Biology subjects

Liu, H.

Publications and source records attributed to Liu, H..

At least 577 records · Page 32Linked to original sources

bioRxiv2023

Chitosan oligosaccharide induces plant resistance gene expression in Pinus massoniana

Chitosan oligosaccharides are the main degradation products from chitosan or chitin and have been reported to induce resistance to diseases in herbaceous plants like cucumber and Arabidopsis. Concomitantly, pine wilt disease is a devastating disease of conifer tree species. Here, we hypothesized that chitosan oligosaccharides induce plant resistance gene (PRG) expression in the woody plant Masson pine, Pinus massoniana. Chitosan oligosaccharides were inoculated into P. massoniana seedlings and the BGISEQ-500 platform was used to generate transcriptomes from chitosan oligosaccharide-treated P. massoniana and control seedlings. A total of 501 differentially expressed genes (DEGs) were identified by comparing the treatment and control groups. A total of 251 (50.1%) DEGs were up-regulated in the treatment relative to the control seedlings and 250 (49.9%) were down-regulated. Inoculation of chitosan oligosaccharide induced the expression of 31 PRGs in P. massoniana seedlings and the relative expression levels of six of the PRGs were verified by RT-qPCR. This is the first study to demonstrate that chitosan oligosaccharide induces the expression of PRGs in a tree species. These results provide important insights into the function of chitosan oligosaccharides and further the prospects of developing a chitosan oligosaccharide-based immune inducer for controlling pine wilt disease.

genomics↗

bioRxiv2023

Insulin determines the effects of TGF-beta on HNF4alpha transcription and epithelial-to-mesenchymal transition in hepatocytes

To date, epithelial-to-mesenchymal transition (EMT) has been observed in cultured hepatocytes, but not in vivo. TGF-{beta} is supposed to initiate EMT in hepatocytes by inhibiting HNF4 through the SMAD2/3 complex. We report that TGF-{beta} does not directly inhibit HNF4, but contributes to its transcriptional regulation by SMAD2/3 recruiting acetyltransferase CBP/p300 to the HNF4 promoter. The recruitment of CBP/p300 is indispensable for C/EBPa binding, another essential requirement for constitutive HNF4 expression in hepatocytes. In contrast to the observed induction of HNF4, SMAD2/3 inhibits C/EBP transcription. Therefore, long-term TGF-{beta} incubation results in C/EBP depletion, which abrogates HNF4 expression. Intriguingly, SMAD2/3 inhibitory binding to the C/EBP promoter is abolished by insulin. Thus, maintaining a high insulin concentration in culture medium ensures constitutive HNF4 and thereby prevents TGF-{beta}-induced hepatocyte EMT. Furthermore, insulin inhibits TGF-{beta}-induced SMAD2/3 binding to the promoters of core EMT transcription factors e.g., SNAI1. SNAI1 transcription requires both SMAD2/3 and FOXO1 in nuclei. Insulin inhibits SNAI1 transcription through impeding SMAD2/3 binding to its promoter and inducing FOXO1 phosphorylation. Hence, insulin is the key factor that prevents TGF-{beta}-induced EMT in hepatocytes.

cell biology↗

bioRxiv2023

High-throughput single molecule tracking identifies drug interactions and cellular mechanisms

The regulation of cell physiology depends largely upon interactions of functionally distinct proteins and cellular components. These interactions may be transient or long-lived, but often affect protein motion. Measurement of protein dynamics within a cellular environment, particularly while perturbing protein function with small molecules, may enable dissection of key interactions and facilitate drug discovery; however, current approaches are limited by throughput with respect to data acquisition and analysis. As a result, studies using super-resolution imaging are typically drawing conclusions from tens of cells and a few experimental conditions tested. We addressed these limitations by developing a high-throughput single-molecule tracking (htSMT) platform for pharmacologic dissection of protein dynamics in living cells at an unprecedented scale (capable of imaging > 106 cells/day and screening > 104 compounds). We applied htSMT to measure the cellular dynamics of fluorescently tagged estrogen receptor (ER) and screened a diverse library to identify small molecules that perturbed ER function in real time. With this one experimental modality, we determined the potency, pathway selectivity, target engagement, and mechanism of action for identified hits. Kinetic htSMT experiments were capable of distinguishing between on-target and on-pathway modulators of ER signaling. Integrated pathway analysis recapitulated the network of known ER interaction partners and suggested potentially novel, kinase-mediated regulatory mechanisms. The sensitivity of htSMT revealed a new correlation between ER dynamics and the ability of ER antagonists to suppress cancer cell growth. Therefore, measuring protein motion at scale is a powerful method to investigate dynamic interactions among proteins and may facilitate the identification and characterization of novel therapeutics.

