Biology subjects

Chen, K.

Publications and source records attributed to Chen, K..

At least 235 records · Page 13Linked to original sources

bioRxiv2023

Pathway Centric Analysis for single-cell RNA-seq and Spatial Transcriptomics Data with GSDensity

Advances in single-cell technology have enabled molecular cellular dissection of heterogeneous biospecimens at unprecedented scales and resolutions. Although cluster-centric approaches followed by gene-set analysis can reveal distinct cell types and states, they have limited power in dissecting and interpretating highly heterogenous, dynamically evolving data. Here, we present GSDensity, a graph-modeling approach that allows users to obtain pathway-centric interpretation and dissection of single-cell and spatial transcriptomics (ST) data without performing clustering. We show that GSDensity can not only accurately detect biologically distinct gene sets but also reveal novel cell-pathway associations that are ignored by existing methods. This is particularly evident in characterizing cancer cell states that are transcriptomically distinct but are driven by shared tumor-immune interaction mechanisms. Moreover, we show that GSDensity, combined with trajectory analysis can identify pathways that are active at various stages of mouse brain development. Finally, we show that GSDensity can identify spatially relevant pathways in mouse brains including those following a high-order organizational patterns in the ST data. We also created a pan-cancer pathway activity ST map, which revealed pathways spatially relevant and recurrently active across six different tumor types. GSDensity is available as an open-source R package and can be widely applied to single-cell and ST data generated by various technologies.

bioinformatics↗

bioRxiv2023

cProSite: A web based interactive platform for online proteomics, phosphoproteomics, and genomics data analysis

We developed cProSite, a website that provides online genomics, proteomics, and phosphoproteomics analysis for the data of The National Cancer Institutes Clinical Proteomic Tumor Analysis Consortium (CPTAC). This tool focuses on comparisons and correlations between different proteins and mRNAs of tumors and normal tissues. Our website is designed with biologists and clinicians in mind, with a user-friendly environment and fast search engine. The search results of cProSite can be used for clinical data validation and provide useful strategic information to identify drug targets at proteomic, phosphoproteomic, or genomic levels. The site is available at http://cprosite.ccr.cancer.gov. SignificanceAn interactive database for the expression and correlation for proteins, proteomic phosphorylations, and mRNA levels has been developed for analyzing the molecular alterations between tumors and normal tissues of various tumor types.

bioinformatics↗

bioRxiv2023

Transfer Learning Enhanced Graph Neural Network for Aldehyde Oxidase Metabolism Prediction and Its Experimental Application

Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.

bioinformatics↗

bioRxiv2023

Monocyte production of C1q potentiates CD8+ T cell effector function following respiratory viral infection

Respiratory viral infections remain a leading cause of morbidity and mortality. Using a murine model of human metapneumovirus (HMPV), we identified recruitment of a C1q-producing inflammatory monocyte population concomitant with viral clearance by adaptive immune cells. Genetic ablation of C1q led to reduced CD8+ T cell function. Production of C1q by a myeloid lineage was sufficient to enhance CD8+ T cell function. Activated and dividing CD8+ T cells expressed a putative C1q receptor, gC1qR. Perturbation of gC1qR signaling led to altered CD8+ T cell IFN-{gamma} production and metabolic capacity. Autopsy specimens from fatal respiratory viral infections in children demonstrated diffuse production of C1q by an interstitial population. Humans with severe COVID-19 infection also demonstrated upregulation of gC1qR on activated and rapidly dividing CD8+ T cells. Collectively, these studies implicate C1q production from monocytes as a critical regulator of CD8+ T cell function following respiratory viral infection.

immunology↗

bioRxiv2023

Impairment of autophagy-lysosomal activity near the chronically implanted microelectrodes

Intracortical microelectrodes that can record and stimulate brain activity have become a valuable technique for basic science research and clinical applications. However, long-term implantation of these microelectrodes can lead to progressive neurodegeneration in the surrounding microenvironment, characterized by elevation in disease-associated markers. Dysregulation of autophagy-lysosomal degradation, a major intracellular waste removal process, is considered a key factor in the onset and progression of neurodegenerative diseases. It is plausible that similar dysfunctions in autophagy-lysosomal degradation contribute to tissue degeneration following implantation-induced focal brain injury, ultimately impacting recording performance. To understand how the focal, persistent brain injury caused by long-term microelectrode implantation impairs the autophagy-lysosomal pathway, we employed two-photon microscopy and immunohistology. This investigation focused on the spatiotemporal characterization of autophagy-lysosomal activity near the chronically implanted microelectrode. We observed an aberrant accumulation of immature autophagy vesicles near the microelectrode over the chronic implantation period. Additionally, we found deficits in autophagy-lysosomal clearance proximal to the chronic implant, which was associated with an accumulation of autophagy cargo and a reduction in lysosomal protease level during the chronic period. Furthermore, our evidence suggests astrocytes contribute to the clearance of myelin debris via autophagy-lysosomal degradation near the implanted microelectrode. Together, this study sheds light on the process of brain tissue degeneration caused by long-term microelectrode implantation, with a specific focus on impaired intracellular waste degradation.

