Biology subjects

Zhang, G.

Publications and source records attributed to Zhang, G..

At least 307 records · Page 17Linked to original sources

bioRxiv2022

Structural analogue-based protein structure domain assembly assisted by deep learning

MotivationWith the breakthrough of AlphaFold2, the protein structure prediction problem has made a remarkable progress through end-to-end deep learning techniques, in which correct folds could be built for nearly all single-domain proteins. However, the full-chain modelling appears to be lower on average accuracy than that for the constituent domains and requires higher demand on computing hardware, indicating the performance of full-chain modelling still needs to be improved. In this study, we investigate whether the predicted accuracy of full-chain model can be further improved by domain assembly assisted by deep learning. ResultsIn this article, we developed a structural analogue-based protein structure domain assembly method assisted by deep learning, named SADA. In SADA, a multi-domain protein structure database (MPDB) was constructed for the full-chain analogue detection using individual domain models. Starting from the initial model constructed from the analogue, the domain assembly simulation was performed to generate the full-chain model through a two-stage differential evolution algorithm guided by the physics-based force field and an inter-residue distance potential predicted by deep learning. SADA was compared with the state-of-the-art domain assembly methods on 356 benchmark proteins, and the average TM-score of SADA models is 8.1% and 27.0% higher than that of DEMO and AIDA, respectively. We also assembled full-chain models of 20 human multi-domain proteins using individual domain models independently predicted by AlphaFold2, where the SADA full-chain models obtained a 4.8% higher average TM-score than full-chain models directly predicted by AlphaFold2 and fewer computing resources were required. In addition, we also find that the domains often interact in the similar way in the quaternary orientations if the domains have similar tertiary structures. Furthermore, homologous templates and structural analogues are complementary for multi-domain protein full-chain modelling. AvailabilityThe SADA web server are freely available at http://zhanglab-bioinf.com/SADA.

bioinformatics↗

bioRxiv2022

Spinning Disk Multifocal Microscopy for Dynamic Arbitrarily Shaped Surface Imaging at Centimetre Scale and Micrometre Resolution

The large-scale fluorescence microscopy has enabled the observation of dynamic physiological activities at the single cellular level across the mouse cortex, such as distributed neuronal population representations. However, video-rate high-resolution microscopy at sophisticated biological surfaces in nature keeps a challenging task for the tradeoff between the speed, resolution, and field of view. Here we propose Spinning Disk Multifocal Microscopy (SDiM) for arbitrarily shaped surfaces, which enables imaging at centimeter field-of-view, micrometer resolution and up to 30 frames per second across the depth range of 450 {micro}m. We apply this technique in various microscopic systems, including customized macroscopic systems and the Real-time Ultra-large-Scale imaging at High resolution macroscopy (RUSH), in both the reflective mode and the fluorescence mode, and in the study of cortex-wide single-neuron imaging and immune cell tracking. SDiM provides an opportunity for studying the cortex-wide multi-scale cellular interactions in biological tissues.

bioengineering↗

bioRxiv2022

A novel intranasal administration adenoviral vector-based platform for rapid COVID-19 vaccine development

The coronavirus SARS-CoV-2 has a severe impact on global public health, and the emerging variants threaten the efficacy of the circulating vaccines. Here, we report that a single vaccination with a non-replicating chimpanzee adenovirus-based vaccine against the SARS-CoV-2 Delta variant (JS1-delta) elicits potent humoral, cellular and mucosal immunity in mice. Additionally, a single intranasal administration of JS1-delta provides effective protection against the Delta (B.1.617.2) variant challenge in mice. This study indicates that chimpanzee adenovirus type 3 (ChAd3) derived vector represents a promising platform for antiviral vaccine development against respiratory infections and JS1-delta is worth further investigation in human clinical trials. HighlightsO_LIA new chimpanzee adenoviral vaccine against the SARS-CoV-2 Delta variant was developed. C_LIO_LIThe vaccine elicited potent humoral, cellular and mucosal immunity in mice. C_LIO_LIThe vaccine protected mice from the Delta variant challenge. C_LI

immunology↗

bioRxiv2022

Vector competence and transcriptional response of Aedes aegypti for Ebinur Lake virus, a newly mosquito-borne orthobunyavirus