cell biology↗

bioRxiv2022

Obtaining Increased Functional Proteomics Insights from Thermal Proteome Profiling through Optimized Melt Shift Calculation and Statistical Analysis

Thermal Proteome Profiling (TPP) is an invaluable tool for functional proteomics studies that has been shown to discover changes associated with protein-ligand, protein- protein, and protein-RNA interaction dynamics along with changes in protein stability resulting from cellular signaling. The increasing number of reports employing this assay has not been met concomitantly with advancements and improvements in the quality and sensitivity of the corresponding data analysis. The gap between data acquisition and data analysis tools is even more apparent as TPP findings have reported more subtle melt shift changes related to protein post-translational modifications. In this study, we have improved the Inflect data analysis pipeline (now referred to as InflectSSP, available at https://CRAN.R-project.org/package=InflectSSP) to increase the sensitivity of detection for both large and subtle changes in the proteome as measured by TPP. Specifically, InflectSSP now has integrated statistical and bioinformatic functions to improve objective functional proteomics findings from the quantitative results obtained from TPP studies through increasing both the sensitivity and specificity of the data analysis pipeline. To benchmark InflectSSP, we have reanalyzed two publicly available datasets to demonstrate the performance of this publicly available R based program for TPP data analysis. Additionally, we report new findings following temporal treatment of human cells with the small molecule Thapsigargin which induces the unfolded protein response (UPR). InflectSSP analysis of our UPR study revealed highly reproducible target engagement over time while simultaneously providing new insights into the dynamics of UPR induction.

biophysics↗

bioRxiv2022

Neuronal TIMP2 regulates hippocampus-dependent plasticity and extracellular matrix complexity

The functional output of the hippocampus, a brain region subserving memory processes, depends on highly orchestrated cellular and molecular processes that regulate synaptic plasticity throughout life. The structural requirements of such plasticity and molecular processes involved in this regulation are poorly understood. Specific molecules, including tissue inhibitor of metalloproteinases-2 (TIMP2) have been implicated in processes of plasticity in the hippocampus, a role that decreases with brain aging as expression is lost. Here, we report that TIMP2 is highly expressed by neurons within the hippocampus and its loss drives changes in cellular programs related to adult neurogenesis and dendritic spine turnover with corresponding impairments in hippocampus-dependent memory. Consistent with the accumulation of ECM in the hippocampus we observe with aging, we find that TIMP2 acts to reduce accumulation of extracellular matrix (ECM) around synapses in the hippocampus. Moreover, its removal results in hindrance of newborn neuron migration through a denser ECM network. A novel conditional TIMP2 KO mouse reveals that neuronal TIMP2 regulates adult neurogenesis, accumulation of ECM, and ultimately hippocampus-dependent memory. Our results define a mechanism whereby hippocampus- dependent function is regulated by TIMP2 and its interactions with the ECM to regulate diverse processes associated with synaptic plasticity.

neuroscience↗

bioRxiv2022

De novo protein backbone generation based on diffusion with structured priors and adversarial training

In de novo deisgn of protein backbones with deep generative methods, the designability or physical plausibility of the generated backbones needs to be emphasized. Here we report SCUBA-D, a method using denoising diffusion with priors of non-zero means to transform a low quality initial backbone into a high quality backbone. SCUBA-D has been developed by gradually adding new components to a basic denoising diffusion module to improve the physical plausibility of the denoised backbone. It comprises a module that uese one-step denoising to generate prior backbones, followed by a high resolution denoising diffusion module, in which structure diffusion is assisted by the simultaneous diffusion of a language model representation of the amino acid sequence. To ensure high physical plausibility of the denoised output backbone, multiple generative adversarial network (GAN)-style discriminators are used to provide additional losses in training. We have computationally evaluated SCUBA-D by applying structure prediction to amino acid sequences designed on the denoised backbones. The results suggest that SCUBA-D can generate high quality backbones from initial backbones that contain noises of various types or magnitudes, such as initial backbones coarsely sketched to follow certain overall shapes, or initial backbones comprising well-defined functional sites connected by unknown scaffolding regions.

