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Hui, L.

Publications and source records attributed to Hui, L..

16 recordsLinked to original sources

Single-cell RNA-seq of amniotic fluid provides unique insight into fetal development

Background: Human fetal development is difficult to study due to ethical and practical constraints on the collection and use of human fetal tissue. Amniotic fluid (AF) is routinely collected during clinical amniocentesis and contains live fetal cells shed from developing tissues. Thus, we use single-cell RNA-sequencing (scRNA-seq) to build the first cell atlas of amniotic fluid from healthy second-trimester fetuses. Methods: scRNA-seq was performed on AF samples collected from seven euploid, structurally normal pregnancies at 15-25 weeks' gestation, all of which resulted in live births of healthy infants. Mapping to a modified transcriptome was used to help reduce counts sparsity. Supervised cell type annotation, unsupervised clustering and marker gene analyses were used to determine the cell types present in AF. Gestational age-related differences between earlier (<=19 weeks) and later (>= weeks) gestation samples were examined using differential gene expression (DGE) and differential proportion analyses. Results: Fetal skin cells were the most abundant cell type in AF, followed by myeloid and lymphoid cell types. We observed significant gestational age-related shifts in cell type composition, with an increased proportion of lung epithelium cells in later-age samples, coinciding with the canalicular phase of lung development. DGE analysis of fetal skin cells between earlier and later gestation revealed numerous gene expression changes that recapitulated known developmental processes across the second trimester. These were also enriched in an independent AF dataset from pregnancies with diverse fetal pathologies. Our dataset provides an annotated atlas of 11,414 healthy fetal human cells, permitting further study into normal second trimester development. We provide an integrated fetal cell atlas of 45,048 cells combining previous data with our healthy samples. Conclusions: This study applied novel analytical approaches to demonstrate the utility of scRNA-seq in characterising AF and its capacity to capture a diverse range of viable fetal cell types. Our results suggest that changes in AF cellular composition mirror organ development, underscoring the potential of AF scRNA-seq to deepen our understanding of normal and pathological fetal biology.

bioinformatics↗

Same-section spatial metabolo-transcriptomics using Stereo-meta-seq reveals DHA-driven kidney maturation

A central unresolved question in developmental biology is whether local metabolites merely accompany, or actively instruct, tissue maturation. Addressing this question requires direct spatial coupling of metabolic states with genome-wide transcriptional programs in situ at high spatial resolution, which existing approaches do not readily achieve. Here, we introduce Stereo-meta-seq, a workflow that integrates quantitative MALDI-MSI with Stereo-seq spatial transcriptomics within a single tissue section. A conductive adapter was designed to overcome the electrical incompatibility of non-conductive Stereo-seq chips with vacuum MALDI platforms, improving efficiency of MSI detection that preserves RNA integrity. MALDI laser-ablation marks are retained in downstream Stereo-seq data and serve as intrinsic fiducials for direct co-registration at 10 m or 20 m resolution, enabling fine grained spatial metabolite-transcript integration. Applying Stereo-meta-seq to human kidney development, we uncover selective enrichment of docosahexaenoic acid (DHA) in maturing proximal tubules. Functional studies in human kidney organoids demonstrate that DHA activates PPAR-and HNF4-driven transcriptional programs and promotes proximal tubule maturation in vitro and after transplantation in vivo. These findings identify lipid metabolism as an instructive regulator of human nephrogenesis and establish Stereo-meta-seq as a practical platform for dissecting metabolite-gene coupling and tissue heterogeneity in situ.

Cell Biology↗

SPCoral: diagonal integration of spatial multi-omics across diverse modalities and technologies

Spatial multi-omics is indispensable for decoding the comprehensive molecular landscape of biological systems. However, the integration of multi-omics remains largely unresolved due to inherent disparities in molecular features, spatial morphology, and resolution. Here we developed SPCoral for diagonal integration of spatial multiomics across adjacent slices. SPCoral extracts spatial covariation patterns via graph attention networks, followed by the use of optimal transport to identify high-confidence anchors in an unsupervised, feature-independent manner. SPCoral utilizes a crossmodality attention network to enable seamless cross-resolution feature integration alongside robust cross-omics prediction. Comprehensive benchmarking demonstrates SPCorals superior performance across different technologies, modalities and varied resolutions. The integrated multi-omics representation further improves spatial domain identification, effectively augments experimental data, enables cross-modal association analysis, and facilitates cell-cell communication. SPCoral exhibits good scalability with data size, reveals biological insights that are not attainable using a single modality. In summary, SPCoral offers a powerful framework for spatial multi-omics integration across various technologies and biological scenarios.

