Biology subjects

Luo, Z.

Publications and source records attributed to Luo, Z..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Dynamic evolution of the heterochromatin sensing histone demethylase IBM1

Heterochromatin constitutes a fundamental aspect of genomes that is crucial for maintaining genome stability. In flowering plants, maintenance of heterochromatin relies on a positive feedback loop involving the histone 3 lysine nine methyltransferase (H3K9), KRYPTONITE (KYP), and the DNA methyltransferase, CHROMOMETHYLASE3 (CMT3). An H3K9 demethylase, INCREASED IN BONSAI METHYLATION 1 (IBM1), has evolved to modulate the activity of KYP-CMT3 within transcribed genes. The absence of IBM1 activity results in aberrant methylation of gene bodies, which is deleterious. This study demonstrates extensive genetic and gene expression variations in KYP, CMT3, and IBM1 within and between flowering plant species. IBM1 activity in Arabidopsis thaliana is uniquely regulated by the abundance of H3K9me2 in a repetitive sequence within an intron preceding the histone demethylase domain. This mechanism enables IBM1 to monitor global levels of H3K9me2. We discovered that the methylated intron is prevalent across flowering plants, however, its underlying sequence exhibits dynamic evolution. Its absence in species lacking gene body DNA methylation suggests its primary role in sensing H3K9me2 and preventing its integration into these constitutively expressed genes. Furthermore, our investigation uncovered Arabidopsis thaliana accessions resembling weak ibm1 mutants, several Brassicaceae species with reduced IBM1 expression, and a potential IBM1 deletion. Evolution towards reduced IBM1 activity in some flowering plants could explain the frequent natural occurrence of diminished or lost CMT3 activity, as cmt3 mutants in A. thaliana mitigate the deleterious effects of IBM1.

plant biology↗

bioRxiv2024

In vitro determination of osteo-adipogenic lineage choice of bone marrow stromal/stem cells (BMSCs)

Bone marrow stromal/stem cells (BMSCs) are primitive and heterogeneous cells that can be differentiated into osteoblasts, adipocytes and other subsets. Their bone-fat lineage commitment is responsible for the homeostasis of bone marrow microenvironment. However, there are little effective methods and evidence to simultaneously evaluate the lineage commitment of BMSCs. Here we provide a mixed osteo-adipogenic (OA) differentiation medium that could enable BMSCs differentiation into osteoblasts and adipocytes in vitro, and establish a method for simultaneous assessment of bone-fat lineage allocation of BMSCs based on the Alizarin red S and Oil red O staining, which have been used for detection of specific mineralized nodules and lipid droplets, respectively. This assay provides a specifically simple but effective and low-cost method to visualize the osteogenesis and adipogenesis of BMSCs, and evaluate the differentiation efficiency of lineage allocation of BMSCs.

cell biology↗

bioRxiv2023

Climate change decreases the likelihood of tropical forest community persistence with a strong mediation of plant-plant network structures

Climate change is known to negatively impact tropical forests; yet how climate change impacts tree community persistence at local scales remains less clear. Using data from a long-term tropical forest census plot over 25 years, we constructed plant- plant interaction networks based on tree growth. We then quantified community persistence as feasibility domain of constituent species using recently developed frameworks of structural stability. We found a decrease in structural stability under warming and precipitation changes over time as evidenced by both direct environmental effects and indirect effects via network structure; and indirect effects were stronger than direct effects. Among these structures, facilitation:competition degree ratio and competitive transitivity were most positively related with structural stability. Our study highlights how the lens of plant-plant interaction networks can identify novel details about risk to tropical forest diversity under climate change at local scales. Insights from this work will be helpful for aligning forest management activities with areas under the greatest risk of species loss.

ecology↗

bioRxiv2023

Towards establishing a rapid constant temperature detection method for canine parvovirus based on endonuclease activities

