Biology subjects

Guo, Z.

Publications and source records attributed to Guo, Z..

At least 109 records · Page 6Linked to original sources

bioRxiv2024

Freestanding rGO electrodes with tunable porous structures for improved neural recording

Invasive neural electrodes prepared from materials with miniaturized geometrical size could improve the longevity of implants by reducing the chronic inflammatory response. Graphene-based microfibers with tunable porous structures have a large electrochemical surface area (ESA)/geometrical surface area (GSA) ratio that has been reported to possess low impedance and high charge injection capacity (CIC), yet the control of the porous structure remains to be fully investigated. In this study, we introduce wet-spun graphene-based electrodes with pores tuned by sucrose concentrations in the coagulation bath. The electrochemical properties of thermally reduced rGO were optimized by adjusting the ratio of rGO to sucrose, resulting in significantly lower impedance, higher CIC, and higher charge storage capacity (CSC) than platinum microwires. Tensile and insertion tests confirmed that optimized electrodes had sufficient strength to ensure a 100% insertion success rate with low angle shift, thus allowing precise implantation without the need for additional mechanical enhancement. Acute in-vivo recordings from the auditory cortex found low impedance benefits from the recorded amplitude of spikes, leading to an increase in the signal-to-noise ratio (SNR). Ex-vivo recordings from hippocampal brain slices demonstrate that it is possible to record and/or stimulate with graphene-based electrodes with good fidelity compared with conventional electrodes.

neuroscience↗

bioRxiv2024

Rate variation and recurrent sequence errors in pandemic-scale phylogenetics

Phylogenetic analyses of genome sequences from infectious pathogens reveal essential information regarding their evolution and transmission, as seen during the COVID-19 pandemic. Recently developed pandemic-scale phylogenetic inference methods reduce the computational demand of phylogenetic reconstruction from genomic epidemiological datasets, allowing the analysis of millions of closely related genomes. However, widespread homoplasies, due to recurrent mutations and sequence errors, cause phylogenetic uncertainty and biases. We present new algorithms and models to substantially improve the computational performance and accuracy of pandemic-scale phylogenetics. In particular, we account for, and identify, mutation rate variation and recurrent sequence errors. We reconstruct reliable and public sequence alignment and phylogenetic tree of > 2 million SARS-CoV-2 genomes encapsulating the evolutionary history and global spread of the virus up to February 2023.

bioinformatics↗

bioRxiv2024

Hippocampal-prefrontal communication subspaces align with behavioral and network patterns in a spatial memory task

Rhythmic network states have been theorized to facilitate communication between brain regions, but how these oscillations influence communication subspaces, i.e, the low-dimensional neural activity patterns that mediate inter-regional communication, and in turn how subspaces impact behavior remains unclear. Using a spatial memory task in rats, we simultaneously recorded ensembles from hippocampal CA1 and the prefrontal cortex (PFC) to address this question. We found that task behaviors best aligned with low-dimensional, shared subspaces between these regions, rather than local activity in either region. Critically, both network oscillations and speed modulated the structure and performance of this communication subspace. Contrary to expectations, theta coherence did not better predict CA1-PFC shared activity, while theta power played a more significant role. To understand the communication space, we visualized shared CA1-PFC communication geometry using manifold techniques and found ring-like structures. We hypothesize that these shared activity manifolds are utilized to mediate the task behavior. These findings suggest that memory-guided behaviors are driven by shared CA1-PFC interactions that are dynamically modulated by oscillatory states, offering a novel perspective on the interplay between rhythms and behaviorally relevant neural communication.

neuroscience↗

bioRxiv2024

Mutation of phosphatidate phosphohydrolase genes confers broad-spectrum disease resistance in plants

