Biology subjects

Zhao, Q.

Publications and source records attributed to Zhao, Q..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

The Placental Transcriptome Serves as a Mechanistic Link between Prenatal Phthalate Exposure and Placental Efficiency

Prenatal exposure to phthalates, pervasive endocrine-disrupting chemicals, has been linked to child health outcomes, including prematurity and low birthweight. Placental transcriptomics data can reveal mechanisms by which environmental toxicants alter placental and fetal growth. This study aims to investigate the placental transcriptome as a mediator between prenatal maternal urinary phthalate metabolites and placental efficiency. We identified significant associations between maternal urinary concentrations of two phthalate metabolites and the placental transcriptome (132 genes and 27 gene modules). 7 genes and 3 gene modules exhibited significant consistent mediation of the relationship between phthalates and placental efficiency measures. These genes were involved in syncytialization, metabolism, DNA damage and cellular senescence, and steroid biosynthesis--processes essential to fetal growth and development because of the placentas role in nutrient supply, hormone production, and detoxification. These findings suggest a key mediating role of the placental transcriptome in toxicological mechanisms by which phthalates may disrupt fetal growth. TeaserPlacental gene expression mediates the relationship between prenatal phthalate exposure and fetal growth measures.

developmental biology↗

bioRxiv2025

TopoLa: A Universal Framework to Enhance Cell Representations for Single-cell and Spatial Omics through Topology-encoded Latent Hyperbolic Geometry

Recent advances in cellular research demonstrate that scRNA-seq characterizes cellular heterogeneity, while spatial transcriptomics reveals the spatial distribution of gene expression. Cell representation is the fundamental issue in the two fields. Here, we propose Topology-encoded Latent Hyperbolic Geometry (TopoLa), a computational framework enhancing cell representations by capturing fine-grained intercellular topological relationships. The framework introduces a new metric, TopoLa distance (TLd), which quantifies the geometric distance between cells within latent hyperbolic space, capturing the networks topological structure more effectively. With this framework, the cell representation can be enhanced considerably by performing convolution on its neighboring cells. Performance evaluation across seven biological tasks, including scRNA-seq data clustering and spatial transcriptomics domain identification, shows that TopoLa significantly improves the performance of several state-of-the-art models. These results underscore the generalizability and robustness of TopoLa, establishing it as a valuable tool for advancing both biological discovery and computational methodologies.

bioinformatics↗

bioRxiv2025

Diversity of motility gene signatures distinguishes commensal Clostridiathat elicit divergent host immune responses

Adaptive immune responses to commensal flagellins are hallmarks of Crohns disease, but it is unclear whether flagellins themselves promote inflammation or whether flagellated commensals can also be colitogenic. Here, we show that the arrangement of motility loci and the diversity of encoded flagellins can separate flagellated gut-derived Clostridia into at least 2 functionally distinct groups. In gnotobiotic mice, both groups induce tolerogenic responses but only one group promoted tissue inflammation following barrier disruption. Accordingly, specific flagellins expressed by members of this pro-inflammatory group displayed a heightened capacity for TLR5 activation which could be altered by modification of a defined region of the flagellin D0 domain. Finally, bacteria belonging to the pro-inflammatory group were found to be elevated in Crohns disease biopsies. Collectively, our study identified key features of specific commensal bacteria that possess colitogenic potential and revealed one mechanism whereby these organisms can potentially initiate intestinal inflammation.

immunology↗

bioRxiv2025

AtlasAgent: Vision language model and Agent-guided Framework for Evaluation of Atlas-scale Single-cell Integration