Canine parvovirus can cause a high morbidity and mortality rate in puppies, posing a significant threat to both pet dogs and the breeding industry. Rapid, accurate and convenient detection methods are important for the early intervention and treatment of canine parvovirus. In this study, we propose a visual CPV detection system called nucleic acid mismatch enzyme digestion (NMED). This system combines reverse transcription-loop mediated isothermal amplification (RT-LAMP), endonuclease for gene mismatch detection and colloidal gold lateral chromatography. We demonstrated that NMED can induce the binding of the amplicon from the sample to the specific labeling probe, which in turn triggers digestion by the endonuclease. The sensitivity and visual visibility of RT-LAMP were increased by combining of endonuclease and colloidal gold lateral chromatography assisted by a simple temperature-controlled device. The sensitivity of the NMED assay was 1 copy/L, which was consistent with qPCR. The method was validated with 10 clinical samples that potentially had CPV infection and achieved 100% accuracy. As a rapid, accurate and convenient molecular diagnostic method, NMED has great potential for application in the field of pathogenic microorganism detection.

molecular biology↗

bioRxiv2023

De novo design and optimization of aptamers with AptaDiff

Aptamers are single-stranded nucleic acid ligands, featuring high affinity and specificity to target molecules. Traditionally they are identified from large DNA/RNA libraries using in vitro methods, like Systematic Evolution of Ligands by Exponential Enrichment (SELEX). However, these libraries capture only a small fraction of theoretical sequence space, and various aptamer candidates are constrained by actual sequencing capabilities from the experiment. Addressing this, we proposed AptaDiff, the first in silico aptamer design and optimization method based on the diffusion model. Our Aptadiff can generate aptamers beyond the constraints of high-throughput sequencing data, leveraging motif-dependent latent embeddings from variational autoencoder, and can optimize aptamers by affinity-guided aptamer generation according to Bayesian optimization. Comparative evaluations revealed AptaDiffs superiority over existing aptamer generation methods in terms of quality and fidelity across four high-throughput screening data targeting distinct proteins. Moreover, Surface Plasmon Resonance (SPR) experiments were conducted to validate the binding affinity of aptamers generated through Bayesian optimization for two target proteins. The results unveiled a significant boost of 87.9% and 60.2% in RU values, along with a 3.6-fold and 2.4-fold decrease in KD values for the respective target proteins. Notably, the optimized aptamers demonstrated superior binding affinity compared to top experimental candidates selected through SELEX, underscoring the promising outcomes of our AptaDiff in accelerating the discovery of superior aptamers. Key PointsO_LIWe proposed AptaDiff, the first in silico aptamer design method based on the diffusion model. Aptadiff can generate aptamers beyond the constraints of high-throughput sequencing data. C_LIO_LIAptadiff can optimize aptamers through affinity-guided generation via Bayesian optimization within a motif-dependent latent space, and the affinity of the optimized aptamers to the target protein is better than the best experimental candidate from traditional SELEX screening. C_LIO_LIAptadiff consistently outperforms the current state-of-the-art method in terms of quality and fidelity across high-throughput screening data targeting distinct proteins. C_LI

bioinformatics↗

bioRxiv2023

Legionella pneumophila exploits the endo-lysosomal network for phagosome biogenesis by co-opting SUMOylated Rab7

L. pneumophila strains harboring wild-type rpsL such as Lp02rpsLWT cannot replicate in mouse bone marrow-derived macrophages (BMDMs) due to induction of extensive lysosome damage and apoptosis. The mechanism of this unique infection-induced cell death remains unknown. Using a genome-wide CRISPR/Cas9 screening, we identified Hmg20a and Nol9 as host factors important for restricting strain Lp02rpsLWT in BMDMs. Depletion of Hmg20a protects macrophages from infection-induced lysosomal damage and apoptosis, allowing productive bacterial replication. The restriction imposed by Hmg20a was mediated by repressing the expression of several endo-lysosomal proteins, including the small GTPase Rab7. We found that SUMOylated Rab7 is recruited to the bacterial phagosome via SulF, a Dot/Icm effector that harbors a SUMO-interacting motif (SIM). Moreover, overexpression of Rab7 rescues intracellular growth of strain Lp02rpsLWT in BMDMs. Our results establish that L. pneumophila exploits the lysosomal network for the biogenesis of its phagosome in BMDMs.