bioinformatics↗

Glycemia Shift Pancreatic Islets Rhythmicity via δ-α Cell in vivo, Impairment in Diabetes

Blood glucose homeostasis relies on the well-coordinated rhythmic activity of millions of islets throughout the pancreas. Islet rhythmicity is triggered by glucose elevation and mediated by paracrine interactions. However, the dynamics of islet population rhythmicity in healthy and diabetic pancreases in vivo remain poorly understood. Using simultaneous multi-islet Ca2+ imaging (20-100 islets per experiment) in both live mice and pancreatic tissue slices, we systematically studied how glycemia fluctuations and intra-islet paracrine signaling collectively shape the islet rhythmicity. In this study, we report that a transition from Hyperglycemia to Euglycemia induces a coordinated shift from slow to fast islet Ca2+ oscillations (HESF) in vivo. HESF is conserved in pancreatic tissue slices and isolated islets, however, not dispersed single cells in vitro, suggesting a mechanistic link with paracrine interactions. We found HESF arises from -cell activation, which is inhibited by {delta} cells upon glucose elevation. The autonomous islets mostly differ in phase and period at high glucose level. Diabetic mice with disrupted glycemic stability lost HESF both in vivo and in vitro. Interestingly, HESF is preserved in {beta}-cell knockout Gcgr transgenetic mice, both in vivo and in vitro, suggesting HESFs dependence on Glp1r. Indeed, HESF was restored in semaglutide-treated diabetic mice with stabilized glycemic stability. These findings offer a comprehensive understanding of how {delta} and cells influence islet rhythmicity and precisely maintain the stability of blood glucose.

physiology↗

First-trimester exposure to anti-cytomegalovirus medications: a study of the effects of valaciclovir, letermovir and maribavir on early placental development

Congenital cytomegalovirus (CMV) infection is the leading preventable cause of childhood disability, including sensorineural hearing loss and cerebral palsy in high-income countries. Early maternal treatment with valaciclovir has been shown to reduce fetal infection. However, newer, more potent anti-CMV medications such as letermovir and maribavir are not routinely used in pregnancy due to limited safety data. This study aimed to assess the effect of aciclovir (the active metabolite of valaciclovir), letermovir, and maribavir on cell viability, functionality, and key cell signalling pathways in first-trimester human placental tissue. First-trimester placental tissue was obtained from individuals undergoing surgical abortion for psychosocial indications at 9-13 weeks of gestation. The effect of anti-CMV medications on primary cytotrophoblast cell survival was measured using a standard cell viability assay. The effects of anti-CMV medication exposure on Wnt and epithelial-to-mesenchymal transition (EMT) signalling pathways were evaluated in placental explant cultures. Their impact on cellular proliferation and migration was assessed using placental outgrowth cultures. Exposure to physiological or supraphysiological levels of aciclovir, letermovir, or maribavir for 48 hours did not significantly alter cytotrophoblast cell viability compared to vehicle-treated controls. Aciclovir did not significantly impact Wnt and EMT signalling gene expression in first-trimester placental explants; however, letermovir and maribavir induced significant gene dysregulation. None of the three anti-CMV medications altered first-trimester trophoblast proliferation or migration. These results provide reassuring data supporting the safety of maternal valaciclovir therapy in the first trimester. They may also inform the selection of newer anti-CMV medications for future clinical trials for use in pregnancy.

developmental biology↗

Amniotic fluid extracellular vesicle properties evolve with gestational age and reflect fetal development

