Biology subjects

Li, G.

Publications and source records attributed to Li, G..

At least 541 records · Page 30Linked to original sources

bioRxiv2019

STING recruits NLRP3 to the ER and deubiquitinates NLRP3 to activate the inflammasome

One of the fundamental reactions of the innate immune responses to pathogen infection is the release of pro-inflammatory cytokines, including IL-1{beta}, processed by the NLRP3 inflammasome. STING is essential for innate immune responses and inflammasome activation. Here we reveal a distinct mechanism by which STING regulates the NLRP3 inflammasome activation, IL-1{beta} secretion, and inflammatory responses in human cell lines, mice primary cells, and mice. Interestingly, upon HSV-1 infection and cytosolic DNA stimulation, STING binds to NLRP3 and promotes the inflammasome activation through two approaches. First, STING recruits NLRP3 and promotes NLRP3 translocation to the endoplasmic reticulum, thereby facilitating the inflammasome formation. Second, STING interacts with NLRP3 and removes K48- and K63-linked polyubiquitination of NLRP3, thereby promoting the inflammasome activation. Collectively, we demonstrate that the cGAS-STING-NLRP3 signaling is essential for host defense against DNA virus infection.

immunology↗

bioRxiv2019

Degradation of miR-466d-3p by JEV NS3 facilitates viral replication and IL-1β expression

Previous studies revealed that Japanese encephalitis virus (JEV) infection alters the expression of miRNA in central nervous system (CNS). However, the mechanism of JEV infection contributes to the regulation of miRNAs in CNS remain obscure. Here, we found that a global degradation of mature miRNA in mouse brain and neuroblastoma cells after JEV infection. In additional, the integrative analysis of miRNAs and mRNAs suggests that those down-regulated miRNAs are primarily targeted inflammation genes and the miR-466d-3p target the IL-1{beta} which in the middle of those inflammation genes. Transfection of miR-466d-3p decreased the IL-1{beta} expression and inhibited the JEV replication in NA cells. Interestingly, the miR-466d-3p level increased after JEV infection in the presence of cycloheximide, which indicated that viral protein expression reduces miR-466d-3p. Therefore, we generated all the JEV coding protein and demonstrated that NS3 is a potent miRNA suppressor. Furthermore, the NS3 of ZIKA virus, WNV, DENV1 and DENV2 also decreased the expression of miR-466d-3p. The in vitro unwinding assay demonstrated that the NS3 could unwind the pre-miR-466d and induce the disfunction of miRNA. Using computational models and RNA immunoprecipitation assay, we found that arginine-rich domains of NS3 are critical for pre-miRNA binding and the degradation of host miRNAs. Importantly, site-directed mutagenesis of conserved residues revealed that R226G and R202W significantly reduced the binding affinity and degradation of pre-miR-466d. Together, these results extend the helicase of Flavivirus function beyond unwinding duplex RNA to the decay of pre-miRNAs, which provides a new mechanism of NS3 in regulating miRNA pathways and promoting the neuroinflammation.\n\nAuthor SummaryHost miRNAs had been reported to regulate JEV induced inflammation in central nervous system. We found that the NS3 of JEV can reduce most of host miRNA expression. The helicase region of the NS3 specifically binds to precursors of miRNA and lead to incorrect unwinding of precursors of miRNAs which inhibits the function of miRNAs. This observation leads to two major findings. First, we identified the miR-466d-3p targets to the host IL-1{beta} and E protein of JEV, and NS3 degrades the miR-466d-3p to promote the brain inflammation and viral replication. Second, we proved that the arginine on the helicase of NS3 is the main miRNA binding sites, and the miRNA degradation by NS3 was abolished when the R226 and R202 were mutated on the NS3. These findings were also confirmed with NS3 of ZIKA virus, WNV and DENV which could decrease the expression level of miR-466d-3p to enhance the inflammation. Our study provides new insights into the molecular mechanism of encephalitis caused by JEV, and reveals several amino acid sites to further attenuate the JEV vaccine.

