Biology subjects

Chen, L.

Publications and source records attributed to Chen, L..

At least 919 records · Page 51Linked to original sources

bioRxiv2019

Enhancing Gesture Decoding Performance Using Signals from Posterior Parietal Cortex: A Stereo-Electroencephalograhy (SEEG) Study

ObjectiveHand movement is a crucial function for humans daily life. Developing brain-machine interface (BMI) to control a robotic hand by brain signals would help the severely paralyzed people partially regain the functional independence. Previous intracranial electroencephalography (iEEG)-based BMIs towards gesture decoding mostly used neural signals from the primary sensorimotor cortex while ignoring the hand movement related signals from posterior parietal cortex (PPC). Here, we propose combining iEEG recordings from PPC with that from primary sensorimotor cortex to enhance the gesture decoding performance of iEEG-based BMI. ApproachStereoelectroencephalography (SEEG) signals from 25 epilepsy subjects were recorded when they performed a three-class hand gesture task. Across all 25 subjects, we identified 524, 114 and 221 electrodes from three regions of interest (ROIs), including PPC, postcentral cortex (POC) and precentral cortex (PRC), respectively. Based on the time-varying high gamma power (55-150 Hz) of SEEG signal, both the general activation in the task and the fine selectivity to gestures of each electrode in these ROIs along time was evaluated by the coefficient of determination r2. According to the activation along time, we further assessed the first activation time of each ROI. Finally, the decoding accuracy for gestures was obtained by linear support vector machine classifier to comparatively explore if the PPC will assist PRC and POC for gesture decoding. Main ResultsWe find that a majority(L: >60%, R: >40%) of electrodes in all the three ROIs present significant activation during the task. A large scale temporal activation sequence exists among the ROIs, where PPC activates first, PRC second and POC last. Among the activated electrodes, 15% (PRC), 26% (POC) and 4% (left PPC) of electrodes are significantly selective to gestures. Moreover, decoding accuracy obtained by combining the selective electrodes from three ROIs together is 5%, 3.6%, and 8% higher than that from only PRC and POC when decoding features across, before, and after the movement onset, were used. SignificanceThis is the first human iEEG study demonstrating that PPC contains neural information about fine hand movement, supporting the role of PPC in hand shape encoding. Combining PPC with primary sensorimotor cortex can provide more information to improve the gesture decoding performance. Our results suggest that PPC could be a rich neural source for iEEG-based BMI. Our findings also demonstrate the early involvement of human PPC in visuomotor task and thus may provide additional implications for further scientific research and BMI applications.

neuroscience↗

bioRxiv2019

Protein adlayer thickness on colloidal nanoparticle determined by Rayleigh-Gans-Debye approximation

Reference materials (RM)-assisted Rayleigh-Gans-Debye approximation (rm-RGDA) has been developed and used to in situ determine the size and thickness of the adlayer on the particles in solution. The particle size determined by rm-RGDA is quite close to that measured by electron microscopy but significantly smaller than that measured by DLS. The BSA adlayer absorbed on PS50, PS100 and SiO2 NPs is 3.3, 0.9 and 1.2 nm, respectively, and close to those observed by SEM, which is 4.6, 1.3 and 3.8 nm, respectively. The FTIR analysis results show that the BSA absorbed on larger particles or hydroxyl-abundant surface, e.g. PS100 and SiO2 NPs can lose its secondary structure, e.g. -helix, to a great extent and that absorbed on a more curve surface, e.g. smaller PS50 particles can largely preserve its secondary structure as its free state. The measurement results show the curvature of the NPs is closely related to the structure change of the adsorbed protein. This method provide a facile and new approach to measure the size and its adlayer change of the hybrid and core-shell structured nanoparticles in a wide range of wavelength. SIGNIFICANCEQuantitative study on the adsorption of the protein on colloidal nanoparticles is an important approach to understand the biophysical effect, compared with other ex situ methods such as TEM and SEM, where the specimen are undergone pre-processing and no longer the original state in measurement. It is, therefore, a big challenge. In order to cope with this challenge, UV-vis based RGDA has been developed and applied to in situ measure the size of the dispersed colloidal nanoparticles and their protein adlayer thickness, where the protein adlayer thickness on the colloidal nanoparticles can be easily determined. We believe this method provide a facile and sensitive way to in situ measure the dimension change of hybrid colloidal nanoparticles.

