Biology subjects

Chen, K.

Publications and source records attributed to Chen, K..

At least 271 records · Page 15Linked to original sources

bioRxiv2022

Oxytocin enhances the triangular association among behavioral performance, resting state, and task-state functional connectivity

The role of oxytocin (OT) in social behavior and social brain networks has been widely documented. However, the effect of OT on the association between social behavior and brain functional connectivity (FC) is yet to be comprehensively explored. In this study, using a face-perception task and multiple connectome-based predictive (CPM) models, we aimed to: 1) determine whether OT could enhance the association between task behavioral performance, resting-state functional connectivity (rsFC), and task-state functional connectivity (tsFC), and 2) if so, determine the role of OT in enhancing this triangular association. We found that both rsFC and tsFC could independently and significantly predict task performance in the OT group, but not in the placebo (PL) group. In addition, the correlation coefficient between rsFC and tsFC was substantially higher in the OT group than in the PL group. The strength of these associations could be partly explained by OT altering the brains FCs related to social cognition and face-perception in both resting and task states, mainly in brain regions such as the limbic system, prefrontal cortex (PFC), temporal poles (TP), and temporoparietal junction (TPJ). Together, these results suggest that neuropeptides can increase the consistency of individual differences in different modalities (e.g., behavioral and brain level data).

neuroscience↗

bioRxiv2022

novoRNABreak: local assembly for novel splice junction and fusion transcript detection from RNA-seq data

We present novoRNABreak, a unified framework for cancer specific novel splice junction and fusion transcript detection in RNA-seq data obtained from human cancer samples. novoRNABreak is based on a local assembly model, which offers a tradeoff between the alignment-based and de novo whole transcriptome assembly (WTA) approaches, namely, being more sensitive in assembling novel junctions that cannot be directly aligned, and more efficient due to the strategy that focuses on junctions rather than full-length transcripts. The performance of novoRNABreak is demonstrated by a comprehensive set of experiments using synthetic data generated based on genome reference, as well as real RNA-seq data from breast cancer and prostate cancer samples. The results show that novoRNABreak can detect novel splice junctions and fusion transcripts efficiently with high sensitivity and reasonable specificity.

bioinformatics↗

bioRxiv2022

A high-throughput COPD bronchosphere model for disease-relevant phenotypic compound screening

COPD is the third leading cause of death worldwide, but current therapies for COPD are only effective at treating the symptoms of the disease rather than targeting the underlying pathways that are driving the pathogenic changes. The lack of targeted therapies for COPD is in part due to a lack of knowledge about drivers of disease progression and the difficulty in building relevant and high throughput models that can recapitulate the phenotypic and transcriptomic changes associated with pathogenesis of COPD. To identify these drivers, we have developed a cigarette smoke extract (CSE)-treated bronchosphere assay in 384-well plate format that exhibits CSE-induced decreases in size and increase in luminal secretion of MUC5AC. Transcriptomic changes in CSE-treated bronchospheres resemble changes that occur in human smokers both with and without COPD compared to healthy groups, indicating that this model can capture human smoking signature. To identify new targets, we ran a small molecule compound deck screening with diversity in target mechanisms of action and identified hit compounds that attenuated CSE induced changes, either decreasing spheroid size or increasing secreted mucus. This work provides insight into the utility of this bronchosphere model in examining human respiratory diseases, the pathways implicated by CSE, and compounds with known mechanisms of action for therapeutic development.

cell biology↗

bioRxiv2022

Cuticle development and underlying transcriptome-metabolome associations during early seedling establishment

The plant cuticle is a complex extracellular lipid barrier that provides protection from numerous environmental stressors and is critical for normal organ development. In this study, we investigated cuticle deposition by integrating metabolomics and transcriptomics data gathered from six different maize seedling organs of four genotypes, the inbred lines B73 and Mo17, and their reciprocal hybrids. These datasets captured the developmental transition of the seedling from heterotrophic skotomorphogenic growth to autotrophic photomorphogenic growth, which is a transition that is highly vulnerable to environmental stresses. Statistical interrogation of these data reveals that the predominant determinant of cuticle composition is seedling organ type, whereas the seedling genotype has a smaller effect on this phenotype. Gene-to-metabolite associations assessed by joint statistical analyses of transcriptome and metabolome datasets identified three gene networks connected with the deposition of different fractions of the cuticle: a) cuticular waxes; b) cutin of aerial organs and suberin of roots; and c) both of these fractions. These networks consist of genes that encode known components of the machinery that supports cuticle deposition, demonstrating the utility of this integrated omics approach. Moreover, these gene networks reveal three additional metabolic programs that appear to support cuticle deposition, including processes of a) chloroplast biogenesis, b) lipid metabolism, and c) molecular regulation (e.g., transcription factors, post-translational regulators and phytohormones). This study demonstrates the wider physiological metabolic context that can determine cuticle deposition and lays the groundwork for new targets for modulating properties of this protective barrier.

