Biology subjects

Gu, X.

Publications and source records attributed to Gu, X..

At least 145 records · Page 8Linked to original sources

bioRxiv2020

Adult Neurogenesis in Peripheral Nervous System

Although postnatal neurogenesis has been discovered in some regions of the peripheral nervous system (PNS), only indirect evidences indicated that some progenitors in the adult sciatic nerve and dorsal root ganglion (DRG) serve as a source of newly born sensory neurons. Here, we report the discovery of neurons and neuronal stem cells in the adult rat sciatic nerve. Lineage tracing detected a population of sciatic nerve neurons as progeny of adult neuronal stem cells. With the further finding of labeled DRG neurons in adult transgenic rats with local sciatic nerve staining, we propose a model of adult neurogenesis in the sciatic nerve in which neuronal stem cells in sciatic nerve mature as sensory neurons in adults along the sciatic nerve to DRG. This hypothesis provides a new way to understand sensory formation in adults. Those neuronal stem cells in the sciatic nerve may help to therapy of nerve trauma and disease in the future.

neuroscience↗

bioRxiv2020

Mutating PINK1 gene by paired truncated sgRNA/Cas9-D10A in Cynomolgus Monkey

Mutations of PINK1 cause early-onset Parkinsons disease (PD) with selective neurodegeneration in humans. However,current PINK1 knockout mouse and pig models are unable to recapitulate the typical neurodegenerative phenotypes observed in PD patients, indicating that it is essential to generate PINK1 disease models in non-human primates (NHPs) that are highly close to humans, to investigate the unique function of PINK1 in primate brains. Paired single guide RNA (sgRNA)/Cas9-D10A nickases and truncated sgRNA/Cas9, both enabling the reduction of the off-target effect without apparently compromising the on-target editing, are two optimized strategies in applying the CRISPR/Cas9 system to establish disease animal models. Here, we combined the two strategies and injected Cas9-D10A mRNA and two truncated sgRNAs into one-cell-stage cynomolgus zygotes to target PINK1 gene. We show precise and efficient gene editing of the target site in the three new born cynomolgus monkeys. The frame shift mutations of PINK1 in mutant fibroblasts leaded to the reduction of the mRNA, However, western-blot and immunofluorescencestaining confirmed the PINK1 proteinlevels werecomparable to that in the wild-type fibroblasts. We further reprogramed mutant fibroblast into induced pluripotent stem cells (iPSCs) and they show similar ability of differentiation into dopamine (DA) neurons. Taken together, our results showed that coinjection of Cas9-D10A nickase mRNA and sgRNA into one-cell-stage cynomolgus embryos enable the generation of human disease models in NHPs and the target editing by paired truncated sgRNA/Cas9-D10A in PINK1 gene exon 2 did not impact the protein expression.

genetics↗

bioRxiv2020

Immunogenicity of novel mRNA COVID-19 vaccine MRT5500 in mice and non-human primates

An effective vaccine to address the global pandemic of coronavirus disease 2019 (COVID-19) is an urgent public health priority1. Novel synthetic mRNA and vector-based vaccine technologies offer an expeditious development path alternative to traditional vaccine approaches. Here we describe the efforts to utilize an mRNA platform for rational design and evaluations of mRNA vaccine candidates based on Spike (S) glycoprotein of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the virus causing COVID-19. Several mRNA constructs expressing various structural conformations of S-protein, including wild type (WT), a pre-fusion stabilized mutant (2P), a furin cleavage-site mutant (GSAS) and a double mutant form (2P/GSAS), were tested in a preclinical animal model for their capacity to elicit neutralizing antibodies (nAbs). The lead 2P/GSAS candidate was further assessed in dose-ranging studies in mice and Cynomolgus macaques. The selected 2P/GSAS vaccine formulation, now designated MRT5500, elicited potent nAbs as measured in two types of neutralization assays. In addition, MRT5500 elicited TH1-biased responses in both mouse and non-human primate species, a result that helps to address a hypothetical concern regarding potential vaccine-associated enhanced respiratory diseases associated with TH2-biased responses. These data position MRT5500 as a viable vaccine candidate for clinical development against COVID-19.

