Biology subjects

Zhao, T.

Publications and source records attributed to Zhao, T..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

The continuous differentiation of multiscale structural gradients from childhood to adolescence correlates with the maturation of cortical morphology and functional specialization

From childhood to adolescence, the structural organization of the human brain undergoes dynamic and regionally heterogeneous changes across multiple scales, from synaptic pruning to the reorganization of large-scale anatomical wiring. However, during this period, the developmental process of multiscale structural architecture, its association with cortical morphological changes, and its role in the maturation of functional organization remain largely unknown. Here, we utilized a longitudinal multimodal imaging dataset including 276 children aged 6 to 14 years to investigate the developmental process of multiscale cortical wiring. We used an in vivo model of cortical wiring that combines features of white matter tractography, cortico-cortical proximity, and microstructural similarity to construct a multiscale brain structural connectome. By employing the gradient mapping method, the gradient space derived from the multiscale structural connectome effectively recapitulated the sensory-association axis and anterior-posterior axis. Our findings revealed a continuous expansion of the multiscale structural gradient space during development, with the principal gradient increasingly distinguishing between primary and transmodal regions. This age-related differentiation coincided with regionally heterogeneous changes in cortical morphology. Furthermore, our study revealed that developmental changes in coupling between multiscale structural and functional connectivity were correlated with functional specialization refinement, as evidenced by changes in the participation coefficient. We also found that the differentiation of the principal multiscale structural gradient was associated with improved cognitive abilities, such as enhanced working memory and attention performance, and potentially supported by molecular processes related to synaptic functions. These findings advance our understanding of the intricate maturation process of brain structural organization and its implications for cognitive performance.

neuroscience↗

bioRxiv2024

Systematic identification of secondary bile acid production genes in global microbiome

Microbial metabolism of bile acids (BAs) is crucial for maintaining homeostasis in vertebrate hosts and environments. Although certain organisms involved in BA metabolism have been identified, a global, comprehensive elucidation of the microbes, metabolic enzymes, and BA remains incomplete. To bridge this gap, we employed hidden Markov models to systematically search in a large-scale and high-quality search library comprising 28,813 RefSeq multi-kingdom microbial complete genomes, which enabled us to construct a secondary bile acid (SBA)-production gene catalog. This catalog greatly expanded the distribution of SBA-production genes across 11 phyla, encompassing bacteria, archaea and fungi, and extended to 14 habitats spanning hosts and environmental contexts. Furthermore, we highlighted the associations between SBAs and gastrointestinal and hepatic disorders, including inflammatory bowel disease, colorectal cancer and nonalcoholic fatty liver disease, further elucidating disease-specific alterations in SBA-production genes. Additionally, we proposed the pig as a particularly suitable animal model for investigating SBA production in humans, given its closely aligned SBA-production gene composition. This gene catalog provides a comprehensive and reliable foundation on microbial BA metabolism for future studies, offering new insights into the microbial contributions to health and disease.

genomics↗

bioRxiv2024

An organoid co-culture model for probing systemic anti-tumor immunity in lung cancer

Deciphering the interactions between tumor micro- and systemic immune macro-environment is essential for developing more effective cancer diagnosis and treatment strategies. Here, we established a gel-liquid interface (GLI) co-culture of lung cancer organoids (LCOs) and paired peripheral blood mononuclear cells (PBMCs), featuring with enhanced interactions of immune cells and tumor organoids, to mimic the in vivo systemic anti-tumor immunity induced by immune checkpoint inhibitors (ICI). The co-culture model recapitulates the in vivo ICI-induced T cell recruitment and subsequent tumor regression, predicting the clinical results precisely. We demonstrated that circulating tumor-reactive T cells, which are effector memory-like with high expression levels of GNLY, CD44 and CD9, can serve as an indicator of the immunotherapy efficacy. Interestingly, enhanced inflammatory signaling in blood T cells is accompanied with prompted exhaustion and compromised anti-tumor function, when encountering with organoids. Our findings suggest that the GLI co-culture can be used for developing diagnostic strategies for precision immunotherapies as well as understanding the underlying mechanisms. Summary figure O_FIG O_LINKSMALLFIG WIDTH=178 HEIGHT=200 SRC="FIGDIR/small/597327v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@a0829dorg.highwire.dtl.DTLVardef@1df3083org.highwire.dtl.DTLVardef@1ea1065org.highwire.dtl.DTLVardef@1da9464_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Isolation and characterization of three lytic podo-bacteriophages with two receptor recognition modules against multidrug-resistant Klebsiella pneumoniae