systems biology↗

bioRxiv2022

Monopogen: single nucleotide variant calling from single cell sequencing

Distinguishing how genetics impact cellular processes can improve our understanding of variable risk for diseases. Although single-cell omics have provided molecular characterization of cell types and states on diverse tissue samples, their genetic ancestry and effects on cellular molecular traits are largely understudied. Here, we developed Monopogen, a computational tool enabling researchers to detect single nucleotide variants (SNVs) from a variety of single cell transcriptomic and epigenomic sequencing data. It leverages linkage disequilibrium from external reference panels to identify germline SNVs from sparse sequencing data and uses Monovar to identify novel SNVs at cluster (or cell type) levels. Monopogen can identify 100K~3M germline SNVs from various single cell sequencing platforms (scRNA-seq, snRNA-seq, snATAC-seq etc), with genotyping accuracy higher than 95%, when compared against matched whole genome sequencing data. We applied Monopogen on human retina, normal breast and Asian immune diversity atlases, showing that that derived genotypes enable accurate global and local ancestry inference and identification of admixed samples from ancestrally diverse donors. In addition, we applied Monopogen on ~4M cells from 65 human heart left ventricle single cell samples and identified novel variants associated with cardiomyocyte metabolic levels and epigenomic programs. In summary, Monopogen provides a novel computational framework that brings together population genetics and single cell omics to uncover genetic determinants of cellular quantitative traits.

bioinformatics↗

bioRxiv2022

Detection of IL23p40 via Positron Emission Tomography Visualized Inflammatory Bowel Disease

Background and aimsInflammatory bowel disease (IBD), which includes both Crohns Disease (CD) and ulcerative colitis (UC), is a relapsing inflammatory disease of the gastrointestinal (GI) tract. Long term chronic inflammatory conditions elevate patients risk for colorectal cancer (CRC). Currently, diagnosis requires endoscopy with biopsy. This procedure is invasive and requires bowel preparatory regimen, adding to patient burden. Interleukin 23 (IL23) plays a key role in inflammation especially in the pathogenesis of IBD and is an established therapeutic target. We propose that imaging of IL23 via immunopositron emission tomography (immunoPET) will potentially lead to a new non-invasive diagnostic approach. MethodsThe aim of the present study is to investigate the potential of immunoPET to image inflammation in a chemically induced mouse model of colitis using dextran sodium sulfate (DSS) by targeting IL23 via its p40 subunit with a 89Zr-radiolabeled -IL23p40 antibody. ResultsHigh uptake of the IL23p40 immunoPET agent in mice were displayed in DSS-administered mice, which correlated with increased IL23p40 present in sera. Competitive binding studies confirmed the specificity of the radiotracer for IL23p40 in the GI tract. ConclusionTaken together, these promising results set the stage for developing this radiotracer as an imaging biomarker for IBD diagnosis. Noninvasive imaging of IBD with IL23p40 immunoPET may help physicians in their treatment decisions for IBD management.

molecular biology↗

bioRxiv2022

Spatial Localization Ability of Planarians Identified Through the Light Maze Paradigm

Spatial localization ability is crucial for free-living animals to fit the environment. As shown by previous studies, planarians can be conditioned to discriminate directions. However, due to their simplicity and primitiveness, they had never been considered to have true spatial localization ability to retrieve locations of objects and places in the environment. Here, we introduce a light maze training paradigm to demonstrate that a planarian worm can navigate to a former recognized place from the start point, even if the worm is transferred into a newly produced maze. This finding identifies the spatial localization ability of planarians for the first time, which provides clues for the evolution of spatial learning. Since the planarians have a primitive brain with simple structures, this paradigm can also provide a simplified model for a detailed investigation of spatial learning.

animal behavior and cognition↗

bioRxiv2022

Multi-omics of Circular RNAs and Their Responses to Hormones in Moso Bamboo (Phyllostachys edulis)

