Biology subjects

Zhao, K.

Publications and source records attributed to Zhao, K..

At least 91 records · Page 5Linked to original sources

bioRxiv2022

Hi-TrAC reveals fine-scale chromatin structures organized by transcription factors

The three-dimensional genomic structure plays a critical role in gene expression, cellular differentiation, and pathological conditions. It is pivotal to elucidate fine-scale chromatin architectures, especially interactions of regulatory elements, to understand the temporospatial regulation of gene expression. In this study, we report Hi-TrAC as a proximity ligation free, robust, and sensitive technique to profile genome-wide chromatin interactions at high-resolution among accessible regulatory elements. Hi-TrAC detects chromatin looping among accessible chromatin regions at single nucleosome resolution. With almost half-million identified loops, we constructed a comprehensive interaction network of regulatory elements across the genome. After integrating chromatin binding profiles of transcription factors, we discovered that cohesin complex and CTCF are responsible for organizing long-range chromatin loops, related to domain formation; whereas ZNF143 and HCFC1 are involved in structuring short-range chromatin loops between regulatory elements, which directly regulate gene expression. Thus, we developed a new methodology to identify a delicate and comprehensive network of cis-regulatory elements, revealing the complexity and a division of labor of TFs in chromatin looping for genome organization and gene expression.

genomics↗

bioRxiv2022

Relationship between biased mutagenesis and H3K4me1-targeted DNA repair in plants

Mutation is the ultimate source of genetic variation. Mutation rate variability has been observed within plant genomes, but the underlying mechanisms have been unclear. We previously found that mutations occur less often in functionally constrained regions of the genome in Arabidopsis thaliana and that this mutation rate reduction is predicted by H3K4me1, a histone modification found in the gene bodies of actively expressed and evolutionarily conserved genes in plants. We reanalyzed de novo germline single base substitutions in fast neutron irradiated mutation accumulation lines in Kitaake rice (Oryza sativa) and found the same reduction in mutations associated with H3K4me1, gene bodies, and constrained genes as in A. thaliana, suggesting conserved mechanisms for mutation reduction in plants. Here, we characterize a model of targeted DNA repair to explain these observations; PDS5C and MSH6 DNA repair-related proteins target H3K4me1 through their Tudor domains, resulting in nearby DNA experiencing elevated repair. Experimental data and in-silico modeling support the high affinity of the Tudor domain for H3K4me1 in both proteins, and that this affinity is conserved between plant species. ChIP-seq data from PDS5C confirms its localization to conserved and low mutation rate genome regions. Somatic and germline mutations observed by deep sequencing of wild-type and MSH6 knockout lines confirm that MSH6 preferentially repairs gene bodies and H3K4me1-enriched regions. These findings inspire further research to characterize the origins of mechanisms of targeted DNA repair in eukaryotes and their consequences on tuning the evolutionary trajectories of genomes.

genomics↗

bioRxiv2022

Scale Bar of Aging Trajectories for Screening Personal Rejuvenation Treatments

Although aging is an increasingly severe healthy, economic, and social global problem, it is far from well-modeling aging due to the aging processs complexity. To promote the aging modeling, here we did the quantitative measurement based on aging blood transcriptome. Specifically, the aging blood transcriptome landscape was constructed through ensemble modeling in a cohort of 505 people, and 1138 age-related genes were identified. To assess the aging rate in the linear dimension of aging, we constructed a simplified linear aging clock, which distinguished fast-aging and slow-aging populations and showed the differences in the composition of immune cells. Meanwhile, the non-linear dimension of aging revealed the transcriptome fluctuations with a crest around the age of 40 and showed that this crest came earlier and was more vigorous in the fast-aging population. Moreover, the aging clock was applied to evaluate the rejuvenation effect of molecules in vitro, such as Nicotinamide Mononucleotide (NMN) and Metformin. In sum, this study developed a de novo aging clock to evaluate agedependent precise medicine by revealing its fluctuation nature based on comprehensively mining the aging blood transcriptome, promoting the development of personal aging monitoring and anti-aging therapies.

