Biology subjects

Yu, H.

Publications and source records attributed to Yu, H..

At least 451 records · Page 25Linked to original sources

bioRxiv2019

Chemistry of cation hydration and conduction in a skeletal muscle ryanodine receptor

Ryanodine receptors (RyRs) are Ca2+-regulated Ca2+ channels of 2.2-megadalton in muscles and neurons for calcium signaling. How Ca2+ regulates ion conduction in the RyR channels remains elusive. We determined a 2.6-[A] cryo-EM structure of rabbit skeletal muscle RyR1, and used multiscale dynamics simulations to elucidate cation interactions with RyR1. We investigated 21 potential cation-binding sites that may together rationalize biphasic Ca2+ response of RyR1. The selectivity filter captures a cation hydration complex by hydrogen-bonding with both the inner and outer hydration shells of water molecules. Molecular dynamics simulations suggest that adjacent Ca2+ ions moving in concert along ion-permeation pathway are separated by at least two cation-binding sites. Our analysis reveals that RyR1 has been evolved to favor its interactions with two hydration shells of cations.

biochemistry↗

bioRxiv2019

Simultaneous optimization of donor and acceptor substrate specificity for transketolase by a small but smart library

A narrow substrate range is a major limitation in exploiting enzymes more widely as catalysts in synthetic organic chemistry. For enzymes using two substrates, the simultaneous optimization of both substrate specificities, is also required for the rapid expansion of accepted substrates. Transketolase catalyses the reversible transfer of a C2-ketol unit from a donor substrate to an aldehyde acceptor and suffers the limitation of narrow substrate scope for widely industrial applications. Herein, transketolase from E. coli was engineered to simultaneously accept both pyruvate as a novel donor substrate, and unnatural acceptor aldehydes, including propanal, pentanal, hexanal and 3-formylbenzoic acid. Twenty single-mutant variants were firstly designed and characterized experimentally. Beneficial mutations were then recombined to construct a small but smart library. Screening of this library identified the best variant with a 9.2-fold improvement in the yield towards pyruvate and propionaldehyde, relative to WT. Pentanal and hexanal were used as acceptors to determine stereoselectivities of the reactions, which were found to be higher than 98% ee for the S configuration. Three variants were identified to be active for the reaction between pyruvate and 3-formylbenzoic acid. The best variant was able to convert 47% of substrate into product within 24 h, whereas no conversion was observed for WT. Docking experiments suggested a cooperation between the mutations responsible for donor and acceptor acceptances, that would promote the activity towards both the acceptor and donor. The variants obtained have the potential to be used for developing catalytic pathways to a diverse range of high-value products.

bioengineering↗

bioRxiv2019

Population genomics and pathotypic evaluation of the bacterial leaf blight pathogen of rice

Xanthomonas oryzae pv. oryzae (Xoo) causes bacterial blight disease, which reduces crop yield by up to 50% in rice production. Despite its substantial threat on food production worldwide, knowledge about its population structure, virulence diversity and the relationship between them is limited. We used whole-genome sequencing to explore the diversity and evolution of Xoo during the past 30 years in the main rice-planting areas of China. Six separate lineages were revealed by phylogenomic analysis, with CX-5 and CX-6 predominating in the population for decades. The recent sporadic outbreaks were respectively caused by Xoo derived from these lineages especially the two major ones. The lineage and sub-lineage distribution of isolates strongly correlated to their geographical origin, which was found to be mainly determined by the planting of the two major rice subspecies, indica and japonica. Large-scale virulence testing was conducted to evaluate the diversity of pathogenicity for Xoo. We found rapid virulence dynamics against rice, and its determinant factors including genetic background of Xoo, rice resistance genes and the planting environment of rice. Genetic background was investigated deeply by comparative genomics, which indicates that transposition events contributing the most to evolution of the Xoo genome and the rapid diversification of virulence. This study provided a good model to understand the evolution and dynamics of plant pathogens in the context of interaction with their hosts which are influenced by both geographical conditions and farming practices.

genomics↗

bioRxiv2019

Immune responses in mice induced by multi-epitope DNA vaccine and protein vaccine of Crimean-Congo Hemorrhagic Fever Virus