biophysics↗

bioRxiv2019

Characterization of Isoforms of the Ovine Granulocyte Colony Stimulating Factor

The granulocyte colony-stimulating factor (GCSF) regulates the maturation, proliferation, and differentiation of precursor cells of neutrophilic granulocytes, and has been widely studied in several species. To investigate the function of variants of sheep GCSF (sGCSF), this study compared difference in their mRNA expression levels. Both the activity and mRNA expression level of GCSFv2 were higher than those of GCSFv1. Their sequences were aligned, which showed that they had the highest homology with bovine GCSF. Then, predicted ovine GCSF isoforms and their constant C-terminals were cloned and expressed, which were stably expressed in mammalian cells. After purification, all GCSF functions were different both in vitro and in vivo, and the GCSF C-terminal was best. These results indicated that the ability to stimulate both the proliferation and differentiation of progenitor cells and to activate the maturation of neutrophils could be used for research of efficacious non-antibiotic protein drugs. Furthermore, GCSF can be used as candidate target of genetic breeding to specifically improve sheep immunity.

genetics↗

bioRxiv2019

Transposon-mediated telomere destabilization: a driver of genome evolution in the blast fungus

Magnaporthe oryzae is a filamentous ascomycete fungus that causes devastating diseases of crops that include rice and wheat, and a variety of turf, forage and wild grasses. Strains from ryegrasses possess highly stable chromosome ends that undergo frequent rearrangements during vegetative growth in culture and in planta. Instability is associated with the presence of two related retrotransposons (Magnaporthe oryzae Telomeric Retrotransposons - MoTeRs) inserted within the telomere repeat tracts. The objective of the present study was to determine the mechanisms by which MoTeRs promote telomere instability. Targeted cloning, restriction mapping, and sequencing of both parental and novel telomeric restriction fragments, along with MinION sequencing of DNA from three single-spore cultures, allowed us to document the molecular alterations for 109 newly-formed telomeres. Rearrangement events included truncations of subterminal rDNA sequences; acquisition of MoTeR insertions by "plain" telomeres; insertion of the MAGGY retrotransposons into MoTeR arrays; expansion and contraction of subtelomeric tandem repeats; MoTeR truncations; duplication and terminalization of internal sequences; and breakage at long, interstitial telomeres generated during MoTeR insertion. Together, our data show that when MoTeRs invade the telomeres, they can dramatically perturb the integrity of chromosome ends, leading to the generation of unprotected DNA termini whose repair has the potential to generate chromosome alterations that extend well into the genome interior.

genomics↗

bioRxiv2019

A Plausible Accelerating Function of Intermediate States in Cancer Metastasis

Epithelial-to-mesenchymal transition (EMT) is a fundamental cellular process and plays an essential role in development, tissue regeneration, and cancer metastasis. Interestingly, EMT is not a binary process but instead proceeds with multiple partial intermediate states. However, the functions of these intermediate states are not fully understood. Here, we focus on a general question about how the number of partial EMT states affects cell transformation. First, by fitting a hidden Markov model of EMT with experimental data, we propose a statistical mechanism for EMT in which many unobservable microstates may exist within one of the observable macrostates. Furthermore, we find that increasing the number of intermediate states can accelerate the EMT process and that adding parallel paths or transition layers accelerates the process even further. Last, a stabilized intermediate state traps cells in one partial EMT state. This work advances our understanding of the dynamics and functions of EMT plasticity during cancer metastasis.

systems biology↗

bioRxiv2019

A Versatile Polypharmacology Platform Promotes Cytoprotection and Viability of Human Pluripotent and Differentiated Cells

Clinical translation of human pluripotent stem cells (hPSCs) requires advanced strategies that ensure safe and robust long-term growth and functional differentiation. Pluripotent cells are capable of extensive self-renewal, yet remain highly sensitive to environmental perturbations in vitro, posing challenges to their therapeutic use. Here, we deployed innovative high-throughput screening strategies to identify a small molecule cocktail that dramatically improves viability of hPSCs and their differentiated progeny. We discovered that the combination of Chroman 1, Emricasan, Polyamines, and Trans-ISRIB (CEPT) enhanced cell survival of genetically stable hPSCs by simultaneously blocking several stress mechanisms that otherwise compromise cell structure and function. In proof-of-principle experiments we then demonstrated the strong improvements that CEPT provided for several key applications in stem cell research, including routine cell passaging, cryopreservation of pluripotent and differentiated cells, embryoid body and organoid formation, single-cell cloning, genome editing, and new iPSC line generation. Thus, CEPT represents a unique polypharmacology strategy for comprehensive cytoprotection, providing a new rationale for efficient and safe utilization of hPSCs. Conferring cell fitness by multi-target drug combinations may become a common approach in cryobiology, drug development, and regenerative medicine.

