Biology subjects

Chen, K.

Publications and source records attributed to Chen, K..

At least 361 records · Page 20Linked to original sources

bioRxiv2021

Spatial drivers and pre-cancer populations collaborate with the microenvironment in untreated and chemo-resistant pancreatic cancer

Pancreatic Ductal Adenocarcinoma (PDAC) is a lethal disease with limited treatment options and poor survival. We studied 73 samples from 21 patients (7 treatment-naive and 14 treated with neoadjuvant regimens), analyzing distinct spatial units and performing bulk proteogenomics, single cell sequencing, and cellular imaging. Spatial drivers, including mutant KRAS, SMAD4, and GNAQ, were associated with differential phosphosignaling and metabolic responses compared to wild type. Single cell subtyping discovered 12 of 21 tumors with mixed basal and classical features. Trefoil factor family members were upregulated in classical populations, while the basal populations showed enhanced expression of mesenchymal genes, including VIM and IGTB1. Acinar-ductal metaplasia (ADM) populations, present in 95% of patients, with 46% reduction of driver mutation fractions compared to tumor populations, exhibited suppressive and oncogenic features linked to morphologic states. We identified coordinated expression of TIGIT in exhausted and regulatory T cells and Nectin receptor expression in tumor cells. Higher expression of angiogenic and stress response genes in dendritic cells compared to tumor cells suggests they have a pro-tumorigenic role in remodeling the microenvironment. Treated samples contain a three-fold enrichment of inflammatory CAFs when compared to untreated samples, while other CAF subtypes remain similar. A subset of tumor and/or ADM-specific biomarkers showed differential expression between treatment groups, and several known drug targets displayed potential cross-cell type reactivities. This resolution that spatially defined single cell omics provides reveals the diversity of tumor and microenvironment populations in PDAC. Such understanding may lead to more optimal treatment regimens for patients with this devastating disease. HIGHLIGHTSO_LIAcinar-ductal metaplasia (ADM) cells represent a genetic and morphologic transition state between acinar and tumor cells. C_LIO_LIInflammatory cancer associated fibroblasts (iCAFs) are a major component of the PDAC TME and are significantly higher in treated samples C_LIO_LIReceptor-ligand analysis reveals tumor cell-TME interactions through NECTIN4-TIGIT C_LIO_LITumor and ADM cell proteogenomics differ between treated and untreated samples, with unique and shared potential drug targets C_LI

cancer biology↗

bioRxiv2021

MYC overexpression leads to increased chromatin interactions at superenhancers and c-Myc binding sites

The MYC oncogene encodes for the c-Myc protein and is frequently dysregulated across multiple cancer cell types, making it an attractive target for cancer therapy. There have been many difficulties in targeting c-Myc, due to its complex network of regulators and the unstructured nature of its protein. Thus, we are interested in looking at the downstream cancer-specific functions of c-Myc. Overexpression of MYC leads to c-Myc binding at active enhancers, resulting in a global transcriptional amplification of active genes. However, the mechanism underlying this c-Myc enhancer invasion has not been well studied. To that end, we performed ChIP-seq, RNA-seq, 4C-seq and SIQHiC (Spike-in Quantitative Hi-C) on the U2OS osteosarcoma cell line with tetracycline-inducible MYC. MYC overexpression in U2OS cells modulated histone acetylation and increased c-Myc binding at superenhancers. SIQHiC analysis revealed increased global chromatin contact frequency, particularly at chromatin interactions connecting c-Myc binding sites. Our results suggest that c-Myc molecules are recruited to and accumulates within zones of high transcription activity, binding first at stable promoter binding sites at low expression levels, then at superenhancer binding sites when overexpressed. At the same time, the recruitment of c-Myc and other transcription factors may stabilize chromatin interactions to increase chromatin contact frequency. The accumulation of c-Myc at cancer-type specific superenhancers may then drive the expression of interacting oncogenes that each cancer is highly reliant on. By elucidating the chromatin landscape of c-Myc driven cancers, we can potentially target these chromatin interactions for cancer therapy, without affecting physiological c-Myc signaling.