The multidrug-resistant nosocomial pathogen Klebsiella pneumoniae is considered as one of the major threats to public health. Recent studies showed that bacteriophages could be used as an alternative to antibiotics for treating infections caused by multidrug-resistant K. pneumoniae. Here we isolated and characterized three lytic bacteriophages Kp7, Kp9 and Kp11 of K. pneumoniae. Transmission electron microscopy analysis showed that all three phages have an isometric head of approximately 60 nm in diameter and a short noncontractile tail. Host specificity, one-step growth curve, tolerance to pH and temperature changes were characterized for Kp7, Kp9, and Kp11. Mass-spectrum and bioinformatical analysis identified two different types of tail fibers in each phage. The tail fiber proteins gp52 of Kp7, gp43 of Kp9 and gp46 of Kp11 are homologous and have robust enzymatic activity in digesting purified serotype K2 capsule of K. pneumoniae. However, tail fiber proteins gp51 of Kp7, gp42 of Kp9 and gp45 of Kp11 have diverse sequences and show weak or no enzyme activity in digesting purified serotype K2 capsule. Genetic knockout and biochemical assays indicated that the capsule is essential for the infection of Kp7, Kp9 and Kp11. Spot tests showed that 15 clinical isolates of drug-resistant K. pneumoniae with the serotype K2 capsule can all be infected by Kp7, Kp9 and Kp11 but with different susceptibility. Further mechanistic studies showed that transcriptional inhibition at the early stage of phage infection determines the susceptibility of different K. pneumoniae isolates.

microbiology↗

bioRxiv2024

Stochastic growth and selective stabilization generate stereotyped dendritic arbors

Stereotyped dendritic arbors are shaped by dynamic and stochastic growth during neuronal development. It remains unclear how guidance receptors and ligands coordinate branch dynamic growth, retraction, and stabilization to specify dendritic arbors. We previously showed that extracellular ligand SAX-7/LICAM dictates the shape of the PVD sensory neuron via binding to the dendritic guidance receptor DMA-1, a single transmembrane adhesion molecule. Here, we perform structure-function analyses of DMA-1 and unexpectedly find that robust, stochastic dendritic growth does not require ligand-binding. Instead, ligand-binding inhibits growth, prevents retraction, and specifies arbor shape. Furthermore, we demonstrate that dendritic growth requires a pool of ligand-free DMA-1, which is maintained by receptor endocytosis and reinsertion to the plasma membrane via recycling endosomes. Mutants defective of DMA-1 endocytosis show severely truncated dendritic arbors. We present a model in which ligand-free guidance receptor mediates intrinsic, stochastic dendritic growth, while extracellular ligands instruct dendrite shape by inhibiting growth.

neuroscience↗

bioRxiv2024

Development of the overlapping network modules in the human brain

Developmental connectomic studies have shown that the modular organization of functional networks in the human brain undergoes substantial reorganization with age to support cognitive growth. However, these studies implicitly assume that each brain region belongs to one and only one specific network module, ignoring the potential spatial overlap between functional modules. How the overlapping functional modular architecture develops and whether this development is related to structural signatures remain unknown. Using longitudinal multimodal structural, functional, and diffusion MRI data from 305 children (aged 6-14 years), we investigated the development of the overlapping modular architecture of functional networks, and further explored their structural associations. Specifically, an edge-centric network model was used to identify the overlapping functional modules, and the nodal overlap in module affiliations was quantified using the entropy measure. We showed a remarkable regional inhomogeneity in module overlap in children, with higher entropy in the ventral attention, somatomotor, and subcortical networks and lower entropy in the visual and default-mode networks. Furthermore, the overlapping modules developed in a linear, spatially dissociable manner from childhood to adolescence, with significantly reduced entropy in the prefrontal cortex and putamen and increased entropy in the parietal lobules. Personalized overlapping modular patterns capture individual brain maturity as characterized by brain age. Finally, the overlapping functional modules can be significantly predicted by integrating gray matter morphology and white matter network properties. Our findings highlight the maturation of overlapping network modules and their structural substrates, thereby advancing our understanding of the principles of connectome development.

