Biology subjects

Zhou, X.

Publications and source records attributed to Zhou, X..

At least 487 records · Page 27Linked to original sources

bioRxiv2022

DelaySSAToolkit.jl: stochastic simulation of reaction systems with time delays in Julia

SummaryDelaySSAToolkit.jl is a Julia package for modelling reaction systems with non-Markovian dynamics, specifically those with time delays. These delays implicitly capture multiple intermediate reaction steps and hence serve as an effective model reduction technique for complex systems in biology, chemistry, ecology and genetics. The package implements a variety of exact formulations of the delay stochastic simulation algorithm. Contactxmfu@ecust.edu.cn, zcao@ecust.edu.cn, or ramon.grima@ed.ac.uk Availability and ImplementationThe source code and documentation of DelaySSAToolkit.jl are available at https://github.com/palmtree2013/DelaySSAToolkit.jl.

systems biology↗

bioRxiv2022

Microenvironmental sensing by fibroblasts controls macrophage population size

Animal tissues are comprised of diverse cell types. However, the mechanisms controlling the number of each cell type within tissue compartments remain poorly understood. Here, we report that different cell types utilize distinct strategies to control population numbers. Proliferation of fibroblasts, stromal cells important for tissue integrity, is limited by space availability. In contrast, proliferation of macrophages, innate immune cells involved in defense, repair, and homeostasis, is constrained by growth factor availability. Examination of density-dependent gene expression in fibroblasts revealed that Hippo and TGF-{beta} target genes are both regulated by cell density. We found YAP1, the transcriptional co-activator of the Hippo signaling pathway, directly regulates expression of Csf1, the lineage-specific growth factor for macrophages, through an enhancer of Csf1 that is specifically active in fibroblasts. Activation of YAP1 in fibroblasts elevates Csf1 expression and is sufficient to increase the number of macrophages at steady state. Our data also suggest that expression programs in fibroblasts that change with density may result from sensing of mechanical force through actin-dependent mechanisms. Altogether, we demonstrate that two different modes of population control are connected and coordinated to regulate cell numbers of distinct cell types. Sensing of the tissue environment may serve as a general strategy to control tissue composition. Significance StatementCollections of distinct cell types constitute animal tissues. To perform their unique functions, each cell type must exist in the correct number and proportion in a given tissue compartment. However, many of the mechanisms regulating and coordinating cell population sizes remain enigmatic. Our study characterizes two different modes of population size control, utilized by two ubiquitous cell types, macrophages and fibroblasts. Macrophage populations are more sensitive to the presence of growth factors in the environment and fibroblasts are more sensitive to space limitations. Intriguingly, space-sensing mechanisms in fibroblasts directly control the production of growth factor for macrophages and thus macrophage numbers. This link suggests a mechanism by which macrophage compartment size is controlled by stromal cells according to the microenvironment.

immunology↗

bioRxiv2022

Spatially Aware Dimension Reduction for Spatial Transcriptomics

Spatial transcriptomics are a collection of genomic technologies that have enabled transcriptomic profiling on tissues with spatial localization information. Analyzing spatial transcriptomic data is computationally challenging, as the data collected from various spatial transcriptomic technologies are often noisy and display substantial spatial correlation across tissue locations. Here, we develop a spatially-aware dimension reduction method, SpatialPCA, that can extract a low dimensional representation of the spatial transcriptomics data with enriched biological signal and preserved spatial correlation structure, thus unlocking many existing computational tools previously developed in single-cell RNAseq studies for tailored and novel analysis of spatial transcriptomics. We illustrate the benefits of SpatialPCA for spatial domain detection and explores its utility for trajectory inference on the tissue and for high-resolution spatial map construction. In the real data applications, SpatialPCA identifies key molecular and immunological signatures in a newly detected tumor surrounding microenvironment, including a tertiary lymphoid structure that shapes the gradual transcriptomic transition during tumorigenesis and metastasis. In addition, SpatialPCA detects the past neuronal developmental history that underlies the current transcriptomic landscape across tissue locations in the cortex.

genetics↗

bioRxiv2022

Outbreak.info: A standardized, searchable platform to discover and explore COVID-19 resources and data

