Biology subjects

Shen, Q.

Publications and source records attributed to Shen, Q..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

LorMe: a streamlined and interoperable R framework for end-to-end microbiome analysis

Microbiome research is rapidly evolving accompanied by increasingly diverse analytical strategies and visualization formats. However, existing R-based tools remain fragmented, differ in data structures, and often require extensive package-specific pre-processing. This increases command-line complexity and limits both interoperability and reproducibility across packages. Here, we present LorMe (Lightweight One-line Resolving Microbial Ecology), an R package that provides a unified, interoperable, and user-friendly framework for microbiome data analysis. LorMe incorporates a standardized S4 object system with fully bidirectional compatibility with phyloseq and microeco, which enables seamless data exchange across major microbial analysis packages. A global configuration system ensures consistent parameter control and visualization standards, and a modular architecture supports both complete end-to-end workflows and flexible execution of individual analytical components. Based on these, LorMe further offers an one-command pipeline that conducts the full spectrum of microbial community analyses, including alpha and beta diversity, differential abundance testing, co-occurrence network inference, and meta-network construction, while archiving all intermediate objects and source data to ensure complete reproducibility. Demonstrations using sample datasets show that LorMe performs comprehensive analyses within minute, produces publication-ready outputs, and maintains methodological transparency. Application to a real rhizosphere dataset revealed biologically coherent patterns across diversity metrics, differential taxa, and network modules, highlighting the capacity of LorMe to support robust ecological interpretation. Collectively, LorMe provides a lightweight, extensible, and flexible solution that reduces technical barriers and enhances reproducibility in microbiome research. LorMe package is freely accessible from both CRAN (https://cran.r-project.org/web/packages/LorMe) and github (https://github.com/wangnq111/LorMe)

bioinformatics↗

bioRxiv2025

Oncogenic EGFR rewires STING-TBK1 immune machinery to license DNA damage tolerance

EGFR hotspot mutations (mEGFR), including primary L858R, exon 19 deletion, and secondary T790M, are pivotal oncogenic drivers in human non-small cell lung cancer (NSCLC). Meanwhile, NSCLC resistance to third-generation tyrosine kinase inhibitors (TKIs) is a major clinical challenge and remains mechanistically unresolved. Here, we uncover a previously unrecognized immunological mechanism whereby mEGFR exploits cGAS-STING innate immune signaling, conventionally regarded as tumor-suppressive, to sustain oncogenic signaling and therapeutic resistance. Mechanistically, mutant EGFR kinase aberrantly incorporates into STING signalosomes, directly phosphorylating STING (Y245/Y314) and TBK1 (Y577/Y677), stabilizing and hyperactivating TBK1 proteins, and establishing an unexpected and kinase loop critical for DNA damage repair. Disruption of this mEGFR-STING-TBK1 axis, genetically or pharmacologically, profoundly sensitized resistant patient-derived NSCLC organoids to chemotherapy. Combining TBK1 inhibition with cisplatin notably eradicated mEGFR-driven tumors in spontaneous and immunocompetent NSCLC murine models and patient-derived organoids. Our findings suggest a new function of cGAS-STING in the DNA damage repair program, its paradoxical exploitation by oncogenic driver mutations, and an innate immune therapeutic vulnerability in NSCLC.

cancer biology↗

bioRxiv2025

Multi-immersion Oblique Plane Microscope (miOPM): A reconfigurable platform for high-resolution Light-Sheet Fluorescence Microscopy.

Light-Sheet Fluorescence Microscopy (LSFM) enables gentle, rapid, and efficient volumetric imaging of biological specimens. Despite its potential, LSFM has fragmented into multiple variants, each narrowly optimized for specific samples or imaging regimes, limiting its broad applicability. To overcome this barrier, we introduce the multi-immersion oblique plane microscope (miOPM), an adaptable LSFM platform for high-resolution imaging ranging from subcellular dynamics to whole organisms and cleared tissues. miOPM uniquely supports seamless interchangeability of oil, water, and air objectives, and maintains diffraction limited performance across a refractive index range of 1.33 - 1.51. It is compatible with standard sample mounting, current clearing protocols and high-throughput 3D imaging. We leverage miOPM to image diverse biological specimens at multiple spatial scales. By greatly expanding the adaptability and ease of use of LSFM, miOPM is poised to democratize advanced three-dimensional imaging.

