Biology subjects

Chen, J. Y.

Publications and source records attributed to Chen, J. Y..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

A PERTURBATION CELL ATLAS OF HUMAN INDUCED PLURIPOTENT STEM CELLS

Towards comprehensively investigating the genotype-phenotype relationships governing the human pluripotent stem cell state, we generated an expressed genome-scale CRISPRi Perturbation Cell Atlas in KOLF2.1J human induced pluripotent stem cells (hiPSCs) mapping transcriptional and fitness phenotypes associated with 11,739 targeted genes. Using the transcriptional phenotypes, we created a minimum distortion embedding map of the pluripotent state, demonstrating rich recapitulation of protein complexes, such as strong co-clustering of MRPL, BAF, SAGA, and Ragulator family members. Additionally, we uncovered transcriptional regulators that are uncoupled from cell fitness, discovering potential novel pluripotency (JOSD1, RNF7) and metabolic factors (ZBTB41). We validated these findings via phenotypic, protein-interaction, and metabolic tracing assays. Finally, we propose a contrastive human-cell engineering framework (CHEF), a machine learning architecture that learns from perturbation cell atlases to predict perturbation recipes that achieve desired transcriptional states. Taken together, our study presents a comprehensive resource for interrogating the regulatory networks governing pluripotency.

bioengineering↗

bioRxiv2024

AI-readiness for Biomedical Data: Bridge2AI Recommendations

Biomedical research is rapidly adopting artificial intelligence (AI). Yet the inherent complexity of biomedical data preparation requires implementing actionable, robust criteria for ethical and explainable AI (XAI) at the "pre-model" stage, encompassing data acquisition, detailed transformations, and ethical governance. Simple conformance to FAIR (Findable, Accessible, Interoperable, Reusable) Principles is insufficient. Here, we define criteria and practices for reliable AI-readiness of biomedical data, developed by the NIH Bridge to Artificial Intelligence (Bridge2AI) Standards Working Group across seven core dimensions of dataset AI-readiness: FAIRness, Provenance, Characterization, Ethics, Pre-model Explainability, Sustainability, and Computability. Conformance to these criteria provides a basis for pre-model scientific rigor and ethical integrity, mitigating downstream risks of bias and error prior to AI modeling. We apply and evaluate these standards across all four Bridge2AI flagship datasets, spanning functional genomics to clinical medicine, and encode them in machine-actionable metadata bound to the datasets. This framework sets a benchmark for preparing ethical, reusable datasets in biomedical AI and provides standardized methods for reliable pre-model data evaluation.

bioinformatics↗

bioRxiv2024

Toden-E: Topology-Based and Density-Based Ensembled Clustering for the Development of Super-PAG in Functional Genomics using PAG Network and LLM

The integrative analysis of gene sets, networks, and pathways is pivotal for deciphering omics data in translational biomedical research. To significantly increase gene coverage and enhance the utility of pathways, annotated gene lists, and gene signatures from diverse sources, we introduced pathways, annotated gene lists, and gene signatures (PAGs) enriched with metadata to represent biological functions. Furthermore, we established PAG-PAG networks by leveraging gene member similarity and gene regulations. However, in practice, high similarity in functional descriptions or gene membership often leads to redundant PAGs, hindering the interpretation from a fuzzy enriched PAG list. In this study, we developed todenE (topology-based and density-based ensemble) clustering, pioneering in integrating topology-based and density-based clustering methods to detect PAG communities leveraging the PAG network and Large Language Models (LLM). In computational genomics annotation, the genes can be grouped/clustered through the gene relationships and gene functions via guilt by association. Similarly, PAGs can be grouped into higher-level clusters, forming concise functional representations called Super-PAGs. TodenE captures PAG-PAG similarity and encapsulates functional information through LLM, in characterizing network-based functional Super-PAGs. In synthetic data, we introduced a metric called the Disparity Index (DI), measuring the connectivity of gene neighbors to gauge clusterability. We compared multiple clustering algorithms to identify the best method for generating performance-driven clusters. In non-simulated data (Gene Ontology), by leveraging transfer learning and LLM, we formed a language-based similarity embedding. TodenE utilizes this embedding together with the topology-based embedding to generate putative Super-PAGs with superior performance in semantic and gene member inclusiveness.