microbiology↗

bioRxiv2019

Altered White Matter Microstructural Organization in Post-Traumatic Stress Disorder across 3,049 Adults: Results from the PGC-ENIGMA PTSD Consortium

A growing number of studies have examined alterations in white matter organization in people with posttraumatic stress disorder (PTSD) using diffusion MRI (dMRI), but the results have been mixed, which may be partially due to relatively small sample sizes among studies. Altered structural connectivity may be both a neurobiological vulnerability for, and a result of, PTSD. In an effort to find reliable effects, we present a multi-cohort analysis of dMRI metrics across 3,049 individuals from 28 cohorts currently participating in the PGC-ENIGMA PTSD working group (a joint partnership between the Psychiatric Genomics Consortium and the Enhancing NeuroImaging Genetics through Meta-Analysis consortium). Comparing regional white matter metrics across the full brain in 1,446 individuals with PTSD and 1,603 controls (2152 males/897 females) between ages 18-83, 92% of whom were trauma-exposed, we report associations between PTSD and disrupted white matter organization measured by lower fractional anisotropy (FA) in the tapetum region of the corpus callosum (Cohens d=-0.12, p=0.0021). The tapetum connects the left and right hippocampus, structures for which structure and function have been consistently implicated in PTSD. Results remained significant/similar after accounting for the effects of multiple potentially confounding variables: childhood trauma exposure, comorbid depression, history of traumatic brain injury, current alcohol abuse or dependence, and current use of psychotropic medications. Our results show that PTSD may be associated with alterations in the broader hippocampal network.

neuroscience↗

bioRxiv2019

SMNN: Batch Effect Correction for Single-cell RNA-seq data via Supervised Mutual Nearest Neighbor Detection

Batch effect correction has been recognized to be indispensable when integrating single-cell RNA sequencing (scRNA-seq) data from multiple batches. State-of-the-art methods ignore single-cell cluster label information, but such information can improve effectiveness of batch effect correction, particularly under realistic scenarios where biological differences are not orthogonal to batch effects. To address this issue, we propose SMNN for batch effect correction of scRNA-seq data via supervised mutual nearest neighbor detection. Our extensive evaluations in simulated and real datasets show that SMNN provides improved merging within the corresponding cell types across batches, leading to reduced differentiation across batches over MNN, Seurat v3, and LIGER. Furthermore, SMNN retains more cell type-specific features, partially manifested by differentially expressed genes identified between cell types after SMNN correction being biologically more relevant, with precision improving by up to 841%. Key PointsO_LIBatch effect correction has been recognized to be critical when integrating scRNA-seq data from multiple batches due to systematic differences in time points, generating laboratory and/or handling technician(s), experimental protocol, and/or sequencing platform. C_LIO_LIExisting batch effect correction methods that leverages information from mutual nearest neighbors across batches (for example, implemented in SC3 or Seurat) ignore cell type information and suffer from potentially mismatching single cells from different cell types across batches, which would lead to undesired correction results, especially under the scenario where variation from batch effects is non-negligible compared with biological effects. C_LIO_LITo address this critical issue, here we present SMNN, a supervised machine learning method that first takes cluster/cell-type label information from users or inferred from scRNA-seq clustering, and then searches mutual nearest neighbors within each cell type instead of global searching. C_LIO_LIOur SMNN method shows clear advantages over three state-of-the-art batch effect correction methods and can better mix cells of the same cell type across batches and more effectively recover cell-type specific features, in both simulations and real datasets. C_LI

bioinformatics↗

bioRxiv2019

Genome sequence of the model rice variety KitaakeX

Here, we report the de novo genome sequencing and analysis of Oryza sativa ssp. japonica variety KitaakeX, a Kitaake plant carrying the rice XA21 immune receptor. Our KitaakeX sequence assembly contains 377.6 Mb, consisting of 33 scaffolds (476 contigs) with a contig N50 of 1.4 Mb. Complementing the assembly are detailed gene annotations of 35,594 protein coding genes. We identified 331,335 genomic variations between KitaakeX and Nipponbare (ssp. japonica), and 2,785,991 variations between KitaakeX and Zhenshan97 (ssp. indica). We also compared Kitaake resequencing reads to the KitaakeX assembly and identified 219 small variations. The high-quality genome of the model rice plant KitaakeX will accelerate rice functional genomics.