bioengineering↗

bioRxiv2025

Uncovering directionally and temporally variable genes with STAVAG

Spatially variable genes (SVGs) are crucial for understanding spatial heterogeneity in spatial transcriptomics. Yet, SVGs are challenging to align with established biological axes and lack straightforward mechanistic interpretation, thereby limiting their ability to inform downstream experiments or clinical applications. Here, we introduce the concept of directionally variable genes (DVGs) and temporally variable genes (TVGs). Also, we propose a unified framework, STAVAG, that models spatial or temporal information to identify DVGs and TVGs. STAVAG effectively identifies biologically meaningful DVGs for uncovering prognostically relevant gene modules that align with the malignant-immune-stroma structure in the tumor microenvironment, identifying marker genes in three-dimensional brain data, and detecting 12 polarization genes regulating planarian regeneration. Furthermore, by tracking the progression of myocardial infarction and tissue development, STAVAG reveals critical TVGs that can serve as diagnostic biomarkers for the ultra-acute phase of myocardial infarction. STAVAG also identifies both global and local gene modules involved in mouse placentation, as well as tissue-specific and interactive TVG modules that dynamically evolve during mouse embryonic development.

bioinformatics↗

bioRxiv2025

Metabolite Interactions Mediate Beneficial Alliances Between Bacillus and Trichoderma for Effective Fusarium Wilt Control

Bacteria-Fungi Interactions play a crucial role in soil nutrient cycling and plant disease suppression. Bacillus and Trichoderma exhibit antagonism when inoculated on laboratory media, global soil sample analysis reveals a positive correlation between these two genera in addition to enhanced plant-pathogen Fusarium oxysporum (FOC) suppression and plant growth promotion. Here, we depict a complexity of interactions in a cross-kingdom consortia of Bacillus velezensis and Trichoderma guizhouense. Transcriptomic profiling revealed that in the presence of fungi, the key stress sigma factor of B. velezensis activates expression of biosynthetic genes for antimicrobial secondary metabolite production. Among these, surfactin induces T22azaphilone production in T. guizhouense that hinders oxidative stress. Both surfactin and T22azaphilone contribute to Bacillus and Trichoderma maintenance in soil in the presence of FOC. Finally, FOC-secreted fusaric acid temporarily inhibits B. velezensis growth while it is efficiently degraded by T. guizhouense. These metabolite-mediated interactions reveal how competing soil microorganisms could form effective alliances that ultimately enhance plant protection against soil-borne pathogens.

microbiology↗

bioRxiv2025

Pp6-Pfkfb1 axis modulates intracellular bacterial proliferation by orchestrating host-pathogen metabolic crosstalk

Intracellular bacterial pathogens exhibit heterogeneous replication rates within host macrophages, but the mechanisms by which they manipulate host factors for survival remain incompletely understood. Using a fluorescence-dilution reporter system in Salmonella typhimurium (Salmonella)-infected macrophages, we found that Protein Phosphatase 6 (Pp6) was downregulated in macrophages harboring growing bacteria. Conditional knockout of Pp6 elevated host susceptibility to Salmonella-mediated lethality due to compromised antimicrobial defenses. MicroRNA-31 (miR-31) was identified as a negative regulator of Pp6, and its conditional ablation enhanced bacterial clearance. Yeast two-hybrid screening identified 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1 (Pfkfb1), a metabolic regulator, as a substrate of Pp6. Pp6 deficiency resulted in significantly elevated expression of Pfkfb1, which was highly expressed in macrophages containing replicating Salmonella. Pfkfb1 deletion restricted bacterial proliferation by promoting nitric oxide (NO) production while concurrently suppressing arginase-1 (Arg-1) expression and impairing arginine metabolism in macrophages. Collectively, these results establish the Pp6-Pfkfb1 axis as a key regulator of host metabolic adaptation and intracellular bacterial survival, offering potential therapeutic targets against multidrug-resistant pathogens. Author summaryIntracellular pathogens secrete effector proteins that intercept and modify host cells to usurp host defenses and establish habitable intracellular niches, yet the host factors they manipulate for survival and virulence are not fully understood. Using a fluorescence-dilution reporter system in Salmonella typhimurium (Salmonella)-infected macrophages, we found Protein Phosphatase 6 (Pp6) was significantly decreased in macrophages harboring replicating Salmonella and its deficiency indulged bacterial growth in macrophages. However, the deletion of microRNA-31 (miR-31), a negative regulator of Pp6, enhanced Salmonella clearance. Furthermore, through yeast two- hybrid screening, we identified 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 1 (Pfkfb1) is a substrate of Pp6. And we demonstrated Pfkfb1, abundantly expressed in macrophages containing growing bacteria, is crucial for Salmonella proliferation by regulating nitric oxide (NO) levels, arginase-1 (Arg-1) expression and arginine metabolism. Overall, the molecular changes in Pp6-Pfkfb1 axis drive host metabolic adaptations that enable intracellular bacterial survival.