The global impact of mosquito-borne diseases is increasing in the last decades. The newly classified orthobunyavirus, Ebinur Lake virus (EBIV) has been verified with highly virulent pathogenic to adult laboratory mice, and antibodies against EBIV have been detected in humans. As a potential emerging virus, it is necessary to assess the vector capacity of mosquitoes for EBIV to predicting its risk to public health. Herein, Aedes aegypti, the gradually important vector in China, was used as a model to evaluate the vector competence for EBIV. It was showed that EBIV can be transmitted by Ae. aegypti through oral feeding and the transmission rates could get to 11.8% at 14 days post infection (dpi). The highest infection rate, dissemination rate and ovary infection rate were 70%, 42.9%, and 29.4%, respectively. Through intrathoracic infection, Ae. aegypti was highly susceptible to EBIV and the transmission rates could get to 90% at 10 dpi. Moreover, the infection rate, dissemination rate and ovary infection rate were all 100%. Transcriptome analysis demonstrated EBIV can alter expressions of mosquito genes related to immune-related process and metabolism-related process. Defensin-C and chitinase 10 had been continuously down-regulated in the mosquitoes infected by intrathoracic inoculation. Our studies made the comprehensive analysis of the vector competence and transcriptional response of Ae. aegypti for EBIV, which implied the potential risk of EBIV to public health. Moreover, these findings indicated a complex interplay between EBIV and the mosquito immune system to affect the vector transmission capability.

molecular biology↗

bioRxiv2022

Functional characterization of a neuropeptide receptor exogenously expressed in Aplysia neurons

Neuropeptides act mostly on a class of G-protein coupled receptors, and play a fundamental role in the functions of neural circuits underlying behaviors. However, the functions of neuropeptide receptors are poorly understood. Here, we used the mollusc model system Aplysia and microinjected the exogenous neuropeptide receptor apATRPR (Aplysia Allatotropin-related peptide receptor) with an expression vector (pNEX3) into Aplysia neurons that did not express the receptor. Physiological experiments demonstrated that apATRPR could mediate the excitability increase activated by its ligand, apATRP (Aplysia Allatotropin-related peptide), in the Aplysia neurons that now express the receptor. This study provides the first definitive evidence for a physiological function of a neuropeptide receptor in molluscan animals.

neuroscience↗

bioRxiv2022

dbDEMC 3.0: Functional Exploration of Differentially Expressed miRNAs in Cancers of Human and Model Organisms

microRNAs (miRNAs) are important regulators in gene expression. The deregulation of miRNA expression is widely reported in the transformation from physiological to pathological state of cells. A large amount of differentially expressed miRNAs (DEMs) have been identified in various human cancers by using high-throughput technologies, such as microarray and miRNA-seq. Through mining of published researches with high-throughput experiment information, the database of differentially expressed miRNAs in human cancers (dbDEMC) was constructed with the aim of providing a systematic resource for the storage and query of the DEMs. Here we report an update of the dbDEMC to version 3.0, containing two-fold more data entries than the previous version, now including also data from mouse and rat. The dbDEMC 3.0 contains 3,268 unique DEMs in 40 different cancer types. The current datasets for differential expression analysis have expanded to 9 generalized categories. Moreover, the current release integrates functional annotations of DEMs obtained from experimentally validated targets. The annotations can greatly benefit integrative analysis of DEMs. In summary, dbDEMC 3.0 provides a valuable resource for characterizing molecular functions and regulatory mechanisms of DEMs in human cancers. The dbDEMC 3.0 is freely accessible at https://www.biosino.org/dbDEMC.

bioinformatics↗

bioRxiv2022

An atlas of gene expression variation across the Caenorhabditis elegans species

Phenotypic variation in diverse organism-level traits have been studied in Caenorhabditis elegans wild strains, but differences in gene expression and the underlying variation in regulatory mechanisms are largely unknown. Here, we use natural variation in gene expression to connect genetic variants to differences in organismal- level traits, including drug and toxicant responses. We performed transcriptomic analysis on 207 genetically distinct C. elegans wild strains to study natural regulatory variation of gene expression. Using this massive dataset, we performed genome-wide association mappings to investigate the genetic basis underlying gene expression variation and revealed complex genetic architectures. We found a large collection of hotspots enriched for expression quantitative trait loci across the genome. We further used mediation analysis to understand how gene expression variation could underlie organism-level phenotypic variation for a variety of complex traits. These results reveal the natural diversity in gene expression and possible regulatory mechanisms in this keystone model organism, highlighting the promise of gene expression variation in shaping phenotypic diversity.

genetics↗

bioRxiv2022

An allosteric agonist activates BK channels by perturbing coupling between Ca2+ binding and pore opening

