Biology subjects

Xue, L.

Publications and source records attributed to Xue, L..

72 records · Page 4Linked to original sources

bioRxiv2021

Pericentromeric heterochromatin impacts genome compartmentalization and sex chromosome evolution in a fish

Compartmentalization is one of the principles of chromosome 3D organization and has been suggested to be driven by the attraction of heterochromatin. The extent to which the pericentromeric heterochromatin (PCH) impacts chromosome compartmentalization is yet unclear. Here we produced a chromosome-level and fully phased diploid genome of an aquaculture fish, zig-zag eel (Mastacembelus armatus), and identified the centromeric and pericentromeric regions in the majority of chromosomes of both haploid genomes. The PCH is on average 4.2 Mb long, covering 17.7% of the chromosomes, and is the major target of histone 3 lysine 9 trimethylation (H3K9me3). In nearly half of the chromosomes, the PCH drives the chromosomes into two or three megascale chromatin domains with the PCH being a single one. We further demonstrate that PCH has a major impact in submetacentric, metacentric and small telocentric chromosomes in which the PCH drives the distribution of active and inactive compartments along the chromosomes. Additionally, we identified the young and homomorphic XY sex chromosomes that are submetacentric with the entire short-arm heterochromatinized. Interestingly, the sex-determining region seems to arise within the PCH that has been in place prior to the X-Y divergence and recombination suppression. Together, we demonstrate that the PCH can cover a considerably large portion of the chromosomes, and when it does so, it drives chromosome compartmentalization; and we propose a new model for the origin and evolution of homomorphic sex chromosomes in fish.

genomics↗

bioRxiv2020

EKLF/KLF1 expression defines a unique macrophage subset during mouse erythropoiesis

Erythroblastic islands are a specialized niche that contain a central macrophage surrounded by erythroid cells at various stages of maturation. However, identifying the precise genetic and transcriptional control mechanisms in the island macrophage remains difficult due to macrophage heterogeneity. Using unbiased global sequencing and directed genetic approaches focused on early mammalian development, we find that fetal liver macrophage exhibit a unique expression signature that differentiates them from erythroid and adult macrophage cells. The importance of EKLF/KLF1 in this identity is shown by expression analyses in EKLF-/- and in EKLF-marked macrophage cells. Single cell sequence analysis simplifies heterogeneity and identifies clusters of genes important for EKLF-dependent macrophage function and novel cell surface biomarkers. Remarkably, this singular set of macrophage island cells appears transiently during embryogenesis. Together these studies provide a detailed perspective on the importance of EKLF in establishment of the dynamic gene expression network within erythroblastic islands in the developing embryo and provide the means for their efficient isolation.

developmental biology↗

bioRxiv2020

Multi-particle cryo-EM refinement with M visualizes ribosome-antibiotic complex at 3.7 A inside cells

Cryo-electron microscopy (cryo-EM) enables macromolecular structure determination in vitro and in situ. In addition to aligning individual particles, accurate registration of sample motion and 3D deformation during exposures is crucial for achieving high resolution. Here we describe M, a software tool that establishes a reference-based, multi-particle refinement framework for cryo-EM data and improves the results of structure determination. M provides a unified optimization framework for both in vitro frame series and in situ tomographic tilt series data. We show that tilt series data can provide the same resolution as frame series, indicating that the alignment step no longer limits the resolution obtainable from tomographic data. In combination with Warp and RELION, M improves upon previous methods, and resolves a 70S ribosome bound to an antibiotic inside bacterial cells at a nominal resolution of 3.7 [A]. Thus, computational tools are now available to resolve structures from tomographic in situ cryo-EM data at residue level.

biophysics↗

bioRxiv2020

Cytotoxicity evaluation of chloroquine and hydroxychloroquine in multiple cell lines and tissues by dynamic imaging system and PBPK model