immunology↗

bioRxiv2020

OpenAWSEM with Open3SPN2: a fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations

We present OpenAWSEM and Open3SPN2, new cross-compatible implementations of coarse-grained models for protein (AWSEM) and DNA (3SPN2) molecular dynamics simulations within the OpenMM framework. These new implementations retain the chemical accuracy and intrinsic efficiency of the original models while adding GPU acceleration and the ease of forcefield modification provided by OpenMMs Custom Forces software framework. By utilizing GPUs, we achieve more than a 100-fold speedup in protein and protein-DNA simulations over the existing LAMMPS-based implementations running on a CPU. We showcase the benefits of OpenMMs Custom Forces framework by devising and implementing two new potentials that allow us to address important aspects of protein folding and structure prediction and by testing the ability of the combined OpenAWSEM and Open3SPN2 to model protein-DNA binding. The first potential is used to describe the changes in effective interactions that occur as a protein becomes partially buried in a membrane. We also introduced an interaction to describe proteins with multiple disulfide bonds. Using simple pairwise disulfide bonding terms results in unphysical clustering of cysteine residues, posing a problem when simulating the folding of proteins with many cysteines. We now can computationally reproduce Anfinsens early Nobel prize winning experiments [1] by using OpenMMs Custom Forces framework to introduce a multi-body disulfide bonding term that prevents unphysical clustering. Our protein-DNA simulations show that the binding landscape is funneled towards structures that are quite similar to those found using experiments. In summary, this paper provides a simulation tool for the molecular biophysics community that is both easy to use and sufficiently efficient to simulate large proteins and large protein-DNA systems that are central to many cellular processes. These codes should facilitate the interplay between molecular simulations and cellular studies, which have been hampered by the large mismatch between the time and length scales accessible to molecular simulations and those relevant to cell biology. Author summaryThe cells most important pieces of machinery are large complexes of proteins often along with nucleic acids. From the ribosome, to CRISPR-Cas9, to transcription factors and DNA-wrangling proteins like the SMC-Kleisins, these complexes allow organisms to replicate and enable cells to respond to environmental cues. Computer simulation is a key technology that can be used to connect physical theories with biological reality. Unfortunately, the time and length scales accessible to molecular simulation have not kept pace with our ambition to study the cells molecular factories. Many simulation codes also unfortunately remain effectively locked away from the user community who need to modify them as more of the underlying physics is learned. In this paper, we present OpenAWSEM and Open3SPN2, two new easy-to-use and easy to modify implementations of efficient and accurate coarse-grained protein and DNA simulation forcefields that can now be run hundreds of times faster than before, thereby making studies of large biomolecular machines more facile.

molecular biology↗

bioRxiv2020

Evolutionary Transcriptome Analysis Based on Differentially Expressed (DE) Genes

To address how gene regulation plays a key role in phenotypic innovations through high throughput transcriptomes, it is desirable to develop statistically-sound methods that enable researchers to study the pattern of transcriptome evolution. Most methods currently available are based on the Ornstein-Uhlenbeck (OU) model that considers the stabilizing selection as the baseline model of transcriptome evolution. In this paper, we developed a new evolutionary approach, based on the genome-wide p-value profile arising from statistical testing of differentially expressed (DE) genes between species. Our current approach is focused on the estimation of transcriptome distance between species. We first establish the relationship between the evolutionary model (the Markov-chain or Poisson model) and the proportion of null hypothesis (u0), which can be used to estimate the transcriptome distance. Further, we calculate the posterior probability of a gene being DE when a p-value is given, denoted by Q=P(DE|p), and develop a simple algorithm to estimate the transcriptome distance for any number of genes in the genome. Our compute simulations showed the statistical performance of these new methods are generally satisfactory.

evolutionary biology↗

bioRxiv2020

A Statistical Framework for Evolutionary Analysis of Recurrent Somatic Mutations in Cancers

