Biology subjects

Xu, Y.

Publications and source records attributed to Xu, Y..

At least 541 records · Page 30Linked to original sources

bioRxiv2023

Exploring NCATS In-House Biomedical Data for Evidence-based Drug Repurposing

AbstractDrug repurposing is a strategy for identifying new uses of approved or investigational drugs that are outside the scope of the original medical indication. Even though many repurposed drugs have been found serendipitously in the past, the increasing availability of large volumes of biomedical data has enabled more systemic, data-driven approaches for drug candidate identification. At National Center of Advancing Translational Sciences (NCATS), we invent new methods to generate new data and information publicly available to spur innovation and scientific discovery. In this study, we aimed to explore and demonstrate biomedical data generated and collected via two NCATS research programs, the Toxicology in the 21st Century program (Tox21) and the Biomedical Data Translator (Translator) for the application of drug repurposing. These two programs provide complementary types of biomedical data from uncovering underlying biological mechanisms with bioassay screening data from Tox21 for chemical clustering, to enrich clustered chemicals with scientific evidence mined from the Translator towards drug repurposing. 129 chemical clusters have been generated and three of them have been further investigated for drug repurposing candidate identification, which is detailed as case studies.

bioinformatics↗

bioRxiv2023

Modeling Mechanical Activation of Macrophages During Pulmonary Fibrogenesis for Targeted Anti-Fibrosis Therapy

Pulmonary fibrosis, as seen in idiopathic pulmonary fibrosis (IPF) and COVID-induced pulmonary fibrosis, is an often-fatal lung disease. Increased numbers of immune cells such as macrophages were shown to accumulate in the fibrotic lung, but it is unclear how they contribute to the development of fibrosis. To recapitulate the macrophage mechanical activation in the fibrotic lung tissue microenvironment, we developed a fibrotic microtissue model with cocultured human macrophages and fibroblasts. We show that profibrotic macrophages seeded on topographically controlled stromal tissue constructs become mechanically activated. The resulting co-alignment of macrophages, collagen fibers and fibroblasts promote widespread fibrogenesis in micro-engineered lung tissues. Anti-fibrosis treatment using pirfenidone disrupts the polarization and mechanical activation of profibrotic macrophages, leading to fibrosis inhibition. Pirfenidone inhibits the mechanical activation of macrophages by suppressing integrin M{beta}2 (CD11b/CD18) and Rho-associated kinase 2, which is a previously unknown mechanism of action of the drug. Together, these results demonstrate a potential pulmonary fibrogenesis mechanism at the tissue level contributed by mechanically activated macrophages. We propose the coculture, force-sensing microtissue model as a powerful tool to study the complex immune-stromal cell interactions and the mechanism of action of anti-fibrosis drugs.

bioengineering↗

bioRxiv2023

T2T-YAO: a Telomere-to-telomere Assembled Diploid Reference Genome for Han Chinese

Since its initial release in 2001, the human reference genome has been continuously improved in both continuity and accuracy, and the recently-released telomere-to-telomere version--T2T-CHM13--reaches its top quality after 20 years of effort. However, T2T-CHM13 does not represent an authentic diploid human genome, but rather one derived from a simplified, nearly homozygous genome of a hydatidiform mole cell line. To address this limitation and provide an alternative pertinent to the Chinese population, the largest ethnic group in the world, we have assembled a complete diploid human genome of a male Han Chinese, T2T-YAO, which includes telomere-to-telomere assemblies for all the 22+X+M and 22+Y chromosomes in his two haploids inherited separately from his parents. Both haplotypes contain no artificial sequences or model nucleotides and possess a high quality comparable to CHM13, with fewer than one error per [~]14 Mb. Derived from the individual who lives in the aboriginal region of Han Chinese, T2T-YAO shows clear ancestry and potential genetic continuity from the ancient ancestors of the Han population. Each haplotype of T2T-YAO possesses [~]340 Mb exclusive sequences and [~]3100 unique genes as compared to CHM13, and their genome sequences show greater genetic distance to CHM13 than to each other in terms of nucleotide polymorphism and structural variations. The construction of T2T-YAO would serve as a high-quality diploid reference that enables precise delineation of genomic variations in a haplotype-sensitive manner, which could advance our understandings in human evolution, hereditability of diseases and phenotypes, especially within the context of the unique variations of the Chinese population.

