Biology subjects

Liu, G.

Publications and source records attributed to Liu, G..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Reproducibility of Scientific Claims in Drosophila Immunity: A Retrospective Analysis of 400 Publications

Drosophila immunity has been the focus of intense study and has impacted other research fields including innate immunity and agriculturally or epidemiologically relevant investigations of insect pests and vectors. Unsurprisingly for such a large body of work, some published results were later found to be irreplicable. Although some results have been contradicted in the literature, many have no published follow-up, either due to a lack of research or low motivation to publish negative or contradictory results. We have addressed this by performing a reproducibility project that analyses the conceptual replicability of claims from articles published on Drosophila immunity before 2011. To assess replicability, we extracted claims from 400 articles on the Drosophila immune response to bacteria and fungi and performed preliminary verification by comparing these claims to other published literature in the field. Using alternative approaches, we also experimentally tested some unchallenged claims, with no published follow-up. The intent of this analysis was to centralize evidence on insights and findings to improve clarity for scientists that may base research programs on these data. Although the aim of the ReproSci project is to assess the replicability of claims made in articles published in the field of Drosophila immunity, it is in no way an assessment of the scientific value of the research. All our data are published on a publicly available website associated with this article (https://ReproSci.epfl.ch/) that encourages community participation. This article provides a short summary of claims that were found to have contradictory evidence, which may help the community to assess past findings on Drosophila immunity and improve clarity going forward. Statistical analysis of this reproducibility study and metascience insights obtained from this approach are discussed in a companion article.

genetics↗

bioRxiv2025

Neural Timescale of Adolescents Major Depressive Disorder

Adolescent major depressive disorder (MDD) is characterized by heterogeneous symptomatology and complex neurodevelopmental underpinnings. Here, we investigated whether cortical intrinsic neural timescales (INT)--a measure of temporal stability in neural activity--are altered in adolescents with MDD and whether these alterations relate to clinical symptoms, suicidality, early-life adversity, and underlying neurobiological mechanisms. Using resting-state fMRI in adolescents with MDD and healthy controls (HCs), we found widespread reductions in INT in frontal, parietal, and sensorimotor regions, with a notable prolongation in the left temporoparietal junction. Disrupted timescales significantly impaired network modularity and clustering, and SVR-based machine learning revealed that altered INT patterns predicted individual depression and anxiety severity. INT abnormalities were further associated with suicidal ideation and childhood trauma, particularly emotional and physical neglect. Biophysical modeling linked INT variations to local recurrent excitation and external input strength, differing between HCs and MDD. Spatial correlations with PET-derived neurotransmitter receptor maps demonstrated that INT alterations colocalize with serotonergic, dopaminergic, and cholinergic systems. Transcriptomic enrichment analysis revealed associations with genes involved in mitochondrial function, synaptic signaling, and metabolic regulation. Together, these findings identify neural timescale disruption as a core pathophysiological feature of adolescent MDD, bridging macroscale dynamics with microcircuit and molecular architecture. INT may serve as a promising biomarker and mechanistic target for precision psychiatry in youth depression.

neuroscience↗

bioRxiv2025

Smartphone-integrated RPA-CRISPR-Cas12a Detection System with Microneedle Sampling for Point-of-Care Diagnosis of Potato Late Blight in Early Stage

Potato late blight, caused by the oomycete pathogen Phytophthora infestans, is one of the most devastating diseases affecting potato crops in the history. Although conventional detection methods of plant diseases such as PCR and LAMP are highly sensitive and specific, they rely on bulky and expensive laboratory equipment and involve complex operations, making them impracticable for point-of care diagnosis in the field. Here in this study, we report a portable RPA-CRISPR based diagnosis system for plant disease, integrating smartphone for acquisition and analysis of fluorescent images. A polyvinyl alcohol (PVA) microneedle patch was employed for sample extraction on the plant leaves within one minute, the DNA extraction efficiency achieved 56 g/mg, which is [~]3 times to the traditional CTAB methods (18 g/mg). The system of RPA-CRISPR-Cas12a isothermal assay was established to specifically target P. infestans with no cross-reactivity observed against closely-related species (P. sojae, P. capsici). The system demonstrated a detection limit of 2 pg/L for P. infestans genomic DNA, offering sensitivity comparable to that of benchtop laboratory equipment. The system demonstrates the early-stage diagnosis capability by achieving a [~]80% and 100% detection rate on the third and fourth day post-inoculation respectively, before visible symptoms observed on the leaves. The smartphone-based "sample-to-result" system decouples the limitations of traditional methods that rely heavily on specialized equipment, offering a promising way for early-stage plant disease detection and control in the field.