microbiology↗

bioRxiv2023

Regulator of G protein signaling 6 (RGS6) in ventral tegmental area (VTA) dopamine neurons promotes EtOH seeking, behavioral reward and susceptibility to relapse

Mesolimbic dopamine (DA) transmission is believed to play a critical role in mediating reward responses to drugs of abuse, including alcohol (EtOH). EtOH is the most abused substance worldwide with chronic consumption often leading to the development of dependence and abuse. Unfortunately, the neurobiological mechanisms underlying EtOH-seeking behavior and dependence are not fully understood, and abstinence remains the only effective way to prevent alcohol use disorders (AUDs). Here, we developed novel RGS6fl/fl; DAT-iCreER mice to determine the role of RGS6 in VTA DA neurons on EtOH consumption and reward behaviors. We found that RGS6 is expressed in DA neurons in both human and mouse VTA, and that RGS6 loss in mice upregulates DA transporter (DAT) expression in VTA DA neuron synaptic terminals. Remarkably, loss of RGS6 in VTA DA neurons significantly reduced EtOH consumption, preference, and reward in a manner indistinguishable from that seen in RGS6-/- mice. Strikingly, RGS6 loss from VTA DA neurons before or after EtOH behavioral reward is established significantly reduced ([~]50%) re-instatement of reward following extinguishment, demonstrating distinct roles of RGS6 in promoting reward and relapse susceptibility to EtOH. These studies illuminate a critical role of RGS6 in the mesolimbic circuit in promoting EtOH seeking, reward, and reinstatement. We propose that RGS6 functions to promote DA transmission through its function as a negative modulator of GPCR-Gi/o-DAT signaling in VTA DA neurons. These studies identify RGS6 as a potential therapeutic target for behavioral reward and relapse to EtOH.

neuroscience↗

bioRxiv2023

OPUS-Rota5: A Highly Accurate Protein Side-chain Modeling Method with 3D-Unet and RotaFormer

Accurate protein side-chain modeling is crucial for protein folding and design. This is particularly true for molecular docking as ligands primarily interact with side chains. A protein structure with large errors in side chains has limited usage such as in drug design. Previous research on AlphaFold2 (AF2) predictions of GPCR targets indicates that the docking of natural ligands back on AF2-predicted structures has limited successful rate presumably due to large errors in side chains. Here, we introduce a two-stage side-chain modeling approach called OPUS-Rota5. It leverages a modified 3D-Unet to capture the local environmental features including ligand information of each residue, and then employs RotaFormer module to aggregate various types of feature. Evaluation on three test sets, including recently released targets from CAMEO and CASP15, reveals that side chains modeled by OPUS-Rota5 are significantly more accurate than those predicted by other methods. We also employ OPUS-Rota5 to refine the side chains of 25 GPCR targets predicted by AF2 and then performed docking of their natural ligands back with a significantly improved successful rate. Such results suggest that OPUS-Rota5 could be a valuable tool for molecular docking, particularly for targets with relatively accurate predicted backbones, but not side chains.

bioinformatics↗

bioRxiv2023

SARS-CoV-2 N protein-induced Dicer, XPO5, SRSF3, and hnRNPA3 downregulation causes pneumonia

Age is a major risk factor for coronavirus disease (COVID-19)-associated severe pneumonia and mortality; however, the underlying mechanism remains unclear. Herein, we investigated whether age-related deregulation of RNAi components and RNA splicing factors affects COVID-19 severity. Decreased expression of RNAi components (Dicer and XPO5) and splicing factors (SRSF3 and hnRNPA3) correlated with increased severity of COVID-19 and SARS-CoV-2 nucleocapsid (N) protein-induced pneumonia. N protein induced autophagic degradation of Dicer, XPO5, SRSF3, and hnRNPA3, repressing miRNA biogenesis and RNA splicing and inducing DNA damage, proteotoxic stress, and pneumonia. Dicer, XPO5, SRSF3, and hnRNPA3 were downregulated with age in mouse lung tissues. Older mice experienced more severe N protein-induced pneumonia than younger mice. However, treatment with a poly(ADP-ribose) polymerase inhibitor (PJ34) or aromatase inhibitor (anastrozole) relieved N protein-induced pneumonia by restoring Dicer, XPO5, SRSF3, and hnRNPA3 expression. These findings will aid in developing improved treatments for SARS-CoV-2-associated pneumonia.