bioengineering↗

bioRxiv2022

De novo protein structure prediction by incremental inter-residue geometries prediction and model quality assessment using deep learning

MotivationThe successful application of deep learning has promoted progress in protein model quality assessment. How to use model quality assessment to further improve the accuracy of protein structure prediction, especially not reliant on the existing templates, is helpful for unraveling the folding mechanism. Here, we investigate whether model quality assessment can be introduced into structure prediction to form a closed-loop feedback, and iteratively improve the accuracy of de novo protein structure prediction. ResultsIn this study, we propose a de novo protein structure prediction method called RocketX. In RocketX, a feedback mechanism is constructed through the geometric constraint prediction network GeomNet, the structural simulation module, and the model quality evaluation network EmaNet. In GeomNet, the co-evolutionary features extracted from MSA that search from the sequence databases are sent to an improved residual neural network to predict the inter-residue geometric constraints. The structure model is folded based on the predicted geometric constraints. In EmaNet, the 1D and 2D features are extracted from the folded model and sent to the deep residual neural network to estimate the inter-residue distance deviation and per-residue lDDT of the model, which will be fed back to GeomNet as dynamic features to correct the geometries prediction and progressively improve model accuracy. RocketX is tested on 483 benchmark proteins and 20 FM targets of CASP14. Experimental results show that the closed-loop feedback mechanism significantly contributes to the performance of RocketX, and the prediction accuracy of RocketX outperforms that of the state-of-the-art methods trRosetta (without templates) and RaptorX. In addition, the blind test results on CAMEO show that although no template is used, the prediction accuracy of RocketX on medium and hard targets is comparable to the advanced methods that integrate templates. AvailabilityThe RocketX web server are freely available at http://zhanglab-bioinf.com/RocketX. Contactzgj@zjut.edu.cn

bioinformatics↗

bioRxiv2022

Construct a variable-length fragment library for de novo protein structure prediction

Although remarkable achievements, such as AlphaFold2, have been made in end-to-end structure prediction, fragment libraries remain essential for de novo protein structure prediction, which can help explore and understand the protein-folding mechanism. In this work, we developed a variable-length fragment library (VFlib). In VFlib, a master structure database was first constructed from the Protein Data Bank through sequence clustering. The Hidden Markov Model (HMM) profile of each protein in the master structure database was generated by HHsuite, and the secondary structure of each protein was calculated by DSSP. For the query sequence, the HMM-profile was first constructed. Then, variable-length fragments were retrieved from the master structure database through dynamically variable-length profile-profile comparison. A complete method for chopping the query HMM-profile during this process was proposed to obtain fragments with increased diversity. Finally, secondary structure information was used to further screen the retrieved fragments to generate the final fragment library of specific query sequence. The experimental results obtained with a set of 120 nonredundant proteins showed that the global precision and coverage of the fragment library generated by VFlib were 55.04% and 94.95% at the RMSD cutoff of 1.5 [A], respectively. Compared to the benchmark method of NNMake, the global precision of our fragment library had increased by 62.89% with equivalent coverage. Furthermore, the fragments generated by VFlib and NNMake were used to predict structure models through fragment assembly. Controlled experimental results demonstrated that the average TM-score of VFlib was 16.00% higher than that of NNMake.

bioinformatics↗

bioRxiv2021

An enzyme-based system for the extraction of small extracellular vesicles from plants

Plant-derived nanovesicles (NVs) and extracellular vesicles (EVs) are considered to be the next generation of nanocarrier platforms for biotherapeutics and drug delivery. However, EVs exist not only in the extracellular space, but also within the cell wall. Due to the limitation of isolation methods, the extraction efficiency is low, resulting in the waste of a large number of plants, especially rare and expensive medicinal plants.There are few studies comparing EVs and NVs. To overcome these challenges, we proposed and validated a novel method for the isolation of plant EVs by degrading the plant cell wall with enzymes to release the EVs in the cell wall, making it easier for EVs to break the cell wall barrier and be collected. We extracted EVs from the roots of Morinda officinalis by enzymatic degradation(MOEVs) and nanoparticles by grinding method (MONVs) as a comparison group. The results showed smaller diameter and higher yield of MOEVs.Both MOEVs and MONVs were readily absorbed by endothelial cells without cytotoxicity and promoted the expression of miR-155. The difference is that the promotion of miR-155 by MOEVs is dose-effective. More importantly, MOEVs and MONVs are naturally characterized by bone enrichment. These results support that EVs in plants can be efficiently extracted by enzymatic cell wall digestion and also confirm the potential of MOEVs as therapeutic agents and drug carriers.

