Biology subjects
Publications and source records attributed to Zhu, C..
The high-quality genome assembly of the JSU-FSP provides valuable information on how jasmine produces the abundant VTs and VPBs that synergistically contribute to the pleasant aroma of jasmine flower.
Transcranial magnetic stimulation efficacy is largely dependent upon coil position and orientation. A good method for describing coil placement is required for both computational optimization (planning) and actual placement (implementation). In coordinate dependent parameter-spaces (CDPs), three-dimensional coordinates are used to represent coil position and three orthogonal unit vectors are used to represent coil orientation. A CDP can precisely describe arbitrary coil placement; therefore it offers great advantage in computational optimization which checks through all possible placements. However, a neuronavigation system is usually required to accurately implement the optimized CDP parameters on a participants head. Routine clinical practice, on the other hand, often uses the International 10-20 system to describe coil placement. Although the 10-20 system can only perform modeling and placement at limited scalp landmarks, it allows the synthesis of different individuals targeting effects to find group-optimal parameters; it also allows manual placement, which is important for commonly-seen use cases without individual MRI scans and navigation devices. This study proposes a new scalp geometry based parameter-space (SGP), integrating the advantages of CDP and 10-20 methods. Our SGP 1) can quantitatively specify all possible conventional coil positions and orientations on an individuals scalp, which is important for electrical modeling and optimization, 2) maintains inter-individual correspondence, which is important for synthesizing TMS effects from different individuals and studies. 3) enables fast and simple manual implementation. Demonstration experiments were conducted to illustrate the application of an SGP-based framework for both individual and group-based optimization. A measurement experiment was performed to evaluate speed, precision and reliability of SGP-based manual implementation; results show it surpasses previous manual placement methods.
Central to T cell biology, the T cell receptor (TCR) integrates forces in its triggering process upon interaction with peptide-major histocompatibility complex (pMHC)1-3. Phenotypically, forces elicit TCR catch-slip bonds with strong pMHCs but slip-only bonds with weak pMHCs4-10. While such correlation is commonly observed, the quantitative bond pattern and degree of "catchiness" vary. We developed two models based on the structure, elastic properties, and force-induced conformational changes of the TCR-pMHC-I/II complexes to derive from their bond characteristics more intrinsic parameters that underlie structural mechanisms, predict T cell signaling, and discriminate antigens. Applying the models to 55 datasets of 12 {beta}TCRs and their mutants interacting with corresponding pMHCs without coreceptor engagement demonstrated the ability for structural and physical parameters to quantitatively integrate and classify a broad range of bond behaviors and biological activities. Comparing to the generic two-state model for catch-slip bond that also fits the data, our models can distinguish class I from class II MHC systems and their best-fit parameters correlate with the TCR/pMHC potency to trigger T cell activation, which the generic model cannot. The models were tested by mutagenesis using structural analysis, bond profile measurement, and functional assay of a MHC and a TCR mutated to alter conformation changes. The extensive comparisons between theory and experiment provided strong validation of the models and testable hypothesis regarding specific conformational changes that control bond profiles, thereby suggesting structural mechanisms for the inner workings of the TCR mechanosensing machinery and plausible explanation of why and how force may amplify TCR signaling and antigen discrimination.