bioinformatics↗

bioRxiv2024

MLPA: A Multi-scale Digital Twin Framework for Personalized Cancer Simulation and Treatment Optimization

This research proposes a new personalized cancer modeling and treatment strategy: the Multi-level Parameterized Automata (MLPA), an innovative digital twin framework. The MLPA framework fully integrates macroscopic electronic health records (EHR) and microscopic genomic data for the first time, employing stochastic cellular automata to model tumor progression and treatment efficacy dynamically. The multi-scale strategy effectively enables MLPA to simulate complex cancer behaviors, including metastasis and pharmacological responses, with remarkable precision. The validation using bioluminescent imaging from mice demonstrates MLPAs exceptional predictive power, achieving a state-of-the-art R{superscript 2} value of 0.93, improvement over previously reported conventional models, and fitting within 95% confidence intervals. The proposed MLPA framework accurately captures tumors characteristic S-shaped growth curve and shows high fidelity in simulating various scenarios, from natural progression to aggressive growth and drug treatment responses. MLPAs ability to simulate drug effects through gene pathway perturbation, with predicted tumor cell counts being within a 2.5% equivalence margin interval, underscores its potential as a powerful method for precision oncology. The proposed MLPA framework not only offers a more reliable platform for exploring personalized treatment strategies, but also potentially transforms patient outcomes by optimizing therapy based on individual human biological profiles. As clinically adopted technology progresses towards precision medicine, MLPA stands at the forefront, offering new possibilities in cancer simulation and treatment optimization. The code and imaging dataset used is available at https://github.com/alphamind-club/MLPA.

cancer biology↗

bioRxiv2024

Detecting Data Embedding Spatial Patterns and Identifying Biomarkers with BioRSP

Low-dimensional embeddings such as UMAP and t-SNE are routinely used to visually interpret high-dimensional omics data, yet claims based on embedding geometry are often qualitative, embedding-sensitive, and weakly calibrated. We present BioRSP (Biological Radar Scanning Plots), a geometry-first framework that quantifies how a user-defined foreground subset is distributed across the embedding footprint of a fixed analysis set. BioRSP converts 2D coordinates to polar form around a robust vantage point, scans the set by angle, and computes a radar profile that summarizes signed radial enrichment of foreground relative to background within sliding angular windows using a distance-based radial discrepancy. The profile is reduced to interpretable summaries including anisotropy magnitude, peak directionality, and coverage, and is accompanied by explicit adequacy rules and subsampling-based stability diagnostics so the method can abstain when the geometry is underpowered. We demonstrate BioRSP in a community-standard human kidney single-nucleus reference by analyzing thick ascending limb (TAL) nuclei using published UMAP coordinates and a standardized within-set top-decile foreground rule. Within TAL, BioRSP distinguishes sharply localized rim-enrichment patterns, broadly supported but structured within-type heterogeneity, and near-isotropic profiles, with anisotropy spanning more than an order of magnitude in the pooled TAL analysis. Donor-aware reruns show that per-donor adequacy is frequently limiting, but that directional profiles are stable when donor-level support is sufficient. BioRSP is provided as open-source software producing standardized plots, summary tables, and run manifests to support reproducible embedding-aligned enrichment analysis.

bioinformatics↗

bioRxiv2024

The effect of circulating neutralizing antibodies on the replication of SARS-CoV-2 variants following post-vaccination infections.

The impact of pre-existing neutralizing antibodies (NAbs) titers on SARS-CoV-2 viral shedding dynamics in post-vaccination infection (PVI) are not well understood. We characterized viral shedding longitudinally in nasal specimens in relation to baseline (pre/peri-infection) serum neutralizing antibody titers in 125 participants infected with distinct SARS-CoV-2 variants. Among 68 participants who had received vaccinations, we quantified the effect of baseline serum NAb titers on maximum viral RNA titers and on the duration of infectivity. Baseline NAb titers were higher and efficiently targeted a broader range of variants in participants who received one or two monovalent ancestral booster vaccinations compared to those with a full primary vaccine series. In participants with Delta variant infections, baseline NAb titers targeting Delta were negatively correlated with maximum viral RNA copies. Per log10 increase in baseline NAb IC50, maximum viral load was reduced -2.43 (95% confidence interval [CI] -3.76, -1.11) log10 N copies and days of infectious viral shedding were reduced -2.79 [95% CI: -4.99, -0.60] days. By contrast, in those with Omicron infections (BA.1, BA.2, BA.4 or BA.5 lineages) baseline NAb responses against Omicron lineages did not predict viral outcomes. Our results provide robust estimates of the effect of baseline NAbs on the magnitude and duration of nasal viral replication after PVI (albeit with an unclear effect on transmission) and show how immune escape variants efficiently evade these modulating effects.