genetics↗

bioRxiv2023

Heme oxygenase-1 expressing omental macrophages as a therapeutic target in ovarian high grade serous carcinoma

Ovarian high grade serous carcinoma (HGSC) remains a disease of poor prognosis that is unresponsive to current immune checkpoint inhibitors. Although PI3K pathway alterations are common in HGSC, attempts to target this pathway have been unsuccessful. We hypothesised aberrant PI3K pathway activation may alter the HGSC immune microenvironment and present a novel targeting strategy. We used both murine models and HGSC patient samples to study the impact of loss of Pten, a negative regulator of PI3K pathway signalling. We identified populations of resident macrophages specifically in Pten null omental tumours. These macrophages derive from peritoneal fluid macrophages and have a unique gene expression programme, marked by high levels of HMOX1 expression, the gene for the enzyme heme oxygenase-1. Targeting resident peritoneal macrophages prevents appearance of HMOX1hi macrophages and in doing so reduces tumour growth. Furthermore, direct inhibition of HMOX1 extends survival in vivo. HMOX1hi macrophages with corresponding gene expression programmes are also identified in human HGSC tumours and their presence correlates with activated tumoural PI3K pathway/mTOR signalling and poor overall survival in HGSC patients. In contrast, tumours with low number of HMOX1hi macrophages are marked by increased adaptive immune response gene expression. Our data suggest that HMOX1hi macrophages represent a potential therapeutic target and biomarker for poor prognosis HGSC.

cancer biology↗

bioRxiv2023

M2-polarized macrophages prevent preterm birth and improve neonatal survival and immunity

Preterm birth (PTB), often preceded by preterm labor, is a major cause of neonatal morbidity and mortality worldwide. Most PTB cases involve intra-amniotic inflammation without detectable microorganisms, termed in utero sterile inflammation, for which there is no established treatment. Here, we propose homeostatic macrophages to prevent PTB and adverse neonatal outcomes caused by in utero sterile inflammation. Single-cell atlases of the maternal-fetal interface revealed that homeostatic maternal macrophages are reduced with human labor. M2 macrophage treatment prevented PTB and reduced adverse neonatal outcomes in mice with in utero sterile inflammation. Specifically, M2 macrophages halted premature labor by suppressing inflammatory responses in the amniotic cavity, including inflammasome activation, and mitigated placental and offspring lung inflammation. Moreover, M2 macrophages restored neonatal gut homeostasis and enhanced resistance to systemic bacterial infection. Our findings show that M2 macrophages are a promising strategy to mitigate PTB and improve neonatal outcomes from in utero sterile inflammation.

immunology↗

bioRxiv2023

Deep spatial proteomic exploration of severe COVID-19-related pulmonary injury in post-mortem specimens

The lung, as a primary target of SARS-CoV-2, exhibits heterogeneous microenvironment accompanied by various histopathological changes following virus infection. However, comprehensive insight into the protein basis of COVID-19-related pulmonary injury with spatial resolution is currently deficient. Here, we generated a region-resolved quantitative proteomic atlas of seven major pathological structures within the lungs of COVID-19 victims by integrating histological examination, laser microdissection, and ultrasensitive proteomic technologies. Over 10,000 proteins were quantified across 71 dissected FFPE post-mortem specimens. By comparison with control samples, we identified a spectrum of COVID-19-induced protein and pathway dysregulations in alveolar epithelium, bronchial epithelium, and pulmonary blood vessels, providing evidence for the proliferation of transitional-state pneumocytes. Additionally, we profiled the region-specific proteomes of hallmark COVID-19 pulmonary injuries, including bronchiole mucus plug, pulmonary fibrosis, airspace inflammation, and hyperplastic alveolar type 2 cells. Bioinformatic analysis revealed the enrichment of cell-type and functional markers in these regions (e.g. enriched TGFBI in fibrotic region). Furthermore, we identified the up-regulation of proteins associated with viral entry, host restriction, and inflammatory response in COVID-19 lungs, such as FURIN and HGF. Collectively, this study provides spatial proteomic insights for understanding COVID-19-caused pulmonary injury, and may serve as a valuable reference for improving therapeutic intervention for severe pneumonia.

