Biology subjects

Chen, K.

Publications and source records attributed to Chen, K..

At least 397 records · Page 22Linked to original sources

bioRxiv2020

Cell-free DNA Tissues-of-Origin Profiling to Predict Graft versus Host Disease and Detect Infection after Hematopoietic Cell Transplantation

Allogeneic hematopoietic cell transplantation (HCT) provides effective treatment for hematologic malignancies and immune disorders. Monitoring of post-transplant complications is critical, yet current diagnostic options are limited. Here, we show that cell-free DNA (cfDNA) in blood is a highly versatile analyte for monitoring of the most important complications that occur after HCT: graft-versus-host disease (GVHD), a frequent immune complication of HCT; infection; relapse of underlying disease; and graft failure. We demonstrate that these different therapeutic complications can be informed from a single assay, low-coverage bisulfite sequencing of cfDNA, followed by disease-specific bioinformatic analyses. To inform GVHD, we profile cfDNA methylation marks to trace the cfDNA tissues-of-origin and to quantify tissue-specific injury. To inform on infections, we implement metagenomic cfDNA profiling. To inform cancer relapse, we implement analyses of tumor-specific genomic aberrations. Finally, to detect graft failure we quantify the proportion of donor and recipient specific cfDNA. We applied this assay to 170 plasma samples collected from 27 HCT recipients at predetermined time points before and after allogeneic HCT. We found that the abundance of solid-organ derived cfDNA in the blood at one-month after HCT is an early predictor of acute graft-versus-host disease (area under the curve, 0.88). Metagenomic profiling of cfDNA revealed the frequent occurrence of viral reactivation in this patient population. The fraction of donor specific cfDNA was indicative of cell chimerism, relapse and remission, and the fraction of tumor specific cfDNA was informative of cancer relapse. This proof-of-principle study shows that cfDNA has the potential to improve the care of allogeneic HCT recipients by enabling earlier detection and better prediction of the complex array of complications that occur after HCT.

genomics↗

bioRxiv2020

Genomic Architecture of Cells in Tissues (GeACT): Study of Human Mid-gestation Fetus

By circumventing cellular heterogeneity, single cell omics have now been widely utilized for cell typing in human tissues, culminating with the undertaking of human cell atlas aimed at characterizing all human cell types. However, more important are the probing of gene regulatory networks, underlying chromatin architecture and critical transcription factors for each cell type. Here we report the Genomic Architecture of Cells in Tissues (GeACT), a comprehensive genomic data base that collectively address the above needs with the goal of understanding the functional genome in action. GeACT was made possible by our novel single-cell RNA-seq (MALBAC-DT) and ATAC-seq (METATAC) methods of high detectability and precision. We exemplified GeACT by first studying representative organs in human mid-gestation fetus. In particular, correlated gene modules (CGMs) are observed and found to be cell-type-dependent. We linked gene expression profiles to the underlying chromatin states, and found the key transcription factors for representative CGMs. HighlightsO_LIGenomic Architecture of Cells in Tissues (GeACT) data for human mid-gestation fetus C_LIO_LIDetermining correlated gene modules (CGMs) in different cell types by MALBAC-DT C_LIO_LIMeasuring chromatin open regions in single cells with high detectability by METATAC C_LIO_LIIntegrating transcriptomics and chromatin accessibility to reveal key TFs for a CGM C_LI

genomics↗

bioRxiv2020

Single-cell copy number lineage tracing enabling gene discovery

Aneuploidy plays critical roles in genome evolution. Alleles, whose dosages affect the fitness of an ancestor, will have altered frequencies in the descendant populations upon perturbation. Single-cell sequencing enables comprehensive genome-wide copy number profiling of thousands of cells at various evolutionary stage and lineage. That makes it possible to discover dosage effects invisible at tissue level, provided that the cell lineages can be accurately reconstructed. Here, we present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles. We also present a statistical routine named lineage speciation analysis (LSA), which facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. We assessed our approaches using a variety of single-cell datasets. Overall, MEDALT appeared more accurate than phylogenetics approaches in reconstructing copy number lineage. From the single-cell DNA-sequencing data of 20 triple-negative breast cancer patients, our approaches effectively prioritized genes that are essential for breast cancer cell fitness and are predictive of patient survival, including those implicating convergent evolution. Similar benefits were observed when applying our approaches on single-cell RNA sequencing data obtained from cancer patients. The source code of our study is available at https://github.com/KChen-lab/MEDALT.