Crimean-Congo Hemorrhagic Fever (CCHF), caused by the CCHF virus (CCHFV), is a severe tick borne zoonosis widely distributed in over 30 countries and regions. Currently, there is no licensed vaccine available for CCHF in China. To evaluate the cellular and humoral immune responses induced by multi-epitope DNA and protein vaccine of CCHF in BALB/c mice, a multi-epitope gene (MEPX) segment with tandem including six highly conservative and immunedominant B cell epitopes was designed based on the analysis of hydrophilicity and antigenic determinant sites in amino acid sequences of nucleoprotein and glycoprotein from CCHFV strain YL04057. The single and double-copy multi-epitope gene (MEPX and MEPX2) were respectively cloned into the eukaryotic expression vector pVAX I to construct the recombinant (r) plasmid pVAX-MEPX and pVAX-MEPX2 as DNA vaccines. The results of immunofluorescence in vitro showed that the pVAX-MEPX and pVAX-MEPX2 could be expressed in 293T cells. The recombinant prokaryotic plasmid pET-32a-MEPX and pET-32a-MEPX2 constructed previously were transformed them into E. coli BL21 (DE3), and recombinant multi-epitope proteins (rMEPX and rMEPX2) were obtained and purificated by Nickel affinity chromatography. Western blot results showed that rMEPX and rMEPX2 had good antigenicity. BALB/c mice were immunized with DNA vaccine alone, protein vaccine alone, and DNA prime followed by recombinant protein boost immunization strategy, respectively. After three immunizations, MTT assay, cytokine content assay, and ELISA assay for antibody titers were used to evaluate the immune response. The proliferation of mouse specific T lymphocytes in the enhanced by pVAX-MEPX2 combined with rMEPX2 boosting group was significant, and the expression levels of serum IFN-{gamma} and IL-4 in mice were as high as 118.67 pg/mL and 135.33 pg/mL with significant difference compared to the control group (p<0.01), and serum antibody titer could reach up to 4.1x105. Double-copy multi-epitope vaccines groups (pVAX-MEPX2+ rMEPX2) generated better cellular and humoral immune responses by DNA prime-protein vaccine boost combinatorial immunization. This result could lay the foundation for the development of CCHFV multi-epitope vaccine candidates.

immunology↗

bioRxiv2019

RSVdb: A comprehensive database of in vivo mRNA structure

RNA fulfills a crucial regulatory role in cells by folding into a complex RNA structure. To date, a chemical compound, dimethyl sulfate (DMS), has been developed to effectively probe the RNA structure at the transcriptome level. We proposed a database, RSVdb (https://taolab.nwafu.edu.cn/rsvdb/), for the browsing and visualization of transcriptome RNA structures. RSVdb, including 626,225 RNAs with validated DMS reactivity from 178 samples in 8 species, supports four main functions: information retrieval, research overview, structure prediction, and resource download. Users can search for species, studies, transcripts and genes of interest; browse the quality control of sequencing data and statistical charts of RNA structure information; preview and perform online prediction of RNA structures in silico and under DMS restraint of different experimental treatments; and download RNA structure data for species and studies. Together, RSVdb provides a reference for RNA structure and will support future research on the function of RNA structure at the transcriptome level.

bioinformatics↗

bioRxiv2019

In-depth and 3-Dimensional Exploration of the Budding Yeast Phosphoproteome

Phosphorylation is one of the most dynamic and widespread post-translational modifications regulating virtually every aspect of eukaryotic cell biology. Here we present a comprehensive phosphoproteomic dataset for budding yeast, comprised of over 30,000 high confidence phosphorylation sites identified by mass spectrometry. This single dataset nearly doubles the size of the known phosphoproteome in budding yeast and defines a set of cell cycle-regulated phosphorylation events. With the goal of enhancing the identification of functional phosphorylation events, we performed computational positioning of phosphorylation sites on available 3D protein structures and systematically identified events predicted to regulate protein complex architecture. Results reveal a large number of phosphorylation sites mapping to or near protein interaction interfaces, many of which result in steric or electrostatic \"clashes\" predicted to disrupt the interaction. Phosphorylation site mutants experimentally validate our predictions and support a role for phosphorylation in negatively regulating protein-protein interactions. With the advancement of Cryo-EM and the increasing number of available structures, our approach should help drive the functional and spatial exploration of the phosphoproteome.