Chloroquine (CQ) and hydroxychloroquine (HCQ) have been used in treating COVID-19 patients recently. However, both drugs have some contradictions and rare but severe side effects, such as hypoglycemia, retina and cardiac toxicity. To further uncover the toxicity profile of CQ and HCQ in different tissues, we evaluated the cytotoxicity of them in 8 cell lines, and further adopted the physiologically-based pharmacokinetic models (PBPK) to predict the tissue risk respectively. Retina, myocardium, lung, liver, kidney, vascular endothelium and intestinal epithelium originated cells were included in the toxicity evaluation of CQ and HCQ respectively. The proliferation pattern was monitored in 0-72 hours by IncuCyte S3, which could perform long-term continuous image and video of cells upon CQ or HCQ treatment. CC50 and the ratio of tissue trough concentrations to CC50 (RTTCC) were brought into predicted toxicity profiles. The CC50 at 24 h, 48 h, 72 h of CQ and HCQ decreased in the time-dependent manner, which indicates the accumulative cytotoxic effect. HCQ was found to be less toxic in 7 cell types except cardiomyocytes H9C2 cells (CC50-48 h=29.55 M; CC50-72 h=15.26 M). In addition, RTTCC is significant higher in CQ treatment group compared to HCQ group, which indicates that relative safety of HCQ. Both CQ and HCQ have certain cytotoxicity in time dependent manner which indicates the necessity of short period administration clinically. HCQ has the less impact in 7 cell lines proliferation and less toxicity compared to CQ in heart, liver, kidney and lung.

pharmacology and toxicology↗

bioRxiv2020

Two antagonistic effect genes mediate separation of sexes in a fully dioecious plant

Plant sex determining systems and sex chromosomes are often evolutionarily young. Here, we present the early stage of sex chromosome in a fully dioecious plant, P. deltoides, by determining separate sequences of the physically small X- and Y-linked regions. Intriguingly, two Y genes are absent from the X counterpart. One gene represses female structures by producing siRNAs that block expression of a gene necessary for development of female structures, via RNA-directed DNA methylation and siRNA-guided mRNA cleavage. The other gene generates long non-coding RNA transcripts that, in males, soak up miRNAs that specifically inhibit androecium development. Transformation experiments in Arabidopsis thaliana show that the two genes affect gynoecium and androecium development independently and antagonistically. Sex determination in the poplar therefore has the properties proposed for the first steps in the evolution of dioecy in flowering plants, with two genes whose joint effects favor close linkage, as is observed in poplar.

plant biology↗

bioRxiv2020

Rapid growth and fusion of protocells in surface-adhered membrane networks

Elevated temperatures might have promoted the nucleation, growth and replication of protocells on the early Earth. Recent reports have shown evidence that moderately high temperatures not only permit protocell assembly at the origin of life, but could have actively supported it. Here we show the fast nucleation and growth of vesicular compartments from autonomously formed lipid networks on solid surfaces, induced by a moderate increase in temperature. Branches of the networks, initially consisting of self-assembled interconnected nanotubes, rapidly swell into microcompartments which can spontaneously encapsulate RNA fragments. The increase in temperature further causes fusion of adjacent network-connected compartments, resulting in the redistribution of the RNA. The experimental observations and the mathematical model indicate that the presence of nanotubular interconnections between protocells facilitates the fusion process.

biophysics↗

bioRxiv2020

In-cell architecture of an actively transcribing-translating expressome

Structural biology performed inside cells can capture molecular machines in action within their native context. Here we develop an integrative in-cell structural approach using the genome-reduced human pathogen Mycoplasma pneumoniae. We combine whole-cell crosslinking mass spectrometry, cellular cryo-electron tomography, and integrative modeling to determine an in-cell architecture of a transcribing and translating expressome at sub-nanometer resolution. The expressome comprises RNA polymerase (RNAP), the ribosome, and the transcription elongation factors NusG and NusA. We pinpoint NusA at the interface between a NusG-bound elongating RNAP and the ribosome, and propose it could mediate transcription-translation coupling. Translation inhibition dissociates the expressome, whereas transcription inhibition stalls and rearranges it, demonstrating that the active expressome architecture requires both translation and transcription elongation within the cell.

molecular biology↗

bioRxiv2019

Correlation of p53 and DNA repair gene mutation patterns in human malignancies indicates different tumour suppression mechanisms of p53

P53 suppresses tumorigenesis through multiple cellular functions/mechanisms. Recently, Janic A, et al. reported that DNA repair pathways are critical mediators of p53-dependent tumor suppression. We showed, by mining cBioPortal data of a range of human cancers, that the tendency of mutual exclusivity of mutations in p53 and DNA repair genes only exist in very limited human cancer types. In the majority of human cancers, p53 mutations are equally distributed between DNA repair gene mutation positive and negative cases and in a number of human cancers, p53 and DNA repair gene mutations have a tendency of co-occurrence. These different correlation patterns of p53 and DNA repair gene mutations in human malignancies may reflect different critical molecular/cellular pathways activated by p53 in different organs or cell types to suppress tumorigenesis.

cancer biology↗

bioRxiv2019

Compositional knockoff filter for high-dimensional regression analysis of microbiome data