bioengineering↗

bioRxiv2023

Deciphering deep-sea chemosynthetic symbiosis by single-nucleus RNA-sequencing

Bathymodioline mussels dominate deep-sea methane seep and hydrothermal vent habitats and obtain nutrients and energy primarily through chemosynthetic endosymbiotic bacteria in the bacteriocytes of their gill. However, the molecular mechanisms that orchestrate mussel host-symbiont interactions remain unclear. Here, we constructed a comprehensive cell atlas of the gill in the mussel Gigantidas platifrons from the South China Sea methane seeps (1100m depth) using single-nucleus RNA sequencing (snRNA-seq) and whole-mount in situ hybridisation. We identified 13 types of cells, including three previously unknown ones, and uncovered unknown tissue heterogeneity. Every cell type has a designated function in supporting the gills structure and function, creating an optimal environment for chemosynthesis, and effectively acquiring nutrients from the endosymbiotic bacteria. Analysis of snRNA-seq of in situ transplanted mussels clearly showed the shifts in cell state in response to environmental oscillations. Our findings provide insight into principles of host-symbiont interaction and the bivalves environmental adaption mechanisms.

ecology↗

bioRxiv2023

RNA tertiary structure modeling with BRiQ potential in CASP15

We describe the modeling method for RNA tertiary structures employed by team AIchemy_RNA2 in the 15th Critical Assessment of Protein Structure Prediction (CASP15). The method consists of the following steps. Firstly, secondary structure information was derived from various manually-verified sources. With this information, the full length RNA was fragmented into structural motifs. The structures of each motif were predicted and then assembled into the full structure. To reduce the searching conformational space, a RNA structure was organized into an optimal base folding tree. And to further improve the sampling efficiency, the energy surface was smoothed at high temperatures during the Monte Carlo sampling to make it easier to move across the energy barrier. The statistical potential energy function BRiQ was employed during Monte Carlo energy optimization.

bioinformatics↗

bioRxiv2023

StressME: unified computing framework of Escherichia coli metabolism, gene expression, and stress responses

Generalist microbes have adapted to a multitude of environmental stresses through their integrated stress response system. Individual stress responses have been quantified by E. coli metabolism and expression (ME) models under thermal, oxidative and acid stress, respectively. However, the systematic quantification of crosstalk among these stress responses remains lacking. Here, we present StressME: the unified stress response model of E. coli combining thermal (FoldME), oxidative (OxidizeME) and acid (AcidifyME) stress responses. StressME is the most up to date ME model for E. coli and it reproduces all published single-stress ME models. Additionally, it includes refined rate constants to improve prediction accuracy for wild-type and stress-evolved strains. StressME revealed certain optimal proteome allocation strategies associated with cross-stress responses. These stress-optimal proteomes were shaped by trade-offs between protective vs. metabolic enzymes; cytoplasmic vs. periplasmic chaperones; and expression of stress-specific proteins. As StressME is tuned to compute metabolic and gene expression responses under mild acid, oxidative, and thermal stresses, it is useful for engineering and health applications. The modular design of our open-source package also facilitates model expansion (e.g., to new stress mechanisms) by the computational biology community. Author summaryA fundamental understanding of multi-stress adaptation in E.coli has potential industrial relevance. While individual stress responses have been quantified through the protein regulatory network in E.coli, the systematic quantification of the crosstalk among stress responses remains lacking. Here, we develop a new modeling pipeline by which thermal, oxidative and acid stress response can be coupled to each other, and the metabolic activities, protein and metabolic flux redistribution due to cross stress can be quantified. We optimize the effective rate constants in the integrated model. We then confirm the model robustness by validating against the published data under single stress. Finally, we use the model to characterize the cross-adaptation between protective and catalytic proteins as well as between chaperones present in different cellular compartments. We find effective cross-protection against cross stress by adapting the E.coli cells to the thermal stress first. We also indicate the presence of trade-offs by which the cell may refuse to give up more protein allocation away from one stress response to the other, because doing so would decrease stress tolerance further. The single stress plug-in design makes the model build-up pipeline flexible and expandable, allowing incorporation of more stressors into the model architecture for industrial applications.

