Biology subjects

Jin, W.

Publications and source records attributed to Jin, W..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

DSMBind: SE(3) denoising score matching for unsupervised binding energy prediction and nanobody design

Modeling the binding between proteins and other molecules is pivotal to drug discovery. Geometric deep learning is a promising paradigm for protein-ligand/protein-protein binding energy prediction, but its accuracy is limited by the size of training data as high-throughput binding assays are expensive. Herein, we propose an unsupervised binding energy prediction framework, named DSMBind, which does not need experimental binding data for training. DSMBind is an energy-based model that estimates the likelihood of a protein complex via SE(3) denoising score matching (DSM). This objective, applied at both backbone and side-chain levels, builds on a novel equivariant rotation prediction network derived from Eulers Rotation Equations. We find that the learned log-likelihood of protein complexes is highly correlated with experimental binding energy across multiple benchmarks, even matching the performance of supervised models trained on experimental data. We further demonstrate DSMBinds zero-shot binder design capability through a PD-L1 nanobody design task, where we randomize all three complementarity-determining regions (CDRs) and select the best CDR sequences based on DSMBind score. We experimentally tested the designed nanobodies with ELISA binding assay and successfully discovered a novel PD-L1 binder. In summary, DSMBind offers a versatile framework for binding energy prediction and binder design. Our code is publicly available at github.com/wengong-jin/DSMBind.

bioinformatics↗

bioRxiv2023

Upstream open reading frames dynamically modulate CLOCK protein translation to regulate circadian rhythm and sleep

The circadian rhythm is an evolutionarily conserved mechanism with translational regulation increasingly recognized as pivotal in its modulation. In this study, we found that upstream open reading frames (uORFs) are enriched in circadian rhythm genes, with particularly conserved uORFs present in core circadian clock genes. We demonstrate evidence that the uORFs of the core clock gene, Clock (Clk), rhythmically and substantially attenuate CLK protein translation in Drosophila, with pronounced suppression occurring during daylight hours. Eliminating Clk uORFs results in elevated CLK protein levels during the day and a compressed circadian cycle, along with a broad shift in clock gene expression rhythms. Interestingly, Clk uORF deletion also augments morning sleep by reducing dopaminergic activity. Beyond daily circadian adjustments, Clk uORFs play a role in modulating sleep patterns in response to the varying day lengths of different seasons, inhibiting translation in a day-length contingent manner. Furthermore, the Clk uORFs act as a master regulator to shape the rhythmic expression of a vast array of genes and influence multifaceted physiological outcomes. Collectively, our research sheds light on the intricate ways uORFs dynamically adjust downstream coding sequences to acclimate to environmental shifts.

neuroscience↗

bioRxiv2023

The chromatin accessibility dynamics during cell fate specifications in zebrafish early embryogenesis

Chromatin accessibility plays a critical role in the regulation of cell fate decisions. Although gene expression changes have been extensively profiled at the single-cell level during early embryogenesis, the dynamics of chromatin accessibility at cis-regulatory elements remain poorly studied. Here, we used a plate-based single-cell ATAC-seq method to profile the chromatin accessibility dynamics of over 10, 000 nuclei from zebrafish embryos. We investigated several important time points immediately after zygotic genome activation (ZGA), covering key developmental stages up to dome. The results revealed key chromatin signatures in the first cell fate specifications when cells start to differentiate into enveloping layer (EVL) and yolk syncytial layer (YSL) cells. Finally, we uncovered many potential cell-type specific enhancers and transcription factor motifs that are important for the cell fate specifications.

genomics↗

bioRxiv2023

CellPLM: Pre-training of Cell Language Model Beyond Single Cells

The current state-of-the-art single-cell pre-trained models are greatly inspired by the success of large language models. They trained transformers by treating genes as tokens and cells as sentences. However, three fundamental differences between single-cell data and natural language data are overlooked: (1) scRNA-seq data are presented as bag-of-genes instead of sequences of RNAs; (2) Cell-cell relations are more intricate and important than inter-sentence relations; and (3) The quantity of single-cell data is considerably inferior to text data, and they are very noisy. In light of these characteristics, we propose a new pre-trained model CellPLM, which takes cells as tokens and tissues as sentences. In addition, we leverage spatially-resolved transcriptomic data in pre-training to facilitate learning cell-cell relationships and introduce a Gaussian mixture prior distribution as an additional inductive bias to overcome data limitation. CellPLM is the first single-cell pre-trained transformer that encodes cell-cell relations and it consistently outperforms existing pre-trained and non-pre-trained models in diverse downstream tasks, with 100x times higher inference speed compared to existing pre-trained models.

