Biology subjects

Luo, X.

Publications and source records attributed to Luo, X..

At least 217 records · Page 12Linked to original sources

bioRxiv2019

Bacterial Hyperswarming as a Protective Response to Intestinal Stress

Bacterial swarming, a collective movement on a surface, has rarely been associated with human pathophysiology. Here, we report for the first time that bacterial swarmers are associated with protection against intestinal inflammation. We show that bacterial swarmers are highly predictive of intestinal stress in mice and humans. We isolated a novel Enterobacter swarming strain, SM3, from mouse feces. SM3 and other known commensal swarmers contrast to their respective swarming-deficient, but swimming-competent isogenic strains abrogated intestinal inflammation in mice. Treatment of colitic mice with SM3, but not its mutants, enriched beneficial fecal anaerobes belonging to the family, Bacteroidales S24-7. We observed SM3 swarming associated pathways in the in vivo fecal metatranscriptomes. In vitro growth of S24-7 was enriched in presence of SM3 or its mutants conjecturing that bacterial swarming in vivo might influence SM3s access to S24-7 in the intestines. Overall, our work identifies a new paradigm in which intestinal stress allows for the emergence of swarming bacteria, which can counterintuitively heal intestinal inflammation.

microbiology↗

bioRxiv2019

Deepprune: Learning efficient and interpretable convolutional networks through weight pruning for predicting DNA-protein binding

Convolutional neural network (CNN) based methods have outperformed conventional machine learning methods in predicting the binding preference of DNA-protein binding. Although studies in the past have shown that more convolutional kernels help to achieve better performance, visualization of the model can be obscured by the use of many kernels, resulting in overfitting and reduced interpretation because the number of motifs in true models is limited. Therefore, we aim to arrive at high performance, but with limited kernel numbers, in CNN-based models for motif inference.\n\nWe herein present Deepprune, a novel deep learning framework, which prunes the weights in the dense layer and fine-tunes iteratively. These two steps enable the training of CNN-based models with limited kernel numbers, allowing easy interpretation of the learned model. We demonstrate that Deepprune significantly improves motif inference performance for the simulated datasets. Furthermore, we show that Deepprune outperforms the baseline with limited kernel numbers when inferring DNA-binding sites from ChIP-seq data.

bioinformatics↗

bioRxiv2019

Biological Pathways and Gene Networks Link Inflammation and Vascular Remodeling to Both Heart Failure with Preserved and Reduced Ejection Fraction in Women across Ethnicities

IntroductionHeart failure (HF) is understudied among women; especially, genomic evidence implicating shared or unique mechanisms of HF with respect to reduced or preserved ejection fraction (HFrEF, HFpEF) is lacking across ethnic populations of women. Prior genome-wide association studies (GWAS) have identified approximately 30 suggestive genetic variants for HF, although none have been specifically linked to HFrEF or HFpEF.\n\nObjectivesWe aimed to define, replicate, and annotate genetic variants to HFrEF, HFpEF, or both, as well as to investigate potential biological mechanisms underlying HFrEF and HFpEF among African American (AA) and European American (EA) women in three well-characterized, high-quality prospective cohorts, the Womens Health Initiative (WHI) study, the Jackson Heart Study (JHS), and the Framingham Heart Study (FHS).\n\nMethodsGWAS analysis on HFrEF and HFpEF were first performed among 7,982 AA and 4,133 EA in the WHI, followed by pathway analysis employing two independent methodological platforms (GSA-SNP and Mergeomics) curating KEGG, Reactome, and BioCarta pathway databases. GWAS signals and biological pathways identified using the WHI were replicated in the JHS and FHS. For all replicated pathways, we performed cross-phenotype and cross-ethnicity validation analyses to examine shared pathways between HFrEF and HFpEF, and phenotype-specific pathways, across ethnicities. We further prioritized key driver genes for HF according to specific pathways identified.\n\nResultsWe validated one previously reported genetic locus and identified six new ones, among which one locus was allocated to HFrEF and five to HFpEF. Additionally, we defined five biological pathways shared between HFrEF and HFpEF and discovered six HFpEF-specific pathways. These pathways overlapped in two main domains for molecular signaling: 1) inflammation and 2) vascular remodeling (including angiogenesis and vascular patterning), involving key driver genes from collagen and HLA gene families.\n\nConclusionsOur network analysis of three large prospective cohorts of women in the United States defined several novel loci for HF and its subtypes. In particular, several key driver genes reinforce the mechanistic role of inflammation and vascular remodeling in the development of HF, especially HFpEF. Given that therapeutic strategies developed for left ventricular dysfunction have had limited success for HFpEF, several new targets and pathways identified and validated in this study should be further assessed in risk stratification as well as the design of potential new HF interventions.

