Biology subjects

Xu, G.

Publications and source records attributed to Xu, G..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

Retrospective varying coefficient association analysis of longitudinal binary traits: application to the identification of genetic loci associated with hypertension

Many genetic studies contain rich information on longitudinal phenotypes that require powerful analytical tools for optimal analysis. Genetic analysis of longitudinal data that incorporates temporal variation is important for understanding the genetic architecture and biological variation of complex diseases. Most of the existing methods assume that the contribution of genetic variants is constant over time and fail to capture the dynamic pattern of disease progression. However, the relative influence of genetic variants on complex traits fluctuates over time. In this study, we propose a retrospective varying coefficient mixed model association test, RVMMAT, to detect time-varying genetic effect on longitudinal binary traits. We model dynamic genetic effect using smoothing splines, estimate model parameters by maximizing a double penalized quasi-likelihood function, design a joint test using a Cauchy combination method, and evaluate statistical significance via a retrospective approach to achieve robustness to model misspecification. Through simulations, we illustrated that the retrospective varying-coefficient test was robust to model misspecification under different ascertainment schemes and gained power over the association methods assuming constant genetic effect. We applied RVMMAT to a genome-wide association analysis of longitudinal measure of hypertension in the Multi-Ethnic Study of Atherosclerosis. Pathway analysis identified two important pathways related to G-protein signaling and DNA damage. Our results demonstrated that RVMMAT could detect biologically relevant loci and pathways in a genome scan and provided insight into the genetic architecture of hypertension.

genetics↗

bioRxiv2022

A Common Resequencing-Based Genetic Marker Dataset for Global Maize Diversity

Maize (Zea mays ssp. mays) populations exhibit vast amounts of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole genome resequencing strategies, identifying millions of segregating single-nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies, and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here we employ resequencing data from 1,276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of [~]366 million segregating variants and [~]46 million high confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering time genes using previously published trait datasets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

plant biology↗

bioRxiv2022

Deciphering the non-coding code of pathogenicity and sexual differentiation in the human malaria parasite.

The complex life cycle of Plasmodium falciparum requires coordinated gene expression regulation to allow host cell invasion, transmission, and immune evasion. However, this cascade of transcripts is unlikely to be regulated by the limited number of identified parasite-specific transcription factors. Increasing evidence now suggests a major role for epigenetic mechanisms in gene expression in the parasite. In eukaryotes, many lncRNAs have been identified and shown to be pivotal regulators of genome structure and gene expression. To investigate the regulatory roles of lncRNAs in P. falciparum we explored the intergenic lncRNA distribution in nuclear and cytoplasmic subcellular locations. Using nascent RNA expression profiles, we identified a total of 1,768 lncRNAs, of which 58% were identified as novel lncRNAs in P. falciparum. The subcellular localization and stage-specific expression of several putative lncRNAs were validated using RNA fluorescence in situ hybridization (RNA-FISH). Additionally, the genome-wide occupancy of several candidate nuclear lncRNAs was explored using Chromatin Isolation by RNA Purification (ChIRP). ChIRP-seq of candidate lncRNAs revealed that lncRNA occupancy sites within the parasite genome are focal and sequence-specific with a particular enrichment for several parasite-specific gene families, including those involved in pathogenesis, erythrocyte remodeling, and regulation of sexual differentiation. We further validated the function of one specific lncRNA (lncRNA-ch14) using the CRISPR-Cas9 genome editing tool. Genomic and phenotypic analysis of the {bigtriangleup}lncRNA-ch14 line demonstrated the importance of this lncRNA in sexual differentiation and sexual reproduction. Our findings bring a new level of insight into the role of lncRNAs in pathogenicity, gene regulation and sexual differentiation. These findings also open new avenues for targeted approaches towards therapeutic strategies against the deadly malaria parasite.

microbiology↗

bioRxiv2022

OPUS-Fold3: a gradient-based protein all-atom folding and docking framework on TensorFlow