As single-cell omics transitions into the era of AI-virtual cells (AIVC), where large-scale single-cell data integration becomes prevalent, the computational demands of integration evaluation emerge as critical scalability bottlenecks. Traditional integration evaluation pipelines, requiring metrics like k-nearest-neighbor batch effect test (kBET) and Local Inverse Simpsons Index (iLISI) employed by state-of-the-art scIB method, often demand large computational resources and long runtimes, making them infeasible for large scale integration studies. Herein, we present AtlasAgent, the first vision-language model (VLM)-powered and AI agent framework to accelerate atlas-scale integration evaluation at unprecedented speed and scale. We systematically evaluate batch correction quality, biological signal preservation and overcorrection risks using chain-of-thought reasoning in conjunction with few-shot and zero-shot prompting strategies. AtlasAgent completes evaluation within 32 seconds, in contrast to scIBs runtime of 5.55 hours in GPU, while identifying the scIB-determint best integration methods within the top-3 in 88.3% of the time, lowering evaluation time from hours to seconds while preserving alignment with domain expert reasoning. AtlasAgent pioneers the use of VLMs to realize scalable and rapid integration evaluation at atlas scale.

bioinformatics↗

bioRxiv2025

Destabilizing effects of eco-evolutionary feedback on community stability and the role of climate change

What underpins the stability of natural systems is a central topic in ecology for decades. Evidence from simple communities with few species shows that eco-evolutionary feedback has the potential to stabilize community dynamics. Here, we show that these findings may not hold in more complex natural systems with many species. We first simulated an eco-evolutionary model of producer-herbivores dynamics, and found destabilizing, rather than stabilizing effect of the eco-evolutionary feedback (i.e. an increasing Lyapunov exponent). We then analyzed 11 long term monitoring data sets of natural aquatic communities, containing the temporal dynamics of a key individual-level trait (body mass) and of population densities. This analysis matched the model results and further showed that warming tends to make eco-evolutionary feedback even more destabilizing. Our results indicate that eco-evolutionary feedback may play a role in destabilizing community dynamics and the climate may mediate the magnitude.

evolutionary biology↗

bioRxiv2025

Vascular smooth muscle cell atherosclerosis trajectories characterized at single cell resolution identify causal transcriptomic and epigenomic mechanisms of disease risk

Vascular smooth muscle cells (SMC) contribute to heritable coronary artery disease (CAD) risk and undergo complex cell state transitions to multiple disease related phenotypes. To investigate the genetic basis of SMC state trajectories that underlie the SMC component of CAD causality we have developed a dense timecourse single cell transcriptomic and epigenetic map of atherosclerosis in a murine disease animal model. Cellular trajectories were derived from the temporal data and probabilistic fate modeling with Waddington-Optimal Transport (WOT). We created transcription factor (TF) centered regulons mapped across the developmental timeline and through network-based prioritization with WOT predicted TFs and in silico TF perturbation, identified key drivers of cell state changes associated with EMT, vascular development, and circadian clock functions. Integration of mouse disease data with human CAD genetic findings identified transition SMC phenotypes that mediate disease risk and point to causal disease mechanisms. Parallel studies using knockout of the validated CAD gene Tcf21 revealed its impact on SMC transition cellular phenotypes and disease risk genes, due in part to a role regulating the transition of SMC precursor cells in the secondary heart field. Together, these studies characterize atherosclerosis trajectories at single cell resolution and identify genetic causal transcriptomic and epigenomic mechanisms of CAD risk.

genomics↗

bioRxiv2025

Central nervous system atlas of larval zebrafish constructed using the morphology of single excitatory and inhibitory neurons

Single-neuron morphology mapping is fundamental for deciphering brain architecture and function, yet in vertebrates it remains limited in spatial coverage and cell-type information. Here we present a nervous system-wide single-neuron morphology atlas of larval zebrafish with annotated excitatory/inhibitory identity and dendrite-axon polarity. The atlas comprises >20,000 reconstructed neurons from >13,400 animals, spanning the central and peripheral nervous system and representing [~]24.5% of the total excitatory and inhibitory neurons in the brain, all integrated into a common physical space with neuroanatomical parcellations. We define >500 excitatory and inhibitory neuronal morphotypes and construct putative inter-cell-type and interregional connectomes. Projection and morphotype analyses reveal distinct laterality and directionality biases and modular innervation patterns in excitatory and inhibitory neurons, while network analyses uncover fundamental connectivity motifs, hubs, and sensorimotor pathways. Accessible through custom-built interactive platform ZExplorer, this atlas provides a foundational resource for multimodal data integration, circuit analysis, computational modeling, and hypothesis-driven research.