genomics↗

bioRxiv2020

Divergent molecular signatures of regeneration and fibrosis during wound repair

Regeneration is the "holy grail" of tissue repair, but skin injury typically yields fibrotic, non-functional scars. Developing pro-regenerative therapies requires rigorous understanding of the molecular progression from injury to fibrosis or regeneration. Here, we report the divergent molecular events driving skin wound cells toward either scarring or regenerative fates. We profile scarring versus YAP inhibition-induced wound regeneration at the transcriptional (single-cell RNA-sequencing), protein (timsTOF proteomics), and tissue (extracellular matrix ultrastructural analysis) levels. Using cell surface barcoding, we integrate these data to reveal fibrotic and regenerative "molecular trajectories" of healing. We show that disrupting YAP mechanical signaling yields regenerative repair orchestrated by fibroblasts with activated Trps1 and Wnt signaling. Our findings serve as a multimodal map of wound regeneration and could have therapeutic implications for pathologic fibroses.

cell biology↗

bioRxiv2020

Unbiased integration of single cell multi-omics data

Acquiring accurate single-cell multiomics profiles often requires performing unbiased in silico integration of data matrices generated by different single-cell technologies from the same biological sample. However, both the rows and the columns can represent different entities in different data matrices, making such integration a computational challenge that has only been solved approximately by existing approaches. Here, we present bindSC, a single-cell data integration tool that realizes simultaneous alignment of the rows and the columns between data matrices without making approximations. Using datasets produced by multiomics technologies as gold standard, we show that bindSC generates accurate multimodal co-embeddings that are substantially more accurate than those generated by existing approaches. Particularly, bindSC effectively integrated single cell RNA sequencing (scRNA-seq) and single cell chromatin accessibility sequencing (scATAC-seq) data towards discovering key regulatory elements in cancer cell-lines and mouse cells. It achieved accurate integration of both common and rare cell types (<0.25% abundance) in a novel mouse retina cell atlas generated using the 10x Genomics Multiome ATAC+RNA kit. Further, it achieves unbiased integration of scRNA-seq and 10x Visium spatial transcriptomics data derived from mouse brain cortex samples. Lastly, it demonstrated efficacy in delineating immune cell types via integrating single-cell RNA and protein data. Thus, bindSC, available at https://github.com/KChen-lab/bindSC, can be applied in a broad variety of context to accelerate discovery of complex cellular and biological identities and associated molecular underpinnings in diseases and developing organisms.

bioinformatics↗

bioRxiv2020

Single-Cell Manifold Preserving Feature Selection (SCMER)

1AO_SCPLOWBSTRACTC_SCPLOWA key challenge in studying organisms and diseases is to detect rare molecular programs and rare cell populations (RCPs) that drive development, differentiation, and transformation. Molecular features such as genes and proteins defining RCPs are often unknown and difficult to detect from unenriched single-cell data, using conventional dimensionality reduction and clustering-based approaches. Here, we propose a novel unsupervised approach, named SCMER, which performs UMAP style dimensionality reduction via selecting a compact set of molecular features with definitive meanings. We applied SCMER in the context of hematopoiesis, lymphogenesis, tumorigenesis, and drug resistance and response. We found that SCMER can identify non-redundant features that sensitively delineate both common cell lineages and rare cellular states ignored by current approaches. SCMER can be widely used for discovering novel molecular features in a high dimensional dataset, designing targeted, cost-effective assays for clinical applications, and facilitating multi-modality integration.

bioinformatics↗

bioRxiv2020

A Novel SARS-CoV-2 Multitope Protein/Peptide Vaccine Candidate is Highly Immunogenic and Prevents Lung Infection in an Adeno Associated Virus Human Angiotensin-Converting Enzyme 2 (AAV hACE2) Mouse Model