genomics↗

bioRxiv2019

Drivers of HIV-1 transmission: the Portuguese case

BackgroundPortugal has one of the most severe HIV-1 epidemic in Western Europe. Two subtypes circulate in parallel since the beginning of the epidemic. Comparing their transmission patterns and its association with transmitted drug resistance (TDR) is important to pinpoint transmission hotspots and to develop evidence-based treatment guidelines.\n\nMethods3599 HIV-1 naive patients collected between 2001 and 2014 were included in the study. Sequences obtained from drug resistance testing were used for subtyping, TDR determination and transmission clusters (TC) analyses.\n\nResultsSubtype B transmission was significantly associated with young males, while subtype G was associated with older heterosexuals. Young males infected with subtype B were more likely to be included in TC. Consistently, a decreasing trend of prevalence and transmission of subtype G in Portuguese originated people was observed. Active TCs were associated with subtype B-infected males residing in Lisbon. TDR was significantly different when comparing subtypes B (10.8% [9.5-12.2]) and G (7.6% [6.4-9.0]) (p=0.001).\n\nDiscussionTC analyses shows that the subtype B epidemic is active and fueled by young male patients residing in Lisbon and that transmission of subtype G in Portugal is decreasing. Despite similar treatment rates for both subtypes in Portugal, TDR is different between subtypes.

molecular biology↗

bioRxiv2019

Exploring the Mechanism of Olfactory Recognition at the Initial Stage by Modeling the Emission Spectrum of Electron Transfer

Olfactory sense remains elusive regarding the primary reception mechanism. Some studies suggest that olfaction is a spectral sense, the olfactory event is triggered by electron transfer (ET) across the odorants at the active sites of odorant receptors (ORs). Herein we present a Donor-Bridge-Acceptor model, proposing that the ET process can be viewed as an electron hopping from the donor molecule to the odorant molecule (Bridge), then hopping off to the acceptor molecule, making the electronic state of the odorant molecule change along with vibrations (vibronic transition). The odorant specific parameter, Huang-Rhys factor can be derived from ab initio calculations, which make the simulation of ET spectra achievable. In this study, we revealed that the emission spectra (after Gaussian convolution) can be acted as odor characteristic spectra. Using the emission spectrum of ET, we were able to reasonably interpret the similar bitter-almond odors among hydrogen cyanide, benzaldehyde and nitrobenzene. In terms of isotope effects, we succeeded in explaining why subjects can easily distinguish cyclopentadecanone from its fully deuterated analogue cyclopentadecanone-d28 but not distinguishing acetophenone from acetophenone-d8.

biophysics↗

bioRxiv2019

Multiplex RNA single molecule FISH of inducible mRNAs in single yeast cells

Transcript levels powerfully influence cell behavior and phenotype and are carefully regulated at several steps. Recently developed single cell approaches such as RNA single molecule fluorescence in-situ hybridization (smFISH) have produced advances in our understanding of how these steps work within the cell. In comparison to single-cell sequencing, smFISH provides more accurate quantification of RNA levels. Additionally, transcript subcellular localization is directly visualized, enabling the analysis of transcription (initiation and elongation), RNA export and degradation. As part of our efforts to investigate how this type of analysis can generate improved models of gene expression, we used smFISH to quantify the kinetic expression of STL1 and CTT1 mRNAs in single Saccharomyces cerevisiae cells upon 0.2 and 0.4M NaCl osmotic stress. In this Data Descriptor, we outline our procedure along with our data in the form of raw images and processed mRNA counts. We discuss how these data can be used to develop single cell modelling approaches, to study fundamental processes in transcription regulation and develop single cell image processing approaches.