neuroscience↗

bioRxiv2024

Metabolic Vulnerabilities of Temozolomide-Resistant Glioblastoma Cells: Implications for Targeted Therapies and Overcoming Chemoresistance

Chemoresistance is a major clinical challenge in the management of glioblastoma (GB), making it difficult to achieve long-term success with traditional treatments. Therefore, there is a need for the development of novel drugs. We explored the metabolic vulnerabilities of temozolomide (TMZ)-resistant GB and their potential implications for targeted therapies. In monolayer and tumoroid cultures, we found elevated reliance on oxidative phosphorylation in TMZ-resistant cells. Notably, iron reduction in TMZ-resistant cells reduced viability and proliferation, upregulated hypoxia-inducible factor 1- (Hif1-) expression, induced autophagy, inhibited autophagic flux, and increased reactive oxygen species (ROS) generation, indicating the significance of iron in metabolic vulnerabilities of these cells. Hypoxic cells showed acquired resistance to iron chelation compared to their normoxic state, suggesting an adaptive mechanism associated to hypoxia. Viability, size, and invasion were reduced in TMZ-resistant tumoroids. Additionally, we reported IC50 for the combination of TMZ with a range of DFO and DFP, making the combination therapy a promising drug candidate to improve therapeutic treatments. TeaserCombining iron reduction and chemotherapy in drug-resistant glioblastoma cells enhances therapeutic outcomes.

cancer biology↗

bioRxiv2024

Discovering Genetic Modulators of the Protein Homeostasis System through Multilevel Analysis

Every protein progresses through a natural lifecycle from birth to maturation to death; this process is coordinated by the protein homeostasis system. Environmental or physiological conditions trigger pathways that maintain the homeostasis of the proteome. An open question is how these pathways are modulated to respond to the many stresses that an organism encounters during its lifetime. To address this question, we tested how the fitness landscape changes in response to environmental and genetic perturbations using directed and massively parallel transposon mutagenesis in Caulobacter crescentus. We developed a general computational pipeline for the analysis of gene-by-environment interactions in transposon mutagenesis experiments. This pipeline uses a combination of general linear models (GLMs), statistical knockoffs, and a nonparametric Bayesian statistical model to identify essential genetic network components that are shared across environmental perturbations. This analysis allows us to quantify the similarity of proteotoxic environmental perturbations from the perspective of the fitness landscape. We find that essential genes vary more by genetic background than by environmental conditions, with limited overlap among mutant strains targeting different facets of the protein homeostasis system. We also identified 146 unique fitness determinants across different strains, with 19 genes common to at least two strains, showing varying resilience to proteotoxic stresses. Experiments exposing cells to a combination of genetic perturbations and dual environmental stressors show that perturbations that are quantitatively dissimilar from the perspective of the fitness landscape are likely to have a synergistic effect on the growth defect. Significance StatementThis study provides critical insights into how cells adapt to environmental and genetic challenges affecting protein homeostasis. Using multilevel statistical analysis and transposon mutagenesis, we find that a model organism, Caulobacter crescentus, lacks a universal redundancy mechanism for coping with stress, as evidenced by the limited overlap in essential genes across different environmental and genetic perturbations. Our methods also pinpoint key fitness determinants and enable the prediction of perturbation combinations that synergistically affect cell growth.

systems biology↗

bioRxiv2024

Feed-forward stimulation of CAMK2 by the oncogenic pseudokinase PEAK1 generates a therapeutically "actionable" signalling axis in triple negative breast cancer

