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Chi, Y.

Publications and source records attributed to Chi, Y..

At least 37 records · Page 2Linked to original sources

HSV-1 orchestrates host RAP80 ubiquitination by ICP0 and UL36USP to promote viral survival

Herpes simplex virus 1 (HSV-1) is a widespread human pathogen that establishes lifelong infections, ubiquitination is crucial for HSV - 1 to interact with the host and regulate its life activities. But the mechanisms of how HSV-1 dynamically modulates host proteins at different infection stages to promote its own survival remains challenging. Here we identified DNA damage response protein RAP80 as a critical target of HSV-1 ubiquitination enzymes ICP0 and UL36USP throughout HSV-1s infection cycle. In early stages, RAP80 inhibits HSV-1 transcription by directly binding to the viral genome, blocking viral protein ICP4 binding to transcription factors. This interaction is regulated by phase separation via an intricate interplay between RAP80 and ICP0/ICP4. As infection progresses, the viral E3 ligase ICP0 degrades RAP80, dissolving phase separation, and allowing the formation of a mature viral replication compartment. In late infection stages, RAP80 is deubiquitinated by the viral deubiquitinase UL36USP, which restores cellular homeostasis and promotes HSV-1 survival. This process involves modulating the R-loop-cGAS-apoptosis pathway. These findings underscore the dynamic interplay between viral and host factors and the complex mechanisms used by HSV-1 to subvert host defenses, offering practical implications for the future development of antiviral strategies.

molecular biology↗

The Effects of Alginate Oligosaccharides (AOS) with Degree of Polymerization (DP) 2, 3, 4, 5, 6, and 7 on Tomato Yields

This study evaluated the effects of alginate oligosaccharide (AOS) fractions with degrees of polymerization (DP) 2-7 on tomato (Solanum lycopersicum L.) growth, yield, fruit quality, physiology, nutrient uptake, and defense responses under greenhouse conditions. AOS application significantly enhanced total yield, increasing from 2.5 kg/plant in the control to 4.2 kg and 4.0 kg in DP 2 and DP 3, respectively (p < 0.001). Marketable yield, fruit number, and average fruit weight also improved, with the highest values observed in DP 2 and DP 3 treatments. Fruit quality parameters, including total soluble solids (6.2 {degrees}Brix) and lycopene content (4.8 mg/100 g), were significantly higher in these groups. Plant growth metrics, such as height (70 cm), leaf number (25 leaves), and biomass accumulation, were markedly increased. Physiological traits, including photosynthetic rate (18.5 {micro}mol CO2 m-{superscript 2} s-{superscript 1}), chlorophyll content, and stomatal conductance, were also enhanced. Nutrient uptake of nitrogen, phosphorus, and potassium, as well as antioxidant enzyme activities (PAL, peroxidase, catalase, and SOD), were significantly elevated, while malondialdehyde (MDA) content was reduced. These findings suggest that AOS, particularly DP 2 and DP 3, effectively promote tomato productivity, fruit quality, and stress tolerance through improved physiological performance and defense activation.

bioengineering↗

Constructing a consensus serum metabolome

Blood analysis is the most common in biomedical applications and a reference metabolome will be critical for effective annotation and for guiding scientific investigations. However, compiling such a reference is hindered by many technical challenges, despite the availability of large amount of metabolomics data today. Based on a new set of data structures and tools, we have assembled a consensus serum metabolome (CSM) from over 100,000 mass spectrometry acquisitions of more than 200 million spectra. This provides a comprehensive survey of human blood chemistry, revealing the frequency dependent nature of metabolome and exposome. Major gaps are found between CSM and the current databases. The CSM enables community-level data alignment and significantly improves annotation quality of LC-MS metabolomics. HighlightsO_LIA reference of human biochemistry linked to observation frequency C_LIO_LIMajor gaps revealed in current databases and experimental methods C_LIO_LIEnabling cross-laboratory, cross-platform data alignment C_LIO_LIAccelerated and cumulative metabolite annotation C_LI

biochemistry↗

Virus-host interactome reveals host cellular pathways perturbed by tick-borne encephalitis virus infection