pharmacology and toxicology↗

bioRxiv2021

Cryo-EM structure of an amyloid fibril formed by full-length human SOD1 reveals its pathological conformational conversion

Amyotrophic lateral sclerosis (ALS) is a progressive, fatal neurodegenerative disease characterized by the selective death of motor neurons. Misfolded Cu, Zn-superoxide dismutase (SOD1) has been linked to both familial ALS and sporadic ALS. SOD1 fibrils formed in vitro are able to incorporate into cells, transmit intercellularly, and share toxic properties with ALS inclusions. Here we produced amyloid fibrils in vitro from recombinant, full-length apo human SOD1 under semi-reducing conditions and determined the atomic structure using cryo-EM. The SOD1 fibril consists of a single protofibril with a left-handed helix. The fibril core exhibits a serpentine fold comprising N-terminal segment (residues 3 to 55) and C-terminal segment (residues 86 to 153) with a structural break. The two segments are zipped up by three salt bridge pairs. By comparison with the structure of apo SOD1 dimer, we propose that eight {beta}-strands (to form a {beta}-barrel) and one -helix in the subunit of apo SOD1 convert into thirteen {beta}-strands stabilized by five hydrophobic cavities in the SOD1 fibril. Our data provide insights into how SOD1 converts between structurally and functionally distinct states.

biochemistry↗

bioRxiv2021

Prediction of drug targets for specific diseases leveraging gene perturbation data: A machine learning approach

Identification of the correct targets is a key element for successful drug development. However, there are limited approaches for predicting drug targets for specific diseases using omics data, and few have leveraged expression profiles from gene perturbations. We present a novel computational target discovery approach based on machine learning(ML) models. ML models are first trained on drug-induced expression profiles, with outcomes defined as whether the drug treats the studied disease. The goal is to "learn" expression patterns associated with treatment. The fitted ML models were then applied to expression profiles from gene perturbations(over-expression[OE]/knockdown[KD]). We prioritized targets based on predicted probabilities from the ML model, which reflects treatment potential. The methodology was applied to predict targets for hypertension, diabetes mellitus(DM), rheumatoid arthritis(RA) and schizophrenia(SCZ). We validated our approach by evaluating whether the identified targets may re-discover known drug targets from an external database(OpenTargets). We indeed found evidence of significant enrichment across all diseases under study. Further literature search revealed that many candidates were supported by previous studies. For example, we predicted PSMB8 inhibition to be associated with treatment of RA, which was supported by a study showing PSMB8 inhibitors(PR-957) ameliorated experimental RA in mice. In conclusion, we propose a new ML approach to integrate expression profiles from drugs and gene perturbations and validated the framework. Our approach is flexible and may provide an independent source of information when prioritizing targets.

bioinformatics↗

bioRxiv2021

Differential neutralization and inhibition of SARS-CoV-2 variants by antibodies elicited by COVID-19 mRNA vaccines

IntroductoryThe evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the emergence of many new variant lineages that have exacerbated the COVID-19 pandemic. Some of those variants were designated as variants of concern/interest (VOC/VOI) by national or international authorities based on many factors including their potential impact on vaccines. To ascertain and rank the risk of VOCs and VOIs, we analyzed their ability to escape from vaccine-induced antibodies. The variants showed differential reductions in neutralization and replication titers by post-vaccination sera. Although the Omicron variant showed the most escape from neutralization, sera collected after a third dose of vaccine (booster sera) retained moderate neutralizing activity against that variant. Therefore, vaccination remains the most effective strategy to combat the COVID-19 pandemic.

