Biology subjects

Lai, L.

Publications and source records attributed to Lai, L..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Hypoimmunogenic human motor neurons induced from iPSCs in vivo substantially ameliorate ALS disease in large animal models

Stem cell-based therapy holds great potential for substituting degenerated motor neurons (MNs) in amyotrophic lateral sclerosis (ALS). Missing protocols for advanced differentiation of transplanted cells into MNs, immune rejection, and the lack of suitable ALS models for preclinical trials have slowed the development of effective therapies. Here, we employed multiplex genetic-editing to generate a novel human pluripotent stem cell line containing doxycycline (Dox)-inducible MNs-specific transcription factors and comprehensively modified immunomodulatory genes. We transplanted these cells into the spinal cord of ALS large animal models (SOD1G93A pigs and TIA1P362L rabbits), which faithfully recapitulate pathologies and symptoms observed in ALS patients. The transplanted cells could efficiently differentiate into functional MNs upon Dox treatment in vivo, distribute throughout the spinal cord and motor cortex via extensive migration, survive long-term without the need for immunosuppression. Notably, these MNs integrated into host neural circuits, as evidenced by their long projection of peripheral axons to target muscle and reformation of neuromuscular junctions. As result, pathologies and motor deficits were substantially ameliorated in both animal models. One Sentence SummaryHypoimmunogenic human motor neurons induced from iPSCs in vivo reform neuromuscular junctions and ameliorate ALS disease in pig and rabbit models.

neuroscience↗

bioRxiv2025

BioScientist Agent: Designing LLM-Biomedical Agents with KG-Augmented RL Reasoning Modules for Drug Repurposing and Mechanistic of Action Elucidation

Drug discovery is protracted, resource-intensive, and afflicted by attrition rates exceeding 90 %, which leaves most diseases, particularly rare or neglected indications, without effective therapies. Drug repurposing offers a cost effective alternative, yet systematic identification of novel drug indication pairs and mechanistic rationales remains hindered by the scale and heterogeneity of biomedical knowledge. We present BioScientist Agent, an end to end framework that unifies a billion-fact biomedical knowledge graph with (i) a variational graph auto-encoder for representation learning and link prediction driven drug repurposing, (ii) a reinforcement learning module that traverses the graph to recover biologically plausible mechanistic paths, and (iii) A large language model (LLM) multi-agent layer that orchestrates these components, enabling inference of target pathways for a drug disease pair, and automatic generation of coherent causal reports. In all downstream tasks, the BioScientist Agent surpasses existing state of the art baseline models across various metrics and provides mechanistic explanations consistent with the literature. Its open and modular design accelerates hypothesis generation and reduces experimental overhead in early stage discovery.

bioinformatics↗

bioRxiv2025

Comparative assessment of co-folding methods for molecular glue ternary structure prediction

Molecular glues (MGs) represent an emerging therapeutic paradigm capable of inducing or stabilizing protein-protein interactions, with broad applications in creating neomorphic interactomes and targeted protein degradation. However, current discovery efforts remain largely confined to experimental screening, while in silico rational design of MGs persists as a formidable challenge. A critical step toward rational design lies in accurate ternary complex modeling. Given the scarcity of such complexes in the Protein Data Bank for training specialized predictive models, we tested the ability of recently developed co-folding models, including AlphaFold 3, Boltz-1, Chai-1, Protenix, and RoseTTAFold All-Atom in building the complex models. We systematically curated a dataset, named MG-PDB, with 221 non-covalent MG-engaged ternary complexes. MGBench were further introduced as a comprehensive benchmark set, which comprises 88 ternary structures excluded from co-folding models training data through rigorous time-based partitioning. Our benchmark results demonstrated that AlphaFold3 achieved the best overall performance among co-folding methods, in terms of both protein-protein interaction interface prediction (50.6% success rate) and MG-protein interaction recovery (32.9% success rate). However, our homology study showed that most of their successful predictions actually stemmed from memorization. Further analysis revealed three phenomena of current co-folding methods for MG ternary structure prediction. Firstly, these methods struggle to accurately model large interaction interfaces. Secondly, their predictive accuracy is notably reduced for domain-domain complexes compared to domain-motif interactions. Lastly, they face specific challenges in modeling MG degrader complexes with sufficient accuracy. We showcased they relied on the existing interaction patterns, and highlighted the need for further improved in novel E3 ligase systems. These findings reveal fundamental gaps in existing methods to learn atomic-level interaction rules for MG-engaged ternary complex modeling. MG-PDB and MGBench provide critical resources and mechanistic insights to advance computational MG discovery. Table of Contents Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=127 SRC="FIGDIR/small/655997v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@172b19borg.highwire.dtl.DTLVardef@ea4844org.highwire.dtl.DTLVardef@12ea246org.highwire.dtl.DTLVardef@9fb4bc_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Isoform-Specific Roles of NTRK2 in Pulmonary Vascular Regeneration