bioinformatics↗

bioRxiv2020

Relative Abundance of SARS-CoV-2 Entry Genes in the Enterocytes of the Lower Gastrointestinal Tract

COVID-19, the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly spread throughout the world and was declared a pandemic by the World Health Organization, thus leading to a rapid surge in the efforts to understand the mechanisms of transmission, methods of prevention, and potential therapies. While COVID-19 frequently manifests as a respiratory infection,1 there is evidence for infection of the gastrointestinal (GI) tract1-4 with documented viral RNA shedding in the stool of infected patients.2,4 In this study, we aimed to investigate the expression of ACE2 and TMPRSS2, which are required for SARS-CoV-2 entry into mammalian cells,5 from single-cell RNA sequencing (scRNA-seq) datasets of five different parts of the GI tract: esophagus, stomach, pancreas, small intestine, and colon/rectum.

bioinformatics↗

bioRxiv2020

Computational target fishing by mining transcriptional data using a novel Siamese spectral-based graph convolutional network

Computational target fishing aims to investigate the mechanism of action or the side effects of bioactive small molecules. Unfortunately, conventional ligand-based computational methods only explore a confined chemical space, and structure-based methods are limited by the availability of crystal structures. Moreover, these methods cannot describe cellular context-dependent effects and are thus not useful for exploring the targets of drugs in specific cells. To address these challenges, we propose a novel Siamese spectral-based graph convolutional network (SSGCN) model for inferring the protein targets of chemical compounds from gene transcriptional profiles. Although the gene signature of a compound perturbation only provides indirect clues of the interacting targets, the SSGCN model was successfully trained to learn from known compound-target pairs by uncovering the hidden correlations between compound perturbation profiles and gene knockdown profiles. Using a benchmark set, the model achieved impressive target inference results compared with previous methods such as Connectivity Map and ProTINA. More importantly, the powerful generalization ability of the model observed with the external LINCS phase II dataset suggests that the model is an efficient target fishing or repositioning tool for bioactive compounds.

bioinformatics↗

bioRxiv2020

Paxillin Promotes ATP-induced Activation of P2X7 Receptor and NLRP3 Inflammasome

The stimulation of P2X7 receptor by extracellular ATP leads to activation of NLRP3 inflammasome and release of pro-inflammatory cytokines. Here, we reveal a distinct mechanism by which Paxillin promotes ATP-induced activation of P2X7 receptor and NLRP3 inflammasome. Extracellular ATP induces Paxillin phosphorylation and facilitates Paxillin-NLRP3 interaction. Interestingly, Paxillin enhances NLRP3 deubiquitination and activates NLRP3 inflammasome upon ATP treatment and K+ efflux. Moreover, we reveal that UPS13 is a key enzyme for Paxillin-mediated NLRP3 deubiquitination upon ATP treatment. Notably, extracellular ATP promotes Paxillin and NLRP3 migration from cytosol to plasma membrane and facilitates P2X7-Paxillin interaction and Paxillin-NLRP3 association, resulting in the formation of P2X7-Paxillin-NLRP3 complex. Functionally, Paxillin is essential for ATP-induced NLRP3 inflammasome activation in mouse BMDMs and BMDCs as we as in human PBMCs and THP-1-differentiated macrophages. Thus, Paxillin plays key roles in ATP-induced activation of P2X7 receptor and NLRP3 inflammasome by facilitating the formation of the P2X7-Paxillin-NLRP3 complex.

immunology↗

bioRxiv2020

Inhibition of the av integrin-TGF-b axis improves natural killer cell function against glioblastoma stem cells

