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Biology subjects

Li, P.

Publications and source records attributed to Li, P..

At least 253 records · Page 14Linked to original sources

NDR1 and the Arabidopsis Plasma Membrane ATPase AHA5 are Required for Processes that Converge on Drought Tolerance and Immunity

NON-RACE-SPECIFIC DISEASE RISISTANCE1 (NDR1) is a key component of plant immune signaling, required for defense against the bacterial pathogen Pseudomonas syringae. Plant stress responses have overlapping molecular, physiological, and cell biology signatures, and given the central role of NDR1 during biotic stress perception and signaling, we hypothesized that NDR1 also functions in abiotic stress responses, including in a role that mediates signaling at the plasma membrane (PM) - cell wall (CW) continuum. Here, we demonstrate that NDR1 is required for the induction of drought stress responses in plants, a role that couples stress signaling in an abscisic acid-dependent manner. We show that NDR1 physically associates with the PM-localized H+-ATPases AHA1, AHA2, and AHA5 and is required for proper regulation of H+-ATPase activity and stomatal guard cell dynamics, providing a mechanistic function of NDR1 during drought responses. In the current study, we demonstrate that NDR1 functions in signaling processes associated with both biotic and abiotic stress response pathways, a function we hypothesize represents NDR1s role in the maintenance of cellular homeostasis during stress. We propose a role for NDR1 as a core transducer of signaling between cell membrane processes and intercellular stress response activation.

plant biology↗

A connectomic study of a petascale fragment of human cerebral cortex

We acquired a rapidly preserved human surgical sample from the temporal lobe of the cerebral cortex. We stained a 1 mm3 volume with heavy metals, embedded it in resin, cut more than 5000 slices at [~]30 nm and imaged these sections using a high-speed multibeam scanning electron microscope. We used computational methods to render the three-dimensional structure containing 57,216 cells, hundreds of millions of neurites and 133.7 million synaptic connections. The 1.4 petabyte electron microscopy volume, the segmented cells, cell parts, blood vessels, myelin, inhibitory and excitatory synapses, and 104 manually proofread cells are available to peruse online. Many interesting and unusual features were evident in this dataset. Glia outnumbered neurons 2:1 and oligodendrocytes were the most common cell type in the volume. Excitatory spiny neurons comprised 69% of the neuronal population, and excitatory synapses also were in the majority (76%). The synaptic drive onto spiny neurons was biased more strongly toward excitation (70%) than was the case for inhibitory interneurons (48%). Despite incompleteness of the automated segmentation caused by split and merge errors, we could automatically generate (and then validate) connections between most of the excitatory and inhibitory neuron types both within and between layers. In studying these neurons we found that deep layer excitatory cell types can be classified into new subsets, based on structural and connectivity differences, and that chandelier interneurons not only innervate excitatory neuron initial segments as previously described, but also each others initial segments. Furthermore, among the thousands of weak connections established on each neuron, there exist rarer highly powerful axonal inputs that establish multi-synaptic contacts (up to [~]20 synapses) with target neurons. Our analysis indicates that these strong inputs are specific, and allow small numbers of axons to have an outsized role in the activity of some of their postsynaptic partners.

neuroscience↗

Implicit Laplacian of Enhanced Edge (ILEE): An unguided quantitative cytoskeletal imaging algorithm

The eukaryotic cytoskeleton plays essential roles in cell signaling and trafficking, which is broadly associated with immunity and diseases of human and plants. To date, most analyses aiming at defining the temporal and spatial dynamics of the cytoskeleton have relied on qualitative and quantitative analysis of fluorescence images to describe cytoskeletal function. While state-of-the-art, these approaches have limitations: the diverse shape and brightness of the cytoskeleton cause considerable inaccuracy in both human-driven and automated approaches, and the widely adopted image projection process (3D to 2D) leads to bias and information loss. Here, we describe the development and application of Implicit Laplacian of Enhanced Edge (ILEE), an unguided approach that uses a 2D/3D-compatible local thresholding algorithm for the quantitative evaluation of cytoskeletal status and organization at high performance. Using ILEE, we constructed a Python library to enable automated cytoskeletal image analysis, providing numerous biologically-interpretable indices measuring the density, bundling, severing, branching, and directionality of the cytoskeleton. The data presented herein demonstrate that ILEE resolves the defects of classic cytoskeleton analysis approaches, enables the measurement of novel cytoskeletal features, and yields quantitatively descriptive data with superior accuracy, stability, and robustness. We released the ILEE algorithm as an open-source library and further developed a Google Colab interface as a community resource.