For refining and designing protein structures, it is essential to have an efficient protein folding and docking framework that generates a protein 3D structure based on given constraints. In this study, we introduce OPUS-Fold3 as a gradient-based, all-atom protein folding and docking framework, which accurately generates 3D protein structures in compliance with specified constraints, such as a potential function as long as it can be expressed as a function of positions of heavy atoms. Our tests show that, for example, OPUS-Fold3 achieves performance comparable to pyRosetta in backbone folding, and significantly better in side-chain modeling. Developed using Python and TensorFlow 2.4, OPUS-Fold3 is user-friendly for any source-code level modifications and can be seamlessly combined with other deep learning models, thus facilitating collaboration between the biology and AI communities. The source code of OPUS-Fold3 can be downloaded from http://github.com/OPUS-MaLab/opus_fold3. It is freely available for academic usage.

bioinformatics↗

bioRxiv2022

Propagation dynamics of electrotactic motility in large epithelial cell sheets

Directional migration initiated at the wound edge leads epithelial sheets to migrate in wound healing. How such coherent migration is achieved is not well understood. Here we used electric fields to induce robust migration of sheets of human keratinocytes and developed an in silico model to characterize initiation and propagation of epithelial collective migration. Electric fields initiate increase in migrations directionality and speed at the leading edge. The increases propagate across the epithelial sheets, resulting in directional migration of cell sheets as coherent units. Both the experimental and in silico models demonstrated vector-like integration of the electric and default directional cues at the free edge in space and time. The resultant collective migration is remarkably consistent in experiments and modeling, both qualitatively and quantitatively. The keratinocyte model thus faithfully reflects key features of epithelial migration as a coherent tissue in vivo, e.g. that leading cells lead, and that epithelium maintains cell- cell junction.

cell biology↗

bioRxiv2022

Novel insights into L-serine exporters in Corynebacterium glutamicum from gene mining and functional analysis

Amino acid exporters play an important role in regulating amino acid production by Corynebacterium glutamicum, and over 90% of amino acid export is attributed to exporters in this species. ThrE was reported to be an O_SCPLOWLC_SCPLOW-serine exporter, and SerE was identified as an O_SCPLOWLC_SCPLOW-serine exporter in our previous study. However, when both ThrE and SerE were deleted, the O_SCPLOWLC_SCPLOW-serine titer was decreased by 60%, suggesting other O_SCPLOWLC_SCPLOW-serine exporters may exist. In the present study, NCgl0254 and NCgl0255 were identified as novel O_SCPLOWLC_SCPLOW-serine exporters through comparative transcriptomics and gene functional analyses. The contributions of the four exporters (ThrE, SerE, NCgl0254 and NCgl0255) in O_SCPLOWLC_SCPLOW-serine export were studied by gene deletion, gene overexpression, amino acid export assay and real-time quantitative PCR (RT-qPCR). The results showed that SerE is the major O_SCPLOWLC_SCPLOW-serine exporter in C. glutamicum. Fermentation and amino acid export assays of SSAAI, SSAAI-serE-thrE-ncgl0254-ncgl0255 and SSAAI{Delta}serE{Delta}thrE{Delta}ncgl0254{Delta}ncgl0255 indicated that the four O_SCPLOWLC_SCPLOW-serine exporters undertake most of the O_SCPLOWLC_SCPLOW-serine export, and their overexpression enhanced export of O_SCPLOWLC_SCPLOW-serine in SSAAI. When one O_SCPLOWLC_SCPLOW-serine exporter was deleted, the transcription level of the other three exporters was upregulated. However, the decrease in O_SCPLOWLC_SCPLOW-serine titer caused by deletion of one exporter was not fully compensated by upregulation of the other three exporters at the transcription level, indicating that O_SCPLOWLC_SCPLOW-serine production by C. glutamicum may be determined by cooperative efficiency of all four O_SCPLOWLC_SCPLOW-serine exporters, with each being interdependent. IMPORTANCEThis work identified the novel O_SCPLOWLC_SCPLOW-serine exporters NCgl0254 and NCgl0255, and revealed their roles in O_SCPLOWLC_SCPLOW-serine export alongside the O_SCPLOWLC_SCPLOW-serine exporters. All four O_SCPLOWLC_SCPLOW-serine exporters are interdependent and undertake most of the O_SCPLOWLC_SCPLOW-serine export, but SerE is the major O_SCPLOWLC_SCPLOW-serine exporter. The findings expand our knowledge of amino acid exporters in C. glutamicum, and the approach can be employed for exploring of bacterial exporters of unknown function.