BackgroundHypoxia-inducible factor-1 (HIF-1) plays an important regulatory role in inflammatory and hypoxic diseases. Higher HIF-1 level was found in lungs of chronic obstructive pulmonary disease (COPD) patients, however, its role in cigarette smoke (CS)-induced COPD has not been fully studied. Digoxin has been showed to inhibit HIF-1 translation and block HIF-1 activity and thus is often used as the HIF-1 inhibitor. Therefore, in the present study, we chose digoxin as the inhibitor to investigate whether HIF-1 contributes to the progression of COPD and possible mechanism. MethodsCS-exposed mice were intragastrically treated with different doses of digoxin, and COPD-associated phenotypes such as pathological changes in lungs, inflammation, lung function and mucus secretion in airways were evaluated. Meanwhile, CSE-treated A549 cells were administrated with digoxin or S7959. Moreover, EMT-associated markers together with HIF-1\TGF-{beta}1\Smad3 signaling pathway were detected both in vivo and in vitro. ResultsThe level of HIF-1 was significantly increased in lungs of COPD mice and CSE-exposed A549 cells, which was markedly suppressed by digoxin. Moreover, digoxin inhibited CS-induced inflammatory responses, lung function decline, and mucus hyper-secretion in COPD mouse model. In in vitro studies, digoxin decreased CSE-induced pro-inflammatory cytokine release. Importantly, CS-induced or CSE-induced EMT and up-regulation of HIF-1/TGF-{beta}1/Smad pathway was inhibited by digoxin. Additionally, S7959 mitigated CSE-induced EMT in A549 cells. ConclusionsDigoxin can protect CS-induced COPD and prevent CS-induced EMT possibly through HIF-1/TGF-{beta}1/Smad3 signaling pathway. This study suggests HIF1- could be a potential intervention target for COPD prevention and treatment, especially for EMT in CS-induced COPD.
Since SARS-CoV-2 Omicron variant (B.1.1.529) was reported in November 2021, it has quickly spread to many countries and outcompeted the globally dominant Delta variant in several countries. The Omicron variant contains the largest number of mutations to date, with 32 mutations located at spike (S) glycoprotein, which raised great concern for its enhanced viral fitness and immune escape[1-4]. In this study, we reported the crystal structure of the receptor binding domain (RBD) of Omicron variant S glycoprotein bound to human ACE2 at a resolution of 2.6 [A]. Structural comparison, molecular dynamics simulation and binding free energy calculation collectively identified four key mutations (S477N, G496S, Q498R and N501Y) for the enhanced binding of ACE2 by the Omicron RBD compared to the WT RBD. Representative states of the WT and Omicron RBD-ACE2 systems were identified by Markov State Model, which provides a dynamic explanation for the enhanced binding of Omicron RBD. The effects of the mutations in the RBD for antibody recognition were analyzed, especially for the S371L/S373P/S375F substitutions significantly changing the local conformation of the residing loop to deactivate several class IV neutralizing antibodies.
Antigen recognition of CD4+ T cells by the T cell receptor (TCR) can be greatly enhanced by the coreceptor CD41-7. Yet, understanding of the molecular mechanism is hindered by the ultra-low affinity of CD4 binding to class-II peptide-major histocompatibility complexes (pMHC)1,7-10. Using two-dimensional (2D) mechanical-based assays, we determined a CD4-pMHC interaction to have 3-4 logs lower affinity than cognate TCR-pMHC interactions8, and to be susceptible to increased dissociation by forces (slip bond)5,8,11. In contrast, CD4 binds TCR-prebound pMHC at 3-6 logs higher affinity, forming TCR-pMHC-CD4 trimolecular bonds that are prolonged by force (catch bond)5,8,11 and modulated by protein mobility on the cell membrane, indicating profound TCR-CD4 cooperativity. Consistent with a tri-crystal structure12, using DNA origami as a molecular ruler to titrate spacing between TCR and CD4 indicates that 7-nm proximity optimizes trimolecular bond formation with pMHC. Our results reveal how CD4 augments TCR antigen recognition.
{gamma}{delta} T cells physiologically scan the intestinal epithelium, representing a substantial fraction of infiltrating lymphocytes in colorectal cancer (CRC), albeit their role in CRC remains unclear. Using murine CRC models, we found that most {gamma}{delta} T cells in pre- or non-tumor colon express V{gamma}1+ or V{gamma}7+ and exhibit a cytotoxic profile. Targeting these {gamma}{delta} T cell subsets, as well as conditionally interfering with {gamma}{delta} T cell function at early stages of tumorigenesis led to heightened tumor development, suggesting anti-CRC functions for V{gamma}1+ and V{gamma}7+ subsets. In contrast, ROR{gamma}t+ {gamma}{delta} T cell subsets, including V{gamma}4+ and microbiotadependent V{gamma}6+, accumulated during CRC progression. Conditional deletion of ROR{gamma}t or V{gamma} chains revealed redundant roles for IL-17-producing V{gamma}4+ and V{gamma}6+ {gamma}{delta} T cells in promoting tumor growth. Our results uncover pro- and anti-tumor roles for {gamma}{delta} T cell subsets.
