Biology subjects

Chen, C.-J.

Publications and source records attributed to Chen, C.-J..

12 recordsLinked to original sources

bioRxiv2026

MICRON learns outcome-associated representations of spatial immune microenvironments

Spatial imaging proteomics modalities, such as imaging mass cytometry, enable comprehensive identification of immune microenvironments driving disease outcomes. Identifying outcome-associated immune microenvironments from these data has proven to be complex, as it requires segmenting cells with complex shapes and reconciling spatial signatures across many heterogeneous samples. We present MICRON, a segmentation-free, fully automated multiple-instance learning based tool for automatic identification of outcome-linked immune microenvironments. MICRON learns representations of samples profiled with spatial imaging proteomics modalities, enabling more accurate prognostic and diagnostic prediction over existing approaches. As a case study, we show that MICRON generates a comprehensive importance map that reveals key outcome-associated immune microenvironments in brain cancer, uncovering coordinated cell-cell communication between astrocytes, NK cells, and macrophages linked to survival outcomes. MICRON is provided as open source software for broad use by clinicians and biologists at https://github.com/ChenCookie/micron.

bioinformatics↗

bioRxiv2025

Single-cell multiomic human brain atlas reveals regulatory drivers of cortical regionality

Distinct regional functionality of the human cortex is orchestrated by diverse cellular and molecular processes, yet the underlying regulatory mechanisms remain poorly understood. We performed multiomic single-cell and spatial characterization of nine regions of the human cortex to define the gene regulatory networks and transcription factors that govern cell-type and region specificity. With the combined data of over three million cells, two striking patterns of cortical neuron specialization were uncovered: a rostral-caudal gradient of calcium regulatory machinery, and subunit switching of multiple signaling receptor families across the transmodal-sensory axis. Gene regulatory network analysis revealed putative transcriptional regulators of cortical neuron specialization with cell-type- and region-specific gene regulation patterns. While regionalization was observed in gene expression, chromatin accessibility, and spatial distributions, these modalities exhibited distinct cortical patterns. Our findings illuminate critical neuronal pathways that vary throughout the cortex and the gene regulatory networks that establish cortical regionalization in the human brain.

neuroscience↗

bioRxiv2024

Enolase-1 is essential for neutrophil recruitment during acute inflammation

Enolase-1 (ENO1) is a moonlighting protein with multiple functions. When expressed on the cell surface, ENO1 binds plasminogen (PLG) and promotes cell migration by facilitating plasmin (PLM)-mediated extracellular matrix degradation. Here, we observed that inflammatory stimulation significantly upregulated ENO1 expression on the neutrophil surface, both in vitro and in vivo. An anti-ENO1 monoclonal antibody (mAb), 7E5, which blocks the ENO1-PLG interaction, effectively suppressed neutrophil transmigration. In mouse models of acute inflammation, including lipopolysaccharide (LPS)-induced lung injury and necrotic cell challenge, 7E5 treatment markedly reduced neutrophil recruitment and neutrophil extracellular trap (NET) formation. Moreover, 7E5 neutralized the immunostimulatory activity of soluble ENO1, which was significantly elevated in circulation during acute inflammation. These findings highlight ENO1 as a key regulator of inflammation and neutrophil infiltration. Targeting ENO1 with antibodies could be a promising strategy to mitigate tissue damage caused by excessive neutrophilic inflammation.

immunology↗

bioRxiv2024

Ganoderma formosanum polysaccharides enhance antitumor immune responses by downregulating the differentiation of myeloid-derived suppressor cells and tumor-associated macrophages