cell biology↗

AutoGGN: A Gene Graph Network AutoML tool for Multi-Omics Research

Omics data identifies biological characteristics from genetic to phenotypic levels during the life span. Molecular interaction networks have a fundamental impact on life activities. Integrating omics data and molecular interaction networks will help researchers delve into comprehensive information underlying the data. Here, we proposed a new multimodal method called AutoGGN to aggregate multi-omics data and molecular interaction networks based on graph convolutional neural networks. We evaluated AutoGGN using two different tasks: cancer type classification and single-cell stage classification. On both tasks, AutoGGN showed better performance compared to other methods, the trend is relevant to the ability of utilizing much more information from biological data. The phenomenon indicated AutoGGN has the potential to incorporate valuable information from molecular interaction networks and multi-omics data effectively. Furthermore, in order to provide a better understanding of the mechanism of prediction results, we assessed the explanation using SHAP module and identified the key genes contributing to the prediction of classification, which will provide insights for the downstream design of biological experiments.

bioinformatics↗

Lhx2 is a progenitor-intrinsic modulator of Sonic Hedgehog signaling during early retinal neurogenesis

An important question in organogenesis is how tissue-specific transcription factors interact with signaling pathways. In some cases, transcription factors define the context for how signaling pathways elicit tissue- or cell-specific responses, and in others, they influence signaling through transcriptional regulation of signaling components or accessory factors. We previously showed that during optic vesicle patterning, the Lim-homeodomain transcription factor Lhx2 has a contextual role by linking the Sonic Hedgehog (Shh) pathway to downstream targets without regulating the pathway itself. Here, we show that during early retinal neurogenesis, Lhx2 is a multilevel regulator of Shh signaling. Specifically, Lhx2 acts cell autonomously to control the expression of pathway genes required for efficient activation and maintenance of signaling in retinal progenitor cells. The Shh co-receptors Cdon and Gas1 are candidate direct targets of Lhx2 that mediate pathway activation, whereas Lhx2 directly or indirectly promotes the expression of other pathway components important for activation and sustained signaling. We also provide genetic evidence suggesting that Lhx2 has a contextual role by linking the Shh pathway to downstream targets. Through these interactions, Lhx2 establishes the competence for Shh signaling in retinal progenitors and the context for the pathway to promote early retinal neurogenesis. The temporally distinct interactions between Lhx2 and the Shh pathway in retinal development illustrate how transcription factors and signaling pathways adapt to meet stage-dependent requirements of tissue formation.

developmental biology↗

Analysis of viral RNA-host protein interactomes enables rapid antiviral drug discovery

RNA viruses including SARS-CoV-2, Ebola virus (EBOV), and Zika virus (ZIKV) constitute a major threat to global public health and society. The interactions between viral genomes and host proteins are essential in the life cycle of RNA viruses and thus provide targets for drug development. However, viral RNA-host protein interactions have remained poorly characterized. Here we applied ChIRP-MS to profile the interactomes of human proteins and the RNA genomes of SARS-CoV-2, EBOV, and ZIKV in infected cells. Integrated interactome analyses revealed interaction patterns that reflect both common and virus-specific host responses, and enabled rapid drug screening to target the vulnerable host factors. We identified Enasidenib as a SARS-CoV-2 specific antiviral agent, and Trifluoperazine and Cepharanthine as broad spectrum antivirals against all three RNA viruses. One Sentence SummaryInteractome analyses of host proteins and the SARS-CoV-2, EBOV, and ZIKV RNA genomes unveil viral biology and drug targets.