immunology↗

bioRxiv2024

Mondrian Map: Piet Mondrian's Abstraction for Differential Pathway Analysis

In this study, we introduce the Mondrian Map, an innovative visualization tool inspired by Piet Mondrians abstract art, to address the complexities inherent in visualizing biological networks. By converting intricate biological data into a structured and intuitive format, the Mondrian Map enables clear and meaningful representations of biological pathways, facilitating a deeper understanding of molecular dynamics. Each pathway is represented by a square whose size corresponds to fold change, with color indicating the direction of regulation (up or down) and statistical significance. The spatial arrangement of pathways is derived from language model embeddings, preserving neighborhood relationships and enabling the identification of clusters of related pathways. Additionally, colored lines highlight potential crosstalk between pathways, with distinctions between short- and long-range functional interactions. In a case study of glioblastoma multiforme (GBM), the Mondrian Map effectively revealed distinct pathway patterns across patient profiles at different stages of disease progression. These insights demonstrate the tools potential to enhance downstream bioinformatics analysis by providing a more comprehensive and visually accessible overview of pathway interactions, offering new avenues for therapeutic exploration and personalized medicine.

bioinformatics↗

bioRxiv2023

Screening the human druggable genome identifies ABHD17B as an anti-fibrotic target in hepatic stellate cells

Hepatic stellate cells (HSCs) are activated with chronic liver injury and transdifferentiate into myofibroblasts, which produce excessive extracellular matrices that form the fibrotic scar. While the progression of fibrosis is understood to be the cause of end-stage liver disease, there are no approved therapies directed at interfering with the activity of HSC myofibroblasts. We performed a high-throughput small interfering RNA (siRNA) screen in primary human HSC myofibroblasts to identify gene products necessary for the fibrotic phenotype of HSCs. We found that depletion of ABHD17B promotes the inactivation of HSCs, characterized by reduced COL1A1 and ACTA2 expression and accumulation of lipid droplets. Mice deficient for Abhd17b are also protected from fibrosis in the setting of in vivo liver injury. While ABHD17B is a depalmitoylase, our data suggest that ABHD17B promotes fibrosis through pathways independent of depalmitoylation that include interaction with MYO1B to modulate gene expression and HSC migration. Together, our results provide an analysis of the phenotypic consequences for siRNAs targeting RNAs from >9,500 genes in primary human HSCs and identify ABHD17B as a potential therapeutic target to inhibit liver fibrosis.

cell biology↗

bioRxiv2023

Conserved long noncoding RNA TILAM promotes liver fibrosis through interaction with PML in hepatic stellate cells

Background & AimsFibrosis is the common endpoint for all forms of chronic liver injury, and progression of fibrosis leads to the development of end-stage liver disease. Activation of hepatic stellate cells (HSCs) and their transdifferentiation to myofibroblasts results in the accumulation of extracellular matrix (ECM) proteins that form the fibrotic scar. Long noncoding (lnc) RNAs regulate the activity of HSCs and may provide targets for fibrotic therapies. MethodsWe identified lncRNA TILAM as expressed near COL1A1 in human HSCs and performed loss-of-function studies in human HSCs and liver organoids. Transcriptomic analyses of HSCs isolated from mice defined the murine ortholog of TILAM. We then generated Tilam-deficient GFP reporter mice and quantified fibrotic responses to carbon tetrachloride (CCl4) and choline-deficient L-amino acid defined high fat diet (CDA-HFD). Co-precipitation studies, mass spectrometry, and gene expression analyses identified protein partners of TILAM. ResultsTILAM is conserved between human and mouse HSCs and regulates expression of ECM proteins, including collagen. Tilam is selectively induced in HSCs during the development of fibrosis in vivo. In both male and female mice, loss of Tilam results in reduced fibrosis in the setting of CCl4 and CDA-HFD injury models. TILAM interacts with promyelocytic leukemia protein (PML) to stabilize PML protein levels and promote the fibrotic activity of HSCs. ConclusionTILAM is activated in HSCs and interacts with PML to drive the development of liver fibrosis. Depletion of TILAM may serve as a therapeutic approach to combat the development of end stage liver disease.

