Biology subjects

Zhao, H.

Publications and source records attributed to Zhao, H..

At least 289 records · Page 16Linked to original sources

bioRxiv2024

CRISPR-repressed toxin-antitoxin provides population-level immunity against diverse anti-CRISPR elements

Prokaryotic CRISPR-Cas systems are highly vulnerable to phage-encoded anti-CRISPR (Acr) factors. How CRISPR-Cas systems protect themselves remains unclear. Here, we uncovered a broad-spectrum anti-anti-CRISPR strategy involving a phage-derived toxic protein. Transcription of this toxin is normally reppressed by the CRISPR-Cas effector, but is activated to halt cell division when the effector is inhibited by any anti-CRISPR proteins or RNAs. We showed that this abortive infection-like effect efficiently expels Acr elements from bacterial population. Furthermore, we exploited this anti-anti-CRISPR mechanism to develop a screening method for specific Acr candidates for a CRISPR-Cas system, and successfully identified two distinct Acr proteins that enhance the binding of CRISPR effector to non-target DNA. Our data highlight the broad-spectrum role of CRISPR-repressed toxins in counteracting various types of Acr factors, which illuminates that the regulatory function of CRISPR-Cas confers host cells herd immunity against Acr-encoding genetic invaders, no matter they are CRISPR-targeted or not.

microbiology↗

bioRxiv2024

Structural Basis of Conformational Dynamics in the PROTAC-Induced Protein Degradation

Pronounced conformational dynamics is unveiled upon analyzing multiple crystal structures of the same proteins recruited to the same E3 ligases by PROTACs, and yet, is largely permissive for targeted protein degradation due to the intrinsic mobility of E3 assemblies creating a large ubiquitylation zone. Mathematical modelling of ternary dynamics on ubiquitylation probability confirms the experimental finding that ternary complex rigidification need not correlate with enhanced protein degradation. Salt bridges are found to prevail in the PROTAC-induced ternary complexes, and may contribute to a positive cooperativity and prolonged half-life. The analysis highlights the importance of presenting lysines close to the active site of the E2 enzyme while constraining ternary dynamics in PROTAC design to achieve high degradation efficiency. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/572291v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@c41af3org.highwire.dtl.DTLVardef@c57f4eorg.highwire.dtl.DTLVardef@28fa14org.highwire.dtl.DTLVardef@3a4370_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2023

Activation of plant immunity through conversion of a helper NLR homodimer into a resistosome

Nucleotide-binding domain and leucine-rich repeat (NLR) proteins can engage in complex interactions to detect pathogens and execute a robust immune response via downstream helper NLRs. However, the biochemical mechanisms of helper NLR activation by upstream sensor NLRs remain poorly understood. Here, we show that the coiled-coil helper NLR NRC2 accumulates in vivo as a homodimer that converts into a higher order oligomer upon activation by its upstream virus disease resistance protein Rx. The Cryo-EM structure of NRC2 in its resting state revealed intermolecular interactions that mediate homodimer formation. These dimerization interfaces have diverged between paralogous NRC proteins to insulate critical network nodes and enable redundant immune pathways. Our results expand the molecular mechanisms of NLR activation pointing to transition from homodimers to higher-order oligomeric resistosomes.

plant biology↗

bioRxiv2023

Battery-Free Optoelectronic Patch for Photodynamic and Light Therapies in Treating Bacteria-Infected Wounds

Light therapy is an effective approach for the treatment of a variety of challenging dermatological conditions. In contrast to existing methods involving high doses and large areas of illumination, alternative strategies based on wearable designs that utilize a low light dose over an extended period provide a precise and convenient treatment. In this study, we present a battery-free, skin-integrated optoelectronic patch that incorporates a coil-powered circuit, an array of microscale violet and red light emitting diodes (LEDs), and polymer microneedles (MNs) loaded with 5-aminolevulinic acid (5-ALA). This polymer MNs, based on the biodegradable composite materials of polyvinyl alcohol (PVA) and hyaluronic acid (HA), serves as light waveguides for optical access and a medium for drug release into deeper skin layers. Unlike conventional clinical photomedical appliances with a rigid and fixed light source, this flexible design allows for a conformable light source that can be applied directly to the skin. In animal models with bacterial-infected wounds, the experimental group with the combination treatment of metronomic photodynamic and light therapies reduced 2.48 log10 CFU mL-1 in bactericidal level compared to the control group, indicating an effective anti-infective response. Furthermore, post-treatment analysis revealed the activation of proregenerative genes in monocyte and macrophage cell populations, suggesting enhanced tissue regeneration, neovascularization, and dermal recovery. Overall, this optoelectronic patch design broadens the scope for targeting deep skin lesions, and provides an alternative with the functionality of standard clinical light therapy methods.

