision-based automatic synapse detection. Using these tools, we can longitudinally track how the strength of synapses changes during behavior. We used this approach to generate an unprecedentedly detailed spatiotemporal map of synaptic plasticity underlying sensory experience. More generally, these tools can be used as an optical probe capable of measuring functional synapse strength across entire brain areas during any behavioral paradigm, describing complex system-wide changes with molecular precision.

neuroscience↗

Characterizing Sleep-Wake Circadian Rhythm Consolidation in Early Childhood and Its Association with Motor Development Using Actigraphy

BackgroundWearable devices have been widely used in clinical studies to study daily activity patterns, but the analysis remains the major obstacle for researchers. Study ObjectiveThis study proposed a novel method to characterize sleep-activity rhythms using actigraphy and further used it to describe early childhood daily rhythm formation and examine its association with physical development. MethodsWe developed a machine learning-based Penalized Multi-band Learning (PML) algorithm to sequentially infer dominant periodicities based on Fast Fourier Transform (FFT) and further characterize daily rhythms. We implemented and applied the algorithm to Actiwatch data collected from a 262 healthy infant cohort at 6-, 12-, 18-, and 24-month old, with 159, 101, 111, and 141 subjects participating at each time point respectively. Autocorrelation analysis and Fishers test for harmonic analysis with Bonferroni correction were applied to compare with PML. The association between activity rhythm features and early childhood motor development, assessed by Peabody Developmental Motor Scales-Second Edition (PDMS-2), was studied through linear regression. ResultsPML results showed that 1-day periodicity is most dominant at 6 and 12 months, whereas 1-day, 1/3-day, and 1/2-day periodicities are most dominant at 18 and 24 months. These periodicities are all significant in Fishers test, with 1/4-day periodicity also significant at 12 months. Autocorrelation effectively detected 1-day periodicity but not others. At 6 months, PDMS-2 is associated with assessment seasons. At 12 months, PDMS-2 is associated with seasons and FFT signals at 1/3-day periodicity (P<.001) and 1/2-day periodicity (P=.04). In particular, subcategories of stationary, locomotion, and gross motor are associated with FFT signals at 1/3-day periodicity (P<.001). ConclusionsThe proposed PML algorithm can effectively conduct circadian rhythm analysis using time-series wearable device data. Application of the method effectively characterized sleep-wake rhythm development and identified the association between daily rhythm formation and motor development during early childhood.

neuroscience↗

iterb-PPse: Identification of transcriptional terminators in bacterial by incorporating nucleotide properties into PseKNC

Terminator is a DNA sequence that give the RNA polymerase the transcriptional termination signal. Identifying terminators correctly can optimize the genome annotation, more importantly, it has considerable application value in disease diagnosis and therapies. However, accurate prediction methods are deficient and in urgent need. Therefore, we proposed a prediction method "iterb-PPse" for terminators by incorporating 47 nucleotide properties into PseKNC- I and PseKNC- II and utilizing Extreme Gradient Boosting to predict terminators based on Escherichia coli and Bacillus subtilis. Combing with the preceding methods, we employed three new feature extraction methods K-pwm, Base-content, Nucleotidepro to formulate raw samples. The two-step method was applied to select features. When identifying terminators based on optimized features, we compared five single models as well as 16 ensemble models. As a result, the accuracy of our method on benchmark dataset achieved 99.88%, higher than the existing state-of-the-art predictor iTerm-PseKNC in 100 times five-fold cross-validation test. Its prediction accuracy for two independent datasets reached 94.24% and 99.45% respectively. For the convenience of users, a software was developed with the same name on the basis of "iterb-PPse". The open software and source code of "iterb-PPse" are available at https://github.com/Sarahyouzi/iterb-PPse.

