Biology subjects

Weng, L.

Publications and source records attributed to Weng, L..

12 recordsLinked to original sources

bioRxiv2026

Microglial lipid signaling drives glioblastoma invasion and represents a therapeutic vulnerability

Glioblastoma (GBM) is characterized by diffuse infiltration into the surrounding brain, which precludes complete surgical resection, the strongest determinant of patient survival. The mechanisms that drive this invasive growth remain incompletely understood. Here we identify a lipid-mediated paracrine signaling axis through which microglia, the resident macrophages of the brain, promote glioma invasion. Integrating single-cell transcriptomics, spatial lipidomics, and functional perturbation across mouse models and human GBM samples, we show that invading tumor cells engage and reprogram microglia via CSF1R-PI3K signaling. This induces a metabolic switch in microglia, leading to the secretion of bioactive lipids, including lysophosphatidylcholines (LPCs) and lysophosphatidic acids (LPAs), which act as pro-invasive cues across GBM subtypes through distinct downstream pathways. Disruption of the microglia-GBM axis, either by inhibiting CSF1R signaling or by blocking lipid mobilization, reduces lipid secretion and suppresses tumor invasion. Targeting downstream LPA-LPAR or YAP/TAZ signaling further constrains invasion in a context-dependent manner. Together, these findings define a lipid-driven signaling circuit that links the tumor microenvironment to glioma invasion and identify therapeutic strategies to limit tumor infiltration and improve surgical resectability.

cancer biology↗

bioRxiv2026

Heterozygote Advantage of a Single-Copy SNAP18 Truncation Allele Enables Dominant SCN Resistance and Yield Preservation in Soybean

Soybean cyst nematode (SCN, Heterodera glycines) is the most devastating pathogen threatening global soybean production. The long-term over-reliance on rhg1-a/b resistance has led to the rapid emergence of virulent SCN populations, creating an urgent demand for novel genetic resources to safeguard soybean yield. Here, we identified a rare gain-of-function allele, SNAP18lmm3, via map-based cloning of the lesion-mimic mutant (lmm3) in the SCN-susceptible Williams 82 (rhg1-c) background. This allele encodes a 24-amino-acid C-terminal truncation of SNAP18 and exhibits an unusual mixed dominance genetic profile: the autoimmune-related leaf lesion phenotype is recessive, whereas SCN resistance is dominant. Homozygous lmm3 plants suffer significant yield losses due to spontaneous cell death, but heterozygous (LMM3+/-) plants maintain normal growth, agronomic performance, and seed yield comparable to wild-type Williams 82 in SCN-free field environments. Critically, under artificial SCN inoculation in both field trials and controlled environments, LMM3+/- heterozygotes confer robust resistance, achieving a [~]4-fold yield advantage over SCN-infested Williams 82 and a [~]44% reduction in cyst formation relative to Williams 82. This resistance profile aligns with the broad-spectrum activity of the lmm3 homozygous mutant, supported by the conserved resistance mechanism of SNAP18lmm3. Transgenic expression of SNAP18lmm3 driven by the nematode-responsive HIP promoter (HIPpro) potently arrested nematode development at the J2 stage in transgenic hairy roots, as evidenced by the drastically reduced proportion of advanced-stage nematodes. Our findings establish SNAP18lmm3 as a potent, "plug-and-play" genetic resource that circumvents the limitations of traditional dosage-dependent resistance loci. This allele enables the development of high-yielding, SCN-resistant soybean cultivars through marker-assisted selection for the heterozygous state or precision genome editing, providing a practical solution for sustainable SCN management.

plant biology↗

bioRxiv2026

SNAP18 Truncation Triggers a Competitive Binding Switch Between NSF and ATG8f, Balancing Vesicular Trafficking and Autophagy for SCN Resistance in Soybean