genetics↗

bioRxiv2019

Recommendations for application of the functional evidence PS3/BS3 criterion using the ACMG/AMP sequence variant interpretation framework

BackgroundThe American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) clinical variant interpretation guidelines established criteria (PS3/BS3) for functional assays that specified a \"strong\" level of evidence. However, they did not provide detailed guidance on how functional evidence should be evaluated, and differences in the application of the PS3/BS3 codes is a contributor to variant interpretation discordance between laboratories. This recommendation seeks to provide a more structured approach to the assessment of functional assays for variant interpretation and guidance on the use of various levels of strength based on assay validation.\n\nMethodsThe Clinical Genome Resource (ClinGen) Sequence Variant Interpretation (SVI) Working Group used curated functional evidence from ClinGen Variant Curation Expert Panel-developed rule specifications and expert opinions to refine the PS3/BS3 criteria over multiple in-person and virtual meetings. We estimated odds of pathogenicity for assays using various numbers of variant controls to determine the minimum controls required to reach moderate level evidence. Feedback from the ClinGen Steering Committee and outside experts were incorporated into the recommendations at multiple stages of development.\n\nResultsThe SVI Working Group developed recommendations for evaluators regarding the assessment of the clinical validity of functional data and a four-step provisional framework to determine the appropriate strength of evidence that can be applied in clinical variant interpretation. These steps are: 1. Define the disease mechanism; 2. Evaluate applicability of general classes of assays used in the field; 3. Evaluate validity of specific instances of assays; 4. Apply evidence to individual variant interpretation. We found that a minimum of eleven total pathogenic and benign variant controls are required to reach moderate-level evidence in the absence of rigorous statistical analysis.\n\nConclusionsThe recommendations and approach to functional evidence evaluation described here should help clarify the clinical variant interpretation process for functional assays. Further, we hope that these recommendations will help develop productive partnerships with basic scientists who have developed functional assays that are useful for interrogating the function of a variety of genes.

genetics↗

bioRxiv2019

Long-read assembly of the Chinese rhesus macaque genome and identification of ape-specific structural variants

Rhesus macaque (Macaca mulatta) is a widely-studied nonhuman primate. Here we present a high-quality de novo genome assembly of the Chinese rhesus macaque (rheMacS) using long-read sequencing and multiplatform scaffolding approaches. Compared to the current Indian rhesus macaque reference genome (rheMac8), the rheMacS genome assembly improves sequence contiguity by 75-fold, closing 21,940 of the remaining assembly gaps (60.8 Mbp). To improve gene annotation, we generated more than two million full-length transcripts from ten different tissues by long-read RNA sequencing. We sequence resolve 53,916 structural variants (96% novel) and identify 17,000 ape-specific structural variants (ASSVs) based on comparison to the long-read assembly of ape genomes. We show that many ASSVs map within ChIP-seq predicted enhancer regions where apes and macaque show diverged enhancer activity and gene expression. We further characterize a set of candidate ASSVs that may contribute to ape- or great-ape-specific phenotypic traits, including taillessness, brain volume expansion, improved manual dexterity, and large body size. This improved rheMacS genome assembly serves as an ideal reference for future biomedical and evolutionary studies.

genomics↗

bioRxiv2019

Expectation pooling: An effective and interpretable pooling method for predicting DNA-protein binding