A novel multitope protein-peptide vaccine against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and disease is described in this report. The initial development and characterization experiments are presented along with proof-of-concept studies for the vaccine candidate UB-612. UB-612 consists of eight components rationally designed for induction of potently neutralizing antibodies and broad T cell responses against SARS-CoV-2: the S1-RBD-sFc fusion protein, six synthetic peptides (one universal peptide and five SARS-CoV-2-derived peptides), a proprietary CpG TLR-9 agonist at low concentration as an excipient, and aluminum phosphate adjuvant. Through immunogenicity studies in Guinea pigs and rats, we optimized the design of protein/peptide immunogens and selected an adjuvant system, yielding a vaccine that provides excellent S1-RBD binding and high neutralizing antibody responses, robust cellular responses, and a Th1-oriented response at low doses. In challenge studies, UB- 612 vaccination reduced viral load and prevented development of disease in mouse and non-human primate challenge models. With a Phase 1 trial completed, a Phase 2 trial ongoing in Taiwan, and additional trials planned to support global authorizations, UB-612 is a highly promising and differentiated vaccine candidate for prevention of SARS-CoV-2 infection and COVID-19 disease. Author SummarySARS-CoV-2 virus, the causative agent of Coronavirus Disease 2019 (COVID-19), has spread globally since its origin in 2019, causing an unprecedented public health crisis that has resulted in greater than 4.7 million deaths worldwide. Many vaccines are under development to limit disease spread and reduce the number of cases, but additional candidates that promote a robust immune response are needed. Here, we describe a multitope protein-peptide vaccine platform that is unique among COVID-19 vaccines. The advantages of our approach are induction of both high levels of neutralizing antibodies as well as a Th/CTL response in the vaccinated host, which mimics the immune response that occurs after natural infection with SARS-CoV-2. We demonstrate that our vaccine is immunogenic and effective in preventing disease in several animal models, including AAV- hACE-2 transduced mice, and both rhesus and cynomolgus macaques. Importantly, no immunopathology was observed in the lungs of immunized animals, therefore showing that antibody-dependent enhancement (ADE) does not occur. Our study provides an additional, novel vaccine candidate for advancement in clinical trials to treat and prevent SARS-CoV-2 infection and COVID-19 disease.

immunology↗

bioRxiv2020

3D DNA structural barcode copying and random access

Three-dimensional (3D) DNA nanostructures built via DNA self-assembly have established recent applications in multiplexed biosensing and storing digital information. However, a key challenge is that 3D DNA structures are not easily copied which is of vital importance for their large-scale production and for access to desired molecules by target-specific amplification. Here, we build 3D DNA structural barcodes and demonstrate the copying and random access of the barcodes from a library of molecules using a modified polymerase chain reaction (PCR). The 3D barcodes were assembled by annealing a single-stranded DNA scaffold with complementary short oligonucleotides containing 3D protrusions at defined locations. DNA nicks in these structures are ligated to facilitate barcode copying using PCR. To randomly access a target from a library of barcodes, we employ a non-complementary end in the DNA construct that serves as a barcode-specific primer template. Readout of the 3D DNA structural barcodes was performed with nanopore measurements. Our study provides a roadmap for convenient production of large quantities of self-assembled 3D DNA nanostructures. In addition, this strategy offers access to specific targets, a crucial capability for multiplexed single-molecule sensing and for DNA data storage.

biophysics↗

bioRxiv2020

Intracellular localisation of Mycobacterium tuberculosis affects antibiotic efficacy

To be effective, chemotherapy against tuberculosis (TB) must kill the intracellular population of Mycobacterium tuberculosis (Mtb). However, how host cell environments affect antibiotic accumulation and efficacy remains elusive. Pyrazinamide (PZA) is a key antibiotic against TB, yet its behaviour is not fully understood. Here, by using correlative light, electron, and ion microscopy to image PZA at the subcellular level, we investigated how human macrophage environments affect PZA activity. We discovered that PZA accumulates heterogeneously between individual bacteria in multiple host cell environments. Crucially, Mtb phagosomal localisation and acidification increase PZA accumulation and efficacy. By imaging two antibiotics commonly used in combined TB therapy, we showed that bedaquiline (BDQ) significantly enhances PZA accumulation by a host cell mediated mechanism. Thus, intracellular localisation and specific microenvironments affect PZA accumulation and efficacy; explaining the potent in vivo efficacy compared to its modest in vitro activity and the critical contribution to TB combination chemotherapy.

