Biology subjects

Qiu, X.

Publications and source records attributed to Qiu, X..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

Epigenetic Subtypes of High-Grade T1 Bladder Cancer Reveal Intra-Tumor Heterogeneity and Distinct Interactions with Tumor Microenvironment.

High-Grade T1 (HGT1) Non-Muscle Invasive Bladder Cancer (NMIBC) is a clinically heterogeneous disease, characterized by unpredictable treatment responses and limited tools for recurrence prediction. Although molecular classification efforts have been made, patient stratification still primarily relies on clinicopathological features, which offer limited clinical precision. In this study, we integrated chromatin profiling in bulk with single-nuclei(sn) RNA-seq, immunohistochemistry and spatial transcriptomics to define epigenetic subtypes of HGT1, characterize their heterogeneity, and investigate tumor-microenvironment interactions. Our findings reveal distinct chromatin profiles differentiating urothelial (URO) and micropapillary (MP) histological variants of high-risk HGT1. We identified three epigenetic states: two within the URO group, luminal-like inflammatory (LLI) and basal-like (BL), and a separate signature unique to MP tumors. Single-cell and spatial resolution approaches validated intratumoral heterogeneity and provided insight into subtype-specific microenvironmental contexts. Notably, [~]40% of URO tumors exhibited spatially distinct coexisting LLI and BL components. BL regions showed enrichment for angiogenesis and hypoxia pathways and were preferentially located near vascular stroma, while LLI regions showed to be located at the core of the tumor. MP tumors featured a markedly different microenvironment, characterized by diverse populations of cancer-associated fibroblasts (CAFs) and M2-polarized macrophages intermingled with tumor cells, suggesting a more immunosuppressive niche which could account for their worse clinical outcome. URO tumors, by comparison, showed a more immune-excluded phenotype. These findings provide a detailed molecular and spatial map of bladder cancer heterogeneity, highlighting how distinct epigenetic subtypes and histological variants are associated with tumor architecture and microenvironmental interactions. Our data underscore the need for subtype-specific therapeutic strategies to more effectively address the complexity already existing at HGT1 bladder cancer.

cancer biology↗

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

Lack of synergy between AR targeted therapies and PARP inhibitors in homologous recombination-proficient prostate cancer

Recent clinical trials have explored the combination of androgen receptor (AR) pathway inhibitors and poly (ADP-ribose) polymerase (PARP) inhibitors as a potential treatment for castration-resistant prostate cancer. This combination treatment is based on the premise that AR directly regulates expression of DNA repair genes, leading to synergy between PARP and AR inhibition. Despite some promising preclinical evidence, this combination therapy has shown limited efficacy in patients with homologous recombination (HR)-proficient tumors. To investigate this discrepancy between preclinical and clinical results, we profiled the effects of PARP inhibition in prostate cancer models in the presence or absence of AR inhibition. Surprisingly, AR inhibition impaired response to PARP inhibitors in castration-sensitive cells and had no effect on response in castration-resistant cells. AR inhibition also did not regulate DNA repair in either the castration-resistant or castration-sensitive setting. Instead, we find that cell cycle progression is required for response to PARP inhibition in homologous-recombination proficient prostate cancer. STATEMENT OF SIGNIFICANCEAndrogen deprivation does not inhibit DNA repair and does not synergize with PARP inhibition in prostate cancer with intact homologous recombination repair.

cancer biology↗

bioRxiv2025

Human genetic variation shapes the antibody repertoire across B cell development

The peripheral antibody repertoire is shaped by inherited genetic variation and selection during B cell development. However, how the repertoire changes across developmental stages--and the relative impact of genetics and selection in establishing the antibody repertoire--remain largely unknown. To dissect the individual and combined effects of these factors, we integrated antibody repertoire transcriptomics across pro-B, pre-B, immature, and naive B cells with single-molecule real-time long-read DNA sequencing of the immunoglobulin heavy (IGH), kappa (IGK), and lambda (IGL) chain loci. We find that IGH genetic variants establish gene usage biases at the pro-B stage that persist throughout development. In contrast, IGK and IGL repertoires are extensively remodeled during maturation, consistent with receptor editing. Surprisingly, IGH variants also exert trans effects on light chain gene usage, suggesting coordinated constraints on heavy-light chain pairing. Principal component and allele-specific analyses reveal that genetics primarily shapes the heavy chain repertoire, while selection more strongly influences light chain diversity. These findings define distinct dynamics of antibody repertoire development and underscore the importance of personal immunogenomics in understanding individual immune responses.