MotivationConvolutional neural networks (CNNs) have outperformed conventional methods in modeling the sequence specificity of DNA-protein binding. While previous studies have built a connection between CNNs and probabilistic models, simple models of CNNs cannot achieve sufficient accuracy on this problem. Recently, some methods of neural networks have increased performance using complex neural networks whose results cannot be directly interpreted. However, it is difficult to combine probabilistic models and CNNs effectively to improve DNA-protein binding predictions.\n\nResultsIn this paper, we present a novel global pooling method: expectation pooling for predicting DNA-protein binding. Our pooling method stems naturally from the EM algorithm, and its benefits can be interpreted both statistically and via deep learning theory. Through experiments, we demonstrate that our pooling method improves the prediction performance DNA-protein binding. Our interpretable pooling method combines probabilistic ideas with global pooling by taking the expectations of inputs without increasing the number of parameters. We also analyze the hyperparameters in our method and propose optional structures to help fit different datasets. We explore how to effectively utilize these novel pooling methods and show that combining statistical methods with deep learning is highly beneficial, which is promising and meaningful for future studies in this field.\n\nContactdengmh@pku.edu.cn, gaog@mail.cbi.pku.edu.cn\n\nSupplementary informationAll code is public in https://github.com/gao-lab/ePooling

bioinformatics↗

bioRxiv2019

VGLUT2/ Cdk5/p25 Signaling Pathway Contributed to Inflammatory Pain By CFA

Vesicular glutamate transporter type 2 (VGLUT2) is known to play an important role in mediating the heat hyperalgesia induced by inflammation. However, the underlying mechanism for this activity is poorly understood. Cyclin-dependent kinase 5 (Cdk5), serving as a key regulator in mediating release of glutamate, contributed to the inflammatory heat. It remains unknown whether there is a bridge between Cdk5 and VGLUT2 for mediating inflammatory pain. Therefore, we designed the experiment to determine whether VGLUT2 signaling pathway is involved in Inflammatory pain mediated by Cdk5 and the heat hyperalgesia induced by complete Freunds adjuvant (CFA) can be reversed by roscovitine, a selective inhibitor for Cdk5 through inhibition of VGLUT2 expression. Immunohistochemistry results suggest that when compared with rats in a control group, rats in an experimental group showed significant coexpression of Cdk5/VGLUT2 in small and medium-sized neuronal cells of the dorsal root ganglion (DRG) and spinal cord between days 1 and 3 following subcutaneous injection of CFA. Moreover, our study revealed that the expression of VGLUT2 protein in DRG and spinal cord was remarkably increased between days 1 and 3 following CFA injection. Additionally, p25 but not p35, a activator of Cdk5, protein was significantly increased and reduced by roscovitine. The increased expressions of VGLUT2 protein was significantly reduced by roscovitine as well. Our study showed that VGLUT2/Cdk5 signaling pathway contributed to the inflammatory pain medicated by Cdk5/p25.

neuroscience↗

bioRxiv2019

Time-dependent Canonical Correlation Analysis for Multilevel Time Series

Canonical Correlation Analysis is a technique in multivariate data analysis for finding linear projections that maximize the correlation between two groups of variables. The correlations are typically defined without accounting for the serial correlations between observations, a typical setting for time series data. To understand the coupling dynamics and temporal variations between the two time-varying sources, we introduce the time-dependent canonical correlation analysis (TDCCA), a method for inferring time-dependent canonical vectors from multilevel time series data. A convex formulation of the problem is proposed, which leverages the singular value decomposition (SVD) characterization of all solutions of the CCA problem. We use simulated datasets to validate the proposed algorithm. Moreover, we propose a novel measure, canonical correlation variation as another way to assess the dynamic pattern of brain connections and we apply it to a real resting state fMRI dataset to study the aging effects on brain connectivity. Additionally, we explore our proposed method in a task-related fMRI to detect the temporal dynamics due to different motor tasks. We show that, compared to extant methods, the TDCCA-based approach not only detect temporal changes but also improves feature extraction. Together, this paper contributes broadly to new computational methodologies in understanding multilevel time series.