Glioblastoma, the most aggressive brain cancer, often recurs because glioblastoma stem cells (GSCs) are resistant to all standard therapies. Here, we show that patient-derived GSCs, but not normal astrocytes, are highly sensitive to lysis by healthy allogeneic natural killer (NK) cells in vitro. In contrast, single cell analysis of autologous, tissue infiltrating NK cells isolated from surgical samples of high-grade glioblastoma patient tumors using mass cytometry and single cell RNA sequencing revealed an abnormal phenotype associated with impaired lytic function compared with peripheral blood NK cells from GBM patients or healthy donors. This immunosuppression was attributed to an integrin-TGF-{beta} mechanism, activated by direct cell-cell contact between GSCs and NK cells. Treatment of GSC-engrafted mice with allogeneic NK cells in combination with inhibitors of integrin or TGF-{beta} signaling, or with TGF-{beta} receptor 2 gene-edited NK cells prevented GSC-induced NK cell dysfunction and tumor growth. Collectively, our findings reveal a novel mechanism of NK cell immune evasion by GSCs and implicate the integrin-TGF-{beta} axis as a useful therapeutic target to eliminate GSCs in this devastating tumor.

immunology↗

bioRxiv2020

CIS checkpoint deletion enhances the fitness of cord blood derived natural killer cells transduced with a chimeric antigen receptor

Immune checkpoint therapy has produced remarkable improvements in the outcome for certain cancers. To broaden the clinical impact of checkpoint targeting, we devised a strategy that couples targeting of the cytokine-inducible SH2-containing (CIS) protein, a key negative regulator of interleukin (IL)-15 signaling, with chimeric antigen receptor (CAR) engineering of natural killer (NK) cells. This combined strategy boosted NK cell effector function through enhancing the Akt/mTORC1 axis and c-MYC signaling, resulting in increased aerobic glycolysis. When tested in a lymphoma mouse model, this combined approach improved NK cell anti-tumor activity more than either alteration alone, eradicating lymphoma xenografts without signs of any measurable toxicity. We conclude that combining CIS checkpoint deletion with CAR engineering promotes the metabolic fitness of NK cells in an otherwise suppressive tumor microenvironment. This approach, together with the prolonged survival afforded by CAR modification, represents a promising milestone in the development of the next generation of NK cells for cancer immunotherapy.

immunology↗

bioRxiv2020

A role for KIF9 in male fertility

A mouse was generated containing a floxed exon 3 of the gene for the kinesin family member KIF9. By in situ hybridization, expression of KIF9 mRNA was highest in the testis and was also strong in epithelia containing multi-ciliated cells such as the ependyma, bronchioles and oviduct. Deletion of the exon led to loss of KIF9 expression at the mRNA and protein level with no effect on viability. However, homozygous KIF9 knockout males were sterile. Although KIF9 knockout sperm were motile, they were unable to fertilize oocytes in an in vitro fertilization assay. Closer examination of sperm motility indicated a subtle difference in waveform. Our results suggest that KIF9 plays a role male fertility, possibly through regulation of flagellar waveforms in ciliated cells.

developmental biology↗

bioRxiv2020

Facing small and biased data dilemma in drug discovery with federated learning

Artificial intelligence (AI) models usually require large amounts of high-quality training data, which is in striking contrast to the situation of small and biased data faced by current drug discovery pipelines. The concept of federated learning has been proposed to utilize distributed data from different sources without leaking sensitive information of these data. This emerging decentralized machine learning paradigm is expected to dramatically improve the success of AI-powered drug discovery. We here simulate the federated learning process with 7 aqueous solubility datasets from different sources, among which there are overlapping molecules with high or low biases in the recorded values. Beyond the benefit of gaining more data, we also demonstrate federated training has a regularization effect making it superior than centralized training on the pooled datasets with high biases. Further, two more cases are studied to test the usability of federated learning in drug discovery. Our work demonstrates the application of federated learning in predicting drug related properties, but also highlights its promising role in addressing the small data and biased data dilemma in drug discovery.