bioinformatics↗

Topological Dependent Abundance of Spontaneous DNA Damage in Single Human Cells

In the studies of single-cell genomics, the large endeavor has been focused on the detection of the permanent changes in the genome. On the other hand, spontaneous DNA damage frequently occurs and results in transient single-stranded changes to the genome until they are repaired. So far, successful profiling of these dynamic changes has not been demonstrated by single-cell whole-genome amplification methods. Here we reported a novel single-cell WGA method: Linearly Produced Semiamplicon based Split Amplification Reaction (LPSSAR), which allows, for the first time, the genome-wide detection of the DNA damage associated single nucleotide variants (dSNVs) in single human cells. The sequence-based detection of dSNVs allows the direct characterization of the major damage signature that occurred in human cells. In the analysis of the abundance of dSNVs along the genome, we observed two modules of dSNV abundance, instead of a homogeneous abundance of dSNVs. Interestingly, we found that the two modules are associated with the A/B topological compartments of the genome. This result suggests that the genome topology directly influences genome stability. Furthermore, with the detection of a large number of dSNVs in single cells, we showed that only under a stringent filtering condition, can we distinguish the de novo mutations from the dSNVs and achieve a reliable estimation of the total level of de novo mutations in a single cell.

genomics↗

Transcriptional regulatory network controlling the ontogeny of hematopoietic stem cells

Hematopoietic stem cell (HSC) ontogeny is accompanied by dynamic changes in gene regulatory networks. We performed RNA-Seq and histone mark ChIP-Seq to define the transcriptomes and epigenomes of cells representing key developmental stages of HSC ontogeny in the mouse. The five populations analyzed were embryonic day 10.5 (E10.5) endothelium and hemogenic endothelium from the major arteries (dorsal aorta, umbilical and vitelline), an enriched population of pre-hematopoietic stem cells (pre-HSCs), fetal liver HSCs, and adult bone marrow HSCs. We observed dynamic and combinatorial epigenetic changes that mark regulatory DNA sequences including gene promoters and enhancers. Using epigenetic signatures, we identified enhancers for each developmental stage. Only 12% of enhancers are primed, and 78% are active, suggesting the vast majority of enhancers are established de novo at the developmental stages where they are required to control their target genes, without prior priming in earlier stages. We constructed developmental-stage-specific transcriptional regulatory networks during HSC ontogeny by linking enhancers and predicted bound transcription factors to their target promoters using a novel computational algorithm. Our computational analyses predicted known transcriptional regulators for the endothelial-to-hematopoietic transition, validating our overall approach, and identified putative novel transcription factors whose regulon activities correlate with the emergence of pre-HSCs. We validated roles for the broadly expressed transcription factors SP3 and MAZ in arterial hemogenic endothelium. Our data and computational analyses provide a useful resource for uncovering regulators of HSC formation.

developmental biology↗

Developmental trajectory of pre-hematopoietic stem cell formation fromendothelium

Hematopoietic stem and progenitor cells (HSPCs) differentiate from hemogenic endothelial (HE) cells through an endothelial to hematopoietic cell transition (EHT). Newly formed HSPCs accumulate in intra-arterial clusters (IACs) before colonizing the fetal liver. To examine the cell and molecular transitions during the EHT, and the heterogeneity of HSPCs within IACs, we profiled [~]37,000 cells from the caudal arteries of embryonic day 9.5 (E9.5) to E11.5 mouse embryos by single-cell transcriptome and chromatin accessibility sequencing. We identified an intermediate developmental stage prior to HE that we termed pre-HE, characterized by increased accessibility of chromatin enriched for SOX, FOX, GATA, and SMAD motifs. A developmental bottleneck separates pre-HE from HE, with RUNX1 dosage regulating the efficiency of the pre-HE to HE transition. Distinct developmental trajectories within IAC cells result in two populations of CD45+ HSPCs; an initial wave of lympho-myeloid-biased progenitors, followed by precursors of hematopoietic stem cells (pre-HSCs).

developmental biology↗

scATAC-pro: a comprehensive workbench for single-cell chromatin accessibility sequencing data