Current cancer genomics databases have accumulated millions of somatic mutations that remain to be further explored, faciltating enormous high throuput analyses to explore the underlying mechanisms that may contribute to malignant initiation or progression. In the context of over-dominant passenger mutations (unrelated to cancers), the challenge is to identify somatic mutations that are cancer-driving. Under the notion that carcinogenesis is a form of somatic-cell evolution, we developed a two-component mixture model that enables to accomplish the following analyses. (i) We formulated a quasi-likelihood approach to test whether the two-component model is significantly better than a single-component model, which can be used for new cancer gene predicting. (ii) We implemented an empirical Bayesian method to calculate the posterior probabilities of a site to be cancer-driving for all sites of a gene, which can be used for new driving site predicting. (iii) We developed a computational procedure to calculate the somatic selection intensity at driver sites and passenger sites, respectively, as well as site-specific profiles for all sites. Using these newly-developed methods, we comprehensively analyzed 294 known cancer genes based on The Cancer Genome Atlas (TCGA) database.

evolutionary biology↗

bioRxiv2020

Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity that may underly population disparities in this disease

Systemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underly the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertook a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture were identified. Nine disease loci showed clear ancestral group heterogeneity and implicated antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores performed significantly better when trained on matched ancestral data sets. These analyses help to reveal the genetic bases for disparities in SLE among ancestral groups.

genetics↗

bioRxiv2020

An insula-driven network computes decision uncertainty and promotes abstinence in chronic cocaine users

The anterior insular cortex (AIC) and its interconnected brain regions have been associated with both addiction and decision-making under uncertainty. However, the causal interactions in this uncertainty-encoding neurocircuitry and how these neural dynamics impact relapse remain elusive. Here, we used model-based fMRI to measure choice uncertainty in a motor decision task in 61 individuals with cocaine use disorder (CUD) and 25 healthy controls. CUD participants were assessed before discharge from a residential treatment program and followed for up to 24 weeks. We found that choice uncertainty was tracked by the AIC, dorsal anterior cingulate cortex (dACC), and ventral striatum (VS), across participants. Stronger activations in these regions measured pre-discharge predicted longer abstinence after discharge in individuals with CUD. Dynamic causal modelling revealed an AIC-to-dACC directed connectivity modulated by uncertainty in controls, but a dACC-to-AIC connectivity in CUD participants. This reversal was mostly driven by early-relapsers (<30 days). Furthermore, CUD individuals who displayed a stronger AIC-to-dACC excitatory connection during uncertainty encoding remained abstinent for longer periods. These findings reveal a critical role of an AIC-driven, uncertainty-encoding neurocircuitry in protecting against relapse and promoting abstinence.

neuroscience↗

bioRxiv2020

Identification and exploration of 2'-O-methylation sites in rRNA and mRNA with a novel RNase based platform

Ribose 2'-O-methylation is involved in critical biological processes, but its biological functions and significance in mRNAs remain largely unknown due to the lack of accurate and efficient identification tools. To overcome this gap, we established NJU-seq (an accurate high-throughput single-base method) and Nm-VAQ (a site-specific quantification tool). We identified thousands of new Nm sites on mRNA of human and mouse cell lines, in which 68 of 84 selected sites were further validated to be 2'-O-methylated more than 1%. Unlike rRNA, the methylated ratios of most validated mRNA Nm sites were lower than 30%. In addition, mRNA 2'-O-methylation was dynamic-changing according to the circumstance, which was presented with MHV infection. Furthermore, Nm sites of lung surgery samples revealed commonness of lung cancer pathogenesis, providing potential new diagnostic markers.

biochemistry↗

bioRxiv2020

Dynamic Behaviors of Expression Compensation between Duplicate Genes

While gene or genome duplications have provided raw genetic materials for evolutionary innovations, these events have also generated massive duplicate genes, resulting in a tremendous increase to the genetic robustness of organism. Duplicate compensation indicate functional redundancies generated by gene duplications, which are widespread in all known genomes. However, the fitness trade-offs of their mutational compensation (genetic robustness) and their role in evolutionary innovation remains largely obscure. In this paper, we discuss how we can utilize the mathematical modeling approach to predicting under which condition duplicate compensation may occur. After a critical review for the models about expression dosage, compensation, and long-term survival of duplicate genes, we highlight the importance to distinguish between Function (F)-triggered and Expression (E)-triggered mechanism of duplicate compensation. Moreover, we address three fundamental questions: (i) Why a backup duplicate can be effectively activated by any silence mutation of the dominant duplicate, but hardly by any coding mutation resulting in impaired protein function? (ii) Why a dispensable duplicate gene, i.e., knockout leads to virtually no phenotype, still remains a great deal of selective constraints in the coding region? And (iii) under which condition expression subfunctionalization between duplicates is reversible (dosage-sharing) or irreversible (long-term survival)?