biochemistry↗

bioRxiv2019

GCA: An R package for genetic connectedness analysis using pedigree and genomic data

BackgroundGenetic connectedness is a critical component of genetic evaluation as it assesses the comparability of predicted genetic values across units. Genetic connectedness also plays an essential role in quantifying the linkage between reference and validation sets in whole-genome prediction. Despite its importance, there is no user-friendly software tool available to calculate connectedness statistics. ResultsWe developed the GCA R package to perform genetic connectedness analysis for pedigree and genomic data. The software implements a large collection of various connectedness statistics as a function of prediction error variance or variance of unit effect estimates. The GCA R package is available at GitHub and the source code is provided as open source. ConclusionsThe GCA R package allows users to easily assess the connectedness of their data. It is also useful to determine the potential risk of comparing predicted genetic values of individuals across units or measure the connectedness level between training and testing sets in genomic prediction.

genetics↗

bioRxiv2019

Guilty by association: How group-based (collective) guilt arises in the brain

People do not only feel guilty for transgressions of social norms/expectations that they are causally responsible for, but they also feel guilty for transgressions committed by those they identify as in-group (i.e., collective or group-based guilt). However, the neurocognitive basis of group-based guilt and its relation to personal guilt are unknown. To address these questions, we combined functional MRI with an interaction-based minimal group paradigm in which participants either directly caused harm to victims (i.e., personal guilt), or observed in-group members cause harm to the victims (i.e., group-based guilt). In three experiments (N = 90), we demonstrated that perceived shared responsibility with in-group members in the transgression predicted behavioral and neural manifestations of group-based guilt. Multivariate pattern analysis of the functional MRI data showed that group-based guilt recruited a similar brain representation in anterior middle cingulate cortex as personal guilt. These results have broaden our understanding of how group membership is integrated into social emotions.

neuroscience↗

bioRxiv2019

The Ca2+ Permeation Mechanism of the Ryanodine Receptor Revealed by a Multi-Site Ion Model

The ryanodine receptors (RyR) are ion channels responsible for the release of Ca2+ from the sarco/endoplasmic reticulum and play a crucial role in the precise control of Ca2+ concentration in the cytosol. The detailed permeation mechanism of Ca2+ through RyR is still elusive. By using molecular dynamics simulations with a specially designed Ca2+ model, here we show that multiple Ca2+ accumulate in the upper selectivity filter of RyR1, but only one Ca2+ can enter and translocate in the narrow pore at a time. The Ca2+ is nearly fully hydrated during the whole permeation process, with the first solvation shell intact even at the narrowest constrict sites of the selectivity filter and gate. These results present a one-at-a-time permeation pattern for the hydrated ions, which is distinct from the fully/partially dehydrated knock-on permeation in K+ and Na+ channels and uncovers the underlying reason for the high permeability and low selectivity of the RyR channels.

biophysics↗

bioRxiv2019

Linking genotypes with multiple phenotypes in single-cell CRISPR screens

CRISPR/Cas9 based functional screening coupled with single-cell RNA-seq (\"single-cell CRISPR screening\") unravels gene regulatory networks and enhancer-gene regulations in a large scale. We propose scMAGeCK, a computational framework to systematically identify genes and non-coding elements associated with multiple expression-based phenotypes in single-cell CRISPR screening. scMAGeCK identified genes and enhancers that modulate the expression of a known proliferation marker, MKI67 (Ki-67), a result that resembles the outcome of proliferation-linked CRISPR screening. We further performed single-cell CRISPR screening on mouse embryonic stem cells (mESC), and identified key genes associated with different pluripotency states. scMAGeCK enabled an unbiased construction of genotype-phenotype network, where multiple phenotypes can be regulated by different gene perturbations. Finally, we studied key factors that improve the statistical power of single-cell CRISPR screens, including target gene expression and the number of guide RNAs (gRNAs) per cell. Collectively, scMAGeCK is a novel and effective computational tool to study genotype-phenotype relationships at a single-cell level.