neuroscience↗

bioRxiv2019

UHPLC/MS based large-scale targeted metabolomics method for multiple-biological matrix assay

This new method has the capacity to dynamically analyse the metabolome of interest in diverse biological matrixes by offering coverage of rat urine, plasma, liver, brain, intestine, stomach, heart, spleen, lung, faeces, fresh plant tissues, cells and microbes. In addition, this new method enables specific and efficient analysis of microdontia metabolomes, non-microdontia and whole cell metabolomes, as well as can engage in absolute determination of 84 key clinical-wide metabolites in different biological matrixes, to enable the complementary support of clinical diagnosis and classification of diseases. To demonstrate the applicable capacity of this new method, multiple-matrixes differential metabolomes were firstly characterized using this new method to coordinate metabolic modifications underlie hepatitis induced by carbon tetrachloride (CCL4) in rats, such finding provides novel insight into the pathogenesis and therapeutics of hepatitis in clinic. Altogether, we are fully confident that this new metabolomics method will be widely welcomed by scientists in different niches to solve their key questions accordingly.

biochemistry↗

bioRxiv2019

An All-to-All Approach to the Identification of Sequence-Specific Readers for Epigenetic DNA Modifications on Cytosine

The authors have withdrawn their manuscript whilst they perform additional experiments to test some of their conclusions further. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.Competing Interest StatementThe authors have declared no competing interest.

systems biology↗

bioRxiv2019

Peptidoglycan associated cyclic lipopeptide disrupts viral infectivity

Enteric viruses exploit bacterial components including lipopolysaccharides (LPS) and peptidoglycan (PG) to facilitate infection in humans. With origins in the bat enteric system, we wondered if severe acute respiratory syndrome-coronavirus (SARS-CoV) or Middle East respiratory syndrome-CoV (MERS-CoV) also use bacterial components to modulate infectivity. To test this question, we incubated CoVs with LPS and PG and evaluated infectivity finding no change following LPS treatment. However, PG from B. subtilis reduced infection >10,000-fold while PG from other bacterial species failed to recapitulate this. Treatment with an alcohol solvent transferred inhibitory activity to the wash and mass spectrometry revealed surfactin, a cyclic lipopeptide antibiotic, as the inhibitory compound. This antibiotic had robust dose- and temperature-dependent inhibition of CoV infectivity. Mechanistic studies indicated that surfactin disrupts CoV virion integrity and surfactin treatment of the virus inoculum ablated infection in vivo. Finally, similar cyclic lipopeptides had no effect on CoV infectivity and the inhibitory effect of surfactin extended broadly to enveloped viruses including influenza, Ebola, Zika, Nipah, Chikungunya, Una, Mayaro, Dugbe, and Crimean-Congo hemorrhagic fever viruses. Overall, our results indicate that peptidoglycan-associated surfactin has broad virucidal activity and suggest bacteria byproducts may negatively modulate virus infection.\n\nImportanceIn this manuscript, we considered a role for bacteria in shaping coronavirus infection. Taking cues from studies of enteric viruses, we initially investigated how bacterial surface components might improve CoV infection. Instead, we found that peptidoglycan-associated surfactin is a potent viricidal compound that disrupts virion integrity with broad activity against enveloped viruses. Our results indicate that interactions with commensal bacterial may improve or disrupt viral infections highlighting the importance of understanding these microbial interactions and their implications for viral pathogenesis and treatment.

microbiology↗

bioRxiv2019

Monitoring the depth of anesthesia using Autoregressive model and Sample entropy

Anesthesia is an important part in modern surgery, and the way how to effectively monitor the depth of anesthesia (DOA) is core issue in the anesthesia work. Since anesthetics mainly affected the brain of patients, it is very effective to monitor DOA by electroencephalogram (EEG). This paper proposes a method for monitoring DOA using EEG. First, the sample entropy (SampEn) of EEG were calculated as a feature vector. Simultaneously, the Burg recursive algorithm was used to solve the autoregressive model (AR model) and AR coefficients were extracted as feature vectors. Later, according to the characteristics of uneven distribution of sample points, the weighted k-nearest neighbor (WKNN) classifier was selected. The Anesthesia was divided into awake, mild, moderate and deep by WKNN classifier. According to the results, the correlation coefficient between the SampEn of the EEG and Bispectral Index (BIS) is above 0.8. There is a correlation between the first five orders of AR coefficient and the BIS index, and the correlation of the second order reaches 0.8. Through the validation of 30 patients, this method can assessment of DOA effectively and accurately.