systems biology↗

bioRxiv2023

Endogenous fine-mapping of functional regulatory elements in complex genetic loci

The vast majority of genetic loci associated with polygenic complex traits are located in non-coding regions of the human genome. However, many of these regions exhibit high- order gene regulatory relationships and complicated linkage disequilibrium (LD) configurations, which bring challenges to accurately identify causal variants and their target genes controlling specific molecular processes or traits. We employed multiplexed single-cell CRISPR interference and activation perturbations to explore the links between cis-regulatory element (CRE) and target gene expression within tight LD in the endogenous chromatin context. We validated the prevalence of multiple causality in perfect LD (pLD) for independent expression quantitative trait locus (eQTL), and revealed fine-grained genetic effects on gene expression within pLD. These effects are difficult to decipher using conventional eQTL fine-mapping or to predict via existing computational methods. We found that nearly half of the casual CREs lack classical epigenetic markers, potentially affecting gene expression through hidden regulatory mechanisms. Integrative analysis on different types of perturbation effects suggested a high regulatory plasticity of the human genome. These findings will propel further in-depth exploration of functional genomic elements, facilitating a more comprehensive understanding of gene expression regulatory patterns and the development of complex traits.

genomics↗

bioRxiv2023

Downregulation of the silent potassium channel Kv8.1 increases ALS motor neuron vulnerability

The Kv8.1 potassium ion channel encoded by the KCNV1 gene is a "silent" subunit whose biological function is unknown. In ALS patient-derived motor neurons carrying SOD1(A4V) and C9orf72 mutations, its expression is highly reduced, yielding increased vulnerability to cell death without a change in motor neuronal firing. Our data suggests that Kv8.1 modulates Kv2 channel function to impact neuronal metabolism and lipid/protein transport pathways, but not excitability.

neuroscience↗

bioRxiv2023

Spatially-resolved single-cell atlas of ascidian endostyle provides insights into the origin of vertebrate pharyngeal organs

The pharynx is an endoderm innovation in deuterostome ancestors, the vertebrate descendent structure of which is a pharyngeal developmental organizer involving multi-germ layer and organ derivatives. However, the evolutionary origination of complicated pharynx organs in vertebrates is still largely unknown. Endostyle, a transitional pharyngeal organ exclusively in basal chordates provides an opportunity to reveal the origin of pharyngeal organs. Here, utilizing cutting-edged Stereo-seq and single-cell RNA-seq, we constructed the first spatially-resolved single-cell atlas in the endostyle of urochordate ascidian Styela clava, where the spatial location of Stereo-seq and high capture efficiency of single-cell RNA-seq complement each other and identified 23 highly differentiated cell types. We identified a previously overlooked hemolymphoid region (HLR), which harbors immune and blood cell clusters with enriched stemness capacities, illuminating a mixed rudiment and stem-cell niches for the blood and lymphoid system. More excitingly, we discovered a mechanical-sensitive hair cell candidate in zone 3 homologous to vertebrate acoustico-lateralis system, which was supported by the expression of in situ hybridization-verified inner ear-specific markers, including PTPRQ, USH2A, WHRN, and ADGRV1, ultracellular structure evidence and cross-species comparison. These results thoroughly renewed the comprehension of the basal-chordate pharynx and provides expressional evidence for multiplexed pharyngeal organ evolution.

evolutionary biology↗

bioRxiv2023

A spatially resolved single cell genomic atlas of the adult human breast

The adult human breast comprises an intricate network of epithelial ducts and lobules that are embedded in connective and adipose tissue. While previous studies have mainly focused on the breast epithelial system, many of the non-epithelial cell types remain understudied. Here, we constructed a comprehensive Human Breast Cell Atlas (HBCA) at single-cell and spatial resolution. Our single-cell transcriptomics data profiled 535,941 cells from 62 women, and 120,024 nuclei from 20 women, identifying 11 major cell types and 53 cell states. These data revealed abundant pericyte, endothelial and immune cell populations, and highly diverse luminal epithelial cell states. Our spatial mapping using three technologies revealed an unexpectedly rich ecosystem of tissue-resident immune cells in the ducts and lobules, as well as distinct molecular differences between ductal and lobular regions. Collectively, these data provide an unprecedented reference of adult normal breast tissue for studying mammary biology and disease states such as breast cancer.