systems biology↗

bioRxiv2023

Arabidopsis Transcription Factor WRKY45 Confers Cadmium Tolerance via Activating PCS1 and PCS2 Expression

Cadmium (Cd) has long been recognized as toxic pollutant to crops worldwide. The biosynthesis of glutathione-dependent phytochelatin plays crucial roles in the detoxification of Cd in plants. However, its regulatory mechanism remains elusive. Here, we revealed that Arabidopsis transcription factor WRKY45 confers Cd tolerance via promoting the expression of PC synthesis-related genes PCS1 and PCS2, respectively. Firstly, we found that Cd stress induces the transcript levels of WRKY45 and its protein abundance. Accordingly, in contrast to wild type Col-0, the increased sensitivity to Cd is observed in wrky45 mutant, while overexpressing WRKY45 plants are more tolerant to Cd. Secondly, quantitative real-time PCR revealed that the expression of AtPCS1 and AtPCS2 is stimulated in overexpressing WRKY45 plants, but decreased in wrky45 mutant. Thirdly, WRKY45 promotes the expression of PCS1 and PCS2, electrophoresis mobility shift assay analysis uncovered that WRKY45 directly bind to the W-box cis-element of PCS2 promoter. Lastly, the overexpression of WRKY45 in Col-0 leads to more accumulation of PCs in Arabidopsis, and the overexpression of PCS1 or PCS2 in wrky45 mutant plants rescues the phenotypes induced by Cd stress. In conclusion, our results show that AtWRKY45 positively regulate Cd tolerance in Arabidopsis via activating PCS1 and PCS2 expression. Environmental implicationAccumulation of cadmium (Cd) in soils poses a threat to crop productivity and food safety. It has been revealed that phytochelatin (PC) plays an essential role in plants to alleviate Cd toxicity, yet the regulatory mechanisms governing its expression remain unclear. We have demonstrated that the Arabidopsis transcription factor WRKY45 directly activates the expression of PCS1 and PCS2, which encode PC synthase, thereby increasing the content of PC and enhancing Arabidopsis tolerance to Cd stress. These findings offer insights into precise regulation strategies for crop Cd tolerance via modulation of WRKY45 homologue in crops.

molecular biology↗

bioRxiv2023

Theranostic Bottle-Brush Polymers Tailored for Universal Solid-Tumour Targeting

Nanomedicines involving nanotechnologies and engineering of nanomaterials for medicines have shown great promise in diagnosis and treatment of diseases including cancers. A major hurdle that limits the successful clinical translation of nanomedicines, however, is how to overcome the cascaded biological barriers and improve the delivery efficacy towards the disease sites and minimize the toxicity against healthy tissues and cells. Here, we report a type of bottle-brush-like polymers systematically optimized in their chemical structures, sizes, and surface charges that lead to their outstanding pharmacokinetics and tumour-targeting performances in a variety of both subcutaneous and orthotopic tumour models. The potential mechanism has been studied by revealing the structure-activity relationship of these polymers in overcoming the biological barriers, including their avoidance by the immune system and deep tumour infiltration. Our study may offer insight for a rational design of highly efficient delivery platform of polymeric nanomedicines that could effectively overcome the cascaded biological barriers and thus lead to high tumour-targeting efficacy and low toxicity.

bioengineering↗

bioRxiv2023

Mimicking Kidney Flow Shear Efficiently Induces Aggregation of LECT2, a Protein Involved in Renal Amyloidosis