genomics↗

bioRxiv2025

Spatial Transcriptomics Using Archived Formalin-Fixed Paraffin-Embedded Core Needle Biopsy Tissues Revealed Unique Transcriptomic Signatures in Kidney Transplant Rejections

Clinical core needle biopsies present challenges for transcriptomic analysis due to limited tissue volume. In this study, we determined the feasibility of using spatial transcriptomics to evaluate rejection on formalin-fixed paraffin-embedded (FFPE) core needle biopsies from human kidney allografts. We demonstrated that non-rejection, active antibody mediated rejection (AMR), acute cell mediated rejection (TCMR) and chronic active AMR have distinct transcriptomic signatures. Subclusters of monocytes/macrophages with high Fc gamma receptor IIIA (FCGR3A) expression were identified in C4d-positive active AMR and acute TCMR, and the spatial distribution of these cells corresponded to the characteristic histopathological features. Key markers related to monocyte/macrophage activation and innate alloantigen recognition were upregulated, along with metabolic pathways associated with trained immunity in AMR and TCMR. The discovery of unique transcriptomic signatures associated with AMR and TCMR facilitates the differentiation of acute kidney allograft rejections using spatial transcriptomic data derived from FFPE core needle biopsies.

immunology↗

bioRxiv2025

Cancer Cell Adaptation to Cycling Hypoxia: Integrating Mathematical Modeling with Experimental Validation of HIF-1 Dynamics

The adaptive response of cancer cells to hypoxia, a key microenvironmental factor in solid tumors, is intricately orchestrated by Hypoxia-inducible factor 1 (HIF1). Evidence is accumulating on oxygen dynamics in tumor cores, showing that hypoxia is frequently unstable, or cycling, associated with specific phenotypic outcomes for the cancer. Transcriptomic analysis show that most gene expression changes in cycling hypoxia lie in between the change caused by stable hypoxia, suggesting multi-cycle averaging of dosage in the oxygen tension, and likely HIF-1 induced transcription. However, small subset of genes show an oscillation/cycling hypoxia specific response, suggesting that the transcriptional machinery of these genes may interpret cycling HIF-1 activity differently from stably high HIF-1 activity. Here, we model a gene regulatory circuit, the incoherent feed-forward loops (IFFLs) to explore parameter regimes where oscillatory specific transcription is plausible. In these IFFL models, HIF-1 regulates gene transcription of a target gene directly, as well indirectly via another transcription factor with an opposite effect on gene transcription. We have identified several plausible parameter regimes where oscillation specific gene expression can occur, with potentially significant effect on cancer growth and progression. Finally, we experimentally confirmed that HIF-1 can form IFFLs with two key transcription factors p53, and Notch1, resulting in cycling hypoxia specific gene expression linked to breast cancer progression and poor prognosis. Our models mechanistically reveal how temporal fluctuations in the tumor microenvironment may directly inform downstream transcription, identify hitherto unknown HIF-1 driven mechanism of cancer progression contributing to emergent tumor heterogeneity.

bioinformatics↗

bioRxiv2025

CTCF-RNA interactions orchestrate cell-specific chromatin loop organization

CCCTC-binding factor (CTCF) is essential for chromatin organization. CTCF interacts with endogenous RNAs, and deletion of its ZF1 RNA-binding region ({Delta}ZF1) disrupts chromatin loops in mouse embryonic stem cells (ESCs). However, the functional significance of CTCF-ZF1 RNA interactions during cell differentiation is unknown. Using an ESC-to-neural progenitor cell (NPC) differentiation model, we show that CTCF-ZF1 is crucial for maintaining cell-type-specific chromatin loops. Expression of CTCF-{Delta}ZF1 leads to disrupted loops and dysregulation of genes within these loops, particularly those involved in neuronal development and function. We identified NPC-specific, CTCF-ZF1 interacting RNAs. Truncation of two such coding RNAs, Podxl and Grb10, disrupted chromatin loops in cis, similar to the disruption seen in CTCF-{Delta}ZF1 expressing NPCs. These findings underscore the inherent importance of CTCF-ZF1 RNA interactions in preserving cell-specific genome structure and cellular identity. HIGHLIGHTSO_LICTCF loop anchors induced after differentiation are disrupted in the {Delta}ZF1 RNA-binding mutant. C_LIO_LILoop loss in the {Delta}ZF1 mutant is independent of its DNA binding and protein interactions. C_LIO_LIChromatin loop loss is associated with gene dysregulation. C_LIO_LITruncation of cell-specific, CTCF-ZF1-interacting RNAs disrupts chromatin loops in cis. C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/643339v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1dad736org.highwire.dtl.DTLVardef@674a5dorg.highwire.dtl.DTLVardef@14345d4org.highwire.dtl.DTLVardef@19d83cb_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2025