Amniotic fluid (AF) is a valuable source of extracellular vesicles (EVs) derived from the fetoplacental unit. Preclinical and clinical studies have highlighted promising applications of AF-EVs and their role in cellular communication, yet our understanding of AF-EV physiology is limited. This study aimed to examine the physiological importance of AF-EVs in fetal development from the second trimester to term gestation. We obtained AF samples from routine second-trimester amniocentesis and prelabour Caesarean section at term. We isolated EVs using a combination of differential centrifugation, filtration, and ultracentrifugation and characterised them using nanoparticle tracking analysis, cryoelectron microscopy, and Western blotting. The differential EV proteome was analysed using label-free proteomics. We assessed the second trimester and term AF-EV properties through an enrichment analysis. The EV size and protein enrichment difference revealed a gestational-age-dependent variation in the predominant EV subtype. Second-trimester-derived EVs were enriched in ectosomes, while term EVs contained a significant proportion of exosomes. We identified several morphologies of AF-EVs, including unilamellar, multilamellar, multicompartmental and granular-centred EVs, across gestations. Proteomics analysis of AF-EVs identified 4137 proteins with high confidence, of which 1099 exhibited significant differential expression between the two groups. Second-trimester-enriched AF-EV proteins represented molecule assembly processes, metabolism and organogenesis. At term, AF-EV proteins corresponded to impending newborn functions such as immunity and digestion. In conclusion, we provide compelling evidence that EV biogenesis and secretion in the fetoplacental unit undergo significant alterations across gestation, revealing a complex and dynamic physiology and intercellular communication that adapts to the needs of the developing fetus. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/649052v1_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@3358c4org.highwire.dtl.DTLVardef@108ec96org.highwire.dtl.DTLVardef@e49b91org.highwire.dtl.DTLVardef@a1888b_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO This figure summarises the studys main findings, including the shift in the predominant EV subtype, the different organs and biofluids represented by the enriched proteins at each gestation, and the main biological pathways. C_FIG

developmental biology↗

Molecular insights into early malignant transition of hepatocellular carcinoma

The molecular continuum of premalignant-to-malignant transition remains elusive in carcinogenesis, primarily due to the difficulty in sampling transitional lesions. Here, we present comprehensive genomic and immunological profiling of 21 very early hepatocellular carcinomas (veHCCs) arising within 17 cancer-prone DNs. Surprisingly, 82% of cancer-prone DNs harbored TERT alterations, suggesting a predisposing rather than causative role in malignancy transition. A substantial increase in CNA burden, rather than SNV, was noted, indicating a role of chromosome instability in malignancy transition. Additionally, veHCC-originating DNs showed immune inactivity, not falling into the prevailing paradigm that HCCs develop in a context of chronic inflammation. 43% of veHCCs showed an inflamed phenotype with relatively mild CNA burden but already exhibited immune evasion features. Two major evolutionary scenarios were thus proposed: 1) CNA-dominant progression and 2) early immune evasion of those with mild CNA burden. Collectively, our findings illustrate previously unexplored molecular paradigms in HCC initiation, highlighting the therapeutic potential of immunotherapy for early intervention.

cancer biology↗

Malignant ascites enhance γδ T cell cytotoxicity towards ovarian cancer via modulating chemokines secretion from the cancer cells that recruits γδ T cells

Ovarian cancer patients usually develops peritoneal metastasis and malignant ascites in the advanced stages, which form immuno-suppressive tumor microenvironments that limit the efficacy of immuno-therapies. However, during our previous research trying to develop a {gamma}{delta} T cell-based cell therapy, we noticed that the malignant ascites may enhance the cytotoxicity of {gamma}{delta} T cells towards ovarian cancer cells. Herein, in this work we showed that the phenomenon is real and the low molecular weight components in the ascites act on the cancer to promote the killing by {gamma}{delta} T cells. Transcriptome analysis and in vitro experiments revealed that the malignant ascites induce the secretion of chemokines CXCL2 and CXCL8 by ovarian cancer cells, which recruits {gamma}{delta} T cells through the chemokine receptors CXCR1 and CXCR2, to enhance the cytotoxicity of {gamma}{delta} T cells. Metabolomics analysis discovered compounds that are responsible for the enhancement of {gamma}{delta} T cell cytotoxicity, one of which follows the aforementioned mechanism, while other compounds reflect undiscovered mechanisms. Overall, we presented the positive side of the malignant ascites in anti-tumor immunity, revealed the underlining mechanisms and at least partially interpreted the molecular basis. Our work thus provides new insights into the development of cell therapies for ovarian cancer.