Circular RNAs are endogenous non-coding RNAs with covalently closed structures, which have important functions in plants. However, their biogenesis, degradation, and function upon treatment with gibberellins (GA) and auxins (NAA) remain unknown. Here, we systematically identified and characterized expression patterns, evolutionary conservation, genomic features, and internal structures of circRNAs using RNase R-treated libraries from moso bamboo (Phyllostachys edulis) seedlings. Moreover, we investigated the biogenesis of circRNAs dependent on both cis- and trans-regulation. We determined details regarding the function of circRNAs, including their roles in regulating microRNA-related genes and modulating the alternative splicing of their linear counterparts. Importantly, we developed a customized degradome sequencing approach to detect microRNA-mediated cleavage of circRNAs. Finally, we present a comprehensive view of the participation of circRNAs in the regulation of hormone metabolism upon treatment of bamboo seedlings with gibberellins (GA) and auxins (NAA). Collectively, our study uncovers important features of circRNAs including overall characteristics, biogenesis, function, and microRNA-mediated degradation of circRNAs in moso bamboo.

plant biology↗

bioRxiv2022

Spatially Multiplexed Single-molecule Translocations through a Nanopore at Controlled Speeds

Nanopores are one of the most successful label-free single-molecule techniques with several sensing applications such as biological screening, diagnostics, DNA and protein sequencing1-4. In current nanopore technologies, stochastic processes influence both the selection of the translocating molecule, translocation rate and translocation velocity5,6. As a result, single-molecule translocations are difficult to control spatially and temporally. Here we present a novel method where we engineer precise spatial and temporal control into the single-molecule experiment. We use a glass nanopore mounted on a 3D nanopositioner to spatially select molecules, deterministically tethered on a glass surface, for controlled translocations. By controlling the distance between the nanopore and the glass surface, we can actively select the region of interest on the molecule and scan it a controlled number of times and at controlled velocity. Decreasing the velocity and averaging thousands of consecutive readings of the same molecule increases the signal-to-noise ratio (SNR) by two orders of magnitude compared to free translocations. We applied our method to various DNA constructs, achieving down to single nucleotide gap resolution. The spatial multiplexing combined with the sub-nanometer resolution could be used in conjunction with micro-array technologies to enable screening of DNA, improving point of care devices, or enabling high-density, addressable DNA data storage.

biophysics↗

bioRxiv2022

Comprehensive analysis of intercellular communication in thermogenic adipose niche

Brown adipose tissue (BAT) is responsible for regulating body temperature through adaptive thermogenesis. The ability of thermogenic adipocytes to dissipate chemical energy as heat counteracts weight gain and has gained considerable attention as a strategy against obesity. BAT undergoes major remodeling in a cold environment. This remodeling results from changes in the number and function of brown adipocytes, expanding the network of blood vessels and sympathetic nerves, and changes in the makeup and function of immune cells. All these processes are essential for enhanced BAT thermogenesis to maintain euthermia in the cold. Such synergistic adaptation requires extensive crosstalk between the individual cells in tissues to coordinate their responses. To understand the mechanisms of intercellular communication in BAT, we applied the CellChat algorithm to single-cell transcriptomic data of mouse BAT. We constructed an integrative network of ligand-receptor interactome in BAT and identified the major signaling input and output of each cell type. By comparing the ligand-receptor interactions in BAT of mice housed at different environmental temperatures, we found that cold exposure enhances the intercellular interactions among the major cell types in BAT, including adipocytes, adipocyte progenitors, lymphatic and vascular endothelial cells, myelinated Schwann cells (MSC), nonmyelinated Schwann cells (NMSC), and immune cells. Furthermore, we identified the ligands and receptors that are regulated at the transcriptional level by temperature. These interactions are predicted to regulate the remodeling of extracellular matrix (ECM), inflammatory response, angiogenesis, and neurite growth. Together, our integrative analysis of intercellular communications in BAT and their dynamic regulation in response to housing temperatures establishes a holistic understanding of the mechanisms involved in BAT thermogenesis. The resources presented in this study provide a valuable platform for future investigations of BAT development and thermogenesis.

systems biology↗

bioRxiv2022

Improved Genome Editing by an Engineered CRISPR-Cas12a

CRISPR-Cas12a is an RNA-guided, programmable genome editing enzyme found within bacterial adaptive immune pathways. Unlike CRISPR-Cas9, Cas12a uses only a single catalytic site to both cleave target double-stranded DNA (dsDNA) (cis-activity) and indiscriminately degrade single-stranded DNA (ssDNA) (trans-activity). To investigate how the relative potency of cis- versus trans-DNase activity affects Cas12a-mediated genome editing, we first used structure-guided engineering to generate variants of Lachnospiraceae bacterium Cas12a (LbCas12a) that selectively disrupt trans-activity. The resulting engineered mutant with the biggest differential between cis- and trans-DNase activity in vitro showed minimal genome editing activity in human cells, motivating a second set of experiments using directed evolution to generate additional mutants with robust genome editing activity. Notably, these engineered and evolved mutants had enhanced ability to induce homology-directed repair (HDR) editing by 2-18-fold depending on the genomic locus. Finally, we found that a site-specific reversion mutation produced improved Cas12a (iCas12a) variants with superior genome editing efficiency at genomic sites that are difficult to edit using wild-type Cas12a. This strategy of coupled rational engineering and directed evolution establishes a pipeline for creating improved genome editing tools by combining structural insights with randomization and selection. The availability of experimental and predicted structures of other CRISPR-Cas enzymes will enable this strategy to be applied to improve the efficacy of other genome editing proteins.