Tick-borne encephalitis virus (TBEV) poses an increasingly significant threat to public health. Here, we delved into the virus-host interactome and discovered that TBEV has a profound impact on multiple host cellular pathways. Viral pre-membrane protein (prM), non-structural proteins NS1, NS2B3, NS4A, and NS5 remodel the hosts innate immune responses. PrM and NS2B3 are involved in autophagy, NS4A is associated with neurodegenerative diseases, and NS5 participates in spliceosome dynamics, ribosomal biogenesis, cell cycle regulation, and DNA damage response. Notably, TBEV infection causes G0/G1 cell cycle arrest in host cells. NS5 interacts with histone acetyltransferase P300 to upregulate P16 expression, suppressing CDK4 and resulting in cell cycle arrest. Elevated P16 and reduced CDK4 levels were observed in TBEV-infected brain organoids. The P300 inhibitors and CDK4 agonist can reverse virus-induced cell cycle arrest and inhibit viral replication. Further analysis uncovered potential antiviral targets like KAT6A, XIAP, and RIOK1/BRD9. These findings provide valuable insights into TBEV pathogenicity and hold promise for antiviral drug development.

microbiology↗

A systematic analysis of in-source fragments in LC-MS metabolomics

There is no consensus on how to interpret the large number of unknown features in untargeted metabolomics, which are sometimes referred as the "dark matter". Are these features real compounds or artifacts? Understanding this problem is critical to the annotation and interpretation of metabolomics data and future development of the field. We propose a "detectable khipu" model here, to show that compounds exhibit ion group patterns that depend on their abundance. We apply this model to a systematic analysis of 61 representative public datasets from blood LC-MS metabolomics, the most common data type in biomedical studies. The results indicate that majority of abundant features have identifiable ion patterns, and in-source fragments contribute to less than 10% of features. Each dataset detects 1[~]2,000 high confidence compounds, over half of which are unknown. The major knowledge gap in LC-MS metabolomics is therefore not the methods of grouping ions or counting fragments, but the identification of unknown compounds.

biochemistry↗

Particular Amino Acid on Lateral Interface Maintains FtsZ Function Under Acid Stress in Streptococcus mutans

FtsZ is the core protein for cell division in bacteria that can polymerize into Z-rings and drive cytokinesis. Understanding how bacteria maintain the correct function of FtsZ under various environmental stresses is crucial for novel antibacterial drug discovery. Our previous study revealed that the FtsZ in S. mutans has higher self-assembly and GTPase activity under acidic stress, which may be responsible for the cariogenesis of S. mutans. However, the mechanism is still unknown. Here, we further reported the crystal structure of S. mutans FtsZ, revealing a unique lateral interface. Through protein polymerization and GTPase ability assay, we experimentally demonstrated that mutation of Arg68 on this lateral interface significantly reduced the functional activity of FtsZ in an acidic environment. The phenotype assay and rat caries model further showed that mutation of Arg68 effectively inhibited the acid resistance of S. mutans and the occurrence and progress of dental caries in vivo. By employing a molecular dynamics simulation analysis, we conclude that mutation of Arg68 disrupts the conformation change necessary for SmFtsZ polymerization under acidic conditions. Our study proposes a novel mechanism to maintain FtsZ function in bacteria and could be a potential target for antimicrobial drugs to inhibit the growth of S. mutans in an acidic environment. Significance StatementFtsZ is the core protein that drives cytokinesis. Maintaining the self-assembly and GTPase activity of FtsZ plays a critical role in cell growth under environmental stress. Currently, research on FtsZ function maintenance under stress mainly focuses on model organisms, with less on other pathogenic bacteria. This study reveals a novel structural mechanism for the acidic tolerance of FtsZ in S. mutans which survives in strongly acidic surroundings. Meanwhile, Arg68 on the lateral interface of SmFtsZ may be a potential therapeutic target to regulate microecology and combat S. mutans-associated dental caries.

microbiology↗

TRAIT: A Comprehensive Database for T-cell Receptor-Antigen Interactions

Comprehensive and integrated resources on interactions between T-cell receptors and antigens are still lacking for adoptive T-cell-based immunotherapies, highlighting a significant gap that must be addressed to fully comprehend the mechanisms of antigen recognition by T-cells. In this study, we present TRAIT, a comprehensive database that profiles the interactions between T-cell receptors (TCRs) and antigens. TRAIT stands out due to its comprehensive description of TCR-antigen interactions by integrating sequences, structures and affinities. It provides nearly 8 million experimentally validated TCR-antigen pairs, resulting in an exhaustive landscape of antigen-specific TCRs. Notably, TRAIT emphasizes single-cell omics as a major reliable data source for TCR-antigen interactions and includes millions of reliable non-interactive TCRs. Additionally, it thoroughly demonstrates the interactions between mutations of TCRs and antigens, thereby benefiting affinity maturation of engineered TCRs as well as vaccine design. TCRs on clinical trials were innovatively provided. With the significant efforts made towards elucidating the complex interactions between TCRs and antigens, TRAIT is expected to ultimately contribute superior algorithms and substantial advancements in the field of T-cell-based immunotherapies. TRAIT is freely accessible at https://pgx.zju.edu.cn/traitdb.