bioinformatics↗

bioRxiv2023

Differentiation and migration of hematopoietic stem and progenitor cells cross multiple tissues

Hematopoiesis requires the coordinated differentiation of hematopoietic stem cells and progenitor cells (HSPCs) in multiple tissues. Although differentiation of HSPCs in bone marrow (BM) has been well-studied, our knowledge about the migration and differentiation of HSPCs cross tissues is limited. Here, we collected and integrated single-cell RNA-seq data of human CD34+ cells, which represent HSPCs, from BM, peripheral blood (PB), thymus and mobilized PB (mPB), to investigate the hematopoiesis cross tissues. We constructed a cell atlas of HSPCs cross tissues and found most HSPC subsets in BM had counterparts in PB, indicating migration of HSPCs from BM to PB has a much broad spectrum. We found B progenitors highly expressed CXCR4 for anchoring in BM, while cells with low expression of CXCR4 facilitate their migration out of BM. Among the HSPC subsets from thymus, we only found the counterparts of the earliest thymic progenitors (ETPs) in BM and PB, potentially indicating that ETPs were the subsets that migrated from BM to PB and thymus. We found interaction signaling including CD99-CD99, CXCL12-CXCR4 and CCL19-CCR7 played important roles in ETP homing to thymus. Briefly, these data provided a single unified developmental spectrum of hematopoiesis cross different tissues, connected by cell migration.

genomics↗

bioRxiv2023

Cooperative progression of colitis and leukemia modulated by clonal hematopoiesis via PTX3/IL-1β pro-inflammatory signaling

Clonal hematopoiesis (CH) is considered an important risk factor for all-cause mortality and the development of multiple chronic diseases including hematological neoplasms, cardiovascular diseases, and potentially a range of autoimmune or immune-deficiency diseases. Mutations in TET2 are one of the first identified, most important, and prevalent genetic drivers of CH. However, cooperative factors and mechanisms underlying TET2-deficiency related CH (TedCH) remain largely unknown. Recently, it has been suggested that certain diseases occurred before TedCH and promote TedCH trajectory on the contrary, indicating that diseases in non-hematopoietic organs may act as environmental non-genetic drivers of CH. To clarify the relationships between immune-dysfunctional diseases and CH, here we tested the impact of various challenges on TedCH. We found that expedited TedCH depended on establishment of an inflammatory environment. Primary or chimeric Tet2-mutant mice spontaneously developed co-symptoms reminiscent of human chronic colitis and myeloid leukemia, which was exacerbated by feeding with DSS, an experimental inducer of ulcerative colitis. Single cell RNA-seq (scRNA-seq) analysis reveals in depth the damage of colon in the Tet2-mutant mice in physiological conditions or fed with DSS, along with increase of dysbacteriosis indicated by gut microbiome analysis. Results from colon scRNA-seq from both mouse and human highlight the important roles of PTX3/IL-1{beta} pro-inflammatory signaling in promoting colitis or leukemia. Finally, TedCH trajectory and inflammation in colon and bone marrow were ameliorated by treatment of IL-1R1 inhibitor Anakinra. Our study suggests that PTX3/IL-1{beta} signaling and clonal hematopoiesis cooperate and play important roles in gut-bone marrow axis and related diseases including colitis and leukemia. HighlightsO_LICertain environmental factors, such as Dextran Sulfate Sodium (DSS), an experimental inducer of ulcerative colitis, promote TedCH C_LIO_LIColitis and leukemia are spontaneously and simultaneously developed in Tet2-defficient primary or chimeric mice, along with increased pathogenic gut microbiomes, indicating an aberrant gut-bone marrow axis in the mutant mice. C_LIO_LISingle cell RNA-seq analysis reveals enhanced PTX3, a soluble pattern recognition molecule and IL-1{beta} pro-inflammatory signaling in colitis and leukemia. C_LIO_LIThe In vivo function of the PTX3/IL-1{beta} pro-inflammatory signaling in TedCH is indicated in human colitis and validated in experimental settings. C_LI