bioinformatics↗

bioRxiv2022

The pan-genome and local adaptation of Arabidopsis thaliana

Arabidopsis thaliana has been used as a model species for research in a diverse collection of plant species. However, previous studies based on single reference genomes and short-read sequencing data are restricted to detecting variable genes and large structural variation (SV) underlying local adaptation. Here we de novo assemble high-quality chromosomal genomes of 38 A. thaliana ecotypes (with 6 relict ones) using PacBio-HiFi long-read sequencing. From these newly assembled genomes, we annotate several thousand new genes through pan-genomic analysis in comparison to the previous reference genome. The identified variable genes are mainly enriched in and associated with ecological adaptation and this species substantially expands its gene repertoire for local adaptation. We construct a graph-based pan-genome and identify 62,525 SVs which overlap with 14,243 genes. These genes are enriched in multiple ecological adaptation functions, including secondary metabolic processes, enzyme regulation, and biotic/abiotic stimulus. For example, a 566 bp insertion in the promoter of the light-adaptation KNAT3 gene was specific to the high-altitude relict Tibet-0 ecotype. This SV reduces the expression level of KNAT3 and promotes A. thaliana adaptation to habitats high in light radiation. In addition, compared with the SNPs, the SVs identified in this study captured the missing heritability and we detected novel SV associations with environmental variables in their native range, highlighting the value of SVs in environmental adaptation. The genome resources presented here will help pinpoint genetic changes that include both SVs and the ecotype-specific genes for local adaptation of A. thaliana and increase our understanding of the molecular mechanisms in this model species to respond to varied habitats.

genomics↗

bioRxiv2022

Discovery and biological evaluation of a potent small molecule CRM1 inhibitor for its selective ablation of extranodal NK/T cell lymphoma

BackgroundThe overactivation of NF-{kappa}B signaling is a key hallmark for the pathogenesis of extranodal natural killer/T cell lymphoma (ENKTL), a very aggressive subtype of non-Hodgkins lymphoma yet with rather limited control strategies. Previously, we found that the dysregulated exportin-1 (also known as CRM1) is mainly responsible for tumor cells to evade apoptosis and promote tumor-associated pathways such as NF-{kappa}B signaling. MethodsHerein we reported the discovery and biological evaluation of a potent small molecule CRM1 inhibitor, LFS-1107. We validated that CRM1 is a major cellular target of LFS-1107 by biolayer interferometry assay (BLI) and the knockdown of CRM1 conferred tumor cells with resistance to LFS-1107. ResultsWe found that LFS-1107 can strongly suppresses the growth of ENKTL cells at low-range nanomolar concentration yet with minimal effects on human platelets and healthy peripheral blood mononuclear cells. Treatment of ENKTL cells with LFS-1107 resulted in the nuclear retention of IkB and consequent strong suppression of NF-{kappa}B transcriptional activities, NF-{kappa}B target genes downregulation and attenuated tumor cell growth and proliferation. Furthermore, LFS-1107 exhibited potent activities when administered to immunodeficient mice engrafted with human ENKTL cells. ConclusionsTherefore, LFS-1107 holds great promise for the treatment of ENKTL and may warrant translation for use in clinical trials.