bioengineering↗

bioRxiv2023

Assessing adverse effects and unspecific effects of transcutaneous spinal direct current stimulation (tsDCS)

BackgroundTranscutaneous spinal direct current stimulation (tsDCS) is a relatively recent method for non-invasively modulating neuronal activity in the human spinal cord. Despite its growing prominence, comprehensive studies addressing its potential adverse effects (AEs) and unspecific effects (UEs) are lacking. ObjectiveIn this study, we conducted a systematic investigation into the potential AEs and UEs of tsDCS in healthy volunteers. MethodsWe used a randomized double-blind within-participant design, employing anodal, cathodal and sham tsDCS of the thoracolumbar spinal cord. Our approach involved a newly-developed structured questionnaire (to assess subjectively-reported AEs) in combination with tsDCS-concurrent recording of skin conductance, cardiac and respiratory activity (to assess UEs in bodily state). ResultsThe most frequently participant-reported AEs were sensations of burning, tingling, and itching, although they were largely described as mild; skin redness (experimenter-reported) occurred even more frequently. Importantly, when comparing AEs between active and sham tsDCS via frequentist and Bayesian analysis approaches, the results were largely in favour of no difference between conditions (with the exception of skin redness). A similar picture emerged for most UE metrics, suggesting that tsDCS does not induce changes in bodily state, at least as measured by our autonomic nervous system metrics. ConclusionWe believe that the strategy employed here could serve as a starting point for a systematic AE and UE assessment in clinical populations, longitudinal designs and when stimulating different spinal sites. Taken together, our results contribute to assessing the tolerability, safety and specificity of tsDCS, in order to further the investigation of spinal cord function in health and disease.

neuroscience↗

bioRxiv2023

Differential developmental blueprints of organ-intrinsic nervous systems

The organ-intrinsic nervous system is a major interface between visceral organs and the brain, mediating important sensory and regulatory functions in the body-brain axis and serving as critical local processors for organ homeostasis. Molecularly, anatomically, and functionally, organ-intrinsic neurons are highly specialized for their host organs. However, the underlying mechanism that drives this specialization is largely unknown. Here, we describe the differential strategies utilized to achieve organ-specific organization between the enteric nervous system (ENS)1 and the intrinsic cardiac nervous system (ICNS)2, a neuronal network essential for heart performance but poorly characterized. Integrating high-resolution whole-embryo imaging, single-cell genomics, spatial transcriptomics, proteomics, and bioinformatics, we uncover that unlike the ENS which is highly mobile and colonizes the entire gastrointestinal (GI) tract, the ICNS uses a rich set of extracellular matrix (ECM) genes that match with surrounding heart cells and an intermediate dedicated neuronal progenitor state to stabilize itself for a beads-on-the-necklace organization on heart atria. While ICNS- and ENS-precursors are genetically similar, their differentiation paths are influenced by their host-organs, leading to distinct mature neuron types. Co-culturing ENS-precursors with heart cells shifts their identity towards the ICNS and induces the expression of heart-matching ECM genes. Our cross-organ study thus reveals fundamental principles for the maturation and specialization of organ-intrinsic neurons.

neuroscience↗

bioRxiv2023

scELMo: Embeddings from Language Models are Good Learners for Single-cell Data Analysis

Various Foundation Models (FMs) have been built based on the pre-training and fine-tuning framework to analyze single-cell data with different degrees of success. In this manuscript, we propose a method named scELMo (Single-cell Embedding from Language Models), to analyze single-cell data that utilizes Large Language Models (LLMs) as a generator for both the description of metadata information and the embeddings for such descriptions. We combine the embeddings from LLMs with the raw data under the zero-shot learning framework to further extend its function by using the fine-tuning framework to handle different tasks. We demonstrate that scELMo is capable of cell clustering, batch effect correction, and cell-type annotation without training a new model. Moreover, the fine-tuning framework of scELMo can help with more challenging tasks including in-silico treatment analysis or modeling perturbation. scELMo has a lighter structure and lower requirements for resources. Our method also outperforms recent large-scale FMs (such as scGPT [1], Geneformer [2]) and other LLM-based single-cell data analysis pipelines (such as GenePT [3] and GPTCelltype [4]) based on our evaluations, suggesting a promising path for developing domain-specific FMs.