systems biology↗

bioRxiv2019

Generating kinetic environments to study dynamic cellular processes in single cells

Cells of any organism are consistently exposed to changes over time in their environment. The kinetics by which these changes occur are critical for the cellular response and fate decision. It is therefore important to control the temporal changes of extracellular stimuli precisely to understand biological mechanisms in a quantitative manner. Most current cell culture and biochemical studies focus on instant changes in the environment and therefore neglect the importance of kinetic environments. To address these shortcomings, we developed two experimental methodologies to precisely control the environment of single cells. These methodologies are compatible with standard biochemistry, molecular, cell and quantitative biology assays. We demonstrate applicability by obtaining time series and time point measurements in both live and fixed cells. We demonstrate the feasibility of the methodology in yeast and mammalian cell culture in combination with widely used assays such as flow cytometry, time-lapse microscopy and single-molecule RNA Fluorescent in-situ Hybridization. Our experimental methodologies are easy to implement in most laboratory settings and allows the study of kinetic environments in a wide range of assays and different cell culture conditions.

systems biology↗

bioRxiv2019

Automated cell boundary and 3D nuclear segmentation of cells in suspension

To characterize cell types, cellular functions and intracellular processes, an understanding of the differences between individual cells is required. Although microscopy approaches have made tremendous progress in imaging cells in different contexts, the analysis of these imaging data sets is a long-standing, unsolved problem. The few robust cell segmentation approaches that exist often rely on multiple cellular markers and complex time-consuming image analysis. Recently developed deep learning approaches can address some of these challenges, but they require tremendous amounts of data and well-curated reference data sets for algorithm training. We propose an alternative experimental and computational approach, called CellDissect, in which we first optimize specimen preparation and data acquisition prior to image processing to generate high quality images that are easier to analyze computationally. By focusing on fixed suspension and dissociated adherent cells, CellDissect relies only on widefield images to identify cell boundaries and nuclear staining to automatically segment cells in two dimensions and nuclei in three dimensions. This segmentation can be performed on a desktop computer or a computing cluster for higher throughput. We compare and evaluate the accuracy of different nuclear segmentation approaches against manual expert cell segmentation for different cell lines acquired with different imaging modalities.

systems biology↗

bioRxiv2019

Chromatin interaction analysis with updated ChIA-PET Tool (V3)

Understanding chromatin interactions is important since they create chromosome conformation and link the cis- and trans-regulatory elements to their target genes for transcriptional regulation. Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing is a genome-wide high-throughput technology that detects chromatin interactions associated with a specific protein of interest. Previously we developed ChIA-PET Tool in 2010 for ChIA-PET data analysis. Here we present the updated version of ChIA-PET Tool (V3), is a computational package to process the next-generation sequence data generated from ChIA-PET experiments. It processes the short-read data and long-read ChIA-PET data with multithreading and generates the statistics of results in a HTML file. In this paper, we provide a detailed demonstration of the design of ChIA-PET Tool V3 and how to install it and analyze a specific ChIA-PET data set with it. At present, other ChIA-PET data analysis tools have developed including ChiaSig, MICC, Mango and ChIA-PET2 and so on. We compared our tool with other tools using the same public data set in the same machine. Most of peaks detected by ChIA-PET Tool V3 overlap with those from other tools. There is higher enrichment for significant chromatin interactions of ChIA-PET Tool V3 in APA plot. ChIA-PET Tool V3 is open source and is available at GitHub (https://github.com/GuoliangLi-HZAU/ChIA-PET_Tool_V3/).

genomics↗

bioRxiv2019

Red blood cell-derived extracellular vesicles mediate intercellular communication in ischemic heart failure