Soybean cyst nematode (SCN, Heterodera glycines) poses the most devastating biotic threat to global soybean production. Traditional SCN resistance mediated by the Rhg1 locus predominantly relies on gene copy number expansion and elevated -SNAP protein dosage. Here, we report a novel resistance mechanism in a single-copy rhg1-c background, wherein a C-terminal 24-amino-acid truncation of SNAP18 (designated SNAP18lmm3) triggers a functional switch from vesicular trafficking to autophagic degradation. Biochemical assays and structural modeling demonstrate that this truncation severely impairs the canonical interaction between SNAP18 and N-ethylmaleimide-sensitive factor (NSF), disrupting SNARE complex recycling and inducing localized cytotoxicity. Concomitantly, the truncated SNAP18lmm3 exposes a binding interface for the autophagy-related protein ATG8f, routing the aberrant protein for selective autophagic clearance. This constitutively activated autophagic flux acts as a systemic detoxification system, preventing widespread cell death and ensuring normal plant growth under non-stressed conditions. Upon SCN infection, SNAP18lmm3 specifically hyper-accumulates within nematode-induced syncytia. This accumulation reaches levels fourfold higher than in adjacent cells, which overwhelms the local autophagic capacity and triggering targeted cell death that arrests nematode development. By elucidating this competitive molecular switch between NSF and ATG8f binding, our study establishes a "self-degrading toxin" model that resolves the inherent trade-off between plant growth and immunity. This work provides a new theoretical framework for engineering cellular homeostasis to enhance durable crop resistance against parasitic nematodes.

plant biology↗

bioRxiv2026

Deep models of protein evolution in time generate realistic evolutionary trajectories and functional proteins

Models of protein evolution are foundational to biology, underpinning essential techniques such as phylogenetic tree inference, ancestral sequence reconstruction, multiple sequence alignment, variant effect prediction, and protein design. Historically, for computational tractability, these models have relied on the simplifying - but biologically unrealistic - assumption that sites in a given protein evolve independently of each other. A crucial test of any evolutionary model is its ability to simulate realistic evolutionary trajectories, but the independent-sites assumption leads to simulations that poorly reflect the complexity of natural protein evolution. Here we introduce PEINT (Protein Evolution IN Time), a flexible and generalizable deep learning framework for modeling how the entire protein sequence evolves over time while incorporating complex interactions between sites. This framework enables learning realistic patterns of constrained evolutionary transitions directly from millions of protein sequences spanning diverse fold families. Furthermore, unlike classical models that require pre-aligned sequences, PEINT learns indel dynamics directly from raw, unaligned sequences, thereby eliminating potential biases from alignment errors that can lead to incorrect inference of evolutionary patterns. By capturing higher-order epistatic interactions and modeling insertion-deletion processes that classical models typically ignore, PEINT accurately reproduces key signatures of natural evolution, including conservation patterns and family-specific dynamics. When simulating evolution along phylogenetic trees, PEINT generates highly novel sequences that preserve protein function, which we validate through experimental characterization of simulated carbonic anhydrase variants that retain enzymatic activity. PEINT thus enables realistic simulation of protein evolution that explores new sequence space while respecting structural and functional constraints. This evolution-informed generative modeling framework offers a powerful new tool for advancing both phylogenetic inference and protein engineering.

evolutionary biology↗

bioRxiv2025

Distinct tumor immune microenvironmental (TIME) landscapes drive divergent immunotherapy responses in glioblastoma

BackgroundImmunotherapies have improved outcomes in many cancers but show limited efficacy in glioblastoma (GBM). This study aimed to determine whether immunotherapy could be tailored to GBM by functional subtyping of vascular-immune landscapes. MethodsWe employed single-cell RNA sequencing, multiplex immunohistochemistry to characterize three distinct TIME subtypes in human and murine GBMs. We evaluated responses to combination of anti-angiogenic immunomodulating therapies (CD40 Ag, anti-PDL1, PI3K{gamma}/{delta} inhibition) in orthotopic syngeneic GBM mouse models. ResultsWe identified three distinct functional TIME subtypes with unique vascular-immune landscapes in human and murine GBM: TIME-low (immune-low/deserted, leaky vasculature), TIME-med (intermediate immune-infiltration, angiogenic), and TIME-high (heavily infiltrated with immunosuppressive myeloid cells and dysfunctional T cells). Representative mouse models of TIME-GBMs responded in subtype specific ways to anti-angiogenic immunomodulating therapies. TIME-low GBMs enhanced T-cell activity but relapsed due to emerging myeloid immunosuppression, concomitant with mesenchymal transition. TIME-med displayed the most immune-activated, yet angiogenic phenotype, and showed overall good responses to various anti-angiogenic immunomodulating therapies. TIME-high GBMs were mostly non-responsive but improved when the myeloid-cell PI3K{gamma} was targeted. However, CD40 agonist treatment, expected to enhance APC function, unexpectedly worsened survival by promoting angiogenesis and heightening immunosuppression, leading to dysfunctional T cells and reduced NK cell recruitment, and subsequent enhanced tumor propagation. ConclusionsOur study reveals three GBM TIME subtypes with distinct vascular-immune landscapes that require tailored therapies. TIME-med tumors are predicted to respond best to immunotherapies, TIME-low tumors show transient effects with anti-angiogenic immunomodulating therapies, while TIME-high tumors, due to their profound immunosuppression, can even have worse outcomes. Key pointsO_LIThree TIME subtypes were identified in GBM with distinct vascular-immune landscapes C_LIO_LITIME subtypes show divergent immunotherapy responses C_LIO_LITIME classification supports personalized treatment strategy for GBM immunotherapy C_LI Importance of the StudyThis study advances glioblastoma immunotherapy by providing the first comprehensive single-cell characterization of TIME subtypes, moving beyond bulk RNA-sequencing to reveal detailed functional states of immune cells. We establish clinically relevant murine models that recapitulate human TIME subtypes, enabling preclinical testing of TIME-targeted therapies. Our findings identify TIME-low GBM as immune deserted and TIME-med tumors as the most immunotherapy-responsive subtype that should be prioritized for clinical selection. We found that high immune infiltration correlates with non-responsiveness and even unexpected detrimental effects with CD40 agonist treatment in TIME-high tumors--critical information given ongoing clinical trials. Identifying distinct immunosuppressive mechanisms across TIME subtypes and differential treatment responses provides a framework for personalized immunotherapy selection. The immediate translational impact of this work highlights the importance of TIME classification for treatment stratification and the urgent need to consider TIME status in clinical trial design, potentially explaining variable patient responses in previous GBM immunotherapy trials.