microbiology↗

Auditory attention detection with EEG channel attention

Auditory attention detection (AAD) seeks to detect the attended speech from EEG signals in a multi-talker scenario, i.e. cocktail party. As the EEG channels reflect the activities of different brain areas, a task-oriented channel selection technique improves the performance of brain-computer interface applications. In this study, we propose a soft channel attention mechanism, instead of hard channel selection, that derives an EEG channel mask by optimizing the auditory attention detection task. The neural AAD system consists of a neural channel attention mechanism and a convolutional neural network (CNN) classifier. We evaluate the proposed framework on a publicly available database. We achieve 88.3% and 77.2% for 2-second and 0.1-second decision windows with 64-channel EEG; and 86.1% and 83.9% for 2-second decision windows with 32-channel and 16-channel EEG, respectively. The proposed framework outperforms other competitive models by a large margin in all test cases.

neuroscience↗

Emerging SARS-CoV-2 mutation hotspots associated with clinical outcomes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding the influence of mutations in the SARS-CoV-2 gene on clinical outcomes and related factors is critical for treatment and prevention. Here, we analyzed 209,551 high-coverage complete virus sequences and 321 RNA-seq samples to mine the mutations associated with clinical outcome in the SARS-CoV-2 genome. Several important hotspot variants were found to be associated with severe clinical outcomes. Q57H variant in ORF3a protein were found to be associated with higher mortality rate, and was high proportion in severe cases (39.36%) and 501Y.V2 strains (100%) but poorly proportional to asymptomatic cases (10.04%). T265I could change nsp2 structure and mitochondrial permeability, and evidently higher in severe cases (20.12%) and 501Y.V2 strains (100%) but lower in asymptomatic cases (1.43%). Additionally, R203K and G204R could decrease the flexibility and immunogenic property of N protein with high frequency among severe cases, VUI 202012/01 and 484K.V2 strains. Interestingly, the SARS-CoV-2 genome was more susceptible to mutation because of the high frequency of nt14408 mutation (which located in RNA polymerase) and the high expression levels of ADAR and APOBEC in severe clinical outcomes. In conclusion, several important mutation hotspots in the SARS-CoV-2 genome associated with clinical outcomes was found in our study, and that might correlate with different SARS-CoV-2 mortality rates.

bioinformatics↗

circMRPS35 promotes malignant progression and cisplatin resistance in hepatocellular cancer

Hepatocellular carcinoma (HCC), a common malignant tumor, is one of the main causes of cancer-related deaths worldwide. Circular RNAs (circRNAs), a novel class of non-coding RNA, have been reported to be involved in the etiology of various malignancy. However, the functions of circRNAs in HCC remain unclear. In this study, through mining the RNA sequencing databases from GEO datasets and subsequent experimental verification, we identified that hsa_circ_0000384 (circMRPS35) was highly expressed in HCC. Knockdown of circMRPS35 suppressed the proliferation, migration, invasion, clone formation and cell cycle of HCC cell lines both in vitro and in a xenograft mouse model. Mechanically, circMRPS35 sponged microRNA-148a-3p (miR-148a), which in turn regulated STX3-PTEN axis. Surprisingly, we detected a peptide encoded by circMRPS35 (circMRPS35-168aa), which was significantly induced by chemotherapeutic drugs and promoted cisplatin resistance in HCC cells. These results demonstrated that circMRPS35 might be a novel factor in HCC progress, and has a great potential as a new diagnosis and therapeutic target for treatment of HCC.

cell biology↗

The dynamic interactive network of long non-coding RNAs and chromatin accessibility facilitates erythroid differentiation