Biomembranes adopt varying morphologies that are vital to cellular functions. Many studies use computational modeling to understand how various mechanochemical factors contribute to membrane shape transformations. Compared to approximation-based methods (e.g., finite element method), the class of discrete mesh models offers greater flexibility to simulate complex physics and shapes in three dimensions; its formulation produces an efficient algorithm while maintaining coordinate-free geometric descriptions. However, ambiguities in geometric definitions in the discrete context have led to a lack of consensus on which discrete mesh model is theoretically and numerically optimal; a bijective relationship between the terms contributing to both the energy and forces from the discrete and smooth geometric theories remains to be established. We address this and present an extensible framework, Mem3DG, for modeling 3D mechanochemical dynamics of membranes based on Discrete Differential Geometry (DDG) on triangulated meshes. The formalism of DDG resolves the inconsistency and provides a unifying perspective on how to relate the smooth and discrete energy and forces. To demonstrate, Mem3DG is used to model a sequence of examples with increasing mechanochemical complexity: recovering classical shape transformations such as 1) biconcave disk, dumb-bell, and unduloid and 2) spherical bud on spherical, flat-patch membrane; investigating how the coupling of membrane mechanics with protein mobility jointly affects phase and shape transformation. As high-resolution 3D imaging of membrane ultrastructure becomes more readily available, we envision Mem3DG to be applied as an end-to-end tool to simulate realistic cell geometry under user-specified mechanochemical conditions. Why it mattersCellular membranes have shapes and shape changes which characterize cells/organelles, and support nutrient trafficking among other critical processes. Modeling membrane shape changes using mechanical principles can provide insight into how cells robustly bend membranes to support life. Mathematical and computational strategies to solve the equations describing membrane shape evolution can be complex and challenging without simplifying assumptions. Here, we present a new, general, numerical approach to model arbitrary 3D membrane shapes in response to interaction with curvature sensing and generating membrane proteins. The accompanying implementation, Mem3DG, is a software tool to make computational membrane mechanics accessible to the general researcher. HighlightsO_LIIntroduces a discrete theory for membrane mechanics which connects with smooth theory C_LIO_LIDiscrete energy/force are functions of basic geometric quantities C_LIO_LIRecipes for extending the discrete framework with additional physics are provided C_LIO_LIDescribes a user-friendly software implementation called Mem3DG C_LIO_LIMem3DG is designed to facilitate modeling in tandem with experimental studies C_LI Significance and noveltyHelfrich Hamiltonian is widely used to model biomembranes. Many numerical methods have been developed to solve the geometric PDE. Compared to approximation-based methods, discrete-mesh-based models have many advantages when incorporating multiphysics in 3D due to their flexibility, efficiency, and straightforward implementation. However, there is no consensus on which mesh-based model is optimal, and a connection between the discrete and smooth geometric theory remains obscure. In this work, we provide a unifying perspective by identifying fundamental geometric invariants of the discrete force derived from a discrete energy. As a demonstration of generality of the framework to various physics, we follow a formulaic procedure to derive additional physics such as interfacial line tension, surface-bulk adsorption, protein lateral diffusion, and curvature-dependent protein aggregation.