microbiology↗

bioRxiv2025

An Antibody Cocktail-Based Immunoaffinity-LC-MS Method Enabled Ultra-Sensitive and Robust Quantification of Circulating Proinsulin Proteoforms and C-peptide

Accurately measuring circulating proinsulin proteoforms is crucial for clinical investigation of diabetes, but was previously not feasible owing to limited assay specificity/sensitivity. Here we devised a highly sensitive LC-MS-based strategy to quantify intact proinsulin, des-31,32 and des-64,65 proinsulin, and C-peptide in circulation. The method involves: i)quantitative, robust affinity capture using an optimized antibody cocktail, eliminating the severe quantitative bias across multiple proteomes typically introduced when using a single antibody; ii)Lys-C digestion producing unique signature peptides for each proteoform, and iii)trapping-nano-LC coupled with FAIMS/dCV-MS for an ultra-sensitive analysis. The selective trapping/delivery ensured sensitive/selective analysis of the targets while achieving excellent analytical robustness that is critical for clinical assays, and the FAIMS/dCV substantially reduces baseline noise/interferences, further enhancing S/N. The assay achieved exceptional sensitivity, with serum LOQs of 1.7, 2.3, and 3.6 pg/mL respectively for intact-proinsulin, des-31,32 and des-64,65, representing the first assay capable of sensitively quantifying these major circulating proinsulin proteoforms. We applied this assay to 78 subjects, including autoantibody positive(n=20) and new-onset type-1-diabetes(T1D, n=19) with respective age/sex/BMI-matched controls, enabling the first accurate profiling of proinsulin proteoforms in clinical groups. The assay results demonstrated a clear separation of control and new-onset T1D groups that a parallel total-proinsulin ELISA assay fails to capture. Furthermore, distinct expression patterns in relative abundance ratios among proteoforms were observed across clinical groups. This assay may provide valuable insights into the {beta}-cell functions and the onset/progression of diabetes and other associated conditions. Moreover, the strategy is broadly applicable to targeted measurement of other biomarker proteoforms.

biochemistry↗

bioRxiv2025

CCN1 forms a complex with GPC4 and heparin to fine-tune signaling activities for embryonic cortical neural stem cell maintenance

Radial glial cells (RGCs) are the neural stem cells (NSCs) in the developing brain, capable of self-renewing and generating neurons and glia in order. The developmental behaviors of NSCs are determined by extrinsic factors from the NSC niche, together with intrinsic factors. Here, we show that Cellular Communication Network 1 (CCN1), a secreted matricellular protein, is an autocrine factor derived from RGCs in the embryonic telencephalon. Loss of Ccn1 in RGCs leads to accelerated lineage progression of RGCs, and causes premature cell cycle exit and neuronal differentiation, resulting in a reduction in NSC pool size, and in turn, at the expense of the perinatal gliogenesis. Mechanistically, CCN1 interacts with an RGC-expressed membrane protein GPC4, one of the heparan sulfate proteoglycans (HSPGs), and is required for GPC4 to maintain NSCs through the Sonic Hedgehog (Shh) signaling pathway, depending on the binding of heparin to CCN1. Our work provides a potential mechanism for the dynamic and sophisticated interconnections of niche components that meet the needs of context-dependent maintenance, differentiation, and fate determination of NSCs.

developmental biology↗

bioRxiv2025

Inulin reduces Ralstonia invasion by promoting cooperation between Lysinibacillus sphaericus and Pseudoarthrobacter spp.