Bronchopulmonary dysplasia (BPD) is a chronic lung disease in premature infants with no curative therapy, characterized by impaired alveologenesis and capillary formation. However, the molecular mechanisms underlying endothelial dysfunction, a key driver of BPD pathogenesis in human, remain poorly understood. Here, through multiomic profiling of vascular endothelial cells isolated from control and BPD patient lungs, we uncovered an expansion of general capillary endothelial cells (gCap) with aberrant expression of the neurotrophic receptor tyrosine kinase 2 (NTRK2) in BPD. Importantly, we identified a pathological NTRK2 isoform switch that dictates the regenerative capacity of gCap cells. Full-length NTRK2 (NTRK2-FL) promoted gCap regeneration in response to hyperoxic injury, whereas RBFOX2-mediated splicing of NTRK2-FL into a truncated isoform (NTRK2-T1) contributed to maladaptive responses and irreversible alveolar simplification in severe BPD cases. Restoring NTRK2-FL using lipid nanoparticle-delivered mRNA promoted angiogenesis and reversed alveolar simplification in vessel organoids and BPD-like mice. These findings identified NTRK2 isoform imbalance as a key driver of endothelial dysfunction and support isoform-specific RNA therapy as a promising strategy for vascular regeneration and repair. HIGHLIGHTS* Multiomic and spatial profiling reveal abnormal gCap subtype in human BPD lungs * NTRK2 isoform switch dictates endothelial regeneration in response to hyperoxic injury * RBFOX2 mediates splicing from NTRK2-FL to NTRK2-T1, driving irreversible alveolar damage * NTRK2-FL mRNA therapy restores vascular regeneration after injury

developmental biology↗

bioRxiv2025

Construction of Complete Telomere-to-Telomere Genome Assembly of the Rabbit Using Haploid Embryonic Stem Cells

The rabbit owns commercial importance in meat and fur production, and also has long served as a valuable animal model in biomedical research. Yet, the complete assembly of a high-quality rabbit reference genome has not been established. Here, we present a telomere-to-telomere (T2T) genome assembly of the New Zealand White (NZW) rabbit, the most complete and accurate rabbit genome to date. Using a haploid embryonic stem cells (haESCs) to overcame the challenges of homologous sequence interference and structural variation, we generate a genome with a contig N50 of 137.71 Mb, anchoring all chromosomes with only three gaps, through integrating long-read sequencing (PacBio HiFi, Oxford Nanopore), Hi-C, and Illumina data. Quality assessments reveal near-complete coverage of the BUSCO mammalian gene set, with 99.61% completeness. Notably, this complete assembly allowed for the first comprehensive annotation of the rabbit immunoglobulin loci and major histocompatibility complex region, which were previously unresolved in earlier genome versions. The NZW-T2T assembly based on haESCs not only provides a critical resource for advancing rabbit-based research, but also set a new benchmark for de novo genome assembly for other animals with complex genome.

genomics↗

bioRxiv2025

ROR2 drives right ventricular heart failure via disruption of proteostasis

BackgroundNo therapies exist to reverse right ventricular failure (RVF), and the molecular mechanisms that drive RVF remain under studied. We recently reported that the developmentally restricted noncanonical WNT receptor ROR2 is upregulated in human RVF in proportion to severity of disease. Here we test the mechanistic role of ROR2 in RVF pathogenesis. MethodsROR2 was overexpressed or knocked down in neonatal rat ventricular myocytes (NRVMs) and then characterized using confocal microscopy, RNAseq, proteomics, proteostatic functional assays, and pacing to assess contractile properties. The impact of cardiac ROR2 expression was evaluated in mice by AAV9-mediated overexpression and by AAV9-mediated delivery of shRNA to knockdown ROR2 in a pulmonary artery banded pressure overload model of RVF. ROR2-modified mice were evaluated by echocardiography, histology, and RV protein synthesis and proteasome capacity. ResultsIn NRVMs, we find that ROR2 profoundly dysregulates the coordination between protein translation and folding. This imbalance leads to excess protein clearance by the ubiquitin proteasome system (UPS) with dramatic impacts on sarcomere and cytoskeletal structure and function. Inhibiting the UPS or restoring chaperone expression is sufficient to partially rescue ROR2-induced structural and contractile deficits in cardiomyocytes. In mice, forced cardiac ROR2 expression is sufficient to disrupt proteostasis and drive RVF, while conversely ROR2 knockdown partially rescues proteostasis and RV structure and function in a pressure overload model of RVF. ConclusionsIn sum, ROR2 is a key driver of RVF pathogenesis through proteostatic disruption and, thus, provides a promising target to treat RVF.