Mesenteric ischemia and bacterial translocation precipitate the intoxication phase of yellow fever

Yellow fever (YF) is classically conceptualized as a hepatotropic disease; indeed, the liver is the primary site of yellow fever virus (YFV) replication. However, circumstantial evidence suggests that extra-hepatic disease may be important for the [~]30% of YF cases that progress to the severe "intoxication" phase of the disease. Using a Syrian hamster-adapted (HA)-YFV, we worked backwards from observations in humans to examine early events that precipitate the intoxication phase of YF. HA-YFV caused severe disease in [~]80% of infected animals characterized by lethargy and weight loss that progressed to widespread petechiae and death by day 6. Clinical chemistry, coagulation testing, histology, immunohistochemistry, and in-situ hybridization were consistent with a cascade of hepatocyte-specific virus replication causing liver damage and a defect in clotting factor synthesis. Despite a lack of extra-hepatic HA-YFV replication, severe pathology was observed in the intestines and pancreas. Histopathological analysis over the time-course of HA-YFV infection revealed an ischemic pattern in these tissues, culminating in fibrinoid/coagulative necrosis of these organs. Further investigation showed that ischemia-induced erosion of the gut epithelial barrier serves as an entry point for luminal bacteria that spread systemically via the portal system. Thus, the intoxication phase of YF is a sepsis-like syndrome caused by translocation of bacteria from a damaged gastrointestinal tract. Evaluation of human YF cases for these previously overlooked disease features confirmed this overarching mechanism: bacteria were identified in the portal vein and liver parenchyma of fatal YF cases along with elevations in plasma markers of bacteremia and a bacteria-driven inflammatory response. Importantly, blood concentrations of the gastrointestinal damage marker intestinal fatty acid binding protein (I-FABP) were significantly elevated in fatal YF cases relative to non-fatal cases, suggesting that I-FABP measurements could be useful in prognosis and treatment decision making. Our findings tie together several recent and historically unexplained observations surrounding the highly-lethal intoxication phase of YF in humans: a high AST/ALT ratio, "black vomit," pancreatitis, and paradoxical neutrophilia. A better appreciation for the drivers of mesenteric ischemia, and preemption of bacterial sepsis, may improve outcomes in cases of severe YF.

microbiology↗

bioRxiv2025

MiRNA Locker: A Modularized DNA Assembly As miRNA Inhibitors

MicroRNAs (miRNAs) are vital post-transcriptional regulators that govern key cellular processes such as proliferation, migration, and apoptosis. Current loss-of-function approaches, including chemically modified antisense oligonucleotides (ASOs), face significant challenges, including high costs, limited scalability, and off-target effects. To overcome these limitations, we developed "miRNA Locker", a novel miRNA inhibition platform created using the Overlapped Oligo Assembly (OOA) method. This innovative platform constructs highly stable dumbbell-shaped single-stranded DNA structures, offering improved target specificity, scalability, and cost-effectiveness. Using miR-214 as a proof-of-concept target, we demonstrated that miRNA Lockers effectively bind Argonaute-miRNA complexes, reduce miRNA levels, and induce downstream changes in gene expression and cellular phenotypes, surpassing the performance of commercial antagomirs. Furthermore, applying miRNA Lockers to miR-654 validated the regulatory role of miR-654 in modulating RNF8 expression and promoting epithelial-mesenchymal transition (EMT) in lung cancer cells. Our results highlight the potential of miRNA Lockers as a versatile tool for studying miRNA function and advancing miRNA-based therapies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/632138v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@c6ac1eorg.highwire.dtl.DTLVardef@14e2698org.highwire.dtl.DTLVardef@1c7d84aorg.highwire.dtl.DTLVardef@148f9c1_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Toward a privacy-preserving predictive foundation model of single-cell transcriptomics with federated learning and tabular modeling