molecular biology↗

bioRxiv2025

A Multimodal Adaptive Optical Microscope For In Vivo Imaging from Molecules to Organisms

Understanding biological systems requires observing features and processes across vast spatial and temporal scales, spanning nanometers to centimeters and milliseconds to days, often using multiple imaging modalities within complex native microenvironments. Yet, achieving this comprehensive view is challenging because microscopes optimized for specific tasks typically lack versatility due to inherent optical and sample handling trade-offs, and frequently suffer performance degradation from sample-induced optical aberrations in multicellular contexts. Here, we present MOSAIC, a reconfigurable microscope that integrates multiple advanced imaging techniques including light-sheet, label-free, super-resolution, and multi-photon, all equipped with adaptive optics. MOSAIC enables non-invasive imaging of subcellular dynamics in both cultured cells and live multicellular organisms, nanoscale mapping of molecular architectures across millimeter-scale expanded tissues, and structural/functional neural imaging within live mice. MOSAIC facilitates correlative studies across biological scales within the same specimen, providing an integrated platform for broad biological investigation.

cell biology↗

bioRxiv2025

Mitochondrial calcium influx-driven bioenergetics in the dopaminergic system selectively enable drug reward

Drugs of abuse hijack the brains reward system, driving pathological dopamine surges that underlie compulsive behavior and addiction. However, directly targeting dopamine signaling for treatment risks disrupting natural reward processes. Here, we identify a bioenergetic mechanism that selectively promotes addiction-related dopamine release and behaviors. Opioids and methamphetamine, but not natural rewards, induce mitochondrial calcium (Ca2+) influx via the mitochondrial calcium uniporter (MCU) in dopaminergic terminals of the nucleus accumbens. Optogenetic stimulation reveals that this mitochondrial Ca2+ influx occurs exclusively during high-intensity dopaminergic neuronal activation. This Ca2+ influx drives rapid ATP production, compensating for energy deficits caused by neuronal hyperactivity and enabling sustained dopamine release. Genetic deletion or pharmacological inhibition of MCU in dopaminergic neurons selectively reduces drug-induced dopamine release and prevents addictive behaviors while sparing natural reward processing in mice. These findings uncover a distinct mitochondrial bioenergetic mechanism underlying drug reward and propose MCU as a promising therapeutic target for addiction treatment.

neuroscience↗

bioRxiv2025

Structural Basis for Cas9-Directed Spacer Acquisition in Type II-A CRISPR-Cas Systems

CRISPR-Cas systems confer prokaryotic adaptive immunity by integrating foreign DNA (prespacers) into host arrays. Type II-A systems employ Cas9 for protospacer adjacent motif (PAM) recognition and coordinate with Csn2 and the Cas1-Cas2 integrase during spacer acquisition, yet their structural basis remains unresolved. Here, we report cryo-EM structures of the Enterococcus faecalis Cas9-Csn2-Cas1-Cas2 supercomplex in apo and DNA-bound states. The apo-state structure (Cas92-Csn28-Cas18-Cas24) adopts a resting conformation, with Cas9 locked in a nuclease-inactive state and Cas1-Cas2 sterically blocked from prespacer loading. Upon DNA engagement, Cas9 undergoes a conformational transition, forming a prespacer catching complex that threads the DNA through Csn2s central channel. This architecture enables Cas9 to interrogate the PAM sequence while sliding along the DNA, with Cas9 and Csn2 jointly define a 30-bp DNA segment which matches the prespacer length. Subsequent dissociation of Cas9 triggers a structural reconfiguration of the Csn2-Cas1-Cas2 assembly. The PAM-proximal DNA becomes accessible, and Cas1-Cas2 relocates to bind to the exposed DNA, enabling further prespacer processing and directional integration. These findings reveal how Cas9 collaborates with Csn2 and Cas1-Cas2 to couple PAM recognition with prespacer selection, resolving the dynamic structural transitions that ensure fidelity during type II-A CRISPR adaptation.