immunology↗

Asymmetric subspecies-selection of an NLR-TF immune module and reconstruction of broad-spectrum disease resistance in rice

Artificial selection has greatly shaped crop agronomic traits; however, the mechanistic basis of immunity selection has remained elusive. This study identifies a new rice NLR XA48 and its downstream transcription factor OsVOZ1, which confer bacterial blight resistance. XA48 perceives an ancient pathogen effector, XopG, to activates effector-triggered immunity (ETI). The XA48-OsVOZ1 module has undergone subspecies-specific selection. Xa48 is retained in indica but functionally lost in japonica rice. OsVOZ1 has also diverged into two haplotypes, indica kept both OsVOZ1A/S alleles that match XA48; while japonica only inherited OsVOZ1A that greatly decreases yield when Xa48 is reintroduced into japonica, mechanistically explaining the Xa48 loss in japonica. We resurrected wild rice broad-spectrum resistance by stacking XA48-mediated ETI with XA21-mediated pattern-triggered immunity (PTI). Thus, our study reveals that the asymmetric selection of an NLR-TF module shapes both disease resistance and reproduction, and provides a paradigm for breeding crops by harnessing the immunity of wild relatives.

genetics↗

Exploring phenotype-related single-cells through attention-enhanced representation learning

The scope of atlas-level single-cell investigations reveals the pathogenesis and progression of various diseases. Accurate interpretation of phenotype-related single-cell data necessitates the pre-definition of single-cell subtypes and the identification of their abundance variations for downstream analysis. In this context, biases from batch correlation and the selection of clustering resolutions can significantly impact single-cell data analysis and result interpretation. To strengthen the associations across single cells in each sample and their clinical phenotype, and to enhance single-cell exploration by integrating cell and gene-level information. This study proposes a method to learn phenotype-related sample representations from single cells via the attention-based multiple instance learning (AMIL) mechanism. This approach incorporates gene expression profiles from each single cell for sample-level clinical phenotype prediction. By integrating deep learning interpretation methods and phenotype-specific single-cell attention weights across sample groups, this method highlights critical gene programs and cell subtypes that mostly contribute to the sample-level clinical phenotype, and facilitate mechanistic exploration. Using single-cell atlases from COVID-19 infected patients and age-related healthy human blood, we demonstrate that this method can accurately predict disease severity and age-related phenotypes. Additionally, variations in cellular attention reflect the underlying biological mechanisms associated with these phenotypes. This method proposes a supervised framework for single-cell data interpretation and can be further adapted for other atlas-level clinical phenotype analyses.

bioinformatics↗

Chromosome-level genome assembly of autotetraploid Selenicereus megalanthus and gaining genomic insights into the evolution of trait patterning in diploid and polyploid pitaya species

Yellow pitaya (Selenicereus megalanthus, 2n=4x=44) breeding remains severely hindered due to lacking a reference genome. Here we report yellow pitayas high-quality chromosome-level genome assembly and link the phenotypic trait with genomic data, based on Hi-C, ATAC, and RNA-seq data of specific tissues. We declared yellow pitaya as an autotetraploid with a 7.16 Gb genome size (harboring 27,246 high confidence genes) and majorly evolved from diploid ancestors, which remains unknown. Beyond generating the genome assembly, we explored the 3D chromatin organization which revealed insights into the genome, compartments A (648 and 519), compartments B (728 and 1064), topologically associated domains-TADs (3376 and 2031), and varying numbers of structural variations (SVs) in diploid and polyploid pitaya species, respectively. Overall, TAD boundaries were enriched with the motifs of AP2, WRKY18/60/75, MYB63/116, PHL2, and GATA8 in both pitaya species. By linking the open chromatin genomic structure to function, we identified the major changes in betalains biosynthesis pathway in diploid and polyploid pitaya. Moreover, the higher genetic expression of SmeADH1 [Chr11, Compartment A (135400000 - 135500000), genes inside the TAD region (135480000 - 135520000)], and lower expression of HuDOPA [Chr11, Compartment A (87100000 - 87200000), genes inside the TAD region (87160000-87200000)] acts as a key regulator of yellow and red color on the pericarp of polyploid and diploid pitaya, respectively. In addition, higher expression of HuCYP76AD1 genes in diploid pitaya and lower expression of SmeCYP76AD1 in polyploid pitaya potentially created the difference in the oxidase process that led to the production of betacyanin and betaxanthin, respectively. Furthermore, our results revealed not only the type of motifs that play a potential role in trait patterning but we also further uncovered that motif count in TAD-boundaries may impact the gene expression within the TAD regions of diploid and polyploid pitaya. Our valuable genomic resource and comparison of 3D euchromatin architecture of diploid and polyploid pitaya species will not only aid in the advancement of molecular breeding efforts but also offer insights into the organization of genomes, SVs, compartmentalization (A and B), and TADs, which have the potential to strengthen the idea of TADs-based trait improvement to achieve global food security.