To combat the ongoing COVID-19 pandemic, scientists have been conducting research at breakneck speeds, producing over 52,000 peer-reviewed articles within the first year. To address the challenge in tracking the vast amount of new research located in separate repositories, we developed outbreak.info Research Library, a standardized, searchable interface of COVID-19 and SARS-CoV-2 resources. Unifying metadata from sixteen repositories, we assembled a collection of over 350,000 publications, clinical trials, datasets, protocols, and other resources as of October 2022. We used a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public API, and R package. Finally, we discuss the challenges inherent in combining metadata from scattered and heterogeneous resources and provide recommendations to streamline this process to aid scientific research.

bioinformatics↗

bioRxiv2022

Molecular basis of broad neutralization against SARS-CoV-2 variants including Omicron by a human antibody

Omicron, a newly emerging SARS-CoV-2 variant, carried a large number of mutations in the spike protein leading to an unprecedented evasion from many neutralizing antibodies (nAbs). Here, we performed a head-to-head comparison of Omicron with other existing highly evasive variants in terms of their reduced sensitivities to antibodies, and found that Omicron variant is significantly more evasive than Beta and Mu variants. Of note, some key mutations occur in the conserved epitopes identified previously, especially in the binding sites of Class 4 nAbs, contributing to the increased Ab evasion. We also reported a broadly nAb (bnAb), VacW-209, which effectively neutralized all tested SARS-CoV-2 variants and even SARS-CoV. Finally, we determined six cryo-electron microscopy structures of VacW-209 complexed with the spike ectodomains of wild-type, Delta, Mu, C.1.2, Omicron, and SARS-CoV, and revealed the molecular basis of the broadly neutralizing activities of VacW-209 against SARS-CoV-2 variants. Overall, Omicron has once again raised the alarm over virus variation with significantly compromised neutralization. BnAbs targeting more conserved epitopes among variants will continue to play a key role in pandemic control and prevention. One sentence summaryStructural and functional analyses reveal that a human antibody named VacW-209 confers broad neutralization against SARS-CoV-2 variants including Omicron by recognizing a highly conserved epitope.

immunology↗

bioRxiv2022

TCF7L2 acts as a molecular switch in midbrain to control mammal vocalization through a transcriptional repression mechanism

Vocalization is an essential medium for sexual and social signaling in birds and mammals. Periaqueductal gray (PAG) a conserved midbrain structure is believed to be responsible for innate vocalizations, but its molecular regulation remains largely unknown. Here, through a mouse forward genetic screening we identified one of the key Wnt/ {beta}-catenin effectors TCF7L2/TCF4 controls ultrasonic vocalization (USV) production and syllable complexity during maternal deprivation and sexual encounter. Expression of TCF7L2 in PAG excitatory neurons is necessary for the complex trait, while TCF7L2 loss reduces neuronal gene expressions and synaptic transmission in PAG. TCF7L2-mediated vocal {beta}-catenin-binding domain but dependent of its DNA binding ability. Patient mutations associated with severe speech delay disrupt the transcriptional repression effect of TCF7L2, while mice carrying those mutations display severe USV impairments. Therefore, we conclude that TCF7L2 orchestrates gene expression in midbrain to control vocal production through a transcriptional repression mechanism.

neuroscience↗

bioRxiv2021

Joint dimension reduction and clustering analysis for single-cell RNA-seq and spatial transcriptomics data

Dimension reduction and (spatial) clustering is usually performed sequentially; however, the low-dimensional embeddings estimated in the dimension-reduction step may not be relevant to the class labels inferred in the clustering step. We therefore developed a computation method, Dimension-Reduction Spatial-Clustering (DR-SC), that can simultaneously perform dimension reduction and (spatial) clustering within a unified framework. Joint analysis by DR-SC produces accurate (spatial) clustering results and ensures the effective extraction of biologically informative low-dimensional features. DR-SC is applicable to spatial clustering in spatial transcriptomics that characterizes the spatial organization of the tissue by segregating it into multiple tissue structures. Here, DR-SC relies on a latent hidden Markov random field model to encourage the spatial smoothness of the detected spatial cluster boundaries. Underlying DR-SC is an efficient expectation-maximization algorithm based on an iterative conditional mode. As such, DR-SC is scalable to large sample sizes and can optimize the spatial smoothness parameter in a data-driven manner. With comprehensive simulations and real data applications, we show that DR-SC outperforms existing clustering and spatial clustering methods: it extracts more biologically relevant features than conventional dimension reduction methods, improves clustering performance, and offers improved trajectory inference and visualization for downstream trajectory inference analyses.