molecular biology↗

bioRxiv2025

Enhancing Strain-level Phage-Host Prediction through Experimentally Vali-dated Negatives and Feature Optimization Strategies

BackgroundAccurate prediction of phage-host interactions at the strain level is critical for understanding microbial ecology and for developing phage-based therapeutics. However, existing models are limited by the lack of experimentally validated negative interactions and inconsistencies in data construction strategies. ResultsIn this study, we present a large-scale phage-host interaction dataset comprising 13,000 experimentally verified links between 125 Klebsiella pneumoniae((K. pneumoniae) phages and 104 K. pneumoniae strains. Using this unique resource, we systematically evaluate the impact of negative data construction methods, feature extraction strategies, and machine learning algorithms on predictive performance. We show that randomly generated negatives significantly inflate model accuracy, while models trained on experimental negatives yield more realistic and robust results. Furthermore, protein-derived features outperform DNA-based features across various data conditions. Notably, models using only tail protein sequences achieve performance comparable to those using full-genome sequences, offering a time-efficient alternative without compromising accuracy. Finally, interpretable machine learning reveals amino acid preferences in both phages and hosts that align with known infection mechanisms and suggest novel determinants such as anti-transcriptional proteins. ConclusionsOur findings highlight best practices for constructing high-fidelity strain-level phage-host prediction models. The dataset and insights presented here provide a valuable benchmark for future studies and lay the foundation for more biologically grounded, interpretable modeling frameworks in viromics and microbiome research.

bioinformatics↗

bioRxiv2025

Targeted Ablation of Canonical Disulfide Bonds Mitigates TCR Mismatching in Engineered T Cells

T cell receptor-engineered T (TCR-T) cell therapy holds distinct advantages over chimeric antigen receptor (CAR)-T cell therapy in treating solid tumors by exploiting intracellular targets through MHC-mediated antigen presentation. Despite this potential, only one TCR-T therapy has received FDA approval to date. A key challenge lies in chain mispairing between exogenous therapeutic TCR chains and endogenous TCR chains, which compromises membrane localization efficiency and elevates off-target toxicity risks. While multiple engineering strategies have been developed to enhance TCR surface expression, our systematic evaluation using a novel mispairing assessment platform revealed that conventional approaches may paradoxically exacerbate chain mismatching. Through targeted cysteine mutations that disrupt the native interchain disulfide bonds in TCR constant domains, we achieved a substantial reduction in exogenous-endogenous TCR mispairing. Importantly, these structural modifications preserved both high surface expression level and potent tumor-specific cytotoxicity. This innovative engineering approach establishes a critical foundation for clinical-grade manufacturing of TCR-T therapies with enhanced safety profiles.

immunology↗

bioRxiv2025

Immunomodulatory Biomaterials Enhancing Implant Osseointegration: Knowledge Mapping of Research Evolution from March 2005 to March 2025