cancer biology↗

bioRxiv2025

Single-nucleus transcriptome analyses uncover a dynamic transcriptional landscape of soybean roots in response to soybean cyst nematode infection

Soybean cyst nematode (SCN, Heterodera glycines) causes substantial yield losses by inducing the formation of specialized feeding structure called syncytia, which arise from extensive reprogramming of host root cells. Despite their pivotal role in SCN parasitism, the molecular mechanisms governing syncytium formation and function remain poorly understood, largely due to the technique challenges in precisely isolating these rare cell types. Here, we employed single-nucleus RNA sequencing (snRNA-seq) to generate a comprehensive, high-resolution transcriptomic atlas of SCN-infected soybean roots, comparing two resistant cultivars (PI 88788 and Forrest) with a susceptible cultivar (Williams 82) across multiple infection stages. By leveraging the well-characterized syncytium marker GmSNAP18, we successfully identified and transcriptionally profiled syncytial cells, and validate the spatial expression of known SCN-resistant genes. Our analyses revealed strong induction of resistance-associated genes specifically enriched in syncytia from resistant cultivars. Functional validation further demonstrated that overexpression of three novel candidate genes significantly suppressed SCN development. Pseudotime trajectory analyses traced syncytium development back to procambial cell origins, uncovering distinct, cultivar-specific developmental pathways. Collectively, this work provides a foundational single cell transcriptomic resource, advances our understanding of syncytial biology and SCN resistance mechanisms, and identifies promising molecular targets for engineering nematode-resistant soybean varieties.

plant biology↗

bioRxiv2024

Inter-Kingdom Interactions and Environmental Influences on the Oral Microbiome in Severe Early Childhood Caries

Dental caries arise from intricate interactions among oral microorganisms, impacting ecological stability and disease progression. This study delves into the bacterial-fungal dynamics in severe early childhood caries (S-ECC) among 61 children aged 3-4 years with complete deciduous dentition. We evaluated environmental factors such as saliva pH, buffering capacity, and trace elements (iron, fluoride). We examined the performance of 16S rRNA V1-V9 regions gene and internal transcribed spacer (ITS) primers for bacteria and fungi from plaque and saliva to characterize community compositions and diversity. Saliva pH and buffering capacity were also measured. Findings revealed significant shifts in bacterial diversity in S-ECC saliva samples, marked by decreased diversity and elevated abundance of cariogenic species, particularly Streptococcus mutans. Candida albicans was notably more prevalent in the S-ECC group, implicating its potential role in pathogenesis. Iron and fluoride concentrations showed no significant correlation with microbial community structure. Network analyses uncovered complex intra- and inter-kingdom interactions, underscoring cooperative and competitive dynamics. S-ECC children exhibited higher abundances of bacteria (Streptococcus mutans, Granulicatella, Actinomyces) and fungi (Candida albicans), with specific microbial taxa associated with reduced saliva pH. ImportanceThis study illuminates the intricate relationship between bacteria and fungi within the oral microbial community of children, specifically highlighting differences between those with severe early childhood caries (S-ECC) and those without caries. Through an extensive analysis of the microbial composition in both saliva and dental plaque, we identified a significant increase in the abundance of specific bacterial taxa (e.g., S. mutans, Granulicatella, Actinomyces) and fungal species (e.g., C. albicans) in the oral cavities of children with S-ECC. This finding underscores the potential role of these microorganisms in the development of caries. Contrary to previous studies that emphasize the importance of iron and fluoride in oral health, our research found no significant correlation between the concentrations of these elements and the composition of oral microbial communities. This result challenges conventional understanding and opens new avenues for future research. Additionally, we discovered an association between certain microbial species and reduced salivary pH, offering fresh insights into the relationship between the oral microenvironment and caries development. The implications of our findings are substantial for the development of prevention and intervention strategies targeting childhood caries. They also underscore the critical need for a deeper exploration of oral microbial interactions and their environmental influences.