genomics↗

bioRxiv2021

SpaceX: Gene Co-expression Network Estimation for Spatial Transcriptomics

MotivationThe analysis of spatially-resolved transcriptome enables the understanding of the spatial interactions between the cellular environment and transcriptional regulation. In particular, the characterization of the gene-gene co-expression at distinct spatial locations or cell types in the tissue enables delineation of spatial co-regulatory patterns as opposed to standard differential single gene analyses. To enhance the ability and potential of spatial transcriptomics technologies to drive biological discovery, we develop a statistical framework to detect gene co-expression patterns in a spatially structured tissue consisting of different clusters in the form of cell classes or tissue domains. ResultsWe develop SpaceX (spatially dependent gene co-expression network), a Bayesian methodology to identify both shared and cluster-specific co-expression network across genes. SpaceX uses an over-dispersed spatial Poisson model coupled with a high-dimensional factor model which is based on a dimension reduction technique for computational efficiency. We show via simulations, accuracy gains in co-expression network estimation and structure by accounting for (increasing) spatial correlation and appropriate noise distributions. In-depth analysis of two spatial transcriptomics datasets in mouse hypothalamus and human breast cancer using SpaceX, detected multiple hub genes which are related to cognitive abilities for the hypothalamus data and multiple cancer genes (e.g. collagen family) from the tumor region for the breast cancer data. Availability and implementationThe SpaceX R-package is available at github.com/bayesrx/SpaceX. Contactxzhousph@umich.edu, veerab@umich.edu Supplementary informationSupplementary data are available at bookdown.org/satwik91/SpaceX_supplementary/.

bioinformatics↗

bioRxiv2021

Insight into the mechanism of H+-coupled nucleobase transport

Members of the nucleobase/ascorbic acid transporter (NAT) gene family are found in all kingdoms of life. In mammals, the concentrative uptake of ascorbic acid (vitamin C) by members of the NAT family is driven by the Na+ gradient, while the uptake of nucleobases in bacteria is powered by the H+ gradient. Here we report the structure and function PurTCp, a NAT family member from Colwellia psychrerythraea. The structure of PurTCp was determined to 2.80 [A] resolution by X-ray crystallography. PurTCp forms a homodimer and each protomer has 14 transmembrane segments folded into a substrate-binding domain (core domain) and an interface domain (gate domain) A purine base is present in the structure and defines the location of the substrate binding site. Functional studies reveal that PurTCp transports purines but not pyrimidines, and that purine binding and transport is dependent on the pH. Mutation of a conserved aspartate residue close to the substrate binding site reveals the critical role of this residue in H+-dependent transport of purines. Comparison of the PurTCp structure with transporters of the same structural fold suggests that rigid-body motions of the substrate-binding domain are central for substrate translocation across the membrane.

biochemistry↗

bioRxiv2021

Systems immune profiling of variant-specific vaccination against SARS-CoV-2

Lipid-nanoparticle(LNP)-mRNA vaccines offer protection against COVID-19. However, multiple variant lineages caused widespread breakthrough infections. There is no report on variant-specific vaccines to date. Here, we generated LNP-mRNAs specifically encoding wildtype, B.1.351 and B.1.617 SARS-CoV-2 spikes, and systematically studied their immune responses in animal models. All three LNP-mRNAs induced potent antibody responses in mice. However, WT-LNP-mRNA vaccination showed reduced neutralization against B.1.351 and B.1.617; and B.1.617-specific vaccination showed differential neutralization. All three vaccine candidates elicited antigen-specific CD8 and CD4 T cell responses. Single cell transcriptomics of B.1.351-LNP-mRNA and B.1.617-LNP-mRNA vaccinated animals revealed a systematic landscape of immune cell populations and global gene expression. Variant-specific vaccination induced a systemic increase in reactive CD8 T cell population, with a strong signature of transcriptional and translational machineries in lymphocytes. BCR-seq and TCR-seq unveiled repertoire diversity and clonal expansions in vaccinated animals. These data provide direct systems immune profiling of variant-specific LNP-mRNA vaccination in vivo.