Extracellular vesicles (EV) mediate intercellular signaling by transferring their cargo to recipient cells. Red blood cell (RBC)-derived EVs constitute a significant proportion of circulating EVs and have been implicated in regulating immune responses. Here, we describe a transgenic mouse model for fluorescent-based mapping of RBC-EV target cells based on the functional transfer of EV-contained Cre-recombinase to target cells. In a murine model of ischemic heart failure, we detect an increase in RBC-EV-targeted cardiomyocytes in the hearts and microglial cells in the brains. Cells targeted by RBC-EVs present an enrichment of genes implicated in cell proliferation and metabolism pathways compared to non-recombined (non-targeted) cells. Cardiomyocytes targeted by RBC-EVs are more likely to demonstrate cellular markers of DNA synthesis and proliferation, suggesting functional significance of EV-mediated signaling. In conclusion, we leverage our mouse model for mapping of RBC-EV targets in murine ischemic heart failure to demonstrate quantitative and qualitative changes in RBC-EV recipients.

cell biology↗

bioRxiv2019

Using distant supervision to augment manually annotated data for relation extraction

Significant progress has been made in applying deep learning on natural language processing tasks recently. However, deep learning models typically require a large amount of annotated training data while often only small labeled datasets are available for many natural language processing tasks in biomedical literature. Building large-size datasets for deep learning is expensive since it involves considerable human effort and usually requires domain expertise in specialized fields. In this work, we consider augmenting manually annotated data with large amounts of data using distant supervision. However, data obtained by distant supervision is often noisy, we first apply some heuristics to remove some of the incorrect annotations. Then using methods inspired from transfer learning, we show that the resulting models outperform models trained on the original manually annotated sets.

bioinformatics↗

bioRxiv2019

CoolBox: a interactive genomic data explorer for Jupyter Notebook

SummaryCoolBox is a Python package for interactive genomic data exploration based on Jupyter notebook. It provides a ggplot2-like Application Programming Interface (API) for genomic data visualization, and a Jupyter/ipywidgets based Graphical User Interface (GUI) for interactive data exploration. CoolBox is a versatile multi-omics explorer supporting most types of data formats generated by various sequencing technologies like RNA-Seq, ChIP-Seq, ChIA-PET and Hi-C.\n\nAvailability and implementationCoolBox is purely implemented with Python, and the GUI widget in Jupyter notebook is based on the ipywidgets package. It is open-source and available under GPLv3 license at https://github.com/GangCaoLab/CoolBox.

bioinformatics↗

bioRxiv2019

Imaging chromatin interactions at sub-kilobase resolution Via Tn5-FISH

There is increasing interest in understanding how the three-dimensional organization of the genome is regulated. Different strategies have been employed to identify chromatin interactions genome wide. However, due to the current limitations in resolving genomic contacts, visualization and validation of these genomic loci with sub-kilobase resolution remain the bottleneck for many years. Here, we describe Tn5 transposase-based Fluorescence in situ Hybridization (Tn5-FISH), a Polymerase Chain Reaction (PCR)-based, cost-effective imaging method, which achieved the co-localization of genomic loci with sub-kilobase resolution, to fine dissect genome architecture at sub-kilobase resolution and to verify chromatin interactions detected by Chromatin Configuration Capture (3C)-derivative methods. Especially, Tn5-FISH is very useful to verify short-range chromatin interactions inside of contact domain and Topologically Associated Domain (TAD). It also offers one powerful molecular diagnosis tool for clinical detection of cytogenetic changes in cancers.

cell biology↗

bioRxiv2019

Oligotyping and Genome-Resolved Metagenomics Reveal Distinct Candidatus Accumulibacter Communities in Full-Scale Side-Stream versus Conventional Enhanced Biological Phosphorus Removal (EBPR) Configurations