pharmacology and toxicology↗

bioRxiv2022

Heterotrophic bacteria drive sulfide oxidation in coastal sediments

Sulfate reduction and sulfur oxidation are very active in coastal sediments. They shape the biogeochemistry and microbial ecology at hot places of organic matter metabolism. Different from the well-studied sulfate reduction, sulfur oxidation in coastal sediments is still full of questions. Herein, we investigated the distribution of reduced sulfur compounds in differently layers of coastal sediments at the Yellow sea and found that sulfide (H2S), sulfane sulfur (S0), and thiosulfate mainly accumulated in anaerobic sediments and were mostly oxidized in anoxic and oxic interface in the sediments and the sea water. Bacterial community analysis indicated that heterotrophic bacteria are dominating species in surface sediments and sea water. Metagenome analysis showed that two sulfur-oxidizing genes encoding sulfide:quinone oxidoreductases (SQR) and persufide dioxygenases (PDO), were sharply more abundant than other sulfur-oxidizing genes in the coastal sediments. Since members of the marine Roseobacter clade were dominant in coastal waters and sediments, we studied the sulfur oxidation pathway in the Roseobacter Ruegeria pomeroyi DSS-3 and found that sulfide:quinone oxidoreductase, persulfide dioxygenase, and sulfite-oxidizing enzyme were the main enzymes for the oxidation of H2S, zerovalent sulfur, and sulfite/thiosulfate. This study, for the first time, clarified the dominating function of heterotrophic bacteria in sulfur oxidation in the coastal sediments and sea water. IMPORTANCECoastal sediments are the most productive ecosystems. We performed the microbial community diversity and metagenomic analysis of seawater and coastal sediments of the Yellow Sea and explored the sulfur oxidation process in them. We found that heterotrophic bacteria are dominating species in surface sediments and sea water, sulfide and sulfane sulfur were mostly oxidized in surface sediments, and the genes encoding SQR, PDO, and SOE are abundant. Using Ruegeria pomeroyi DSS-3 as the model strain, we studied how these enzymes cooperate to oxidize H2S to sulfate. Thus, this research revealed the critical role of heterotrophic bacteria in sulfur oxidation in coastal sediments and sea water.

microbiology↗

bioRxiv2022

Synergizing algorithmic design, photoclick chemistry and multi-material volumetric printing for accelerating complex shape engineering

Accelerating the designing and manufacturing of complex shapes has been a driving factor of modern industrialization. This has led to numerous advances in computational design and modeling and novel additive manufacturing (AM) techniques that can create complex shapes for bespoke applications. By combining a new coding-based design approach with high-throughput volumetric printing, we envision a new approach to transform the way we design and fabricate complex shapes. Here, we demonstrate an algorithmic voxel-based approach, which can rapidly generate and analyze porous structures, auxetic meshes and cylinders, or perfusable constructs. We use this design scheme in conjunction with new approaches for multi-material volumetric printing based on thiol-ene photoclick chemistry to rapidly fabricate complex heterogeneous structures. Collectively, the new design and fabrication technique we demonstrate can be used across a wide-spectrum of products such as actuators, biomedical implants and grafts, or tissue and disease models. TeaserA new scheme of rapidly designing and printing complex multi-material structures for implant and tissue graft applications.

bioengineering↗

bioRxiv2022

Predicting Drug Repurposing Candidates and Their Mechanisms from A Biomedical Knowledge Graph

BackgroundComputational drug repurposing is a cost- and time-efficient approach that aims to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It is especially critical for emerging and/or orphan diseases due to its cheaper investment and shorter research cycle compared with traditional wet-lab drug discovery approaches. However, the underlying mechanisms of action (MOAs) between repurposed drugs and their target diseases remain largely unknown, which is still a main obstacle for computational drug repurposing methods to be widely adopted in clinical settings. ResultsIn this work, we propose KGML-xDTD : a Knowledge Graph-based Machine Learning framework for explainably predicting Drugs Treating Diseases. It is a two-module framework that not only predicts the treatment probabilities between drugs/compounds and diseases but also biologically explains them via knowledge graph (KG) path-based, testable mechanisms of action (MOAs). We leverage knowledge-and-publication based information to extract biologically meaningful "demonstration paths" as the intermediate guidance in the Graph-based Reinforcement Learning (GRL) path-finding process. Comprehensive experiments and case study analyses show that the proposed framework can achieve state-of-the-art performance in both predictions of drug repurposing and recapitulation of human-curated drug MOA paths. ConclusionsKGML-xDTD is the first model framework that can offer KG-path explanations for drug repurposing predictions by leveraging the combination of prediction outcomes and existing biological knowledge and publications. We believe it can effectively reduce "black-box" concerns and increase prediction confidence for drug repurposing based on predicted path-based explanations, and further accelerate the process of drug discovery for emerging diseases.