evolutionary biology↗

bioRxiv2020

Distinguish between Duplication of Essential Genes and Duplication of Dispensable Genes

When a dispensable gene is duplicated (ancestral dispensability), genetic buffering and duplicate compensation together maintain the gene dispensability, whereas duplicate compensation is the only mechanism when an essential gene is duplicated (ancestral essentiality). To explore the distinct pattern of genetic robustness between these evolutionary scenarios, we formulated a probabilistic model with some biologically reasonable assumptions for analyzing a set of duplicate pairs with three possible states: double-dispensable (DD), semi-dispensable (one dispensable one essential, DE) or double-essential (EE). A computational pipeline is then developed to predict the distribution of three states (DD, DE and EE) conditional of ancestral dispensability or essentiality, respectively. This model was applied to yeast duplicate pairs from a whole-genome duplication, revealing that the process of essentiality of those duplicated from essential genes could be significantly higher than that of those duplicated from dispensable genes. We thus proposed a hypothesis that the process of sub-functionalization may be faster than neo-functionalization. Our analysis may provide some new insights about the role of duplicate compensation on genetic robustness.

evolutionary biology↗

bioRxiv2020

Evolutionary Distance of Gene-Gene Interactions: Estimation under Statistical Uncertainty

Consider the functional interaction of gene A to an interaction subject X; for instance, it is the gene-gene interaction if X represents for a gene, or gene-tissue interaction (expression status) if X for a tissue. In the simplest case, the status of this A-X interaction is r=1 if they are interacted, or r=0 otherwise. A fundamental problem in molecular evolution is, given two homologous (orthologous or paralogous) genes A and B, to what extent their functional overlapping could be by the means of interaction networks. Given a set of interaction subjects (X1, ... XN), it is straightforward to calculate the interaction distance (IAB) between genes A and B, by a Markov-chain model. However, since the high throughput interaction data always involve a high level of noises, reliable inference of r=1 or r=0 for each gene remains a big challenge. Consequently, the estimated interaction distance (IAB) is highly sensitive to the cutoff of interaction inference which is subject to some arbitrary. In this paper we will address this issue by developing a statistical method for estimating IAB based on the p-values (significant levels). Computer simulations are carried out to evaluate the performance of different p-value transformations against the uncertainty of interaction networks.

evolutionary biology↗

bioRxiv2020

The PK/PD Integration and Resistance of Ti lmi cosin Against Mycoplasma hyopneumoniae

Mycoplasma hyopneumoniae is the major pathogen causing enzootic pneumonia in pigs. M. hyopneumoniae infection can lead to considerable economic losses in the pig-breeding industry. Here, this study established a first-order absorption, one-compartment model to study the relationship between the pharmacokinetics/pharmacodynamics (PK/PD) index of tilmicosin against M. hyopneumoniae in vitro. We simulated the drug concentration of timicosin in the fluid lining the lung epithelia of pigs. The minimum inhibitory concentration (MIC) of tilmicosin against M. hyopneumoniae with an inoculum of 106 CFU/mL was 1.6 g/mL using the microdilution method. Static time-kill curves showed that, if the drug concentration >1 MIC, the antibacterial effect showed different degrees of inhibition. At 32 MIC, the amount of bacteria decreased by 3.16 log10 CFU/mL, thereby achieving a mycoplasmacidal effect. The M. hyopneumoniae count was reduced from 3.61 to 5.11 log10 CFU/mL upon incubation for 96 h in a dynamic model with a dose of 40-200 mg, thereby achieving mycoplasmacidal activity. The peak concentration by MIC (Cmax/MIC) and the area under the concentration-time curve over 96 h divided by the MIC (AUC0-96 h/MIC) were the best-fit PK/PD parameters for predicting the antibacterial activity of tilmicosin against M. hyopneumoniae (R2 = 0.99), suggesting that tilmicosin had concentration-dependent activity. The estimated value for Cmax/MIC and AUC0-96 h/MIC for 2log10 (CFU/mL) reduction and 3log10 (CFU/mL) reduction from baseline was 1.44 and 1.91, and 70.55 h and 96.72 h, respectively. Four M. hyopneumoniae strains (M1-M4) with reduced sensitivity to tilmicosin were isolated from the four dose groups. The susceptibility of these strains to tylosin, erythromycin and lincomycin was also reduced significantly. For sequencing analyses of 23S rRNA, an acquired A2058G transition in region V was found only in resistant M. hyopneumoniae strains (M3, M4). In conclusion, in an in vitro model, the effect of tilmicosin against M. hyopneumoniae was concentration-dependent and had a therapeutic effect. These results will help to design the optimal dosing regimen for tilmicosin in M. hyopneumoniae infection, and minimize the emergence of resistant bacteria.