immunology↗

bioRxiv2021

Structural basis of dynamic P5CS filaments

The bifunctional enzyme {Delta}1-pyrroline-5-carboxylate synthase (P5CS) is central to the synthesis of proline and ornithine. Pathogenic mutations in P5CS gene (ALDH18A1) lead to neurocutaneous syndrome and skin relaxation connective tissue disease in humans, and P5CS deficiency seriously damages the ability to resist adversity in plants, which has an essential role in agriculture and human health. Recently, P5CS has been demonstrated forming the cytoophidium in vivo and filaments in vitro. However, the underlying mechanism for the function of P5CS filamentation and catalyze the synthesis of P5C is hardly accessible without structural basis. Here, we have succeeded in determining the full-length structures of Drosophila P5CS filament in three states at resolution from 3.1 to 4.3 [A] under cryo-electron microscopy, we observed the distinct ligand-binding states and conformational changes for GK and GPR domain separately. These structures show the distinctive spiral filament is assembled by P5CS tetramers and stabilized by multiple interfaces. Point mutations that deplete such interactions disturb P5CS filamentation and greatly reduce the activity. Our findings reveal a previously undescribed mechanism that filamentation is crucial for the coordination between GK and GPR domains, and provide insights into structural basis for catalysis function of P5CS filament.

biochemistry↗

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

Ca2+ activity is required for injury-induced migration of microglia

ObjectivesMicroglia are the resident immune cells in the brain. Brain injury can activate the microglia and induce its directional migration towards injury sites for exerting immune functions. While extracellular ATP released from the injury site mediates the directionality of activated microglias migration, what endows activated microglia with migration capability remains largely unexplored. MethodsIn the present study, we used the larval zebrafish as an in vivo model to visualize the dynamics of both morphology and Ca2+ activity of microglia during its migration evoked by local brain injury. ResultsWe found that, in response to local injury, activated microglia exhibited an immediate Ca2+ transient and later elevated Ca2+ bursts frequency during its migration towards the local injury site (P < 0.01). Furthermore, suppression of Ca2+ activities significantly retarded microglial migration (P < 0.05). ConclusionThus, our study suggests that intracellular Ca2+ activity is required for activated microglias migration.

neuroscience↗

bioRxiv2021

A large-scale genome and transcriptome sequencing analysis reveals the mutation landscapes induced by high-activity adenine base editors in plants

BackgroundThe high-activity adenine base editors (ABEs), engineered with the recently-developed tRNA adenosine deaminases (TadA8e and TadA9), show robust base editing activity but raise concerns about off-target effects. ResultsIn this study, we performed a comprehensive evaluation of ABE8e- and ABE9-induced DNA and RNA mutations in Oryza sativa. Whole-genome sequencing analysis of plants transformed with four ABEs, including SpCas9n-TadA8e, SpCas9n-TadA9, SpCas9n-NG-TadA8e, and SpCas9n-NG-TadA9, revealed that ABEs harboring TadA9 lead to a higher number of off-target A-to-G (A>G) single-nucleotide variants (SNVs), and that those harboring the CRISPR/SpCas9n-NG lead to a higher total number of off-target SNVs in the rice genome. An analysis of the T-DNAs carrying the ABEs indicated that the on-target mutations could be introduced before and/or after T-DNA integration into plant genomes, with more off-target A>G SNVs forming after the ABEs had integrated into the plant genome. Furthermore, we detected off-target A>G RNA mutations in plants with high expression of ABEs but not in plants with low expression of ABEs. The off-target A>G RNA mutations tended to cluster, while off-target A>G DNA mutations rarely clustered. ConclusionOur findings that Cas proteins, TadA variants, temporal expression of ABEs, and expression levels of ABEs contribute to ABE specificity in rice provide insight into the specificity of ABEs and suggest alternative ways to increase ABE specificity besides engineering TadA variants.

plant biology↗

bioRxiv2021

Energy metabolism adaptations and gene expression reprogramming in a cellular MAFLD model