pharmacology and toxicology↗

bioRxiv2020

Structural basis underlying strong interactions between ankyrins and spectrins

Ankyrins (encoded by ANK1/2/3 corresponding to Ankyrin-R/B/G or AnkR/B/G), via binding to spectrins, connect plasma membranes with actin cytoskeleton to maintain mechanical strengths and to modulate excitabilities of diverse cells such as neurons, muscle cells, and erythrocytes. Cellular and genetic evidences suggest that each isoform of ankyrins pairs with a specific {beta}-spectrin in discrete subcellular membrane microdomains for distinct functions, though the molecular mechanisms underlying such ankyrin/{beta}-spectrin pairings are unknown. In this study, we discover that a conserved and short extension N-terminal to the ZU5N-ZU5C-UPA tandem (exZZU) is critical for each ankyrin to bind to {beta}-spectrins with high affinities. Structures of AnkB/G exZZU in complex with spectrin repeats13-15 of {beta}2/{beta}4-spectrins solved here reveal that the extension sequence of exZZU forms an additional {beta}-strand contributing to the structural stability and enhanced affinity of each ZU5N/spectrin repeat interaction. The junction site between the extension and ZU5N is exactly the position of a splicing-mediated miniexon insertion site of AnkB/G. The complex structures further reveal that the UPA domain of exZZU directly participates in spectrin binding. Formation of the exZZU supramodule juxtaposes the ZU5N and UPA domains for simultaneous interacting with spectrin repeats 14 and 15. However, our biochemical and structural investigations indicate that the direct and strong interactions between ankyrins and {beta}-spectrins do not appear to determine their pairing specificities. Therefore, there likely exists additional mechanism(s) for modulating functional pairings between ankyrins and {beta}-spectrins in cells.

biochemistry↗

bioRxiv2020

A global barley panel revealing genomic signatures of breeding in modern cultivars

The future of plant cultivar improvement lies in the evaluation of genetic resources from currently available germplasm. Recent efforts in plant breeding have been aimed at developing new and improved varieties from poorly adapted crops to suit local environments. However, the impact of these breeding efforts is poorly understood. Here, we assess the contributions of both historical and recent breeding efforts to local adaptation and crop improvement in a global barley panel by analysing the distribution of genetic variants with respect to geographic region or historical breeding category. By tracing the impact breeding had on the genetic diversity of barley released in Australia, where the history of barley production is relatively young, we identify 69 candidate regions within 922 genes that were under selection pressure. We also show that modern Australian barley varieties exhibit 12% higher genetic diversity than historical cultivars. Finally, field-trialling and phenotyping for agriculturally relevant traits across a diverse range of Australian environments suggests that genomic regions under strong breeding selection and their candidate genes are closely associated with key agronomic traits. In conclusion, our combined dataset and germplasm collection provide a rich source of genetic diversity that can be applied to understanding and improving environmental adaptation and enhanced yields. Author summaryTodays gene pool of crop genetic diversity has been shaped during domestication and more recently by breeding. Genetic diversity is vital for crop species to be able to adapt to changing environments. There is concern that recent breeding efforts have eroded the genetic diversity of many domesticated crops including barley. The present study assembled a global panel of barley genotypes with a focus on historical and modern Australian varieties. Genome-wide data was used to detect genes that are thought to have been under selection during crop breeding in Australian barley. The results demonstrate that despite being more extensively bred, modern Australian barley varieties exhibit higher genetic diversity than historical cultivars, countering the common perception that intensive breeding leads to genetic erosion of adaptive diversity in modern cultivars. In addition, some loci (particularly those related to phenology) were subject to selection during the introduction of other barley varieties to Australia - these genes might continue to be important targets in breeding efforts in the face of changing climatic conditions.