Candidatus Accumulibacter phosphatis (CAP) and its sub-clades-level diversity has been associated and implicated in successful phosphorus removal performance in enhanced biological phosphorus removal (EBPR). Development of high-throughput untargeted methods to characterize clades of CAP in EBPR communities can enable a better understanding of Accumulibacter ecology at a higher-resolution beyond OTU-level in wastewater resource recovery facilities (WRRFs). In this study, for the first time, using integrated 16S rRNA gene sequencing, oligotyping and genome-resolved metagenomics, we were able to reveal clade-level differences in Accumulibacter communities and associate the differences with two different full-scale EBPR configurations. The results led to the identification and characterization of a distinct and dominant Accumulibacter oligotype - Oligotype 2 (belonging to Clade IIC) and its matching MAG (RC14) associated with side-stream EBPR configuration. We are also able to extract MAGs belonging to CAP clades IIB (RCAB4-2) and II (RC18) which did not have representative genomes before. This study demonstrates and validates the use of a high-throughput approach of oligotyping analysis of 16S rRNA gene sequences to elucidate CAP clade-level diversity. We also show the existence of a previously uncharacterized diversity of CAP clades in full-scale EBPR communities through extraction of MAGs, for the first time from full-scale facilities.

microbiology↗

bioRxiv2019

On the energetics and stability of a minimal fish school

The physical basis for fish schooling is examined using three-dimensional numerical simulations of a pair of swimming fish, with kinematics and geometry obtained from experimental data. Energy expenditure and efficiency are evaluated using a cost of transport function, while the effect of schooling on the stability of each swimmer is examined by probing the lateral force and the lateral and longitudinal force fluctuations. We construct full maps of the aforementioned quantities as functions of the spatial pattern of the swimming fish pair and show that both energy expenditure and stability can be invoked as possible reasons for the swimming patterns and tail-beat synchronization observed in real fish. Our results suggest that high cost of transport zones should be avoided by the fish. Wake capture may be energetically unfavorable in the absence of kinematic adjustment. We hereby hypothesize that fish may restrain from wake capturing and, instead, adopt side-to-side configuration as a conservative strategy, when the conditions of wake energy harvesting are not satisfied. To maintain a stable school configuration, compromise between propulsive efficiency and stability, as well as between school members, ought to be considered.

biophysics↗

bioRxiv2019

Single cell expression variability in highly homogeneous populations of human cells is widespread, heritable, and implies cell function

Because of recent technological developments, single-cell assays such as single-cell RNA sequencing (scRNA-seq) have become much more widely available and have achieved unprecedented resolution in revealing cell heterogeneity. The extent of intrinsic cell-to-cell variability in gene expression, or single cell expression variability (scEV), has thus been increasingly appreciated. However, it remains unclear whether this variability is functionally important and, if so, what its implications are for multi-cellular organisms. We therefore analyzed multiple scRNA-seq data sets from lymphoblastoid cell lines (LCLs), lung airway epithelial cells (LAECs), and dermal fibroblasts (DFs). For each of the three cell types, we estimated scEV in homogeneous populations of cells; we identified 465, 466, and 291 highly variable genes (HVGs), respectively. These HVGs were enriched with specific functions precisely relevant to the cell types, from which the scRNA-seq data used to identify HVGs were generated--e.g., HVGs identified in lymphoblastoid cells were enriched in cytokine signaling pathways, LAECs collagen formation, and DFs keratinization. HVGs were deeply embedded in gene regulatory networks specific to corresponding cell types. We also found that scEV is a heritable trait, partially determined by cell donors genetic makeups. Furthermore, across genes, especially immune genes, levels of scEV and between-individual variability in gene expression were positively correlated, suggesting a potential link between the two variabilities measured at different organizational levels. Taken together, our results support the \"variation is function\" hypothesis, which postulates that scEV is required for higher-level system function. Thus, we argue that quantifying and characterizing scEV in relevant cell types may deepen our understating of normal as well as pathological cellular processes.

genetics↗