ObjectiveTo delineate the evolutionary trajectory of immunomodulatory biomaterials in implant osseointegration through bibliometric analysis, identifying pivotal theoretical breakthroughs and technological advancements. MethodsA total of 419 articles (2005-2025) from the Web of Science Core Collection were analyzed using a multi-tool framework. Current research status and hotspots were evaluated by co-occurrence analysis of keywords and institutions using VOSviewer. The evolution and bursts of the knowledge base were assessed through co-citation analysis of references, authors, and journals via CiteSpace. Thematic evolution and keyword trends were mapped using the bibliometrix package in R. ResultsThe field exhibited "intermittent-explosive" growth (32.7% annual increment), with China leading global contributions (69.4%). The osteoimmunomodulation (OIM) theory emerged as the cornerstone, emphasizing spatiotemporal macrophage polarization (M1/M2 balance) and multi-signal crosstalk (BMP-2/VEGF/OSM). Key technological pathways included: [circled1] Surface engineering (nanotopography, ion-doped coatings); [circled2] Smart materials (3D-printed scaffolds, pH/ROS-responsive carriers); [circled3] Antibacterial-immunomodulatory synergy. Burst detection revealed shifting frontiers toward clinical translation (2023-2025 burst: "3D printing", strength=4.05) and precision modulation ("macrophage polarization", strength=9.02). ConclusionImmunomodulatory biomaterials are transitioning from mechanistic exploration to clinical adaptation. Future development requires integrating dynamic microenvironment-responsive designs with multi-omics validation to address macrophage heterogeneity, ultimately enabling personalized osseointegration therapies.

bioinformatics↗

bioRxiv2025

Unified Genomic and Chemical Representations Enable Bidirectional Bio-synthetic Gene Cluster and Natural Product Retrieval

Natural product discovery is increasingly driven by the ability to analyze microbial genomes for biosynthetic gene clusters (BGCs) that encode secondary metabolites. While existing approaches have successfully linked BGCs to broad classes of chemical products, they typically operate in a single modality (genomic or chemical) limiting the scope of bidirectional prediction. In this work, we propose a multimodal framework that integrates genomic and chemical information by projecting embeddings derived from pretrained language models into a common representation space. We embed genomic sequences using a BGC foundation model and represent molecules through a chemical language model, then use a metric learning model to co-embed BGCs and their associated chemical structures. This co-embedding space allows us to quantify the similarity between BGCs and compounds using similarity measures, enabling both forward and inverse retrieval tasks. Beyond retrieval, we show that the shared space can guide strain selection for targeted compounds. By identifying BGCs closest to a query compound in the embedding space, we prioritize microbial strains that encode similar clusters, thereby streamlining genome mining and retrobiosynthetic design efforts. This approach represents a generalizable, scalable strategy to bridge biological and chemical modalities in natural product discovery.

synthetic biology↗

bioRxiv2025

Synthetic essentiality of TRAIL/TNFSF10 in VHL-deficient renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common and aggressive subtype of kidney cancer. Loss of von Hippel-Lindau (VHL) and the consequent activation of hypoxia-inducible factor- (HIF, especially HIF2) plays an essential role in ccRCC initiation and progression. The approved HIF2 inhibitor belzutifan faces the challenge of resistance, presenting an opportunity of co-targeting HIF2 and another vulnerability. This study elucidates the synthetic essentiality of TRAIL (tumor necrosis factor-related apoptosis-inducing ligand) in VHL-deficient ccRCC, uncovering a novel reciprocal regulation between HIF2 and TRAIL. TRAIL was identified as a direct transcriptional target of HIF2 and paradoxically found to be crucial for cell proliferation, primarily by activating the p38 MAPK pathway and facilitating G1/S phase transition. Depletion of endogenous TRAIL or inhibition of HIF2 with belzutifan sensitizes ccRCC cells to recombinant TRAIL, presenting a promising avenue for combination therapy to overcome both TRAIL resistance and belzutifan resistance in treating ccRCC. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC="FIGDIR/small/621197v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@1d603b9org.highwire.dtl.DTLVardef@18e6dc7org.highwire.dtl.DTLVardef@1c953cdorg.highwire.dtl.DTLVardef@9cd144_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Nuclear Phase Separation Drives NPM1-mutant Acute Myeloid Leukemia