bioengineering↗

bioRxiv2022

Studying protein-protein interaction through side-chain modeling method OPUS-Mut

Protein side chains are vitally important to many biological processes such as protein-protein interaction. In this study, we evaluate the performance of our previous released side-chain modeling method OPUS-Mut, together with some other methods, on three oligomer datasets, CASP14 (11), CAMEO-Homo (65), and CAMEO-Hetero (21). The results show that OPUS-Mut outperforms other methods measured by all residues or by the interfacial residues. We also demonstrate our method on evaluating protein-protein docking pose on a dataset Oligomer-Dock (75) created using the top 10 predictions from ZDOCK 3.0.2. Our scoring function correctly identifies the native pose as the top-1 in 45 out of 75 targets. Different from traditional scoring functions, our method is based on the overall side-chain packing favorableness in accordance with the local packing environment. It emphasizes the significance of side chains and provides a new and effective scoring term for studying protein-protein interaction.

bioinformatics↗

bioRxiv2022

OPUS-Mut: studying the effect of protein mutation through side-chain modeling

Predicting the effect of protein mutation is crucial in many applications such as protein design, protein evolution, and genetic disease analysis. Structurally, the mutation is basically the replacement of the side chain of a particular residue. Therefore, accurate side-chain modeling is useful in studying the effect of mutation. Here, we propose a computational method, namely OPUS-Mut, which significantly outperforms other backbone-dependent side-chain modeling methods including our previous method OPUS-Rota4. We evaluate OPUS-Mut by four case studies on Myoglobin, p53, HIV-1 protease, and T4 lysozyme. The results show that the predicted structures of side chains of different mutants are consistent well with their experimentally determined results. In addition, when the residues with significant structural shifts upon the mutation are considered, it is found that the extent of the predicted structural shift of these affected residues can be correlated reasonably well with the functional changes of the mutant measured by experiments. OPUS-Mut can also help one to identify the harmful and benign mutations, and thus may guide the construction of a protein with relatively low sequence homology but with similar structure.

bioinformatics↗

bioRxiv2022

Phase-separated TRB-PRC2 aggregates contribute to Polycomb silencing in plants

Local accumulation of Polycomb Repressive Complex 2 (PRC2) is essential to gene silencing. Liquid-liquid phase separation (LLPS) mechanism is emerging as a paradigm to concentrate transcriptional machinery for effective gene regulation. Here, we elucidate that a rice single Myb transcription factor TRBF2 forms phase-separated droplets, which aggregate with PRC2 through direct protein interaction. Furthermore, TRB1, the closest homolog of TRBF2 in Arabidopsis, also forms phase-separated aggregates with PRC2. Mutants of TRBF2 and PRC2 component CLF display similar developmental defects, share common differentially expressed genes, and reduced H3K27me3 chromatin regions. Chromatin immunoprecipitation analysis supports that TRBF2 concentrates PRC2 at target loci to promote H3K27me3 deposition. Therefore, we propose that the aggregation of the plant-specific TRBs with PRC2 by the LLPS mechanism contributes to Polycomb silencing. One-Sentence SummaryThe phase-separated plant-specific single Myb transcription factor aggregates with PRC2 to facilitate Polycomb silencing.

plant biology↗

bioRxiv2022

Dual-Resolving of Lipid Positional and Geometric Isomers of C=C Bonds via Bifunctional Photocycloaddition-Photoisomerization Reaction System and Mass Spectrometry