cell biology↗

bioRxiv2019

Protein Phosphatase 1 activity controls a balance between collective and single cell modes of migration

Collective cell migration is central to many developmental and pathological processes. However, the mechanisms that keep cell collectives together and coordinate movement of multiple cells are poorly understood. Using the Drosophila border cell migration model, we find that Protein phosphatase 1 (Pp1) activity controls collective cell cohesion and migration. Inhibition of Pp1 causes border cells to round up, dissociate, and move as single cells with altered motility. We present evidence that Pp1 promotes proper levels of cadherin-catenin complex proteins at cell-cell junctions within the cluster to keep border cells together. Pp1 further restricts actomyosin contractility to the cluster periphery rather than at internal cell-cell contacts. We show that the myosin phosphatase Pp1 complex, which inhibits non-muscle myosin-II (Myo-II) activity, coordinates border cell shape and cluster cohesion. Given the high conservation of Pp1 complexes, this study identifies Pp1 as a major regulator of collective versus single cell migration.

developmental biology↗

bioRxiv2019

Selective targeting of an oncogenic KRAS mutant allele by CRISPR/Cas9 induces efficient tumor regression

BackgroundKRAS is one of the most frequently mutated oncogenes in human cancers, but its activating mutations have remained undruggable due to its picomolar affinity for GTP/GDP and its smooth protein structure resulting in the absence of known allosteric regulatory sites. ResultsWith the goal of treating mutated KRAS-driven cancers, two CRISPR systems, CRISPR-SpCas9 genome-editing system and transcription-regulating system dCas9-KRAB, were developed to directly deplete KRAS mutant allele or to repress its transcription in cancer cells, respectively, through guide RNA specifically targeting the mutant but not wild-type allele. The effect of in vitro proliferation and cell cycle on cancer cells as well as in vivo tumor growth was examined after delivery of Cas9 system. SpCas9 and dCas9-KRAB systems with sgRNA targeting the mutant allele both blocked the expression of mutant KRAS gene, leading to an inhibition of cancer cell proliferation. Local adenoviral injections using SpCas9 and dCas9-KRAB systems both suppressed tumor growth in vivo. The gene-depletion system (SpCas9) performed more effectively than the transcription-suppressing system (dCas9-KRAB) on tumor inhibition. Application of both Cas9 systems to wild-type KRAS tumor cells did not affect cell proliferation in vitro and in vivo. Furthermore, through bioinformatic analysis of 31555 SNP mutations of the top 20 cancer driver genes, we showed that our mutant-specific editing strategy could be extended to a list of oncogenic mutations with high editing potentials, and this pipeline can be applied to analyze the distribution of PAM sequence in the genome to survey the best targets for other editing purpose. ConclusionsWe successfully developed both gene-depletion and transcription-suppressing systems to specifically target an oncogenic mutant allele of KRAS which led to significant tumor regression. It provides a promising strategy for the treatment of tumors with driver gene mutations.

genetics↗

bioRxiv2019

Optimal Multichannel Artifact Prediction and Removal for Brain Machine Interfaces and Neural Prosthetics

Neural implants that electrically stimulate neural tissue such as deep brain stimulators, cochlear implants (CI), and vagal nerve stimulators are becoming the routine treatment options for various diseases. Optimizing electrical stimulation paradigms requires closed-loop stimulation using simultaneous recordings of evoked neural activity in real time. Stimulus-evoked artifacts at the recording site are generally orders of magnitude larger than the neural signals, which challenge the interpretation of evoked neural activity. We developed a generalized artifact removal algorithm that can be applied in a variety of neural recording modalities. The procedure leverages known electrical stimulation currents to derive optimal filters that are used to predict and remove artifacts. We validated the procedure using paired recordings and electrical stimulation from sciatic nerve axons, high-rate bilateral CI stimulation, and concurrent multichannel stimulation in auditory midbrain and recordings in auditory cortex. We demonstrate a vast enhancement in the quality of recording even for high-throughput multi-site stimulation with typical improvements in the signal-to-noise ratio between 20-40 dB. The algorithm is efficient, can be scaled to arbitrary number of sites, and is applicable in range of recording modalities. It has numerous benefits over existing approaches and thus should be valuable for emerging neural recording and stimulation technologies.

neuroscience↗

bioRxiv2019

Systematic Establishment of Robustness and Standards in Patient-Derived Xenograft Experiments and Analysis