Ganoderma formosanum is a native species of Ganoderma isolated in Taiwan, and our previous studies showed that a polysaccharide fraction, PS-F2, purified from the submerged culture fluid of G. formosanum ATCC 76538 exhibited immunostimulatory and antitumor property. In the current study, we investigated the immunomodulatory and antitumor effects of PS-F2 from a UV-mutated G. formosanum variant NTU-1, which produced higher yields of PS-F2 than the original strain. Oral administration of PS-F2 effectively suppressed the growth of colon 26 (CT-26) carcinoma and splenomegaly in tumor-bearing mice without adversely affecting the animals health. We found that PS-F2 treatment resulted in augmented cytotoxic T lymphocyte (CTL) while significantly reducing the accumulation of polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and regulatory T (Treg) cells in the spleen. In the tumor, PS-F2 treatment markedly enhanced CTL and Th1 responses, whereas it reduced the accumulation of tumor-associated macrophages (TAMs). Collectively, our data demonstrate that oral treatment of PS-F2 from G. formosanum NTU-1 in CT26 tumor-bearing mice activates antitumor immune responses and reduces the accumulation of immunosuppressive cells in the spleen and the tumor, leading to delayed tumor progression.

immunology↗

bioRxiv2023

An integrated bioinformatics approach to identify candidate biomarkers and the evaluation of drugs for pheochromocytoma

ObjectivesIdentification of the most potential druggable targets and drugs for treating pheochromocytoma by understanding the molecular mechanisms in the progression of pheochromocytoma and discovering additional biomarkers for early diagnosis. MethodsThe differential gene expression in microarray data was analyzed using CRAN packages such as Geoquery, Affy, Limma, Tidyverse, GOchord, etc., and functional and pathway enrichment was performed through the David database, Further PPI network is constructed by retrieving the Protein partners were retrieved from the STRING database. The top 3 ranked gene products from cytohubba were docked with the ligand molecules, which are all in phase III trials. The complex with the highest binding affinity was simulated using molecular dynamics simulations for 100ns, PCA and FEL analysis were performed to determine the stability of the complex at each time interval additionally miRNA and TRFs were predicted for the prominent genes. ResultsAs a result of functional enrichment, most of the 97 differentially expressed genes (DEGs) are involved in cancer-causing pathways. Pheochromocytomas were associated with CDC42, VEGFA, PIK3R1, ITGAV, and LAMB-1, among prominent genes among the ten hub genes. Simulated results verified the effectiveness of targeting VEGFA with Lenvatinib. ConclusionsWe found that differentially expressed genes in the interactome and hub genes with high correlations could serve as biomarkers, along with their miRNAs and TRFs. By targeting VEGFA as a drug target, Lenvatinib displays a high affinity for VEGFA, as it interacts with other genes through homodimerization, activation, phosphorylation, and dephosphorylation. It also appears to interact with the VEGFA protein via hydrogen bonds. In conclusion, this study suggests that Lenvatinib might be a promising anticancer agent that could treat pheochromocytoma, and VEGF-A, CDC42, PIK3R1, as well as several predicted miRNAs, such as miR-224 and miR-221, might be biomarkers for the early diagnosis.

bioinformatics↗

bioRxiv2022

A Graph Coarsening Algorithm for Compressing Representations of Single-Cell Data with Clinical or Experimental Attributes

Graph-based algorithms have become essential in the analysis of single-cell data for numerous tasks, such as automated cell-phenotyping and identifying cellular correlates of experimental perturbations or disease states. In large multi-patient, multi-sample single-cell datasets, the analysis of cell-cell similarity graphs representations of these data becomes computationally prohibitive. Here, we introduce cytocoarsening, a novel graph-coarsening algorithm that significantly reduces the size of single-cell graph representations, which can then used as input to downstream bioinformatics algorithms for improved computational efficiency. Uniquely, cytocoarsening considers both phenotypical similarity of cells and similarity of cells associated clinical or experimental attributes in order to more readily identify condition-specific cell populations. The resulting coarse graph representations were evaluated based on both their structural correctness and the capacity of downstream algorithms to uncover the same biological conclusions as if the full graph had been used. Cytocoarsening is provided as open source code at https://github.com/ChenCookie/cytocoarsening.

bioinformatics↗

bioRxiv2021

Three-dimensional organization of chromatin associated RNAs and their role in chromatin architecture in human cells