The biological functions of lipids largely depend on their chemical structures. The position and configuration of C=C bonds are two of the essential attributes that determine the structures of unsaturated lipids. However, simultaneous identification of both attributes remains challenging. Here, we developed a bifunctional visible-light-activated photocycloaddition-photoisomerization reaction system, which enabled the dual-resolving of the positional and geometric isomerism of C=C bonds in lipids when combined with liquid chromatographic mass spectrometry. The dual-pathway reaction mechanism was demonstrated by experiments and density functional theory calculations. Based on this bifunctional reaction system, a workflow of deep structural lipidomics was established, and allowed the revealing of unique patterns of cis-trans-isomers in bacteria, as well as the tracking of C=C positional isomers changes in mouse brain ischemia. This study not only offers a powerful tool for deep lipid structural biology, but also provides a new paradigm for developing the multifunctional visible-light-induced reaction.

biochemistry↗

bioRxiv2022

A historically balanced locus under recent directional selection in responding to changed nitrogen conditions during modern maize breeding

Understanding the patterns of selection during plant evolution and recent crop improvement processes is the central topic in plant breeding and genetics. As an essential macronutrient for plant growth and development, nitrogen (N) is a key factor in affecting plant adaptation and crop improvement. The widespread adoption of less expensive industrial N fixation has dramatically reshaped plant morphology by favoring compact maize plants to tolerant crowding stress. The associated genetic changes, however, have not been systematically studied. Here, we investigated maize inbred lines developed before and after the 1960s -- the time point when inorganic N fertilizer started to be widely used for maize production. We identified a strong selective sweep exhibiting pronounced genomic differentiation between Old-Era (pre-1960s) and New-Era (post-1960s) inbred lines. Further study revealed population genetics statistics in the sweep exhibited patterns consistent with historical balancing selection. This balanced genomic interval is associated with a number of morphological, physiological, and metabolite traits related to vegetative N responses. A cluster of three glutamate receptor-like (GLR) genes is located within the region targeted by selection. Functional characterizations suggested differences in transcriptional activity of the GLR genes between the haplotypes carried by Old-Era and New-Era inbred lines likely play an essential role in mediating distinct N responses. The identification of both targets of selection and changes in the regulation of N responsive genes between maize lines developed in different eras sheds light on the N sensing and regulation pathways and paves the way to developing N resilient crops.

genomics↗

bioRxiv2022

CD8 T Cell Memory Inflation is Driven by Latent CMV Infection of Lymphatic Endothelial Cells

CMV, a ubiquitous herpesvirus, elicits an extraordinarily large T cell response that is sustained or increases over time, a phenomenon termed memory inflation. Remarkably, even latent, non-productive infection can drive memory inflation. Despite intense research on this phenomenon, the infected cell type(s) involved are unknown. To identify the responsible cell type(s), we designed a Cre-lox murine CMV (MCMV) system, where a spread-deficient ({Delta}gL) virus expresses recombinant SIINFEKL only in Cre+ host cells. We found that latent infection of endothelial cells (ECs), but not dendritic cells (DCs) or hepatocytes, was sufficient to drive CD8 T cell memory inflation. Infection of Lyve-1-Cre and Prox1-CreERT2 mice revealed that amongst EC subsets, infection of lymphatic ECs was sufficient. Genetic ablation of {beta}2m on lymphatic ECs did not prevent inflation, suggesting another unidentified cell type can also present antigen to CD8 T cells during latency. This novel system definitively shows that antigen presentation by lymphatic ECs drives robust CD8 T cell memory inflation. SUMMARYActive T cell immunosurveillance during latent CMV infection results in T cell memory inflation. A novel Cre-lox genetic system for cell-specific antigen expression reveals that lymphatic ECs, but not DCs or hepatocytes, can drive CD8 T cell memory inflation.

immunology↗

bioRxiv2022

Structural basis for the neurotropic AAV9 and the engineered AAVPHP.eB recognition with cellular receptors