Histone methylation plays crucial roles in the development, gene regulation and maintenance of stem cell pluripotency in mammals. Recent work shows that histone methylation is associated with aging, yet the underlying mechanism remains unclear. In this work, we identified a class of histone 3 lysine 9 mono-/dimethyltransferase genes (met-2, set-6, set-19, set-20, set-21, set-32 and set-33), mutations in which induce synergistic lifespan extension in the long-lived DAF-2 (IGF-1 receptor) mutant in C. elegans. These histone methyltransferase plus daf-2 double mutants not only exhibited an average lifespan nearly three times that of wild-type animals and a maximal lifespan of approximately 100 days, but also significantly increased resistance to oxidative and heat stress. Synergistic lifespan extension depends on the transcription factor DAF-16 (FOXO). mRNA-seq experiments revealed that the mRNA levels of class I DAF-16 target genes, which are activated by DAF-16, were further elevated in the double mutants. Among these genes, F35E8.7, nhr-62, sod-3, asm-2 and Y39G8B.7 are required for the lifespan extension of the daf-2;set-21 double mutant. In addition, treating daf-2 animals with the H3K9me1/2 methyltransferase G9a inhibitor also extends lifespan and increases stress resistance. Therefore, investigation of DAF-2 and H3K9me1/2 methyltransferase deficiency-mediated synergistic longevity will contribute to a better understanding of the molecular mechanisms of aging and therapeutic applications.
The innate immune response of Charybdis japonica treated with Aeromonas hydrophila was explored using bioinformatics. Metabolomics data were integrated with a gut microbial 16S rRNA dataset, together with information on corresponding enzyme activity. The results of the study showed that after being infected with A. hydrophila, some beneficial genera of bacteria in the gut of C. japonica, such as Photobacterium, Rhodobacter, Polaribacter, Psychrilyobacter, Mesoflavibacter, Fusibacter and Phormidium, could directly inhibit Vibrio or produce extracellular polysaccharides with highly effective antibacterial properties. The intestinal probiotics of C. japonica such as Mesoflavibacter have a mutually reinforcing relationship with Phaeobacter, Colwellia, Bacillus, Psychrobacter and Cohaesibacter. Conditional pathogenic bacteria in the gut of healthy crabs may also have such a symbiotic relationship with intestinal probiotics, promoting their growth and reproduction. For example, Phormidium has a mutualistic relationship with Aeromonas and Azopira. Metabolites in the gut of C. japonica infected with A. hydrophila, including beta-alanine metabolism, nitrogen metabolism, inositol phosphate metabolism, galactose metabolism, histidine metabolism, ascorbate and arginine and proline metabolism were increased, with alanine metabolism being the most abundant. The activity of metabolite related enzymes such as lipid peroxidase, phenoloxidase, superoxide dismutase, nitric oxide synthase, glutathione transferase and mid-glutathione decreased and NO levels also decreased. The positive correlation with the probiotic flora suggests that metabolites increase with bacterial abundance and that microbial metabolites or co-metabolites can, in turn, achieve many pleiotropic effects to resist invasion by A. hydrophila. These results may contribute to further research in the resistance of C. japonica to invading pathogens. ImportanceWith the rapid development of the C. japonica farming industry, investors, in pursuit of economic benefits, have encountered problems such as frequent outbreaks of various diseases, resulting in high mortality and huge economic losses. The open water circulation system can give rise to several crab bacterial diseases. Among these, A. hydrophila is a pathogenic bacterium affecting fish and crustaceans, which leads to huge economic losses. Our results suggest that metabolites increased with the abundance of bacteria. It is possible that the autoimmune system and the entry of A. hydrophila into the intestinal tissues of C. japonica react immunologically and that the organism is producing certain metabolites which may be metabolised by various bacteria and absorbed into the circulation. In addition, some of these metabolites are modified or bound in the hepatopancreas to produce microbiota-host co-metabolites. These microbial metabolites or co-metabolites can resist invasion by A. hydrophila.