immunology↗

Alleviation of salt stress in strawberries by hydrogen-rich water: physiological, transcriptomic and metabolomic responses

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=108 SRC="FIGDIR/small/605184v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1aa6488org.highwire.dtl.DTLVardef@1ae580borg.highwire.dtl.DTLVardef@11656bcorg.highwire.dtl.DTLVardef@1985c7b_HPS_FORMAT_FIGEXP M_FIG C_FIG With the continuous advancement of climate change and human activities, cultivable land is becoming increasingly susceptible to the influence of salt ions. Therefore, it is crucial to mitigate the salt stress on plants through various approaches. In this study, strawberry seedlings were selected as the experimental plants, and a comprehensive transcriptomic and metabolomic analysis was conducted to elucidate the effects of hydrogen-rich water (HRW) on strawberries under salt stress. The results indicated that HRW significantly promoted plant growth, particularly increasing root biomass by 49.50%. Additionally, HRW regulated the levels of soluble sugars, malondialdehyde (MDA), and antioxidant enzymes, enhancing the cellular uptake of potassium ions and the expulsion of sodium ions. The levels of Ca2+ and Mg2+ in organelles increased by 2.06 and 2.45-fold, respectively. Transcriptomic analysis revealed that HRW substantially altered gene expression in strawberry roots; under salt stress, HRW up-regulated beneficial biological processes. Furthermore, genes related to ion absorption and transport, antioxidant enzymes, and cell wall biosynthesis were screened. Meanwhile, key common pathways were identified in differentially expressed metabolites (DEMs) and differentially expressed genes (DEGs) related to phenylpropane biosynthesis, alanine, aspartate, and glutamate metabolism, amino and nucleotide sugar metabolism, and galactose metabolism. A molecular mechanism for mitigating salt stress in strawberry seedlings by HRW was provided by the integrated approaches in this research, reflecting the potential applications of hydrogen gas in agriculture.

physiology↗

Antimicrobial Profile from Frog Skin Peptides

This study evaluates the antimicrobial efficacy of frog skin-derived peptides Magainin 1, Magainin 2, and Bombesin against Bacillus subtilis, Escherichia coli, and Trichoderma harzianum. Experimental setups involved uniform inoculation of the microorganisms on 20 mL agar plates, treated with varying volumes (1.5 {micro}L, 5 {micro}L, and 10 {micro}L) of each peptide (10 mg/mL). For Bacillus subtilis, Magainin 2, and Bombesin demonstrated significant antibacterial activity, with inhibition zones increasing in size proportionally to the peptide volumes. Magainin 2 showed the highest efficacy, surpassing ampicillin at higher volumes. In Escherichia coli, similar dose-dependent antibacterial effects were observed, with Magainin 2 again showing superior performance, matching or exceeding the inhibition zones of ampicillin. Notably, Magainin 2, and Bombesin exhibited antifungal activity against Trichoderma harzianum with Amphotericin resistance. These antibacterial peptides show inhibitory activity on fungi, gram-positive higher than gram-negative bacteria. These findings highlight the potential of Magainin 2, and Bombesin as antimicrobial agents except of Magainin 1.

microbiology↗

Common data models to streamline metabolomics processing and annotation, and implementation in a Python pipeline

To standardize metabolomics data analysis and facilitate future computational developments, it is essential is have a set of well-defined templates for common data structures. Here we describe a collection of data structures involved in metabolomics data processing and illustrate how they are utilized in a full-featured Python-centric pipeline. We demonstrate the performance of the pipeline, and the details in annotation and quality control using large-scale LC-MS metabolomics and lipidomics data and LC-MS/MS data. Multiple previously published datasets are also reanalyzed to showcase its utility in biological data analysis. This pipeline allows users to streamline data processing, quality control, annotation, and standardization in an efficient and transparent manner. This work fills a major gap in the Python ecosystem for computational metabolomics. Author SummaryAll life processes involve the consumption, creation, and interconversion of metabolites. Metabolomics is the comprehensive study of these small molecules, often using mass spectrometry, to provide critical information of health and disease. Automated processing of such metabolomics data is desired, especially for the bioinformatics community with familiar tools and infrastructures. Despite of Pythons popularity in bioinformatics and machine learning, the Python ecosystem in computational metabolomics still misses a complete data pipeline. We have developed an end-to-end computational metabolomics data processing pipeline, based on the raw data preprocessor Asari [1]. Our pipeline takes experimental data in .mzML or .raw format and outputs annotated feature tables for subsequent biological interpretation. We demonstrate the application of this pipeline to multiple metabolomics and lipidomics datasets. Accompanying the pipeline, we have designed a set of reusable data structures, released as the MetDataModel package, which shall promote more consistent terminology and software interoperability in this area.