molecular biology↗

bioRxiv2025

Target-based de novo design of cyclic peptide binders

Cyclic peptides have become a new focus in drug discovery due to their ability to bind challenging targets, including "undruggable" protein-protein interactions, with low toxicity. Despite their potential, general methods for de novo design of cyclic peptide ligands based on target protein structures remain limited. Here, we developed CYC_BUILDER, a reinforcement learning based fragment growing method for efficient assembly of peptide fragments and cyclization to generate diverse cyclic peptide binders for target proteins. CYC_BUILDER employs a Monte Carlo Tree Search (MCTS) framework to integrate seed fragment exploration, fragment fusion based peptide growth, structure optimization, evaluation and peptide cyclization. It supports peptide cyclization through both head-to-tail amide bond and disulfide bond formation. We first validated CYC_BUILDER on known protein-cyclic peptide complexes, demonstrating its ability to accurately re-generate cyclic peptide binders in terms of both sequences and binding poses. We then applied it to design cyclic peptide inhibitors for TNF, a key mediator in inflammation-related diseases. Among the nine experimentally tested designed peptides, four showed potent binding to TNF and inhibited its cellular activity. CYC_BUILDER provides an efficient tool for cyclic peptide drug design, offering significant potential for addressing challenging therapeutical targets.

biochemistry↗

bioRxiv2024

SC-MAMBA2: Leveraging State-Space Models for Efficient Single-Cell Ultra-Long Transcriptome Modeling

AO_SCPLOWBSTRACTC_SCPLOWThe rapid advancement of single-cell sequencing technology has significantly deepened our understanding of cellular heterogeneity, yet it concurrently presents substantial challenges for the unified modeling of single-cell data. Simultaneously, pre-trained foundation models have achieved notable success in domains such as natural language processing and image analysis. However, extending these models to accommodate ultra-long single-cell transcriptome sequences, characterized by an extensive number of genes, remains a formidable task. In this study, we introduce SC-MAMBA2, based on the MAMBA2 architecture, meticulously designed with a bidirectional modeling approach tailored for single-cell transcriptomics data. As the first single-cell foundation model to integrate state-space models (SSMs) underlying MAMBA2 architecture, SC-MAMBA2 features over 625 million parameters, covers more than 60,000 genes, and was pre-trained on a dataset of over 57 million cells, making it the most comprehensive solution for processing ultra-long transcriptome sequences. Extensive bench-marking across a diverse array of downstream tasks consistently demonstrates that SC-MAMBA2 surpasses state-of-the-art models, delivering superior accuracy and enhanced computational efficiency.

cell biology↗

bioRxiv2024

Immunogenicity and protective efficacy of an influenza virus-like particle-based SARS-CoV-2 hybrid vaccine candidate in rhesus macaques