pharmacology and toxicology↗

bioRxiv2020

Resistance to decitabine and 5-azacytidine emerges from adaptive responses of the pyrimidine metabolism network

Mechanisms-of-resistance to decitabine and 5-azacytidine, mainstay treatments for myeloid malignancies, require investigation and countermeasures. Both are nucleoside analog pro-drugs processed by pyrimidine metabolism into a nucleotide analog that depletes the key epigenetic regulator DNA methyltranseferase 1 (DNMT1). We report here that DNMT1 protein, although substantially depleted (~50%) in patients bone marrows at response, rebounded at relapse, and explaining this, we found pyrimidine metabolism gene expression shifts averse to the processing of each pro-drug. The same metabolic shifts observed clinically were rapidly recapitulated in leukemia cells exposed to the pro-drugs in vitro. Pyrimidine metabolism is a network that senses and preserves nucleotide balances: Decitabine, a deoxycytidine analog, and 5-azacytidine, a cytidine analog, caused acute and distinct nucleotide imbalances, by off-target inhibition of thymidylate synthase and ribonucleotide reductase respectively. Resulting expression changes in key pyrimidine metabolism enzymes peaked 72-96 hours later. Continuous pro-drug exposure stabilized metabolic shifts generated acutely, preventing DNMT1-depletion and permitting exponential leukemia out-growth as soon as day 40. Although dampening to activity of the pro-drug initially applied, adaptive metabolic responses primed for activity of the other. Hence, in xenotransplant models of chemorefractory AML, alternating decitabine with 5-azacytidine, timed to exploit compensating metabolic shifts, and addition of an inhibitor of a catabolic enzyme induced by decitabine/5-azacytidine, extended DNMT1-depletion and time-to-distress by several months versus either pro-drug alone. In sum, resistance to decitabine and 5-azacytidine emerges from adaptive responses of the pyrimidine metabolism network; these responses can be anticipated and thus exploited. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/958405v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@e3f77aorg.highwire.dtl.DTLVardef@8caaa4org.highwire.dtl.DTLVardef@117236dorg.highwire.dtl.DTLVardef@16ee98_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2020

Tracing Evolutionary Ages of Cancer-Driving Sites by Cancer Somatic Mutations

Evolutionary understanding of cancer genes may provide insights on the nature and evolution of complex life and the origin of multicellularity. In this study, we focus on the evolutionary ages of cancer-driving sites, and try to explore to what extent the amino acids of cancer-driving sites can be traced back to the most recent common ancestor (MRCA) of the gene. According to gene phylostraigraphy analysis, we use the definition of gene age (tg) by the most ancient phylogenetic position that can be traced back, in most cases based on the large-scale homology search of protein sequences. Our results are shown that the site-age profile of cancer-driving sites of TP53 is correlated with the number of cancer types the somatic mutations may affect. In general, those amino acid sites mutated in most cancer types are much ancient. These sites frequently mutated in cancerous cells are possibly responsible for carcinogenesis; some may be very important for basic growth of single-cell organisms, and others may contribute to complex cell regulation of multicellular organisms. The further cancer genomics analysis also indicates that ages of cancer-driving sites are ancient but may have a broad range in early stages of metazoans.