Clade F adeno-associated virus (AAV) 9 has been utilized as therapeutic gene delivery vector, and it is capable of crossing blood brain barrier (BBB). Recently, an AAV9 based engineering serotype with enhanced BBB crossing ability, AAVPHP.eB, further expand clade F AAVs usages in the central nervous system (CNS) gene delivery. In this study, we determined the cryo-electron microscopy (cryo-EM) structures of the AAVPHP.eB, and its parental serotype AAV9 alone or in complex with their essential receptor Adeno-associated virus receptor (AAVR). These structures reveal the molecular details of their AAVR recognition, where the polycystic kidney disease (PKD) repeat domain 2 (PKD2) of AAVR interact to the 3-fold protrusions and the raised capsid regions between the 2- and 5-fold axes termed the 2/5-fold wall of both AAV9 and AAVPHP.eB virions. The interacting patterns of AAVR to AAV9 and AAVPHP.eB are similar with what was observed in AAV1/AAV2-AAVR complexes. Moreover, we found that AAVPHP.eB variable region VIII (VR-VIII) may independently facilitate the new receptor recognition responsible for enhanced CNS transduction. Our study provides insights into different receptor recognition for engineered AAVPHP.eB and parental serotype AAV9, and further reveal the potential molecular basis underlying their different tropism.

microbiology↗

bioRxiv2021

Proteomic Characterization of Serum Small Extracellular Vesicles in Human Breast Cancer

There is a lack of comprehensive understanding of breast cancer (BC) specific sEVs characteristics and composition on BC unique proteomic information from human samples. Here, we interrogated the proteomic landscape of sEVs in 167 serum samples from patients with BC, benign mammary disease (BD) and from healthy donors (HD). The analysis provides a comprehensive landscape of serum sEVs with totally 9,589 proteins identified, considerably expanding the panel of sEVs markers. Of note, serum BC-sEVs protein signatures were distinct from those of BD and HD, representing stage- and molecular subtype-specific patterns. We constructed specific sEVs protein identifiers that could serve as a liquid biopsy tool for diagnosis and classification of BC from benign mammary disease, molecular subtypes, as well as assessment of lymph node metastasis. We also identified 11 potential survival biomarkers for distant metastasis. This work may provide reference value for the accurate diagnosis and monitoring of BC progression using serum sEVs.

bioinformatics↗

bioRxiv2021

Maize root-associated microbes likely under adaptive selection by the host to enhance phenotypic performance

The root-associated microbiome (rhizobiome) plays a non-negligible role in determining plant health, stress tolerance, and nutrient use efficiency. However, it remains unclear to what extent the composition of the rhizobiome is governed by intraspecific variation in host plant genetics in the field and the degree to which host plant selection can reshape the composition of the rhizobiome. Here we quantify the rhizosphere microbial communities associated with a replicated diversity panel of 230 maize (Zea mays L.) genotypes grown in agronomically relevant conditions under high N (+N) and low N (-N) treatments. We show that the abundance of many root-associated microbes within a functional core microbial community of 150 abundant and consistently reproducible microbial groups is explainable by natural genetic variation in the host plant, with a greater proportion of microbial variance attributable to plant genetic variation in low N conditions. Population genetic approaches identify signatures of purifying selection in the maize genome associated with the abundance of several groups of microbes in the maize rhizobiome. Genome-wide association studies conducted using rhizobiome phenotypes identified n = 467 microbe-associated plant loci (MAPLs) in the maize genome linked to variation in the abundance of n = 115 microbial groups in the maize rhizosphere. In 62/115 cases, which is more than expected by chance, the abundance of these same microbial groups was correlated with variation in plant vigor indicators derived from high throughput phenotyping of the same field experiment. This study provides insights into harnessing the full potential of root-associated microbial symbionts in maize production.

plant biology↗

bioRxiv2021

CAR modulates plasma membrane nano-organization and immune signaling downstream of RALF1-FERONIA ligand-receptor signaling system