bioinformatics↗

The dual coding of a single sex pheromone receptor in regulating the mating behavior of Asian Honeybee Apis cerana

In honeybee society, a virgin queen usually mates only once with several drones before founding a colony. For the rest of her prolific life, she will not engage in subsequent mating events. In the Asian honeybee Apis cerana, the mechanisms controlling this reproductive strategy involves the queen-released mandibular pheromone (QMP). This pheromone blend regulates the physiology and reproductive behavior of workers and drones. Its main component, 9-oxo-(E)-2-decenoic acid (9-ODA), acts as a sex pheromone and attracts drones. However, how the QMP prevents additional mating later in the queens life remains elusive. Using behavioral and chemical analysis, we show that the QMP component methyl p-hydroxybenzoate (HOB) released by mated queens inhibits male attraction to 9-ODA. Furthermore, in vivo electroantennogram and single sensillum recording data indicated that HOB alone significantly reduces the spontaneous spike activity of 9-ODA-sensitive olfactory receptor neurons (ORNs). To explore the molecular mechanism underlying this inverse effect, we conducted qPCR and in situ hybridization assays. The results indicated that AcerOr11 is specifically expressed in sensilla placodea from the drones antennae, which are the sensilla that narrowly respond to both 9-ODA and HOB. We then cloned and expressed AcerOr11 in a Xenopus oocyte expression system, where AcerOr11 induced robust inward (regular) currents in response to 9-ODA. Intriguingly, HOB induced inverse currents in a dose-dependent manner. This suggests that HOB may act as an inverse agonist against AcerOr11, providing additional odor-coding information. Based on these findings, we propose a model in which AcerOr11 function as a dual modulators in regulating the mating behavior of A. cerana. The inverse agonist, HOB, can help manage the population dynamics of honeybees in apiculture.

molecular biology↗

BrainCellR: A Precise Cell Type Nomenclature R Package for Comparative Analysis Across Brain Single-Cell Datasets

Single-cell studies in neuroscience require precise cell type classification and consistent nomenclature that allows for meaningful comparisons across diverse datasets. Current approaches often lack the ability to identify fine-grained cell types and establish standardized annotations at the cluster level, hindering comprehensive understanding of the brains cellular composition. To facilitate data integration across multiple models and datasets, we designed BrainCellR. This package provides researchers with a powerful and user-friendly tool for efficient cell type classification and nomination from single-cell transcriptomic data. BrainCellR goes beyond conventional classification approaches by incorporating a standardized nomenclature system for cell types at the cluster level. This feature enables consistent and comparable annotations across different studies, promoting data integration and providing deeper insights into the complex cellular landscape of the brain. Contactsimone.marini@ufl.edu or guangzhong.wang@picb.ac.cn

bioinformatics↗

Spatial Localization Ability of Planarians Identified Through the Light Maze Paradigm

Spatial localization ability is crucial for free-living animals to fit the environment. As shown by previous studies, planarians can be conditioned to discriminate directions. However, due to their simplicity and primitiveness, they had never been considered to have true spatial localization ability to retrieve locations of objects and places in the environment. Here, we introduce a light maze training paradigm to demonstrate that a planarian worm can navigate to a former recognized place from the start point, even if the worm is transferred into a newly produced maze. This finding identifies the spatial localization ability of planarians for the first time, which provides clues for the evolution of spatial learning. Since the planarians have a primitive brain with simple structures, this paradigm can also provide a simplified model for a detailed investigation of spatial learning.

animal behavior and cognition↗

Diving Behavior Reveals Humidity Sensing Ability of Water Deprived Planarians

Humidity sensing ability is crucial to terrestrial animals for fitting the environment. Researchers made great progress in recent study about humidity sensing mechanisms of terrestrial animals. However, it is poorly understood whether humidity sensing exists in aquatic animals. Here, we demonstrate that the aquatic planarians, one of the primitive forerunners of later animals, has the ability of humidity sensing and is capable of using the ability to perceive the water beneath itself from a drought place to seek survival. The behavior we discovered is described as diving because the worms twist its body to break away from the mucus that make them adhere to the drought place and drop into the water. The behavior is triggered by rapidly increasing humidity. This finding suggests that humidity sensing ability exists in the lower aquatic animals, and the ability might be used to seek for water when aquatic animals are facing desiccation. The finding also suggests that survival-seeking and decision-making behavior have appeared in the primitive planarian worms.