Camphor tree (Cinnamomum camphora (L.) J. Presl), a species in the magnoliid family Lauraceae, is known for its rich volatile oils and is used as a medical cardiotonic and as a scent in many perfumed hygiene products. Here, we present a high-quality chromosome-scale genome of C. camphora with a scaffold N50 of 64.34 Mb and an assembled genome size of 755.41 Mb. Phylogenetic inference revealed that the magnoliids are a sister group to the clade of eudicots and monocots. Comparative genomic analyses identified two rounds of ancient whole-genome duplication (WGD). Tandem duplicated genes exhibited a higher evolutionary rate, a more recent evolutionary history and a more clustered distribution on chromosomes, contributing to the production of secondary metabolites, especially monoterpenes and sesquiterpenes, which are the principal essential oil components. Three-dimensional analyses of the volatile metabolites, gene expression and climate data of samples with the same genotype grown in different locations showed that low temperature and low precipitation during the cold season modulate the expression of genes in the terpenoid biosynthesis pathways, especially TPS genes, which facilitates the accumulation of volatile compounds. Our study lays a theoretical foundation for policy-making regarding the agroforestry applications of camphor tree.
Directional transport of auxin is critical for inflorescence and floral development in flowering plants, but the role of auxin influx carriers (AUX1 proteins) has been largely overlooked. Taking advantage of available AUX1 mutants in Setaria viridis and maize, we uncover previously unreported aspects of plant development that are affected by auxin influx, including higher order branches in the inflorescence, stigma branch number, and glume (floral bract) development, and plant fertility. However, disruption of auxin flux does not affect all parts of the plant, with little obvious effect on inflorescence meristem size, time to flowering, and anther morphology. In double mutant studies in maize, disruptions of ZmAUX1 also affect vegetative development. A GFP-tagged construct of SvAUX1 under its native promoter showed that the AUX1 protein localizes to the plasma membrane of outer tissue layers in both roots and inflorescences, and accumulates specifically in inflorescence branch meristems, consistent with the mutant phenotype and expected auxin maxima. RNA-seq analysis finds that most gene expression modules are conserved between mutant and wildtype plants, with only a few hundred genes differentially expressed in spp1 inflorescences. Using CRISPR-Cas9 technology, we disrupted SPP1 and the other four AUX1 homologs in S. viridis. SvAUX1/SPP1 has a larger effect on inflorescence development than the others, although all contribute to plant height, tiller formation, leaf, and root development. The AUX1 importers are thus not fully redundant in S. viridis. Our detailed phenotypic characterization plus a stable GFP-tagged line offer tools for future dissection of the function of auxin influx proteins. One sentence summaryMutations in a single auxin importer gene Spp1/SvAUX1 uncover broad and unexpected effects in nearly all aspects of the development of shoots, inflorescences, and flowers.
Transcriptional phenotypic drug discovery has achieved great success, and various compound perturbation-based data resources, such as Connectivity Map (CMap) and Library of Integrated Network-Based Cellular Signatures (LINCS), have been presented. Computational strategies fully mining these resources for phenotypic drug discovery have been proposed, and among them, a fundamental issue is to define the proper similarity between the transcriptional profiles to elucidate the drug mechanism of actions and identify new drug indications. Traditionally, this similarity has been defined in an unsupervised way, and due to the high dimensionality and the existence of high noise in those high-throughput data, it lacks robustness with limited performance. In our study, we present Dr. Sim, which is a general learning-based framework that automatically infers similarity measurement rather than being manually designed and can be used to characterize transcriptional phenotypic profiles for drug discovery with generalized good performance. We evaluated Dr. Sim on comprehensively publicly available in vitro and in vivo datasets in drug annotation and repositioning using high-throughput transcriptional perturbation data and indicated that Dr. Sim significantly outperforms the existing methods and is proved to be a conceptual improvement by learning transcriptional similarity to facilitate the broad utility of high-throughput transcriptional perturbation data for phenotypic drug discovery. The source code and usage of Dr. Sim is available at https://github.com/bm2-lab/DrSim/.
Prion infections cause conformational changes of PrPC and lead to progressive neurological impairment. Here we show that toxic, prion-mimetic ligands induce an intramolecular R208-H140 hydrogen bond ("H-latch") altering the flexibility of the 2-3 and {beta}2-2 loops of PrPC. Expression of a PrP2Cys mutant mimicking the H-latch was constitutively toxic, whereas a PrPR207A mutant unable to form the H-latch conferred resistance to prion infection. High-affinity ligands that prevented H-latch induction repressed prion-related neurodegeneration in organotypic cerebellar cultures. We then selected phage-displayed ligands binding wild-type PrPC, but not PrP2Cys. These binders depopulated H-latched conformers and conferred protection against prion toxicity. Finally, brain-specific expression of an antibody rationally designed to prevent H-latch formation, prolonged the life of prion-infected mice despite unhampered prion propagation, confirming that the H-latch is causally linked to prion neurotoxicity.