The ability to pre-train on vast amounts of data to build foundation models (FMs) has achieved remarkable success in numerous domains, including natural language processing, computer vision, and, more recently, single-cell genomics--epitomized by GeneFormer, scGPT, and scFoundation. However, as single-cell FMs begin to train on increasingly large corpora, significant privacy and ethical concerns arise. Moreover, unlike text data, single-cell data is unordered and exhibits a unique tabular structure that most existing single-cell FMs overlook. In this study, we propose Tabula, a privacy-preserving and tabular-structure aware FM designed with federated learning (FL) and tabular modeling. Tabula combines the advantages of FMs and FL, enabling collaborative model training across multiple clients without compromising data privacy. In contrast to earlier single-cell FMs--which treat single-cell data like natural language (viewing cells as "words" defined by genes)--Tabula introduces a novel pretraining strategy that explicitly models the tabular structure of single-cell data. Extensive experimental results show that Tabula outperforms state-of-the-art methods in various downstream tasks (including cell type annotation, gene imputation, gene perturbation, multi-batch integration, and multi-omics integration) while requiring only half the data for pretraining and preserving data privacy. Furthermore, Tabula accurately reveals pairwise and even combinatorial regulatory logic across diverse biological systems, including hematopoiesis, pancreatic endogenesis, neurogenesis, and cardiogenesis. Thus, Tabula provides a new foundation model that explicitly incorporates the tabular nature of single-cell data alongside FL, paving the way for creating a "virtual cell" for human health under critical privacy preservation.

bioinformatics↗

bioRxiv2024

Phosphotyrosine Signal Profiling of Clinical CAR-T Reveals Tonic Signaling Associated with Therapeutic Efficacy

Chimeric Antigen Receptor T (CAR-T) therapies have revolutionized the treatment of cancers such as relapsed and refractory B cell malignancies. However, the precise therapeutic mechanism of CAR-T action remain to be elucidated. In this study, we systematically analyzed CAR signaling via phosphotyrosine (pTyr) proteomics in CAR-T cells from both clinical patients and healthy donors. We found that CAR-T products from clinical patients displayed heightened tyrosine phosphorylation, particularly in the JAK-STAT, MAPK and TCR signaling cascades. We also identified the significantly regulated pTyr sites in primary CAR-T cells under tonic signaling or upon stimulation by antigen-presenting CD19-K562 cells. Although both CD28{zeta} and 4-1BB{zeta} CAR-T cells exhibited comparable pTyr changes, CD28{zeta} CAR-T cells displayed a more pronounced activation in the TCR signaling pathway. Additionally, comparative analysis between clinical and primary CAR-T cells suggested that CAR-T products were subject to heightened tonic signaling, which may be related to therapeutic relapse. Our findings reveal the state of clinical CAR-T products and refine the CAR-T signal transduction network, providing comprehensive insights and informed guidance for CAR-T therapies.

immunology↗

bioRxiv2024

Divergence of the Individual repeats in the leucine-rich repeat domains of human Toll-like receptors explain their diversity and functional adaptations.