In field production, beneficial microbial agents are typically applied along with key resources that beneficial microbes prefer to utilize. This practice aims to help the beneficial microbes colonize the field and exert their disease resistance functions. However, the mechanisms by which these key resources influence the colonization and disease resistance effects of beneficial microbes remain unknown. In this study, we found that inulin can enhance the growth capacity of Lysinibacillus sphaericus HR92 and its ability to inhibit Ralstonia solanacearum. Further investigation revealed that inulin can enhance strain HR92s flagellar assembly, bacterial chemotaxis, fatty acid metabolism, and siderophore synthesis capabilities, ultimately improving strain HR92s effectiveness in controlling bacterial wilt. Moreover, adding inulin to the soil can enrich Pseudarthrobacter strains. This genus enhances the expression of genes involved in the synthesis of the antibacterial substance HR92, and competes for nutrients with Ralstonia solanacearum, thereby further inhibiting the occurrence of bacterial wilt disease. Additionally, the combination of inulin and Pseudarthrobacter strains upregulates the valine and leucine pathway genes in strain HR92. These genes play a crucial role in the synthesis of surfactin and the antimicrobial VOC 3-methyl-1-butanol. We have demonstrated that the addition of key resources not only enhances the control efficacy of beneficial bacteria against soil-borne diseases but also enriches the "helpers" of beneficial bacteria in soil. ImportanceRalstonia solanacearum is a plant pathogen that can cause bacterial wilt in several important crops. Given the limitations of beneficial bacterial inoculation, we propose a strategy to enhance the biocontrol efficacy of beneficial microorganisms by utilizing key resources. In this study, we demonstrate that key resources inulin can improve the biological control effects of beneficial bacteria, thereby maintaining plant health. Furthermore, we found that increasing the concentration of inulin altered the diversity of the rhizosphere microbiota and specifically enriched the abundance of Pseudarthrobacter, which compete with pathogens for nutrients on one hand and, on the other hand, synergize with inulin to enhance the biocontrol efficacy of the beneficial bacterium HR92. Together, our study reveals that key resources can enhance the biocontrol efficacy of beneficial bacteria and enrich potential beneficial bacteria in resident microbial communities, further reducing tomato diseases.

microbiology↗

bioRxiv2025

AarMIXTAs: key factors of T-shaped non-glandular trichome development in Artemisia argyi

Trichomes are necessary for stress resistance and metabolite synthesis in plant. T-shaped non-glandular trichomes (TSTs) as the main component of moxa floss, which are the specific characteristics of A. argyi. Here, we observed that TSTs were at an extremely high density on the lower surfaces in A. argyi leaves. The key transcription factors (TFs) involved in regulation of TSTs development of A. argyi were identified through RNA sequencing of TSTs and non-TSTs. The core regulatory genes, AarMIXTAs showed allelic amplification and functional differentiation compared with A. annua, might contribute development of TSTs. The overexpression of AarMIXTA1.2 significantly increased the density of TSTs in transgenic Arabidopsis and may regulate trichome development by regulating the downstream genes, which played an important positively regulatory role in the development of TSTs. This study provides a good reference for the molecular mechanisms related to the development of TSTs and a theoretical basis for the high-yield moxa floss cultivation of A. argyi.

plant biology↗

bioRxiv2025

Dynamic Monomer-Dimer Transition in Ligand-induced Apelin Receptor Activation

G-protein-coupled receptors (GPCRs) are significant signal transducers that exist as monomers and in multiple oligomeric forms. However, molecular mechanism driving their dynamic interconversion to regulate intricate signaling in class A GPCRs remains elusive, compounding our understanding of their related pathophysiological functions. Here, we present a set of 12 assemblies of the apelin receptor (APLNR), including dimeric apo state, agonistic small molecule- or nanobody-bound state of monomeric and dimeric APLNR with and without G-proteins, providing a detailed dynamic view of the monomer-dimer transition. High-resolution cryo-EM structures reveal that different ligands induce varying degrees of pre-dissociation of dimers in the absence of G-protein, with G-protein coupling facilitating the transition from dimeric to monomeric receptor. Functional studies further highlight the critical role of cholesterol clusters in stabilizing the APLNR dimers. These insights enhance our understanding of the dynamic regulation of class A GPCRs across different aggregated forms and advance the rational drug design strategies aimed at selectively modulating of APLNR signaling.

molecular biology↗

bioRxiv2025

AMPK- and cGAS-Mediated Dual Sensing of Glucose and dsDNA Synergizes to Enhance Antitumor Immunity