Aggregation of leukocyte cell-derived chemotaxin 2 (LECT2) causes ALECT2, a systemic amyloidosis that affects the kidney and liver. Homozygosity of the I40V LECT2 mutation is believed to be necessary but not sufficient for the disease. Previous studies established that LECT2 fibrillogenesis is greatly accelerated by loss of its single bound zinc ion and stirring or shaking. These forms of agitation are often used to facilitate protein aggregation, but they create heterogeneous shear conditions, including air-liquid interfaces that denature proteins, that are not present in the body. Here, we determined the extent to which a more physiological form of mechanical stress--shear generated by fluid flow through a network of artery and capillary-sized channels--drives LECT2 fibrillogenesis. To mimic blood flow through the human kidney, where LECT2 and other proteins form amyloid deposits, we developed a microfluidic device consisting of progressively branched channels narrowing from 5 mm to 20 m in width. Flow shear was particularly pronounced at the branch points and in the smallest capillaries, and this induced LECT2 aggregation much more efficiently than conventional shaking methods. EM images suggested the resulting fibril structures were different in the two conditions. Importantly, results from the microfluidic device showed the first evidence that the I40V mutation accelerated fibril formation and increased both size and density of the aggregates. These findings suggest that kidney-like flow shear, in combination with zinc loss, acts in combination with the I40V mutation to trigger LECT2 amyloidogenesis. These microfluidic devices may be of general use for uncovering the mechanisms by which blood flow induces misfolding and amyloidosis of circulating proteins.

biochemistry↗

bioRxiv2023

Long-read Transcriptome Landscapes of Primary and Metastatic Liver Cancers at Transcript Resolution

BackgroundThe liver is the sixth most common site of primary cancer in humans and is frequently colonized by metastases from cancers of other organs. Few studies have investigated the transcriptomic profiles of matched primary tumor and hepatic metastases of patients. Moreover, the read length of 100-200 bases in conventional short-read RNA sequencing is too short, which makes it difficult to directly infer the full-length transcript structure. To help develop effective treatments and improve survival, it is crucial to understand the complex and diverse molecular mechanisms of primary and metastatic liver cancers. MethodsNinety-five primary and secondary liver cancer patients who underwent hepatic resection were included with long-read sequencing isoform-sequencing and short-read RNA sequencing. We compared the transcriptome landscapes of primary and metastatic liver cancers and systematically investigated HCC, paired primary tumors and liver metastases, and matched non-tumor liver tissues. ResultsWe defined the full-length isoform-level transcriptome of human primary and metastatic liver cancers and identified isoform-level diversity in HCC and metastasis-associated transcriptome variations in metastatic liver cancers. Specific RNA transcripts and isoform switching events with clinical implications were profoundly discovered in liver cancer. Metastasis-specific transcripts that can predict the metastatic risk and identify the primary sites of cancers of unknown primary liver metastasis patients were defined. Additionally, we found that adjacent paracancerous liver tissues are abnormal and characterized the premetastatic immunological and metabolic alterations in the liver that favor the spread of cancer metastases. ConclusionsOur findings strongly highlight the powerfulness of full-length transcriptome profiling to yield novel biological insights into understanding the molecular basis of tumorigenesis and will further benefit the treatment of primary and metastatic liver cancers.

genomics↗

bioRxiv2023

Learning Complete Protein Representation by Deep Coupling of Sequence and Structure

Learning effective representations is crucial for understanding proteins and their biological functions. Recent advancements in language models and graph neural networks have enabled protein models to leverage primary or tertiary structure information to learn representations. However, the lack of practical methods to deeply co-model the relationships between protein sequences and structures has led to suboptimal embeddings. In this work, we propose CoupleNet, a network that couples protein sequence and structure to obtain informative protein representations. CoupleNet incorporates multiple levels of features in proteins, including the residue identities and positions for sequences, as well as geometric representations for tertiary structures. We construct two types of graphs to model the extracted sequential features and structural geometries, achieving completeness on these graphs, respectively, and perform convolution on nodes and edges simultaneously to obtain superior embeddings. Experimental results on a range of tasks, such as protein fold classification and function prediction, demonstrate that our proposed model outperforms the state-of-the-art methods by large margins.

bioinformatics↗

bioRxiv2023

Augmented Super-Resolution Radial Fluctuations (aSRRF) Pushing the Limits of Structured Illumination Microscopy