Circular RNA (circRNA) is a distinguishable circular formed long non-coding RNA (lncRNA), which has specific roles in transcriptional regulation, multiple biological processes. The identification of circRNA from other lncRNA is necessary for relevant research. In this study, we designed attention-based multi-instance learning (MIL) network architecture, which can be fed with raw sequence, to learn the sparse features in sequences and accomplish the identification task for circRNAs. The model outperformed previously reported models. Following the effectiveness validation of the attention score by the handwritten digit dataset, the key sequence loci underlying circRNAs recognition were obtained based on the corresponding attention score. Moreover, the motif enrichment analysis of the extracted key sequences identified some of the key motifs for circRNA formation. In conclusion, we designed a deep learning network architecture suitable for gene sequence learning with sparse features and implemented to the circRNA identification, and the network has a strong representation capability with its indication of some key loci.
Metagenomic binning is the step in building metagenome-assembled genomes (MAGs) when sequences predicted to originate from the same genome are automatically grouped together. The most widely-used methods for binning are reference-independent, operating de novo and allow the recovery of genomes from previously unsampled clades. However, they do not leverage the knowledge in existing databases. Here, we propose SemiBin, an open source tool that uses neural networks to implement a semi-supervised approach, i.e. SemiBin exploits the information in reference genomes, while retaining the capability of binning genomes that are outside the reference dataset. SemiBin outperforms existing state-of-the-art binning methods in simulated and real microbiome datasets across three different environments (human gut, dog gut, and marine microbiomes). SemiBin returns more high-quality bins with larger taxonomic diversity, including more distinct genera and species. SemiBin is available as open source software at https://github.com/BigDataBiology/SemiBin/.
Unicellular eukaryotes are suggested to undergo self-inflicted destruction. However, molecular details are sparse by comparison to the mechanisms of cell death known for human cells and animal models. Here we report a molecular pathway in Saccharomyces cerevisiae leading to vacuole/lysosome membrane permeabilization and cell death. Following exposure to heat-ramp conditions, a model of environmental stress, we observed that yeast cell death occurs over several hours, suggesting an ongoing molecular dying process. A genome-wide screen for death-promoting factors identified all subunits of the AP-3 adaptor complex. AP-3 promotes stress-induced cell death through its Arf1-GTPase-dependent vesicle trafficking function, which is required to transport and install proteins on the vacuole/lysosome membrane, including a death-promoting protein kinase Yck3. Time-lapse microscopy revealed a sequence of events where AP-3-dependent vacuole permeability occurs hours before the loss of plasma membrane integrity. An AP-3-dependent cell death pathway appears to be conserved in the human pathogen Cryptococcus neoformans.
Hematopoietic differentiation is controlled by both genetic and epigenetic regulators. Long non-coding RNAs (lncRNAs) have been demonstrated to be important for normal hematopoiesis, but their function in erythropoiesis needs to be further explored. We profiled the transcriptomes of 16 murine hematopoietic cell populations by deep RNA-sequencing and identified a novel lncRNA, Gm15915, that was highly expressed in erythroid-related progenitors and erythrocytes. For this reason, we named it lncEry. We also identified a novel lncEry isoform, which was also the principal transcript that has not been reported before. LncEry depletion impaired erythropoiesis, indicating the important role of the lncRNA in regulating erythroid differentiation and maturation. Mechanistically, we found that lncEry interacted with WD repeat-containing protein 82 (WDR82) to promote the transcription of Klf1 and globin genes and thus control the early and late stages of erythropoiesis, respectively. These findings identified lncEry as an important player in the transcriptional regulation of erythropoiesis.