microbiology↗

bioRxiv2024

SeuratExtend: Streamlining Single-Cell RNA-Seq Analysis Through an Integrated and Intuitive Framework

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity, but the rapid expansion of analytical tools has proven to be both a blessing and a curse, presenting researchers with significant challenges. Here, we present SeuratExtend, a comprehensive R package built upon the widely adopted Seurat framework, which streamlines scRNA-seq data analysis by integrating essential tools and databases. SeuratExtend offers a user-friendly and intuitive interface for performing a wide range of analyses, including functional enrichment, trajectory inference, gene regulatory network reconstruction, and denoising. The package seamlessly integrates multiple databases, such as Gene Ontology and Reactome, and incorporates popular Python tools like scVelo, Palantir, and SCENIC through a unified R interface. SeuratExtend enhances data visualization with optimized plotting functions and carefully curated color schemes, ensuring both aesthetic appeal and scientific rigor. We demonstrate SeuratExtends performance through case studies investigating tumor-associated high-endothelial venules and autoinflammatory diseases, and showcase its novel applications in pathway-Level analysis and cluster annotation. SeuratExtend empowers researchers to harness the full potential of scRNA-seq data, making complex analyses accessible to a wider audience. The package, along with comprehensive documentation and tutorials, is freely available at GitHub, providing a valuable resource for the single-cell genomics community. Practitioner PointsO_LISeuratExtend streamlines scRNA-seq workflows by integrating R and Python tools, multiple databases (e.g., GO, Reactome), and comprehensive functional analysis capabilities within the Seurat framework, enabling efficient, multi-faceted analysis in a single environment. C_LIO_LIAdvanced visualization features, including optimized plotting functions and professional color schemes, enhance the clarity and impact of scRNA-seq data presentation. C_LIO_LIA novel clustering approach using pathway enrichment score-cell matrices offers new insights into cellular heterogeneity and functional characteristics, complementing traditional gene expression-based analyses. C_LI

bioinformatics↗

bioRxiv2024

Single-cell profiling reveals the intratumor heterogeneity and immunosuppressive microenvironment in cervical adenocarcinoma

BackgroundCervical adenocarcinoma (ADC) is more aggressive compared to other types of cervical cancer (CC), such as squamous cell carcinoma (SCC). The tumor immune microenvironment (TIME) and tumor heterogeneity are recognized as pivotal factors in cancer progression and therapy. However, the disparities in TIME and heterogeneity between ADC and SCC are poorly understood. MethodsWe performed single-cell RNA sequencing on 11 samples of ADC tumor tissues, with other 4 SCC samples served as controls. The immunochemistry and multiplexed immunofluorescence were conducted to validate our findings. ResultsCompared to SCC, ADC exhibited unique enrichments in several sub-clusters of epithelial cells with elevated stemness and hyper-malignant features, including the Epi_10_CYSTM1 cluster. ADC displayed a highly immunosuppressive environment characterized by the enrichment of regulatory T cells (Tregs) and tumor-promoting neutrophils. The Epi_10_CYSTM1 cluster recruits Tregs via ALCAM-CD6 signaling, while Tregs reciprocally induce stemness in the Epi_10_CYSTM1 cluster through TGF{beta} signaling. Importantly, our study revealed that the Epi_10_CYSTM1 cluster could serve as a valuable predictor of lymph node metastasis for CC patients. ConclusionsThis study highlights the significance of ADC-specific cell clusters in establishing a highly immunosuppressive microenvironment, ultimately contributing to the heightened aggressiveness and poorer prognosis of ADC compared to SCC.