Toll-like receptors (TLRs) are best known pattern recognition receptors of innate immunity, detecting a broad range of pathogen-associated molecular patterns (PAMPs), and endogenous danger associated molecular patterns (DAMPs), initiating inflammatory and antimicrobial responses. TLRs contain two specialized domains, a signaling domain (TIR), and a receptor domain composed of tandem repeats of short 20-30 amino acid segments called Leucine-rich Repeats (LRRs). LRR domains, often paired with other domains, are widespread in all kingdoms of life, invariably forming highly similar, solenoid-like three dimensional structures. Despite this structural conservation, LRR domains overall, and receptor domains of TLRs in particular, exhibit remarkable diversity in binding specificity, recognizing diverse ligands such as lipoproteins, nucleic acids, polysaccharides, other proteins and protein complexes. To understand how this conserved scaffold can accommodate such binding diversity, we performed an in-depth analysis of sequential and structural conservation of individual repeats within the LRR domain of each of the ten human TLRs. We demonstrate that the small variations in repeat lengths and local sequence patterns lead to subtle, but critical structural adaptations, such as changes in local curvature, emergence of loops, cavities and interaction interfaces, each contributing to recognition of specific ligands and formation of the receptor complexes. TLR polymorphisms in human populations can further fine-tune the specificity and strength of ligand recognition, influencing how individuals respond to different pathogens and cell damage causing diseases. We show that in most cases the interfaces with the ligands show high level of polymorphism, suggesting a potential for diverse immune responses to infections among human populations while interfaces with other proteins in the receptor complex are more conserved, pointing to the importance of conserving the overall structure of the signaling pathways. By studying how divergence in LRR repeats affects TLRs structure and function, we provide deeper insights into TLR recognition mechanisms, and a better understanding of the mechanism of evolutionary adaptability of immune recognition systems, both along the evolution of vertebrates, and across the human population. Significance statementHuman Toll-like receptors (hTLRs) play a key role in the innate immune response, recognizing diverse danger molecular patterns through their receptor domains, that consist of tandem repeats of a structural unit called a leucine rich repat (LRR). They are also an example of functionally diverse paralogous family where, despite the overall sequence and structure similarity, each member develops its specific function. Our study reveals that subtle modifications of dividual repeats, without disrupting the overall structure of the receptor domain, form secondary patterns defining the functional specificity of each TLR, enabling them to recognize and respond to a broad array of pathogen and disease associated molecular patterns. These findings offer a new perspective on how sequence variability within conserved protein domains can drive functional evolution and adaptation, with implications both for understanding immune receptor functional adaptation and their fast evolution as well as more general problem of functional diversification in paralogous families.

bioinformatics↗

bioRxiv2024

MoEFold2D: Safeguarding RNA Secondary Structure Prediction with a Mixture of Deep Learning and Physics-based Experts

A mixture of experts (MoE) approach is developed to mitigate poor out-of-distribution (OOD) generalization of deep learning (DL) models for single-sequence-based prediction of RNA secondary structure. The main idea is to use DL models for in-distribution (ID) test sequences to take advantage of their superior ID performances, while relying on physics-based models for OOD sequences to ensure robust predictions. One key ingredient of the pipeline, named MoEFold2D, is automated ID/OOD detection via consensus analysis of an ensemble of DL model predictions without accessing training data during inference. Specifically, motivated by the clustered distribution of known RNA structures, a collection of distinct DL models is trained by iteratively leaving one cluster out. Each DL model hence serves as an expert on all but one cluster in the training data. Consequently, for an ID sequence, all but one DL model makes accurate predictions consistent with one another, while an OOD sequence yields highly inconsistent predictions among all DL models. Consensus analysis of DL predictions categorizes test sequences as ID or OOD. ID sequences are then predicted by averaging the DL models in consensus, and OOD sequences are predicted using physics-based models. Instead of remediating generalization gaps with alternative approaches such as transfer learning and sequence alignment, MoEFold2D circumvents unpredictable ID-OOD gaps and combines the strengths of DL and physics-based models to achieve accurate ID and robust OOD predictions.

bioinformatics↗

bioRxiv2024

Orally surface engineered probiotic system for ulcerative colitis therapy via modulating gut microbiota and immune homeostasis

Oral probiotics have emerged as a promising therapeutical strategy for effectively managing ulcerative colitis (UC) in the world. The existing researches successfully preserve probiotic viability in the upper gastrointestinal tract, but they fall short in achieving precise release profile and effective colonization of probiotics at the site of colitis in colon as well as the understanding of therapeutic mechanism with suboptimal efficacy. This constraint poses a significant barrier to rational design and effective development of oral probiotic system. Here, we fabricate an orally layered-by-layered probiotic (Escherichia coli Nissle 1917, EcN) system (so-called CML@EcN) based on carboxymethyl modified lignin (CML) which can significantly protect EcN in gastric and small intestinal microenvironment and efficiently control release EcN in colon. Interestingly, the release and proliferation process of EcN in the colon are detected and can be modeled as a plug-flow mode. We derive a mathematical expression that highly matches the experimental results, providing a theoretical basis for quantitatively calculation of the release process. Furthermore, CML@EcN significantly alleviates symptoms in dextran sulfate sodium (DSS)-induced UC mice by modulating the multiple organ immune disorder and gut microbiota (GM)/metabolites profile as well as reconstructing the colon barrier. Importantly, we explore the mechanism of immune homeostasis regulation via metabolism from GM. Moreover, the CML armour is excreted and would not influence the process. This work not only reports a novel oral therapeutic for UC treatment with high efficacy as well as the exploration of mechanism between GM and immune homeostasis, but also provides a general approach to engineer probiotics for oral administration.