bioinformatics↗

bioRxiv2022

Epigenomic complexity of the human brain revealed by single-cell DNA methylomes and 3D genome structures

Delineating the gene regulatory programs underlying complex cell types is fundamental for understanding brain functions in health and disease. Here, we comprehensively examine human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in over 500,000 cells from 46 brain regions. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. With these resources, we developed scMCodes that reliably predict brain cell types using their methylation status at select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell type-specific gene regulation in the adult human brain.

neuroscience↗

bioRxiv2022

Kinetic model derivation for design, building and operation of solid waste treatment unit based on system dynamics and computer simulation

Solid waste disposal is significantly important to maintain normal operation of both natural and artificial ecosystems. In this study, a kinetic model of solid waste treatment unit (SWTU) was upfront developed based on microbial ecology, system dynamics, cybernetics and digital simulation, which accurately described the relationships and interactions between solid waste decomposition (SWD) processes and biotic/abiotic factors. Then a specific SWTU prototype was designed and built from this kinetic model. A 370-day experiment demonstrated that SWTU maintained normal operation with robust stability and desired dynamic behaviors, and effectively disposed the solid waste. Therefore, this kinetic model was highly valid due to its high structural and behavioral similarity with the prototype. This research could lay a strong theoretical foundation for further closed-loop control and optimization of SWTU, and provide scientific guidance to environmental management and sustainable development.

ecology↗

bioRxiv2022

Architecture of chloroplast TOC-TIC translocon supercomplex

Chloroplasts rely on the translocon complexes in the outer and inner envelope membranes (termed TOC and TIC, respectively) to import thousands of different nuclear-encoded proteins from the cytosol1-4. While previous studies indicated that the TOC and TIC complexes may assemble into larger supercomplexes5-7, the overall architectures of the TOC-TIC supercomplexes and the mechanism of preprotein translocation are elusive. Here we report the cryo-electron microscopy (cryo-EM) structure of the TOC-TIC supercomplex from Chlamydomonas reinhardtii at an overall resolution of 2.8 [A]. The major subunits of the TOC complex (Toc75, Toc90 and Toc34) and TIC complex (Tic214, Tic20, Tic100 and Tic56), three chloroplast translocon-associated proteins (Ctap3, Ctap4 and Ctap5) and three newly-identified small inner-membrane proteins (Simp1-3) have been located in the supercomplex. As the largest protein, Tic214 traverses the inner membrane, the intermembrane space and the outer membrane, connecting the TOC complex with the TIC proteins. An inositol hexaphosphate (InsP6 or I6P) molecule is located at the Tic214-Toc90 interface and stabilizes their assembly. Moreover, four lipid molecules are located within or above an inner-membrane funnel formed by Tic214, Tic20, Simp1 and Ctap5. Furthermore, multiple potential pathways found in the TOC-TIC supercomplex may support translocation of different substrate preproteins into chloroplasts.

biophysics↗

bioRxiv2022

Incorporating Pre-training Paradigm for Antibody Sequence-Structure Co-design

Antibodies are versatile proteins that can bind to pathogens and provide effective protection for human body. Recently, deep learning-based computational antibody design has attracted popular attention since it automatically mines the antibody patterns from data that could be complementary to human experiences. However, the computational methods heavily rely on the high-quality antibody structure data, which is quite limited. Besides, the complementarity-determining region (CDR), which is the key component of an antibody that determines the specificity and binding affinity, is highly variable and hard to predict. Therefore, data limitation issue further raises the difficulty of CDR generation for antibodies. Fortunately, there exists a large amount of sequence data of antibodies that can help model the CDR and alleviate the reliance on structured data. By witnessing the success of pre-training models for protein modeling, in this paper, we develop an antibody pre-trained language model and incorporate it into the (antigen-specific) antibody design model in a systemic way. Specifically, we first pre-train an antibody language model based on the sequence data, then propose a one-shot way for sequence and structure generation of CDR to avoid the heavy cost and error propagation from an autoregressive manner, and finally leverage the pre-trained antibody model for the antigen-specific antibody generation model with some carefully designed modules. Through various experiments, we show that our method achieves superior performance over previous baselines on different tasks, such as sequence and structure generation, antigen-binding CDR-H3 design.