Erythroid differentiation is a dynamic process regulated by multiple factors, while the interaction between long non-coding RNAs and chromatin accessibility and its influence on erythroid differentiation remains unclear. To elucidate this interaction, we employed hematopoietic stem cells, multipotent progenitor cells, common myeloid progenitor cells, megakaryocyte-erythroid progenitor cells, and erythroblasts from human cord blood as an erythroid differentiation model to explore the coordinated regulatory functions of lncRNAs and chromatin accessibility in erythropoiesis by integrating RNA-Seq and ATAC-Seq data. We revealed that the integrated network of chromatin accessibility and LncRNAs exhibits stage-specific changes throughout the erythroid differentiation process, and that the changes at the EB stage of maturation are dramatic. We identified a subset of stage-specific lncRNAs and transcription factors (TFs) that coordinate with chromatin accessibility during erythroid differentiation, in which lncRNAs are key regulators of terminal erythroid differentiation via a lncRNA-TF-gene network. LncRNA PCED1B-AS1 was revealed to regulate terminal erythroid differentiation by coordinating GATA1 dynamically binding to the chromatin during erythroid differentiation. DANCR, another lncRNA that is highly expressed at the MEP stage, was verified to promote erythroid differentiation by compromising megakaryocyte differentiation and coordinating with chromatin accessibility and TFs, such as RUNX1. Overall, our results identified the interactive network of lncRNAs and chromatin accessibility in erythropoiesis and provide novel insights into erythroid differentiation and abundant resources for further study. Key PointsO_LILncRNAs regulate erythroid differentiation through coordinating with chromatin accessibility. C_LIO_LIThe integrative multi-omics analysis reveals stage-specific interaction network of LncRNAs and chromatin accessibility in erythropoiesis. C_LI

genomics↗

Hydrophobic-cationic peptides enhance RNA polymerase ribozyme activity by accretion

Accretion and the resulting increase in local concentration to enhance target stability and function is a widespread mechanism in biology (for example in the liquid-liquid demixing phases and coacervates). It is widely believed that such macromolecular aggregates (formed through ionic and hydrophobic interactions) may have played a role in the origin of life. Here, we report on the behaviour of a hydrophobic-cationic RNA binding peptide selected by phage display (P43: AKKVWIIMGGS) that forms insoluble aggregates, accrete RNA on their surfaces in a size-dependent manner, and thus enhance the activities of various ribozymes. At low Mg2+ concentrations ([Mg2+]: 25 mM MgCl2), the activity of a small ribozyme (hammerhead ribozyme) was enhanced by P43, while larger ribozymes (RNA polymerase ribozyme (RPR), RNase P, F1* ligase) were inhibited. In contrast, at high [Mg2+] ([≥]200 mM), the RPR activity was enhanced. Another hydrophobic-cationic peptide with a simpler sequence (K2V6: KKVVVVVV) also exhibited similar regulatory effects on the RPR activity. Furthermore, inactive RPR captured on P43 aggregates at low [Mg2+] could be reactivated in a high [Mg2+] buffer. Therefore, in marked contrast to previously studied purely cationic peptides (like K10) that enhance RPR only at low ionic strength, hydrophobic-cationic peptides can reversibly concentrate RNA and enhance the RPR activity even at high ionic strength conditions such as in eutectic ice phases. Such peptides could have aided the emergence of longer and functional RNAs in a fluctuating environment (e.g., dry-wet / freeze-thaw cycles) on the prebiotic earth.

biochemistry↗

Discovery of a molecular glue that enhances UPRmt to restore proteostasis via TRKA-GRB2-EVI1-CRLS1 axis

Lowering proteotoxicity is a potentially powerful approach for the treatment of neurological disorders, such as Parkinsons disease. The unfolded protein response (UPR) is a major mechanism that preserves the network maintaining cellular proteostasis. In the present study, we developed the screening strategy to discover compounds that significantly enhanced the activation of mitochondrial UPR (UPRmt) through increasing cardiolipin content. We identified that ginsenoside Rg3 (Rg3) increased cardiolipin depending on cardiolipin synthase 1 (CRLS1) in both worms and in human neural cells. Using LiP-SMap (limited proteolysis-mass spectrometry) strategy, we identified GRB2 (growth factor receptor bound protein 2) as a direct target of Rg3 in human neural cells. Rg3 enhances the binding between GRB2 and TRKA, that transduces signals via phosphrorylation of ERK. We provide bioinformatic and experimental evidence that EVI1, the critical oncogenic transcriptional regulator in leukemia, binds to CRLS1 promoter region and stimulated CRLS1 expression and subsequently increased cardiolipin content in the presence of Rg3. In a Parkinsons disease mouse model, Rg3 restores motor function by protecting nigral dopaminergic neurons dependent on Grb2. Our data recapitulate the TRKA-GRB2-EVI1-CRLS1 axis in maintaining proteostasis in Parkinsons disease via UPRmt.