microbiology↗

bioRxiv2023

omicsMIC: a Comprehensive Benchmarking Platform for Robust Comparison of Imputation Methods in Mass Spectrometry-based Omics Data

Mass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics, and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive and systematic comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometrybased omics with Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to simulate and evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. OmicsMIC is freely available at https://github.com/WQLin8/omicsMIC.

bioinformatics↗

bioRxiv2023

Joint profiling of multiplex chromatin interactions, gene expression, and RNA-chromatin associations in single cells of the human brain

SUMMARY PARAGRAPHThe dynamically organized chromatin complexes often involve multiplex chromatin interactions and sometimes chromatin-associated RNA (caRNA) 1-3. Chromatin complex compositions change during cellular differentiation and aging, and are expected to be highly heterogeneous among terminally differentiated single cells 4-7. Here we introduce the Multi-Nucleic Acid Interaction Mapping in Single Cell (MUSIC) technique for concurrent profiling of multiplex chromatin interactions, gene expression, and RNA-chromatin associations within individual nuclei. Applied to 14 human frontal cortex samples from elderly donors, MUSIC delineates diverse cortical cell types and states. We observed the nuclei exhibiting fewer short-range chromatin interactions are correlated with an "older" transcriptomic signature and with Alzheimers pathology. Furthermore, the cell type exhibiting chromatin contacts between cis expression quantitative trait loci (cis eQTLs) and a promoter tends to be the cell type where these cis eQTLs specifically affect their target genes expression. Additionally, the female cortical cells exhibit highly heterogeneous interactions between the XIST non-coding RNA and Chromosome X, along with diverse spatial organizations of the X chromosomes. MUSIC presents a potent tool for exploring chromatin architecture and transcription at cellular resolution in complex tissues.

genomics↗

bioRxiv2023

SoyDNGP: A Web-Accessible Deep Learning Framework for Genomic Prediction in Soybean Breeding

Soybean is a globally significant crop, playing a vital role in human nutrition and agriculture. Its complex genetic structure and wide trait variation, however, pose challenges for breeders and researchers aiming to optimize its yield and quality. Addressing this biological complexity requires innovative and accurate tools for trait prediction. In response to this challenge, we have developed SoyDNGP, a Convolutional Neural Networks (CNN)-based model that offers significant advancements in the field of soybean trait prediction. Compared to existing methods, such as DeepGS and DNNGP, SoyDNGP boasts a distinct advantage due to its lower parameter volume and superior predictive accuracy. Through rigorous performance comparison, including prediction accuracy and model complexity, SoyDNGP consistently outperformed its counterparts. Furthermore, it effectively predicted complex traits with remarkable precision, demonstrating robust performance across different sample sizes and trait complexities. We also tested the versatility of SoyDNGP across multiple crop species, including Cotton, Maize, Rice, and Tomato. Our results showed its consistent and comparable performance, emphasizing SoyDNGPs potential as a versatile tool for genomic prediction across a broad range of crops. To enhance its accessibility to users without extensive programming experience, we have designed a user-friendly web server, available at http://xtlab.hzau.edu.cn/SoyDNGP. The server provides two primary features: Trait Lookup, offering users the ability to access pre-existing trait predictions for over 500 soybean accessions, and Trait Prediction, allowing for the upload of VCF files for trait estimation. By providing a high-performing, accessible tool for trait prediction and genomic analysis, SoyDNGP opens up new possibilities in the quest for efficient and optimized soybean breeding.