microbiology↗

bioRxiv2021

Asymmetrical choice-related ensemble activity in direct and indirect-pathway striatal neurons drives perceptual decisions

Sensory-guided decision-making is a vital brain function critically depending on the striatum, a key brain structure transforming sensorimotor information into actions. However, how the two opposing striatal pathways work in concert to select actions during decision-making remains controversial. Here, using cell-type specific two-photon imaging and optogenetic perturbations from the posterior dorsal striatum during decision-making behavior in mice, we uncover the population coding and causal mechanisms of the direct- and indirect-pathway spiny projection neurons (dSPNs and iSPNs) in decision-related action selection. Unexpected from prevailing models, we found that both dSPNs and iSPNs contain divergent subpopulations representing competing choices, and exhibit ensemble-level asymmetry: stronger contralateral dominance in dSPNs than in iSPNs. Such multi-ensemble competition/cooperation causally contributes to decision-related action selection, as supported by systematic optogenetic manipulations and verified by computational modeling. Our results unravel a multi-ensemble coordination mechanism in the striatum for action selection during decision-making.

neuroscience↗

bioRxiv2021

Spatiotemporal mapping of gene expression landscapes and developmental trajectories during zebrafish embryogenesis

Vertebrate embryogenesis is a remarkably dynamic process during which numerous cell types of different lineages generate, change, or disappear within a short period of time. A major challenge in understanding this process is the lack of topographical transcriptomic information that can help correlate microenvironmental cues within the hierarchy of cell fate decisions. Here, we employed Stereo-seq, a high-definition spatially resolved transcriptomic technology, to dissect the spatiotemporal dynamics of gene expression and regulatory networks in the developing zebrafish embryos. We profiled 91 embryo sections covering six critical time points during the first 24 hours of development, obtaining a total of 139,391 spots at cellular size ([~]100 m2) with spatial coordinates. Meanwhile, we identified spatial modules and co-varying genes for specific tissue organizations. By performing the integrative analysis of the Stereo-seq and scRNA-seq data from each time point, we reconstructed the spatially resolved developmental trajectories of cell fate transitions and molecular changes during zebrafish embryogenesis. We further investigated the spatial distribution of ligand-receptor pairs for major signaling pathways and identified novel interactions that potentially crosstalk with the Notch signaling pathway during zebrafish development. Our study constitutes a fundamental reference for further studies aiming to understand vertebrate development.

developmental biology↗

bioRxiv2021

Intracellular glycosyl hydrolase PslG shapes bacterial cell fate, signaling, and the biofilm development of Pseudomonas aeruginosa

Biofilm formation is one of most important causes leading to persistent infections. Exopolysaccharides are usually a main component of biofilm matrix. Genes encoding for glycosyl hydrolases are often found in gene clusters that are involved in the exopolysaccharide synthesis. It remains elusive about the functions of intracellular glycosyl hydrolase and why a polysaccharide synthesis gene cluster requires a glycosyl hydrolase. Here we systematically studied the role of intracellular PslG, a glycosyl hydrolase that is co-transcribed with 15 psl genes, which is responsible for the synthesis of exopolysaccharide Psl (ePsl), a key biofilm matrix polysaccharide in opportunistic pathogen Pseudomonas aeruginosa. We showed that lacking of PslG in this opportunistic pathogen alters the signaling function and structure of ePsl, changes the relative level of cyclic-di-GMP within daughter cells during cell division and shapes the localization of ePsl on bacterial periphery, thus results in long chains of bacterial cells, fast-forming and compact biofilm microcolonies. Our results reveal the important roles of intracellular PslG on the cell fate and biofilm development.

microbiology↗

bioRxiv2021

Sift-PULs: A public repository for specific functional polysaccharide utilization loci