Phosphatidic acid (PA) is considered as a second messenger that interacts with protein kinases, phosphatases and NADPH oxidases, amplifying the signal to initiate plant defense signaling responses (Li and Wang, 2019). In rice, mutation of RBL1 causes the accumulation of PA, enhancing multipathogen resistance (Sha et al., 2023). In our previous study, we attempted to rescue rbl1 mutant by overexpressing phosphatidate phosphohydrolase (PAH) genes. However, overexpression of PAH2 reduced the PA level but did not affect the disease resistance, which made us to reconsider the importance of PA and PAH in rice immunity. Here, we identified that mutation of PAHs caused PA accumulation and enhanced multipathogen resistance in rice and Arabidopsis.

plant biology↗

bioRxiv2024

Exenatide administration time determines the effects on blood pressure dipping in db/db mice via modulation of food intake and sympathetic activity

AbstractType 2 diabetics have an increased prevalence of hypertension and nondipping blood pressure (BP), which worsen cardiovascular outcomes. Exenatide, a short acting glucagon-like peptide-1 receptor agonist (GLP-1RA) used to treat type 2 diabetes, also demonstrates blood pressure (BP)-lowering effects. However, the mechanisms behind this and the impact of administration timing on BP dipping remain unclear. We investigated the effects of exenatide intraperitoneal injected at light onset (ZT0) or dark onset (ZT12) in diabetic (db/db) mice and nondiabetic controls. Using radio-telemetry and BioDAQ cages, we continuously monitored BP and food intake. Db/db mice exhibited non-dipping BP and increased food intake. ZT0 exenatide administration restored BP dipping by specifically lowering light-phase BP, while ZT12 exenatide reversed dipping by lowering dark-phase BP. These effects correlated with altered food intake patterns, and importantly, were abolished when food access was removed. Additionally, urinary norepinephrine excretion, measured by HPLC, was significantly reduced 6 hours post-exenatide at both ZT0 and ZT12, suggesting sympathetic nervous system involvement. Notably, combining exenatide with either ganglionic blocker mecamylamine or -blocker prazosin did not enhance BP reduction beyond the individual effects of each blocker. These findings reveal that exenatide, when administered at light onset, restores BP dipping in db/db mice by suppressing light-phase food intake and sympathetic activity. Importantly, the efficacy of exenatide is dependent on food availability and its timing relative to circadian rhythms, highlighting the potential for chronotherapy in optimizing GLP-1RA- based treatments for type 2 diabetes and hypertension. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=178 HEIGHT=200 SRC="FIGDIR/small/601700v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@29812dorg.highwire.dtl.DTLVardef@dfbaaborg.highwire.dtl.DTLVardef@586343org.highwire.dtl.DTLVardef@dcebe4_HPS_FORMAT_FIGEXP M_FIG C_FIG Article HighlightsO_LIMaintaining a normal blood pressure (BP) circadian rhythm is vital for cardiovascular health, but diabetes often disrupts this rhythm. The effect of exenatide, a GLP-1 receptor agonist (GLP-1RA), on BP rhythm in diabetes is uncertain. C_LIO_LIThis study investigates the impact of exenatide administration timing on BP patterns in diabetic db/db mice. C_LIO_LIFindings indicate that exenatide given at the onset of rest restores normal BP dipping, while at the start of the active phase worsens BP rhythm by modulating food intake and sympathetic activity. C_LIO_LITiming GLP-1 RA administration may optimize BP control and provide cardiovascular benefits for type 2 diabetes patients. C_LI

pharmacology and toxicology↗

bioRxiv2024

Frontal-posterior loop integrating captured attention into visual consciousness in the human brain

We usually perceive what we are attending to. How goal-directed attention contributes to conscious perception remains yet elusive. Here we combined a novel psychophysical paradigm with intracranial electroencephalography data to investigate this issue in the human brain. Relative to unattended conditions, goal-directed attention modulated early activity and inter-regional connectivity, even though this part of attention failed to predict image detectability. Later, the coupling between the frontal and posterior brain got established and maintained but the signals exchanged did not inform fine-grained image contents but instead reflect success or failure of attentional capture. This part of captured attention proportionally predicted image detectability. These results attribute consciousness to attention-based coupling between the frontal and posterior brain as a whole, rather than activity of either part alone.

neuroscience↗

bioRxiv2024

Revealing the Biophysics of Lamina-Associated Domain Formation by Integrating Theoretical Modeling and High-Resolution Imaging