During cancer development, mutations promote gene expression changes that cause transformation. Leukemia is frequently associated with aberrant HOXA expression driven by translocations in nucleoporin genes or KMT2A, and mutations in NPM1. How disparate mutations converge on this regulatory pathway is not understood. Here we demonstrate that mutant NPM1 (NPM1c) forms nuclear condensates in multiple human cell lines, mouse models, and primary patient samples. We show NPM1c phase separation is necessary and sufficient to coordinate the recruitment of NUP98 and KMT2A to condensates. Through extensive mutagenesis and pharmacological destabilization of phase separation, we find that NPM1c condensates are necessary for regulating gene expression, promoting in vivo expansion, and maintaining the undifferentiated leukemic state. Finally, we show that nucleoporin and KMT2A fusion proteins form condensates that are biophysically indistinguishable from NPM1c condensates. Together, these data define a new condensate underlying leukemias that we term coordinating bodies (C-bodies), and propose C-bodies as a therapeutic vulnerability.

biophysics↗

bioRxiv2025

SyntheMol-RL: a flexible reinforcement learning framework for designing novel and synthesizable antibiotics

The rise of antibiotic-resistant pathogens such as Staphylococcus aureus has created an urgent need for new antibiotics. Generative artificial intelligence (AI) has shown promise in drug discovery, but existing models often fail to propose compounds that are both effective and synthetically tractable. To address these challenges, we introduce SyntheMol-RL, a reinforcement learning-based generative model that can rapidly design synthetically accessible small molecule drug candidates from a massive chemical space of 46 billion compounds. SyntheMol-RL improves upon our prior Monte Carlo Tree Search (MCTS)-based SyntheMol model by generalizing across chemically similar building blocks and enabling multi-parameter optimization. We applied SyntheMol-RL to generate candidate antibiotics against S. aureus by optimizing for both antibacterial activity and aqueous solubility, and we found that SyntheMol-RL generated molecules with improved predicted properties compared to both the previous MCTS version of SyntheMol as well as an AI-based virtual screening baseline. We synthesized 79 SyntheMol-RL compounds that were unique relative to the training dataset and found that 13 showed potent in vitro activity, of which seven were structurally novel after detailed literature searches. Furthermore, one hit compound, synthecin, demonstrated efficacy in a murine wound infection model of methicillin-resistant S. aureus (MRSA). These results validate SyntheMol-RLs ability to generate novel and synthetically accessible candidate antibiotics and position SyntheMol-RL as a powerful tool for drug design across therapeutic domains.

biochemistry↗

bioRxiv2025

Universal Dual-Target CAR-γδT Cells Targeting B7-H3 and IL13Rα2 for Glioblastoma Therapy

Glioblastoma (GBM) represents the most prevalent and aggressive primary malignant neoplasm in the adult central nervous system, exhibiting marked infiltrative growth patterns, inevitable recurrence, and dismal therapeutic outcomes with current treatment modalities. While CAR-T cell immunotherapy has demonstrated remarkable success in hematological malignancies, its clinical translation for GBM has been hampered by several fundamental limitations. A key factor among these is tumor-intrinsic heterogeneity, which drives antigen escape and therapeutic resistance. Furthermore, although autologous CAR-T approaches dominate current clinical investigations, they encounter substantial barriers including manufacturing variability, scalability constraints, and practical limitations for widespread clinical deployment. In contrast, allogeneic "off-the-shelf" CAR-T therapy holds greater potential for the future applications. {gamma}{delta} T cells are a particularly compelling candidate for universal CAR therapy, offering several advantages including innate MHC-unrestricted target recognition obviating the need for HLA matching, polyfunctional cytotoxic mechanisms capable of addressing heterogeneous tumor populations, and intrinsic tropism for solid tumors. However, translational implementation has been constrained by their physiological rarity, ex vivo expansion difficulties, and genetic modification inefficiencies. To address these challenges, we adopted a dual-pronged targeting strategy focusing on B7-H3 and IL13R2 - two surface antigens demonstrating preferential overexpression across GBM subtypes while maintaining limited distribution in normal tissues. Using phage display platform and function-based nanobody screening we identified high-affinity binders against both targets. Subsequent optimization of {gamma}{delta} T cell expansion protocols and lentiviral transduction parameters enabled the development of a bispecific, allogeneic CAR-{gamma}{delta} T cell platform. Our in vitro studies revealed that dual-target CAR-{gamma}{delta}T cells sustained proliferative capacity under GMP-compatible culture conditions, exhibited potent and specific cytotoxicity against antigen-positive glioma cells, and critically, they showed superior elimination of target-heterogeneous tumors compared to monospecific CAR-T constructs. These results establish a robust preclinical foundation for clinical translation and highlight the therapeutic potential of combinatorial antigen targeting coupled with allogeneic {gamma}{delta} T cell engineering to overcome the persistent challenges in GBM immunotherapy.