immunology↗

bioRxiv2023

Large-scale map of RNA binding protein interactomes across the mRNA life-cycle

Messenger RNAs (mRNAs) interact with RNA-binding proteins (RBPs) in diverse ribonucleoprotein complexes (RNPs) during distinct life-cycle stages for their processing and maturation. While substantial attention has focused on understanding RNA regulation by assigning proteins, particularly RBPs, to specific RNA substrates, there has been considerably less exploration leveraging protein-protein interaction (PPI) methodologies to identify and study the role of proteins in mRNA life-cycle stages. To address this gap, we generated an RNA-aware RBP-centric PPI map across the mRNA life-cycle by immunopurification (IP-MS) of [~]100 endogenous RBPs across the life-cycle in the presence or absence of RNase, augmented by size exclusion chromatography (SEC-MS). Aside from confirming 8,700 known and discovering 20,359 novel interactions between 1125 proteins, we determined that 73% of our IP interactions are regulated by the presence of RNA. Our PPI data enables us to link proteins to life-cycle stage functions, highlighting that nearly half of the proteins participate in at least two distinct stages. We show that one of the most highly interconnected proteins, ERH, engages in multiple RNA processes, including via interactions with nuclear speckles and the mRNA export machinery. We also demonstrate that the spliceosomal protein SNRNP200 participates in distinct stress granule-associated RNPs and occupies different RNA target regions in the cytoplasm during stress. Our comprehensive RBP-focused PPI network is a novel resource for identifying multi-stage RBPs and exploring RBP complexes in RNA maturation. HIGHLIGHTSO_LIAn RBP-centric RNA-aware PPI network focuses on the mRNA life-cycle in human cells C_LIO_LIPrey-prey correlation analysis assigns prey proteins to life-cycle stages, of which 536 proteins (half of the network) interact with multiple steps C_LIO_LIERH is highly connected to multiple RNPs to affect nuclear speckle organization and mRNA export C_LIO_LISplicing factor SNRNP200 interacts with stress granule proteins and has distinct RNA occupancy in the cytoplasm C_LI

systems biology↗

bioRxiv2023

SIX4 Controls STING Expression Enhancing anti-PD-1 Efficacy

The cGAS/STING cytosolic DNA sensing pathway plays a central role in anti-tumor immunity. Expression of STING is tightly regulated and commonly reduced or defective in many types of cancer. We have identified SIX4 as a significant regulator of STING expression in colon cancer cells. We showed that knockout of SIX4 decreased STING expression at the mRNA and protein levels while ectopic expression of SIX4 increased STING expression. Depletion of SIX4 led to attenuated STING activation and downstream signaling. Re-expression of SIX4 or ectopic expression of STING in SIX4 knockout cells reversed the effect. Ectopic expression of SIX4 enhanced DMXAA and cGAMP-induced STING activation and downstream signaling. Importantly, decrease of SIX4 expression substantially decreased tumor infiltration of CD8+ T-cells and reduced the efficacy of PD-1 antibodies to diminish tumor growth in immune competent mice in vivo. Finally, analysis of TCGA colon cancer dataset indicated that tumors with high SIX4 expression were significantly enriched in the Inflammatory Response pathway. SIX4 expression also correlated with expression of multiple IFN-stimulated genes, inflammatory cytokines and CD8A. Taken together, our results implicate that SIX4 is a principal regulator of STING expression in colon cancer cells, providing an additional mechanism and genetic marker to predict effective immune checkpoint blockade therapy responses.

cancer biology↗

bioRxiv2023

Single cell analyses of cancer cells identified two regulatorily and functionally distinct categories in differentially expressed genes among tumor subclones