bioinformatics↗

bioRxiv2023

metaExpertPro: a computational workflow for metaproteomics spectral library construction and data-independent acquisition mass spectrometry data analysis

BackgroundAnalysis of mass spectrometry-based metaproteomic data, in particular large-scale data-independent acquisition MS (DIA-MS) data, remains a computational challenge. Here, we aim to develop a software tool for efficiently constructing spectral libraries and analyzing extensive datasets of DIA-based metaproteomics. ResultsWe present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS (DDA-MS), protein identification and quantification using DIA-MS, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. To enhance accessibility and ease of use, all modules and dependencies are encapsulated within a Docker container. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap-based and PASEF-based DDA and DIA data. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples demonstrated that metaExpertPro quantified an average of 45,000 peptides in a 60-minute diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual False Discovery Rate (FDR) of less than 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67-0.90) in genus diversity and demonstrated a high correlation (rSpearman = 0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host. ConclusionsmetaExpertPro presents a robust one-stop computational solution for constructing metaproteomics spectral libraries, analyzing DIA-MS data, and annotating taxonomic as well as functional data.

microbiology↗

bioRxiv2023

A Bayesian Approach to Correcting the Attenuation Bias of Regression Using Polygenic Risk Score

Polygenic risk score (PRS) has become increasingly popular for predicting the value of complex traits. In many settings, PRS is used as a covariate in regression analysis to study the association between different phenotypes. However, measurement error in PRS causes attenuation bias in the estimation of regression coefficients. In this paper, we employ a Bayesian approach to accounting for the measurement error of PRS and correcting the attenuation bias in linear and logistic regression. Through simulation, we show that our approach is able to obtain approximately unbiased estimation of coefficients and credible intervals with correct coverage probability. We also empirically compare our Bayesian measurement error model to the conventional regression model by analyzing real traits in the UK Biobank. The results demonstrate the effectiveness of our approach as it significantly reduces the error in coefficient estimates.

genetics↗

bioRxiv2023

LDER-GE estimates phenotypic variance component of gene-environment interactions in human complex traits accurately with GE interaction summary statistics and full LD information

Gene-environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we introduce a statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by approximately 23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307,259 unrelated European-Ancestry subjects and 966,766 variants, across 151 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 35 significant E-Y pairs while LDSC-based method only identified 25 significant E-Y pairs with 23 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits.

genetics↗

bioRxiv2023

Assembly reactions of SARS-CoV-2 nucleocapsid protein with nucleic acid

The viral genome of SARS-CoV-2 is packaged by the nucleocapsid (N-) protein into ribonucleoprotein particles (RNPs), 38{+/-}10 of which are contained in each virion. Their architecture has remained unclear due to the pleomorphism of RNPs, the high flexibility of N-protein intrinsically disordered regions, and highly multivalent interactions between viral RNA and N-protein binding sites in both N-terminal (NTD) and C-terminal domain (CTD). Here we explore critical interaction motifs of RNPs by applying a combination of biophysical techniques to mutant proteins binding different nucleic acids in an in vitro assay for RNP formation, and by examining mutant proteins in a viral assembly assay. We find that nucleic acid-bound N-protein dimers oligomerize via a recently described protein-protein interface presented by a transient helix in its long disordered linker region between NTD and CTD. The resulting hexameric complexes are stabilized by multi-valent protein-nucleic acid interactions that establish crosslinks between dimeric subunits. Assemblies are stabilized by the dimeric CTD of N-protein offering more than one binding site for stem-loop RNA. Our study suggests a model for RNP assembly where N- protein scaffolding at high density on viral RNA is followed by cooperative multimerization through protein-protein interactions in the disordered linker.

biophysics↗

bioRxiv2023

Modulation of Biophysical Properties of Nucleocapsid Protein in the Mutant Spectrum of SARS-CoV-2