pharmacology and toxicology↗

EZH2 Engages TGFβ Signaling to Promote Breast Cancer Bone Metastasis via Integrin β1-FAK Activation

Bone metastasis is a frequent complication of breast cancer, occurring in about 50-70% of breast cancer patients with late-stage disease. The lack of effective therapy suggests that the precise molecular mechanisms underlying bone metastasis are still unclear. Enhancer of zeste homolog 2 (EZH2) is considered a breast cancer oncogene and its expression is correlated with metastasis of breast cancer, but its function in bone metastasis has not been well explored. Herein we report that EZH2 promotes osteolytic metastasis of breast cancer through regulating transforming growth factor beta (TGF{beta}) signaling, a key pathway in bone metastasis. Knocking down EZH2 decreases bone metastasis incidence and outgrowth in vivo. EZH2 induces cancer cell proliferation and osteoclast maturation, when breast cancer cells are co-cultured with osteoblasts and osteoclasts together in vitro. Mechanistically, EZH2 increases transcription of ITGB1, which encodes for integrin {beta}1. Integrin {beta}1 activates focal adhesion kinase (FAK), which phosphorylates TGF{beta} receptor type I (TGF{beta}RI) at tyrosine 182, thus enhances the binding of TGF{beta}RI to TGF{beta} receptor type II (TGF{beta}RII), therefore activates Smad2 and increases parathyroid hormone-like hormone (PTHLH) expression. Clinically applicable FAK inhibitors but not EZH2 methyltransferase inhibitor effectively inhibits breast cancer bone metastasis in vivo. Overall, our data signify integrin {beta}1-FAK as a new downstream effector of EZH2 in breast cancer cells, and EZH2-integrin {beta}1-FAK axis cooperates with TGF{beta} signaling pathway to promote bone metastasis of breast cancer.

cancer biology↗

Molecular mechanism behind the involvement of apple flavonoid glycosyltransferase gene MdGT1 in the color of apple leaves

Nowadays, the plant family 1 UDP-glycosyltransferases (UGTs) are more and more investigated owing to their contribution to the plant secondary metabolism and diverse biological roles. Apple (Malus domestica) is one of the most widely cultivated fruit trees with great economical importance. However, poor knowledge is known about the apple UGTs. In this study, we identified 229 members of family 1 through a genome-wide analysis of the apple UGTs, which were clustered into 18 groups, from A to R. We also performed detailed analysis to 34 apple UGTs with quantitavive RT-PCR, and discovered a number of stress-regulated UGTs. Among them, we characterized the role of MD09G1064900, also named as MdUGT83L3, which is significantly induced by salt and cold. In vivo analysis showed that it has high activity towards cyanidin, and moderate activity towards quercetin and keampferol. The transgenic callus and regenerated apple plants overexpressing MdUGT83L3 showed enhanced tolerance to salt and cold treatments. Overexpression of MdUGT83L3 also increased anthocyanin accumulation in the callus tissues and enhanced ROS clearing upon exposed to salt and cold stresses. Futhermore, via yeast-two-hybrid assay, EMSA and CHIP analysis, we also found that MdUGT83L3 could be directly regualted by MdMYB88. Our study indicated that MdUGT83L3, under the regulation of MdMYB88, plays important roles in salt and cold stress adaptation via modulating flavonoid metabolism in apple.

molecular biology↗

Characterization of novel regulatory modules controlling leaf angle in maize

Leaf angle is an important agronomic trait determining maize planting density and light penetration into the canopy, and contributes significantly to the yield gain in modern maize hybrids. However, little is known about its molecular mechanism beyond the Liguless1 (LG1) and Liguless2 (LG2) genes. In this study, we found that transcription factor ZmBEH1 is targeted by ZmLG2 and regulates the leaf angle formation by influencing the sclerenchyma cells layers on the adaxial side. ZmBEH1 can interact with transcription factor ZmBZR1, whose expression is directly activated by ZmLG1. Both ZmBEH1 and ZmBZR1 bind to the promoter of ZmSCL28, the third transcription factors that influences the leaf angle. Our study demonstrates novel regulatory modules controlling leaf angle, and provides new gene editing targets for creating optimal maize architecture suitable for dense-planting.

plant biology↗

Regulation of lateral root development by shoot-sensed far-red light via HY5 is nitrate-dependent and involves the NRT2.1 nitrate transporter.