bioinformatics↗

bioRxiv2019

MRGPRX4 is a novel bile acid receptor in cholestatic itch

Patients with liver diseases often suffer from chronic itch or pruritus, yet the itch-causing pruritogen(s) and their cognate receptor(s) remain largely elusive. Using transcriptomics and GPCR activation assays, we found that an orphan, primate specific MRGPRX4 is expressed in human dorsal root ganglia (hDRG) and selectively activated by bile acids. In situ hybridization and immunohistochemistry revealed that MRGPRX4 is expressed in [~]7% of hDRG neurons and co-localizes with HRH1, a known itch-inducing GPCR. Bile acids elicited a robust Ca2+ response in a subset of cultured hDRG neurons, and intradermal injection of bile acids and an MRGPRX4 specific agonist induced significant itch in healthy human subjects. Surprisingly, application of agonist for TGR5, a known sequence conserved bile acid receptor previously implicated in cholestatic itch, failed to elicit Ca2+ response in cultured hDRG neurons, nor did it induce pruritus in human subjects. In situ hybridization and immunostaining results revealed that hTGR5 is selectively expressed in satellite glial cells, unlike mTGR5 (in mouse DRG neurons), likely accounting for the inter-species difference functionally. Finally, we found that patients with cholestatic itch have significantly higher plasma bile acid levels compared to non-itchy patients and the bile acid levels significantly decreased after itch relief. This elevated bile acid level in itchy patients is sufficient to activate MRGPRX4. Taken together, our data strongly suggest that MRGPRX4 is a novel bile acid receptor that likely underlies cholestatic itch, providing a promising new drug target for anti-itch therapies.

neuroscience↗

bioRxiv2019

Structure-based validation can drastically under-estimate error rate in proteome-wide cross-linking mass spectrometry studies

Recent, rapid advances in cross-linking mass spectrometry (XL-MS) has enabled detection of novel protein-protein interactions and their structural dynamics at the proteome scale. Given the importance and scale of the novel interactions identified in these proteome-wide XL-MS studies, thorough quality assessment is critical. Almost all current XL-MS studies validate cross-links against known 3D structures of representative protein complexes. However, current structure validation approach only includes cross-links where both peptides mapped to the 3D structures. Here we provide theoretical and experimental evidence demonstrating this approach can drastically underestimate error rates for proteome-wide XL-MS datasets. Addressing current shortcomings, we propose and demonstrate a comprehensive set of four metrics, including orthogonal experimental validation to thoroughly assess quality of proteome-wide XL-MS datasets.

systems biology↗

bioRxiv2019

Mutant p53 Drives Clonal Hematopoiesis through Modulating Epigenetic Pathway

Clonal hematopoiesis of indeterminate potential (CHIP) increases with age and is associated with increased risks of hematological malignancies. While TP53 mutations have been identified in CHIP, the molecular mechanisms by which mutant p53 promotes hematopoietic stem and progenitor cell (HSPC) expansion are largely unknown. We discovered that mutant p53 confers a competitive advantage to HSPCs following transplantation and promotes HSPC expansion after radiation-induced stress. Mechanistically, mutant p53 interacts with EZH2 and enhances its association with the chromatin, thereby increasing the levels of H3K27me3 in genes regulating HSPC self-renewal and differentiation. Further, genetic and pharmacological inhibition of EZH2 decrease the repopulating potential of p53 mutant HSPCs. Thus, we have uncovered an epigenetic mechanism by which mutant p53 drives clonal hematopoiesis. Our work will likely establish epigenetic regulator EZH2 as a novel therapeutic target for preventing CHIP progression and treating hematological malignancies with TP53 mutations.

cancer biology↗

bioRxiv2019

Inhibition of Osteoblast Proliferation and Migration by Exogenous and Endogenous Formaldehyde

Exogenous and endogenous formaldehyde (FA) plays an important role in cell growth and migration; however, its potential role in osteoblasts remains largely unclear. Cell counting kit-8 (CCK-8) and wound healing assays revealed that FA exposure at naturally occurring concentrations inhibited the proliferation and migration of mouse preosteoblast MC3T3-E1 cells. Moreover, RNA sequencing (RNA-seq) analysis revealed that FoxO1 signaling pathway components displayed distinct expression patterns upon FA exposure, reflected through significant enrichment of cell migration. In particular, FoxO1 Sirt1 and FA-induced related protein expression which were closely with cell proliferation and migration were confirmed by western blotting. The present results indicate that the FoxO1 pathway is involved in FA-induced inhibition of cell growth and migration.