BK type Ca2+-activated K+ channels activate in response to both the membrane voltage and intracellular Ca2+ with distinct mechanisms. Ca2+ binds to the cytosolic domain (CTD) to open the pore across the membrane, but the mechanism that couples Ca2+ binding to pore opening is not clear. Here we show that a compound, BC5, identified using in silico screening, interacts with BK channels at the interface between the CTD and the transmembrane voltage sensing domain (VSD) and enhances channel activity by specifically affecting the Ca2+ dependent mechanism. BC5 activates the channel in the absence of Ca2+ binding but Ca2+ binding inhibits BC5 effects. Thus, BC5 perturbs the pathway that couples Ca2+ binding to pore opening to allosterically affect both, which is supported by atomistic simulations and mutagensis. The results suggest that the CTD- VSD interaction makes a major contribution to the mechanism of Ca2+ dependent activation and is an important site for allosteric agonists to modulate BK channel activation.

biophysics↗

bioRxiv2022

Rapid deep widefield neuron finder driven by virtual calcium imaging data

Widefield microscope provides optical access to multi-millimeter fields of view and thousands of neurons in mammalian brains at video rate. However, calcium imaging at cellular resolution has been mostly contaminated by tissue scattering and background signals, making neuronal activities extraction challenging and time-consuming. Here we present a deep widefield neuron finder (DeepWonder), which is fueled by simulated calcium recordings but effectively works on experimental data with an order of magnitude faster speed and improved inference accuracy than traditional approaches. The efficient DeepWonder accomplished fifty-fold signal-to-background ratio enhancement in processing terabytes-scale cortex-wide recording, with over 14000 neurons extracted in 17 hours in workstation-grade computing resources compared to nearly week-long processing time with previous methods. DeepWonder circumvented the numerous computational resources and could serve as a guideline to massive data processing in widefield neuronal imaging.

bioengineering↗

bioRxiv2022

FRET monitoring of transcription factor activities in living bacteria

Bacteria adapt to the constantly changing environments largely by transcriptional regulation through the activities of various transcription factors (TFs). However, techniques that monitor the in situ TF-promoter interactions in living bacteria are lacking. Herein, we developed a whole-cell TF-promoter binding assay based on the intermolecular Forster resonance energy transfer (FRET) between a fluorescent unnatural amino acid CouA which is genetically encoded into defined sites in TFs and the live cell fluorescent nucleic acid stain SYTO 9. We show that this new FRET pair monitors the intricate TF-promoter interactions elicited by various types of signal transduction systems with specificity and sensitivity. Furthermore, the assay is applicable to identify novel modulators of the regulatory systems of interest and monitor TF activities in bacteria colonized in C. elegans. In conclusion, we established a tractable and sensitive TF-promoter binding assay in living bacteria which not only complements currently available approaches for DNA-protein interactions but also provides novel opportunities for functional annotation of bacterial signal transduction systems and studies of the bacteria-host interface.

molecular biology↗

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

Ontogenetic Color Switching in Lizards as a by-Product of Guanine Cell Development

Many animals undergo dramatic changes in colour during development1,2. Changes in predation risk during ontogeny are associated with spectacular switches in defensive colours, typically involving the replacement of skin or the production of new pigment cells3. Ontogenetic colour systems are ideal models for understanding the evolution and formation mechanisms of animal colour which remain largely enigmatic2. We show that defensive colour switching in lizards arises by reorganization of a single photonic system, as an incidental by-product of chromatophore maturation. The defensive blue tail colour of hatchling A. beershebensis lizards is produced by light scattering from premature guanine crystals in underdeveloped iridophore cells. Camouflaged adult tail colours emerge upon reorganization of the guanine crystals into a photonic reflector during chromatophore maturation. The substituent guanine crystals form by the attachment of individual nanoscopic plates, which coalesce during growth to form single crystals. Our results show that the blue colour of hatchlings is a fortuitous, but necessary, precursor to the development of adult colour. Striking functional colours in animals can thus arise not as distinct evolutionary innovations but via exploitation of the timing of naturally occurring changes in chromatophore cell development.

developmental biology↗

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

A haplotype-resolved genome assembly of the Nile rat facilitates exploration of the genetic basis of diabetes