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus co-infections present a heightened COVID-19 disease and hospitalization cases. Here, we studied the immunogenicity and efficacy of an influenza-A/PR8 virus-like particle (FluVLP)-based hybrid vaccine candidate displaying GPI-anchored SARS-CoV-2 receptor binding domain fused to GM-CSF and GPI-anchored interleukin-12 (FluVLP-RBD) in rhesus macaques. Animals (n=4/group) received two doses of either FluVLP or FluVLP-RBD vaccine four weeks apart and were challenged with SARS-CoV-2 (WA1/2020) infection via intranasal and intratracheal routes. We determined vaccine-induced IgG and neutralizing antibody titers in serum and their association with viral replication in the lower and upper airways (lung, throat, and nose) and lung-associated pathologies. FluVLP-RBD vaccine induced a strong binding IgG in serum against multiple SARS-CoV-2 variants (WA1/2020, Delta and Omicron; BA.1). Both vaccines induced strong influenza A/PR8-specific IgG. Following the SARS-CoV-2 challenge, all four animals in the FluVLP-RBD group showed a profound control of virus replication in all three airway compartments as early as day 2 through day 10 (day of euthanasia). This level of viral control was not observed in the FluVLP group as 2-3 animals exhibited high virus replication in all three airway compartments. The protection in the FluVLP-RBD vaccinated group correlated positively with post challenge neutralizing antibody titer. These results demonstrated that a FluVLP-based hybrid SARS-CoV-2 vaccine induces strong antibody responses against influenza-A/PR8 and multiple SARS-CoV-2 RBD variants and protects from SARS-CoV-2 replication in multiple compartments in macaques. These findings provide important insights for developing multivalent vaccine strategies for respiratory viruses. ImportanceCo-infection with multiple respiratory viruses poses a greater risk than individual infections, especially for individuals with underlying health conditions. Studies in humans consistently demonstrated that simultaneous infection with SARS-CoV-2 and influenza leads to more severe respiratory illness and an increased rate of hospitalization. Therefore, developing hybrid vaccines targeting multiple respiratory viruses is of high importance. The hybrid vaccines also help to reduce the economic and logistic burden associated with vaccine coverage, distribution and storage. Here, we evaluate the immunogenicity and effectiveness of a novel hybrid flu-SARS-CoV-2 vaccine candidate using a nonhuman primate pre-clinical model. Our findings reveal that this vaccine elicits a strong immune response against influenza and SARS-CoV-2 viruses. Importantly, it provides strong protection against SARS-CoV-2 infection and associated pathological conditions.

immunology↗

bioRxiv2024

Sodium-glucose co-transporter 2 Inhibitors Act Independently of SGLT2 to Confer Benefit for Heart Failure with Reduced Ejection Fraction in Mice

Sodium-glucose co-transporter 2 inhibitors (SGLT2i) are novel, potent heart failure medications with an unknown mechanism of action. We sought to determine if the beneficial actions of SGLT2i in heart failure were on- or off-target, and related to metabolic reprogramming, including increased lipolysis and ketogenesis. The phenotype of mice treated with empagliflozin and genetically engineered mice constitutively lacking SGLT2 mirrored metabolic changes seen in human clinical trials (including reduced blood glucose, increased ketogenesis, and profound glucosuria). In a mouse heart failure model, SGLT2i treatment, but not generalized SGLT2 knockout, resulted in improved systolic function and reduced pathologic cardiac remodeling. SGLT2i treatment of the SGLT2 knockout mice sustained the cardiac benefits, demonstrating an off-target role for these drugs. This benefit is independent of metabolic changes, including ketosis. The mechanism of action and target of SGLT2i in HF remain elusive.

physiology↗

bioRxiv2024

Transcriptome-wide identification of 5-methylcytosine by deaminase and reader protein-assisted sequencing

5-Methylcytosine (m5C) is one of the post-transcriptional modifications in mRNA and is involved in the pathogenesis of various diseases. However, the capacity of existing assays for accurately and comprehensively transcriptome-wide m5C mapping still needs improvement. Here, we develop a detection method named DRAM (deaminase and reader protein assisted RNA methylation analysis), in which deaminases (APOBEC1 and TadA-8e) are fused with m5C reader proteins (ALYREF and YBX1) to identify the m5C sites through deamination events neighboring the methylation sites. This antibody-free and bisulfite-free approach provides transcriptome-wide editing regions which are highly overlapped with the publicly available BS-seq datasets and allows for a more stable and comprehensive identification of the m5C loci. In addition, DRAM system even supports ultra-low input RNA (10ng). We anticipate that the DRAM system could pave the way for uncovering further biological functions of m5C modifications.