SO_SCPLOWUMMARYC_SCPLOWA critical task in microbiome data analysis is to explore the association between a scalar response of interest and a large number of microbial taxa that are summarized as compositional data at different taxonomic levels. Motivated by fine-mapping of the microbiome, we propose a two-step compositional knockoff filter (CKF) to provide the effective finite-sample false discovery rate (FDR) control in high-dimensional linear log-contrast regression analysis of microbiome compositional data. In the first step, we employ the compositional screening procedure to remove insignificant microbial taxa while retaining the essential sum-to-zero constraint. In the second step, we extend the knockoff filter to identify the significant microbial taxa in the sparse regression model for compositional data. Thereby, a subset of the microbes is selected from the high-dimensional microbial taxa as related to the response using a pre-specified FDR threshold. We study the asymptotic properties of the proposed two-step procedure, including both sure screening and effective false discovery control. We demonstrate the finite-sample properties in simulation studies, which show the gain in the empirical power while controlling the nominal FDR. The potential usefulness of the proposed method is also illustrated with application to an inflammatory bowel disease dataset to identify microbial taxa that influence host gene expressions.

bioinformatics↗

bioRxiv2019

iScore: an MPI supported software for ranking protein-protein docking models based on a random walk graph kernel and support vector machines.

Computational docking is a promising tool to model three-dimensional (3D) structures of protein-protein complexes, which provides fundamental insights of protein functions in the cellular life. Singling out near-native models from the huge pool of generated docking models (referred to as the scoring problem) remains as a major challenge in computational docking. We recently published iScore, a novel graph kernel based scoring function. iScore ranks docking models based on their interface graph similarities to the training interface graph set. iScore uses a support vector machine approach with random-walk graph kernels to classify and rank protein-protein interfaces.\n\nHere, we present the software for iScore. The software provides executable scripts that fully automatize the computational workflow. In addition, the creation and analysis of the interface graph can be distributed across different processes using Message Passing interface (MPI) and can be offloaded to GPUs thanks to dedicated CUDA kernels.

bioinformatics↗

bioRxiv2019

An overview of data-driven HADDOCK strategies in CAPRI rounds 38-45.

Our information-driven docking approach HADDOCK has demonstrated a sustained performance since the start of its participation to CAPRI. This is due, in part, to its ability to integrate data into the modelling process, and to the robustness of its scoring function. We participated in CAPRI both as server and as manual predictors.\n\nIn CAPRI rounds 38-45, we have used various strategies depending on the information at hand. These ranged from imposing restraints to a few residues identified from literature as being important for the interaction, to binding pockets identified from homologous complexes or template-based refinement / CA-CA restraint-guided docking from identified templates. When relevant, symmetry restraints were used to limit the conformational sampling. We also tested for a large decamer target a new implementation of the MARTINI coarse-grained force field in HADDOCK. Overall in the current rounds, we obtained acceptable or better predictions for 13 and 11 server and manual submissions, respectively, out of the 22 interfaces. Our server performance (acceptable models) was better (59%) than the manual (50%) one, in which we typically experiment with various combinations of protocols and data sources. Again, our simple scoring function based on a linear combination of intermolecular van der Waals and electrostatic energies and an empirical desolvation term demonstrated a good performance in the scoring experiment with a 63% success rate across all 22 interfaces.\n\nAn analysis of model quality indicates that, while we are consistently performing well in generating acceptable models, there is room for improvement for generating/identifying higher quality models.

bioinformatics↗

bioRxiv2019

A general strategy to develop cell permeable and fluorogenic probes for multi-colour nanoscopy

Live-cell fluorescence nanoscopy is a powerful tool to study cellular biology on a molecular scale, yet its use is held back by the paucity of suitable fluorescent probes. Fluorescent probes based on regular fluorophores usually suffer from low cell permeability and unspecific background signal. We report a general strategy to transform regular fluorophores into fluorogenic probes with excellent cell permeability and low unspecific background signal. The strategy is based on the conversion of a carboxyl group found in rhodamines and related fluorophores into an electron-deficient amide. This conversion does not affect the spectroscopic properties of the fluorophore but permits it to exist in a dynamic equilibrium between two different forms: a fluorescent zwitterion and a non-fluorescent, cell permeable spirolactam. Probes based on such fluorophores generally are fluorogenic as the equilibrium shifts towards the fluorescent form when the probe binds to its cellular targets. The resulting increase in fluorescence can be up to 1000-fold. Using this simple design principle we created fluorogenic probes in various colours for different cellular targets for wash-free, multicolour, live-cell nanoscopy. The work establishes a general strategy to develop fluorogenic probes for live-cell bioimaging.