O_LIThe receptor-like kinase (RLK) FERONIA (FER) senses peptide ligands in the plasma membrane (PM), modulates plant growth and development, and integrates biotic and abiotic stress signaling for downstream adaptive response. However, the molecular interplay of these diverse processes is largely unknown. C_LIO_LIHere, we show that FER, the receptor of Rapid Alkalinization Factor 1 (RALF1), physically interacts with C2 domain ABA-related (CAR) proteins to control the nano-organization of the PM in Arabidopsis. C_LIO_LIDuring this process, the RALF1-FER pathway upregulates CAR protein translation, and then more CAR proteins are recruited to PM. This acts as a rapid feedforward loop to stabilize PM liquid-ordered phase. FER interacts with and phosphorylates CARs, and reducing their lipid-binding ability, which breaks the feedback regulation CAR activity at latter time point. C_LIO_LISimilar to FER mutant, pentuple car14569 mutants inhibit flg22-induced FLS2-BAK1 immune complex formation, which depends on the integrity of nanodomains. O_LITogether, we propose that the FER-CAR module controls the formation of the PM nano-organization during RALF signaling through a self-contained amplifying loop including both positive and negative feedbacks. C_LI C_LI

plant biology↗

bioRxiv2021

Serum glycoprotein markers in non-alcoholic steatohepatitis and hepatocellular carcinoma

Fatty liver disease progresses through stages of fat accumulation and inflammation to non-alcoholic steatohepatitis (NASH), fibrosis and cirrhosis and eventually hepatocellular carcinoma (HCC). Currently available diagnostic tools for HCC lack sensitivity and specificity and deliver little value to patients. In this study, we investigated the use of circulating serum glycoproteins to identify a panel of potential prognostic markers that may be indicative of progression from the healthy state to NASH and further to HCC. Serum samples were processed using a standard pre-analytical sample preparation protocol and were analyzed using a novel high throughput glycoproteomics platform. We analyzed 413 glycopeptides, representing 57 abundant serum proteins and compared among the three phenotypes. Our initial dataset contained healthy, NASH, and HCC serum samples. We analyzed normalized abundance of common glycoforms and found 40 glycopeptides with statistically significant differences in abundances in NASH and HCC compared to controls. Summary level relative abundance of core-fucosylated, sialylated and branched glycans containing glycopeptides were higher in NASH and HCC as compared to controls. We replicated some of our findings in an independent set of samples of individuals with benign liver conditions and HCC, respectively. Our results may be of value in the management of liver diseases. TOC only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/462486v2_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@91672corg.highwire.dtl.DTLVardef@cad49org.highwire.dtl.DTLVardef@4496b9org.highwire.dtl.DTLVardef@103615c_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2021

OPUS-Rota4: A Gradient-Based Protein Side-Chain Modeling Framework Assisted by Deep Learning-Based Predictors

Accurate protein side-chain modeling is crucial for protein folding and protein design. In the past decades, many successful methods have been proposed to address this issue. However, most of them depend on the discrete samples from the rotamer library, which may have limitations on their accuracies and usages. In this study, we report an open-source toolkit for protein side-chain modeling, named OPUS-Rota4. It consists of three modules: OPUS-RotaNN2, which predicts protein side-chain dihedral angles; OPUS-RotaCM, which measures the distance and orientation information between the side chain of different residue pairs; and OPUS-Fold2, which applies the constraints derived from the first two modules to guide side-chain modeling. In summary, OPUS-Rota4 adopts the dihedral angles predicted by OPUS-RotaNN2 as its initial states, and uses OPUS-Fold2 to refine the side-chain conformation with the constraints derived from OPUS-RotaCM. In this case, we convert the protein side-chain modeling problem into a side-chain contact map prediction problem. OPUS-Fold2 is written in Python and TensorFlow2.4, which is user-friendly to include other differentiable energy terms into its side-chain modeling procedure. In other words, OPUS-Rota4 provides a platform in which the protein side-chain conformation can be dynamically adjusted under the influence of other processes, such as protein-protein interaction. We apply OPUS-Rota4 on 15 FM predictions submitted by Alphafold2 on CASP14, the results show that the side chains modeled by OPUS-Rota4 are closer to their native counterparts than the side chains predicted by Alphafold2.

bioinformatics↗