BackgroundPolysaccharide utilization loci (PULs) were bacterial gene clusters encoding genes responsible for polysaccharide utilization process. PUL studies are blooming in recent years but the biochemical characterization speed is relative slow. There is a growing demand for PUL database with function annotations. ResultsUsing signature genes corresponding for specific polysaccharide, 10422 PULs specific for 6 polysaccharides (agar, alginate, pectin, carrageenan, chitin and {beta}-manan) from various bacterial phyla were predicted. Then online website of specific functional polysaccharide utilization loci (Sift-PULs) was constructed. Sift-PULs provides a repository where users could browse, search and download interested PULs without registration. ConclusionsThe key advantage of Sift-PULs is to assign a function annotation of each PUL, which is not available in existing PUL databases. PULs functional annotation lays a foundation for studying novel enzymes, new pathways, PUL evolution or bioengineering. The website is available on https://sift-puls.org

bioinformatics↗

bioRxiv2021

cLoops2: a full-stack comprehensive analytical tool for chromatin interactions

Investigating chromatin interactions between regulatory regions such as enhancer and promoter elements is vital for a deeper understanding of gene expression regulation. The emerging 3D mapping technologies focusing on enriched signals such as Hi-TrAC/TrAC-looping, compared to Hi-C and variants, reduce the sequencing cost and provide higher interaction resolution for cis-regulatory elements. A robust pipeline is needed for the comprehensive interpretation of these data, especially for loop-centric analysis. Therefore, we have developed a new versatile tool named cLoops2 for the full-stack analysis of the 3D chromatin interaction data. cLoops2 consists of core modules for peak-calling, loop-calling, differentially enriched loops calling and loops annotation. Additionally, it also contains multiple modules to carry out interaction resolution estimation, data similarity estimation, features quantification and aggregation analysis, and visualization. cLoops2 with documentation and example data are open source and freely available at GitHub: https://github.com/YaqiangCao/cLoops2.

bioinformatics↗

bioRxiv2021

A de novo protein structure prediction by iterative partition sampling, topology adjustment, and residue-level distance deviation optimization

MotivationWith the great progress of deep learning-based inter-residue contact/distance prediction, the discrete space formed by fragment assembly cannot satisfy the distance constraint well. Thus, the optimal solution of the continuous space may not be achieved. Designing an effective closed-loop continuous dihedral angle optimization strategy that complements the discrete fragment assembly is crucial to improve the performance of the distance-assisted fragment assembly method. ResultsIn this article, we proposed a de novo protein structure prediction method called IPTDFold based on closed-loop iterative partition sampling, topology adjustment and residue-level distance deviation optimization. First, local dihedral angle crossover and mutation operators are designed to explore the conformational space extensively and achieve information exchange between the conformations in the population. Then, the dihedral angle rotation model of loop region with partial inter-residue distance constraints is constructed, and the rotation angle satisfying the constraints is obtained by differential evolution algorithm, so as to adjust the spatial position relationship between the secondary structures. Lastly, the residue distance deviation is evaluated according to the difference between the conformation and the predicted distance, and the dihedral angle of the residue is optimized with biased probability. The final model is generated by iterating the above three steps. IPTDFold is tested on 462 benchmark proteins, 24 FM targets of CASP13, and 20 FM targets of CASP14. Results show that IPTDFold is significantly superior to the distance-assisted fragment assembly method Rosetta_D (Rosetta with distance). In particular, the prediction accuracy of IPTDFold does not decrease as the length of the protein increases. When using the same FastRelax protocol, the prediction accuracy of IPTDFold is significantly superior to that of trRosetta without orientation constraints, and is equivalent to that of the full version of trRosetta. AvailabilityThe source code and executable are freely available at https://github.com/iobio-zjut/IPTDFold. Contactzgj@zjut.edu.cn

bioinformatics↗

bioRxiv2021

A Bivalent Chromatin Controls Timing of Expression of Camalexin Biosynthesis Genes in Response to a Pathogen Signal in Arabidopsis