The interactions between chromatin and the nuclear lamina orchestrate cell type-specific gene activity by forming lamina-associated domains (LADs) which preserve cellular characteristics through gene repression. However, unlike the interactions between chromatin segments, the strength of chromatin-lamina interactions and their dependence on cellular environment are not well understood. Here, we develop a theory to predict the size and shape of peripheral heterochromatin domains by considering the energetics of chromatin-chromatin interactions, the affinity between chromatin and the nuclear lamina and the kinetics of methylation and acetylation9in human mesenchymal stem cells (hMSCs). Through the analysis of super-resolution images of peripheral heterochromatin domains using this theoretical framework, we determine the nuclear lamina-wide distribution of chromatin-lamina affinities. We find that the extracted affinity is highly spatially heterogeneous and shows a bimodal distribution, indicating regions along the lamina with strong chromatin binding and those exhibiting vanishing chromatin affinity interspersed with some regions exhibiting a relatively diminished chromatin interactions, in line with the presence of structures such as nuclear pores. Exploring the role of environmental cues on peripheral chromatin, we find that LAD thickness increases when hMSCs are cultured on a softer substrate, in correlation with contractility-dependent translocation of histone deacetylase 3 (HDAC3) from the cytosol to the nucleus. In soft microenvironments, chromatin becomes sequestered at the nuclear lamina, likely due to the interactions of HDAC3 with the chromatin anchoring protein LAP2{beta} ,increasing chromatin-lamina affinity, as well as elevated levels of the intranuclear histone methylation. Our findings are further corroborated by pharmacological interventions that inhibit contractility, as well as by manipulating methylation levels using epigenetic drugs. Notably, in the context of tendinosis, a chronic condition characterized by collagen degeneration, we observed a similar increase in the thickness of peripheral chromatin akin to that of cells cultured on soft substrates consistent with theoretical predictions. Our findings underscore the pivotal role of the microenvironment in shaping genome organization and highlight its relevance in pathological conditions.

biophysics↗

bioRxiv2024

Amd1-skp2 cascade regulates hepatocyte proliferation during liver growth and hepatocellular carcinoma development in zebrafish

Rapid hepatocyte proliferation is a common characteristic of liver growth in early liver development and hepatocellular carcinoma (HCC). Clarifying the mechanism how liver growth is regulated in development would benefit studying HCC progress. Although many genes have been reported to be involved in liver growth during early development, the mechanism underlying liver growth is far from being elucidated. Here we found that the liver undergoes rapid growth from 2dpf to 5dpf in zebrafish. Comparing the transcriptome for different staged hepatocytes identified 813 hepatocyte enriched genes at 3 dpf. Among them, S-adenosylmethionine decarboxylase proenzyme (AMD1) had not been previously reported to be involved in liver development. Our study further confirmed that amd1 was highly enriched in hepatocytes during liver rapid growth and that amd1 mutation inhibited liver growth mainly by repressing hepatocyte proliferation. Mechanistically, amd1 loss of function downregulated the expression of skp2, and skp2 is required for amd1 to regulate hepatocyte proliferation. Furthermore, the role of Amd1-Skp2 cascade in regulating hepatocyte proliferation was also conserved in a zebrafish HCC model. In conclusion, our study systematically identified some uncharacterized genes possibly being involved in regulating liver growth during zebrafish development, and revealed the role of amd1-skp2 cascade in regulating hepatocyte proliferation during liver growth and HCC progression. This work also provided a database which would benefit elucidating the mechanism how hepatocyte proliferation is regulated during liver growth and HCC progress.

developmental biology↗

bioRxiv2024

Giraffe: a tool for comprehensive processing andvisualization of multiple long-read sequencing data