biochemistry↗

bioRxiv2024

All-atom protein sequence design based on geometric deep learning

The development of advanced deep learning methods has revolutionized computational protein design. Although the success rate of design has been significantly increased, the overall accuracy of de novo design remains low. Many computational sequence design approaches are devoted to recover the original sequences for given protein structures by encoding the environment of the central residue without considering atomic details of side chains. This may limit the exploration of new sequences that can fold into the same structure and restrain function design that depends on interaction details. In this study, we proposed a novel deep learning frame-work, GeoSeqBuilder, to learn the relationship between protein structure and sequence based on rotational and translational invariance by extracting the information from relative locations. We utilized geometric deep learning to fetch the spatial local geometric features from protein backbones and explicitly incorporated three-body interactions to learn the inter-residue coupling information, and then determined the central residue type. Our model recovers over 50% native residue types and simultaneously gives highly accurate prediction of side-chain conformations which gives the atomic interaction details and circumvents the dependence of protein structure prediction tools. We used the likelihood confidence logP as scoring function for sequence and structure consistence evaluation which exhibits strong correlation with TM-score, and can be applied to recognize near-native structures from protein decoys pool in protein structure prediction. We have used GeoSeqBuilder to design sequences for two proteins, including thiore-doxin and a de novo hallucinated protein. All of the 15 sequences experimentally tested can be expressed as soluble monomeric proteins with high thermal stability and correct secondary structures. We further solved one crystal structure for thioredoxin and two for the hallucinated structure and all the experimentally solved structures are in good agreement with the designed models. The two designed sequences for the hallucination structure are novel without any homologous sequences within the latest released database clust30. The ability of GeoSeqBuilder to design new sequences for given protein structures with atomic details makes it applicable, not only for de novo sequence design, but also for protein-protein interaction and functional protein design.

biophysics↗

bioRxiv2024

Lysis buffer selection guidance for mass spectrometry-based global proteomics including studies on the intersection of signal transduction and metabolism

Prerequisite for a successful proteomics experiment is a high-quality lysis of the sample of interest, resulting in a large number of identified proteins as well as a high coverage of protein sequences. Therefore, the choice of suitable lysis conditions is crucial. Many buffers were previously employed in proteomics studies, yet a comprehensive comparison of lysate preparation conditions was so far missing. In this study, we compared the efficiency of four commonly used lysis buffers, containing the agents NP40, SDS, urea or GdnHCl, in four different types of biological samples (suspension and adherent cell lines, primary mouse cells and mouse liver tissue). After liquid chromatography-mass spectrometry (LC-MS) measurement and MaxQuant analysis, we compared chromatograms, intensities, number of identified proteins and the localization of the identified proteins. Overall, SDS emerged as the most reliable reagent, ensuring stable performance and reproducibility across diverse samples. Furthermore, our data advocated for a dual-sample lysis approach, including that the resulting pellet is lysed again after the initial lysis with a urea lysis buffer and subsequently both lysates are combined for a single LC-MS run to maximize the proteome coverage. However, none of the investigated lysis buffers proved to be superior in every category, indicating that the lysis buffer of choice depends on the proteins of interest and on the biological question. Further, we demonstrated with our systematic studies the establishment of conditions that allows to perform global proteomics and affinity purification-based interactome characterization from the same lysate. In sum our results provide guidance for the best-suited lysis buffer for mass spectrometry-based proteomics depending on the question of interest.

systems biology↗

bioRxiv2024

XBB.1.5 monovalent booster improves antibody binding and neutralization against emerging SARS-CoV-2 Omicron variants

The rapid emergence of divergent SARS-CoV-2 variants has led to an update of the COVID-19 booster vaccine to a monovalent version containing the XBB.1.5 spike. To determine the neutralization breadth following booster immunization, we collected blood samples from 24 individuals pre- and post-XBB.1.5 mRNA booster vaccination ([~]1 month). The XBB.1.5 booster improved both neutralizing activity against the ancestral SARS-CoV-2 strain (WA1) and the circulating Omicron variants, including EG.5.1, HK.3, HV.1, XBB.1.5 and JN.1. Relative to the pre-boost titers, the XBB.1.5 monovalent booster induced greater total IgG and IgG subclass binding, particular IgG4, to the XBB.1.5 spike as compared to the WA1 spike. We evaluated antigen-specific memory B cells (MBCs) using either spike or receptor binding domain (RBD) probes and found that the monovalent booster largely increases non-RBD cross-reactive MBCs. These data suggest that the XBB.1.5 monovalent booster induces cross-reactive antibodies that neutralize XBB.1.5 and related Omicron variants.

immunology↗

bioRxiv2023

Comparative Analysis of SARS-CoV-2 Antigenicity across Assays and in Human and Animal Model Sera

The antigenic evolution of SARS-CoV-2 requires ongoing monitoring to judge the immune escape of newly arising variants. A surveillance system necessitates an understanding of differences in neutralization titers measured in different assays and using human and animal sera. We compared 18 datasets generated using human, hamster, and mouse sera, and six different neutralization assays. Titer magnitude was lowest in human, intermediate in hamster, and highest in mouse sera. Fold change, immunodominance patterns and antigenic maps were similar among sera. Most assays yielded similar results, except for differences in fold change in cytopathic effect assays. Not enough data was available for conclusively judging mouse sera, but hamster sera were a consistent surrogate for human first-infection sera.