plant biology↗

bioRxiv2023

Selective neuroimmune modulation by type I interferon drives neuropathology and neurologic dysfunction following traumatic brain injury

Accumulating evidence suggests that type I interferon (IFN-I) signaling is a key contributor to immune cell-mediated neuropathology in neurodegenerative diseases. Recently, we demonstrated a robust upregulation of type I interferon-stimulated genes in microglia and astrocytes following experimental traumatic brain injury (TBI). The specific molecular and cellular mechanisms by which IFN-I signaling impacts the neuroimmune response and neuropathology following TBI remains unknown. Using the lateral fluid percussion injury model (FPI) in adult male mice, we demonstrated that IFN /{beta} receptor (IFNAR) deficiency resulted in selective and sustained blockade of type I interferon-stimulated genes following TBI as well as decreased microgliosis and monocyte infiltration. Phenotypic alteration of reactive microglia also occurred with diminished expression of molecules needed for MHC class I antigen processing and presentation following TBI. This was associated with decreased accumulation of cytotoxic T cells in the brain. The IFNAR-dependent modulation of the neuroimmune response was accompanied by protection from secondary neuronal death, white matter disruption, and neurobehavioral dysfunction. These data support further efforts to leverage the IFN-I pathway for novel, targeted therapy of TBI.

neuroscience↗

bioRxiv2023

Morphological brain networks of white matter: mapping, evaluation, characterization and application

Neuroimaging-based connectomics studies have long focused on the wiring patterns between gray matter regions. In recent years, increasing evidence emerges that neural activity in specific sets of white matter (WM) tracts dynamically fluctuates in a coordinated manner. However, the structural basis underlying the coordination is poorly understood largely due to the lack of approaches for estimating structural relations between WM regions. Here, we developed an approach to construct morphological WM networks based on structural magnetic resonance imaging. We found that the morphological WM networks exhibited nontrivial organizational principles, presented good to excellent short- and long-term reliability, accounted for phenotypic interindividual differences (Motor and Cognition), and were under genetic control. Interestingly, highly heritable edges contributed largely to interindividual differences in phenotype. Through integration with other multimodal and multiscale data, we further showed that the morphological WM networks were able to predict regional profiles of hamodynamic coherence, metabolic synchronization, gene co-expression and chemoarchitectonic covariance. Moreover, the prediction followed functional connectomic hierarchy of WM for hamodynamic coherence, was driven by genes enriched in the forebrain neuron development and differentiation for gene co-expression, and was attributed to serotonergic system-related receptors and transporters for chemoarchitectonic covariance. Finally, applying our approach to multiple sclerosis and neuromyelitis optica spectrum disorders, we found that both diseases were associated with morphological WM dysconnectivity, which was correlated with clinical variables and able to diagnose and differentiate the diseases. Altogether, our findings indicate that morphological WM networks provide a reliable and meaningful means to explore WM architecture in health and disease.

neuroscience↗

bioRxiv2023

Large-scale genomic rearrangements boost SCRaMbLE in Saccharomyces cerevisiae

Genomic rearrangements contribute to gene copy number alterations, disruption of protein-coding sequences and/or perturbation of cis-regulatory networks. SCRaMbLE, a Cre/loxP-based system implanted in synthetic yeast chromosomes, can effectively introduce genomic rearrangements, and is thus a potential tool to study genomic rearrangements. However, the potential of SCRaMbLE to study genomic rearrangements is currently hindered, because a strain containing all 16 synthetic chromosomes is not yet available. Here, we constructed a yeast strain, SparLox83, containing 83 loxPsym sites distributed across all 16 chromosomes, with at least two sites per chromosome. Inducing Cre recombinase expression in SparLox83 produced versatile genome-wide genomic rearrangements, including inter-chromosomal events. Moreover, SCRaMbLE of the hetero-diploid strains derived from crossing SparLox83 with strains possessing synthetic chromosome III (synIII) from the Sc2.0 project led to increased diversity of genomic rearrangements and relatively faster evolution of traits compared to a strain with only synIII. Analysis of these evolved strains demonstrates that genomic rearrangements can perturb the transcriptome and 3D genome structure and can consequently impact phenotypes. In summary, a genome with sparsely distributed loxPsym sites can serve as a powerful tool to study the consequence of genomic rearrangements and help accelerate strain engineering in Saccharomyces cerevisiae.