Genetic diversity is a hallmark of RNA viruses and the basis for their evolutionary success. Taking advantage of the uniquely large genomic database of SARS-CoV-2, we examine the impact of mutations across the spectrum of viable amino acid sequences on the biophysical phenotypes of the highly expressed and multifunctional nucleocapsid protein. We find variation in the physicochemical parameters of its extended intrinsically disordered regions (IDRs) sufficient to allow local plasticity, but also exhibiting functional constraints that similarly occur in related coronaviruses. In biophysical experiments with several N-protein species carrying mutations associated with major variants, we find that point mutations in the IDRs can have nonlocal impact and modulate thermodynamic stability, secondary structure, protein oligomeric state, particle formation, and liquid-liquid phase separation. In the Omicron variant, distant mutations in different IDRs have compensatory effects in shifting a delicate balance of interactions controlling protein assembly properties, and include the creation of a new protein-protein interaction interface in the N-terminal IDR through the defining P13L mutation. A picture emerges where genetic diversity is accompanied by significant variation in biophysical characteristics of functional N-protein species, in particular in the IDRs.

biophysics↗

bioRxiv2023

Enhancer regulatory networks globally connect non-coding breast cancer loci to cancer genes

Genetic studies have associated thousands of enhancers with breast cancer. However, the vast majority have not been functionally characterized. Thus, it remains unclear how variant-associated enhancers contribute to cancer. Here, we perform single-cell CRISPRi screens of 3,512 regulatory elements associated with breast cancer to measure the impact of these regions on transcriptional phenotypes. Analysis of >500,000 single-cell transcriptomes in two breast cancer cell lines shows that perturbation of variant-associated enhancers disrupts breast cancer gene programs. We observe variant-associated enhancers that directly or indirectly regulate the expression of cancer genes. We also find one-to-multiple and multiple-to-one network motifs where enhancers indirectly regulate cancer genes. Notably, multiple variant-associated enhancers indirectly regulate TP53. Comparative studies illustrate sub-type specific functions between enhancers in ER+ and ER- cells. Finally, we developed the pySpade package to facilitate analysis of single-cell enhancer screens. Overall, we demonstrate that enhancers form regulatory networks that link cancer genes in the genome, providing a more comprehensive understanding of the contribution of enhancers to breast cancer development.

genomics↗

bioRxiv2023

Chromosome-level scaffolding of haplotype-resolved assemblies using Hi-C data without reference genomes

Scaffolding is crucial for constructing most chromosome-level genomes. The high-throughput chromatin conformation capture (Hi-C) technology has become the primary scaffolding strategy due to its convenience and cost-effectiveness. As sequencing technologies and assembly algorithms advance, constructing haplotype-resolved genomes is increasingly preferred because haplotypes can provide additional genetic information on allelic and non-allelic variations. ALLHiC is a widely used allele-aware scaffolding tool designed for this purpose. However, its dependence on chromosome-level reference genomes and a higher chromosome misassignment rate still impede the unraveling of haplotype-resolved genomes. In this paper, we present HapHiC, a reference-independent allele-aware scaffolding tool with superior performance on chromosome assignment as well as contig ordering and orientation. Additionally, we provide new insights into the challenges in allele-aware scaffolding by conducting comprehensive analyses on various adverse factors. Finally, with the help of HapHiC, we constructed the haplotype-resolved allotriploid genome for Miscanthus x giganteus, an important lignocellulosic bioenergy crop. HapHiC is available at https://github.com/zengxiaofei/HapHiC.

bioinformatics↗

bioRxiv2023

Genome folding principles revealed in condensin-depleted mitotic chromosomes

During mitosis, condensin activity interferes with interphase chromatin structures. Here, we generated condensin-free mitotic chromosomes to investigate genome folding principles. Co- depletion of condensin I and II, but neither alone, triggered mitotic chromosome compartmentalization in ways that differ from interphase. Two distinct euchromatic compartments, indistinguishable in interphase, rapidly emerged upon condensin loss with different interaction preferences and dependence on H3K27ac. Constitutive heterochromatin gradually self-aggregated and co-compartmentalized with the facultative heterochromatin, contrasting with their separation during interphase. While topologically associating domains (TADs) and CTCF/cohesin mediated structural loops remained undetectable, cis-regulatory element contacts became apparent, providing an explanation for their quick re-establishment during mitotic exit. HP1 proteins, which are thought to partition constitutive heterochromatin, were absent from mitotic chromosomes, suggesting, surprisingly, that constitutive heterochromatin can self-aggregate without HP1. Indeed, in cells traversing from M- to G1-phase in the combined absence of HP1, HP1{Pi} and HP1{gamma}, re-established constitutive heterochromatin compartments normally. In sum, "clean-slate" condensin-deficient mitotic chromosomes illuminate mechanisms of genome compartmentalization not revealed in interphase cells.