Mitochondrial dysfunction plays a critical role in metabolic associated fatty liver disease (MAFLD). This study aims to characterize mitochondrial dysfunctions in a human MAFLD Huh7 cell model triggered by free fatty acid (FFA) (palmitate and oleate) overload for 24 hours. We investigate its impact on cellular energy metabolism and identify potential targets for MAFLD treatment. FFA-treated cells displayed an accumulation of lipid droplets and slightly decreased viability but no significant changes in mitochondrial superoxide levels. Bioenergetic analysis showed a shift to more respiration and less glycolytic fermentation. Comprehensive transcriptomics and proteomics analyses identified changes in the expression of genes prominently involved in fatty acid handling and metabolism. The expressions of seven genes were consistently and significantly (p < 0.05) altered (4 upregulated and 3 downregulated genes) in both proteomics and transcriptomics. The FFA-treated Huh7 cell model is an appropriate in vitro model to study fatty acid metabolism and suitable to investigate the role of mitochondria, glycolysis, and multiple metabolic pathways in MAFLD. Our comprehensive analyses form a basis for drug discovery and screening using this model.

cell biology↗

bioRxiv2021

Structural basis of main proteases of coronavirus bound to drug candidate PF-07321332

The high mutation rate of COVID-19 and the prevalence of multiple variants strongly support the need for pharmacological options to complement vaccine strategies. One region that appears highly conserved among different genus of coronaviruses is the substrate binding site of the main protease (Mpro or 3CLpro), making it an attractive target for the development of broad-spectrum drugs for multiple coronaviruses. PF-07321332 developed by Pfizer is the first orally administered inhibitor targeting the main protease of SARS-CoV-2, which also has shown potency against other coronaviruses. Here we report three crystal structures of main protease of SARS-CoV-2, SARS-CoV and MERS-CoV bound to the inhibitor PF-07321332. The structures reveal a ligand-binding site that is conserved among SARS-CoV-2, SARS-CoV and MERS-CoV, providing insights into the mechanism of inhibition of viral replication. The long and narrow cavity in the cleft between domains I and II of main protease harbors multiple inhibitor binding sites, where PF-07321332 occupies subsites S1, S2 and S4 and appears more restricted compared with other inhibitors. A detailed analysis of these structures illuminated key structural determinants essential for inhibition and elucidated the binding mode of action of main proteases from different coronaviruses. Given the importance of main protease for the treatment of SARS-CoV-2 infection, insights derived from this study should accelerate the design of safer and more effective antivirals.

biophysics↗

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↗

bioRxiv2021

Gut microbiota analyses of Saudi populations for type 2 diabetes-related phenotypes reveals significant association

Large-scale gut microbiome sequencing has revealed key links between microbiome dysfunction and metabolic diseases such as T2D. To date, these efforts have largely focused on Western populations, with few studies assessing T2D microbiota associations in Middle Eastern communities where T2D prevalence is now over 20%. We analyzed the composition of stool 16S rRNA from 461 T2D and 119 non-T2Dparticipants from the Eastern Province of Saudi Arabia. We quantified the abundance of microbial communities to examine any significant differences between subpopulations of samples based on diabetes status and glucose level. We observed overall positive enrichment within diabetics compared to healthy individuals and amongst diabetic participants; those with high glucose levels exhibited slightly more positive enrichment compared to those at lower risk of fasting hyperglycemia. In particular, the genus Firmicutes was upregulated in diabetic participants compared to non-diabetic participants, and T2D was associated with an elevated Firmicutes/Bacteroidetes ratio, consistent with previous findings. Based on diabetes status and glucose levels of Saudi participants, relatively stable differences in stool composition were perceived by differential abundance and alpha diversity measures. Author summaryThe rates of Type 2 diabetes (T2D) in Saudi Arabia have risen dramatically in the last several decades due to socio-economic changes resulting in changes in dietary and sedentary lifestyles. This emergence has grown more rapidly and affects larger proportions of the population with estimates of T2D prevalence impacting 25% of the population. There is a paucity of microbiome data from Middle Eastern populations, and previous studies have been conducted on small sample sizes. Here we report on the first-ever characterization of gut microbiota T2D versus non-T2D and largest microbiome study ever conducted in a Middle Eastern country. The datasets from this study are important to create a regional reference T2D-microbiome catalogue which will propel the understanding of regional gut flora which are associated with T2D development. Based on T2D status and quantified glucose levels of Middle Eastern participants, relatively stable differences in stool composition were observed by differential abundance and alpha diversity measures. Comparing overlapping and varying patterns in gut microbiota with other studies is critical to assessing novel treatment options in light of a rapidly growing T2D health epidemic.

microbiology↗