Single cell chromatin accessibility sequencing (scCAS) has become a powerful technology for understanding epigenetic heterogeneity of complex tissues. The development of several experimental protocols has led to a rapid accumulation of scCAS data. In contrast, there is a lack of open-source software tools for comprehensive processing, analysis and visualization of scCAS data generated using all existing experimental protocols. Here we present scATAC-pro for quality assessment, analysis and visualization of scCAS data. scATAC-pro provides flexible choice of methods for different data processing and analytical tasks, with carefully curated default parameters. A range of quality control metrics are computed for several key steps of the experimental protocol. scATAC-pro generates summary reports for both quality assessment and downstream analysis. It also provides additional utility functions for generating input files for various types of downstream analyses and data visualization. With the rapid accumulation of scCAS data, scATAC-pro will facilitate studies of epigenomic heterogeneity in healthy and diseased tissues.

bioinformatics↗

Learning Your Heart Actions From Pulse: ECG Waveform Reconstruction From PPG

This paper studies the relation between electrocardiogram (ECG) and photoplethysmogram (PPG) and infers the waveform of ECG via the PPG signals that can be obtained from affordable wearable Internet-of-Things (IoT) devices for mobile health. In order to address this inverse problem, a transform is proposed to map the discrete cosine transform (DCT) coefficients of each PPG cycle to those of the corresponding ECG cycle based on our proposed cardiovascular signal model. The proposed method is evaluated with different morphologies of the PPG and ECG signals on three benchmark datasets with a variety of combinations of age, weight, and health conditions using different training setups. Experimental results show that the proposed method can achieve a high prediction accuracy greater than 0.92 in averaged correlation for each dataset when the model is trained subject-wise. With a signal processing and learning system that is designed synergistically, we are able to reconstruct ECG signals by exploiting the relation of these two types of cardiovascular measurement. The reconstruction capability of the proposed method can enable low-cost ECG screening from affordable wearable IoT devices for continuous and long-term monitoring. This work may open up a new research direction to transfer the understanding of the clinical ECG knowledge base to build a knowledge base for PPG and data from wearable devices.

bioinformatics↗

Genome-wide association analyses identify variants in IRF4 associated with Acute Myeloid Leukemia and Myelodysplastic Syndrome susceptibility

The role of common genetic variation in susceptibility to acute myeloid leukemia (AML), and myelodysplastic syndrome (MDS), a group of rare clonal hematologic disorders characterized by dysplastic hematopoiesis and high mortality, remains unclear. We performed AML and MDS genome-wide association studies (GWAS) in the DISCOVeRY-BMT cohorts (2309 cases and 2814 controls). Association analysis based on subsets (ASSET) was used to conduct a summary statistics SNP-based analysis of MDS and AML subtypes. For each AML and MDS case and control we used PrediXcan to estimate the component of gene expression determined by their genetic profile and correlate this imputed gene expression level with risk of developing disease in a transcriptome-wide association study (TWAS). ASSET identified an increased risk for de novo AML and MDS (OR=1.38, 95% CI, 1.26-1.51, Pmeta=2.8x10-12) in patients carrying the T allele at rs12203592 in Interferon Regulatory Factor 4 (IRF4), a transcription factor which regulates myeloid and lymphoid hematopoietic differentiation. Our TWAS analyses showed increased IRF4 gene expression is associated with increased risk of de novo AML and MDS (OR=3.90, 95% CI, 2.36-6.44, Pmeta =1.0x10-7). The identification of IRF4 by both GWAS and TWAS contributes valuable insight on the role of genetic variation in AML and MDS susceptibility.

genomics↗

Golgi-localized PAQR4 mediates Anti-apoptotic Ceramidase Activity in Breast Cancer

The metabolic network of sphingolipids plays important roles in cancer biology. Prominent sphingolipids include ceramides and sphingosine-1-phosphate that regulate multiple aspects of growth, apoptosis and cellular signaling. Although many significant enzymatic regulators of the sphingolipid pathway have been described in detail, the list is currently incomplete. Here, we applied a systemic approach to identify and molecularly define progestin and adipoQ receptor family member IV (PAQR4) as a Golgi-localized ceramidase. We find PAQR4 to be [~]5 fold upregulated in breast cancer compared to matched control tissue and that its overexpression correlate with disease-specific survival rates in breast cancer. PAQR4 is a seven transmembrane protein, and depletion of PAQR4 leads to cellular apoptosis through accumulation of ceramides. Our findings establish PAQR4 as Golgi-localized ceramidase required for cellular growth in breast cancer.