genomics↗

bioRxiv2023

Learning from the expert: studying Salicornia to understand salinity tolerance

Salinity remains a major inhibitor of crop production in irrigated and marginal lands. The identification of genes involved in salinity tolerance has been predominantly limited to model plants and crop species. However, plants naturally adapted to highly saline environments can provide key insights into mechanisms of salinity tolerance. Plants of the genus Salicornia grow in coastal salt marshes, and their growth is even stimulated by NaCl - much can be learnt from them. We generated genome sequences of two Salicornia species and studied the transcriptomic and proteomic responses of Salicornia bigelovii to NaCl. Through the generation of subcellular membrane proteomes, we found that SbiSOS1, a homolog of the well-known SALT-OVERLY-SENSITIVE 1 (SOS1) protein, appears to localize to the tonoplast, where it could be involved in mediating Na+ translocation into the vacuole to prevent toxicity in the cytosol. We identified 11 proteins of interest which, when expressed in yeast, altered salinity tolerance. One of these proteins, SbiSALTY, substantially improves yeast growth on saline media. Structural characterization using NMR showed it to be an intrinsically disordered protein and to localize to the endoplasmic reticulum in planta, where it could interact with ribosomes and RNA, potentially stabilizing or protecting them during salt stress. The study and understanding of the molecular mechanisms providing high salinity tolerance in S. bigelovii is likely to provide significant insights for improving salinity tolerance of crop plants.

plant biology↗

bioRxiv2023

MmcA is an electron conduit that facilitates both intracellular and extracellular electron transport in Methanosarcina acetivorans

Methanogens are a diverse group of Archaea that couple energy conservation to the production of methane gas. While most methanogens have no alternate mode of energy conservation, strains like Methanosarcina acetivorans are known to also conserve energy by dissimilatory metal reduction (DSMR) in the presence of soluble ferric iron or iron-containing minerals. The ecological ramifications of energy conservation decoupled from methane production in methanogens are substantial, yet the molecular details are poorly understood. In this work, we conducted in vitro and in vivo studies with a multiheme c-type cytochrome (MHC), called MmcA, to establish its role during methanogenesis and DSMR in M. acetivorans. MmcA purified from M. acetivorans can donate electrons to methanophenazine, a membrane-bound electron carrier, to facilitate methanogenesis. In addition, MmcA can also reduce Fe(III) and the humic acid analog anthraquinone-2,6-disulfonate (AQDS) during DSMR. Furthermore, mutants lacking mmcA have slower Fe(III) reduction rates. The redox reactivities of MmcA are consistent with the electrochemical data where MmcA displays reversible redox features ranging from -100 to -450 mV versus SHE. MmcA is prevalent in members of the Order Methanosarcinales but does not belong to a known family of MHCs linked to extracellular electron transfer, bioinformatically, and instead forms a distinct clade that is closely related to octaheme tetrathionate reductases. Taken together, this study shows that MmcA is widespread in methanogens with cytochromes where it acts as an electron conduit to support a variety of energy conservation strategies that extend beyond methanogenesis.

microbiology↗

bioRxiv2023

Lead (Pb) Inhibits-PMA Induced Microglia Multinucleation

Multinucleated Microglia are formed in response to aging, inflammation, the presence of some pathogens, and are a histological feature of several CNS pathologies. Multinucleated microglia may be involved with increased clearance of CNS debris and whole cells. The present study has sought to determine the best model by which to study multinucleation in microglia in vitro, in order to investigate whether the known neurotoxicant metal lead (Pb) impacts the formation of multinucleated microglia. It was determined that isolated rat microglia (Sprague-Dawley), compared to murine (BV2) and human (HMC3) microglia cell-lines, when induced by Phorbol-myristate-acetate (PMA) results in the greatest amount of cell multinucleation and multinuclearity. In this model, it was shown that long-term exposure to Pb inhibited microglia cell proliferation, multinucleation, and multinuclearity in a dose-dependent manner. Pb appears to inhibit multinucleation in microglia by induction of multinuclear regression (karyolysis, pyknosis, or karyorrhexis) resulting in large mononuclear cells. The mechanism by which PMA induces multinucleation may involve p38/MAPK activity and Pb interferes with this activation.

pharmacology and toxicology↗

bioRxiv2023

Piezo inhibition prevents and rescues scarring by targeting the adipocyte to fibroblast transition