genomics↗

bioRxiv2020

Artificial-Cell-Type Aware Cell Type Classification in CITE-seq

Cellular Indexing of Transcriptomes and Epitopes by sequencing (CITE-seq), couples the measurement of surface marker proteins with simultaneous sequencing of mRNA at single cell level, which brings accurate cell surface phenotyping to single cell transcriptomics. Unfortunately, multiplets in CITE-seq datasets create artificial cell types and complicates the automation of cell surface phenotyping. We propose CITE-sort, an artificial-cell-type aware surface marker clustering method for CITE-seq. CITE-sort is aware of and is robust to multiplet-induced artificial cell types. We benchmarked CITE-sort with real and simulated CITE-seq datasets and compared CITE-sort against canonical clustering methods. We show that CITE-sort produces the best clustering performance across the board. CITE-sort not only accurately identifies real biological cell types but also consistently and reliably separates multiplet-induced artificial-cell-type droplet clusters from real biological-cell-type droplet clusters. In addition, CITE-sort organizes its clustering process with a binary tree, which facilitates easy interpretation and verification of its clustering result and simplifies cell type annotation with domain knowledge in CITE-seq.

bioinformatics↗

bioRxiv2020

Hidden state dynamics reveals metastability across the adult lifespan

Adult lifespan is accompanied by functional reorganization of brain networks, but the dynamic patterns behind this reorganization remain largely unclear. This study focuses on modelling the dynamic process of spontaneous activity of large-scale networks using hidden Markov model (HMM), and investigates how it changes with age. The HMM with 12 hidden states was applied to temporally concatenated resting state fMRI data from two dataset of 176 / 170 subjects (aged 20-80 years), and each hidden state was characterized by distinct activation patterns of 17 brain networks. Results showed that (a) For both datasets, the elder tended to spend less time on and had less transitions to states showing antagonistic activity between various pairs of networks including default mode network, cognitive control and salience/ventral attention networks. (b) For both datasets, the elder were probable to spend more time on, have less transitions from and have more transitions to an baseline state with only moderate-level activation of all networks, the time spent on this state also showed an U-shaped lifespan trajectory. (c) For both datasets, HMM exhibited higher specificity and reproducibility in uncovering the age effects compared with temporal clustering method, especially for age effects in transition probability. (d) These results demonstrate the age-correlated decrease of the anti-correlation between various networks, and further validate the prediction of Naik et al. (2017) that the existence of a particular network state with lower transition probability and higher fractional occupancy in old cohort, which may reflect the shift of the dynamical working point across the adult lifespan.

neuroscience↗

bioRxiv2020

A metabolomics study of ascorbic acid-induced in situ freezing tolerance in spinach (Spinacia oleracea L.)

Freeze-thaw stress is one of the major environmental constraints that limit plant growth and reduces productivity and quality. Plants exhibit a variety of cellular dysfunction following freeze-thaw stress, including accumulation of reactive oxygen species (ROS). This means that enhancement of antioxidant capacity by exogenous application of antioxidants could potentially be one of major strategies for improving freezing tolerance (FT) of plants. Exogenous application of ascorbic acid (AsA), as an antioxidant, has been shown to improve plant tolerance against abiotic stresses but its effect on FT has not been investigated. We evaluated the effect of AsA-feeding on FT of spinach (Spinacia oleracea L.) at whole-plant and excised leaf level, and conducted metabolite profiling of leaves before and after AsA-treatment to explore metabolic explanation for change in FT. AsA-application did not impede leaf-growth; instead slightly promoted it. Temperature-controlled freeze-thaw tests revealed AsA-fed plants were more freezing tolerant as indicated by: 1) less visual damage/mortality; 2) lower ion-leakage; and 3) less oxidative-injury, lower abundance of free radicals (O2 *- and H2O2). Comparative leaf metabolic profiling revealed clear separation of metabolic phenotypes for control vs. AsA-fed leaves. Specifically, AsA-fed leaves had greater abundance of antioxidants (AsA, glutathione, alpha-& gamma-tocopherol) and compatible solutes (proline, galactinol, myo-inositol). AsA-fed leaves also had higher activity of antioxidant enzymes (superoxide dismutase, ascorbate peroxidase, catalase). These changes, together, may improve FT via alleviating freeze-induced oxidative stress as well as protecting membranes from freeze-desiccation. Additionally, improved FT by AsA-feeding may potentially include enhanced cell wall/lignin augmentation and bolstered secondary metabolism as indicated by diminished level of phenylalanine and increased abundance of branched amino acids, respectively.

plant biology↗

bioRxiv2020

Regulation of olfactory-based sex behaviors in the silkworm by genes in the sex-determination cascade