Temporal dynamics of gene expression underpins the responses to internal and environmental stimuli. In eukaryotes, regulation of gene induction includes changing chromatin states at the target genes, and recruitment of the transcriptional machinery that includes transcription factors. As one of the most potent specialized metabolites in Arabidopsis thaliana, camalexin can be rapidly induced by bacterial and fungal infections. Though several transcription factors controlling camalexin biosynthesis genes have been characterized, it remains unknown how the rapid activation of genes in this pathway upon a pathogen signal happens. By combining publicly available epigenomic data with in vivo chromatin mapping, we found that camalexin biosynthesis genes are marked with two epigenetic modifications with opposite effects on gene expression, H3K27me3 (repression) and H3K18ac (activation), to form a bivalent chromatin. Mutants with reduced H3K27m3 or H3K18ac showed that both modifications were required to determine the timing of gene expression and metabolite accumulation at an early stage of the stress response. Our study indicates that this type of bivalent chromatin, which we name a kairostat, plays an important role controlling the timely induction of gene expression upon stimuli in plants.

plant biology↗

bioRxiv2021

DEPDC1/ EEF1A1 complex promotes the progression of human osteosarcoma via downregulation of FOXO3a

There are currently lack of effective therapeutic strategies for osteosarcoma, primarily due to insufficient understanding of the underlying mechanisms of the tumor cells. This study deciphers a potentially critical interplay of DEPDC1-EEF1A1-FOXO3a axis during the osteosarcoma progression. Bioinformatics analysis of documented 25,035 genes for differentially expressed genes were accompanied by transcriptional and translational examinations of clinical osteosarcoma specimens and osteosarcoma cell lines to assess the roles and interactions of DEP domain-containing 1 (DEPDC1), Elongation Factor 1-alpha 1 (EEF1A1), and FOXO3a in the tumor cells proliferation and prognosis. Gene expression profile analysis and clinical tests revealed highly expressed DEPDC1 in human osteosarcoma cells and tumor tissues. Vector-mediated silence of DEPDC1 resulted in halted osteosarcoma cell proliferation, promoted apoptosis, and ceased tumor metastasis. Immunoprecipitation assay confirmed that EEF1A1 directly bind to DEPDC1 protein through three binding regions. Further, DEPDC1/EEF1A1 complex significantly decreased the expression of FOXO3a at transcription and translation levels, which subsequently promoted the proliferation of osteosarcoma cells and tumor metastasis. Correlation studies exhibited that overexpression of DEPDC1/EEF1A1 complex in the clinical specimens negatively correlated with the patient survival rate. In conclusion, DEPDC1-EEF1A1-FOXO3a axis plays as a critical pathway that regulates the progression and prognosis of osteosarcoma.

cell biology↗

bioRxiv2021

Effects of imidacloprid and thiamethoxam at LC30 and LC50 on the life table of soybean aphid Aphis glycines (Hemiptera: Aphididae)

The soybean aphid, Aphis glycines Matsumura (Hemiptera: Aphididae), is a main pests of soybean that poses a serious threat to its production. Studies were conducted to understand effects of the different concentrations of the insecticides (imidacloprid and thiamethoxam) on the life table of A. glycines to provide vital information for its effective management. We found that the mean generation time, adult and total pre-oviposition periods in A. glycines specimens exposed to LC50 imidacloprid and thiamethoxam were significantly longer than those in the control group. However, when exposed to LC30 imidacloprid and thiamethoxam, the adult pre-ovipositional period was significantly shorter than that in the control group. The mean fecundity per female adult, net reproductive rate, intrinsic rate of increase, and finite rate of increase were significantly decreased in individuals exposed to LC30 and LC50 concentrations of imidacloprid and thiamethoxam, respectively (P < 0.05). Both insecticides produce stress effects on A. glycines, and specimens treated with LC50 concentrations of the two insecticides exhibited a significant decrease in their growth rates than those treated with LC30 concentrations. This study provides data that can be used as a reference to predict the effect of imidacloprid and thiamethoxam on the population dynamics in the field, and agricultural producers could attach importance to prevent stimulation the reproduction made by low-lethal concentrations during actually applying pesticides.

pharmacology and toxicology↗