cancer biology↗

Genome-wide identification and transcriptomic analysis of microRNAs across various amphioxus organs using deep sequencing

Amphioxus is the closest living invertebrate proxy of the vertebrate ancestor. Systematic gene identification and expression profile analysis of amphioxus organs is thus important for clarifying the molecular mechanisms of organ function formation and further understanding the evolutionary origin of organs and genes in vertebrates. The precise regulation of microRNAs (miRNAs) is crucial for the functional specification and differentiation of organs. In particular, those miRNAs that are expressed specifically in organs (OSMs) play key roles in organ identity, differentiation, and function. In this study, the genome-wide miRNA transcriptome was analyzed in eight organs of adult amphioxus Branchiostoma belcheri using deep sequencing. A total of 167 known miRNAs and 23 novel miRNAs (named novel_mir), including 139 conserved miRNAs, were discovered, and 79 of these were identified as OSMs. Additionally, analyses of the expression patterns of eight randomly selected known miRNAs demonstrated the accuracy of the miRNA deep sequencing that was used in this study. Furthermore, potentially OSM-regulated genes were predicted for each organ type. Functional enrichment of these predicted targets, as well as further functional analyses of known OSMs, was conducted. We found that the OSMs were potentially to be involved in organ specific functions, such as epidermis development, gonad development, muscle cell development, proteolysis, lipid metabolism and generation of neurons. Moreover, OSMs with non-organ specific functions were detected, and primarily include those related to innate immunity and response to stimuli. These findings provide insights into the regulatory roles of OSMs in various amphioxus organs.

genetics↗

Targeting USP9x/SOX2 axis contributes to the anti-osteosarcoma effect of neogambogic acid

SOX2 has been viewed as a critical oncoprotein in osteosarcoma. Emerging evidence show that inducing the degradation of transcription factors such as SOX2 is a promising strategy to make them druggable. Here, we show that neogambogic acid (NGA), an active ingredients in garcinia, significantly inhibited the proliferation of osteosarcoma cells with ubiquitin proteasome-mediated degradation of SOX2 in vitro and in vivo. We further identified USP9x as a bona fide deubiquitinase for SOX2 and NGA directly interacts with USP9x in cells. Moreover, knockdown of USP9x inhibited the proliferation and colony formation of osteosarcoma cells, which could be rescued by overexpression of SOX2. Consistent with this, knockdown of USP9x inhibited the proliferation of osteosarcoma cells in a xenograft mouse model. Collectively, we identify USP9x as the first deubiquitinating enzyme for controlling the stability of SOX2 and USP9x is a direct target for NGA. We propose that targeting the USP9x/SOX2 axis represents a novel strategy for the therapeutic of osteosarcoma and other SOX2 related cancers.

cancer biology↗

Giotto, a pipeline for integrative analysis and visualization of single-cell spatial transcriptomic data

The rapid development of novel spatial transcriptomic and proteomic technologies has provided new opportunities to investigate the interactions between cells and their native microenvironment. However, effective use of such technologies requires the development of innovative computational tools that are easily accessible and intuitive to use. Here we present Giotto, a comprehensive, flexible, robust, and open-source toolbox for spatial transcriptomic and proteomic data analysis and visualization. The data analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing cell-type distribution, spatially coherent gene expression patterns, and interactions between each cell and its surrounding neighbors. Furthermore, Giotto can also be used in conjunction with external single-cell RNAseq data to infer the spatial enrichment of cell types from data that do not have single-cell resolution. The data visualization module allows users to interactively visualize the gene expression data, analysis outputs, and additional imaging features, thereby providing a user-friendly workspace to explore multiple modalities of information for biological investigation. These two modules can be used iteratively for refined analysis and hypothesis development. We applied Giotto to a wide range of public datasets encompassing diverse technologies and platforms, thereby demonstrating its general applicability for spatial transcriptomic and proteomic data analysis and visualization.