The interphase genome is dynamically organized in the nucleus and decorated with chromatin-associated RNA (caRNA). It remains unclear whether the genome architecture modulates the spatial distribution of caRNA and vice versa. Here, we generate a resource of genome-wide RNA-DNA and DNA-DNA contact maps in human cells. These maps reveal the chromosomal domains demarcated by locally transcribed RNA, hereafter termed RNA-defined chromosomal domains. Further, the spreading of caRNA is constrained by the boundaries of topologically associating domains (TADs), demonstrating the role of the 3D genome structure in modulating the spatial distribution of RNA. Conversely, stopping transcription or acute depletion of RNA induces thousands of chromatin loops genome-wide. Activation or suppression of the transcription of specific genes suppresses or creates chromatin loops straddling these genes. Deletion of a specific caRNA-producing genomic sequence promotes chromatin loops that straddle the interchromosomal target sequences of this caRNA. These data suggest a feedback loop where the 3D genome modulates the spatial distribution of RNA, which in turn affects the dynamic 3D genome organization.

genomics↗

bioRxiv2020

Characterization of the dimeric interactions of dimeric and tetrameric conformations of the PvNV protrusion-domain using a mixed DFT/QTAIM approach

The protrusion-domain (P-domain) of Penaeus vannamei nodavirus (PvNV) exists as two dimer-dimer conformations: one is a protein dimer and the other is a protein tetramer. We undertook a theoretical study to gain a clear understanding of the nature of the stabilizing interactions at the dimeric interfaces of the dimeric and tetrameric conformations of the PvNV P-domain (PvNVPd) using the quantum theory of atoms in molecules (QTAIM) and natural-bond orbital (NBO) analyses in the framework of the density-functional theory (DFT) approach. The QTAIM analysis characterized the presence of multiple hydrogen bonds of common types with strength ranging from electrostatic to the covalent limit inside the PvNVPd dimer-dimer interfaces. Val257-Lys335, Phe294-Val330, Gln296-Thr328, Glu296-Thr329, Thr328-Gln297, Val330-Ala293, Lys335-Asp256 and Lys335-Val257 pairs are critical residue pairs of all three dimeric interfaces of PvNVPd. They preserve these dimeric interfaces through charge-charge, charge-dipole, dipole-dipole, hydrophobic and hydrogen bond interactions. The strongest intermolecular dimer-dimer interactions belong to the dimeric interface between subunits A and B of PvNVPd in the tetrameric conformation.

biochemistry↗

bioRxiv2019

Kinetics of Xist-induced gene silencing can be predicted from combinations of epigenetic and genomic features

To initiate X-chromosome inactivation (XCI), the long non-coding RNA Xist mediates chromosome-wide gene silencing of one X chromosome in female mammals to equalize gene dosage between the sexes. The efficiency of gene silencing, however is highly variable across genes, with some genes even escaping XCI in somatic cells. A genes susceptibility to Xist-mediated silencing appears to be determined by a complex interplay of epigenetic and genomic features; however, the underlying rules remain poorly understood. We have quantified chromosome-wide gene silencing kinetics at the level of the nascent transcriptome using allele-specific Precision nuclear Run-On sequencing (PRO-seq). We have developed a Random Forest machine learning model that can predict the measured silencing dynamics based on a large set of epigenetic and genomic features and tested its predictive power experimentally. While the genomic distance to the Xist locus is the prime determinant of the speed of gene silencing, we find that also pre-marking of gene promoters with polycomb complexes is associated with fast silencing. Moreover, a series of features associated with active transcription and the O-GlcNAc transferase Ogt are enriched at rapidly silenced genes. Our machine learning approach can thus uncover the complex combinatorial rules underlying gene silencing during X inactivation.