cell biology↗

bioRxiv2023

Prioritizing Complex Disease Genes from Heterogeneous Public Databases

BackgroundComplex human diseases are defined not only by sophisticated patterns of genetic variants/mutations upstream but also by many interplaying genes, RNAs, and proteins downstream. Analyzing multiple genomic and functional genomic data types to determine a short list of genes or molecules of interest is a common task called "gene prioritization" in biology. There are many statistical, biological, and bioinformatic methods developed to perform gene prioritization tasks. However, little research has been conducted to examine the relationships among the technique used, merged/separate use of each data modality, the gene lists network/pathway context, and various gene ranking/expansions. MethodsWe introduce a new analytical framework called "Gene Ranking and Iterative Prioritization based on Pathways" (GRIPP) to prioritize genes derived from different modalities. Multiple data sources, such as CBioPortal, PAGER, and COSMIC were used to compile the initial gene list. We used the PAGER software to expand the gene list based on biological pathways and the BEERE software to construct protein-protein interaction networks that include the gene list to rank order genes. We produced a final gene list for each data modality iteratively from an initial draft gene list, using glioblastoma multiform (GBM) as a case study. ConclusionWe demonstrated that GBM gene lists obtained from three modalities (differential gene expressions, gene mutations, and copy number alterations) and several data sources could be iteratively expanded and ranked using GRIPP. While integrating various modalities of data can be useful to generate an integrated ranked gene list related to any specific disease, the integration may also decrease the overall significance of ranked genes derived from specific data modalities. Therefore, we recommend carefully sorting and integrating gene lists according to each modality, such as gene mutations, epigenetic controls, or differential expressions, to procure modality-specific biological insights into the prioritized genes.

bioinformatics↗

bioRxiv2023

A remarkable transformation catalyzed by a domain-of-unknown-function 692 during the biosynthesis of a new RiPP natural product

The domain of unknown function 692 (DUF692) is an emerging family of posttranslational modification enzymes involved in the biosynthesis of ribosomally-synthesized and posttranslationally modified peptide (RiPP) natural products. Members of this family are multinuclear iron-containing enzymes and only two members have been functionally characterized to date: MbnB and TglH. Here, we used bioinformatics to select another member of the DUF692 family, ChrH, that is ubiquitously encoded in the genomes of the Chryseobacterium genus along with a partner protein ChrI. We structurally characterized the ChrH reaction product and show that the enzyme catalyzes an unprecedented chemical transformation that results in the formation of a macrocycle, an imidazolidinedione heterocycle, two thioaminals, and a thiomethylation. Based on isotopic labeling studies, we propose a mechanism for the four-electron oxidation and methylation of the substrate peptide. This work identifies the first SAM-dependent DUF692 enzyme, further expanding the repertoire of remarkable reactions catalyzed by these enzymes.

biochemistry↗

bioRxiv2023

Novel genetically encoded tools for imaging or silencing neuropeptide release from presynaptic terminals in vivo

Neurons produce and release neuropeptides to communicate with one another. Despite their profound impact on critical brain functions, circuit-based mechanisms of peptidergic transmission are poorly understood, primarily due to the lack of tools for monitoring and manipulating neuropeptide release in vivo. Here, we report the development of two genetically encoded tools for investigating peptidergic transmission in behaving mice: a genetically encoded large dense core vesicle (LDCV) sensor that detects the neuropeptides release presynaptically, and a genetically encoded silencer that specifically degrades neuropeptides inside the LDCV. Monitoring and silencing peptidergic and glutamatergic transmissions from presynaptic terminals using our newly developed tools and existing genetic tools, respectively, reveal that neuropeptides, not glutamate, are the primary transmitter in encoding unconditioned stimulus during Pavlovian threat learning. These results show that our sensor and silencer for peptidergic transmission are reliable tools to investigate neuropeptidergic systems in awake behaving animals.