Patient-Derived Xenografts (PDXs) are tumor-in-mouse models for cancer. PDX collections, such as those supported by the NCI PDXNet program, are powerful resources for preclinical therapeutic testing. However, variations in experimental design and analysis procedures have limited interpretability. To determine the robustness of PDX studies, the PDXNet tested temozolomide drug response for three pre-validated PDX models (sensitive, resistant, and intermediate) across four blinded PDX Development and Trial Centers (PDTCs) using independently selected SOPs. Each PDTC was able to correctly identify the sensitive, resistant, and intermediate models, and statistical evaluations were concordant across all groups. We also developed and benchmarked optimized PDX informatics pipelines, and these yielded robust assessments across xenograft biological replicates. These studies show that PDX drug responses and sequence results are reproducible across diverse experimental protocols. Here we share the range of experimental procedures that maintained robustness, as well as standardized cloud-based workflows for PDX exome-seq and RNA-Seq analysis and for evaluating growth.

cancer biology↗

bioRxiv2019

A pentylenetetrazole-induced kindling zebrafish larval model for evoked recurrent seizures

BackgroundTransient pentylenetetrazol (PTZ) treatment on zebrafish larvae has been widely accepted a promising animal model for human epilepsy. However, this model is not ideal due to its acuteness and lack of recurrent seizures, which are the key feature of epilepsy in human disease. It is important to develop a more sensitive zebrafish model for epilepsy with well-controlled, predictable, recurrent seizures.\n\nNew MethodThe new method includes an experimental setup and a treatment protocol. The setup tracks the locomotion activity of up to 48 larvae simultaneously, while a visual stimulus can be presented to each of the 48 animals individually. The protocol treated the larvae through a water bath in 5 mM PTZ while being stimulated with rotating grating stimuli for 1 hour/day from 5 to 7 days postfertilization.\n\nResultsThe setup captured the locomotion activity of zebrafish larvae during visual stimulation. The new protocol generated recurrent responses after flashing lights 4 hours post PTZ treatment. The effects could be suppressed by the anti-epileptic drug valproic acid. The characteristics of the visual stimulus play a major role in this kindling model.\n\nComparisons with Existing MethodsWe compared the proposed method with the transient PTZ model and confirmed that the flashing-light-evoked recurrent seizure is a new feature in addition to the transient changes.\n\nConclusionsThe new method generated non-drug-triggered predictable recurrent seizures in response to intermittent photic stimulation in zebrafish larvae and may serve as a sensitive method for anti-epileptic drug screening or a new research protocol in epilepsy research.

neuroscience↗

bioRxiv2019

I-Impute: a self-consistent method to impute single cell RNA sequencing data

Single-cell RNA-sequencing (scRNA-seq) is essential for the study of cell-specific transcriptome landscapes. The scRNA-seq techniques capture merely a small fraction of the gene due to \"dropout\" events. When analyzing with scRNA-seq data, the dropout events receive intensive attentions. Imputation tools are proposed to estimate the values of the dropout events and de-noise the data. To evaluate the imputation tools, researchers have developed different clustering criteria by incorporating the ground-truth cell subgroup labels. There lack measurements without cell subgroup knowledge. A reliable imputation tool should follow the \"self-consistency\" principle; that is, the tool reports the results only if it finds no further errors or dropouts from the data. Here, we propose \"self-consistency\" as an explicit evaluation criterion; also, we propose I-Impute, a \"self-consistent\" method, to impute scRNA-seq data. I-Impute lever-ages continuous similarities and dropout probabilities and refines the data iteratively to make the final output self-consistent. On the in silico data sets, I-Impute exhibited the highest Pearson correlations for different dropout rates consistently compared with the state-of-art methods SAVER and scImpute. On the datasets of 90.87%, 70.98% and 56.65% zero rates, I-Impute exhibited the correlations as 0.78, 0.90, and 0.94, respectively, between ground truth entries and predicted values, while SAVER exhibited the correlations as 0.58, 0.79 and 0.88, respectively and scImpute exhibited correlations as 0.65, 0.86, and 0.93, respectively. Furthermore, we collected three wetlab datasets, mouse bladder cells dataset, embryonic stem cells dataset, and aortic leukocyte cells dataset, to evaluate the tools. I-Impute exhibited feasible cell subpopulation discovery efficacy on all the three datasets. It achieves the highest clustering accuracy compared with SAVER and scImpute; that is, I-Impute displayed the adjusted Rand indices of the three datasets as 0.61, 0.7, 0.52, which improved the indices of SAVER by 0.01 to 0.17, and improved the indices of scImpute by 0.19 to 0.4. Also, I-impute promoted normalized mutual information of the three datasets by 0.01 to 0.09 comparing with SAVER, and by 0.15 to 0.34 comparing with scImpute. I-Impute exhibits robust imputation ability and follows the \"self-consistency\" principle. It offers perspicacity to uncover the underlying cell subtypes in real scRNA-Seq data. Source code of I-Impute can be accessed at https://github.com/xikanfeng2/I-Impute.