genomics↗

bioRxiv2018

Nifedipine Modulated Renal Lipogenesis via AMPK-SREBP Transcriptional Pathways

Lipid accumulation in renal cells has been implicated in the pathogenesis of obesity-related kidney disease, and lipotoxicity occurring in the kidney can be a surrogate marker for renal failure or renal fibrosis. Nifedipine-induced renal lipotoxicity has never been cited, although a few studies have shown that nifedipine inhibits lipogenesis via activation of the LKB1-AMPK pathway. Therefore, we utilized NRK52E cell models to examine this further. We pre-treated cells with varying concentrations of nifedipine (7.5, 15, or 30 M) for 24 or 48 h prior to examining the activity of lipogenesis enzymes and lipotoxicity.\n\nNifedipine was found to activate acetyl CoA synthetase, acetyl CoA carboxylase, long chain fatty acyl CoA elongase, ATP-citrate lyase, and HMG CoA reductase, suggesting elevated production of cholesterol, triacylglycerides, and phospholipids. Nifedipine exposure induced a vast accumulation of cytosolic free fatty acids (FFA) and stimulated the production of reactive oxygen species, upregulated CD36 and KIM-1 (kidney injury molecule-1) expression, inhibited p-AMPK activity, and triggered the transcription of SREBP-1/2 and lipin-1, underscoring the potential of nifedipine to induce lipotoxicity with renal damage.\n\nIn the present study, we elucidated the mechanism of action of nifedipine that leads to renal lipotoxicity via the AMPK-SREBP-1/2 pathway. To our knowledge, this is the first report demonstrating nifedipine-induced lipid accumulation in the kidney.

biochemistry↗

bioRxiv2017

Differential epigenetic landscapes and transcription factors explain X-linked gene behaviours during X-chromosome reactivation in the mouse inner cell mass

X-chromosome inactivation (XCI) is established in two waves during mouse development. First, silencing of the paternal X chromosome (Xp) is triggered, with transcriptional repression of most genes and enrichment of epigenetic marks such as H3K27me3 being achieved in all cells by the early blastocyst stage. XCI is then reversed in the inner cell mass (ICM), followed by a second wave of maternal or paternal XCI, in the embryo-proper. Although the role of Xist RNA in triggering XCI is now clear, the mechanisms underlying Xp reactivation in the inner cell mass have remained enigmatic. Here we use in vivo single cell approaches (allele-specific RNAseq, nascent RNA FISH and immunofluorescence) and find that different genes show very different timing of reactivation. We observe that the genes reactivate at different stages and that initial enrichment in H3K27me3 anti-correlates with the speed of reactivation. To define whether this repressive histone mark is lost actively or passively, we investigate embryos mutant for the X-encoded H3K27me3 demethylase, UTX. Xp genes that normally reactivate slowly are retarded in their reactivation in Utx mutants, while those that reactive rapidly are unaffected. Therefore, efficient reprogramming of some X-linked genes in the inner cell mass is very rapid, indicating minimal epigenetic memory and potentially driven by transcription factors, whereas others may require active erasure of chromatin marks such as H3K27me3.

developmental biology↗

bioRxiv2017

Mupirocin-associated temporal changes in the nasal microbiota and host’s antimicrobial responses: A pilot study in healthy staphylococcal carriers

BackgroundHow mupirocin affects the human nasal microbiota over time remains uncharacterized.\n\nMethodsWe repeatedly sampled the anterior nares of four healthy staphylococcal carriers before and after mupirocin use. By sequencing bacterial 16S ribosomal cDNA, we characterized sequential changes in the carriage status, the nasal microbiota, and the hosts antimicrobial peptide expression up to 90 days after decolonization.\n\nResultsBefore mupirocin use, the nasal microbiota differed by the initial, culture-based staphylococcal carriage status, with Firmicutes (54.1%) being the most predominant in carriers and Proteobacteria (75.8%) in the only noncarrier. The nasal microbiota became less diverse (Shannon diversity: 1.33, 95% confidence interval [CI]: 1.06-1.54) immediately after decolonisation than that before decolonisation (1.78, 95%CI: 0.58-1.93). Based on results of differential abundance analysis, Firmicutes were significantly enriched (log2 fold changes [≥] 4, Benjamini-Hochberg adjusted P < .01) while Actinobacteria, particularly Corynbebacterium, were relatively depleted in samples from staphylococcal carriers. Results of nonmetric multidimensional scaling (NMDS) and constrained correspondence analysis (CCA) also suggested that the initial staphylococcal carriage status, human neutrophil peptide 1 levels, and sampling times were major contributors to the between-community dissimilarities (P for marginal permutation test: .014) though the significance attenuated when within-group correlation was considered (P for blocked permutation test: .047).\n\nConclusionThese findings suggest that large-scale investigations on antibiotic effects on the human nasal microbiota are warranted.

microbiology↗