biochemistry↗

bioRxiv2022

Integrated single-cell functional and molecular profiling of extracellular vesicle secretion in metastatic breast cancer

Extracellular vesicles (EVs) regulate the tumor microenvironment by facilitating transport of biomolecular cargo including RNA, protein, and metabolites. The biological effects of EV-mediated transport have been studied using supra-physiological concentrations of EVs, but the cells that are responsible for EV secretion and the mechanisms that support EV secretion are not well characterized. We developed an integrated method based on arrays of nanowells to identify individual cells with differences in EV secretion and used an automated robot to perform linked single-cell RNA-sequencing on cloned single cells from the metastatic breast cancer cell line, MDAMB231. Gene expression profiles of clonal cells with differences in EV secretion were analyzed, and a four-gene signature of breast cancer EV secretion was identified: HSP90AA1, HSPH1, EIF5, and DIAPH3. We functionally validated this gene signature by testing it across different cell lines with different metastatic potential demonstrating that the signature correlated with levels of EV secretion. Analysis of the TCGA and METABRIC datasets showed that this signature is associated with poor survival, more invasive breast cancer types, and reduced CD8+ T cell infiltration in human tumors. We anticipate that our method for directly identifying the molecular determinants of EV secretion will have broad applications across cell types and diseases.

cancer biology↗

bioRxiv2022

Transformer Enables Reference Free And Unsupervised Analysis of Spatial Transcriptomics

The development of spatial transcriptomics technologies makes it possible to study tissue heterogeneity at the scale of spatial expressed microenvironment. However, most of the previous methods collapse the spatial patterns in the low spatial resolution. Existing reference based deconvolution methods integrate single-cell reference and spatial transcriptomics data to predict the proportion of cell-types, but the availability of suitable single-cell reference is often limited. In this paper, we propose a novel Transformer based model (TransfromerST) to integrate the spatial gene expression measurements and their spatial patterns in the histology image (if available) without single cell reference. TransfromerST enables the learning of the locally realistic and globally consistent constituents at nearly single cell resolution. TransfromerST firstly uses a transformer based variational autoencoder to explore the latent representation of gene expression, which is further embedded with the spatial relationship learned from adaptive graph Transformer model. The super-resolved cross-scale graph network improves the model-fit to enhanced structure-functional interactions. The public and in-house experimental results with multimodal spatial transcriptomics data demonstrate TransfromerST could highlight the tissue structures at nearly single cell resolution and detect the spatial variable genes and meta gene for each spatial domain. In summary, TransfromerST provides an effective and efficient alternative for spatial transcriptomics tissue clustering, super-resolution and gene expression prediction from histology image.

bioinformatics↗

bioRxiv2022

LinguaPhylo: a probabilistic model specification language for reproducible phylogenetic analyses

Phylogenetic models have become increasingly complex, and phylogenetic data sets have expanded in both size and richness. However, current inference tools lack a model specification language that can concisely describe a complete phylogenetic analysis while remaining independent of implementation details. We introduce a new lightweight and concise model specification language, LPhy, which is designed to be both human and machine-readable. A graphical user interface accompanies LPhy, allowing users to build models, simulate data, and create natural language narratives describing the models. These narratives can serve as the foundation for manuscript method sections. Additionally, we present a command-line interface for converting LPhy-specified models into analysis specification files (in XML format) compatible with the BEAST2 software platform. Collectively, these tools aim to enhance the clarity of descriptions and reporting of probabilistic models in phylogenetic studies, ultimately promoting reproducibility of results.

evolutionary biology↗

bioRxiv2022

A comprehensive single-cell breast tumor atlas defines cancer epithelial and immune cell heterogeneity and interactions predicting anti-PD-1 therapy response