bioinformatics↗

bioRxiv2019

Coordinate Enhancer Reprogramming by GATA3 and AP1 Promotes Phenotypic Plasticity to Achieve Breast Cancer Endocrine Resistance

Acquired therapy resistance is a major problem for anticancer treatment, yet the underlying molecular mechanisms remain unclear. Using an established breast cancer cellular model for endocrine resistance, we show that hormone resistance is associated with enhanced phenotypic plasticity, indicated by a general downregulation of luminal/epithelial differentiation markers and upregulation of basal/mesenchymal invasive markers. Our extensive omics studies, including GRO-seq on enhancer landscapes, demonstrate that the global enhancer gain/loss reprogramming driven by the differential interactions between ER and other oncogenic transcription factors (TFs), predominantly GATA3 and AP1, profoundly alters breast cancer transcriptional programs. Our functional studies in multiple biological systems including culture and xenograft models of MCF7 and T47D lines support a coordinate role of GATA3 and AP1 in enhancer reprogramming that promotes phenotypic plasticity and endocrine resistance. Collectively, our study implicates that changes in TF-TF and TF-enhancer interactions can lead to genome-wide enhancer reprogramming, resulting in transcriptional dysregulations that promote plasticity and cancer therapy-resistance progression.

cancer biology↗

bioRxiv2019

Predicting protein subcellular location using learned distributed representations from a protein-protein network

Functions of proteins are in general related to their subcellular locations. To identify the functions of a protein, we first need know where this protein is located. Interacting proteins tend to locate in the same subcellular location. Thus, it is imperative to take the protein-protein interactions into account for computational identification of protein subcellular locations.In this study, we present a deep learning-based method, node2loc, to predict protein subcellular location. node2loc first learns distributed representations of proteins in a protein-protein network using node2vec, which acquires representations from unlabeled data for downstream tasks. Then the learned representations are further fed into a recurrent neural network (RNN) to predict subcellular locations. Considering the severe class imbalance of different subcellular locations, Synthetic Minority Over-sampling Technique (SMOTE) is applied to artificially boost subcellular locations with few proteins.We construct a benchmark dataset with 16 subcellular locations and evaluate node2loc on this dataset. node2loc yields a Matthews correlation coefficient (MCC) value of 0.812, which outperforms other baseline methods. The results demonstrate that the learned presentations from a protein-protein network have strong discriminate ability for classifying protein subcellular locations and the RNN is a more powerful classifier than traditional machine learning models. node2loc is freely available at https://github.com/xypan1232/node2loc.

bioinformatics↗

bioRxiv2019

Variations of gut microbiome profile under different storage conditions and preservation periods: A multi-dimensional evaluation

Gut dysbiosis contributes to the development of various human diseases. There are thousands of publications per year for investigating the role of gut microbiota in development of various diseases. However, emerging evidence has indicated data inconsistency between different studies frequently, but gained very little attention by scientists. There are many factors that can cause data variation and inconsistency during the process of microbiota study, in particular, sample storage conditions and subsequent sequencing process. Here, we systemically evaluated the impacts of six fecal sample storage conditions (including -80 {degrees}C, -80 {degrees}C with 70% ethanol (ET_-80 {degrees}C), 4{degrees}C with 70% ethanol (ET_4{degrees}C), and three commercial storage reagents including OMNIgene*GUT OMR-200 (GT), MGIEasy (MGIE), and Longsee (LS)), storage periods (1, 2 weeks or 6 months), and sequencing platform on gut microbiome profile using 16S rRNA gene sequencing. Our results suggested that -80{degrees}C is acceptable for fecal sample storage, and the addition of 70% ethanol offers some benefits. Meanwhile, we found that samples in ET_4 {degrees}Cand GT reagents are comparable, both introduced multi-dimensional variations. The use of MGIE resulted in the least alteration, while the greatest changes were observed in samples stored in LS reagents during the whole experiment. Finally, we also confirmed that variations caused by storage condition were larger than that of storage time and sequencing platform.\n\nIMPORTANCEIn the current study, we performed a multi-dimensional evaluation on the variations introduced by types of storage conditions, preservation period and sequencing platform on the basis of data acquired from 16S rRNA gene sequencing. The efficacy of preservation methods was comprehensively evaluated by DNA yield and quality, and {beta} diversity, relative abundance of the dominant bacteria and functional bacteria associated with SCFAs producing and BAs metabolism. Our results confirmed that variations introduced by storage condition were larger than that of storage periods and sequencing platform. Collectively, our study provided a comprehensive view to the impacts of storage conditions, storage times, and sequencing platform on gut microbial profile.