bioengineering↗

bioRxiv2019

TeraVR Empowers Precise Reconstruction of Complete 3-D Neuronal Morphology in the Whole Brain

Neuron morphology is recognized as a key determinant of cell type, yet the quantitative profiling of a mammalian neurons complete three-dimensional (3-D) morphology remains arduous when the neuron has complex arborization and long projection. Whole-brain reconstruction of neuron morphology is even more challenging as it involves processing tens of teravoxels of imaging data. Validating such reconstructions is extremely laborious. We developed TeraVR, an open-source virtual reality annotation system, to address these challenges. TeraVR integrates immersive and collaborative 3-D visualization, interaction, and hierarchical streaming of teravoxel-scale images. Using TeraVR, we produced precise 3-D full morphology of long-projecting neurons in whole mouse brains and developed a collaborative workflow for highly accurate neuronal reconstruction.

neuroscience↗

bioRxiv2019

Workshops increase invasive species reports to EDDMapS in the Mid-Atlantic United States

As the prevalence of smartphones and smartphone applications has penetrated the cellular phone market, and the capabilities of features within smartphones allowed for the replacement of commonly used mapping and identification tools, Bugwood developers began to release smartphone applications for reporting invasive species. To encourage and demonstrate reporting, workshops have been held to walk users through these apps features and overall EDDMapS capabilities. To ascertain the effectiveness of workshops in encouraging reporting via smartphone apps and the EDDMapS MAEDN website, a General Linear Model was used to evaluate the number of records received across the 2012-2017 time frame and evaluate if there was a difference in the number of records in the years MAEDN workshops were held at the Mid-Atlantic Invasive Plant Council conferences and workshops and years no MAEDN workshop was held. The model indicated that the workshops and time were significant factors in the number of records submitted. Being able to confidently demonstrate the effect that workshops can positively impact data recruitment can aid in funding for outreach and educational events.

scientific communication and education↗

bioRxiv2019

Seasonal Change of Microbial Diversity and Its Relation with Soil Chemical Properties in Orchard

This study aimed to determine the microbial diversity of different soil depths (0-5 and 5-20 cm) in a subtropical orchard during different seasons (i.e., Spring, Summer and Autumn) for enrich the knowledgements on micorbes roles in orchard ecosystem balance. In tracking experiments conducted in an orchard (established in 1996), the phospholipid fatty acid (PLFA) biomarker method was employed to know soil microbial system. Total PLFAs concentration did not vary significantly between soil depths but changed between seasons. It peaked in the summer at 258.97 {+/-} 23.48 g g-1 soil from 0-5 cm and at 270.99 {+/-} 58.94 g g-1 soil from 5-20 cm. A total of 33 microbial fatty acid biomarkers were observed and identified in the sampled soil. Quantities of PLFAs for 29 microbe groups varied significantly between seasons, except for 15:0 iso 3OH, 15:1 iso G, 16:0 2OH, and 17:0 iso 3OH. The bacterial PLFAs and fungal and actinomycotic PLFAs in the orchard soil collected in Summer were significantly higher than in the Spring or Autumn (P < 0.01). The number of soil microorganism species (Richness) and the Simpson and Shannon-Wiener indexes were all the highest in summer. The total PLFAs, bacterial PLFAs, fungal PLFAs, actinomycotic PLFAs, Richness, or the Simpson and Shannon-Wiener indexes were all significantly negatively correlated with soil pH, total carbon (TOC), total nitrogen (TN) and cation-exchange capacity (CEC) (P < 0.05).

microbiology↗

bioRxiv2019

Temporal resolution of global gene expression and DNA methylation changes in the final phases of reprogramming towards induced pluripotency.