Intratumoral glucose availability is linked considerably to tumor growth, immune evasion, and metastasis. However, the precise molecular mechanisms by which glucose levels govern cellular and immune responses against tumors remain incompletely understood. Here, we explored the context of tumors of intersections between AMP-activated protein kinase (AMPK) and cGAS-STING signaling, a key pathway initiating antitumor immunity. We unexpectedly found that AMPK activation robustly enhances cGAS-STING signaling within cancer and immune cells, which potently impacts melanoma and colorectal cell senescence, organoid apoptosis, and the infiltration of CD4+ and CD8+ T lymphocytes. Using classic or newly developed AMPK agonist Aldometanib, TBK1S511E/S511E knock-in (KI) mice, glucose metabolic modulator, as well as AMPK1/2 dKO melanoma, we demonstrated that dual sensing of intratumoral glucose and dsDNA integrated by the AMPK-TBK1 cascade is essential for initiating antitumor immunity and suppressing cancer progressions. Notably, novel AMPK agonists or intervening in glucose glycolysis by Lonidamine synergized effectively with STING agonists, substantially inhibiting melanoma growth. Therefore, these findings unravel a concise mechanism integrating glucose metabolism and innate DNA sensing into cancer cell fate and propose an effective therapeutic strategy to enhance antitumor immunity. HIGHLIGHTSO_LIDual and synergistic sensing of glucose and dsDNA facilitates antitumor immunity in melanoma and colorectal cancer; C_LIO_LIAMPK substitutes intratumoral cGAS-STING-IRF3 signaling through TBK1 phosphorylation at S511; C_LIO_LIGlucose deficiency induces cancer cell senescence, apoptosis, and T lymphocyte infiltration via the AMPK-TBK1 cascade; C_LIO_LINewly developed AMPK agonists synergize with STING agonists to retrieve striking tumor suppression. C_LI

cancer biology↗

bioRxiv2025

Toward highly accurate reference and method selection for universal cross-dataset cell type annotation

Cell type annotation is a critical and essential task in single-cell data analysis. Various reference-based methods have provided rapid annotation for diverse single-cell data. However, how to select the optimal references and methods is often overlooked. To this end, we present a cross-dataset cell-type annotation methodology with a universal reference data and method selection strategy (CAMUS) to achieve highly accurate and efficient annotations. We demonstrate the advantages of CAMUS by conducting comprehensive analyses on 672 pairs of cross-species scRNA-seq datasets. The annotation results with references selected by CAMUS achieved substantial accuracy gains (25.0-124.7%) over random selection strategies across five reference-based methods. CAMUS achieved high accuracy in choosing the best reference-method pair among 3360 pairs (49.1%). Moreover, CAMUS showed high accuracy in selecting the best methods on the 80 scST datasets (82.5%) and five scATAC-seq datasets (100.0%), illustrating its universal applicability. In addition, we utilized the CAMUS score with other metrics to predict the annotation accuracy, providing direct guidance on whether to accept current annotation results.

bioinformatics↗

bioRxiv2025

Spatiotemporal changes in soil properties predict plant health at continental scale

Abiotic and biotic soil properties are strong predictors of plant yield globally1-5, but they become unreliable over large areas when plant health is threatened by pathogen6-8. Here we present a novel approach to predict plant health based on spatiotemporal changes in soil chemical and biological properties. We first demonstrate that plant health and soil properties consistently respond to environmental change (organic fertilization) regardless of the soil type or geographical origin. Second, we experimentally show that trackable shifts in soil properties reliably explain soil suppressiveness to the Ralstonia solanacearum bacterial pathogen and that a scalable spatiotemporal model predicts plant health with 84% accuracy across multiple climatic zones and cropping systems. Our results suggest that this tight coupling between soil properties and plant health could facilitate the development of agricultural practices aimed at sustainably improving crop yields while safeguarding crop health.

ecology↗

bioRxiv2025

High-precision cell-type mapping and annotation of single-cell spatial transcriptomics with STAMapper

Recent advances in single-cell spatial transcriptomics (scST) have enabled the analysis of gene transcription levels in individual cells while preserving their spatial positions. Cell-type mapping and annotation are crucial in understanding the complex interactions between cells and their microenvironments within a spatial context. To this end, we develop a heterogeneous graph neural network, STAMapper, to transfer the cell-type labels from single-cell RNA-seq data to scST data. STAMapper captures both the expression similarity among cells and the expression relationships between cells and genes and adopts a graph attention classifier to conduct semi-supervised learning for more accurate cell-type prediction. We collected 81 scST datasets consisting of 344 slices and 16 paired scRNA-seq datasets from eight technologies and five tissues to validate the efficiency of STAMapper. STAMapper achieved the best performance on 75 out of 81 datasets compared to competing methods in accuracy. STAMapper demonstrated enhanced performance over manual annotations, particularly at the boundaries of cell clusters, enabled the unknown cell-type detection in scST data, and exhibited precise cell subtype annotations. Additionally, STAMapper provided biologically meaningful gene embeddings, facilitating the identification of shared or unique gene modules across datasets.