animal behavior and cognition↗

TSNAdb v2.0: the updated version of tumor-specific neoantigen database

Tumor neoantigens have been well-acknowledged as ideal targets for tumor immunotherapy in recent years. With the deepening of research on neoantigen-based tumor immunotherapy, comprehensive neoantigen databases are urgently needed to meet the growing demand for clinical studies. We have built the Tumor-Specific NeoAntigen Database (TSNAdb v1.0) previously, which has attracted wide attention. In this study, we provide an updated version of the Tumor-Specific NeoAntigen Database (TSNAdb v2.0) with several new features including 1) taking stricter criteria for neoantigen identification. 2) providing predicted neoantigens derived from three types of somatic mutations. 3) collecting experimentally validated neoantigens and classifying them according to the evidence. TSNAdb v2.0 is freely available at https://pgx.zju.edu.cn/tsnadb/.

bioinformatics↗

Dominant constraints on the evolution of rhythmic gene expression

Although the individual transcriptional regulators of the core circadian clock are distinct amongst different organisms, the autoregulatory feedback loops they form are conserved. This unified design principle explains how daily physiological activities oscillate across species. However, whether analogous design principles govern the gene expression output of circadian clocks is unknown. Herein, we performed a comparative analysis of rhythmic gene expression in eight diverse species and captured four common distribution patterns of cycling gene expression across these species. We hypothesized that maintenance of reduced energetic costs constrains the evolution of rhythmic gene expression. Our large-scale computational simulations support this hypothesis by showing that selection against high-energy expenditure completely regenerates all cycling gene patterns. Moreover, we find that the late- and early-phase peaks of rhythmic expression have been subjected to this type of selective pressure. Therefore, energetic costs have constricted the cycling transcriptome throughout evolutionary history.

cell biology↗

Reconstruction of the cell pseudo-space from single-cell RNA sequencing data with scSpace

Tissues are highly complicated with spatial heterogeneity in gene expression. However, the cutting-edge single-cell RNA-seq technology eliminates the spatial information of individual cells, which contributes to the characterization of cell identities. Herein, we propose single-cell spatial position associated co-embeddings (scSpace), an integrative algorithm to distinguish spatially variable cell subclusters by reconstructing cells onto a pseudo-space with spatial transcriptome references (Visium, STARmap, Slide-seq, etc.). We demonstrated that scSpace can define biologically meaningful cell subpopulations neglected by single-cell RNA-seq or spatially resolved transcriptomics. The use of scSpace to uncover the spatial association within single-cell data, reproduced, the hierarchical distribution of cells in the brain cortex and liver lobules, and the regional variation of cells in heart ventricles and the intestinal villus. scSpace identified cell subclusters in intratelencephalic neurons, which were confirmed by their biomarkers. The application of scSpace in melanoma and Covid-19 exhibited a broad prospect in the discovery of spatial therapeutic markers.

bioinformatics↗

Biological responses to terahertz radiation with different power density in primary hippocampal neurons

BackgroundTerahertz (THz) radiation is a valuable imaging and sensing tool which is widely used in industry and medicine. However, it biological effects including genotoxicity and cytotoxicity are not clear, particularly on the nervous system. In this study, we investigated how THz radiation with different frequency and intensity would affect the morphology, cell growth and function of rat hippocampal neurons in vitro. MethodsPrimary hippocampal neuronal cells were isolated from newborn Wistar rat pups and were exposed to THz radiation with the frequencies of 0.12 THz and 0.141 THz, at an power intensities of 10 mW/cm2 and 30 mW/cm2 respectively. The cellular activities were evaluated by Cell Counting Kit-8 after exposure for 10 min and 30 min. The cellular apoptosis was examined by Annexin V staining using flow cytometry and the ultrastructure was detected by electron microscopy. Moreover, the amount of amino acid in the cultured neurons was measured by high performance liquid chromatography (HPLC). ResultsNo obvious morphological changes, such as axon length and axon number, could be detected in primary neurons after exposure to 10mW/cm2 or 50 mW/cm2 THz for 30 min. However, the overall cellular activities were differentially affected by 10mW/cm2 and 50 mW/cm2 THz. Obvious cellular apoptosis was induced by both 10mW/cm2 and 50 mW/cm2 exposure. We also found that the amounts of most amino acids did not change significantly after exposure to these two types of THz radiation. ConclusionsThe effects of THz radiation on hippocampal neurons depend on frequency, power, exposure time as well as the measurement time after the exposure. These results will provide important information for further investigation of the effect of THz radiation on the nervous system.

neuroscience↗