biochemistry↗

bioRxiv2018

Impact of fruit-tree shade intensity on the growth, yield, and quality of intercropped wheat

Agroforestry is a common traditional practice in China-especially in the southern Xinjiang of Northwest China. However, the productivity of many agroforestry systems has been lower than expected in recent years, highlighting the need for an actionably deep mechanistic understanding of the competition between crops and trees. Here, we chose 3 different fruit tree/wheat intercropping agroforestry systems to investigate influence of different fruit tree shade intensity on the growth, yield and quality of intercropping wheat: jujube/wheat, apricot /wheat, and walnut /wheat. We found that compared to the monoculture wheat system, the mean daily shade intensity of the jujube-, apricot-, and walnut-based intercropping systems were, respectively, 23.2%, 57.5%, and 80.7% shade. The photosynthetic rate of wheat in the jujube-, apricot-, and walnut-based intercropping systems decreased by, respectively, 11.3%, 31.9%, and 36.2% compared to monoculture wheat, and the mean number of fertile florets per spike decreased by 26.4%, 37.4%, and 49.5%. Moreover, the apricot- and walnut-based intercropping systems deleteriously affected grain yield (constituent components spike number, grains per spike, and thousand grain weight) and decreased the total N, P, and K content of intercropping wheat. Tree shading intensity strongly enhanced the protein content, wet gluten content, falling number, dough development time, and dough stability time of wheat, but significantly decreased the softening degree. Strong negative linear correlations were observed between tree shade intensity and the number of fertile florets, grain yield (including spike number, grains per spike, and thousand grain weight), nutrient content (N, P and K), and softening degree of wheat. In contrast, we found that daily shade intensity was positively linearly correlated with protein content, wet gluten content, falling number, dough development time, and dough stability time. We conclude that jujube-based intercropping systems can be practical in the region, as they do not decrease the yield and quality of intercropping wheat. Further research should focus on the above-ground/below-ground interspecific interactions and the mechanisms behind the observations that we observed amongst the intercropping systems.

physiology↗

bioRxiv2018

Impact of Premorbid Infection on Onset and Disease Activity of Rheumatoid Arthritis

ObjectiveInfections have been implicated in rheumatoid arthritis (RA) development. However, the impact of premorbid infection on initiation and perpetuation of RA has not been well elucidated. Thus, we sought to conduct a large scale on-site survey to study whether premorbid infection may trigger RA and influence status of the disease.\n\nMethodsPremorbid infectious events were collected in cohort of 902 RA patients from December 2015 to June 2016. Type of infections prior to RA onset and its possible effects on disease status were analyzed.\n\nResultThree hundred and thirty-four out of 902 patients (37.03%) experienced infections within one month preceding RA onset. The most frequent infections were respiratory (16.08%), intestinal (11.09%) and urinary tract (9.87%) infection, respectively. The infection was associated with increased disease activity. Early onset was found in patients with urinary infection. High disease activity risk was increased in patients who pre-exposure to urinary infection (OR=3.813, 95%CI=1.717-12.418) and upper respiratory infection (OR=2.475, 95%CI= 0.971-6.312).\n\nConclusionPre-exposure infections are associated with development of RA. Severe disease status of RA and persistent of active disease status are related to preceding infections.

epidemiology↗

bioRxiv2018

Condition-adaptive fused graphical lasso (CFGL): an adaptive procedure for inferring condition-specific gene co-expression network