We present an integrated single-cell RNA-seq resource of the breast tumor microenvironment consisting of 236,363 cells from 119 biopsy samples across 8 publicly available datasets. In this computational study, we first leverage this novel resource to define cancer epithelial cell heterogeneity based on two clinically relevant markers and identify six new and distinct subsets of natural killer cells. We then illustrate how cancer epithelial cell heterogeneity impacts immune cell interactions. We develop T cell InteractPrint, which considers how cancer epithelial cell heterogeneity shifts the predicted strength of T cell interactions. We use InteractPrint to predict response to immune checkpoint inhibition (ICI) in two clinical trials testing immunotherapy in patients with breast cancer. T cell InteractPrint was predictive in both trials (AUC = 0.81 and 0.84), versus PD-L1 expression (AUC = 0.54 and 0.72). This result provides an alternative predictive biomarker to PD-L1 to select patients who should receive ICI. STATEMENT OF SIGNIFICANCEWe developed a novel integrated single-cell atlas of the breast tumor microenvironment to interrogate breast tumor cell heterogeneity and define how heterogenous cancer epithelial cell and immune cell interactions predict response to anti-PD-1 therapy.

cancer biology↗

bioRxiv2022

Structure of the NuA4 acetyltransferase complex bound to the nucleosome

DNA in eukaryotes wraps around the histone octamer to form nucleosomes1, the fundamental unit of chromatin. The N-termini of histone H4 interact with nearby nucleosomes, and play an important role in the formation of high order chromatin structure and heterochromatin silencing2-4. NuA4 in yeast and its homolog Tip60 complex in mammalian cells are the key enzymes that catalyze H4 acetylation, which in turn regulate chromatin packaging, and function in transcription activation and DNA repair5-10. Here we report the cryo-EM structure of NuA4 from Saccharomyces cerevisiae bound to the nucleosome. NuA4 comprises two major modules: the catalytic histone acetyltransferase (HAT) module and the transcription activator-binding TRA module. The nucleosome is mainly bound by the HAT module, and positioned close to a polybasic surface of the TRA module, which is important for the optimal activity of NuA4. The nucleosomal linker DNA carrying the upstream activation sequence is oriented towards the conserved, transcription-activator-binding surface of the Tra1 subunit, which suggests a potential mechanism of NuA4 to act as a transcription co-activator. The HAT module recognizes the disk face of the nucleosome through the H2A-H2B acidic patch and the nucleosomal DNA, projecting the catalytic pocket of Esa1 to the N-terminal tail of H4, supporting its function in selective acetylation of H4. Together, our findings illustrate how NuA4 is assembled, and provide mechanistic insights into nucleosome recognition and transcription coactivation by a histone acetyltransferase.

biophysics↗

bioRxiv2022

Swapped genetic code blocks viral infections and gene transfer

Removing cellular transfer RNAs (tRNAs), making their cognate codons unreadable, creates a genetic firewall that prevents viral replication and horizontal gene transfer. However, numerous viruses and mobile genetic elements encode parts of the translational apparatus, including tRNAs, potentially rendering a genetic-code-based firewall ineffective. In this paper, we show that such horizontally transferred tRNA genes can enable viral replication in Escherichia coli cells despite the genome-wide lack of three codons and the previously essential cognate tRNAs and release factor 1. By repurposing viral tRNAs, we then develop recoded cells bearing an amino-acid-swapped genetic code that reassigns two of the six serine codons to leucine during translation. This amino-acid-swapped genetic code renders cells completely resistant to viral infections by mistranslating viral proteomes and prevents the escape of synthetic genetic information by engineered reliance on serine codons to produce leucine-requiring proteins. Finally, we also repurpose the third free codon to biocontain this virus-resistant host via dependence on an amino acid not found in nature.

synthetic biology↗

bioRxiv2022

Modifying Pavlovian-To-Instrumental Transfer By Approach Avoidance Training In Healthy Subjects - A Proof of Concept Study

The modulation of instrumental action by conditioned Pavlovian cues is hypothesized to play a role in the emergence and maintenance of maladaptive behavior. The Pavlovian-to-instrumental transfer (PIT) task is designed to examine the magnitude of the influence of cues on behavior and we aim to manipulate the motivational value of Pavlovian cues to reduce their effect on instrumental responding. To this end, we utilized a joystick-based modification of approach and avoidance propensities that has shown success in clinical populations. In 35 healthy subjects, we examined changes in PIT after completion of either avoidance training or sham training. We found no effect of training on approach avoidance propensities but higher response rate towards negative stimuli during PIT after systematic avoidance training compared to sham training. On the other hand, we saw an increased PIT effect after sham training. These results imply that training can alter the strength of the influence of cues on instrumental behavior and suggest training to be beneficial in reducing environmental triggers of maladaptive behavior.

neuroscience↗