bioinformatics↗

bioRxiv2023

Unraveling the role of Xist in X chromosome inactivation: insights from rabbit model and deletion analysis of exons and repeat A

X chromosome inactivation (XCI) is a dosage compensation process that aims to equalize the expression of X-linked genes between males and females. Initiation of XCI relies on Xist, which is continuously expressed in somatic cells during XCI maintenance. How Xist impacts XCI maintenance remains unclear, and its functional motifs remain unclear. In this study, we conducted a comprehensive analysis of the Xist. The results demonstrate that rabbits serve as an ideal non-primate animal model for investigating the functions of Xist in vivo. And homozygous knockout of exon 1, exon 6 and repeat A in females resulted in embryonic lethality. However, X{Delta}ReAX females with Xist expression from the intact X chromosome, did not display any abnormalities. Interestingly, there were no significant differences between females with homozygous knockout of exons 2-5 and wild-type rabbits. This suggests that exons 2, 3, 4, and 5 of Xist are less important for XCI. These insights provide valuable knowledge about the functional mechanism of Xist.

developmental biology↗

bioRxiv2023

A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans

Recently, there has been rapid development in model-induced drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models are commonly used in early drug discovery to predict drug properties. However, basic PBPK models require a large number of molecule-specific inputs from in vitro experiments, which hinders the efficiency and accuracy of these models. To address this issue, this paper introduces a new computational platform that combines ML and PBPK models. The platform predicts molecule PK profiles with high accuracy and without the need for experimental data. This study developed a whole-body PBPK model and ML models of plasma protein unbinding (fup), Caco-2 cell permeability, and total plasma clearance to predict the PK of small molecules. Pharmacokinetic profiles were simulated using a "bottom-up" PBPK modeling approach with ML inputs. Additionally, 40 compounds were used to evaluate the platforms accuracy. Results showed that the ML-PBPK model predicted the area under the concentration-time curve (AUC) with 62.5% accuracy within a 2-fold range, which was higher than using in vitro inputs with 47.5% accuracy. The ML-PBPK model platform provides high accuracy in prediction and reduces the number of experiments and time required compared to traditional PBPK approaches. The platform successfully predicts human PK parameters without in vitro and in vivo experiments and can potentially guide early drug discovery and development.

pharmacology and toxicology↗

bioRxiv2023

Two subtypes of GTPase-activating proteins coordinate tip growth and cell size regulation in Physcomitrium patens

The establishment of cell polarity is a prerequisite for many developmental processes. However, how it is achieved during tip growth in plants remains elusive. Here, we show that the RHO OF PLANTs (ROPs), ROP GUANINE NUCLEOTIDE EXCHANGE FACTORs (RopGEFs), and ROP GTPASE-ACTIVATING PROTEINs (RopGAPs) assemble into membrane domains in tip-growing cells of the moss Physcomitrium patens. The confinement of membrane domains requires redundant global inactivation of ROPs by PpRopGAPs and the PLECKSTRIN HOMOLOGY (PH) domain-containing RenGAP PpREN. Unexpectedly, PpRopGAPs and PpREN exert opposing effects on domain size and cell width upon overexpression. Biochemical and functional analyses indicate that PpRopGAPs are recruited to the membrane by active ROPs to restrict domain size through clustering, whereas PpREN rapidly inactivates ROPs and inhibits PpRopGAP-induced clustering. We propose that the activity- and clustering-based domain organization by RopGAPs and RenGAPs is a general mechanism for coordinating polarized cell growth and cell size regulation in plants. SignificanceUsing the moss Physcomitrium patens, we show that PpRopGAPs and PpRenGAP redundantly regulate tip growth by inactivating ROP GTPases and influencing their membrane organization. They display distinct GAP activities and binding capacities to ROPs and could oppositely regulate cell width when overexpressed. We propose that tip growth and cell size regulation are coordinated by two subtypes of GTPase-activating proteins that act together to maintain an optimal amount of active ROPs but reversely regulate the membrane clustering of ROPs. The involvement of functionally diverged GAPs in modulating ROP activity and localization may represent a general mechanism for cell morphology regulation in plants.

plant biology↗