To explore the feature of cancer cells and tumor subclones, we analyzed 101,065 single-cell transcriptomes from 12 colorectal cancer (CRC) patients and 92 single cell genomes from one of these patients. We found cancer cells, endothelial cells and stromal cells in tumor tissue expressed much more genes and had stronger cell-cell interactions than their counterparts in normal tissue. We identified copy number variations (CNVs) in each cancer cell and found correlation between gene copy number and expression level in cancer cells at single cell resolution. Analysis of tumor subclones inferred by CNVs showed accumulation of mutations in each tumor subclone along lineage trajectories. We found differentially expressed genes (DEGs) between tumor subclones had two populations: DEGCNV and DEGreg. DEGCNV, showing high CNV-expression correlation and whose expression differences depend on the differences of CNV level, enriched in housekeeping genes and cell adhesion associated genes. DEGreg, showing low CNV-expression correlation and mainly in low CNV variation regions and regions without CNVs, enriched in cytokine signaling genes. Furthermore, cell-cell communication analyses showed that DEGCNV tends to involve in cell-cell contact while DEGreg tends to involve in secreted signaling, which further support that DEGCNV and DEGreg are two regulatorily and functionally distinct categories.

genomics↗

bioRxiv2023

SpatialCTD: a large-scale TME spatial transcriptomic dataset to evaluate cell type deconvolution for immuno-oncology

Recent technological advancements have enabled spatially resolved transcriptomic profiling but at multi-cellular resolution. The task of cell type deconvolution has been introduced to disentangle discrete cell types from such multi-cellular spots. However, existing datasets for cell type deconvolution are limited in scale, predominantly encompassing data on mice, and are not designed for human immuno-oncology. In order to overcome these limitations and promote comprehensive investigation of cell type deconvolution for human immuno-oncology, we introduce a large-scale spatial transcriptomic dataset named SO_SCPLOWPATIALC_SCPLOWCTD, encompassing 1.8 million cells from the human tumor microenvironment across the lung, kidney, and liver. Distinct from existing approaches that primarily depend on single-cell RNA sequencing data as a reference without incorporating spatial information, we introduce Graph Neural Network-based method (i.e., GNNDO_SCPLOWECONVOLVERC_SCPLOW) that effectively utilize the spatial information from reference samples, and extensive experiments show that GNNDO_SCPLOWECONVOLVERC_SCPLOW often outperforms existing state-of-the-art methods by a substantial margin, without requiring single-cell RNA-seq data. To enable comprehensive evaluations on spatial transcriptomics data from flexible protocols, we provide an online tool capable of converting spatial transcriptomic data from other platforms (e.g., 10x Visium, MERFISH and sci-Space) into pseudo spots, featuring adjustable spot size. The SO_SCPLOWPATIALC_SCPLOWCTD dataset and GNNDO_SCPLOWECONVOLVERC_SCPLOW implementation are available at https://github.com/OmicsML/SpatialCTD, and the online converter tool can be accessed at https://omicsml.github.io/SpatialCTD/.

bioinformatics↗

bioRxiv2023

Selective S1PR1 activation improves brain infarction, neurological outcome, and cerebrovascular endothelial health following experimental ischemic injury

Sphingosine-1-phosphate receptor 1 (S1PR1) is highly expressed in endothelial cells and receptor activation plays an important role in mediating endothelial function and health, thus showing promise as a pharmacologic target for acute ischemic stroke (AIS) treatment. Here, we examined the effect of a selective S1PR1 ligand, RP101075, on infarct volume and neurological outcome in adult male mice subjected to transient middle cerebral artery occlusion (tMCAO). Concomitantly, we examined S1PR1 expression profile in the ischemic mouse brain, as well as S1PR1 expression and impact of receptor activation on human brain microvascular endothelial cell (HBMEC) proliferation and survival following hypoxia plus glucose deprivation (HGD). We observed that RP101075 administration at onset of reperfusion reduced infarct volume and lessened neurological deficits in tMCAO mice and these responses were S1PR1 dependent. Additionally, we observed that tMCAO increased brain S1PR1 protein levels and flow cytometry revealed increases in S1PR1 levels are greatest in brain endothelial cells compared to other brain cell types (astrocyte, neuron, microglia). In cultured HBMECs, RP101075 increased cell proliferation and ozanimod, parent compound of RP1010175, increased live cell count during HGD; this response was S1PR1 dependent. In conclusion, S1PR1 activation improves neuroprotection/outcome post-stroke and preserves brain endothelial cell survival following ischemia-like injury.

neuroscience↗

bioRxiv2023

Microglial phagocytosis mediates long-term restructuring of spinal GABAergic circuits following early life injury