neuroscience↗

bioRxiv2025

PEARL: Integrative multi-omics classification and omics feature discovery via deep graph learning

Integrating multi-omics data provides valuable insights into biological processes by capturing information across multiple molecular layers, enabling a comprehensive understanding of complex diseases and driving advancements in precision medicine. However, existing computational methods for multi-omics integration face significant challenges, such as low reliability and poor generalizability, due to the high dimensionality and low sample size nature of omics data. To address these challenges, we present PEARL (Pearson-Enhanced spectrAl gRaph convoLutional networks), a novel deep graph learning method for biomedical classification and functional important omics features identification. PEARL leverages a simple yet effective learning architecture to achieve superior and robust performance in high-dimensional, low-sample-size multi-omics settings. Our results demonstrate that PEARL significantly outperforms existing state-of-the-art methods on both synthetic and real biomedical datasets. Furthermore, applied to Alzheimers disease (AD) brain multi-omics data, features prioritized by PEARL lead to functionally important genes that demonstrate significant enrichment in AD-related pathways. These findings highlight PEARLs practical utility in biomedical research and its potential to enhance biological interpretability in multi-omics studies.

bioinformatics↗

bioRxiv2025

TRiC-assisted folding of class I HDAC family proteins regulated by distinct co-chaperone and cofactor networks

Class I histone deacetylases (HDACs), including HDAC1, HDAC2, HDAC3, and HDAC8, are essential for diverse cellular processes. Although the chaperonin TRiC is implicated in the activation of class I HDACs, the underlying mechanisms remain elusive. Using cryo-electron microscopy (cryo-EM), cross-linking mass spectrometry (XL-MS), and biochemistry analyses, we established class I HDACs as novel TRiC substrates and elucidate TRiC-assisted folding of HDAC1 and HDAC3 during its ATPase cycle, orchestrated by distinct co-chaperone and cofactor networks. In the closed TRiC chamber, both HDAC1 and HDAC3 adopt near-native states with shared binding interfaces. However, their open-state configurations diverge: Hsp70 and PDCD5 engage atop and within TRiC, respectively, for HDAC3, whereas prefoldin (PFD) binds atop TRiC for HDAC1, suggesting roles in substrate delivery and folding modulation. Furthermore, an unexpected bent conformation of CCT4, detected in TRiC-HDAC1 complex, may facilitate co-chaperone dissociation from TRiC. In contrast, HDAC8 folds independently of TRiC. Our study reveals the mechanism governing TRiC-assisted folding of class I HDACs in orchestration of dynamic co-chaperone/cofactor network, shielding new lights on the sophisticated regulatory landscape of TRiC, and open promising avenues for designing peptides or small molecules to selectively modulate TRiC-assisted folding of class I HDACs and other substrates.

molecular biology↗

bioRxiv2025

Dynamic regulation of neuronal Vault trafficking and RNA cargo by the noncoding RNA, Vaultrc5

Vaults are large ribonucleoprotein complexes of unknown function. Here, we report that the vault-associated noncoding RNA, Vaultrc5, is highly enriched at the synapse and is required for activity-dependent vault trafficking in primary cortical neurons. We have discovered that vaults are comprised of unique populations of coding and non-coding RNA, and that this cargo varies dynamically between subcellular compartments. In addition, Vaultrc5 knockdown at the synapse shifts the RNA cargo toward transcripts associated with immune surveillance, and Vaultrc5 knockdown, in vivo, leads to altered fear extinction learning. These findings suggest that the Vaultrc5 is critically involved in coordinating the experience-dependent trafficking of vaults and related RNA cargo, which may represent a novel feature of neuronal plasticity associated with learning and memory.

neuroscience↗

bioRxiv2025

Cycloheximide resistant ribosomes reveal adaptive translation dynamics in C. elegans