plant biology↗

Evidence for impaired hippocampal circuitry in schizophrenia and its link to memory dysfunction

Pattern separation and pattern completion are opposing yet complementary components of mnemonic processing that heavily rely on the hippocampus. It has been shown that processing within the dentate gyrus (DG) subfield promotes pattern separation while operations within the CA3 subfield are important for pattern completion. Schizophrenia has been associated with anatomical and functional hippocampal abnormalities, including within the DG and CA3. We hypothesized that an impairment in hippocampal circuitry in individuals with first-episode schizophrenia leads to deficits in pattern separation (mnemonic discrimination) and pattern completion (recognition memory), that these deficits contribute to delusions, and that antipsychotic treatment improves circuit functioning. We measured behavioral and neural responses during the identification of new, repeated, and similar stimuli using high-resolution fMRI in 45 medication-free or minimally-treated patients with first-episode schizophrenia and 49 matched controls. We found recognition memory and pattern separation deficits in patients and a negative association between memory performance and the severity of delusions. Neural analyses revealed deficits in both univariate BOLD responses and multivariate patterns in the hippocampus during mnemonic discrimination in patients compared to controls. Importantly, by investigating the association between trial-level neural activity and behavior before and after treatment, we found that antipsychotics normalized DG activity during pattern separation and CA3 activity during pattern completion. Lastly, trial-level cortical responses during mnemonic discrimination predicted performance in patients at baseline, suggesting a compensatory role. This study provides new insight into the impact of schizophrenia and antipsychotic treatment on memory systems and uncovers systems-level contributions to pattern separation and pattern completion.

neuroscience↗

Windborne migration amplifies insect-mediated pollination services

Worldwide, hoverflies (Syrphidae: Diptera) provide crucial ecosystem services (ES) such as pollination and biological pest control. Although many hoverfly species exhibit migratory behavior, the spatiotemporal facets of these movement dynamics and their ES implications are poorly understood. In this study, we use long-term (16 yr) trapping records, trajectory analysis and intrinsic (i.e., isotope, genetic, pollen) markers to describe migration patterns of the hoverfly Episyrphus balteatus in China. Our work reveals long-range, windborne migration with spring migrants originating in northern China and exhibiting return migration during autumn. Given the substantial night-time dispersal of E. balteatus, this species possibly adopts a dual migration strategy. The extensive genetic mixing and high genetic diversity of E. balteatus populations underscore its adaptive capacity to environmental disturbances e.g., climate change. Pollen markers and molecular gut-analysis further illuminate how E. balteatus visits min. 1,012 flowering plant species (39 orders) over space and time. By thus delineating E. balteatus trans-regional movements and pollination networks, we advance our understanding of its migration ecology and facilitate the design of targeted strategies to conserve and enhance its ecosystem services.

ecology↗

A non-bactericidal cathelicidin provides prophylactic efficacy against bacterial infection by driving phagocyte influx