microbiology↗

bioRxiv2020

Improved prediction of femoral fracture toughness in mice by combining standard medical imaging with Raman spectroscopy

Bone fragility and fracture risk are assessed by measuring the areal bone mineral density (aBMD) using dual-energy X-ray absorptiometry (DXA). While aBMD correlates with bone strength, it is a poor predictor of fragility fracture risk. Alternatively, fracture toughness assesses the bones resistance to crack propagation and fracture, making it a suitable bone quality metric. Here, we explored how femoral midshaft measurements from DXA, micro-computed tomography (CT), and Raman spectroscopy could predict fracture toughness. We hypothesized that ovariectomy (OVX) decreases aBMD and fracture toughness compared to controls and we can optimize a multivariate assessment of bone quality by combining results from X-ray and Raman spectroscopy. Female mice underwent an OVX (n=5) or sham (n=5) surgery at 3 months of age. Femurs were excised 3 months after ovariectomy and assessed with Raman spectroscopy, CT, and DXA. Subsequently, a notch was created on the anterior side of the mid-diaphysis of the femurs. Three-point bending induced a controlled fracture that initiated at the notch. The OVX mice had a significantly lower aBMD, cortical thickness, and fracture toughness when compared to controls (p<0.05). A leave one out cross-validated (LOOCV) partial least squares regression (PLSR) model based only on the combination of aBMD and cortical thickness showed no significant predictive correlations with fracture toughness, whereas a PLSR model based on principal components derived from the full Raman spectra yielded significant prediction (r2=0.71, p<0.05). Further, the PLSR model was improved by incorporating aBMD, cortical thickness, and principal components from Raman spectra (r2=0.92, p<0.001). This exploratory study demonstrates combining X-ray with Raman spectroscopy leads to a more accurate assessment of bone fracture toughness and could be a useful diagnostic tool for the assessment of fragility fracture risk.

bioengineering↗

bioRxiv2020

MiR-17-5p regulates proliferation and apoptosis of uterine fibroids via targeting ESR1

The treatment of uterine fibroids and the development of new drugs depend on adeeper understanding of the developmental mechanisms of uterine fibroids. Here, the role of ESR1 and miR-17 on the uterine fibroids cell proliferation and apoptosis and their relationship were investigated in USMCs. Our results showed that ESR1 increased the proliferation of USMCs and inhibited their apoptosis. In addition, ESR1 could directly bind the promoter regionof TP53 and inhibit its expression. MiR-17 increased the apoptosis of USMCs and inhibited their proliferation via decreasing the level of ESR1 by targeting its 3UTR. Our research provides a new understanding of the development of uterine fibroids and provides a theoretical basis for the treatment of uterine fibroids.

molecular biology↗

bioRxiv2020

OmicPioneer-sc: an integrated, interactive visualization environment for single-cell sequencing data

OmicPioneer-sc is an open-source data visualization/analysis package that integrates dimensionality-reduction plots (DRPs) such as t-SNE and UMAP with Next-Generation Clustered Heat Maps (NGCHMs) and Pathway Visualization Modules (PVMs) in a seamless, highly interactive exploratory environment. It includes fluent zooming and navigation, a statistical toolkit, dozens of link-outs to external public bioinformatic resources, high-resolution graphics that meet the requirements of all major journals, and the ability to store all metadata needed to reproduce the visualizations at a later time. A user-friendly, multi-panel graphical interface enables non-informaticians to interact with the system without programming, asking and answering questions that require navigation among the three types of modules or extension from them to the Gene Ontology or information on therapies. The visual integration can be useful for detective work to identify and annotate cell-types for color-coding of the DRPs, and multiple NGCHMs can be layered on top of each other (with toggling among them) as an aid to multi-omic analysis. The tools are available in containerized form with APIs to facilitate incorporation as a plug-in to other bioinformatic environments. The capabilities of OmicPioneer-sc are illustrated here through application to a single-cell RNA-seq airway dataset pertinent to the biology of both cancer and COVID-19. [Supplemental material is available for this article.]