neuroscience↗

bioRxiv2022

Molecular and Anatomical Characterization of Parabrachial Neurons and Their Axonal Projections

The parabrachial nucleus (PBN) is a major hub that receives sensory information from both internal and external environments. Specific populations of PBN neurons are involved in behaviors including food and water intake, pain sensation, breathing regulation, as well as learning and responding appropriately to threatening stimuli. However, it is unclear how many PBN neuron populations exist and how different behaviors may be encoded by unique signaling molecules or receptors. Here we provide a repository of data on the molecular identity, spatial location, and projection patterns on dozens of PBN neuron subclusters. Using single-cell RNA sequencing, we identified 21 subclusters of neurons in the PBN and neighboring regions. Multiplexed in situ hybridization showed many of these subclusters are localized to distinct PBN subregions. We also describe two major ascending pathways that innervate distinct brain regions by analyzing axonal projections in 21 Cre-driver lines of mice. These results are all publicly available for download and provide a foundation for further interrogation of PBN functions and connections.

neuroscience↗

bioRxiv2022

Targeting Acid Ceramidase Ameliorates Fibrosis in Mouse Models of Nonalcoholic Steatohepatitis

1)Nonalcoholic fatty liver disease (NAFLD) is a common cause of liver disease worldwide, and is characterized by the accumulation of fat in the liver. Nonalcoholic steatohepatitis (NASH), an advanced form of NAFLD, is a leading cause of liver transplantation. Fibrosis is the histologic feature most associated with liver-related morbidity and mortality in patients with NASH, and treatment options remain limited. In previous studies, we discovered that acid ceramidase (aCDase) is a potent antifibrotic target using human hepatic stellate cells (HSCs) and models of hepatic fibrogenesis. Using two dietary mouse models, we demonstrate that depletion of aCDase in HSC reduces fibrosis without worsening metabolic features of NASH, including steatosis, inflammation, and insulin resistance. Consistently, pharmacologic inhibition of aCDase ameliorates fibrosis but does not alter metabolic parameters. The findings suggest that targeting aCDase is a viable therapeutic option to reduce fibrosis in patients with NASH.

systems biology↗

bioRxiv2021

Nanchangmycin regulates FYN, FAK and ERK to control the fibrotic activity of hepatic stellate cells

Chronic liver injury causes fibrosis, characterized by the formation of scar tissue resulting from excessive accumulation of extracellular matrix (ECM) proteins. Hepatic stellate cell (HSC) myofibroblasts are the primary cell type responsible for liver fibrosis, yet there are currently no therapies directed at inhibiting the activity of HSC myofibroblasts. To search for potential anti-fibrotic drugs, we performed a high-throughput compound screen in primary human HSC myofibroblasts and identified 19 small molecules that induce HSC inactivation, including the polyether ionophore nanchangmycin (NCMC). NCMC induces lipid re-accumulation while reducing collagen expression, deposition of collagen in the extracellular matrix, cell proliferation, and migration. We find that NCMC increases cytosolic Ca2+ and reduces the phosphorylated protein levels of FYN, FAK, ERK1/2, HSP27 and STAT5B. Further, depletion of each of these kinases suppress COL1A1 expression. These studies reveal a signaling network triggered by NCMC to inactivate HSC myofibroblasts and reduce expression of proteins that compose the fibrotic scar. The identification of the antifibrotic effects of NCMC and the pathways by which NCMC inhibits fibrosis provides new tools and therapeutic targets to combat the development and progression of liver fibrosis.

cell biology↗

bioRxiv2021

A Non-redundant Role for T cell-derived IL-22 in Antibacterial Defense of Colonic Crypts