The roles of bactericidal cathelicidins against bacterial infection have been extensively studied. However, the anti-bacterial property and mechanism of action of non-bactericidal cathelicidins are rarely known. Herein, a novel naturally occurring cathelicidin (PopuCATH) from tree frog (Polypedates puerensis) didnt show any direct anti-bacterial activity in vitro. Intriguingly, intraperitoneal injection of PopuCATH before bacterial inoculation significantly reduced the bacterial load in tree frogs and mice, and reduced the inflammatory response induced by bacterial inoculation in mice. PopuCATH pretreatment also increased the survival rates of septic mice induced by a lethal dose of bacterial inoculation or cecal ligation and puncture (CLP). Intraperitoneal injection of PopuCATH significantly drove the leukocyte influx in both frogs and mice. In mice, PopuCATH rapidly drove neutrophil, monocyte/macrophage influx in mouse abdominal cavity and peripheral blood with a negligible impact on T and B lymphocytes, and neutrophils, monocytes/macrophages, but not T and B lymphocytes, were required for the preventive efficacy of PopuCATH. PopuCATH did not directly act as chemoattractant for phagocytes, but PopuCATH obviously drove phagocyte migration when it was cultured with macrophages. PopuCATH significantly elicited chemokine/cytokine production in macrophages through activating p38/ERK mitogen-activated protein kinases (MAPKs) and NF-{kappa}B p65. PopuCATH markedly enhanced neutrophil phagocytosis via promoting the release of neutrophil extracellular traps (NETs). Additionally, PopuCATH showed low side effects both in vitro and in vivo. Collectively, PopuCATH acts as a host-based immune defense regulator that provides prophylactic efficacy against bacterial infection without direct antimicrobial effects. Our findings reveal a non-bactericidal cathelicidin which possesses unique anti-bacterial action, and highlight the potential of PopuCATH to prevent bacterial infection.

immunology↗

RNA helicase DDX5 enables STAT1 mRNA translation and interferon signaling in hepatitis B virus replicating hepatocytes

ObjectiveRNA helicase DDX5 is downregulated during hepatitis B virus (HBV) replication, and poor prognosis HBV-related hepatocellular carcinoma (HCC). The objective of this study is to understand the significance of DDX5 downregulation during HBV infection and poor prognosis HCC, as it pertains to therapy of chronically HBV-infected patients with HCC. IFN- therapy is effective only for a subgroup of HBV-infected patients, for reasons not understood. Herein, we investigated a novel mechanism of STAT1 translational control, involving DDX5-mediated resolution of a G-quadruplex structure, located at the 5UTR of STAT1 mRNA, enabling STAT1 translation. Design and ResultsMolecular, pharmacologic, and biophysical assays were used together with cellular model of HBV replication, HCC cell lines, and HBV-related liver tumors. We observed, the protein level of DDX5 correlated with that of transcription factor STAT1. We show, DDX5 regulates STAT1 mRNA translation by resolving a G-quadruplex (rG4) RNA structure, proximal to the 5 end of STAT1 5UTR. We employed luciferase reporter assays comparing wild type (WT) vs. mutant (MT) rG4 sequence, rG4-stabilizing compounds, CRISPR/Cas9 editing of the rG4 sequence, and circular dichroism determination of rG4 structure. Ribonucleoprotein assays identified direct DDX5 binding to WT but not MT rG4. Importantly, liver cancer cell lines expressing low DDX5 exhibited reduced interferon response, while immunohistochemistry of HBV-related HCCs exhibiting absence of DDX5, also lacked STAT1. ConclusionDDX5 resolves a G-quadruplex structure in 5UTR of STAT1 mRNA, enabling STAT1 translation. DDX5 is a key regulator of the dynamic range of interferon response during innate immunity and adjuvant IFN- therapy.

cancer biology↗

Personalized anti-cancer drug combination prediction by an Integrated Multi-level Network

Anti-cancer drug combination is an effective solution to improve treatment efficacy and overcome resistance. Here we propose a network-based method (DComboNet) to prioritize the candidate drug combinations. The level one model is to predict generalized anti-cancer drug combination effectiveness and level two model is to predict personalized drug combinations. By integrating drugs, genes, pathways and their associations, DComboNet achieves better performance than previous methods, with high AUC value of around 0.8. The level two model performs better than level one model by introducing cancer sample specific transcriptome data into network construction. DComboNet is further applied on finding combinable drugs for sorafenib in hepatocellular cancer, and the results are verified with literatures and cell line experiments. More importantly, three potential mechanism modes of combinations were inferred based on network analysis. In summary, DComboNet is valuable for prioritizing drug combination and the network model may facilitate the understanding of the combination mechanisms.

bioinformatics↗