genomics↗

bioRxiv2023

Vina-GPU 2.1: towards further optimizing docking speed and precision of AutoDock Vina and its derivatives

AutoDock Vina and its derivatives have established themselves as a prevailing pipeline for virtual screening in contemporary drug discovery. Our Vina-GPU method leverages the parallel computing power of GPUs to accelerate AutoDock Vina, and Vina-GPU 2.0 further enhances the speed of AutoDock Vina and its derivatives. Given the prevalence of large virtual screens in modern drug discovery, the improvement of speed and accuracy in virtual screening has become a longstanding challenge. In this study, we propose Vina-GPU 2.1, aimed at enhancing the docking speed and precision of AutoDock Vina and its derivatives through the integration of novel algorithms to facil-itate improved docking and virtual screening outcomes. Building upon the foundations laid by Vina-GPU 2.0, we introduce a novel algorithm, namely Reduced Iteration and Low Complexity BFGS (RILC-BFGS), designed to expedite the most time-consuming operation. Additionally, we implement grid cache optimization to further enhance the docking speed. Furthermore, we employ optimal strategies to individually optimize the structures of ligands, receptors, and binding pockets, thereby enhancing the docking precision. To assess the performance of Vina-GPU 2.1, we conduct extensive virtual screening experiments on three prominent targets, utilizing two fundamental compound libraries and seven docking tools. Our results demonstrate that Vina-GPU 2.1 achieves an average 4.97-fold acceleration in docking speed and an average 342% improvement in EF1% compared to Vina-GPU 2.0. The source code and tools for Vina-GPU 2.1 are freely available at https://github.com/DeltaGroupNJUPT/Vina-GPU-2.1, accompanied by comprehensive instructions and illustrative examples.

developmental biology↗

bioRxiv2023

Leveraging genetic correlations and multiple populations to improve genetic risk prediction for non-European populations

Genetic prediction accuracy for non-European populations is hindered by the limited sample size of Genome-wide association studies (GWAS) data in these populations. Additionally, it is challenging to tune model parameters with a small tuning dataset for methods that require tuning data, which is often the case for non-European samples. To address these challenges, we propose JointPRS, a novel, data-adaptive framework that simultaneously models multiple populations using GWAS summary statistics. JointPRS incorporates genetic correlation structures into the prediction framework, enabling accurate performance even without individual-level tuning data. Additionally, it uniquely employs a data-adaptive approach, providing a robust solution when only a small tuning dataset is available. Through extensive simulations and real data applications to 22 quantitative traits and four binary traits in five continental populations (European (EUR); East Asian (EAS); African (AFR); South Asian (SAS); and Admixed American (AMR)) evaluated using the UK Biobank (UKBB) and All of Us (AoU), we demonstrate that JointPRS outperforms six other state-of-art methods across three different data scenarios (no tuning data, tuning and testing data from the same cohort, and tuning and testing data from different cohorts) for most traits in non-European populations, while maintaining model simplicity and computational efficiency.

genetics↗

bioRxiv2023

Non-modular Fatty Acid Synthases Yield Unique Acylation in Ribosomal Peptides

Recent efforts in genome mining of ribosomally synthesized and post-translationally modified peptides (RiPPs) have expanded the diversity of post-translational modification chemistries1, 2. However, RiPPs are rarely reported as hybrid molecules incorporating biosynthetic machineries from other natural product families3-8. Here, we report lipoavitides, a class of RiPP/fatty acid hybrid lipopeptides that display a unique, membrane-targeting 4-hydroxy-2,4-dimethylpentanoyl (HMP)-modified N-terminus. The HMP is formed via condensation of isobutyryl-CoA and methylmalonyl-CoA catalyzed by a 3-ketoacyl-ACP synthase III enzyme, followed by successive tailoring reactions in the fatty acid biosynthetic pathway. The HMP and RiPP substructures are then connected by an acyltransferase exhibiting promiscuous activity towards the fatty acyl and RiPP substrates. Overall, the discovery of lipoavitides contributes a prototype of RiPP/fatty acid hybrids and provides possible enzymatic tools for lipopeptide bioengineering.

biochemistry↗