While past studies have suggested that plasticity exists between dermal fibroblasts and adipocytes, it remains unknown whether fat actively contributes to fibrosis in scarring. We show that adipocytes convert to scar-forming fibroblasts in response to Piezo-mediated mechanosensing to drive wound fibrosis. We establish that mechanics alone are sufficient to drive adipocyte-to- fibroblast conversion. By leveraging clonal-lineage-tracing in combination with scRNA-seq, Visium, and CODEX, we define a "mechanically naive" fibroblast-subpopulation that represents a transcriptionally intermediate state between adipocytes and scar-fibroblasts. Finally, we show that Piezo1 or Piezo2-inhibition yields regenerative healing by preventing adipocytes activation to fibroblasts, in both mouse-wounds and a novel human-xenograft-wound model. Importantly, Piezo1-inhibition induced wound regeneration even in pre-existing established scars, a finding that suggests a role for adipocyte-to-fibroblast transition in wound remodeling, the least-understood phase of wound healing. Adipocyte-to-fibroblast transition may thus represent a therapeutic target for minimizing fibrosis via Piezo-inhibition in organs where fat contributes to fibrosis.

cell biology↗

bioRxiv2023

Quantitative relations among causality measures with applications to pulse-output nonlinear network reconstruction

The causal connectivity of a network is often inferred to understand the network function. It is arguably acknowledged that the inferred causal connectivity relies on the causality measure one applies, and it may differ from the networks underlying structural connectivity. However, the interpretation of causal connectivity remains to be fully clarified, in particular, how causal connectivity depends on causality measures and how causal connectivity relates to structural connectivity. Here, we focus on nonlinear networks with pulse signals as measured output, e.g., neural networks with spike output, and address the above issues based on four intensively utilized causality measures, i.e., time-delayed correlation coefficient, time-delayed mutual information, Granger causality, and transfer entropy. We theoretically show how these causality measures are related to one another when applied to pulse signals. Taking the simulated Hodgkin-Huxley neural network and the real mouse brain network as two illustrative examples, we further verify the quantitative relations among the four causality measures and demonstrate that the causal connectivity inferred by any of the four well coincides with the underlying network structural connectivity, therefore establishing a direct link between the causal and structural connectivity. We stress that the structural connectivity of networks can be reconstructed pairwise without conditioning on the global information of all other nodes in a network, thus circumventing the curse of dimensionality. Our framework provides a practical and effective approach for pulse-output network reconstruction. Significance StatementInferring network connectivity is a key challenge in many diverse scientific fields. We investigate networks with pulse signal as measured output and solve the above reverse-engineering issue by establishing a direct link between the networks causal connectivity and structural connectivity. Here, the causal connectivity can be inferred by any one of the four causality measures, i.e., time-delayed correlation coefficient, time-delayed mutual information, Granger causality, and transfer entropy. We analytically reveal the relationship among these four measures and show that they are equally effective to fully reconstruct the network connectivity pairwise. Our work provides a practical framework to reconstruct the structural connectivity in general pulse-output nonlinear networks or subnetworks.

neuroscience↗

bioRxiv2023

Elevated ENO2 Disrupts VSMCs Homeostasis Facilitating the Development of Aortic Dissection

OBJECTIVEAortic dissection (AD) is a dangerous cardiovascular disease. However, its regulatory mechanism remains poorly understood. Autophagy is an important pathway for maintaining cellular homeostasis. Recent studies have shown that glycolysis and autophagy are essential for the development of AD. Elevated glycolysis can promote cells autophagy, but the relationship between the two is unclear. Enolase 2 (ENO2) is a glycolytic enzyme. Here, we investigated whether ENO2 can regulate autophagy in vascular smooth muscle cells (VSMCs) involved in the progression of AD. APPROACH AND RESULTSThe levels of ENO2 and autophagy-related proteins in aortic tissues from AD patients were identified by qRT-PCR, Western blot and IHC. We found that autophagosome clearance was impaired in aortic tissues and positively correlated with elevated ENO2 expression. Furthermore, aortic application of smooth muscle-specific adeno-associated virus (AAV) inhibiting ENO2 expression attenuated the development of AD in mice. in vitro experiments, downregulation of ENO2 partially restored PDGF-BB-induced impairment of autophagic flux, as evidenced by reduced expression of Beclin-1, SQSTM1, LC3BII/I and increased levels of LAMP2 in human aortic vascular smooth muscle cells (HAVSMCs). Similarly, increased levels of ENO2 exacerbated the autophagic dysfunction in HAVSMCs. Mechanistically, ENO2 may block autophagic flux through the ENO2-GAP43-ATF4 pathway and disrupt cellular homeostasis. CONCLUSIONSOur data reveal a perturbing role of ENO2 in the homeostasis of VSMCs, suggesting ENO2 as a potential target for intervention in AD.

molecular biology↗