The Nile rat (Avicanthis niloticus) is an important animal model for biomedical research, including the study of diurnal rhythms and type 2 diabetes. Here, we report a 2.5 Gb, chromosome-level reference genome assembly with fully resolved parental haplotypes, generated with the Vertebrate Genomes Project (VGP). The assembly is highly contiguous, with contig N50 of 11.1 Mb, scaffold N50 of 83 Mb, and 95.2% of the sequence assigned to chromosomes. We used a novel workflow to identify 3,613 segmental duplications and quantify duplicated genes. Comparative analyses revealed unique genomic features of the Nile rat, including those that affect genes associated with type 2 diabetes and metabolic dysfunctions. These include 14 genes that are heterozygous in the Nile rat or highly diverged from the house mouse. Our findings reflect the exceptional level of genomic detail present in this assembly, which will greatly expand the potential of the Nile rat as a model organism for genetic studies.

genomics↗

bioRxiv2021

Active forces in confluent cell monolayers

We use a computational phase-field model together with analytical analysis to study how inter-cellular active forces can mediate individual cell morphology and collective motion in a confluent cell monolayer. Contractile inter-cellular interactions lead to cell elongation, nematic ordering and active turbulence, characterised by motile topological defects. Extensile interactions result in frustration, and perpendicular cell orientations become more prevalent. Furthermore, we show that contractile behaviour can change to extensile behaviour if anisotropic fluctuations in cell shape are considered.

biophysics↗

bioRxiv2021

DomBpred: protein domain boundary predictor using inter-residue distance and domain-residue level clustering

Domain boundary prediction is one of the most important problems in the study of protein structure and function, especially for large proteins. At present, most domain boundary prediction methods have low accuracy and limitations in dealing with multi-domain proteins. In this study, we develop a sequence-based protein domain boundary predictor, named DomBpred. In DomBpred, the input sequence is firstly classified as either a single-domain protein or a multi-domain protein through a designed effective sequence metric based on a constructed single-domain sequence library. For the multi-domain protein, a domain-residue level clustering algorithm inspired by Ising model is proposed to cluster the spatially close residues according inter-residue distance. The unclassified residues and the residues at the edge of the cluster are then tuned by the secondary structure to form potential cut points. Finally, a domain boundary scoring function is proposed to recursively evaluate the potential cut points to generate the domain boundary. DomBpred is tested on a large-scale test set of FUpred comprising 2549 proteins. Experimental results show that DomBpred better performs than the state-of-the-art methods in classifying whether protein sequences are composed by single or multiple domains, and the Matthews correlation coefficient is 0.882. Moreover, on 849 multi-domain proteins, the domain boundary distance and normalised domain overlap scores of DomBpred are 0.523 and 0.824, respectively, which are 5.0% and 4.2% higher than those of the best comparison method, respectively. Comparison with other methods on the given test set shows that DomBpred outperforms most state-of-the-art sequence-based methods and even achieves better results than the top-level template-based method.

bioinformatics↗

bioRxiv2021

Transcriptome innovations in primates revealed by single-molecule long-read sequencing

Transcriptomic diversity greatly contributes to the fundamentals of disease, lineage-specific biology, and environmental adaptation. However, much of the actual isoform repertoire contributing to shaping primate evolution remains unknown. Here, we combined deep long- and short-read sequencing complemented with mass spectrometry proteomics in a panel of lymphoblastoid cell lines (LCLs) from human, three other great apes, and rhesus macaque, producing the largest full-length isoform catalog in primates to date. Our transcriptomes reveal thousands of novel transcripts, some of them under active translation, expanding and completing the repertoire of primate gene models. Our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these innovations with signals of positive selection and their limited impact in the proteome points to changes in alternative splicing in genes involved in immune response as an important target of recent regulatory divergence in primates.

evolutionary biology↗

bioRxiv2021

MPDB: a unified multi-domain protein structure database integrating structural analogue detection

With the development of protein structure prediction methods and biological experimental determination techniques, the structure of single-domain proteins can be relatively easier to be modeled or experimentally solved. However, more than 80% of eukaryotic proteins and 67% of prokaryotic proteins contain multiple domains. Constructing a unified multi-domain protein structure database will promote the research of multi-domain proteins, especially in the modeling of multi-domain protein structures. In this work, we develop a unified multi-domain protein structure database (MPDB). Based on MPDB, we also develop a server with two functional modules: (1) the culling module, which filters the whole MPDB according to input criteria; (2) the detection module, which identifies structural analogues of the full-chain according to the structural similarity between input domain models and the protein in MPDB. The module can discover the potential analogue structures, which will contribute to high-quality multi-domain protein structure modeling.

bioinformatics↗