Plants are very effective in responding to environmental changes during competition for light and nutrients. Low Red:Far-Red (low R:FR)-mediated neighbor detection allows plants to compete successfully with other plants for available light. This above-ground signal can also reduce lateral root growth by inhibiting lateral root emergence, a process that might help the plant invest resources in shoot growth. Nitrate is an essential nutrient for plant growth and Arabidopsis thaliana responds to low nitrate conditions by enhancing nutrient uptake and reducing lateral and main root growth. There are indications that low R:FR signaling and low nitrate signaling can affect each other. It is unknown which response is prioritized when low R:FR light- and low nitrate signaling co-occur. We investigated the effect of low nitrate conditions on the low R:FR response of the A. thaliana root system in agar plate media, combined with the application of supplemental Far-Red (FR) light to the shoot. We observed that under low nitrate conditions main and lateral root growth was reduced, but more importantly, that the response of the root system to low R:FR was suppressed. Consistently, a loss-of-function mutant of a nitrate transporter gene NRT2.1 lacked low R:FR-induced lateral root reduction and its root growth was hypersensitive to low nitrate. ELONGATED HYPOCOTYL5 (HY5) plays an important role in the root response to low R:FR and we found that it was less sensitive to low nitrate conditions with regards to lateral root growth. In addition, we found that low R:FR increases NRT2.1 expression and that low nitrate enhances HY5 expression. HY5 also affects NRT2.1 expression, however, it depended on the presence of ammonium in which direction this effect was. Replacing part of the nitrogen source with ammonium also removed the effect of low R:FR on the root system, showing that changes in nitrogen sources can be crucial for root plasticity. Together our results show that nitrate signaling can repress low R:FR responses and that this involves signaling via HY5 and NRT2.1.

plant biology↗

In vivo structure and dynamics of the RNA genome of SARS-Cov-2

The SARS-CoV-2 coronavirus, which causes the COVID-19 pandemic, is one of the largest positive strand RNA viruses. Here we developed a simplified SPLASH assay and comprehensively mapped the in vivo RNA-RNA interactome of SARS-CoV-2 RNA during the viral life cycle. We observed canonical and alternative structures including 3-UTR and 5-UTR, frameshifting element (FSE) pseudoknot and genome cyclization in cells and in virions. We provide direct evidence of interactions between Transcription Regulating Sequences (TRS-L and TRS-Bs), which facilitate discontinuous transcription. In addition, we reveal alternative short and long distance arches around FSE, forming a "high-order pseudoknot" embedding FSE, which might help ribosome stalling at frameshift sites. More importantly, we found that within virions, while SARS-CoV-2 genome RNA undergoes intensive compaction, genome cyclization is weakened and genome domains remain stable. Our data provides a structural basis for the regulation of replication, discontinuous transcription and translational frameshifting, describes dynamics of RNA structures during life cycle of SARS-CoV-2, and will help to develop antiviral strategies.

genomics↗

Extensive High-Order Complexes within SARS-CoV-2 Proteome Revealed by Compartmentalization-Aided Interaction Screening

Bearing the largest single-stranded RNA genome in nature, SARS-CoV-2 utilizes sophisticated replication/transcription complexes (RTCs), mainly composed of a network of nonstructural proteins and nucleocapsid protein, to establish efficient infection. Here, we developed an innovative interaction screening strategy based on phase separation in cellulo, namely compartmentalization of protein-protein interactions in cells (CoPIC). Utilizing CoPIC screening, we mapped the interaction network among RTC-related viral proteins. We identified a total of 47 binary interactions among 14 proteins governing replication, discontinuous transcription, and translation of coronaviruses. Further exploration via CoPIC led to the discovery of extensive ternary complexes composed of these components, which infer potential higher-order complexes. Taken together, our results present an efficient, and robust interaction screening strategy, and indicate the existence of a complex interaction network among RTC-related factors, thus opening up new opportunities to understand SARS-CoV-2 biology and develop therapeutic interventions for COVID-19.

microbiology↗