evolutionary biology↗

bioRxiv2020

A New Model of Genetic Variation and Evolution Evaluates Relative Impacts of Background Selections and Selective Sweeps

Intra-population genetic variation and interspecies divergence in chromosome regions can be considerably affected by different local recombination rates. There are two models: (i) the selective sweeps that reduces the genetic diversity at linked sites and elevates the divergence rate; and (ii) the background selection that reduces the genetic diversity at linked sites and divergence rate. An intriguing question, yet highly controversial, is which one is dominant. In this paper, I develop a framework of generalize background selection, formulated by a diffusion model with two killing functions: the one associated with (negative) background selection is the rate to stop a fixation process of a mutation randomly, and the other associated with positive background selection (selective sweep) is the rate to stop a loss process of a mutation randomly. A simple relationship between the level of reduced diversity and the rate of divergence is derived, depending on the strength of generalized background selection (G) and the proportion of positive background selection ({beta}). We analyzed the interspecies divergence and intra-population diversity in low-recombination regions of three organisms (fruitfly, soybean and human). Strikingly, all datasets demonstrated the dominance of (negative) background selection, and the positive background selection (selective sweeps) only has a small contribution ({beta}[~]10%). However, our analysis rejects the notion of {beta}=0, namely, a complete negative background selection is unlikely. These findings may shed some lights on the long-term debates around Neutral Theory.

evolutionary biology↗

bioRxiv2019

In vivo studies of glucagon secretion by human islets transplanted in mice

Relatively little is known about regulated glucagon secretion by human islet cells compared to insulin secretion from {beta} cells, despite conclusive evidence of dysfunction in both cell types in diabetes mellitus. Distinct insulin sequences in humans and mice permit in vivo studies of {beta} cell regulation after human islet transplantation in immunocompromised mice, whereas identical glucagon sequences prevent analogous in vivo measures of glucagon output from human cells. We used CRISPR/Cas9 genome editing to remove glucagon-encoding codons 2-29 in immunocompromised (NSG) mice, preserving production of other proglucagon-derived hormones, like Glucagon-like-peptide 1. These NSG-Glucagon knockout (NSG-GKO) mice had phenotypes associated with glucagon signaling deficits, including hypoglycemia, hyperaminoacidemia, hypoinsulinemia, and islet cell hyperplasia. NSG-GKO host metabolic and islet phenotypes reverted after human islet transplantation, and human islets retained regulated glucagon and insulin secretion. NSG-GKO mice provide an unprecedented resource to investigate unique, species-specific human cell regulation in vivo.

physiology↗

bioRxiv2019

A specific exocytic pathway is essential for polarization of PIN proteins in the establishment and maintenance of auxin gradients.

O_LIThe plant hormone auxin and its directional intercellular transport plays a major role in diverse aspects of plant growth and development. The establishment of auxin gradients in plants requires asymmetric distribution of members of the auxin efflux carrier PIN-FORMED (PIN) protein family to the plasma membrane. An endocytic pathway regulates the recycling of PIN proteins between the plasma membrane and endosomes, providing a mechanism for dynamic localization. C_LIO_LIN-ethylmaleimide-sensitive factor adaptor protein receptors (SNAP receptors, SNAREs) mediate fusion between vesicles and target membranes and are classed as Q- or R-SNAREs based on their sequence. We analysed gain- and loss-of-function mutants, dominant negative transgenics and protein localization of the Arabidopsis R-SNARE VAMP714 to understand its function. C_LIO_LIWe demonstrate that VAMP714 is essential for the insertion of PINs into the plasmamembrane, for polar auxin transport, and for root gravitropism and morphogenesis. VAMP714 gene expression is upregulated by auxin, and the VAMP714 protein co-localizes with ER and Golgi vesicles and with PIN proteins at the plasma membrane. C_LIO_LIIt is proposed that VAMP714 mediates the delivery of PIN-carrying vesicles to the plasma membrane, and that this forms part of a positive regulatory loop in which auxin activates a VAMP714-dependent PIN/auxin transport system to control development. C_LI

plant biology↗