Peripheral injury during the early postnatal period alters the somatosensory system, leading to behavioural hyperalgesia upon re-injury in adulthood. Spinal microglia have been implicated as the cellular mediators of this phenomenon, but the mechanism is unclear. We hypothesised that neonatal injury (1) alters microglial phagocytosis of synapses in the dorsal horn leading to long-term structural changes in neurons, and/or (2) trains microglia, leading to a stronger microglial response after re-injury in adulthood. Using hindpaw surgical incision as a model we showed that microglial density and phagocytosis increased in the dorsal horn region innervated by the hindpaw. Dorsal horn microglia increased engulfment of synapses following injury, with a preference for those expressing the vesicular GABA transporter VGAT and primary afferent A-fibre terminals in neonates. This led to a long-term reduction of VGAT density in the dorsal horn and reduced microglial phagocytosis of VGLUT2 terminals. We also saw an increase in apoptosis following neonatal injury, which was not limited to the dorsal horn suggesting that larger circuit wide changes are happening. In adults, hindpaw incision increased microglial engulfment of predominantly VGAT synapses but did not alter the engulfment of A-fibres. This engulfment was not affected by prior neonatal injury, suggesting that microglial phagocytosis was not trained. These results highlight microglial phagocytosis in the dorsal horn as an important physiological response towards peripheral injury with potential long-term consequences and reveals differences in microglial responses between neonates and adults.

neuroscience↗

bioRxiv2022

HydRA: Deep-learning models for predicting RNA-binding capacity from protein interaction association context and protein sequence

RNA-binding proteins (RBPs) control RNA metabolism to orchestrate gene expression, and dysfunctional RBPs underlie many human diseases. Proteome-wide discovery efforts predict thousands of novel RBPs, many of which lack canonical RNA-binding domains. Here, we present a hybrid ensemble RBP classifier (HydRA) that leverages information from both intermolecular protein interactions and internal protein sequence patterns to predict RNA-binding capacity with unparalleled specificity and sensitivity using support vector machine, convolutional neural networks and transformer-based protein language models. HydRA enables Occlusion Mapping to robustly detect known RNA-binding domains and to predict hundreds of uncharacterized RNA-binding domains. Enhanced CLIP validation for a diverse collection of RBP candidates reveals genome-wide targets and confirms RNA-binding activity for HydRA-predicted domains. The HydRA computational framework accelerates construction of a comprehensive RBP catalogue and expands the set of known RNA-binding protein domains. HighlightsO_LIHydRA combines protein-protein interaction and amino acid sequence information to predict RNA binding activity for 1,487 candidate genes. C_LIO_LIHydRA predicts RNA binding with higher specificity and sensitivity than current approaches, notably for RBPs without well-defined RNA-binding domains. C_LIO_LIOcclusion Mapping with HydRA enables RNA-binding domain discovery. C_LIO_LIEnhanced CLIP confirms HydRA RBP predictions with RNA-binding domain resolution. C_LI

bioinformatics↗

bioRxiv2022

Hypothalamic supramammillary neurons that project to the medial septum control wakefulness

The hypothalamic supramammillary nucleus (SuM) plays a key role in controlling wakefulness, but the downstream target regions participating in this control process remain unknown. Here, using circuit-specific fiber photometry and single-neuron electrophysiology together with electroencephalogram, electromyogram and behavioral recordings, we find approximately half of SuM neurons that project to the medial septum (MS) are wake-active. Optogenetic stimulation of axonal terminals of SuM-MS projection induces a rapid and reliable transition to wakefulness from NREM or REM sleep, and chemogenetic activation of SuMMS projecting neurons significantly increases wakefulness time and prolongs latency to sleep. Consistently, chemogenetically inhibiting these neurons significantly reduces wakefulness time and latency to sleep. Therefore, these results identify the MS as a functional downstream target of SuM and provide evidence for a causal role for this hypothalamic-septal projection in wakefulness control.