microbiology↗

bioRxiv2024

Horizontally acquired CSP genes contribute to wheat adaptation and improvement

Although horizontal gene transfer (HGT) often facilitates environmental adaptation of recipient organisms, whether and how they might affect crop evolution and domestication is unclear. Here we show that three genes encoding cold shock proteins (CSPs) were transferred from bacteria to the last common ancestor of Triticeae, a tribe of the grass family that includes several major staple crops such as wheat, barley, and rye. The acquired CSP genes in wheat (TaCSPs) are functionally conserved with their bacterial homologs by encoding a nucleic acid binding protein. Experimental evidence indicates that TaCSP genes positively regulate drought response and improve photosynthetic efficiency under water deficit conditions, by directly targeting a type 1 metallothionein gene to increase ROS scavenging, which in turn contributed to the geographic expansion of wheat. We identified an elite CSP haplotype in Aegilops-tauschii, introduction of which to wheat significantly increased drought tolerance, photosynthetic efficiency and grain yields. These findings not only provide major insights into the role of HGT in crop adaptation and domestication, but also demonstrate that novel microbial genes introduced through HGT offer a stable and naturally optimized resource for transgenic crop breeding and improvement.

plant biology↗

bioRxiv2024

Affective Symptoms in Pregnancy are Associated with the Vaginal Microbiome

Composition of the vaginal microbiome in pregnancy is associated with adverse maternal, obstetric, and child health outcomes. Identifying the sources of individual differences in the vaginal microbiome is therefore of considerable clinical and public health interest. The current study tested the hypothesis that vaginal microbiome composition during pregnancy is associated with an individuals experience of affective symptoms and stress exposure. Data were based on a prospective longitudinal study of a diverse and medically healthy community sample of 275 mother-infant pairs. Affective symptoms and stress exposure and select measures of associated biomarkers (diurnal salivary cortisol, serum measures of sex hormones) were collected at each trimester; self-report, clinical, and medical records were used to collect detailed data on socio-demographic factors and health behavior, including diet and sleep. Vaginal microbiome samples were collected in the third trimester (34-40 weeks) and characterized by 16S rRNA sequencing. Identified taxa were clustered into three community state types (CST1-3) based on dissimilarity of vaginal microbiota composition. Results indicate that depressive symptoms during pregnancy were reliably associated with individual taxa and CST3 in the third trimester. Prediction of functional potential from 16S taxonomy revealed a differential abundance of metabolic pathways in CST1-3 and individual taxa, including biosynthetic pathways for the neuroactive metabolites, serotonin and dopamine. With the exception of bioavailable testosterone, no significant associations were found between symptoms- and stress-related biomarkers and CSTs. Our results provide further evidence of how prenatal psychological distress during pregnancy alters the maternal-fetal microbiome ecosystem that may be important for understanding maternal and child health outcomes. ImportancePrenatal affective symptoms and stress are associated with maternal, obstetric, and child health outcomes, but the mechanisms underlying these links and their application to intervention remain unclear. The findings from this investigation extend prior microbiome-oriented research by demonstrating that the maternal vaginal microbiome composition has a biologically plausible mechanistic link with affective symptoms that also suggest additional clinical applications for assessment and intervention.

microbiology↗

bioRxiv2024

Graph Contrastive Learning of Subcellular-resolution Spatial Transcriptomics Improves Cell Type Annotation and Reveals Critical Molecular Pathways