IL-22 is a key cytokine in immune defense against pathogens at barrier sites. In response to enteric attaching and effacing bacteria, IL-22 produced by type 3 innate lymphoid cells (ILC3s) is thought to be important early for induction of antimicrobial peptides (AMPs) that protect intestinal epithelial cells (IECs) in advance of T cell-derived IL-22 that arises later. Yet, the basis for a requirement for both innate and adaptive IL-22-producing immune cells in protecting the intestinal mucosa is unknown. Here, using novel mice that both report IL-22 expression and can be targeted for its lineage-specific deletion, we show that mice with deficiency of IL-22 targeted to innate immune cells, including ILC3s, have impaired STAT3 activation of surface colonic IECs colonized by bacteria early in infection. In contrast, mice with IL-22 deficiency limited to T cells have complete loss of STAT3 activation in IECs lining colonic crypts and fail to protect the crypts from bacterial invasion late despite ongoing production of IL-22 from ILC3s. T cell-derived IL-22 is required for upregulation of many host-protective genes by crypt IECs, including those encoding AMPs, neutrophil-recruiting chemokines, and mucins and mucin-related molecules, while also restricting pro-inflammatory genes downstream of IFN{gamma} and TNF signals. Thus, T cell-derived IL-22 is indispensable for antibacterial defense and damage control of intestinal crypts.

immunology↗

bioRxiv2020

Microglia Stimulate Zebrafish Brain Repair Via a Specific Inflammatory Cascade

The adult zebrafish brain, unlike mammals, has a remarkable regenerative capacity. Although inflammation inhibits regeneration in mammals, it is necessary for zebrafish brain repair. Microglia are resident brain immune cells that regulate the inflammatory response. To explore the microglial role in repair, we used liposomal clodronate, colony stimulating factor-1 receptor (csf1r) inhibition to ablate microglia and two genetic mutants that lacks microglia during brain injury. We found that microglial ablation inhibited injury-induced neurogenesis and regeneration. Microglial suppression specifically attenuated cell proliferation at the progenitor cell amplification stage of neurogenesis. Notably, the loss of microglia impaired phospho-stat3 (signal transducer and activator of transcription 3) and {beta}-catenin signaling by dynamic regulation of tumor necrosis factor-a after injury, and the ectopic activation of stat3 and {beta}-catenin rescued neurogenesis defects caused by microglial loss. Microglial absence leads to neutrophil accumulation, hindering the resolution of inflammation and macrophages are not sufficient for regeneration. These findings reveal specific roles of microglia and inflammatory signaling during zebrafish telencephalic regeneration that should provide strategies to improve mammalian brain repair.

neuroscience↗

bioRxiv2020

Lentiviral interleukin-10 gene therapy preserves fine motor circuitry and function after a cervical spinal cord injury in male and female mice

In mammals, spinal cord injuries often result in muscle paralysis through the apoptosis of lower motor neurons and denervation of neuromuscular junctions. Previous research shows that the inflammatory response to a spinal cord injury can cause additional tissue damage after the initial trauma. To modulate this inflammatory response, we delivered lentiviral anti-inflammatory interleukin-10, via loading onto an implantable biomaterial scaffold, into a left-sided hemisection at the C5 vertebra in mice. We hypothesized that improved behavioral outcomes associated with anti-inflammatory treatment are due to the sparing of fine motor circuit components. We examined behavioral recovery using a ladder beam, lower motor neuron apoptosis and muscle innervation using histology, and electromyogram recordings using intraspinal optogenetic stimulation at 2 weeks post-injury. Ladder beam analysis shows interleukin-10 treatment results in significant improvement of behavioral recovery at 2 and 12 weeks post-injury when compared to mice treated with a control virus. Histology shows interleukin-10 results in greater numbers of lower motor neurons and muscle innervation at 2 weeks post-injury. Furthermore, electromyogram recordings suggest that interleukin-10-treated animals have signal-to-noise ratios and peak-to-peak amplitudes more similar to that of uninjured controls than to that of control injured animals at 2 weeks post-injury. These data show that gene therapy using anti-inflammatory interleukin-10 can significantly reduce lower motor neuron loss, muscle denervation, and subsequent motor deficits after a spinal cord injury. Together, these results suggest that early modulation of the injury response can preserve muscle function with long-lasting benefits.

neuroscience↗