The PEAK family of pseudokinases, comprising PEAK1-3, are signalling scaffolds that play oncogenic roles in several poor prognosis human cancers, including triple negative breast cancer (TNBC). However, therapeutic targeting of pseudokinases is challenging due to their lack of catalytic activity. To address this, we screened for PEAK1 effectors by affinity purification and mass spectrometry, identifying calcium/calmodulin-dependent protein kinase 2 (CAMK2)D and CAMK2G. PEAK1 promoted CAMK2D/G activation in TNBC cells via a novel feed-forward mechanism involving PEAK1/PLC{gamma}1/Ca2+ signalling and direct binding via a consensus CAMK2 interaction motif in the PEAK1 N-terminus. In turn, CAMK2 phosphorylated PEAK1 to enhance association with PEAK2, which is critical for PEAK1 oncogenic signalling. To achieve pharmacologic targeting of PEAK1/CAMK2, we repurposed RA306, a second generation CAMK2 inhibitor under pre-clinical development for treatment of cardiovascular disease. RA306 demonstrated on-target activity against CAMK2 in TNBC cells and inhibited PEAK1-enhanced migration and invasion in vitro. Moreover, RA306 significantly attenuated TNBC xenograft growth and blocked metastasis in a manner mirrored by CRISPR-mediated PEAK1 ablation. Overall, these studies establish PEAK1 as a critical cell signalling nexus, identify a novel mechanism for regulation of Ca2+ signalling and its integration with tyrosine kinase signals, and identify CAMK2 as a therapeutically actionable target downstream of PEAK1.

cancer biology↗

bioRxiv2024

Biological management, rather than chemical management, promotes the interaction between plants and their microbiome

In the face of climate change, developing sustainable agricultural practices to reduce the use of synthetic herbicides and pesticides is crucial. However, breeding for higher yields can lead to the decoupling of plant roots and beneficial rhizosphere microbes. In this study, we aim to identify potato cultivars with functional traits facilitating efficient interactions with the rhizosphere microbiome under various agricultural treatments in the field. With the results of profiling microbial communities with amplicon sequencing data of bacteria (16S rRNA gene fragments) and fungi (ITS2 region), a piecewise structural equation model was developed. This model explains the trade-off effects of agricultural management and potato cultivars on plant growth by affecting the rhizosphere microbiome. Furthermore, we highlight that plant cultivar and the rhizosphere microbiome together determine plant below-ground growth under biological management. In contrast, both components are found to be uncoupled under chemical and control management. Our study reveals the importance of considering microbiomes in the breeding process to achieve the goals of sustainable agriculture.

microbiology↗

bioRxiv2024

Topographic, cognitive, and neurobiological profiling of the interdependent structural and functional connectome in the human brain

The structural connectome (SC) is tightly coupled to the functional connectome (FC) in the human brain. Most previous related studies have modeled and analyzed SC or FC as isolated brain networks. However, challenges remain in modeling the interdependent structural-functional connectome and elucidating its cognitive implications and molecular underpinnings. Here, we present a multilayer connectome model composed of SC and FC components and further characterize their interacting topological properties. We found that the interdependent connectome is topographically heterogeneous, with the transmodal cortex exhibiting greater modular variability across layers. This spatial topography reflects cortical hierarchy and evolution and shows high test-retest reliability, reproducibility, and heritability. The interdependent connectome contributes to high-order cognitive processes and is associated with multiple neurotransmitter systems and transcriptional signatures of synaptic transmission. Our results provide insights into the nontrivial interdependencies of SC and FC, highlighting their cognitive significance and the molecular mechanisms underlying the connectome of connectomes.

neuroscience↗

bioRxiv2023

Function-associated scRNA-seq on single lung cancer organoids unravels the immune landscape of tumor parenchyma

In vitro models coupled with multimodal approaches are urgently needed to decipher the local tumor immune microenvironment (TIME) owing to the heterogeneous nature of immune cells and their diverse spatial distributions. Here we generate primary lung cancer organoids (pLCOs) by isolating the tumor cell clusters, including the infiltrated immune cells, from dissected lung cancer samples. A FascRNA-seq platform allowing both phenotypic evaluation and the scRNA-seq of all the single cells in an organoid was developed to dissect the TIME in individual pLCOs. Our analysis on 171 individual pLCOs derived from 7 patients revealed that pLCOs retained the fundamental features as well as intra-tumor heterogeneity of local TIME in the parenchyma of parental tumor tissues, providing a series of models with consistent genetic background but various TIME. Linking the single cell transcriptome data of individual pLCOs with their responses to ICB allowed us to confirm the pivotal role of CD8+ Ts in ICB induced anti-tumor immunity, to identify the potential tumor-reactive T cells with a set of 10 genes, and to unravel the factors regulating T cell activity.