Imaging based spatial transcriptomics (iST), such as MERFISH, CosMx SMI, and Xenium, quantify gene expression level across cells in space, but more importantly, they directly reveal the subcellular distribution of RNA transcripts at the single-molecule resolution. The subcellular localization of RNA molecules plays a crucial role in the compartmentalization-dependent regulation of genes within individual cells. Understanding the intracellular spatial distribution of RNA for a particular cell type thus not only improves the characterization of cell identity but also is of paramount importance in elucidating unique subcellular regulatory mechanisms specific to the cell type. However, current cell type annotation approaches of iST primarily utilize gene expression information while neglecting the spatial distribution of RNAs within cells. In this work, we introduce a semi-supervised graph contrastive learning method called Focus, the first method, to the best of our knowledge, that explicitly models RNAs subcellular distribution and community to improve cell type annotation. Focus first constructs gene neighborhood networks based on the subcellular colocalization relationship of RNA transcripts. Next, the subcellular graph of each cell can be augmented by adding important edges and nodes or removing trivial edges and nodes. Focus then aims to maximize the similarity between positive pairs from two augmented views of the same cell and minimize the similarity between negative pairs from different cells within a common batch. Guided by a limited amount of labeled data, Focus is capable of assigning cell type identities for the entire datasets at high accuracy. Extensive experiments demonstrate the effectiveness of Focus compared to existing state-of-the-art approaches across a range of spatial transcriptomics platforms and biological systems. Furthermore, Focus enjoys the advantages of revealing intricate cell type-specific subcellular spatial gene patterns and providing interpretable subcellular gene analysis, such as defining the gene importance score. Importantly, with the importance score, Focus identifies genes harboring strong relevance to cell type-specific pathways, indicating its potential in uncovering novel regulatory programs across numerous biological systems. Focus is freely accessible at https://github.com/OmicsML/focus.

bioinformatics↗

bioRxiv2024

Coronavirus Nucleocapsid Protein Enhances the binding of p-PKCα to RACK1: Implications for Inhibition of Nucleocytoplasmic Trafficking and Suppression of the Innate Immune Response

The hallmark of coronavirus infection lies in its ability to evade host immune defenses, a process intricately linked to the nuclear entry of transcription factors crucial for initiating the expression of antiviral genes. Central to this evasion strategy is the manipulation of the nucleocytoplasmic trafficking system, which serves as an effective target for the virus to modulate the expression of immune response-related genes. In this investigation, we discovered that infection with the infectious bronchitis virus (IBV) dynamically impedes the nuclear translocation of several transcription factors such as IRF3, STAT1, STAT2, NF-{kappa}B p65, and the p38 mitogen-activated protein kinase (MAPK), leading to compromised transcriptional induction of key antiviral genes such as IFN{beta}, IFITM3, and IL-8. Further examination revealed that during the infection process, components of the nuclear pore complex (NPC), particularly FG-Nups (such as NUP62, NUP153, NUP42, and TPR), undergo cytosolic dispersion from the nuclear envelope; NUP62 undergoes phosphorylation, and NUP42 exhibits a mobility shift in size. These observations suggest a disruption in nucleocytoplasmic trafficking. Screening efforts identified the IBV nucleocapsid protein (N) as the agent responsible for the cytoplasmic distribution of FG-Nups, subsequently hindering the nuclear entry of transcription factors and suppressing the expression of antiviral genes. Interactome analysis further revealed that the IBV N protein interacts with the scaffold protein RACK1, facilitating the recruitment of activated protein kinase C alpha (p-PKC) to RACK1 and relocating the RACK1-PKC complex to the cytoplasm. These observations are conserved across pan-coronaviruses N proteins. Concurrently, the presence of both RACK1 and PKC/{beta} proved essential for the phosphorylation and cytoplasmic dispersion of NUP62, the suppression of antiviral cytokine expression, and efficient virus replication. These findings unveil a novel, highly effective, and evolutionarily conserved mechanism. Author summaryCoronaviruses employ diverse strategies to suppress the host innate immune defense. In this study, we uncovered a novel and highly effective strategy utilized by pan-coronaviruses to inhibit the innate immune response. Specifically, we found that the coronavirus N protein facilitates the binding of p-PKC to RACK1, leading to the phosphorylation of NUP62 and the cytoplasmic redistribution of multiple FG-Nups. This phenomenon is accompanied by the disruption of nuclear translocation of several innate immune response-related transcription factors and suppression of antiviral/pro-inflammatory genes expression. Our research represents the first elucidation of how the N protein targets and impairs NPC function through the promotion of RACK1-PKC interaction and NUP62 phosphorylation/disassembly. This discovery unveils a novel mechanism employed by pan-coronaviruses to counteract the host immune response.

microbiology↗