bioinformatics↗

bioRxiv2024

Heat Acclimation in Mice Requires Preoptic BDNF Neurons and Postsynaptic Potentiation

Heat acclimation (HA) is a key adaptive response in mammals to repeated heat exposure, essential for fitness and survival1-3. HA improves cardiovascular function, thermal comfort, and exercise capacity4, 5. However, the lack of a genetically tractable model has hindered understanding of the molecular and neural mechanisms underlying HA. Here, we show that 10 days of daily 38{degrees}C exposure lowers core body temperature (Tcore) and reduces anxiety during subsequent heat exposures in mice. HA increases brain-derived neurotrophic factor (BDNF) expression in the medial preoptic area (MPO). BDNF-expressing MPO neurons (MPOBDNF) show increased intrinsic heat sensitivity after HA. These neurons orchestrate downstream targets in the dorsomedial hypothalamus (DMH) and rostral raphe pallidus (rRPa) to mediate HA effects. BDNF, acting through its receptor tropomyosin-related kinase B (TrkB) in the DMH, facilitates the anxiolytic effect of HA by enhancing excitatory synaptic connections between MPOBDNF and DMH neurons. This study provides new insights into HA mechanisms, setting the stage for future research on heat stress reduction and exercise optimization.

neuroscience↗

bioRxiv2024

Substrate utilization and cross-feeding synergistically determine microbiome resistance to pathogen invasion

Understanding how microbiomes resist pathogen invasion remains a key challenge in natural ecosystems. Here, we combined genome-scale metabolic models with synthetic community experiments to unravel the mechanisms driving pathogen suppression. We developed curated genome-scale models for each strain, incorporating 48 common resource utilization profiles to fully capture their metabolic capacities. Trophic interactions inferred from models accurately predicted pathogen invasion outcomes, achieving an F1 score of 96% across 620 invasion tests involving diverse microbial communities and nutrient environments. Importantly, considering both substrate and metabolite features provided a more holistic understanding of pathogen suppression. In particular, cross-feeding metabolites within the native community emerged as crucial yet often overlooked predictors of community resistance, disproportionally favoring native species over invaders. This study lays the foundation for designing disease-resistant microbiomes, with broad implications for mitigating pathogen exposure in diverse environments.

ecology↗

bioRxiv2024

Structural Basis of GPCR-G Protein Pre-coupling and Activation: Insights from CCR1-Gi Complex

GPCR-mediated G protein activation cycle contains obligated step of the receptor-G protein assembly before G protein activation (pre-coupling state). However, transient nature of this pre-coupling state has prevented structural and mechanistic understanding of this essential step of G protein activation cycle. In this study, we discover that CCR1 has high level of pre-coupling state, which allows its rapid response to chemokines. Taking advantage of this observation, we uncover molecular mechanism of the pre-coupling state by solving the cryo-electron microscopy structure of the chemokine receptor CCR1 in complex with its cognate G protein (Gi) in a pre-coupled, inactivated state. This structure reveals that CCR1 adopts a conformation distinct from both its fully active and inactive states, with the G proteins 5 helix partially inserted into the receptors intracellular cavity. Notably, the C-terminal four residues of the G subunit are disordered in this pre-coupled state, contrasting with their well-defined -helical structure in the fully active complex. Functional assays demonstrate that while deletion of these four C-terminal G residues does not affect pre-coupling, it abolishes G protein activation upon agonist binding. This finding highlights the critical role of these residues in GPCR-mediated G protein activation, but not in initial recruitment. Furthermore, our studies indicate that the ability to form pre-coupled complexes is conserved among chemokine receptors, suggesting a common mechanism for rapid signal transduction in this GPCR subfamily. These results provide the first structural evidence for GPCR-G protein pre-coupling and offer molecular insights into the transition from inactive to active states. Our findings fill the long-missing gap in understanding GPCR-mediated G protein activated cycle.

biophysics↗