bioinformatics↗

Enhancer-dependence of gene expression increases with developmental age

How overall principles of gene regulation (the \"logic\") may change during ontogeny is largely unexplored. We compared transcriptomic, epigenomic and topological profiles in embryonic (EryP) and adult (EryD) erythroblasts. Despite reduced chromatin accessibility compared to EryP, distal chromatin of EryD is enriched in H3K27ac, Gata1 and Myb occupancy. In contrast to EryP-specific genes, which exhibit promoter-centric regulation through Gata1, EryD-specific genes employ distal enhancers for long-range regulation through enhancer-promoter looping, confirmed by Gata1 HiChIP. Genome editing demonstrated distal enhancers are required for gene expression in EryD but not in EryP. Applying a metric for enhancer-dependence of transcription, we observed a progressive reliance on enhancer control with increasing age of ontogeny among diverse primary cells and tissues of mouse and human origin. Our findings highlight fundamental and conserved differences in regulatory logic at distinct developmental stages, characterized by simpler promoter-centric regulation in embryonic cells and combinatorial enhancer-driven control in adult cells.\n\nHighlightsO_LIRegulation of embryonic-specific erythroid genes is promoter-centric through Gata1\nC_LIO_LIAdult-specific control is combinatorial enhancer-driven and requires Myb\nC_LIO_LIAdult specific genes have increased enhancer-promoter chromatin interactions\nC_LIO_LIEnhancer-dependence increases progressively with increasing developmental age\nC_LI

molecular biology↗

TeXP: Deconvolving the effects of pervasive and autonomous transcription of transposable elements

Long interspersed nuclear element 1 (LINE-1) is a primary source of genetic variation in humans and other mammals. Despite its importance, LINE-1 activity remains difficult to study because of its highly repetitive nature. Here, we developed and validated a method called TeXP to gauge LINE-1 activity accurately. TeXP builds mappability signatures from LINE-1 subfamilies to deconvolve the effect of pervasive transcription from autonomous LINE-1 activity. In particular, it apportions the multiple reads aligned to the many LINE-1 instances in the genome into these two categories. Using our method, we evaluated well-established cell lines, cell-line compartments and healthy tissues and found that the vast majority (91.7%) of transcriptome reads overlapping LINE-1 derive from pervasive transcription. We validated TeXP by independently estimating the levels of LINE-1 autonomous transcription using ddPCR, finding high concordance. Next, we applied our method to comprehensively measure LINE-1 activity across healthy somatic cells, while backing out the effect of pervasive transcription. Unexpectedly, we found that LINE-1 activity is present in many normal somatic cells. This finding contrasts with earlier studies showing that LINE-1 has limited activity in healthy somatic tissues, except for neuroprogenitor cells. Interestingly, we found that the amount of LINE-1 activity was associated with the with the amount of cell turnover, with tissues with low cell turnover rates (e.g. the adult central nervous system) showing lower LINE-1 activity. Altogether, our results show how accounting for pervasive transcription is critical to accurately quantify the activity of highly repetitive regions of the human genome.\n\nAuthor SummaryRepetitive sequences, such as LINEs, comprise more than half of the human genome. Due to their repetitive nature, LINEs are hard to grasp. In particular, we find that pervasive transcription is a major confounding factor in transcriptome data. We observe that, on average, more than 90% of LINE signal derives from pervasive transcription. To investigate this issue, we developed and validated a new method called TeXP. TeXP accounts and removes the effects of pervasive transcription when quantifying LINE activity. Our method uses the broad distribution of LINEs to estimate the effects of pervasive transcription. Using TeXP, we processed thousands of transcriptome datasets to uniformly, and unbiasedly measure LINE-1 activity across healthy somatic cells. By removing the pervasive transcription component, we find that (1) LINE-1 is broadly expressed in healthy somatic tissues; (2) Adult brain show small levels of LINE transcription and; (3) LINE-1 transcription level is correlated with tissue cell turnover. Our method thus offers insights into how repetitive sequences and influenced by pervasive transcription. Moreover, we uncover the activity of LINE-1 in somatic tissues at an unmatched scale.