Third-generation sequencing techniques have become increasingly popular due to their ability to generate long, high-quality reads. Utilizing datasets from various samples and multiple sequencing platforms for comparative and comprehensive analysis is essential for exploring biological mechanisms and establishing benchmark baselines. However, current tools for long reads primarily focus on quality control (QC) and read processing for individual samples, complicating the profiling and comparison of multiple datasets. The lack of tools for data comparison and visualization presents challenges for researchers with limited bioinformatics experience. Furthermore, developing a comprehensive long-read QC method that facilitates comparative analysis and visualization across multiple samples and platforms is necessary to establish benchmark baselines for selecting appropriate sequencing platforms. We introduce Giraffe, a Python3-based command line tool designed for comparative analysis and visualization across multiple samples and platforms. Giraffe enables the assessment of read quality, sequencing bias, and genomic regional methylation proportions for both DNA and direct RNA sequencing reads. Its usability has been demonstrated in various scenarios, including comparisons of different biological processing methods (whole genome amplification vs. shotgun), sequencing platforms (Oxford Nanopore Technology vs. Pacific Biosciences), tissues (kidney marrow with and without blood), and biological replicates (kidney marrows). Additionally, our findings indicate that Oxford Nanopore duplex reads outperform PacBio HiFi reads in homopolymer identification and GC evenness while maintaining comparable overall read quality.

bioinformatics↗

bioRxiv2024

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure-function relationship, and numerous transient but stable conformations of Intrinsically Disordered Proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper we first introduce a deep learning-based model, termed Internal Coordinate Net (ICoN), which learns the physical principles of conformational changes from Molecular Dynamics (MD) simulation data. Second, we selected interpolating data points in the learned latent space that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-{beta}1-42 (A{beta}42) monomer, our deep learning model provided a comprehensive sampling of A{beta}42s conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. This approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability of deep learning to utilize learned natural atomistic motions in protein conformation sampling.

biophysics↗

bioRxiv2024

siRNADesign: A Graph Neural Network for siRNA Efficacy Prediction via Deep RNA Sequence Analysis

The clinical adoption of small interfering RNAs (siRNAs) has prompted the development of various computational strategies for siRNA design, from traditional data analysis to advanced machine learning techniques. However, previous studies have inadequately considered the full complexity of the siRNA silencing mechanism, neglecting critical elements such as siRNA positioning on mRNA, RNA base-pairing probabilities, and RNA-AGO2 interactions, thereby limiting the insight and accuracy of existing models. Here, we introduce siRNADesign, a Graph Neural Network (GNN) framework that leverages both non-empirical and empirical rules-based features of siRNA and mRNA to effectively capture the complex dynamics of gene silencing. In multiple internal datasets, siRNADesign achieves state-of-the-art performance. Significantly, siRNADesign also outperforms existing methodologies in in vitro wet lab experiments and an externally validated dataset. Additionally, we develop a new data-splitting methodology that addresses the data leakage issue, a frequently overlooked issue in previous studies, ensuring the robustness and stability of our model under various experimental settings. Through rigorous testing, siRNADesign has demonstrated remarkable predictive accuracy and robustness, making significant contributions to the field of gene silencing. Furthermore, our approach in redefining data-splitting standards aims to set new benchmarks for future research in the domain of predictive biological modeling for siRNA.

bioinformatics↗

bioRxiv2024

Artificial Intelligence-Enabled AlphaFold II Pipeline Guides Functional Fluorescence Labeling of Tubulin Across Species

Dynamic properties are essential for microtubule (MT) physiology. Current techniques for in vivo imaging of MTs present intrinsic limitations in elucidating the isotype-specific nuances of tubulins, which contribute to their versatile functions. Harnessing the power of AlphaFold II pipeline, we engineered a strategy for the minimally invasive fluorescence labeling of endogenous tubulin isotypes or those harboring missense mutations. We demonstrated that a specifically designed 16-amino acid linker, coupled with sfGFP11 from the split-sfGFP system and integration into the H1-S2 loop of tubulin, facilitated tubulin labeling without compromising MT dynamics, embryonic development, or ciliogenesis in C. elegans. Extending this technique to human cells and murine oocytes, we visualized MTs with the minimal background fluorescence and a pathogenic tubulin isoform with fidelity. The utility of our approach across biological contexts and species set an additional paradigm for studying tubulin dynamics and functional specificity, with implications for understanding tubulin-related diseases known as tubulinopathies.