molecular biology↗

bioRxiv2022

eccDNA Atlas: a comprehensive resource of eccDNA catalog

Extrachromosomal circular DNA (eccDNA) represents a large category of nonmitochondrial and nonplasmid circular extrachromosomal DNA playing an indispensable role in various aspects such as tumorigenesis, immune responses, liquid biopsy, etc. However, characteristic and functions of eccDNA are fragmented, hiding behind abundant literatures and massive whole-genome sequencing (WGS) data, which have not been sufficiently used for identification of eccDNAs. Therefore, establishing an integrated repository portal is essential for identifying and analyzing eccDNAs. Here, we developed eccDNA Atlas (http://lcbb.swjtu.edu.cn/eccDNAatlas), a user-friendly database of eccDNAs that aims to provide a high-quality and integrated resource for browsing, searching and analyzing eccDNAs from multiple species. eccDNA Atlas currently containing 630,434 eccDNAs and 7,774 ecDNAs manually curated from literatures and 1,105 ecDNAs predicted by AmpliconArchitect based on WGS data involved in 66 diseases, 57 tissue and 319 cell lines. The content of each eccDNA entry included multiple aspects such as sequence, disease, function, characteristic, validation strategies, etc. Furthermore, abundant annotations and analyzing utilities were provided to explore existed eccDNAs in eccDNA Atlas or user-defined eccDNAs including oncogenes, typical enhancers, super enhancers, gene expression, survival, and genome visualization. Based on these resources, eccDNA Atlas will significantly improve our understanding of eccDNAs and serve as an important catalyst for future research of eccDNAs.

bioinformatics↗

bioRxiv2022

Repurposing clemastine to target glioblastoma cell stemness

Brain tumor-initiating cells (BTICs) and tumor cell plasticity promote glioblastoma (GBM) progression. Here, we demonstrate that clemastine, an over-the-counter drug for treating hay fever and allergy symptoms, effectively attenuated the stemness and suppressed the propagation of primary BTIC cultures bearing PDGFRA amplification. These effects on BTICs were accompanied by altered gene expression profiling indicative of their more differentiated states, resonating with the activity of clemastine in promoting the differentiation of normal oligodendrocyte progenitor cells (OPCs) into mature oligodendrocytes. Functional assays for pharmacological targets of clemastine revealed that Emopamil binding protein (EBP), an enzyme in the cholesterol biosynthesis pathway, is essential for BTIC propagation and a target that mediates the suppressive effects of clemastine. Finally, we showed that a neural stem cell-derived mouse glioma model displaying predominantly proneural features was similarly susceptible to clemastine treatment. Collectively, these results identify pathways essential for maintaining the stemness and progenitor features of GBMs, uncover BTIC dependency on EBP, and suggest that non-oncology, low-toxicity drugs with OPC differentiation-promoting activity can be repurposed to target GBM stemness and aid in their treatment.

cancer biology↗

bioRxiv2022

A permissive role for dopamine in the production of vigorous movements

Dopamine is essential for the production of vigorous movements, but how dopamine modifies the gain of motor commands remains unclear. Here, we developed a dexterous motor task in which head-restrained mice self-initiate fast and large-amplitude lever pushes with their left forelimb to earn rewards. We show that this task is goal-directed and depends on cortico-striatal circuits in the hemisphere contralateral to the limb used to push the lever. We find that unilateral loss of midbrain dopamine neurons reduces the speed and amplitude of lever pushes, and that levodopa treatment rapidly restores motor vigor, consistent with parkinsonian bradykinesia. Photometry recordings of striatal dopamine levels indicate that the therapeutic efficacy of levodopa does not require phasic dopamine release. In dopamine-intact mice, optogenetic stimulation of midbrain dopamine neurons calibrated to mimic transients evoked by rewards is also insufficient to increase the speed and amplitude of forelimb movements. Together, our data show that phasic dopamine transients are unlikely to specify the vigor of forelimb movements online as they are being executed, and suggest instead that dopamine plays a permissive role in the selection and production of vigorous movements. Our findings have important implications for our understanding of how the basal ganglia contribute to motor control under physiological conditions and in Parkinsons disease.

neuroscience↗