Structured illumination microscopy (SIM) is a versatile super-resolution technique known for its compatibility with a wide range of probes and fast implementation. While 3D SIM is capable of achieving a spatial resolution of [~]120 nm laterally and [~]300 nm axially, attempting to further enhance the resolution through methods such as nonlinear SIM or 4-beam SIM introduces complexities in optical configurations, increased phototoxicity, and reduced temporal resolution. Here, we have developed a novel method that combines SIM with augmented super-resolution radial fluctuations (aSRRF) utilizing a single image through image augmentation. By applying aSRRF reconstruction to SIM images, we can enhance the SIM resolution to [~]50 nm isotopically, without requiring any modifications to the optical system or sample acquisition process. Additionaly, we have incorporated the aSRRF approach into an ImageJ plugin and demonstrated its versatility across various fluorescence microscopy images, showcasing a remarkable two-fold resolution increase.

cell biology↗

bioRxiv2023

Cryo-EM structure of TMEM63C suggests it functions as a monomer

The TMEM63 family proteins (A, B, and C), calcium-permeable channels in animals that are preferentially activated by hypo-osmolality, have been implicated in various physiological functions. Deficiency of these channels would cause many diseases including hearing loss. However, their structures and physiological roles are not yet well understood. In this study, we determined the cryo-EM structure of the mouse TMEM63C at 3.56 [A], and revealed structural differences compared to its plant orthologues OSCAs. Further structural guided mutagenesis and electrophysiological studies demonstrated the important roles of the coupling of TM0 and TM6 in channel activity. Additionally, we confirmed that the physiological state of TMEM63C is monomer, while TMEM63B is a mix of monomer and dimer in cells, suggesting that oligomerization is a novel regulatory mechanism for TMEM63 proteins.

biophysics↗

bioRxiv2023

Structural insights into dual-antagonize mechanism of AB928 on adenosine A2 receptors

The adenosine subfamily G protein-coupled receptors A2AR and A2BR were identified as promising candidates for cancer immunotherapy within recent years. One of the A2AR/A2BR dual antagonist, AB928, has progressed to phase II clinic trial for the treatment of rectal cancer. However, the precise mechanism underlying its dual-antagonistic properties remains elusive. Herein, we report crystal structures of A2AR in complex with AB928 and a selective A2AR antagonist, 2-118. The structures reveal a common binding mode on A2AR, wherein the ligands establish extensive interactions with residues from both the orthosteric pocket and the secondary pocket. Conversely, the cAMP assay together with molecular dynamics simulations conducted on both A2AR and A2BR indicate that the ligands adopt distinct binding modes on A2BR. Detailed analysis of their chemical structures suggests that AB928 can readily adapt to the A2BR pocket, while 2-118 cannot due to its intrinsic differences. This disparity potentially accounts for their divergent inhibitory efficacies between A2BR and A2AR. The findings from this study can serve as valuable structural templates for future development of selective or dual inhibitors targeting A2AR/A2BR in the context of cancer therapy.

cell biology↗

bioRxiv2023

DrugGPT: A GPT-based Strategy for Designing Potential Ligands Targeting Specific Proteins

DrugGPT presents a ligand design strategy based on the autoregressive model, GPT, focusing on chemical space exploration and the discovery of ligands for specific proteins. Deep learning language models have shown significant potential in various domains including protein design and biomedical text analysis, providing strong support for the proposition of DrugGPT. In this study, we employ the DrugGPT model to learn a substantial amount of protein-ligand binding data, aiming to discover novel molecules that can bind with specific proteins. This strategy not only significantly improves the efficiency of ligand design but also offers a swift and effective avenue for the drug development process, bringing new possibilities to the pharmaceutical domain. In our research, we particularly optimized and trained the GPT-2 model to better adapt to the requirements of drug design. Given the characteristics of proteins and ligands, we redesigned the tokenizer using the BPE algorithm, abandoned the original tokenizer, and trained the GPT-2 model from scratch. This improvement enables DrugGPT to more accurately capture and understand the structural information and chemical rules of drug molecules. It also enhances its comprehension of binding information between proteins and ligands, thereby generating potentially active drug candidate molecules. Theoretically, DrugGPT has significant advantages. During the model training process, DrugGPT aims to maximize the conditional probability and employs the back-propagation algorithm for training, making the training process more stable and avoiding the Mode Collapse problem that may occur in Generative Adversarial Networks in drug design. Furthermore, the design philosophy of DrugGPT endows it with strong generalization capabilities, giving it the potential to adapt to different tasks. In conclusion, DrugGPT provides a forward-thinking and practical new approach to ligand design. By optimizing the tokenizer and retraining the GPT-2 model, the ligand design process becomes more direct and efficient. This not only reflects the theoretical advantages of DrugGPT but also reveals its potential applications in the drug development process, thereby opening new perspectives and possibilities in the pharmaceutical field.

bioinformatics↗

bioRxiv2023

Timecourse and source localization of abstract and concrete semantic representations.