Protein translation regulation is critical for cellular responses and development, yet how disruptions during the elongation stage shape these processes remains incompletely understood. Here, we identify and validate a single amino acid substitution (P55Q) in the ribosomal protein RPL-36A of Caenorhabditis elegans that confers complete resistance to high concentrations of the elongation inhibitor cycloheximide (CHX). Heterozygous animals carrying both wild-type RPL-36A and RPL-36A(P55Q) exhibit normal development but intermediate CHX resistance, indicating a partial dominant effect. Leveraging RPL-36A(P55Q) as a single-copy positive selection marker for CRISPR-based genome editing, we introduced targeted modifications into multiple ribosomal protein genes, confirming its broad utility for altering essential loci. In L4-stage heterozygotes, where CHX-sensitive and CHX-resistant ribosomes coexist, ribosome profiling revealed increased start-codon occupancy, suggesting early stalling of CHX sensitive ribosomes. Chronic CHX reduced ribosome collisions, evidenced by fewer disomes and unchanged codon distributions in monosomes. Surprisingly, prolonged elongation inhibition did not activate well characterized stress pathways-including ribosome quality control (RQC), the ribotoxic stress response (RSR), or the integrated stress response (ISR)-as indicated by absence of changes in RPS-10 ubiquitination, eIF2 phosphorylation, PMK-1 phosphorylation, or the transcriptional upregulation of ATF-4 target genes. Instead, RNA-normalized ribosome footprints revealed gene-specific changes in translation efficiency, with nucleolar and P granule components significantly decreased while oocyte development genes were increased. Consistent with these observations, we detected premature oogenesis in L4 animals, suggesting that partial translation elongation inhibition reshapes translation efficiency, to fine-tune developmental timing.

genetics↗

bioRxiv2025

RNA Pol I activity maintains chromatin condensation and the H3K4me3 gradient essential for oogenesis, independent of ribosome production

Oogenesis requires extensive and dynamic chromatin remodeling that primes gene promoters for later transcriptional activation during embryonic development. Here, we uncover a pivotal, non-canonical role for RNA Polymerase I (Pol I) in driving these chromatin state transitions during Caenorhabditis elegans oogenesis. Using the auxin-inducible degron system to selectively deplete either Pol I catalytic subunits or ribosome assembly factors, we disentangle the consequences of impaired nucleolar integrity from reductions in ribosome biogenesis. Strikingly, although disrupting ribosome assembly caused minimal effects on oocyte production, loss of Pol I activity led to widespread changes in chromatin accessibility, a dampening of the distal-proximal H3K4me3 gradient required for oogenesis, reduced synapsis, and elevated ATM/ATR phosphorylation, resulting in fewer but significantly larger oocytes. Despite their promoters becoming more accessible, oogenesis genes did not show large changes in steady-state mRNA, consistent with transcriptional repression prior to fertilization. Instead, Pol I depletion prematurely remodeled oogenic chromatin, through a misdirection of H3K4me3 deposition towards promoters normally primed for zygotic genome activation. These findings reveal an epigenetic gating function for nucleolar integrity in oocyte maturation: Pol I preserves three-dimensional chromatin organization and maintains proper spatiotemporal regulation of histone modifications, independent of ribosome production. Given the evolutionary conservation of nucleolar dynamics and histone modifications during gametogenesis, our work suggests that nucleolar stress, whether from environmental factors, aging, or genetic disorders, could broadly compromise fertility by disrupting oogenic chromatin priming. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/652530v2_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@9b95bforg.highwire.dtl.DTLVardef@844eb5org.highwire.dtl.DTLVardef@4b7a79org.highwire.dtl.DTLVardef@155ca31_HPS_FORMAT_FIGEXP M_FIG C_FIG

developmental biology↗

bioRxiv2025

Glucocorticoid receptor and RUNX transcription factors cooperatively drive CD8 T cells dysfunction in human cancer