cell biology↗

bioRxiv2024

EAP: a versatile cloud-based platform for comprehensive and interactive analysis of large-scale ChIP/ATAC-seq data sets

Epigenome profiling techniques such as ChIP-seq and ATAC-seq have revolutionized our understanding of gene expression regulation in tissue development and disease progression. However, increasing amount of ChIP/ATAC-seq data poses challenges in computational resources, and the absence of systematic tools for epigenomic analysis underscores the necessity for an efficient analysis platform. To address these issues, we developed the Epigenomic Analysis Platform (EAP, https://www.biosino.org/epigenetics), a scalable cloud-based tool that efficiently analyzes large-scale ChIP/ATAC-seq data sets. EAP employs advanced computational algorithms to derive biologically meaningful insights from heterogeneous datasets and automatically generates publication-ready figures and tabular results, enabling comprehensive epigenomic analysis and data mining in areas like cancer subtyping and therapeutic target discovery.

bioinformatics↗

bioRxiv2024

The subcommissural organ regulates brain development via secreted peptides

The subcommissural organ (SCO) is a gland located at the entrance of the aqueduct of Sylvius in the brain. It exists in species as distantly related as amphioxus and humans, but its function is largely unknown. To explore its function, we compared transcriptomes of SCO and non-SCO brain regions and found three genes, Sspo, Car3, and Spdef, that are highly expressed in the SCO. Mouse strains expressing Cre recombinase from endogenous promoter/enhancer elements of these genes were used to genetically ablate SCO cells during embryonic development, resulting in severe hydrocephalus and defects in neuronal migration and development of neuronal axons and dendrites. Unbiased peptidomic analysis revealed enrichment of three SCO-derived peptides, namely thymosin beta 4, thymosin beta 10, and NP24, and their reintroduction into SCO-ablated brain ventricles substantially rescued developmental defects. Together, these data identify a critical role for the SCO in brain development.

neuroscience↗

bioRxiv2024

LncRNA-Snhg3 Aggravates Hepatic Steatosis by Regulating PPARγ via SND1/H3K27me3

LncRNAs are involved in modulating the individual risk and the severity of progression in metabolic dysfunction-associated fatty liver disease (MASLD), but their precise roles remain largely unknown. This study aimed to investigate the role of lncRNA Snhg3 in the development and progression of MASLD, along with the underlying mechanisms. The result showed that Snhg3 was significantly downregulated in the liver of high-fat diet-induced obesity (DIO) mice. Notably, palmitic acid promoted the expression of Snhg3 and overexpression of Snhg3 increased lipid accumulation in primary hepatocytes. Furthermore, hepatocyte-specific Snhg3 deficiency decreased body and liver weight, alleviated hepatic steatosis and promoted hepatic fatty acid metabolism in DIO mice, whereas overexpression induced the opposite effect. Mechanistically, Snhg3 promoted the expression, stability and nuclear localization of SND1 protein via interacting with SND1, thereby inducing K63-linked ubiquitination modification of SND1. Moreover, Snhg3 decreased the H3K27me3 level and induced SND1-mediated chromatin loose remodeling, thus reducing H3K27me3 enrichment at the Ppar{gamma} promoter and enhancing Ppar{gamma} expression. The administration of PPAR{gamma} antagonist T0070907 improved Snhg3-aggravated hepatic steatosis. Our study revealed a new signaling pathway, Snhg3/SND1/H3K27me3/PPAR{gamma}, responsible for MASLD and indicates that lncRNA-mediated epigenetic modification has a crucial role in the pathology of MASLD.