bioinformatics↗

A lineage-resolved molecular atlas of C. elegans embryogenesis at single cell resolution

C. elegans is an animal with few cells, but a striking diversity of cell types. Here, we characterize the molecular basis for their specification by profiling the transcriptomes of 84,625 single embryonic cells. We identify 284 terminal and pre-terminal cell types, mapping most single cell transcriptomes to their exact position in C. elegans invariant lineage. We use these annotations to perform the first quantitative analysis of the relationship between lineage and the transcriptome for a whole organism. We find that a strong lineage-transcriptome correlation in the early embryo breaks down in the final two cell divisions as cells adopt their terminal fates and that most distinct lineages that produce the same anatomical cell type converge to a homogenous transcriptomic state. Users can explore our data with a graphical application "VisCello".

genomics↗

CUT&RUNTools: a flexible pipeline for CUT&RUN processing and footprint analysis

We introduce CUT&RUNTools as a flexible, general pipeline for facilitating the identification of chromatin-associated protein binding and genomic footprinting analysis from antibody-targeted CUT&RUN primary cleavage data. CUT&RUNTools extracts endonuclease cut site information from sequences of short read fragments and produces single-locus binding estimates, aggregate motif footprints, and informative visualizations to support the high-resolution mapping capability of CUT&RUN. CUT&RUNTools is available at https://bitbucket.org/qzhudfci/cutruntools/.

genomics↗

3D-printing Enabled Micro-assembly of Microfluidic Electroporation System for 3D Tissue Engineering

Electro-transfection is an essential workhorse tool for regulating cellular responses and engineering cellular materials in tissue engineering. However, existing approaches, including microfluidic platforms and bench top methods, are only able to study monolayer cell suspensions in vitro, and are incapable of clinical translation within in vivo tissue microenvironment. Knowledge regarding the three-dimensional (3D) electric field distribution and mass transport in a tissue microenvironment is lacking. However, building a 3D electro-transfection system that is compatible with 3D cell culture for mimicking in vivo tissue microenvironment is challenging, due to the substantial difficulties in control of 3D electric field distribution as well as the cellular growth. To address such challenges, we introduce a novel 3D micro-assembling strategy assisted by 3D printing, which enables the molding of 3D microstructures as LEGO(R) parts from 3D-printed molds. The molded PDMS LEGO(R) bricks are then assembled into a 3D-cell culture chamber interconnected with vertical and horizontal perfusion microchannels as a 3D channel network. Such 3D perfusion microchannel network is unattainable by direct 3D printing or other microfabrication approaches, which can facilitate the high-efficient exchange of nutrition and waste for 3D cell growth. Four flat electrodes are mounted into the 3D culture chamber via a 3D-printed holder and controlled by a programmable power sequencer for multi-directional electric frequency scanning (3D -electro-transfection). This multi-directional scanning not only can create transient pores all over the cell membrane, but also can generate local oscillation for enhancing mass transport and improving cell transfection efficiency. As a proof-of-concept, we electro-delivered pAcGFP1-C1 vector to 3D cultured HeLa cells within peptide hydrogel scaffolding. The expressed GFP level from transfected HeLa cells reflects the transfection efficiency. We found two key parameters including electric field strength and plasmid concentration playing more important roles than manipulating pulse duration and duty cycles. The results showed an effective transfection efficiency of ~15% with ~85% cell viability, which is a 3-fold increase compared to the conventional benchtop 3D cell transfection. This 3D -electrotransfection system was further used for genetically editing 3D-cultured Hek-293 cells via direct delivery of CRISPR/Cas9 plasmid which showed successful transfection with GFP expressed in the cytoplasm as the reporter. The 3D-printing enabled micro-assembly allows facile creation of novel 3D culture system for electro-transfection which can be employed for versatile gene delivery and cellular engineering, as well as building in-vivo like tissue models for fundamentally studying cellular regulatory mechanisms.

bioengineering↗