Co-expression network analysis provides useful information for studying gene regulation in biological processes. Examining condition-specific patterns of co-expression can provide insights into the underlying cellular processes activated in a particular condition. One challenge in this type of analysis is that the sample sizes in each condition are usually small, making the statistical inference of co-expression patterns highly underpowered. A joint network construction that borrows information from related structures across conditions has the potential to improve the power of the analysis.\n\nOne possible approach to constructing the co-expression network is to use the Gaussian graphical model. Though several methods are available for joint estimation of multiple graphical models, they do not fully account for the heterogeneity between samples and between co-expression patterns introduced by condition specificity. Here we develop the condition-adaptive fused graphical lasso (CFGL), a data-driven approach to incorporate condition specificity in the estimation of co-expression networks. We show that this method improves the accuracy with which networks are learned. The application of this method on a rat multi-tissue dataset and The Cancer Genome Atlas (TCGA) breast cancer dataset provides interesting biological insights. In both analyses, we identify numerous modules enriched for Gene Ontology functions and observe that the modules that are upregulated in a particular condition are often involved in condition-specific activities. Interestingly, we observe that the genes strongly associated with survival time in the TCGA dataset are less likely to be network hubs, suggesting that genes associated with cancer progression are likely to govern specific functions, rather than regulating a large number of biological processes. Additionally, we observed that the tumor-specific hub genes tend to have few shared edges with normal tissue, revealing tumor-specific regulatory mechanism.\n\nAuthor summaryGene co-expression networks provide insights into the mechanism of cellular activity and gene regulation. Condition-specific mechanisms may be identified by constructing and comparing co-expression networks of multiple conditions. We propose a novel statistical method to jointly construct co-expression networks for gene expression profiles from multiple conditions. By using a data-driven approach to capture condition-specific co-expression patterns, this method is effective in identifying both co-expression patterns that are specific to a condition and that are common across conditions. The application of this method on real datasets reveals interesting biological insights.

bioinformatics↗

bioRxiv2018

Type-2 CD8+ T lymphocytes responsive to PGD2 and LTE4 in severe eosinophilic asthma

The functions and in vivo roles of type-2 CD8+ T cells in humans have not been well defined and this cell type has been largely overlooked in models of disease. We investigated this in the context of severe asthma with persistent airway eosinophilia - a phenotype associated with high exacerbation risk and responsiveness to type-2 cytokine-targeted therapies. In two independent cohorts we show that, in contrast to Th2 cells, type-2 cytokine-secreting CD8+CRTH2+ (Tc2) cells are enriched in blood and airways in severe eosinophilic asthma. Concentrations of prostaglandin D2 (PGD2) and cysteinyl leukotriene E4 (LTE4) are also increased in the airways of the same group of patients. In vitro PGD2 and LTE4 function synergistically to trigger Tc2 cell recruitment and activation in a TCR-independent manner. These lipids regulate diverse genes in Tc2 cells inducing type-2 cytokines and many other pro-inflammatory cytokines and chemokines which could contribute to eosinophilia. These findings are consistent with an important innate-like role for human Tc2 cells in severe eosinophilic asthma and suggest a potential target for therapeutic intervention in this and other diseases.

immunology↗

bioRxiv2017

GWAS of epigenetic ageing rates in blood reveals a critical role for TERT

DNA methylation age is an accurate biomarker of chronological age and predicts lifespan, but its underlying molecular mechanisms are unknown. In this genome-wide association study of 9,907 individuals, we found gene variants mapping to five loci associated with intrinsic epigenetic age acceleration (IEAA) and gene variants in 3 loci associated extrinsic epigenetic age acceleration (EEAA). Mendelian randomization analysis suggested causal influences of menarche and menopause on IEAA and lipid levels on IEAA and EEAA. Variants associated with longer leukocyte telomere length (LTL) in the telomerase reverse transcriptase gene (TERT) locus at 5p15.33 confer higher IEAA (P<2.7x10-11). Causal modelling indicates TERT-specific and independent effects on LTL and IEAA. Experimental hTERT expression in primary human fibroblasts engenders a linear increase in DNA methylation age with cell population doubling number. Together, these findings indicate a critical role for hTERT in regulating the DNA methylation clock, in addition to its established role of compensating for cell replication-dependent telomere shortening.

genetics↗

bioRxiv2017

A toolbox of immunoprecipitation-grade monoclonal antibodies against human transcription factors.

A key component to overcoming the reproducibility crisis in biomedical research is the development of readily available, rigorously validated and renewable protein affinity reagents. As part of the NIH Protein Capture Reagents Program (PCRP), we have generated a collection of 1406 highly validated, immunoprecipitation (IP) and/or immunoblotting (IB) grade, mouse monoclonal antibodies (mAbs) to 736 human transcription factors. We used HuProt human protein microarrays to identify mAbs that recognize their cognate targets with exceptional specificity. Using an integrated production and validation pipeline, we validated these mAbs in multiple experimental applications, and have distributed them to the Developmental Studies Hybridoma Bank (DSHB) and several commercial suppliers. This study allowed us to perform a meta-analysis that identified critical variables that contribute to the generation of high quality mAbs. We find that using full-length antigens for immunization, in combination with HuProt analysis, provides the highest overall success rates. The efficiencies built into this pipeline ensure substantial cost savings compared to current standard practices.

biochemistry↗