The generation of induced pluripotent stem cells (iPSCs) involves activation of the endogenous pluripotency circuitry and global DNA demethylation late in reprogramming, but temporal resolution of these events using existing markers is insufficient. Here, we generated murine transgenic lines harboring dual fluorescent reporters reflecting cell-state specific expression of the master pluripotency factor Oct4 and the 5-methylcytosine dioxygenase Tet1. By assessing reprogramming intermediates based on dual reporter patterns, we identified a sequential order of Tet1 and Oct4 gene activation at proximal and distal regulatory elements following pluripotency entry. Full induction of Tet1 marks a pivotal late intermediate stage occurring after a phase of global gene repression, and preceding full activation of Oct4 along with late naive pluripotency and germline-specific genes. Sequential activation of Tet1 further distinguishes two waves of global DNA demethylation, targeting distinct genomic features and largely uncoupled from transcriptional changes, with dynamics unique to iPSC reprogramming. Moreover, we demonstrate that loss of Tet1 is compatible with reprogramming towards full Oct4 gene activation, but generates iPSCs with aberrant DNA methylation, chromosomal instability during lineage priming and defective differentiation potential. Therefore, the transcriptional logic of Tet1 expression signals a deterministic epigenetic roadmap towards generation of high quality iPSCs.

cell biology↗

bioRxiv2019

Mammalian Amoeboid Swimming is propelled by molecular and not protrusion-based paddling in Lymphocytes

Mammalian cells developed two main migration modes. The slow mesenchymatous mode, like fibroblasts crawling, relies on maturation of adhesion complexes and actin fiber traction, while the fast amoeboid mode, observed exclusively for leukocytes and cancer cells, is characterized by weak adhesion, highly dynamic cell shapes, and ubiquitous motility on 2D and in 3D solid matrix. In both cases, interactions with the substrate by adhesion or friction are widely accepted as a prerequisite for mammalian cell motility, which precludes swimming. We show here experimentally and computationally that leukocytes do swim, and that propulsion is not fueled by waves of cell deformation but by a rearward and inhomogeneous treadmilling of the cell envelope. We model the propulsion as a molecular paddling by transmembrane proteins linked to and advected by the actin cortex, whereas freely diffusing transmembrane proteins hinder swimming. This mechanism explains that swimming is five times slower than the cortex retrograde flow. Resultantly the ubiquitous ability of mammalian amoeboid cells to migrate in various environments can be explained for lymphocytes by a single machinery of envelope treadmilling.

biophysics↗

bioRxiv2019

Different integrins mediate haptotaxis of T lymphocytes towards either lower or higher adhesion zones

Guidance of cells by molecules anchored on a substrate, known as haptotaxis, is arguably crucial in development, immunology and cancer, however the exact cues and mechanisms driving cell orientation in vivo are hardly identified. Adhesive haptotaxis has been described in the case of mesenchymatous cells that develop strong pulling forces with their substrates and orient via a tug of war mechanism - a competition between cells pulling edges. In the case of amoeboid cells that migrate with minimal interaction with their substrate, existence of adhesive haptotaxis remains unclear. Here, we studied the crawling of human T lymphocytes on substrates with spatially modulated adhesivity, and observed haptotaxis with surface concentrations of integrin ligands found on high endothelial veinules. Overexpression of ICAM-1 and VCAM-1 molecules observed in vivo at transmigration portals can therefore promote leukocyte recruitment. Mechanistically, we show that integrin-mediated haptotaxis of lymphocytes differ both from active chemotaxis, because no mechanotransduction was detected, and from the passive tug of war mechanism of mesenchymatous cells, because different integrins support opposite phenotypes. Cells favored more adherent zones with VLA-4 and, counterintuitively, less adherent zones with LFA-1. These results reveal that integrins control differential adhesive haptotaxis behaviors without mechanotransduction, and this smart capability may support unsuspected ways for cells path selection.

biophysics↗