cancer biology↗

bioRxiv2021

CAR T cell therapy drives endogenous locoregional T cell dynamics in a responding patient with glioblastoma

CAR T cell therapy has transformed clinical care and management of patients with certain hematological cancers. However, it remains unclear whether the success of CAR T cell therapy relies solely on CAR T cell engagement with tumor antigen, or if it also requires the stimulation of an individual patients endogenous T cell response. Here, we performed combined analysis of longitudinal, single cell RNA and T cell receptor sequencing on glioblastoma tumors, peripheral blood (PB), and cerebrospinal fluid (CSF) from a patient with recurrent multifocal glioblastoma that underwent a remarkable response followed by recurrence on IL13RA2-targeted CAR T cell therapy (Brown et al. 2016). Single cell analysis of a tumor resected prior to CAR T cell therapy revealed the existence of an inflamed tumor microenvironment including a CD8+ cytotoxic, clonally expanded and antigen specific T cell population that disappeared in the recurrent setting. Longitudinal tracking of T cell receptors uncovered distinct T cell dynamics classes in the CSF during CAR T cell therapy. These included T cell clones with transient dynamics, representing intraventricular CAR T cell delivery and endogenous T cell recruitment from the PB into the CSF; and a group of T cells in the cerebrospinal fluid, that tracked with clonally expanded tumor resident T cells and whose dynamics contracted concomitantly with tumor volume. Our results suggest the existence of an endogenous T cell population that was invigorated by intraventricular CAR T cell infusions, and combined with the therapy to produce a complete response.

immunology↗

bioRxiv2021

The role of antifreeze glycopeptides (AFGP) and polyvinyl alcohol/polyglycerol (X/Z-1000) cocktails as ice modulators during partial freezing of rat livers.

The current liver organ shortage has pushed the field of liver transplantation to develop new methods to prolong the preservation time of livers from the current clinical standard of static cold storage. Our approach, termed partial freezing, aims to induce a thermodynamically stable frozen state at deeper storage temperatures (-10{degrees}C to -15{degrees}C) than can be achieved with supercooling, while simultaneously maintaining a sufficient unfrozen fraction to limit dehydration and ice damage. This research first demonstrated that partially frozen glycerol treated rat livers were functionally similar after thawing from either -10 or -15{degrees}C with respect to subnormothermic machine perfusion metrics and histology. Next, we assessed the effect of adding either of two ice modulators, antifreeze glycoprotein (AFGP) and a polyvinyl alcohol/polyglycerol combination (X/Z-1000), on the viability and structural integrity of partially frozen rat livers compared to glycerol-only control livers. Results showed that AFGP livers had high levels of ATP and the least edema but suffered from significant endothelial cell damage. X/Z-1000 livers had the highest levels of ATP and energy charge (EC) but also demonstrated endothelial damage and post-thaw edema. Glycerol-only control livers exhibited the least DNA damage on Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining but also had the lowest levels of ATP and EC. Further research is necessary to optimize the ideal ice modulator cocktail for our partial-freezing protocol. Modifications to cryoprotective agent (CPA) combinations, as well as improvements to machine perfusion CPA loading and unloading, can help improve the viability of these partially frozen organs.

physiology↗

bioRxiv2021

Conversion of cancer-associated fibroblasts from pro- to antitumor improves the sensitivity of pancreatic cancer to chemotherapeutics

Previous therapeutic attempts to deplete cancer-associated fibroblasts (CAFs) or inhibit their proliferation in pancreatic ductal adenocarcinoma (PDAC) were not successful in mice or patients. Thus, CAFs may be tumor suppressive or heterogeneous, with distinct cancer-restraining and -promoting CAFs (rCAFs and pCAFs, respectively). Here, we show that induced expression of the glycosylphosphatidylinositol-anchored protein Meflin, a rCAF-specific marker, in CAFs by genetic and pharmacological approaches improved the chemosensitivity of mouse PDAC. A chemical library screen identified Am80, a synthetic, non-natural retinoid, as a reagent that effectively induced Meflin expression in CAFs. Am80 administration improved the sensitivity of PDAC to chemotherapeutics, accompanied by increases in tumor vessel area and intratumoral drug delivery. Mechanistically, Meflin was involved in the suppression of tissue stiffening by interacting with lysyl oxidase to inhibit its collagen crosslinking activity. These data suggested that modulation of CAF heterogeneity may represent a strategy for PDAC treatment.

cancer biology↗