cell biology↗

bioRxiv2019

Revealing new therapeutic opportunities through drug target prediction via class imbalance-tolerant machine learning

In silico drug target prediction provides valuable information for drug repurposing, understanding of side effects as well as expansion of the druggable genome. In particular, discovery of actionable drug targets is critical to developing targeted therapies for diseases. Here, we develop a robust method for drug target prediction by leveraging a class imbalance-tolerant machine learning framework with a novel training scheme. We incorporate novel features, including drug-gene phenotype similarity and gene expression profile similarity, that capture information orthogonal to other features. We show that our classifier achieves robust performance and is able to predict gene targets for new drugs as well as drugs that target unexplored genes. By providing newly predicted drug-target associations, we uncover novel opportunities of drug repurposing that may benefit cancer treatment through action on either known drug targets or currently undrugged genes.

bioinformatics↗

bioRxiv2019

Streamlined low-input transcriptomics through EASY-RNAseq

High-throughput sequencing for transcriptome profiling is an increasingly accessible and important tool for biological research. However, accurate profiling of small cell populations remains challenging due to issues with gene detection sensitivity and experimental complexity. Here we describe a streamlined RNAseq protocol (EASY RNAseq) for sensitive transcriptome assessment starting from low amount of input materials. EASY RNAseq is technically robust enough for sequencing small pools of homogenous and heterogeneous cells, recovering higher numbers of genes and with a more even expression distribution pattern than other commonly used methods. Application of EASY RNAseq to single human embryos at the 8-cell stage was able to achieve detection of 70% protein-coding genes. This workflow may thus serve as a useful tool for sensitive interrogation of rare cell populations.

genomics↗

bioRxiv2019

Leveraging genetic interaction for adverse drug-drug interaction prediction

In light of increased co-prescription of multiple drugs, the ability to discern and predict drug-drug interactions (DDI) has become crucial to guarantee the safety of patients undergoing treatment with multiple drugs. However, information on DDI profiles is incomplete and the experimental determination of DDIs is labor-intensive and time-consuming. Although previous studies have explored various feature spaces for in silico screening of interacting drug pairs, no method currently provides reliable predictions outside of their training sets. Here we demonstrate for the first time targets of adversely interacting drug pairs are significantly more likely to have synergistic genetic interactions than non-interacting drug pairs. Leveraging genetic interaction features and a novel training scheme, we construct a gradient boosting-based classifier that achieves robust DDI prediction even for drugs whose interaction profiles are completely unseen during training. We demonstrate that in addition to classification power--including the prediction of 432 novel DDIs--our genetic interaction approach offers interpretability by providing plausible mechanistic insights into the mode of action of DDIs.

bioinformatics↗

bioRxiv2019

MaXLinker: proteome-wide cross-link identifications with high specificity and sensitivity

Protein-protein interactions play a vital role in nearly all cellular functions. Hence, understanding their interaction patterns and three-dimensional structural conformations can provide crucial insights about various biological processes and underlying molecular mechanisms for many disease phenotypes. Cross-linking mass spectrometry has the unique capability to detect protein-protein interactions at a large scale along with spatial constraints between interaction partners. However, the current cross-link search algorithms follow an "MS2-centric" approach and, as a result, suffer from a high rate of mis-identified cross-links (~15%). We address this urgent problem, by designing a novel "MS3-centric" approach for cross-link identification and implemented it as a search engine called MaXLinker. MaXLinker significantly outperforms the current state of the art search engine with up to 18-fold lower false positive rate. Additionally, MaXLinker results in up to 31% more cross-links, demonstrating its superior sensitivity and specificity. Moreover, we performed proteome-wide cross-linking mass spectrometry using K562 cells. Employing MaXLinker, we unveiled the most comprehensive set of 9,319 unique cross-links at 1% false discovery rate, comprising 8,051 intraprotein and 1,268 interprotein cross-links. Finally, we experimentally validated the quality of a large number of novel interactions identified in our study, providing a conclusive evidence for MaXLinkers robust performance.

systems biology↗