immunology↗

bioRxiv2025

Probing the CaV1.2 interactome in heart failure identifies a positive modulator of inotropy and lusitropy

BackgroundMaladaptive changes in the function, expression and localization of proteins involved in calcium-handling worsen the impaired contractility of systolic heart failure (HF). Standard proteomics techniques require cell lysis and so are unable to characterize changes specific to the critical sub-cellular domain bounded by the T-tubule and the sarcoplasmic reticulum, known as the cardiac dyad. Traditional approaches are also less likely to capture low-affinity protein-protein interactions on lipid membranes. To improve our understanding of heart failure pathophysiology, we applied proximity proteomics to the cardiac dyad of mice with ischemic cardiomyopathy. MethodsUsing two lines of transgenic mice expressing fusion proteins of the engineered ascorbate peroxidase APEX2 with subunits of the cardiac voltage gated calcium channel, CaV1.2, we labeled the dyad proteome of live, intact myocytes from healthy mice (N=6) and mice with coronary artery ligation HF (N=5) by peroxidase-catalyzed biotinylation. Quantitative mass spectrometry with isobaric tandem mass tags (TMT) was used to assess alterations in the local dyad proteome in myocytes from mice with chronic, remodeled HF. We subsequently generated a mouse with inducible cardiac overexpression of Galectin-1 to examine the effects of this protein on cardiac function and more specifically on the calcium-handling properties of mature myocytes, using cellular electrophysiology, calcium imaging, and echocardiography. ResultsFrom mice with HF, we found significant enrichment of 43 proteins defined by their abundance and proximity to transgenic CaV1.2 1C channels, and a significant reduction in 22 proteins, out a of a total of 2326 proteins quantified. We also significantly enriched 286 proteins, and saw a reduction in 13 proteins, defined by proximity and abundance to CaV1.2 {beta}2B-subunits, out of a total 2236 proteins identified. Pathway analysis revealed HF is associated with increased abundance of components of the 26s proteasome and microtubules in the dyad, as well as the dimerizing, carbohydrate binding protein Galectin-1. Cardiac specific overexpression of Galectin-1 in healthy mice increases activation of CaV1.2 and the Ryanodine receptor and accelerates myocyte relaxation through phosphorylation of Phospholamban. ConclusionsUsing proximity proteomics to examine the effects of HF in vivo, we find increased localization of Galectin-1 to the cardiac dyad, and that overexpression of Galectin-1 accelerates calcium kinetics in the heart.

cell biology↗

bioRxiv2025

Serpine1 plays a critical role in Th17 cell differentiation and psoriasis pathogenesis

A large body of evidence indicates that Th17 cells play essential roles in mucosal immune responses and trigger autoimmune diseases, including multiple sclerosis, inflammatory bowel disease, and psoriasis. Targeting Th17 cells holds promise for therapeutic innovation. However, the molecular mechanisms underlying Th17 cell differentiation remain poorly understood. Here, we found that Serpine1 was preferentially induced in Th17 cells. Genetic ablation of Serpine1 inhibited Th17 cell polarization in vitro, reproducing the phenotype caused by pharmaceutical inhibition against Serpine1 product PAI-1. Moreover, we confirmed that, despite normal T-cell initiation in vivo, deletion or inhibition of Serpine1 significantly attenuated disease severity and notably reduced skin inflammation in an IMQ-induced psoriasis model. Notably, this protective effect was also recapitulated in the CD4 conditional knockout mouse pathogenic model, ruling out the non-T cell autologous effect of Serpine1. Collectively, our results revealed a critical role of Serpine1 in regulating Th17 cell differentiation and autoimmune diseases, suggesting that Serpine1 is a promising therapeutic target for autoimmune disease treatment. SignificanceUsing multiple genetic and pharmaceutical ablation model systems, we have demonstrated that Serpine1 plays a critical role in regulating Th17 differentiation and psoriasis pathogenesis. Serpine1 intervention attenuates disease symptoms in a psoriatic mouse model in a Th17 cell-dependent manner. This finding extends our understanding of Serpine1s role in inflammatory diseases, highlighting its therapeutic potential.