bioinformatics↗

bioRxiv2020

Oleic acid triggers hippocampal neurogenesis by binding to TLX/NR2E1

Adult hippocampal neurogenesis underpins learning, memory, and mood, but diminishes with age and illness. The orphan nuclear receptor TLX/NR2E1 is known to regulate neural stem and progenitor cell self-renewal and proliferation, but the precise mechanism by which it accomplishes this is unknown. We found that neural stem and progenitor cells require monounsaturated fatty acids to survive and proliferate. Specifically, oleic acid (18:1{omega}9) binds to TLX to convert it from a transcriptional repressor to a transcriptional activator of cell cycle and neurogenesis genes. We propose a model in which sufficient quantities of this endogenous ligand must bind to TLX to trigger the switch to proliferation. These findings pave the way for future therapeutic manipulations to counteract pathogenic impairments of neurogenesis.

neuroscience↗

bioRxiv2020

Satellite subgenomic particles are key regulators of adeno-associated virus life cycle

Historically, AAV defective interfering particles (DI) were known as abnormal virions arising from natural replication and encapsidation errors. Through single virion genome analysis, we revealed that a major category of DI particles contains a double stranded DNA genome in a "snapback" configuration (SBG). The 5-SBGs include the P5 promoters and partial rep gene sequences. The 3-SBGs contains the capsid region. The molecular configuration of 5-SBGs allowed double stranded RNA transcription in their dimer configuration, which in turn regulate AAV rep expression and may improve AAV packaging. In contrast, 3-SBGs at its dimer configuration increased levels of cap protein. The generation and accumulation of 5-SBGs and 3-SBGs appears to be coordinated to balance the viral gene expression level. Therefore, the functions of 5-SBGs and 3-SBGs may help maximize the yield of AAV progenies. We postulate that AAV virus population behaved as a colony and utilizes its subgenomic particles to overcome the size limit of viral genome and encodes additional essential functions.

molecular biology↗

bioRxiv2020

Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,125 Individuals from the ADNI and OASIS Databases

Biomarker-assisted preclinical/early detection and intervention in Alzheimers disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (A{beta}) plaques in the human brain. However, current methods to detect A{beta} pathology are either invasive (lumbar puncture) or quite costly and not widely available (amyloid PET). Our prior studies show that MRI-based hippocampal multivariate morphometry statistics (MMS) are an effective neurodegenerative biomarker for preclinical AD. Here we attempt to use MRI-MMS to make inferences regarding brain A{beta} burden at the individual subject level. As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each subject. Then we apply these individual representations and a binary random forest classifier to predict brain A{beta} positivity for each person. We test our method in two independent cohorts, 841 subjects from the Alzheimers Disease Neuroimaging Initiative (ADNI) and 260 subjects from the Open Access Series of Imaging Studies (OASIS). Experimental results suggest that our proposed PASCS-MP method and MMS can discriminate A{beta} positivity in people with mild cognitive impairment (MCI) (Accuracy (ACC)=0.89 (ADNI)) and in cognitively unimpaired (CU) individuals (ACC=0.79 (ADNI) and ACC=0.81 (OASIS)). These results compare favorably relative to measures derived from traditional algorithms, including hippocampal volume and surface area, shape measures based on spherical harmonics (SPHARM), and our prior Patch Analysis-based Surface Sparse-coding and Max-Pooling (PASS-MP) methods.

bioinformatics↗

bioRxiv2020

Batch-Corrected Distance Mitigates Temporal and Spatial Variability for Clustering and Visualization of Single-Cell Gene Expression Data