Dual coding theories of knowledge suggest that meaning is represented in the brain by a double code, which comprises language-derived representations in the Anterior Temporal Lobe and sensory-derived representations in perceptual and motor regions. This approach predicts that concrete semantic features should activate both codes, whereas abstract features rely exclusively on the linguistic code. Using magnetoencephalography (MEG), we adopted a temporally resolved multiple regression approach to identify the contribution of abstract and concrete semantic predictors to the underlying brain signal. Results evidenced early involvement of anterior-temporal and inferior-frontal brain areas in both abstract and concrete semantic information encoding. At later stages, occipito-temporal regions showed greater responses to concrete compared to abstract features. The present findings shed new light on the temporal dynamics of abstract and concrete semantic representations in the brain and suggest that the concreteness of words processed first with a transmodal/linguistic code, housed in frontotemporal brain systems, and only after with an imagistic/sensorimotor code in perceptual and motor regions.

neuroscience↗

bioRxiv2023

KaScape: A sequencing-based method for global characterization of protein-DNA binding affinity

It is difficult to exhaustively screen all possible DNA binding sequences for a given transcription factor (TF). Here, we develop a method named "KaScape", by which, TFs bind to all possible DNA sequences in the same DNA pool where the DNA sequences are prepared by randomized oligo synthesis and the random length can be adjusted to, e.g., 4, 5, 6, or 7, etc. After separating the bound from unbound double-strand DNA, their sequences are determined by next-generation sequencing. To demonstrate the relative binding affinities of all possible DNA sequences determined by KaScape, we develop a three-dimensional KaScape viewing software based on a K-mer graph. We apply KaScape to 12 plant TF family AtWRKY proteins and find that all AtWRKY proteins bind to the core sequence GAC with similar profiles. KaScape not only can detect binding sequences that are consistent with the consensus W-box "TTGAC(C/T)", but also other sequences with weak affinity. KaScape provides a high-throughput, easy-to-operate, sensitive, and exhaustive method to quantitatively characterize the relative binding strength of a TF to all possible binding sequences, allowing us to comprehensively characterize the specificity and affinity landscape of transcription factors, particularly for moderate and low affinity binding sites. HighlightsO_LIA general method, KaScape, using NGS (next-generation sequencing) with a series of random dsDNA for exhaustive characterization of protein-DNA binding. C_LIO_LIA K-mer-based analysis and display software tool KGViewer developed to analyze the relative affinity landscape of KaScape results. C_LI

biochemistry↗

bioRxiv2023

Guanine-containing ssDNA and RNA induce dimeric and tetrameric SAMHD1 in cryo-EM and binding studies

The dNTPase activity of tetrameric SAM and HD domain containing deoxynucleoside triphosphate triphosphohydrolase 1 (SAMHD1) plays a critical role in cellular dNTP regulation. SAMHD1 also associates with stalled DNA replication forks, DNA repair foci, ssRNA, and telomeres. The above functions require nucleic acid binding by SAMHD1, which may be modulated by its oligomeric state. Here we establish that the guanine-specific A1 activator site of each SAMHD1 monomer is used to target the enzyme to guanine nucleotides within single-stranded (ss) DNA and RNA. Remarkably, nucleic acid strands containing a single guanine base induce dimeric SAMHD1, while two or more guanines with [~]20 nucleotide spacing induce a tetrameric form. A cryo-EM structure of ssRNA-bound tetrameric SAMHD1 shows how ssRNA strands bridge two SAMHD1 dimers and stabilize the structure. This ssRNA-bound tetramer is inactive with respect to dNTPase and RNase activity.

biochemistry↗