Glucocorticoids (GCs) are potent modulators of immune responses; however, the mechanisms by which GCs regulate gene expression in human CD8 T cells remain incompletely defined. Here, we delineate how physiological cortisol signalling shapes the transcriptional and chromatin landscapes of primary human CD8 T cells. We identify a substantial cohort of GC-responsive genes that are co-regulated through the cooperative activity of the glucocorticoid receptor (GR) and RUNX transcription factors. Integrative RNA sequencing and ChIP sequencing analyses identified genome-wide cortisol-responsive immunoregulatory genes. Genetic deletion of the GR (encoded by NR3C1) abolished cortisol-induced gene expression changes, confirming GR-dependency. Notably, GR chromatin occupancy in cortisol-treated CD8 T cells was strongly enriched at RUNX transcription factor (TF) motif rather than canonical GC response elements (GREs). Co-immunoprecipitation assays validated a ligand-dependent physical interaction between GR and RUNX and revealed the interacting domains. Single-cell transcriptomic analyses of tumour infiltrating CD8 T cells revealed significant enrichment of cortisol-responsive genes, indicating an active GC signalling (response) within the tumour microenvironment. GR-RUNX dual controlled genes were enriched in tumour-infiltrating CD8 T cells across multiple cancer types, including lung adenocarcinoma, head and neck squamous carcinoma, pancreatic cancer, and breast cancer. We found GR-RUNX co-regulated genes are predominantly expressed in the predysfunctional state of CD8 T cell population of different solid tumours. These results suggest that local cortisol signalling within tumour microenvironments drives CD8 T cell dysfunction through GR-RUNX TF cooperation. Collectively, our findings identify RUNX3 TF as a critical mediator of GR signalling in human CD8 T cells and reveal a novel mechanism by which endogenous GCs influence antitumour immunity, which could be therapeutically targetable.

immunology↗

bioRxiv2025

Recognition of unique cell surface glycopolymers by diversified lectin domains specifies umbrella toxin targeting

The bacterial cell envelope provides structural integrity and is an essential conduit through which the organism interacts with its environment. However, the molecular structures of its constituents can also be exploited as receptors, permitting threats such as toxins and phage access to the cell. We previously demonstrated that Streptomyces coelicolor secretes an umbrella toxin particle that acts in a highly selective manner to inhibit the hyphal growth of competing Streptomyces strains. Here, we identify the receptor of umbrella toxins as teichuronic acid (TUA) oligosaccharides anchored to the cell surface through linkage to wall teichoic acids (WTA). We show that the carbohydrate portion of this previously undescribed hybrid TUA-WTA molecule is variable across species and that targeting specificity derives from its selective recognition by diversified lectin domains associated with umbrella particles. A cryo-EM structure of a lectin-TUA complex reveals the molecular basis for umbrella toxin cell targeting and, in conjunction with bioinformatic analyses, provides insights into a molecular arms race that we posit drives diversification of umbrella particles and the chemical composition of Streptomyces cell envelopes.

microbiology↗

bioRxiv2025

Single cell mapping of the human endometrium and first trimester decidua identifies distinct epithelial and stromal cell contributions to fertility

The human endometrium undergoes dynamic changes across the menstrual cycle to establish a receptive state for embryo implantation. Using bulk and single-cell RNA sequencing, we characterized gene expression dynamics in the cycling endometrium and the decidua from early pregnancy. We are the first to demonstrate that during the mid-secretory phase--the period encompassing the window of implantation--secretory glandular epithelial cells undergo notable transcriptional changes in cell-cell communication. Through comprehensive analyses, we identified the Glandular Epithelium Receptivity Module (GERM) signature, comprising 556 genes associated with endometrial receptivity. This GERM signature was consistently perturbed across multiple datasets of endometrial samples from women with impaired fertility, validating its relevance as a marker of receptivity. In addition to epithelial changes, we observed shifts in stromal cell populations, notably involving decidual and senescent subsets, which also play key roles in modulating implantation. Together, these findings provide a high-resolution transcriptomic atlas of the receptive and early pregnant endometrium and shed light on key molecular pathways underlying successful implantation.

molecular biology↗

bioRxiv2025

The photoreaction process of a large-Stokes-shift red fluorescence protein-LSSmCherry1