microbiology↗

bioRxiv2019

MACF1 Facilitates SMAD7 Nuclear Translocation to Drive Bone Formation in Mice

MACF1 is a large crosslinker that contributes to cytoskeleton integrity and cell differentiation. Loss of MACF1 impairs multiple cellular functions in neuron development and epidermal migration, and is the molecular basis for many diseases such as heart failure and Parkinsons disease. MACF1 is highly abundant in bones, however, its involvements in osteogenic differentiation and bone formation are still unknown. In this study, by conditional gene targeting to delete the Macf1 gene specifically in MSCs, we observed ossification retardation and bone loss in MACF1 deficient mice in different developmental stages, which we traced to disorganized cytoskeleton and decreased osteogenic differentiation capability in MSCs. Further, we show that MACF1 interacts and facilitates SMAD7 nuclear translocation to initiate downstream transcription. These findings are hopefully to expand the biological scope of MACF1 in bones, and provide experimental basis for targeting MACF1 in degenerative bone diseases such as osteoporosis.

developmental biology↗

bioRxiv2019

DeepMF: Deciphering the Latent Patterns in Omics Profiles with a Deep Learning Method

With recent advances in high-throughput technologies, matrix factorization techniques are increasingly being utilized for mapping quantitative omics profiling matrix data into low-dimensional embedding space, in the hope of uncovering insights in the underlying biological processes. Nevertheless, current matrix factorization tools fall short in handling noisy data and missing entries, both deficiencies that are often found in real-life data. Here, we propose DeepMF, a deep neural network-based factorization model. DeepMF disentangles the association between molecular feature-associated and sample-associated latent matrices, and is tolerant to noisy and missing values. It exhibited feasible subtype discovery efficacy on mRNA, miRNA, and protein profiles of medulloblastoma cancer, leukemia cancer, breast cancer, and small-blue-round-cell cancer, achieving the highest clustering accuracy of 76%, 100%, 92%, and 100% respectively. When analyzing data sets with 70% missing entries, DeepMF gave the best recovery capacity with silhouette values of 0.47, 0.6, 0.28, and 0.44, outperforming other state-of-the-art MF tools on the cancer data sets Medulloblastoma, Leukemia, TCGA BRCA, and SRBCT. Its embedding strength as measured by clustering accuracy is 88%, 100%, 84%, and 96% on these data sets, which improves on the current best methods 76%, 100%, 78%, and 87%. DeepMF demonstrated robust denoising, imputation, and embedding ability. It offers insights to uncover the underlying biological processes such as cancer subtype discovery. Our implementation of DeepMF can be found at https://gitlab.deepomics.org/jiaox96/DeepMF.

bioinformatics↗

bioRxiv2019

NbCycB2 represses Nbwo activity via a negative feedback loop in the tobacco trichome developmemt

The wo protein and its downstream gene, SlCycB2 have been demonstrated to regulate the trichome development in tomato. It was shown that only gain-of-function mutant form of wo, Wov (wo woolly motif mutant allele) could induce the increase of trichome density. However, it is still unclear the relationships between wo, Wov and SlCycB2 in trichome regulation. In this study, we demonstrated Nbwo (NbWov) directly regulated the expressions NbCycB2 by binding to the promoter of NbCycB2 and its genomic sequences. As a feedback regulation, NbCycB2 negatively regulates the trichome formation by repressing Nbwo activity at protein level. We further found that the mutations of Nbwo woolly motif could prevent repression of NbWov by NbCycB2, which results in the significant increase of active Nbwo proteins, trichome density and branches. Our results revealed a novel reciprocal mechanism between NbCycB2 and Nbwo during the trichome formation in Nicotiana benthamiana.\n\nHighlightNbCycB2 is specifically expressed in trichomes of Nicotiana benthamiana and represses the Nbwo activity via a negative feedback loop in tobacco trichome developmemt.

plant biology↗