cancer biology↗

bioRxiv2023

SCC3 acts as the cohesin and inhibits inter-sister chromatids repair during rice meiosis

Cohesin is a multi-subunit protein that plays a pivotal role in holding sister chromatids together during cell division. Sister chromatid cohesion 3 (SCC3), constituents of cohesin complex, is highly conserved from yeast to mammals. Since the deletion of individual cohesin subunit always causes lethality, it is difficult to dissect its biological function in both mitosis and meiosis. Here, we obtained scc3 weak mutants using CRISPR-Cas9 system to explore its function during rice mitosis and meiosis. The scc3 weak mutants displayed obvious vegetative defects and complete sterility, underscoring the essential roles of SCC3 in both mitosis and meiosis. SCC3 is localized on chromatin from interphase to prometaphase in mitosis. However, in meiosis, SCC3 acts as an axial element during early prophase I and subsequently situates onto centromeric regions following the disassembly of the synaptonemal complex. The loading of SCC3 onto meiotic chromosomes depends on REC8. scc3 shows severe defects in homologous pairing and synapsis. Consequently, SCC3 functions as an axial element that is essential for maintaining homologous chromosome pairing and synapsis during meiosis.

genetics↗

bioRxiv2023

Dual long-axis reorganization of hippocampus in youth

The reorganization of human hippocampus, especially its interaction with cortex, remains largely undefined in youth. The organization of a single hippocampal long-axis has been predominantly characterized as monotonic1-6, despite recent indications of nonmonotonic features in neuron density7 and geometric eigenmodes8. While the human cortical hierarchy has been well recognized for significant developmental and evolutionary advantages9-12, hippocampus has been typically considered an evolutionarily conserved brain structure1,13,14, and overlooked regarding its integrative role of cortical hierarchical processing during development. Here, we corroborated the presence and significance of a dual long-axis representation of the hippocampal connectome and geometry including both linear and quadratic gradients along its long-axis in youth. This finding was robust across two independent large-scale developmental cohorts. Charting development of the dual long-axis gradients underscored their specific contributions to the cortical hierarchy maturation from the frontoparietal and salience/ventral attention networks. The observed developmental variability in spontaneous brain activities in youth parallels the gradients of myelin content. During childhood through adolescence to early adulthood, the hippocampus reorganized the dual long-axis by gradually relaxing its geometric constraints on the intrinsic network organization of cortical spontaneous activity for refined executive functions. Molecular processes underlying such reorganization of the dual long-axis in hippocampus are linked to neural growth, stress hormone regulation, and neuroactive signaling. Our findings enrich the understanding of hippocampal-cortical reorganizational principles across structural, functional, and molecular dimensions as well as its maturation, and define the plasticity distribution within the human hippocampus at systems level, holding potentials to enhance and translate neurodevelopment and neuropsychiatric healthcare.

neuroscience↗

bioRxiv2023

CellContrast: Reconstructing Spatial Relationships in Single-Cell RNA Sequencing Data via Deep Contrastive Learning

A vast amount of single-cell RNA-seq (SC) data has been accumulated via various studies and consortiums, but the lack of spatial information limits its analysis of complex biological activities. To bridge this gap, we introduce cellContrast, a computational method for reconstructing spatial relationships among SC cells from spatial transcriptomics (ST) reference. By adopting a contrastive learning framework and training with ST data, cellContrast projects gene expressions into a hidden space where proximate cells share similar representation values. We performed extensive benchmarking on diverse platforms, including SeqFISH, Stereo-Seq, 10X Visium, and MERSCOPE, on mouse embryo and human breast cells. The results reveal that cellContrast substantially outperforms other related methods, facilitating accurate spatial reconstruction of SC. We further demonstrate cellContrasts utility by applying it to cell-type co-localization and cell-cell communication analysis with real-world SC samples, proving the recovered cell locations empower novel discoveries and mitigate potential false positives.

bioinformatics↗

bioRxiv2023

BioKG: a comprehensive, high-quality biomedical knowledge graph for AI-powered, data-driven biomedical research