synthetic biology↗

bioRxiv2023

A high-quality pseudo-phased genome for Melaleuca quinquenervia shows allelic diversity of NLR-type resistance genes

BackgroundThe coastal wetland tree species Melaleuca quinquenervia (Cav.) S.T.Blake (Myrtaceae), commonly named the broad-leaved paperbark, is a foundation species in eastern Australia, Indonesia, Papua New Guinea, and New Caledonia. The species has been widely grown as an ornamental, becoming invasive in areas such as Florida in the United States. Long-lived trees must respond to a wide range pests and pathogens throughout their lifespan, and immune receptors encoded by the nucleotide- binding domain and leucine-rich repeat containing (NLR) gene family play a key role in plant stress responses. Expansion of this gene family is driven largely by tandem duplication, resulting in a clustering arrangement on chromosomes. Due to this clustering and their highly repetitive domain structure, comprehensive annotation of NLR encoding genes within genomes has been difficult. Additionally, as many genomes are still presented in their haploid, collapsed state, the full allelic diversity of the NLR gene family has not been widely published for outcrossing tree species. ResultsWe assembled a chromosome-level pseudo-phased genome for M. quinquenervia and describe the full allelic diversity of plant NLRs using the novel FindPlantNLRs pipeline. Analysis reveals variation in the number of NLR genes on each haplotype, differences in clusters and in the types and numbers of novel integrated domains. ConclusionsWe anticipate that the high quality of the genome for M. quinquenervia will provide a new framework for functional and evolutionary studies into this important tree species. Our results indicate a likely role for maintenance of NLR allelic diversity to enable response to environmental stress, and we suggest that this allelic diversity may be even more important for long-lived plants.

genomics↗

bioRxiv2023

A novel cell division protein critical for the assembly of the bacterial divisome

Identification of unique essential bacterial genes is important for not only the understanding of their cell biology but also the development of new antimicrobials. Here we report a previously unrecognized core component of the Acinetobacter baumannii divisome. Our results reveal that the protein, termed Aeg1 interacts with multiple cell division proteins, including FtsN, which is required for components of the divisome to localize to the midcell. We demonstrate that the FtsAE202K and FtsBE65A mutants effectively bypassed the need of Aeg1 by A. baumannii, as did the activation variants FtsWM254I and FtsWS274G. Our results suggest that Aeg1 is a cell division protein that arrives at the division site to initiate cell division by recruiting FtsN, which activates FtsQLB and FtsA to induce the septal peptidoglycan synthase FtsWI. The discovery of the new essential cell division protein has provided a new target for the development of antibacterial agents.

biochemistry↗

bioRxiv2023

BATF relieves hepatic steatosis by inhibiting PD1 and promoting energy metabolism

The rising prevalence of nonalcoholic fatty liver disease (NAFLD) has become a global health threat that needs to be addressed urgently. Basic leucine zipper ATF-like transcription factor (BATF) is commonly thought to be involved in immunity, but its effect on lipid metabolism is not clear. Here, we investigated the function of BATF in hepatic lipid metabolism. BATF alleviated high-fat diet (HFD)-induced hepatic steatosis and inhibited elevated programmed cell death protein (PD)1 expression induced by HFD. A mechanistic study confirmed that BATF regulated fat accumulation by inhibiting PD1 expression and promoting energy metabolism. PD1 antibodies alleviated hepatic lipid deposition. In conclusion, we identified the regulatory role of BATF in hepatic lipid metabolism and that PD1 is a target for alleviation of NAFLD. This study provides new insights into the relationship between BATF, PD1 and NAFLD.

molecular biology↗