Clustering and visualization are essential parts of single-cell gene expression data analysis. The Euclidean distance used in most distance-based methods is not optimal. Batch effect, i.e., the variability among samples gathered from different times, tissues, and patients, introduces large between-group distance and obscures the true identities of cells. To solve this problem, we introduce Batch-Corrected Distance (BCD), a metric using temporal/spatial locality of the batch effect to control for such factors. We validate BCD on a simulated data as well as applied it to a mouse retina development dataset and a lung dataset. We also found the utility of our approach in understanding the progression of the Coronavirus Disease 2019 (COVID-19). BCD achieves more accurate clusters and better visualizations than state-of-the-art batch correction methods on longitudinal datasets. BCD can be directly integrated with most clustering and visualization methods to enable more scientific findings.

bioinformatics↗

bioRxiv2020

Generation of glucocorticoid resistant SARS-CoV-2 T-cells for adoptive cell therapy

Adoptive cell therapy with viral-specific T cells has been successfully used to treat life-threatening viral infections, supporting the application of this approach against COVID-19. We expanded SARS-CoV-2 T-cells from the peripheral blood of COVID-19-recovered donors and non-exposed controls using different culture conditions. We observed that the choice of cytokines modulates the expansion, phenotype and hierarchy of antigenic recognition by SARS-CoV-2 T-cells. Culture with IL-2/4/7 but not other cytokine-driven conditions resulted in >1000 fold expansion in SARS-CoV-2 T-cells with a retained phenotype, function and hierarchy of antigenic recognition when compared to baseline (pre-expansion) samples. Expanded CTLs were directed against structural SARS-CoV-2 proteins, including the receptor-binding domain of Spike. SARS-CoV-2 T-cells could not be efficiently expanded from the peripheral blood of non-exposed controls. Since corticosteroids are used for the management of severe COVID-19, we developed an efficient strategy to inactivate the glucocorticoid receptor gene (NR3C1) in SARS-CoV-2 CTLs using CRISPR-Cas9 gene editing.

immunology↗

bioRxiv2020

Mapping Mouse Behavior with an Unsupervised Spatio-temporal Sequence Decomposition Framework

Animal behavior usually has a hierarchical structure and dynamics. Therefore, to understand how the neural system coordinates with behaviors, neuroscientists need a quantitative description of the hierarchical dynamics of different behaviors. However, the recent end-to-end machine-learning-based methods for behavior analysis mostly focus on recognizing behavioral identities on a static timescale or based on limited observations. These approaches usually lose rich dynamic information on cross-scale behaviors. Inspired by the natural structure of animal behaviors, we addressed this challenge by proposing a novel parallel and multi-layered framework to learn the hierarchical dynamics and generate an objective metric to map the behavior into the feature space. In addition, we characterized the animal 3D kinematics with our low-cost and efficient multi-view 3D animal motion-capture system. Finally, we demonstrated that this framework could monitor spontaneous behavior and automatically identify the behavioral phenotypes of the transgenic animal disease model. The extensive experiment results suggest that our framework has a wide range of applications, including animal disease model phenotyping and the relationships modeling between the neural circuits and behavior.

animal behavior and cognition↗

bioRxiv2020

Human Olfactory Perception is Sensitive to Temporal Information within a Single Sniff

A sniff in humans typically lasts 1-2 seconds and is considered to produce a "snapshot" of the chemical environment that also sets the temporal resolution of olfactory perception. To examine whether the temporal order of events within a sniff influences the perceptual "snapshot", we devised an apparatus that enabled us to phase-lock odor delivery to sniff onset and precisely manipulate onset asynchronies of odorants in humans. Psychophysical testing showed that participants were able to tell apart two odorants presented in the same or different order when the onset asynchrony was as low as 40 milliseconds. The performance improved with longer onset asynchronies and was not based on the molar ratio difference of the two odorants. Meanwhile, they were consistently at chance in reporting which odorant arrived first. These results provide behavioral evidence that human olfaction is sensitive to temporal patterns within a single sniff and indicate that timing of odor-evoked responses in relation to the sniff contributes to the perceived odor quality.

neuroscience↗