Insect courtship and mating depend on integration of olfactory, visual, and tactile cues. Compared to other insects, Bombyx mori, the domesticated silkworm, has relatively simple sexual behaviors as it cannot fly. Here by using CRISPR/Cas and electrophysiological techniques we found that courtship and mating behaviors are regulated in male silk moths by mutating genes in the sex determination cascade belonging to two conserved pathways. Loss of Bmdsx gene expression significantly reduced the peripheral perception of the major pheromone component bombykol by reducing expression of the product of the BmOR1 gene which completely blocked courtship in adult males. Interestingly, we found that mating behavior was regulated independently by another sexual differentiation gene, Bmfru. Loss of Bmfru completely blocked mating, but males displayed normal courtship behavior. Lack of Bmfru expression significantly reduced the perception of the minor pheromone component bombykal due to the down regulation of BmOR3 expression; further, functional analysis revealed that loss of the product of BmOR3 played a key role in terminating male mating behavior. Our results suggest that Bmdsx and Bmfru are at the base of the two primary pathways that regulate olfactory-based sexual behavior. Author SummaryThe fundamental insect sexual behaviors, courtship and mating, result from successful integration of olfactory, vision, tactile and other complex innate behaviors. In the widely used insect model, Drosophila melanogaster, the sex determination cascade genes fruitless and doublesex are involved in the regulation of courtship and mating behaviors; however, little is known about the function of these sexual differentiation genes in regulating sex behaviors of Lepidoptera. Here we combine genetics and electrophysiology to investigate regulation pathway of sexual behaviors in the model lepidopteran insect, the domesticated silk moth, Bombyx mori. Our results support the presence of two genetic pathways in B. mori, named Bmdsx-BmOR1-bombykol and Bmfru-BmOR3-bombykal, which control distinct aspects of male sexual behavior that are modulated by olfaction. This is the first comprehensive report about the role of sex differentiation genes in the male sexual behavior in the silk moth.

genetics↗

bioRxiv2020

Genomic and protein structure modelling analysis depicts the origin and infectivity of 2019-nCoV, a new coronavirus which caused a pneumonia outbreak in Wuhan, China

Detailed genomic and structure-based analysis of a new coronavirus, namely 2019-nCoV, showed that the new virus is a new type of bat coronavirus and is genetically fairly distant from the human SARS coronavirus. Structure analysis of the spike (S) protein of this new virus showed that its S protein only binds weakly to the ACE2 receptor on human cells whereas the human SARS coronavirus exhibits strongly affinity to the ACE receptor. These findings suggest that the new virus does not readily transmit between humans and should theoretically not able to cause very serious human infection. These data are important to guide design of infection control policy and inform the public on the nature of threat imposed by 2019-nCov when results of direct laboratory tests on this virus are not expected to be available in the near future.

microbiology↗

bioRxiv2020

BREM-SC: A Bayesian Random Effects Mixture Model for Joint Clustering Single Cell Multi-omics Data

Droplet-based single cell transcriptome sequencing (scRNA-seq) technology, largely represented by the 10X Genomics Chromium system, is able to measure the gene expression from tens of thousands of single cells simultaneously. More recently, coupled with the cutting-edge Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), the droplet-based system has allowed for immunophenotyping of single cells based on cell surface expression of specific proteins together with simultaneous transcriptome profiling in the same cell. Despite the rapid advances in technologies, novel statistical methods and computational tools for analyzing multi-modal CITE-Seq data are lacking. In this study, we developed BREM-SC, a novel Bayesian Random Effects Mixture model that jointly clusters paired single cell transcriptomic and proteomic data. Through simulation studies and analysis of public and in-house real data sets, we successfully demonstrated the validity and advantages of this method in fully utilizing both types of data to accurately identify cell clusters. In addition, as a probabilistic model-based approach, BREM-SC is able to quantify the clustering uncertainty for each single cell. This new method will greatly facilitate researchers to jointly study transcriptome and surface proteins at the single cell level to make new biological discoveries, particularly in the area of immunology.

genomics↗