To address the rapid growth of scientific publications and data in biomedical research, knowledge graphs (KGs) have become a critical tool for integrating large volumes of heterogeneous data to enable efficient information retrieval and automated knowledge discovery (AKD). However, transforming unstructured scientific literature into KGs remains a significant challenge, with previous methods unable to achieve human-level accuracy. In this study, we utilized an information extraction pipeline that won first place in the LitCoin NLP Challenge (2022) to construct a large-scale KG named iKraph using all PubMed abstracts. The extracted information matches human expert annotations and significantly exceeds the content of manually curated public databases. To enhance the KGs comprehensiveness, we integrated relation data from 40 public databases and relation information inferred from high-throughput genomics data. This KG facilitates rigorous performance evaluation of AKD, which was infeasible in previous studies. We designed an interpretable, probabilistic-based inference method to identify indirect causal relations and applied it to real-time COVID-19 drug repurposing from March 2020 to May 2023. Our method identified 600-1400 candidate drugs per month, with one-third of those discovered in the first two months later supported by clinical trials or PubMed publications. These outcomes are very challenging to attain through alternative approaches that lack a thorough understanding of the existing literature. A cloud-based platform (https://biokde.insilicom.com) was developed for academic users to access this rich structured data and associated tools.

bioinformatics↗

bioRxiv2023

Using encrypted genotypes and phenotypes for collaborative genomic analyses to maintain data confidentiality

To adhere to and capitalize on the benefits of the FAIR (Findable, Accessible, Interoperable and Reusable) principles in agricultural genome-to-phenome studies, it is crucial to address privacy and intellectual property issues that prevent sharing and reuse of data in research and industry. Direct sharing of genotype and phenotype data is often prohibited due to intellectual property and privacy concerns. Thus there is a pressing need for encryption methods that obscure confidential aspects of the data, without affecting the outcomes of certain statistical analyses. A homomorphic encryption method for genotypes and phenotypes (HEGP) has been proposed for single-marker regression in genome-wide association studies using linear mixed models with Gaussian errors. This methodology permits frequentist likelihood-based parameter estimation and inference. In this paper, we extend HEGP to broader applications in genome-to-phenome analyses. We show that HEGP is suited to commonly used linear mixed models for genetic analyses of quantitative traits including GBLUP and RR-BLUP, as well as Bayesian variable selection methods (e.g., those in Bayesian Alphabet), for genetic parameter estimation, genomic prediction, and genome-wide association studies. By advancing the capabilities of HEGP, we offer researchers and industry professionals a secure and efficient approach for collaborative genomic analyses while preserving data confidentiality.

genetics↗

bioRxiv2023

SCancerRNA: Expression at the Single Cell Level and Interaction Resource of Non-coding RNA Biomarkers for Cancers

Non-coding RNAs (ncRNAs) participate in multiple biological processes associated with cancer as tumor suppressors or oncogenic drivers. Due to their high stability in plasma, urine, and many other fluids, ncRNAs have the potential to serve as key biomarkers for early diagnosis and screening of cancers. During cancer progression, tumor heterogeneity plays a crucial role, and it is particularly important to understand the gene expression patterns of individual cells. With the development of single-cell RNA sequencing (scRNA-seq) technologies, uncovering gene expression in different cell types for human cancers has become feasible by profiling transcriptomes at the cellular level. However, a well-organized and comprehensive online resource that provides access to the expression of genes corresponding to ncRNA biomarkers in different cell types at the single cell level is not available yet. Therefore, we developed the SCancerRNA database to summarize experimentally supported data on long ncRNA (lncRNA), microRNA (miRNA), piwi-interacting RNA (piRNA), small nucleolar RNA (snoRNA), and circular RNA (circRNA) biomarkers, as well as data on their differential expression at the cellular level. Furthermore, we collected biological functions and clinical applications of biomarkers to facilitate the application of ncRNA biomarkers to cancer diagnosis, as well as monitoring of progression and targeted therapies. SCancerRNA also allows users to explore interaction networks of different types of ncRNAs, and build computational models in the future. SCancerRNA is freely accessible at http://www.scancerrna.com/BioMarker.

bioinformatics↗