immunology↗

bioRxiv2025

Computational Assessment of Circularization Impact on Saxitoxin G-quadruplex Aptamer Performance

Although high-affinity and high-specificity aptamers can be obtained by SELEX (Systematic Evolution of Ligands by Exponential Enrichment), and have good activity in vitro, their performance in vivo is poor. This is mainly because of the degradation of linear nucleic acids by nucleases in body fluids and the difficulty of maintaining stable 3D structures in complex body fluid environments, which seriously hinders the clinical application of aptamers. This makes circular aptamers, which can resist degradation and are more stable in complex body fluid environments, an attractive option. However, the cyclization process may have a considerable impact on the structure of the original linear aptamer, and blind cyclization may lead to a decrease in its affinity. Here, we developed a new method to guide the cyclization of saxitoxin (STX) aptamers based on molecular computation, and verified the activity of circular aptamers through bioactivity experiments to further verify the authenticity and reliability of our methods. Consistent with the computational analysis, although circularization disrupts the G4 structure, circular aptamer not only has a higher affinity than the linear one but also provides certain protection to mice and greatly prolongs their survival, which proves the accuracy and reliability of the circular structure designed by our computational method. Our findings provide important ideas for better guidance in the design of circular aptamers and demonstrate their great potential in therapeutic applications.

biochemistry↗

bioRxiv2025

Mapping Architecture of Protein complexes in Arabidopsis using XL-MS

Capturing molecular machines in action is essential for understanding protein complex architecture, cellular regulation, and gene function. Here, we present a large-scale structural proteomics resource for Arabidopsis thaliana generated using an optimized cross-linking mass spectrometry (XL-MS) workflow. Using the trifunctional cross-linker PhoX, whose phosphonic acid moiety enables immobilized metal affinity chromatography (IMAC)-based enrichment, we selectively enriched cross-linked peptides from whole-cell lysates, chloroplasts, and nuclei. Analysis with pLink 3.2 identified 52,944 unique cross-linked peptide pairs, corresponding to 37,531 residue-level contacts across 5,064 proteins. These data define 3,083 protein-protein interactions, including 2,385 heteromeric and 698 homomultimeric interactions. Comparison with the STRING database showed that 676 interactions are supported by STRING scores [≥]0.9. Structural mapping to Protein Data Bank (PDB) and AlphaFold models showed that most cross-links were within the expected 35 [A] distance constraint. The dataset further enabled the analysis of protein connectivity and complex topology across diverse molecular assemblies, including the Rubisco holoenzyme, chloroplast 70S ribosome, photosystem complexes, and the cytosolic 80S ribosome together with associated biogenesis and regulatory factors. We also identified histone-associated complexes, including interactions involving an O-acyltransferase. By providing residue-level structural constraints for a substantial portion of the Arabidopsis proteome, this study provides a resource for exploring plant molecular machines and their spatial organization. Significance StatementUnderstanding how proteins interact within living cells is essential to deciphering cellular architecture and function. However, capturing native protein-protein interactions (PPIs) on a global scale has proven technically challenging. Here, we present a proteome-wide cross-linking mass spectrometry (XL-MS) platform that can systematically map direct PPIs in plant cells without requiring transgenic manipulation. This approach identifies thousands of interactions spanning major subcellular compartments and characterizes the in situ organization of critical protein assemblies, such as photosystems, ribosomes, and chromatin-associated connectivity. By mapping both established and less-characterized interactions, this work advances our understanding of the plant protein interactome and provides a valuable resource for investigating the structural organization of the plant proteome.

molecular biology↗