Large Stokes shift red fluorescent proteins are highly valued in fluorescence imaging due to their considerable spectral separation and minimal self-absorption. However, a notable gap remains in our understanding of these proteins excited-state dynamics. Unlocking this knowledge could potentially drive significant advancements in cellular and molecular biology. In this study, we systematically examine the excited-state dynamics of LSSmCherry1, a large Stokes shift red fluorescent protein, under varying isotopic compositions and temperatures. Our aim is to elucidate its distinctive spectral properties. Through steady fluorescence spectral experiments at different temperatures, we demonstrate that the large Stokes shift is significantly reduced by approximately 80 nm at low temperatures compared to room temperature. Using transient fluorescence and absorption spectroscopy, we dissect the excited-state dynamics of LSSmCherry1 in neutral environments. We also investigate the kinetic isotopic effect by comparing spectra in water and heavy water. These analyses allow us to delineate plausible photocyclic pathways. Our results reveal that the excited-state dynamics of LSSmCherry1 follow a model similar to that observed in other fluorescent proteins, such as Green Fluorescent Protein (GFP). Notably, we demonstrate that the excited-state proton transfer (ESPT) process is the primary origin of the large Stokes shift in LSSmCherry1. This ESPT process occurs rapidly, within approximately 365 fs after excitation in the neutral environment. This study provides crucial insights into the mechanisms underlying large Stokes shift fluorescent proteins, potentially paving the way for the development of improved fluorescent probes for biological imaging. TOC GraphicSome journals require a graphical entry for the Table of Contents. This should be laid out "print ready" so that the sizing of the text is correct. Inside the tocentry environment, the font used is Helvetica 8 pt, as required by Journal of the American Chemical Society. The surrounding frame is 9 cm by 3.5 cm, which is the maximum permitted for Journal of the American Chemical Society graphical table of content entries. The box will not resize if the content is too big: instead it will overflow the edge of the box. This box and the associated title will always be printed on a separate page at the end of the document.

biochemistry↗

bioRxiv2025

Warming is associated with temporal decoupling of species' body size and abundance

Eco-phenotypic feedback--reciprocal interactions between phenotypic traits and ecological dynamics--is increasingly recognized as a driver of biodiversity patterns, species interactions, and ecosystem functioning. Through this feedback, phenotypic traits such as body size can rapidly respond to environmental variation through plastic or evolutionary changes, altering population abundance, which in turn feeds back to shape the trait dynamics. Yet, whether the integrity of this feedback remains stable under environmental change remains unclear. Using long-term monitoring data from 101 aquatic and terrestrial ecosystems encompassing multiple generations, we provide the first synthesis showing that warming and species richness systematically weakens the eco-phenotypic feedback loop, while mean species body size strengths it. Our findings reveal that climate change can erode key trait- demography couplings and highlight the importance of integrating ecophenotypic frameworks into global change research.

ecology↗

bioRxiv2025

BioBatchNet: A Dual-Encoder Framework for Robust Batch Effect Correction in Imaging Mass Cytometry

MotivationImaging Mass Cytometry (IMC) is a cutting-edge technology for analysing spatially resolved protein expression at the single-cell level. However, its downstream analyses are often hindered by batch effects, which introduce systematic biases and obscure true biological variations. Existing correction methods, largely developed for scRNA-seq data, struggle to achieve precise control, leading to either over-correction by removing critical biological information, or under-correction by leaving residual batch effects. Moreover, these methods face challenges in adapting to IMC data due to differences in data characteristics. Furthermore, IMC data often feature imbalanced and overlapping cell populations, complicating clustering and downstream analysis. These challenges underscore the need for a robust and controllable batch effect correction approach tailored to IMC data. ResultsWe present BioBatchNet, a dual-encoder framework utilising adversarial training to explicitly disentangle batch-specific and biological signals. BioBatchNet enables controllable batch effect correction, effectively balancing correction with the preservation of biological variation. We evaluated BioBatchNet on three IMC datasets, where it outperformed seven benchmarking methods with robustness in both correction and biological signal conservation. Additionally, we developed a Constrained Pairwise Clustering (CPC) method, which employs constrained pairs to improve clustering performance, even in datasets with imbalanced and overlapping cell populations. To validate its generalisability, BioBatchNet was also applied to four scRNA-seq datasets, where it delivered competitive performance compared to eight typical methods. These results demonstrate BioBatchNets generalisability and robustness in correcting batch effects across diverse single-cell datasets and underscore its potential for large-scale biological analyses.

bioinformatics↗