molecular biology↗

bioRxiv2024

Map based cloning of CT2 and the pilot functional exploration in abiotic stress

Heterotrimeric G-proteins are multifunctional modulators that participate in a wide range of growth and developmental processes in eukaryotic species, from yeast to plants and animals. Component detection and the study of G protein signaling in most plants, including maize, are in the initial stages. In this study, we characterized a maize mutant, ct2, that showed a compact architecture and reproductive organ-related phenotypic variation. The target gene CT2 was cloned using bulked segregant analysis and map-based cloning. Gene structure prediction and phylogenetic analysis indicated that CT2 is a canonical G protein belonging to the monocotyledonous group. Promoter analysis of CT2 and RNA sequencing revealed cis-acting regulatory elements and differentially expressed genes involved in JA signaling and stress tolerance. The transcription of CT2 was repressed by NaCl and PEG treatments, and ct2 mutation in the ct2 line compromised stress tolerance in maize. On the basis of our results, we proposed a schema diagram of CT2-regulated biological process and their feedback on CT2 transcription. This research provides clues for further studies of CT2 function in hormone signaling and stress tolerance, which is beneficial for maize breeding through the screening and application of beneficial alleles.

molecular biology↗

bioRxiv2024

All-atom protein sequence design based on geometric deep learning

The development of advanced deep learning methods has revolutionized computational protein design. Although the success rate of design has been significantly increased, the overall accuracy of de novo design remains low. Many computational sequence design approaches are devoted to recover the original sequences for given protein structures by encoding the environment of the central residue without considering atomic details of side chains. This may limit the exploration of new sequences that can fold into the same structure and restrain function design that depends on interaction details. In this study, we proposed a novel deep learning frame-work, GeoSeqBuilder, to learn the relationship between protein structure and sequence based on rotational and translational invariance by extracting the information from relative locations. We utilized geometric deep learning to fetch the spatial local geometric features from protein backbones and explicitly incorporated three-body interactions to learn the inter-residue coupling information, and then determined the central residue type. Our model recovers over 50% native residue types and simultaneously gives highly accurate prediction of side-chain conformations which gives the atomic interaction details and circumvents the dependence of protein structure prediction tools. We used the likelihood confidence logP as scoring function for sequence and structure consistence evaluation which exhibits strong correlation with TM-score, and can be applied to recognize near-native structures from protein decoys pool in protein structure prediction. We have used GeoSeqBuilder to design sequences for two proteins, including thiore-doxin and a de novo hallucinated protein. All of the 15 sequences experimentally tested can be expressed as soluble monomeric proteins with high thermal stability and correct secondary structures. We further solved one crystal structure for thioredoxin and two for the hallucinated structure and all the experimentally solved structures are in good agreement with the designed models. The two designed sequences for the hallucination structure are novel without any homologous sequences within the latest released database clust30. The ability of GeoSeqBuilder to design new sequences for given protein structures with atomic details makes it applicable, not only for de novo sequence design, but also for protein-protein interaction and functional protein design.

biophysics↗

bioRxiv2024

Cdon is required for organ Left-Right patterning via regulating DFCs migration and the sequential ciliogenesis

Cdon and boc are members of the cell adhesion molecule subfamily III Ig/fibronectin. Although they were reported to be involved in muscle and neural development at late developmental stage, while their early roles in embryonic development are unknown. Here we discovered that zebrafish cdon but not boc was expressed in dorsal forerunner cells (DFCs) and epitheliums of Kupffers vesicle (KV), implying the possible role of cdon in organ LR patterning. Further data showed that the liver and heart LR patterning was disturbed in cdon morphants and cdon mutants. Mechanically, we found that cdon loss of function led to dispersed DFCs migration, smaller KV and defective ciliogenesis, which resulting in randomized Nodal/spaw signaling and the sequential organ LR patterning defect. Finally, predominant distribution of a cdon MO in DFCs led to defects in DFCs migration, KV morphogenesis/ciliogenesis, Nodal/spaw signaling and organ LR asymmetry, being similar to those in cdon morphants and cdon-/- embryos, indicating a cell-autonomous role of cdon in regulating KV formation and ciliogenesis during LR patterning. In conclusion, our data demonstrated that, during gastrulation stage and early somitogenesis stage, cdon is required for proper DFCs migration, KV formation and ciliogenesis, thus playing an important role in setting up organ LR asymmetry.

developmental biology↗