neuroscience↗

bioRxiv2022

DANCE: A Deep Learning Library and Benchmark for Single-Cell Analysis

In the realm of single-cell analysis, computational approaches have brought an increasing number of fantastic prospects for innovation and invention. Meanwhile, it also presents enormous hurdles to reproducing the results of these models due to their diversity and complexity. In addition, the lack of gold-standard benchmark datasets, metrics, and implementations prevents systematic evaluations and fair comparisons of available methods. Thus, we introduce the DANCE platform, the first standard, generic, and extensible benchmark platform for accessing and evaluating computational methods across the spectrum of benchmark datasets for numerous single-cell analysis tasks. Currently, DANCE supports 3 modules and 8 popular tasks with 32 state-of-art methods on 21 benchmark datasets. People can easily reproduce the results of supported algorithms across major benchmark datasets via minimal efforts (e.g., only one command line). In addition, DANCE provides an ecosystem of deep learning architectures and tools for researchers to develop their own models conveniently. The goal of DANCE is to accelerate the development of deep learning models with complete validation and facilitate the overall advancement of single-cell analysis research. DANCE is an open-source python package that welcomes all kinds of contributions. All resources are integrated and available at https://omicsml.ai/.

bioinformatics↗

bioRxiv2022

Dynamics, signals and influencing factors of CD4 T cell activation revealed by single cell RNA-seq

T cell activation is a key event in adaptive immunity. However, factors affecting T cell activation have not been systematically analyzed. Here, we analyzed stimulated CD4 T cells with anti-CD3/CD28 under several conditions to explore the factors affecting T cell activation. We defined stimulated T overlapped with resting T on UMAP as inert T. Inert T expressed activated T specific genes and cytokines, indicating it is a special functional state. Stimulated T derived from peripheral CD4 T has higher fraction of effector T (TEFF) while stimulated T derived from CD4 TN has higher fraction of proliferation T and interferon highly expressed T (IFNhi T). CD4 T was more likely to differentiate into TEFF and less likely to differentiate into heat shock protein specific T (HSPhi T) and IFNhi T in the presence of CD8 T. Interestingly, CXCR4low T responded to stimulation more efficiently than CXCR4hi T. These information facilitates we design stimulation to obtain ideal activated T.

immunology↗

bioRxiv2022

Tracking single cell evolution via clock-like chromatin accessibility

Single cell chromatin accessibility sequencing (scATAC) reconstructs developmental trajectory by phenotypic similarity. However, inferring the exact developmental trajectory is challenging. Here, we show a simple, accurate and phenotypic-neutral measure of cell developmental hierarchy - the fraction of accessible clock-like loci. As cells undergo mitosis, the heterogeneity of chromatin accessibility on clock-like loci is reduced, providing a measure of mitotic age. We developed a method, EpiTrace, that counts the fraction of opened clock-like loci from scATAC data to determine cell age and perform lineage tracing. EpiTrace works in various cell lineages and animal species, shows concordance with known developmental hierarchies, correlates well with DNA methylation-based clocks, and is complementary with mutation-based lineage tracing, RNA velocity, and stemness predictions. Applying EpiTrace to scATAC data revealed a multitude of novel biological insights with clinically relevant implications, ranging from hematopoiesis, organ development, tumor biology and immunity to cortical gyrification. Our work discovered a universal epigenomic hallmark during cellular development, which facilitates the study of cellular hierarchies and organismal aging.

bioinformatics↗

bioRxiv2022

Single-cell RNA Sequencing of Pediatric Ependymoma Unravels Subclonal Heterogeneity Associated with Patient Survival

Ependymoma (EPN) is a malignant glial tumor occurring throughout central nervous system which commonly presents in children. Although recent studies have characterized EPN samples at both the bulk and single-cell level, intra-tumoral heterogeneity across subclones remains a confounding factor which impedes understanding of EPN biology. In this study, we generated a high-resolution single-cell dataset of pediatric ependymoma with a particular focus on the comparison of subclone differences within tumors, and show upregulation of cilium-associated genes in more highly differentiated subclone populations. As a proxy to traditional pseudotime analysis, we applied a novel trajectory scoring method to reveal cellular compositions associated with poor survival outcomes across primary and relapsed patients. Furthermore, we identified putative cell-cell communication features between relapsed and primary samples and show upregulation of pathways associated with immune cell crosstalk. Our results reveal both inter- and intratumoral gene expression profiles and tumor differentiation and provide a framework for studying transcriptomic signatures of individual subclones in ependymoma at single-cell resolution.

bioinformatics↗